International Journal of Software Computing and Testing
International Journal of Software Computing and Testing (IJSCT) eISSN: 2456-2351 Click here for complete Editorial Board Scientific Journal Impact Factor (SJIF): 5.984 International Journal of Software Computing and Testing (IJSCT) is a journal focused towards the rapid publication of fundamental research papers on all areas of software computing and testing. It's a biannual journal, started in 2015. Journal DOI No: 10.37628/IJSCT Readership: Graduates, Postgraduates, Research Scholars, in Institutions, and IT Companies Indexing: The Journal is indexed in Google Scholar, Index Copernicus (ICV: 56.92) Focus and Scope Evolutionary computing Fuzzy computing Hybrid methods Immunological computing Morphic computing Neuro computing Particle swarm Probabilistic computing Software development tools Submission of Paper: All contributions to the journal are rigorously refereed and are selected on the basis of quality and originality of the work. The journal publishes the most significant new research papers or any other original contribution in the form of reviews and reports on new concepts in all areas pertaining to its scope and research being done in the world, thus ensuring its scientific priority and significance. Manuscripts are invited from academicians, students, research scholars and faculties for publication consideration. Papers are accepted for editorial consideration through email info@journalspub.com or nikita@stmjournals.com Abbreviation: IJSCT Frequency: Two issues per year Editorial Board Instructions to Authors
Unlocking the Potential: Machine Learning Driven Explainable AI Applications Across Diverse Domains
Explainable artificial intelligence (XAI) aims to make discoveries and output generated by machine learning algorithms accessible to human users in a trustworthy and easy-to-understand manner. It describes the impact of an AI model and any potential biases, helping in characterizing models with accuracy, fairness, transparency, and outcomes in decision-making powered by AI. XAI focuses on understanding the data used to train the model, its predictions, the specific elements involved in producing those predictions, and the role of the algorithms used. There are several primary categories of approaches to explain AI systems, such as self-interpretable models and post-hoc justifications. The four pillars of explainable artificial intelligence are explicitness, meaningfulness, explanatory accuracy, and knowledge boundaries. AI has been widely used in the medical field, with applications ranging from clinical decision support to cancer localization in MRI scans to report reading and analysis in radiology and pathology. However, AI has also been applied in other areas of the medical industry, with concerns about its perceived "black box" nature, which can lower trust in its accuracy. This has led to the popularity of explainable artificial intelligence (XAI) in the healthcare industry. This study provides an introductory overview of various methods for explaining and understanding predictions generated by complex machine learning models like deep neural networks. It explores various methodologies, including LIME, anchors, Graph LIME, LRP, DTD, PDA, TCAV, XGNN, SHAP, ASV, break-down, Shapley Flow, textual explanations of visual models, causal models, integrated gradients, meaningful perturbations, and X-NeSyL.
Copyright (c) 2024 International Journal of Software Computing and Testing
A Secured Distributed Database System Using Rijndael Encryption Algorithm
There is a pressing need to secure distributed database system in order to address effectively some challenges, such as, no encryption of users’ access details in the database, which could be hacked by skilled hands, and also the security of the data is highly and threateningly compromised when using data encryption standard (DES) algorithm. This is because it has weak or semi-weak keys, inability of DES algorithm to eliminate the possibility of equivalent keys due to linearity of the key expansion and it requires high computational machines when encrypting large data and the data encryption is applied only on textual data. This paper aims to develop a secure distributed database system using the Rijndael encryption algorithm, also known as the advanced encryption standard (AES). The primary and secondary sources of research methodologies in gathering data or information were employed and rapid application development (RAD) was adopted as system development methodology. The proposed system employed an approach that uses secured hash algorithm (SHA-3) for encrypting login details of users, Rijndael algorithm to encrypt and re-encrypt text and image data, in order to improve the security strength and make it difficult for unauthorized personnel to have access to data stored in the database. Based on the results of the proposed system, the system has the capability of capturing the user’s details for registration and encrypting the user’s password with SHA-3 algorithm. The user can send encrypted text and/or image data with less amount of time and can also receive encrypted data, decrypt it without any changes in quality of the data. Conclusively, with this system, it is impossible for intruders to gain access to the application or compromise the security of the text or image data and users can share (send and receive) sensitive data/information in a secured manner without any interception.
Copyright (c) 2023 International Journal of Software Computing and Testing
Support Vector Machine-based Flower Image Classification for Commercial Applications
Flowers are crucial raw materials in many industries, including pharmaceuticals and cosmetics. Classifying flowers manually is time-consuming, inconsistent, and requires professional judgment from a botanist. Computer-aided flower classification is a promising approach to this problem. Image classification often employs support vector machines (SVMs) as widely favored algorithms. This study evaluated the performance of SVMs for flower image classification. The results showed that SVMs can achieve good accuracy on this task, with an accuracy of 85.2%. This suggests that SVMs could be used to develop computer-aided flower classification systems. Such systems could be used to automate the flower classification process in a variety of industries such as pharmaceutical and cosmetics companies can use SVMs to classify flowers based on their chemical composition, color, texture, and shape. The data can subsequently serve as a foundation for the creation of novel pharmaceuticals, therapies, and beauty products.
A Study on Supervised Machine Learning-based Airports/Flight Delay Analysis and Classification
Airline delays are a major cause of the financial losses that plague the global aviation business. Airports, airlines, and passengers all suffer when flights are delayed. Their forecast is vital to the commercial aviation industry's decision-making process. Flight presents a significant obstacle for the aviation sector. Increased air traffic and subsequent flight delays are a direct result of the aviation industry's rapid growth over the past two decades. The economic and ecological costs of flight delays are significant. Flight delays can lead to significant financial setbacks for commercial airlines. That is why they take all the precautions they can think of to ensure that flights are not cancelled or delayed. From a data science point of view, this study gives a comprehensive literature analysis of methods for constructing flight delay prediction models. In this article, we take a look at a taxonomy of efforts made to solve the issue of flight delay prediction and characterize them in terms of their scope, data, and computational approaches, paying special emphasis to the growing prevalence of machine learning methods. In addition, the complexity of the air transportation system, the plethora of forecast methodologies, and the flood of flight data made it difficult to construct effective prediction models for flight delays. Predicting flight delays using machine learning techniques is the topic of this article. The focus of this study is on determining whether or not various machine learning techniques can accurately predict flight delays and isolate the most important contributors to such disruptions. Airline schedules, airport wait times, weather forecasts, and other characteristics are all included in the dataset used for the research. The study opens with a summary of prior research on the topic of utilizing machine learning to anticipate aircraft delays. Overall, the results of this study suggest that machine learning approaches may enhance the precision and utility of flight delay forecasts, leading to a safer and more efficient aviation infrastructure.
A Study of Application of No Regret Learning Algorithm for Development of a Career Counselling Software
This paper explores the application of “no regret learning algorithms” in the development of a career counselling software, aimed at providing individuals with personalized and data-driven career guidance. By harnessing the power of machine learning methods, this groundbreaking approach provides a flexible and responsive system designed to aid users in making well-informed choices regarding their career trajectories. The software incorporates user profiling, reward modelling, continuous feedback mechanisms, and ethical considerations to ensure relevant and unbiased career recommendations. This technology, by minimizing the feeling of missed opportunities and continually improving career choices, holds great promise in the realm of career counselling. It has the potential to enhance the decision-making process, ultimately leading to greater long-term career satisfaction and success for individuals.
A Comprehensive Analysis of Context-aware Recommender Systems Implemented Across a Range of Domains
In many different fields, recommender systems are essential for helping users find pertinent and personalized material. Traditional recommender systems often underestimate the impact of contextual factors on user preferences. Context-aware recommender systems are a potential method that uses dynamic contextual data to increase recommendation accuracy and user satisfaction. This review paper examines the benefits of context-aware recommender systems in many fields and offers a detailed analysis of these systems. We also discuss the difficulties and outstanding research issues related to context-aware recommender systems. These difficulties include problems with scalability, context representation, data sparsity, and privacy issues. The knowledge presented in this review aims to stimulate more developments and improvements in the field, producing more efficient and individualized recommendation systems in various domains.
Detection of Phishing Sites Using Machine Learning
The content of phishing websites and online-based material provides a variety of indicators. One of the criminal attacks that are successful in the online world is phishing sites that direct users to a phishing website that looks and acts like a legitimate website in order to steal the victim's personal and sensitive information. The Extreme Learning Machine-based version that was suggested was excellent at spotting phishing websites. Internet page types vary greatly in terms of their characteristics. So, in order to protect against any phishing attack, we must use a set of web page features. To defend against these threats, a machine learning strategy is used. The phishing dataset that is planned to be imported, authentic URLs from the database, and also the data that is collected are all pre-processed. Four groups of URL characteristics are used to detect phishing websites: domain, address, anomalous based, HTML, and JavaScript features. Data that has been analysed is used to extract URL characteristics and produce URL attribute values. ML approaches are used to analyse URLs and determine the threshold value and range value for URL properties. This project's goal is to develop an ELM categorization for a number of database characteristics and a few phishing sites.
Fake News and Hate Speech Detection Using Deep Learning
Due to the potential for such content to hurt both people and society as a whole, the issue of identifying fake news and hate speech on internet platforms has grown in importance in recent years. This problem has shown great potential for resolution through deep learning, a specific area of machine learning. In this research work, we examine recent studies on the application of deep learning methods for the identification of fake news and hate speech. We begin by outlining the difficulties in identifying such information, such as the difficulty in defining fake news and hate speech, the sheer volume of online text, and the requirement to take context and other contextual elements into account. The use of deep learning for detection is then covered in detail. In order to enhance the performance of models, we also investigate the use of transfer learning and data augmentation strategies. An active study field in NLP and machine learning is the detection of fake news and hate speech using deep learning algorithms. The detection of fake news and hate speech has showed promise when using deep learning algorithms like CNNs, RNNs, and transformers. Using methods like sentiment analysis, topic modeling, and text classification, one can identify false news by examining the news article's wording, citations, and tone. Lack of big, annotated datasets is a barrier in detecting fake news and hate speech, particularly in languages other than English. For the development of precise deep learning models, high-quality annotated datasets are crucial.
