International Journal of Computer Science & Programming languages
International Journal of Computer Science and Programming Languages (IJCSPL) Click here for complete Editorial Board International Journal of Computer Science and Programming Languages (IJCSPL) is a journal focused towards the rapid publication of fundamental research papers on all areas of programming languages and computer science. It's a biannual journal, started in 2015. Journal DOI No: 10.37628/IJCSPL Readership: Graduates, Postgraduates, Research Scholars, in Institutions, and IT Companies Indexing: The Journal is indexed in Google Scholar Focus and Scope Distributed systems Computer networks and network security Distributed systems Web services composition Cryptology Validation, verification, coding, testing, maintenance, metrics and renovation of software Design, implementation and evaluation of programming languages Programming environments Development tools, visualization and animation Management of the development process Human factors in software Operating systems, system administration and network management 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: IJCSPL Frequency: Two issues per year Editorial Board Instructions to Authors
Fault Detection Technique for SMGF and Appearance Faults in Reversible Circuits using Matrix Model
Energy dissipation is a severe issue of present-day technology. The current scenario demands for moving beyond the traditional ways of computing. In this contrast, reversible circuit offers a possible solution to this problem. For confirming the correct behavior of the reversible circuits, a proper testing technique is required to detect and also locate the faults. In this paper, we have concentrated only on generating the test set for detecting the single missing-gate fault (SMGF) and appearance fault. For this purpose, we have investigated the correlation between the two fault models, and based on that an automatic test pattern generation (ATPG) method have been proposed to extract the required test set which is capable of detecting both the faults. In this work, the process of test set generation is developed by the concept of a matrix model by applying some well-defined constraints. Finally, experimental results are provided to verify our claim. Keywords: Appearance fault, ATPG, k-CNOT based reversible circuits, matrix model, SMGF, test set Cite this Article: Mousmee Nath, Abdul Hannan Laskar, Subham Chhetry, Mousum Handique. Fault Detection Technique for SMGF and Appearance Faults in Reversible Circuits using Matrix Model. International Journal of Computer Science and Programming Language. 2020; 6(1): 13–24p.
Copyright (c) 2020 International Journal of Computer Science & Programming languages
Reduce Carbon Emissions using Cyber Security/Digitization
At the height of digitization, every online action has an impact on the environment. The concern over continuously rising global carbon emissions as a result of technological advancements is growing. The environment is harmed by the vast majority of human actions. This effect has mainly been associated with available carbon emissions. However, discoveries have increased people's awareness of digital CO2 emissions. The available CO2 emission rate as a result of general digitization principles is represented by these damaging emissions. Technological advances have contributed significantly to CO2 emissions. In this research report, the overall consequences of carbon emissions are covered. It also shows the CO2 emissions generated by the technology industry worldwide. According to the study, digital services have increased carbon emissions, which affect many different places. The analysis of the global digital carbon footprint, corrective measures, and the relationship between carbon emissions and digitalization are the main topics of the study.
Copyright (c) 2023 International Journal of Computer Science & Programming languages
Chrome Extension for Detection and Prevention of Phishing Websites and Related Attacks by Using Machine Learning and Deep Learning
Phishing is a type of cyber-attack where a fraudulent message is sent by an attacker in order to deceive an individual into revealing sensitive information. The fraudulent message is often designed to mimic a legitimate website or organization, and the attacker can observe the victim's activity on the site. According to the FBI's Internet Crime Complaint Centre, phishing incidents have been recorded at more than twice the rate of any other type of computer crime. In 2022, phishing attacks were the most common type of attack carried out by cybercriminals. The number of phishing attacks reached an alltime high in 2021, with 300,000 attacks recorded in December alone, representing a more than threefold increase from less than 2 years prior. Our aim is to create a chrome extension to detect the Phishing websites and alert the user using machine learning techniques whenever a user visits the website. Whenever a user opens a website on his browser, the extension will work in the background, if the website is detected as phishing website, the user will be alerted with an alert pop up box with an ‘OK’ button. Along with it, the owner of the original website will be informed via email. If the website is not detected as phishing website, then no action will be taken. The project aims to gather URLs from multiple sources, including UCI machine learning repository, Kaggle, Phish Tank, and Alexa URL. We have used various machine learning algorithms along with deep learning algorithms to train the model and it was evaluated on the basis accuracy and on the basis of evaluation function such as recall, F1score, precision. The train/test split rule for dataset were 80/20 respectively. The browser extension was written in JavaScript. The extension contains content.js file which extracts features of URL such as browser popup, use of frames, web traffic, etc. and then applied the algorithm to detect whether the website is legitimate or not.