Analysis of Road Lane Detection Using Computer Vision
Today’s technological advancement brings an opportunity to automate all the essential processes. Driving is one of the challenging tasks. The rapid growth of image processing technologies allows us to achieve an automatic driving system without human intervention. Numerous researchers are working on the development of algorithms for the automation of road lane detection during the self-driving car. This study presents an algorithm which can detect road lanes and the upcoming direction along with curvature using OpenCV. In addition to that, object detection is also performed using cascade classifier. This contribution can be a stage in development for autonomous driving systems. Furthermore, several image processing operations are performed, such as camera calibration, perspective transformation, image thresholding, edge detection for lane, etc. The proposed algorithm has been tested with several video images and found to be satisfactorily good in detecting the road lanes, directions, and objects near the vehicle.
Health Management System Using Researched Application of Big Data
As everyone knows many developing as well as developed countries even poor countries healthcare demand is growing at an extensive rate. As like all other countries, healthcare in India is also facing the growing demand of medical treatment and services; as demand of healthcare and medical treatments increases, parallelly the volume of medical records increases; they must appropriately have all of the patient’s medical history. Management has to maintain proper records because this document serves a number of purposes. A hospital management system (HMS) based on modern technology like a kind of web or software based system that facilitates managing as well as accessing the functioning of an hospital or any medical set up making it user-friendly simple, fast, and cost-effective. This system or software integrates all the information of the hospital or of that medical setup regarding patients’ information and its past medical records, doctors’ information, hospital or that medical set-up’s staff information, hospital administrative details, etc. into one software or system. The basic functionality of the system or software is to register patient details and store them in the provided data base and access those details as and when required. It is planned and designed in a way so that to update the traditional way of finding, storing, managing and accessing hospital information (files) into a much faster way of electronic medical records to solve the problem associated with the manual method. As like any other system or software, Hospital Management System (HMS) can be accessible either by the receptionist or by the administrator. The information in this system is well protected for personal use-only, making rapid data processing.
Breakout Room Escape: Design and Development of an Immersive Unity Game
Three-dimensional (3D) game development is a complex and challenging process that requires expertise in various fields, including programming, art, and design. Due to its adaptability, userfriendly interface, and thorough documentation, Unity is a well-known game engine that is frequently used in the game development industry. This research paper aims to explore the process of developing a 3D game using Unity, focusing on the technical aspects of game development and the importance of user experience. In this paper, we delve deeper into the technical aspects of 3D game development using Unity, starting with the importance of game physics. Game physics is a crucial element in game development, as it provides realistic movement and collision detection in the game environment. Developers can simulate a variety of physical properties, such as gravity, friction, and collision detection, using Unity's powerful physics engine. Another critical aspect of game development is artificial intelligence (AI), which involves creating intelligent agents that can interact with the game environment and make decisions based on their behaviour. Unity provides various tools and plugins to create AI agents, including behaviour trees, decision-making systems, and pathfinding algorithms. Additionally, we discuss the importance of game testing and debugging in 3D game development. Testing involves verifying that the game mechanics, level design, and user interface are functioning correctly, while debugging involves identifying and fixing errors in the game's code. Unity provides a variety of testing and debugging tools to help developers identify and fix errors quickly, ensuring a smooth gameplay experience for players. Furthermore, we address the process of game optimization, which involves improving the game's performance to ensure smooth and consistent frame rates.
Agile Hybrid Education System: Adaptable, Innovative, and Effective
The proposed hybrid learning management system (LMS) aims to provide an automated system for the manual processes by utilizing computerized equipment and software, which can effectively store and manage valuable data for an extended period of time, with easy accessibility and manipulation. This system can ensure error-free, secure, reliable, and fast management, allowing users to focus on other activities instead of record-keeping. As a result, businesses are able to maintain redundant-free computerized records while maximizing their resource usage. This makes it possible for users to access pertinent information without being diverted by unrelated information. We will use internet of things fingerprint scanner for getting the students’ live attendance in classroom. Students’ attendance record would be stored in attendance section in dashboard where the time and date of the scanning would be provided and filtered by date and time whose access would be given to teachers’ account.
Progresses in Network Safety Worldview: A Survey
This survey paper examines the different cautious models and mechanisms utilized so far in network safety. Digital protection is an exceptionally delicate issue, where advances are coordinated step by step. To effectively manage sophisticated attackers, it is necessary to cultivate strengths in the form of a cautious approach to the rapidly evolving landscape of malware and other attack methods. Specifically, digitization and data framework started a fight for strength on the internet. This paper plans to feature different challenges in network safety, ongoing integrated innovations alongside the new advances in digital protection worldview.
Detection of Hate Speech on Social Media Using Machine Learning
As we know, social media platforms are the fastest method of communication because information is transmitted and received virtually instantaneously. Social media platforms' development radically altered how people communicate in our world, and one effect of these changes is a rise in inappropriate behaviors, like the use of derogatory language online. It might be challenging to express harsh or disrespectful ideas to someone right in the face. People believe it is safe to abuse or post inappropriate content online. Hate speech can be detrimental to an individual or a community. The prevalence of hate speech on social media is widely acknowledged to be a serious issue. Techniques for detecting hate speech have received major investment from numerous governments and organizations, and they have also caught the interest of the scientific community. Since each proposed method has its own benefits and drawbacks, it is still challenging to evaluate how well it performs despite the abundance of literature on the subject. Filtering or blocking such content on the Web depends on its detection. Massive amounts of text data require manual processing and classification, which takes time and effort. To recognize this kind of content, however, automatic approaches are crucial because of the enormous quantity of data that is posted day by day. we used machine learning techniques like natural language processing, logistic regression, and random forest.
System Infringement Challenges in Smart Cities
We can increase the urban service use, improve sustainability and minimize environmental harm so that the idea of green infrastructure aims to improve the living standard of the citizens. Cybersecurity is the key issue facing smart cities. To store, process and transmit data we can use data protection, as well as the software infrastructure, all topics covered by cybersecurity. Internet of things (IoT) and internet of everything (IoE) are used by smart cities to power their services and apps. The aim is to find a viable solution. The remaining portions of this document are structured as follows: The workings and elements of the smart city once it is put into place will be covered in detail in the second section. The final segment will discuss deep learning-based cybersecurity issues in smart cities. The application of this pattern in smart city-based cybersecurity is illustrated. We then review the literature on threats to user privacy and cybersecurity concerns in smart cities. Technically speaking, a smart city is an area where governance organizations, public organizations, and private organization work together to develop long-term computerized platforms that impose the use of contemporary technologies such as electronic devices, networks, and methods for intelligent decision-making, as well as mobile cloud computing. The biggest issues facing the world today, such as climate change, resource scarcity, urbanization, and rapid population expansion, are primarily addressed by smart cities.
Satellite Image Classification using Deep Learning
Satellite imagery is essential for lots of applications along with catastrophe response, regulation enforcement, and monitoring an environment. These packages require the guide identity of objects and facilities in imagery. Because the geographical areas to be protected are large and the analysts needed to do the searches are scarce, automation is required. Yet traditional item detection and category algorithms are too inaccurate and unreliable to clear up the problem. Deep gaining knowledge refers to a group of machine mastering algorithms that have shown promise in automating such tasks. Using convolutional neural networks, it has achieved total success in photograph knowledge. In this study, we use them to solve the problem of object and facility repute in high resolution multispectral satellite data. The device is made up of a collection of convolutional neural networks and supplementary neural networks that link satellite metadata with image capabilities. It is written in Python and runs on a Linux server with an NVIDIA Titan X GPU, using the Keras and TensorFlow deep learning libraries.
Copyright (c) 2022 International Journal of Software Computing and Testing
Depression, Stress and Anxiety Prediction
In the fast-moving up-to-date realm, intellectual well-being issues like anxiety, depression and stress have enhanced very coarse between common people. The system has entrenched information to label the sentences and make a decision itself as reaction to answer a question. The table contains chatterbot or chatbot information. It exists of four buttons as offset Time, Date, Questionnaires and Image Processing. Image preparing is used to monitor the exciting rank of one working ahead, calculating is critical for the security of one. In this work, actual-occasion non-obtrusive videos are apprehended, that detect the poignant rank of one by analysing the first verbalization. We discover an individual’s excitement in each television frame and the conclusion on the verbalization of the character is created. We engage a method that admits us to train a model and resolve differences in anticipating the lineaments. Machine intelligence algorithms were used to generate predictions of worry, facial, and stress. In order to administer algorithms, answers were calm from things across various breeding and societies through the Depression, Anxiety and Stress Scale questionnaire.
Development of IoT Devices Using Arduino
IoT or Internet of Things has become a burning sensation in today’s world. In the present times each device that we use has the capability to connect to multiple devices and this opens a host of opportunities for both the developers as well as the end consumers to develop and manufacture a variety of devices which can make our day-to-day operations much easier. In the present study, an overview of IoT is given in general, along with its literature review. This is followed by a discussion on Arduino which is employed to develop the devices using IoT. Also, a brief overview is given about various sensors which act as building blocks of any IoT system. Furthermore, an effort is made to demonstrate IoT implementation using Arduino, which may be used in a variety of useful devices. In the present case, IoT is used to develop a motion sensor alarm and a temperature-controlled selfregulating system. The general drawback of IoT is instead discussed. Overall, the study is meant to provide guidance to anyone who is looking to explore the possibilities of IoT using Arduino.
Trends and Techniques of Software Cost and Performance Measurement
Software measurement is an evolving aspect of software engineering providing the necessary support to plan, execute, control, and improve the software development process. However, Software metrics constitute a set of acceptable variables of measurement encompassing diverse activities that require some level of quantification of which cost, and effort estimation are inclusive. This study was aimed at reviewing the various trends and techniques in software cost and performance measurement. The study provided an overview on existing trends and techniques of software cost and performance measurement. The method adopted in the study is the meta-synthesis systematic literature review which is a non-statistical oriented technique used to analyze, integrate and interpret the outcome of numerous qualitative research studies. For investigation, the techniques’ strengths and flaws were identified and contrasted. Algorithmic and non-algorithmic cost estimation approaches were discovered in the study. The algorithmic technique explores the COCOMO, Putnam and the Function Point Analysis models while the non-algorithmic technique explores the Neural Networks, Particle Swarm Optimization, Genetic Programming, Fuzzy Logic, Expert Judgment, Estimating by Analogy, Top-Down Method, and the Bottom-up Estimating Methods. The comparative results show that there is no single best method as their pros and cons are complementary to one another. A combination of two or more models, on the other hand, is expected to produce better results.
Identification of Plant Leaf Diseases Using CNN
The proposed approach helps detect leaf withering and provides a treatment. Databases retrieved from the internet are strictly isolated; unique leaf seeds are recognized and renamed to create an acceptable database. Next, you will receive a test database consisting of a series of leaf rots that will be used to verify the accuracy and reliability stages of your project. Already used. Then use the coaching statistics to train the classifier and expect the output with the most effective accuracy. In addition, a prototype drone model has been developed that can be used to capture leaf snapshots that cover the living area of large farmlands with large digital cameras and serve as input to software based entirely on it. I am. The software program will tell you if the leaves are healthy. Our software provides a level of leaf seed recognition and its level of self-confidence, as well as a remedy that can be seen as a remedy. The challenge also used the Android platform for the user interface, connecting two unique structures.
Mechanized Physiotherapy Device for Accident Victims
Assistive robots are in high demand because they allow people to work freely. Physiotherapy is a outstanding recovery session given to mostly all accidental victims during recovery span. Although, due to the experimental nature of examination, assessment, and treatment, the lack of scientific measures, current methodologies, and modernization, as well as the empirical nature of examination, assessment, and treatment, this endeavour is hampered. This paper proposes an idea of using an exoskeleton-based system for the physical therapy of the hand (primarily). Our system endeavour to enhances the existing therapy methods by introducing accurate and repeatable linger motion, continuous measurement, interactivity, Great exercise assortment and statistical storage and evaluation. The robotic arm is controlled using robotic kinematics concepts. The graphical user interface (GUI) is used to operate the actuators that control the robotic arm's joints. Because the robotic devices may assist in moving the patient's limbs during exercises, this system helps therapists save time by increasing the number of therapy sessions per patient and the number of patients undergoing therapy.
Search of Higher Speed 5G Wireless Technology
5G stands for 5th generation technology which changed the thinking of mobile with inbuilt Hbank which users have never experienced ever before. It is such a high value technology. The major goal of 5G is to close the technology gap and provide contemporary or sophisticated technology because the transition from 1G to 5G is too long in comparison to technological advancement. There are so many challenges to develop it. However, its development will provide extremely efficient management of wireless and network resources, 5G networks will be very flexible and allow online learning and autonomous decision-making capabilities in a centralized and distributed way. Every good thing has bad things, just like every advantage has some disadvantage. Developed networks harm the birds and humans. It also helps to increase global warming. I hope that these things do not occur, and that the government follows the guideline, which is advantageous to everyone.
Artificial Intelligence in Medical Field: Future Comes True
In the current situation of medical field A.I. is very important as it has almost changed all the areas in the medical field due to which the study and research on various types of diseases is going very smoothly and with perfection. Through intensive research and development, A.I. had already begun to solve difficult challenges in the medical industry. Nowadays, artificial intelligence (A.I.) is utilised to maintain medical records in digital format and conduct patient examinations using digital technologies. In practically every area, artificial intelligence has the potential to change health. It has the ability to solve the complexity in the medicines, surgery and other medical areas. This review paper will deal with the application and limitations of A.I in medical field.
Anomaly Detection Network for Surveillance Video
Anomaly Activity is the prediction of a suspicious activity from a picture or video. This project would include using neural networks to detect suspicious human activity from real-time CCTV video. Human Anomaly Activity is a central issue in computer vision that has been researched for over 15 years. It is significant due to the large number of applications that can benefit from Activity detection. Human pose estimation, for example, is used in applications such as video monitoring, animal tracking and behavior recognition, sign language identification, advanced human-computer interaction, and marker less motion recording. Low-cost depth sensors have disadvantages such as being restricted to indoor use, and their low resolution and noisy depth information make estimating human poses from depth images difficult. As a result, we want to use neural networks to solve these issues. The detection of suspicious human activity in surveillance video is a hot topic in image processing and computer vision science. Human activities in areas such as bus station, highways, and school so on can be monitored using visual surveillance to detect terrorism, robbery, accidents and illegal parking, vandalism, fighting, chain snatching, violence, and other suspicious activities. It is extremely difficult to continuously track public places; thus, intelligent surveillance footage is needed that is capable of real-time monitoring of human activities, classify them as normal or unusual, and generate an alarm. Photographs, rather than recordings, are used for the majority of the analysis. Furthermore, none of the papers reported attempt to use CNNs to detect suspicious activity.
For Analyzing Fraud in Credit Cards, Fuzzy Particle Swarm Optimization (FPSO) with Enhanced Support Vector Machine (ESVM) Classifier
Credit cards are extremely significant in today’s economy. However, as the number of Credit Card clients grew, so did the number of Credit Card fraud instances. To fight the upward thrust in credit score card fraud, a number of techniques were recommended. In previous study, a unique fraud detection system was presented that uses similar cardholders’ behavioural patterns to construct a recent behavioural profile of a cardholder in order to avoid credit card fraud. The selection of appropriate features from samples and the decision cost for accuracy, on the other hand, become the most pressing issues. To shed light on these challenges, the proposed research project proposes a five-phased fraud detection technique. To improve a cardholder’s behavioural styles, first use the cardholder’s past transaction data to classify all cardholders into distinct groups, with members in the same group having similar transaction habits. To aggregate the transactions in each group, the window-sliding approach is provided. In addition, it provides a novel feature selection based on Fuzzy Particle Swarm Optimization (FPSO) for improving credit card fraud detection. An ensemble category is achieved through an Enhanced Kernel primarily based totally Support Vector Machine after deciding on the great and handiest functions the usage of a prolonged wrapper method (EKSVM). The external quality measures Accuracy, Recall, FFDR, and CDDR are used in this proposed work. The dataset utilized is from the University of California, Irvine. The analytical metrics used to assess the effectiveness of the fraud detection approach in question. The simulation results suggest that this proposed fraud detection method outperforms other fraud detection techniques in terms of accuracy.
This paper presents the advancement of home machines dependent on voice order utilizing Android. This framework has been intended to help and offer the help to old and incapacitated individuals at home. Google application has been utilized as voice acknowledgment and cycle the voice contribution from the PDA. In this paper, the voice input has been caught by the android and will be shipped off the Arduino Uno. Bluetooth module in Arduino Uno got the sign and handled the information sign to control the light and fan. The proposed framework expected to control electrical apparatuses with moderately easy to use interface and simplicity of establishment. We have exhibited up to 20 meter of reach to control the home machines through Bluetooth.
Copyright (c) 2021 International Journal of Software Computing and Testing
e-Canteen Ordering System: Food Delivery Software
The Canteen Ordering system is a web based software which is essential because of the recent developments in technology and increasing use of internet. Through our proposed Real-time online food ordering system, food can be ordered in a hassle-free manner. This canteen system enables the end users to register online, read and select their preferred food and order them online through this given website. Canteen employees can then use these orders through an easy to navigate graphical interface for efficient processing. It overcomes the disadvantages of the traditional queueing system by implementing proper online log in structure. The canteen ordering system functions as both ordering software for customers and management system for the organization.
A Review of Modeling and Data Mining Techniques Applied for Analyzing Steel Bridges
The vibration response data measured from the structure contains uncertainties and requires different techniques for its analysis. The present study involves the comprehensive review of the model based and data mining techniques which are frequently applied by various researchers in past to solve various multi criteria decision making and analysis problems. The selection of suitable technique for specific problem is required to obtain accurate outcomes. The literature survey is done to provide summary of articles with used data type, involved uncertainty type, and technique used. The uncertainty in the input data can be due to ambiguity, randomness, and partial information. The paper includes brief about Stochastic, Statistical and Computer based modeling techniques and Artificial Neural Networks (ANN), Fuzzy logic, Support vector machine (SVM), Bayesian classifiers (BC), and Cluster algorithms based data mining techniques. The advantages and disadvantages of each technique are also mentioned.
Because of the pandemic everyone need loan to grow their business so lot of people apply for the bank loan but bank has its limited assets which it has to grant to limited people only, so finding out the person who return the loan in a given time is a difficult job. So Here our machine learning model come in to picture the main motive of our model is try to reduce the risk factor behind selecting the safer person this model save lots of bank effort as well as save lots of bank assets. The machine learning model use information of the past records of individuals to whom the credit was conceded previously and based on these records the machine learning model is trained. The main motive of this model is to predict weather the person is approved for the loan or not.