A Comparative Study of the Performance of High-level Languages Specific to Java and Swift as Console Applications vs. an Effective User Interface Overhead
The proposed study addresses the performance differences in high-level programming languages which take up the frontlines of the Software Development Domain. The study includes an extensive review of the syntactical differences, language specific features, Virtual Machines that enable the complex capabilities of the languages behind the scenes are compared. Java uses the Java Virtual Machine or the JVM whereas Swift makes use of the LLVM or the Low-level Virtual Machine, the performances that the respective VMs facilitate are discussed in detail. Memory management distinction with reference to Garbage Collection in Java and Automatic Reference Counting referred to as ARC are also viewed in depth. The memory management section highlights the technological growth in the development sphere, from manual memory management debugging which is a tedious process to the provision of memory graphs to keep track of any possible memory leaks in an application. This is carried out through the implementation of a pharmacy application in Java, Swift as well as in Swift with User Interface. The study serves as an emphasis on the core technological aspects of development as opposed to language specificness as it is simply a form of expression of the same fundamental conceptions.
Navigating the Risks and Opportunities of AI: Strategies for Ensuring Positive Human Outcomes
In this research work, Artificial Intelligence (AI), dubbed by some as Industrial Revolution (IR) will change not only the way we do things and discuss its impact on human industrial, social, and economic transformation in the 21st century, and then propose a set of bio ethical principles for artificial intelligence. Major social changes were made during IR1.0, the IR of the 18th century, without any direct relationship complications. However, contemporary artificial intelligence has a significant impact on our daily activities and interactions with others. To meet this challenge, new principles of AI ethics must be considered and formulated to provide guidelines that AI technologies must adhere to in order for the world to benefit from the advancement of this new intelligence.
Predicting the Specialized Areas of Computer Science Students of Bachelor of Science Level Analyzing Academic Statements Using Machine-learning Approaches
Knowing the specialized fields of students is very much important in this challenging world for the betterment of their future careers. Especially the job and higher education fields of computer science students are going to be multi-dimensional. In this research, a new architecture is introduced for finding the specialized areas of computer science students by analyzing the whole academic statements. The academic courses are divided into ten specific areas depending on the job market. By getting the help of machine learning techniques, the proposed approach will predict the specialized area of any student. For implementing the whole procedure of prediction, TensorFlow, an open-source library developed by Google, is used. In total, 536 samples are used in this research, where 75% as training and 25% are testing data. Depending on the course dimension and divided areas category, different machine learning algorithms are used. From the used algorithms, Linear Regression provides the best result and the accuracy is almost 99%. Finally, the comparisons of the accuracy of the model with different used algorithms and existing models has been shown.