Face Recognization System: A Survey Report
The fundamental capacity of this progression is to extricate the highlights of the face pictures recognized in the identification step. This progression addresses a face with a bunch of highlights vector called a “signature” that depicts the notice able highlights of the face picture like mouth, nose, and eyes with their calculation circulation. Each face is portrayed by its construction, size, and shape, which permit it to be distinguished. A few procedures includes separating the state of the mouth, eyes, or nose to distinguish the face utilizing the size and distance. Eigen face, free segment examination (ICA), direct discriminating instigation (LDA), scale in variant component change (Filter), Gabor channel, nearby stage quantization (LPQ), Fourier changes, and neighborhood paired example (LBP) methods are broadly used to remove the sensors, are utilized to acquire information. These sensors may give additional data and help the face acknowledgment framework store cognize face pictures in both static picture sand video groupings. Also, three classes of sensors that may improve the unwavering quality and the precision of a face acknowledgment framework by handling the difficulties in corporate light variety, head posture, and look in unadulterated picture/video preparing. The primary gather nonvisual sensors, like sound, profundity, and EEG sensors, which give additional data notwithstanding the visual measurement and improve the acknowledgment dependability, for instance, in bright ending variety and positions hit circumstance.
A Roadmap for Cloud Computing for Higher Education
ABSTRACT Advancement of technology provides new opportunities for improving teaching and learning. The new technology provides opportunity individual to personalize the environment where they work. Here in this paper we try to explore the educational potential of cloud computing to exploit its affordability in teaching in context of higher education. Cloud computing has important place for higher education both as powerful platform and computing tool. Though cloud computing provide number of benefits to educational institute but a successful adoption of cloud computing requires understanding of different dynamics and expertise in different domains. This paper provide roadmap for cloud computing for higher education which provides with various steps for adoption of cloud computing. Keywords: Roadmap Cloud computing, Migration
A Descriptive Blockchain Technology Government Application Analysis
ABSTRACT Blockchain is a flux technology regarding government knowledge resource sharing that enhances its legitimacy and security. During this exposition, we tend to gift a technical organization that includes of managing and accessing knowledge at government level and its use cases that embody digital identity, Hyperledger Indy, Tax Payments and Land register Records. By this, we tend to build a blockchain-based information sharing platform that's secure and a lot of reliable than a traditional system with lower implementation value. Blockchain innovation will prompt advancement and change of legislative cycles. It is a Technology-headed to require driven methodology in which blockchain applications are altered to guarantee a fit with necessities of regulatory cycles and in which the authoritative cycles are changed to profit by the innovation. Government associations need an exhaustive comprehension of the blockchain plan standards, the potential applications in the space of e- government and the investigation of administration instruments to manage the restrictions and difficulties of the blockchain innovation when utilized in a bunch of areas, going from the monetary and business area to the social areas of medical care and training. In this paper, we survey the writing to recognize the potential use cases and use of Blockchain to empower taxpayer driven organizations. Keywords: Audit and Compliance, plenum agreement, decentralization, good contract, Hyperledger
A Survey of Key Policy and Ciphertext Policy Attribute based Encryption on Various Security and Efficiency Parameters
ABSTRACT Cloud is providing various services and out of which storage is one such credential service. Many users are gaining benefits by storing their data in cloud because cloud provides unlimited storage, High speed Computations and better convenience. But the problem arises when the user has to store some critical data in the cloud. So, a promising Cryptographic scheme called as Attribute based encryption is needed which not only is showing potential in safeguarding the data privacy in the cloud but also finding the violations in the privacy. On the basis of various Security requirements of Access control mechanisms and Functional requirements of two primary techniques named as Key Policy and Ciphertext Policy Attribute Based Encryption, a detailed survey has been conducted in this paper and various loopholes and various feature of these two techniques are highlighted in a tabular form. Keywords: Fine Grained Access Control, CP-ABE, KP-ABE, User Revocation, Single Authority, Multi Authority
The Use of Developed Computer Medical Process Manager “Medical Commander” for Application in Medical Practice
ABSTRACT The use of the computer in the medical clinical practice plays an important role for the effective diagnosis, treatment, and management of patients in hospitals. The use of a computer today in medical practice is limited to the creation of medical database management systems that take into account all the requirements of hospital and are capable of providing simple and efficient storage of information about patients who visit the hospital which leads to the completely reduction of paperwork, and reduction of the workload on staff. However, no one database management system does not permit the physician to actively participate in the medical process itself, i.e., in the diagnosis, treatment and monitoring of patients, using a computer. The paper presents the use of original developed computer medical process manager “Medical Commander” for application in the medical practice that allows not only in real time easy to create, complete, edit and obtain upon request of a physician information data base about the patient(medical database management system) , but, using computer statistical processing of this information effectively to participate in the processes of diagnosis treatment and using the optimal interpolating prognostication predict the investigated symptoms and treatments outcomes of patients in the clinical practice. Keywords: Database management system, software development, optimal interpolating prognostication
Cyber Crimes: Their Impacts & Solutions - A Review
This paper distinguishes the significance of being familiar with the impacts of cyber crime remembering the ongoing exercises that have occurred and offering answers for shield oneself from it. In the present period of web based preparing, limit of the data is on the web and inclined to cyber attacks. There are countless cyber attacks and their conduct is hard to early seeing subsequently hard to limit in the early periods of the cyber attacks. Cyber attacks may have some inspiration driving it or might be prepared unwittingly. The attacks those are handled intentionally can be considered as the cyber crime and they have genuine effects over the general public as efficient upset, mental issue, risk to National safeguard and so on. Limitation of cyber crime is subject to legitimate examination of their conduct and comprehension of their effects over different degrees of society. Along these lines, the present original copy gives the comprehension of digital cyber crimes and their effects over society with the future patterns of digital violations. Keywords: Cyber Crimes, Cyber Attacks, Potential Impacts, Cyber Crime Solutions, Digital Violations. Cite this Article: Arshil Noor.Cyber Crimes: Their Impacts & Solutions - A Review.International Journal of Software Computing and Testing. 2020; 6(2): 1–10p.
Copyright (c) 2020 International Journal of Software Computing and Testing
Review of Feature Selection Methods and Semi Supervised Feature Selection Algorithms for Classification
Current evolution in technology has resulted in tremendous growth of data with respect to dimensionality and sample size. Knowledge discovery from these high dimensional data are becoming cumbersome. Though powerful machine learning algorithms are prevalent, noisy data, imperfect sensing and collection of data leads to poor and defective knowledge discovery. Noise and redundant features cannot be circumvented due to which data collection process is biased. Dimensionality reduction techniques namely feature extraction and feature selections are the two most popular techniques to remove redundant and irrelevant features in huge dimensional data. Compared to feature extraction, feature selection leads to better readability and interpretability of features. This paper presents an extensive preliminary understanding about feature selection and attempts a comprehensive recent survey of semi supervised feature selection methods. This summary enables the researcher to obtain a deep understanding in choice of semi supervised feature selection algorithms for improving the learning performance. Keywords: Feature Selection, Semi supervised learning, Filters, Wrappers, Hybrid methods. Cite this Article: A. Meena Kowshalya, M.Lincy, R. Suvarna. Review of Feature Selection Methods and Semi Supervised Feature Selection Algorithms for Classification. International Journal of Software Computing and Testing. 2020; 6(1): 39–51p.
Adaptive Text_Summarization: A Meaningful Summarization of Reviews
Adaptive text_summarization is a model which takes elaborated data set of reviews containing more than two attributes as input and further breaks down those large chunks of text into summarized - form by eliminating attributes which are of less important for final evaluation. We keep only those attributes which contribute for better adaptation of meaning of the dataset. We have executed the techniques of Recurrent Neural-Network and Seq2Seq models to accomplish the aim with better efficiency. The selected attributes are passed through the encoder and decoder. The encoder converts the text into vectorised form of data which further is passed through the unidirectional LSTMs of the decoder providing us with naturally acceptable modified version of the source text. We have also explored both the techniques of extractive and abstractive text_summarization. The extractive text summarization evaluates the source text, analyses the focused words and present them as output without any language formation and disobeying grammatical rules. On the contrary, abstractive text summarization accepts the source dataset and evaluates the meaning out of it producing naturally acceptable summarized form of text. This model can be acquired to overcome the issue of long summary generation in various product reviews published by the users of the e-commerce applications. Keywords: Recurrent neural network, Seq2Seq, DUC (Document Understanding Conferences), abstractive and extractive text summarization, NLP (Natural Language Processing), bidirectional LSTM (Long-short Term Memory) Encoder, unidirectional LSTM (Long-short Term Memory) decoder. Cite this Article: Twinkle Kapoor, Tarushi Chaudhary, Umang Gupta, Sparsh Agarwal. Adaptive Text_Summarization: A Meaningful Summarization of Reviews. International Journal of Software Computing and Testing. 2020; 6(1): 1–7p.
Feature Extraction and Evaluation of Colon Cancer Using PCA, LDA and Gene Expression
At about 90 per cent of cases occurring in 50 people or older, colorectal cancer is the second most common type of cancer globally. Cancers may penetrate the deeper layers of colon and spread to other organs from the inner surface or from the muscular layer of the colon. The illness is lethal left untreated. Current screening of colon cancer is performed by colonoscopy. Visual examination of the colon and rectum mucosal lining with a photograph mounted on an endoscope is required. Testing will then biopsy suspicious areas. Images of colon (top photo) and normal colon tissue were found in the PR-OCT imagery. The green boxes display the probability values of the predicted "teeth" tissue patterns. Effective screening of colon cancer by versatile colonoscopy is carried out. The procedure involves visual inspection with a camera mounted on an endoscope of the mucus lining of the colon and rectum. Testing is then performed on suspicious regions. While this is the present standard of care, it has its drawbacks. This procedure relies first of all on visual identification, but the naked eye is difficult to detect minor lesions, and early malignancies also fail. Furthermore, only shifts in the bowels surface can be observed by visible endoscopy, not in its deeper layers. Keywords: Colon Tissue, PCA, DNA, Colonoscopy, Machine Learning Cite this Article: G. S. Pradeep Ghantasala, Bonam Tanuja, Golla Surya Teja, Anagurthi Sai Abhilash. Feature Extraction and Evaluation of Colon Cancer Using PCA, LDA and Gene Expression. International Journal of Software Computing and Testing. 2020; 6(1): 26–32p.
Mathematical Education visualizing with Printing 3-D Technology
The main objective of this paper is to explain the role of 3D printing technology in the field of mathematical education. Visual teaching has always been an important component of education. Abstract mathematical concepts help students in understanding and mastering knowledge. One of the prominent technologies in visualizing the mathematical concepts is 3D Printing. In this paper, it is discussed that how 3D printing helps in conceptual understanding and creating mathematical ideas for students as well as teachers. Regarding the relationship of this 3D printing Technology and Mathematical Education, a comprehensive introduction is described in a reliable way. Keywords: 3D printing technology, visual teaching, mathematical education, coding, matlab Cite this Article: Ashutosh Gupta, Arun Kumar Yadav. Mathematical Education visualizing with Printing 3-D Technology. International Journal of Software Computing and Testing. 2020; 6(1): 33–38p.
Copyright (c) 0 International Journal of Software Computing and Testing
Experimental Realization of Constrained Optimization of Sliding Mode Controller Parameters with Modified Objective Functions
An appropriately tuning of Sliding Mode Control (SMC) can be used to overcome the weaknesses like sensitivity to parameter variations, modeling errors and external disturbances. In this research article, Non-Dominated Sorting Genetic Algorithm (NSGA-II) based SMC with modified objective function and the best weight values have been evaluated to improve the performance of closed-loop level control system. Equivalent weights and importance weights are assigned to each term of an objective function based on the standard deviation and percentage contribution of the terms. The stability of the closed-loop system satisfies the Lyapunov stability criteria. The experimental results are conferred and compared with Proportional-Integral-Derivative (PID) controller, conventional SMC and NSGA-II algorithm based SMC. Realistic conditions are used for testing the robustness of the controller. Reduction in rise time, settling time, reaching time, response time and delay in the output is achieved using NSGA-II based SMC. The experimental results demonstrate that NSGA-II based SMC strategy provides better set-point tracking performance and the disturbance rejection capability. Keywords: Non-Dominated Sorting Genetic Algorithm-II, Proportional-Integral-Derivative controller, Sliding mode controller, Multi-objective optimization, Real-time experimentation. Cite this Article: Laware A. R., Talange D. B., Bandal V. S. Experimental Realization of Constrained Optimization of Sliding Mode Controller Parameters with Modified Objective Functions. International Journal of Software Computing and Testing. 2020; 6(1): 8–25p.
Waste collection and to dispose is one of the biggest issue that world is facing. This requires huge expenditure and more costing includes manpower, collection bin vehicle cost, fuel cost, and proper ways to dispose it. This factor led the necessity of designing, implementing and executing an intelligent smart waste management system for proper dispose of waste. This paper concentrates on the implementation of smart waste management using IoT computing. This system uses ultrasonic sensor for sensing the level of waste, and using Arduino NodeMCU, it will send the data to the server. Based on the waste level the collector truck will go for collection as per the optimized route generated. This system provides the efficient solution for the waste management system. Keywords: smart waste management system using IoT, Arduino, LCD display, GSM, module, ultrasonic sensor Cite this Article: Amal Baby, Anandu Ranjendran, Jestin. K. Joseph, Jyothisree. K.R. Smart Waste Management System Using IoT. International Journal of Software Computing and Testing. 2019; 5(2): 30–37p.
SARGoT: Smart Autonomous Robotic Goods Transporter
In the present condition industrial loading and unloading of heavy loads manually is one of the most important objectives which turn out to be quite difficult, time-consuming and risky for humans. In this modern era, robots are being developed for various purposes to accomplish many tasks which seem to be too complex for humans. The advantage of using robots, for industrial purpose have been excellent in terms of speed and efficiency of doing required tasks compared to that of humans. To solve this problem we have designed a robot named SARGoT. This robot has got mainly three features and they are: path-tracking. avoiding collision, loading and unloading heavy industrial goods. The autonomous robot is designed to start its movement from a starting position where goods are loaded on it, then follow a black track and unload goods by itself after reaching a destination place. Infrared sensor has been mounted in the front of the robot so that the sensor can detect path by emitting and receiving signals allowing it to move in the predefined path having left and right turns to carry goods from starting position to the destination position. Arduino Uno has been used for the coding section and the control circuit of the robot has been implemented for controlling the robot’s movement within the defined track. The main aim is to load and unload heavy goods safely. Besides, the robot has been designed in such a way that it has the ability to avoid collision with any obstacles that come in its way. Ultrasonic sensor has been used in the robot to send the signal and detect the presence of any obstacle that may appear in the robot’s track and stop momentarily for certain time until the obstacle move away. Building an industrial robot with moderate speed, good efficiency in loading and unloading purpose within a short time to ease human suffering has been the main objective of this paper. Keywords: avoiding collision, path-tracking, Arduino Uno, loading and unloading heavy industrial goods, SARGoT Cite this Article: Akhil Abraham, Ananthakrishnan G.S., Bijeesh B. Varghese, Sivakumar S., Rakesh S. SARGoT: Smart Autonomous Robotic Goods Transporter. International Journal of Software Computing and Testing. 2019; 5(2): 23–29p.
PATrIoT: Precision Agriculture Through Internet of Things
The paper report is on the design of the sensor network when connecting agriculture to the IoT. Reliability, management, interoperability, low-cost and commercialization are considered in the design. Finally, we share our experiences in both development and deployment. This paper developed the decision support system to forecast agricultural production using IoT sensors. This system was also a unified system that supports the processes sowing seeds through selling agricultural products to consumers. The publisher's work on the IoT-based agricultural production system through analysis between the yield measurable data and agricultural environment data has upgraded the capacity of farmers, analysts, and government authorities to dissect current conditions and foresee future harvest. Furthermore, horticultural items quality can be improved because farmers watch the entire cycle from seeding to selling utilizing this IoT-based choice emotionally supportive network. Keywords: IoT, sensors, Arduino, data warehouse, agriculture Cite this Article: Greeshma Thankachan, Nirmal Dev, Shybin P Shibu, Tintu Joseph, Neethan Elizabeth Abraham. PATrIoT: Precision Agriculture through Internet of Things. International Journal of Software Computing and Testing. 2019; 5(2): 16–22p.
Intelligent Traffic Control System for Emergency Ambulance
The growth of population leads to rise in the number of vehicles. This resulting traffic jams and rush hour, congestion is the major barrier for the emergency ambulance are not able to reach their right destination in the right time. To solve this downside, we tend to return up with “intelligent control for emergency ambulance”. This system proposed clears the traffic block and traffic jams for emergency ambulance by turning the red light to green on the path of the ambulance. The system consists of Arduino, IR transmitter and receiver, RF transceiver. The information of the emergency ambulance is transfer with each and every traffic islands on the path it travels to destination using RF transceiver for long range and IR transceiver for short range. This proposed method will clear the traffic congestion till the ambulance passes and later it regains its original flow of control of the traffic signal. Keywords: intelligent traffic control system, Arduino, RF transceiver, IR transmitter and receiver, Buzzer, LCD, transmitter side, receiver side, ambulance Cite this Article: Arunkumar T R, Sijin Sam, Vineeth C A, Varunkumar G, Simi P Thomas. Intelligent Traffic Control System for Emergency Ambulance. International Journal of Software Computing and Testing. 2019; 5(2): 7–15p.
Android Based Smart Tracking for College Bus
Among all public transportation services, bus service is the major one used by public. Especially in a busy city, bus is the easiest, convenient and cheaper transportation. Passengers are impatient while they are waiting in bus stop because they are not able to know exactly how long to wait and where the next coming bus is. At this crucial situation, the idea of vehicle tracking gained more importance in the field of transportation. In view of the case of college students, there are times when they are unknowing of the change in bus or the bus timings due to any emergency cases and miss the bus due to various issues like change in bus timing, change of bus, or bus service unavailable due to breakdown or accident. Taking in account of such a situation, ‘Android-based Smart Tracking for College Bus’ proposes a real-time college bus tracking application which runs on Android smart phones. It mainly focuses on the concept of bus tracking system using global positioning system. It is a real-time system as the current location of the bus is updated every moment in the form of latitude and longitude values which are received by the students through their application on Google maps. The application also estimates the time needed to reach a specific stop on its route. Alerting system is essential for providing the location and information about college bus to the specified authorities. The application uses client–server technology. Keywords: Android, tracking, global positioning system, client–server, global standard for mobile Cite this Article: Akhil K.R., Alka Merin John, Amina M.K., Indu Viswanathan, Resma Chandran. Android-based Smart Tracking for College Bus. International Journal of Software Computing and Testing. 2019; 5(2): 1–6p.