Edge Detection of Images: An Experiment Using P-L-S Methodology
Edges of an image can be represented by applying various edge detectors with different methodologies. Edge detection is a primary and very crucial part in image processing. In this paper, an innovative edge detection methodology which computes edges of several images using the quantitative combination of Prewitt-LOG-Sobel (P-L-S) edge detectors is presented. This methodology 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 technique is compared with each edge detector separately. Keywords: Edge detection, computer vision, image processing, Prewitt-LOG-Sobel edge detectors, multi-scale edge detector
Copyright (c) 2022 International Journal of Computer Science & Programming languages
Digital India and Digital Divide: An Analytical Study
There is a vast rich and poor divide in India. It is directly related to digital divide. Launching Digital India Prime Minister Modi spoke of elimination of digital divide. Can digital divide be eliminated without eliminating economic divide? This paper discusses this problem in the light of recently launched programme. Keywords: Digital divide, economic divide, technologies, internet, mobile applications
A Comparative Study and Survey on Edge Detection of Images Using SMP Approach
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 Sobel-Morphological-Prewitt (SMP) 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. Keywords: Edge detection, computer vision, image processing, Sobel-Morphological-Prewitt (SMP) edge detectors, multi-scale edge detector
An Effective Methodology for Edge Detection of Gray-Scale Images
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-Sobel-Prewitt (MSP) 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. Keywords: computer vision, edge detection, image processing, Morphological-Sobel-Prewitt (MSP) edge detectors, multi-scale edge detector
Suitability of Hidden Markov Model in Part-of-Speech Tagging for Indian Languages
Part-of-speech (POS) tagging is an important activity in Natural Language Processing (NLP) where each token is assigned with an appropriate symbol according to its lexical category. There are many applications of POS tagging in NLP; among them, two main applications are word class classification and word sense disambiguation. A number of approaches have been developed in POS tagging for different languages. However it is a challenging job to develop a universal tagger for all languages because of different grammatical rules available for different languages. Hidden Markov Model (HMM) is a statistical approaches commonly used for all languages. TNT is a popular example of POS tagger that used bi-gram and tri-gram HMM. According to HMM, a tagger tagged its tokens by estimating two kinds of probabilistic functions: observation probability and transition probability. Basically, this model estimated the probability of some hidden states based on previous known states. The category of a word could be predicted from its few previous words categories. This model is found suitable in word sense disambiguation and in information retrieval specifically for English language. Many researchers claimed up to 98% accuracy in their tagging. Unlike English, Indian languages are highly inflectional and have rich morphology. Due to their morphological richness, performance of HMM based tagger degraded. The second difficulty of Indian languages is that structurally they are free word order language. Because of these two significant problems in Indian languages, recent researcher tries to develop POS tagger applying multiple approaches. In this paper, we will discuss some pitfalls of HMM as a POS tagging approach considering few Indian languages including Hindi and try to develop alternative solution for developer. Our objective is to increase the accuracy level of probabilistic tagger specifically for Indian languages. Keywords: contextual information, HMM, observation probability, POST, transition probability
Big data is a wide term for information sets so gigantic or complex that customary information handling applications are deficient. Challenges include examination, catch, information curation, seek, sharing, storage, exchange, perception, questioning and data protection.
This paper talks over security issues for cloud computing & presents a layered framework for secure clouds and then focus on layers, i.e., the storage layer & the data layer. Cloud computing is a set of IT facilities that are as long as to a customer over a network on adhoc basis and with the ability to scale up or down their service requirements. Generally cloud computing services are distributed by a third party provider who owns the groundwork. Its advantages to mention but some include scalability, flexibility, resilience, efficiency & outsourcing noncore actions. This paper will converse secure merged query handing out with map Reduce & Hadoop. Security is one of the key issues which block the development of cloud. Even with the potential advantages achieved from the cloud computing, the organizations are unhurried in accepting it due to security issues and dares associated with it. The idea of handling over important data to another company is worrisome; such that the consumers need to be vigilant in understanding the risks of data breaches in this new environment. This paper introduces a comprehensive analysis of the cloud computing security issues and tasks focusing continuously on the cloud computing types and the service delivery types. This paper describes our approach to securing the cloud.
Multiple Sequence Alignment Algorithms for a Protein Structure for a Biological Data Using Dynamic Programming Method
Many algorithms use dynamic programming to align two sequences. In this paper a new algorithm is proposed to perform multiple Sequence alignment. This algorithm is developed by taking the inspiration of dynamic programming and is implemented on protein structures of any length. It uses particle swarm optimization (PSO) techniques to get the best alignment. The proposed approach tries to improve the sequence alignment obtained by Needleman Wunsch algorithm.
In Today’s world software companies rely on different-different languages for different clients. We need to know about these languages and among them which is more convenient for the clients so that people will learn for technical support.
Examination Management System in Web with PHP, Apache, MySQL, and Open Source
The process of gathering and interpreting facts, diagnosing problems and using the information to recommend improvements to the system is known as system analysis. It includes understanding how the existing system works. What the flow of information through the system look like. It consists of conducting studies emphasis is on gathering information and determining requirements, system analyst clarify the system life cycle into various activities.
Coding and Programming Used for Village Information System Management Through Web-Based Application
In past history rural areas didn’t went for good development in all the aspects, so now-a-days efforts were taken to develop village areas for the same. In this article I want to describe how coding and programming done for village information system through web based application.
Java is an important and mostly used language used in coding in IT industries so by this paper I would like to introduce some facts about Java for the users.