Self-Monitoring Automated Route Trashbin
Waste management is one of the vital role of a smart city. Nowadays smart cities are rapidly increase at the same time the pollution rate was also increased highly. So people are doing the things smartly to reduce the pollution. Since the generation of waste is active in nature, it often outcomes in some garbage cans getting overloaded and leaking while other remains almost vacant. An overflowing waste bin cannot only produce pollution but also provide health threats, especially in warm surroundings. Waste management is one of the major issue in our society which would affect predominantly. This project reduces the trash bin waste smartly. The Passive Infrared sensor (PIR) is used to identify the existence with the assistance of motion. The DC Gear motor is used to open and close trash bin by means of rotation and it is placed inside the trash bin. Infrared (IR) sensor is located inside the trash bin which is used to sense the garbage level within its range. If the trash bin is full the buzzer will be on and GSM modem is used to send the message to the respective authority. The trash bin is built with a microcontroller which is interfaced with GSM, PIR sensor, DC gear motor and IR sensor. Once the waste reaches its limits, IR sensor will activate the GSM modem which will aware the involved authority until the trash in the bin is removed. Once these garbage bins are executed on a large level, by replacing our traditional bins present-day it has decrease the pollution level, remove the garbage with investing less time and keep our environment clean. Keyword: PIC16F877A Controller, PIR, Sensor, Microcontroller, GSM Cite this Article: M. Lizzy Nesa Bagyam, S. Mohamed Sameem, R. Nandhagopal, C. Priyanga. Self-Monitoring Automated Route Trashbin. International Journal of Software Computing and Testing. 2019; 5(1): 22–25p.
Smart Waste Segregation and Management Using IOT
The Internet of Things (IoT) is a concept in which the interconnection is done via the internet of computing devices embedded in everyday objects, enabling them to send and receive data [1]. The initial technical realization of IoT was done by RFID which is used in identification and tracking of devices [5]. Due to the merits and characteristics of IoT, it plays an important role and has its applications in many fields including waste management. This paper proposes a smart waste segregation system composed of smart garbage bags, various sensors, software and hardware. The segregation of waste plays a very crucial role in waste management. Basically, waste can be divided into degradable and further it can be divided into different categories subjected to further use. This waste can be subjected to recycling and can be further used. Waste can be served as a source many times. This paper proposes the effective resource utilization by segregating and managing the waste. Keywords: Garbage Segregation, Smart Garbage System, Smart Garbage Bin, Automatic Waste Segregation, Segregating Wastes, Waste Management. Cite this Article: Anjali Singh, Priya Saroj. IoT Enabled Smart Waste Collection. International Journal of Software Computing and Testing. 2019; 5(1): 15–21p.
Artificial Intelligence in Cyber Security
Security isn't working. While security as a level of IT spend keeps on developing at a powerful rate, the expense of security breaks is becoming significantly quicker. Associations are spending near $100 billion on a bewildering cluster of security items. Truth be told, it isn't exceptional for CISO associations to have 30 to 40 security items in their condition. Be that as it may, in the event that you ask boss data security officers how they feel about their security chance, they will express worries over being exceedingly uncovered and defenseless. Artificial intelligence (AI) and machine learning (ML) can offer IT security professionals a way to enforce good cyber security practices and shrink the attack surface instead of constantly chasing after malicious activity. Cyber security ostensibly is the order that could profit most from the presentation of artificial intelligence (AI). Where ordinary security frameworks may be moderate and deficient, man-made consciousness methods can improve their general security execution and give better assurance from an expanding number of advanced digital dangers. Keywords- machine learning, Cyber security, artificial intelligence Cite this Article: Omkar Devrukhkar, Sandeep Chouhan. Artificial Intelligence in Cyber Security. International Journal of Software Computing and Testing. 2019; 5(1): 9–14p.
Waste management is one of the essential city services. It includes different activities like collection, transportation, treatment and disposal of waste. In this paper we are going to discuss the different waste collection methods which were previously used and the different smart waste collection methods which can be used to ease the overall process and the difficulties that occur in the traditional method. With the help of technology like IOT it is been possible to implement Smart Waste Management. So we will also be discussing about different IOT based Waste Collection techniques. Keywords - Waste Management, Smart waste collection, IOT, Sensors, Smart City, Smart Bins. Cite this Article: Anjali Singh, Priya Saroj. IoT Enabled Smart Waste Collection. International Journal of Software Computing and Testing. 2019; 5(1): 15–21p.
A Study of Extent of Usage of Information Technology in Green Revolution
Horticultural practices and progressions contrast comprehensively—since plants have their very own disparities and the area assumes a job on their improvement too. Yet, through the trading of information from various horticulturally included people from everywhere throughout the world, enhancement of strategies can be experienced too. It has had an effect on how data is shared and having the capacity to utilize this data for the progression of the agrarian segment gives an extraordinary positive effect that is gainful for everybody. IT has turned into a scaffold for individuals from everywhere throughout the world. Keywords— Digital Technologies, VKCs, VRCs, e-choupal, MSSRF Cite this Article: Vipul Sethi, Omkar Sawant. A Study of Extent of Usage of Information Technology in Green Revolution. International Journal of Software Computing and Testing. 2019; 5(1): 1–8p.
User Trust & Item Ratings based Regularized Model
We recommend TrustSVD, a faith grounded frame factorization system for proposals. TrustSVD integrates dissimilar data sources into the suggestion demonstrate to diminish the information sparsity and cool begin issues and their exploitation of proposal execution. An investigation of social trust information from four true informational collections proposes that the express as well as the understood impact of the two evaluations and trust ought to be thought about in a suggestion display. TrustSVD accordingly enlarges over the finest in session application control, SVD++ (which utilizes the unambiguous and silent impression of assessed things), by additionally consolidating both the express and verifiable impact of trusted and putting stock in clients on the expectation of things for a dynamic client. The proposed system is the first to expand SVD++ with social confide in data. Exploratory outcomes on the four informational collections exhibit that TrustSVD accomplishes preferable exactness over other ten partners suggestion systems. Keywords: Item Rating, User Trust, Social Network, Rating.
Speech Based Access of Agricultural Commodity Prices and Weather Information
The mobile and internet revolution has provided solutions to number of different problems, yet farmers in India have not benefit much due to this technological revolution. The reason being lack of knowledge to use internet, smart-phones and illiteracy forces farmers to still follow obsolete and outdated practices. In this paper we are proposing a cloud-based system, wherein the illiterate farmers can make a voice call through a toll-free number which doesn’t even require the Smartphone. The call is automatically answered using a programmable voice interface and expects the farmer to speak in his/her native language Kannada. The farmer can ask about the commodity prices or weather information in Kannada language. The system will automatically answer, process the voice call (Speech processing) , translate it into English language (Language translation), fetch the requested information from the cloud/web and reply with latest commodity price and weather information based on the location of the speaker in Kannada language. Further, the efficiency and reliability of the system has been tested. Keywords: Cloud computing, speech processing, Language translation.
An Innovative Approach for Crop Disease Detection using Image Processing Technique and Pesticide Suggestion for Effective Crop Cultivation
The yield of the crop is important as the farmers are the back bone of our country India. The bacterial attack is going to ruin the early detection of these diseases on leaf and the pomegranate fruit. The proposed framework automatically grades the disease on leaves of crops. The system efficiently instructs Information and Communication Technology (ICT) in Agriculture and hence contributes to Precision Agriculture. Currently, plant pathologists mostly trust on nude eye forecast and a sickness notching scale to mark the ailment. This manual categorizing is not only time taking but also not feasible. Hence, we are proposing an image processing-based approach to automatically grade the disease spread on plant leaves by employing SVM( Support Vector Machine ) classifier to make the decisions. The results are simulated in the Mat lab and it has shown that it has successfully detected the leaf or crop disease and names it. The proposed system can be reliably implemented on the real time scenario. Keywords: Crop disease, detection, Image Processing, effective crop cultivation
Now-a-days computer network, in general, develop over size expanding vulnerable purposes of system. To survey the dependability and security of PC network, one probably won't comprehend those purposes of powerlessness with high volumes of produced reports. With complex systems set up and increment in populace of versatile system hubs, the report may almost certainly transform into pages of information than data as the issues can't be tended to at a solitary go. Keywords: VS Scan, STUXNET (an internet worm), MulVAL.
Software Testing for Mobile Computing: A Review
We present a structure for testing applications for mobile computing devices. At the point when a device is moved into and appended to another system, the best possible working of utilization running on the device frequently relies upon the assets and administrations gave locally in the present system. This structure gives an application-level emulator to mobile computing devices to take care of this issue. Since the emulator is built as a versatile specialist, it can convey applications crosswise over systems for the benefit of its objective device and enable the applications to associate with neighborhood servers in its present system similarly as though they had been moved with and executed on the gadget itself. Keywords—Testing, mobile computing, mobile agent, network-dependent application.
Cryptography and Encryption Techniques- A Survey
Today security plays an vital role to protect your information from intruders and hackers. Information security is the most extreme basic issue in guaranteeing safe transmission of data through web. Also network security issues are now becoming important as security is moving towards digital information era. As more and more users connect to the internet it attracts a lot of cyber-attacks. After noticing constant reports of data, theft and hacking, enhancing security of data has become mandatory. The encryption techniques and various algorithms are used to provide the required security to the applications. This paper deals with the overview on network security and various techniques through which network security can be enhanced i.e. Cryptography. Cryptography provides Confidentiality, Integrity, Non-repudiation and Authentication.