Big data are a wide term for information sets so gigantic or complex that customary information handling applications are deficient. Challenges include examination, catch, information curation, seek, sharing, storage, exchange, perception, questioning and data protection.
Priority-Based Test Case Generation for Multiobject
While performing regression testing, an appropriate choice for test case ordering allows the tester to early discover faults in source code. To this end, test case prioritization techniques can be used. Several existing test case prioritization techniques leave out the execution cost of test cases and exploit a single objective function (e.g., code or requirements coverage). In this paper, we present a multiobjective test case prioritization technique that determines the ordering of test cases that maximize the number of discovered faults that are both technical and business critical. In other words, our new technique aims at both early discovering faults and reducing the execution cost of test cases. To this end, we automatically recover links among software artifacts (i.e., requirements specifications, test cases, and source code) and apply a metric-based approach to automatically identify critical and fault-prone portions of software artifacts, thus becoming able to importance during test case prioritization. We experimentally evaluated our technique on 21 Java applications. The obtained results support our hypotheses on efficiency and effectiveness of our new technique and on the use of automatic artifacts analysis and weighting in test case prioritization.
This work depicts an on-line voting system by taking advantage of the centralized database with a web interface. The main concept of this project is to allow people to cast their vote by online. It saves the desirable time, it reduces the manual work, and information available at time and it provide security for the data. The election commission will maintain this website using face Recognition. User needs to enter respective Aadhar id to cast the vote. User’s face can be captured and compared with Aadhar database. The captured image and id number are recognized and user is allowed to cast the vote. If it is failed then user is not allowed to vote. After the successful completion of voting process, number of votes to the particular candidate and the party will be counted by admin.
Burstiness of Virtual Machine Resource Reservation in Cloud Using Firefly Optimization
In computing clouds, burstiness of a virtual machine (VM) workload widely exists in real applications, where spikes usually occur a periodically with low frequency and short duration. This could be effectively handled through dynamically scaling up/down in a virtualization-based computing cloud; however, to minimize energy consumption, VMs are often highly consolidated with the minimum number of physical machines (PMs) used. In this case, to meet the dynamic runtime resource demands of VMs in a PM, some VMs have to be migrated to some other PMs, which may cause potential performance degradation. In this paper, we investigate the burstiness aware server consolidation problem from the perspective of resource reservation.
Secure Authorized Deduplication with Data Mining in Cloud
Cloud computing offers a new mode of service provision by reorganizing various resources over the internet. In traditional encryption while providing data confidentiality is incompatible with data deduplication. The different users to encrypt their data with their own keys. Thus, identical data copies of different users will lead to different cipher text making deduplication impossible. Convergent encryption method has been proposed to enforce data confidentiality while making deduplication feasible. It encrypt/decrypt a data copy with a convergent key which is attained by computing the cryptographic hash value of the content of the data copy. After key generation and data encryption users retain the keys and send the cipher text to the storage. Since the encryption operation is deterministic and is derived from the data content the identical data copies will generate the same convergent key and hence the same cipher text. Data mining is the process of extracting the information from the data bases. Data deduplication is one of important data mining techniques for eliminating duplicate copies of repeating data by it compares the data in cloud storage to reduce the amount of storage space and save bandwidth. To better protect data security this project makes the first attempt to formally address the problem of authorized data deduplication
Dynamically Cluster Driven of the Person Navigation for Exploring the Search Space
Similarly, the SQL-based group-by operator (SGB) extends the semantics of standard SQL groups by grouping data with similar but not necessarily equal values. Although existing similarity-based grouping operators effectively implement these approximate semantics, they focus on one-dimensional attributes and handle multidimensional properties independently. However, related attributes, such as in spatial data, are processed independently, and therefore, groups in multidimensional space cannot be properly detected. To solve this problem, we introduced two new SGB operators for multidimensional data. The first operator is the community (or all distance) SGB, where all tuples in a group are within a certain distance from each other. The second operator is the distance to any SGB, where the tuple belongs to the group if the tuple is within some distance of any other tuple in the group. Tuples can meet the membership criteria of multiple groups, we introduce three different semantics.