New Approach For Efficient Fuel Filling In Vehicles Using IOT
Checking Systems are basic to track and comprehend the developments that happen in conditions. Remote viewing and information gathering structures are noteworthy and viable instruments to collect data from fuel aggregating tanks. The fuel association structure is Shows how the improvement is being mauled in the fuel stations. In fact the fuel stations are deluding open by blame looking at check for the fuel with the progression. This meander will assist the fuel clients with convergence check the fuel tally by the gadget which is worked in the fuel tank of the each client and a watching contraption in perspective of the Raspberry-Pi PC, it amasses the data of how much fuel filled in to the tank furthermore it takes data about tank's fuel level perseveringly through its sensor and live spilling of the webpage page, by then trades it especially to the web, where it can be investigated at whatever point and wherever through web application. This paper demonstrates the execution of watching structure in context of web of things progression to quit misusing the improvement at the fuel stations what's more shield the peak objectives from theft and offer security to remote regions.
Effective E-Health Monitoring Using IOT (Internet of Things)
The basic purpose of joining of the paper is to address an e-flourishing getting, transmission and watching framework. Tolerant success parameters are checked by remote sensor system and gave to the far end through Zigbee interface. Information got at far end is seen by MATLAB. On the off chance that the parameters are shocking it arranges the GSM module to send SMS on professional PDA. Framework finished in this paper is made for such patients who are not in the key state but rather they should be checked ceaselessly. Precisely when the principal condition happens, framework will start an aggravating message and send it to the expert. It is energetic, more moderate and screens consistent remotely from their homes.
Continuous Mining Approaches with Obsolete Database: A Review
The sequential pattern mining on progressive databases is very incipient approach, in which many researchers progressively discover the patterns in period of interest. Period of interest is a sliding window perpetually advancing as the time goes by. As the focus of sliding window changes, the incipient items are integrated to the dataset of interest and obsolete items are abstracted from it and become au courant. In general, the subsisting proposals do not plenarily explore the authentic world scenario, such as items associated with support in data stream applications such as market basket analysis. Thus, mining consequential erudition from fortified frequent items becomes a nonpicayune research issue. This paper present the sundry works done on progressive sequential pattern mining. This paper presents a review of sequential pattern-mining techniques in the literature. This paper relegating sequential pattern-mining algorithms predicated on paramount key features fortified by the techniques. This relegation aims at understanding of sequential pattern mining quandaries, current status of provided solutions, and direction of research in this area. This paper additionally endeavors to provide a comparative performance analysis of many of the key techniques.
Artificial Intelligence and Associated Technologies
This paper reviews the meaning of artificial intelligence and its various advantages and disadvantages including its applications. It also considers the current progress of this technology in the real world and discusses the applications of AI in the fields of heavy industries, gaming, aviation, weather forecasting, expert systems with the focus being on expert systems. The paper concludes by analyzing the future potential of Artificial Intelligence.
Artificial Intelligence “Humans and Machines”
Character Recognition with Neural Network
In this project artificial neural network has been called for its application as characters recognizing network. The network is made to learn as per the requirement by training them with some specific patterns that corresponds to the character. The number of input and output layer neurons is chosen. The training patterns and testing patterns are designed using matrices 0’s and 1’s.The weights in the network are adjusted using back propagation algorithm (delta rule) for training patterns and are checked for testing patterns. Then we train the network using those input patterns followed by testing the neural network with given training patterns
— In this paper, we pursue to offer an introduction to AI to policymakers and other stakeholders in the wider Internet ecosystem. The paper describes the basics of the technology behind AI, recognizes the key considerations and challenges surrounding the technology, and offers several high-level principles and recommendations to follow when dealing with the technology. Keyword: AI, Machine Learning, Key Consideration, Algorithms.
D-Crush: A stronger approach towards web security
In today’s cyber era the term cybercrime is spreading like fire in the forest because we are becoming much more dependent on the cyberspace. The dependency ranges from the birth date of an individual to all the financial details of any organization. Because of this dependency, the cyber space is much more prone to attacks for the various reasons like financial gains, competition, committing crimes etc. It is evident that with time, the number of attacks has been increased by manifold. So, it is the high time to take some action against otherwise it may ruin someone’s life in form of business failure, private information leakage, mal-governance etc. Therefore, it is required to do a detailed study on the cyber-attacks to provide their counter measures. This research paper reviews and provides a solution for a one such problem of cybercrime. The solution deals with the way of data transfer over the web within clients and servers. The main aim of the solution is to give high quality security to the crucial information.
Edge Detection of Image: A Programmatic Combination of M-B-P Operators
Edges of an image can be represented by using various edge detectors with different approaches. Edge detection is a very fundamental part in image processing and computer vision. In this paper, an emerging edge detection approach which computes edges of different images using the programmatic combination of Morphological-Bergholm-Prewitt (M-B-P) edge detectors is presented. This approach can be used as framework for multi-scale edge detectors for a very wide range of images in the field of image processing and computer vision. Here the proposed approach is compared with each edge detector separately.
INDISCRIMINATE BASED UNIT TESTING FOR AUTOMATED TEST STATEMENT PRODUCTION
Random based mostly Testing is that the follow of victimization organisation for a few aspects of check computer file choice. During this system describe the unit check knowledge generator. Its 2 levels. The lower level could be a Random based mostly unit testing engine that tests a collection of ways in keeping with parameter values specific as genes in a very body, together with parameters that encrypt a worth utilize policy. The higher level could be a genetic algorithmic program that uses fitness analysis, selection, mutation and recombination of chromosomes to search out smart values for the genes. Goodness is evaluated on the idea of check coverage and range of methodology calls performed. Users will use to search out smart parameters, and so perform Random based mostly unit testing supported those parameters. The irregular checking will quickly generate several new test cases that come through high coverage, and might still do therefore for as long as users want to run it.
A Study and Analysis Among Dijkstra’s Algorithm, Bellman–Ford Algorithm and Floyd’s Algorithm on Run-Time Basis Using Source Code
Numerous applications like communication network and transportation use shortest path algorithm to notice the shortest path between two nodes. In the Single source shortest path algorithm, a shortest path is calculating from one node to another node. In the present paper, I have compared the results of the shortest path algorithms (Dijkstra, Bellman–Ford) on the basis of running time. I am using C# programming language to compare the algorithms. I have also compared the algorithms on the basis of complexity and space. I also tried to give some advantages and disadvantages of both the algorithms.
In this review of literature, we have put our efforts to analyze the reported work in the field of mobility models for wireless ad-hoc network. The next section defines the detailed working of mobility models which are presently being used on wireless ad-hoc networks. “Some mobility models that define mobile nodes, movements are free of each other “called Entity mobility models” and also which defines mobile nodes movements are dependent on each other “called, group mobility models” which are already been explained. In current work an attempt has also been made to offer a general idea of individuals mobility models and their important properties.
Web-Based College Mark Management System
College Mark Management System is an online application which is helpful for students as well as the college authorities. In the current system, all the activities are done manually. It is very time consuming and costly. Our Mark Management System deals with the various activities related to the students through computerized service. In the application has three different types of users namely administrator, staff and student. Administrator has the rights to add new student and staff and can edit and delete a user. A student can view his profile, biodata, mark information and notification. The administrator can send notifications and file documents for the student as well as staff. The student can see the marks based on student roll no., College Mark Management System provides one attractive environment where admin can manipulate data and information about students and staff easily. Also in this system includes the staff details, internal mark, semester mark details and all. Staff can enter the marks and view the marks of the students. Finally, this system is most helpful to college management.
Agribot is a robot designed for agricultural purpose. As one of the trends of development on automation and intelligence of agricultural machinery in the 21st century, we are applying the idea of robotics technology in agriculture, since robotics technology is used in many of the fields such as defense, surveillance, medical field, industries and so on. In this paper, the robot system is used to develop the process of cultivating agricultural land without the use of man power. The aim of the paper on Agribot is to reduce the man power, time and increase the productivity rate. It completes the elementary functions involved in farming i.e. harvesting, spraying. And they steadily appear advantages in agricultural production to increase productivity, increase application accuracy and enhance handling safety. It will send the data’s through the GSM module to owner’s phone, this data can be studied and improve the chances of an application to read the data coming through GSM modem. All kinds of agricultural robots have been researched and developed to implement a number of agricultural productions in many countries. This Bot can take humidity, temperature, soil moister, etc. of farm. In agriculture, the opportunities for robot-enhanced productivity are enormous and the robots are appearing on farms in various guises and increasing numbers. We can expect the robots performing agriculture operations autonomously such as spraying and mechanical weed control, watching the farms day and night for an effective report. Agribot is a robot designed for agricultural purposes. It is designed to minimize the labor of farmers in addition to increasing the speed and accuracy of the work so the agribot helps framer to increase productivity by reducing labor cost.
Virtual Machine-Based Task Scheduling Algorithm
Cloud computing is a type of internet-based computing that provides shared computer processing resources and other devices on demand. It is very useful for the applications which sharing their resource on different nodes and also cloud computing has more scalability. The performance and efficiency of cloud computing always depends on the performance of user tasks. Virtualization concept was introduced to improve the efficiency of cloud computing. Virtualization refers to creating a virtual (rather than actual) version of something. Virtualization technology mainly used to virtualize single server to multiple server in cloud computing platform. In cloud computing the load balancing concepts are classified into three types such as data center selection, virtual machine scheduling and task scheduling. Task scheduling plays a key role in cloud computing systems. Scheduling in cloud is responsible for selection of best suitable resource for task execution. Task scheduling methods of cloud computing considering the task resource requirement of CPU and memory without considering bandwidth requirement. In the existing cloud computing environment, most of the tasks scheduling-based algorithms are used. Bandwidth and data transmission are not considered in the existing system. In the proposed system, we are introducing a Quantum Particle Swarm Optimization which is used to solve task scheduling problem with bandwidth and data transmission parameters. The proposed algorithm is simpler and more powerful than the algorithms already existing. It will exhibit minimization of makespan, computation cost, communication cost and the bandwidth to improve the data transmission rate.