Software Requirements and Analysis for Automobile Workshop
Software requirement specification (SRS) is the starting point of the software development activity. Little importance was given to this phase in the early days of software development. The emphasis was first on coding and then shifted to design. As systems grew more complex, it became evident that the goals of the entire system cannot be easily comprehended. Hence the need for the requirement analysis phase arose. Now, for large software systems, requirements analysis is perhaps the most difficult activity and also the most error prone.
A Cloud-Based Smart Remote Controlling and Monitoring of Electrical Appliance Using Android Phone
Now-a-days efficient energy management has become very crucial. In Today’s era the Smartphone based on android platform plays great role in the technical field, which also provides various applications. Today, most mobile phones are a 'smart phone', which offers more advanced capabilities in connectivity issues than regular cell phones. Smart phone usually support one or more short range wireless technologies such as Bluetooth and infrared, making it possible to transfer data via these wireless connections. The use of Bluetooth technology in a smart phone today is not just for the transfer of data and files only. In recent years, smart home automation is one of the applications of Bluetooth technology. we offer electrical appliances Automation system based on Bluetooth technology, especially in Home automation system. There are many problem like Wastage of electricity after completion of work in computer lab or in home. For avoiding this type of problem we make this application which Automatically turn off of electrical appliances(tube, bulb)in computer lab or after completion of work by using GSM and Bluetooth module. In this paper we are proposing low cost Microcontroller (89s51) based design for efficient energy saving by controlling the power flow for light and fan loads
The coding of fingerprint image enhancement is elaborated in this paper. The code is developed in MATLAB for Rotational filter. In MATLAB we have used various functions to reduce the noise from the image and to improve quality of the image.
System Hierarchy, Database and Code Implementation for Industries
For any industry it is necessary to design a hierarchy for overall implementation of database and code. This paper will help people about the same and to know how industries implement the same.
In automobile industries recently computer application were implementing, under which System which we and employees were used need to be design for better and easy handling. This paper is for users to understand how system can be design and helps for the same.
Sentimental Analysis Using Embedding Techniques
The purpose of this research is to assist the stock traders. Stock prices have been demonstrated to fluctuate based on how people perceive about a company. News reports are an excellent predictor of this. The software helps to automate the process by pulling news from Google and performing sentiment analysis on it. Traders can then use this data to choose whether to trade or hold their stocks. This project's purpose is to compare various sentiment analysis approaches. Sentiment analysis is carried out through using deep learning techniques. We want to assist day traders and short stock sellers who must be on edge in order to decide whether to buy or sell a stock depending on its performance, but cannot keep an eye on it for the entire duration. News about the company whose stock they own is one of the signs that helps them decide. However, if a trader receives negative news about a company in the morning and sees it in the evening, the stock value would have plunged by that time. So, every 20 min, we will run a python script that will scrape news websites for any news stories about the firm the trader is interested in, analyze the sentiment of those articles, and decide whether to buy more shares, sell them, or do nothing. Our suggested method will distinguish between favorable and negative evaluations, allowing users to determine whether to buy, hold, or sell stocks depending on the results.
Recognition of Bilingual Translator in American Sign Language
In this study, we are reviewing the designing of desktop application that captures and instantly translates a person’s signing motions in American Sign Language using a computer’s webcam. The implementation of a real-time sign language translator is a critical step in improving communication between the deaf community and the broader public. Based on a convolutional neural network, we provide an American Sign Language (ASL) fingerspelling translator. The creation of a real-time sign language interpreter is a critical step toward enhancing communication between the deaf and the general public. We show how to create and use a convolutional neural network-based fingerspelling translator for American Sign Language (ASL). Semantically relevant word pairs were graded more quickly when the ASL translation form was similar, whereas semantically irrelevant word pairs were judged more slowly. Creating educational tools, information technology, and communication in order to increase learning and facilitate communication between teachers and students. Unaffected persons have a tough time connecting with deaf people due to a lack of sign language development, learning measures, and interpreters.