Seed Quality Analysis by Using Image Processing
Globally, wheat is the principal source of vegetable protein in human food, having higher protein content than other major cereals like maize and rice. In terms of total production tonnages used for food, India is currently at second rank as the main human food crop. Determining the quality of wheat is critical. Specifying the characteristics of wheat manually needs an expert decision and is time consuming. Sometimes the variety of wheat appears so similar that their separation becomes a very tedious task when carried out manually. To overcome this problem, Image processing can be used to classify wheat according to its quality. The seed quality identification is very important in agriculture. Before boring the seed in farm, it must be viewed properly and then sowed. In the current situation, the farmers are taking more efforts in their farm and also spending more time and money. But inspite of their hard work they do not get proper profit. So, the technology can come for rescue here. There are certain limitations to human eye to observe the seed. So, the electronic world helps us to separate the faulty seeds from quality seeds. The image processing algorithm is implemented using Matlab. The proposed technique is defined with the assistance of computerized image processing mechanism on MATLAB.
An Empirical Evaluation of a New Comparison Sort Algorithm
Most of the present day applications are database oriented like telephone directory, list of students, list of employees in an organization, and hospital databases etc. The users of these applications would like the data in some specified order (ascending or descending) that may be arithmetical or lexicographical. The sorting algorithms sort the data stored in database on its primary key or any other key value. This paper presents a new comparison sorting algorithm that is easy to implement and well efficient. We have introduced, analyzed, implemented and compared this new algorithm with bubble sort, insertion sort, selection sort. The results show that the new one algorithm is much better than the bubble sort and insertion sort.
Software Designing, Computerization and Evaluation for the Automation of Centralized Library Activities
The existing library system totally runs in manual. The manual system is error prone and time consuming. It is very difficult for a person to produce report. There are chances for manipulating library reports and changing it. By this article I would like emphasize how software design and evaluate for the same.
Short Communication: Computerization of the Central Library
The concepts of automation of library activities, areas and services such as acquisition, database management, classification and cataloguing circulation, serial control, information retrieval, communication networks, and documentation services etc. It mentions the need for Content Management System. Simplify the steps of software selection with the comparison in between some leading software's. Provides the options for choosing the configuration of computer hardware based on the size of the library
System Analysis and Design for software and Tools used for Village Information System Management through Web based Application
In today’s world everything will be electronic and easy to handle, so our villages we will also modified as electronic computerized ones. In this article author wants to explain how web based applications analyse and design for the same.
System Testing for the Automation of the Automobile Workshop in Automobile Industry
Here the System testing involved is the most widely used testing process consisting of five stages as shown in the figure. In general, the sequence of testing activities is component testing, integration testing, and then user testing. However, as defects are discovered at any one stage, they require program modifications to correct them and this may require other stages in the testing process to be repeated.
Review Insight: Wireless Network Security Threats
From recent years there is a huge development in wireless networking, all the generation peers relying on it. Although every one craving for its benefit not on other aspects (it’s not completely a boon for us bane as well). Hackers and intruders will create utilization of the loopholes of the wireless communication. In this paper we are going to chew over the various remote security dangers to wireless systems and conventions nowadays accessible like Wired Equivalent Privacy (WEP), Wi-Fi Protected Access (WPA) and Wi-Fi Protected Access a pair of (WPA2).Wireless security danger can be on highlight during this paper.
Windows 10 was a big change for Microsoft’s traditional operating system. Windows 10 introduces what Microsoft described as a "universal" application architecture. Windows 10 is configured to send various information to Microsoft and other parties, including the collection of user contacts, calendar data, and "associated input data" to personalize "speech, typing, and inking input", typing and inking data to improve recognition, allowing apps to use a unique "advertising ID" for analytics and advertising personalization and allow apps to request the user's location data and send this data to Microsoft and "trusted partners" to improve location detection (Windows 8 had similar settings, except that location data collection did not include "trusted partners).
Software testing is a critical element of the ultimate review of specification design and coding. Testing of software leads to the uncovering of errors in the software functional and performance requirements are met .Testing also provides a good indication of software reliability and software quality as a whole. The result of different phases of testing are evaluated and then compared with the expected results. If the errors are uncovered they are debugged and corrected. A strategy approach to software testing has the generic characteristics:
Short Communication on Fingerprint Image Enhancement and its Future Scope
The fingerprint images are rarely of perfect quality, due to the reasons like variations in impression condition, skin condition, scanning devices or may be due to non-co-operative attitude of the subject. This degraded quality of image can result in a significant number of spurious minutiae being created and genuine minutiae being ignored. A vital step in studying the statistics of fingerprint minutiae is to reliably extract the minutiae feature from fingerprint images. Thus it is important to employ image enhancement techniques prior to minutiae extraction to obtain a good number of reliable estimates of minutiae locations. The main objective of fingerprint image enhancement is to improve the ridge characteristics of the image, as these ridges carry the information of characteristics features required for minutiae extraction. Ideally, in a well-defined fingerprint image, the ridges and valleys should alternate and in a locally constant direction. This regularity facilitates the detection of ridges and consequently allows minutiae to be precisely extracted from the thinned ridges. Thus, the corruption or noise has to be reduced through image enhancement techniques to get enhanced definition of ridges against valleys in the fingerprint images.
Testing of Fingerprint Image Enhancement
System testing is a critical element of software quality assurance and represents the ultimate review of specification, design and coding. Software testing fundamentals define the overriding objectives for software testing. Testing is a process of executing a program with the intent of finding an error. A good test case is one that has a high probability of finding a yet undiscovered error. A successful test is one that uncovers an as yet undiscovered error.
Identification and Analysis of Characteristic Required by Women Entrepreneur
Abstract Entrepreneurs in the country play a vital role in the overall development of the country. This project basically focuses on the study of several characteristics required for women to become entrepreneurs. This project is mainly executed in many steps the first one involved selection criteria for the women entrepreneurs. Second one was personal visit to for knowing their personal details of an entrepreneur. The questionnaire we prepared covered four aspects analytical, communication, Team work and leadership. The third step involved getting filled a set of questionnaire by selected women entrepreneurs. Finally the output obtained from the questionnaire was taken as an input for entrepreneurial aptitude test software(EAT).The result obtained from the test we obtained the percentage of women to become an entrepreneur. Propose of this empirical study is intended to find out various motivating and de-motivating internal and external factors of women entrepreneurship. Majority of the educated woman entrepreneurs having qualities such as accepts challengers, ambitious, enthusiastic, hard-working, skillful, etc. Software in VB.NET is also developed to analyze the data and tabulate the results conclusion related to the entrepreneurial characteristics were drawn based on the analysis of result. Keywords: characteristic, entrepreneur, function, software, women entrepreneur
Edge Detection of Images: An Analysis Using B-S-P Technique
Abstract Edge detection of images is a very serious challenge to the researchers till date. Several techniques can be implemented to detect the edges of different images. But a single edge detection methodology is not enough to perform very well in each and every possible image context. In this paper, an innovative edge detection methodology is presented, that computes the edges of different images using the combination of Bergholm-Sobel-Prewitt edge detectors (B-S-P). Here the edge detection of images using B-S-P technique is compared with each Operator individually. Keywords: Edge detection, image context, Bergholm-Sobel-Prewitt edge detectors, B-S-P technique
A Survey on Edge Detection of Images Using MPL Approach
Abstract Edges of an image can be represented by implementing several edge detectors with different techniques. Edge detection is a fundamental and very crucial part in image processing. In this paper, an improved edge detection technique which computes edges of several images using the quantitative combination of Mathematical Morphology-Prewitt-LOG (MPL) edge detectors is presented. This methodology can be used as template for multi-scale edge detectors for a very wide range of images in the field of computer vision and image processing. In this paper, the proposed technique is compared with each edge detector separately. Keywords: Edge detection, image processing, computer vision, mathematical morphology-Prewitt-LOG (MPL) edge detectors, multi-scale edge detector
Research Methodology for the Development of Data Mining Driven Forecasting Software Tool for Quality Function Deployment
A well-thought and analysed research methodology is the prerequisite for the development of any flourishing software tool. It acts as centre of operations because entire research process is surrounded by it and keeps the researcher on right track. Selection of right methodology is crucial task, as research must process at right point of time and advance in right direction only. Quality Function Deployment and Data mining are itself very vast and complex processes. The development of proposed software tool requires the integration of both processes in order to generate the forecasts. Thus, a robust methodology needs to be planned and understood for achieving the designing goals. Thus, this paper focuses on the research methodology used for the development of data mining driven forecasting software tool for Quality Function Deployment. Understanding the research methodology of proposed software tool will provide researcher the helping hand for development of data mining driven forecasting software tool. Keywords: Quality function deployment (QFD), data mining, research methodology, forecasting, software tool
Research Methodology for the Development of Software Tool to Improve the Quality of Software Product using Fuzzy Quality Function Deployment
The correct way towards the success of the development of software tool is to follow the acceptable methodology. The software developed according to the correct methodology will never tend to be failed. An elegant research methodology can help in achieving the desired goals related to the development of software in a most efficient way. It acts as a nerve centre between the researcher and its research work. To develop the software product of good quality it is very essential that the process carried out by the researcher is according to the right methodology. For the development of proposed software tool there is strong need to develop the research methodology which will assist in improving the quality of software product. The methodology involves the use of Quality Function Deployment which is integrated with fuzzy in order to achieve more accurate result. This paper represents research methodology for the development of software tool to improve the quality of software product using fuzzy Quality Function Deployment. This will assist the researcher in developing appropriate software product. Keywords: Quality function deployment, software, FQFD, research methodology, researcher