Leukemia develops when the DNA of a single cell in your bone marrow alters (mutates), causing it to be unable to develop and function normally. Leukemia cells frequently act similarly to aberrant white blood cells. Hematologists employ microscopic analysis of human blood, which necessitates the use of technologies such as microscopic color imaging, segmentation, classification, and clustering to identify individuals with leukemia. The microscopic images are visually analyzed by hematologists, which is a time-consuming and laborious approach. The automatic image processing system is desperately needed and can help overcome visual inspection limits. The proposed system that we have suggested will use microscopic images to diagnose leukemia. The capacity to detect leukemia early and efficiently aids in the development of its appropriate treatment. Statistical measures such as mean and standard deviation are used to identify white blood cells from other blood components such as erythrocytes and platelets. For leukemia diagnostic prediction, geometrical characteristics of the white blood cell nucleus, such as area and perimeter, are investigated. The suggested approach has been applied to a large number of photos with promising results for images of different quality. ALL (Acute lymphoblastic leukemia) is a cancer that affects the lymphoid progenitor cells present in the bone marrow, blood, and extracellular locations. Even though 80% of ALL cases are in children, it is a severe disease in adults. In the United States, ALL is projected to affect 1.6 persons out of every 100,000 people. Approximately 1400 persons died from ALL in 2016, with an estimated 6590 new cases as per American Cancer Society. ALL has a bimodal incidence, with its first peak occurring in the childhood and the second peak occurring at 50 years old. While dose-intensification techniques have improved outcomes for children, the elderly continue to have a bad prognosis.
Chatbots are becoming an appealing tool for those seeking medical assistance because of their ongoing availability. It was found that chatbots are mostly used by people who cannot approach healthcare professionals physically as it gives relevant and accurate information. As a result, we suggest creating a chatbot with the name “Covidbot” to reduce the chances of falsehood or wrong information that could spread during the epidemic. Covidbot gives consumers access to a variety of COVID-19 related information, including guidance, responses to frequently asked questions, and symptom checking. To make the chatbot unique we have added a feature called “TRACCINE DEX” in which we can also check the COVID-19 vaccination details of the students from our department. We have trained the bot in a way that, if the user enters the name of any specific student, the bot responds with his/her vaccination details (and personal details). Furthermore, we study how the installation of our bot solves some of the issues and limitations of healthcare and COVID-19 chatbots. Finally, our project deals with giving an accurate and precise information about covid-19 and vaccination details of students and maintaining a proper record.
Sentiment Analysis on IMDb Reviews Using NLP
Sentiment analysis technologies enable organizations to analyze consumer sentiments in online feedback about products, brands, and services. It enables us to determine the mood of the audience. Using the text analysis methods, sentiment analysis measures and classifies the emotions (whether it is positive, negative, and neutral) represented in the text data. IMDb contains information about movies, TV shows, web series, video games, and other media, such as cast, crew, storyline summaries, ratings, and fan and critic reviews. Sentiment Analysis (SA) uses Natural Language Processing (NLP) to provide a common machine learning (ML) solution to this problem. In the proposed study, we performed sentiment analysis on the IMDb movie reviews dataset from Kaggle’s Bag of Words meets Bag of Popcorn to demonstrate how substantial insights can be extracted from a massive quantity of textual data obtained from the internet. The Random Forest (RF) model, a standard machine learning method, is used to obtain these insights. In addition, the Python modules Beautiful Soup and Count Vectorizer are used to translate a given text into a vector depending on the frequency (count) of each word in the full text.
Overview of the Emerging Technology: Cloud Cryptograph
Distributed computing gives clients a virtual registering framework on which you can store information and run applications. In any case, distributed computing thinks of new security challenges as cloud administrators are relied upon to control customer information without being completely trusted. From encouraging remote access to information to the digitization of the instruction framework, cloud innovation has contacted our lives from numerous points of view more than we understand. Today, pretty much every application we use is fueled by distributed computing. On the off chance that you need to take business on the web, you have to get your hands on this progressive innovation at the earliest opportunity. In addition, Cryptography is system of making sure about data and correspondences through utilization of codes so just those individual for whom the data is planned can get it and procedure it. In this way, forestalling unapproved access to data. The prefix "grave" signifies "covered up" and postfix graphy signifies "composing". The systems used to protect data in cryptography are built on numerical ideas and a lot of rule-based thinking known as computations to shift over messages in ways that make them difficult to translate. These computations are used to verify cryptographic key age, computerized marking, secure information security, web browsing on the web, and secure private exchanges, such as charge card and check card exchanges.
Exploring the Potential of the Kotlin Programming Language for Scientific Computing with the KotlinLab Environment
KotlinLab is an easy to use MATLAB-like environment for the Java Virtual Machine (JVM). It implements scripting based on the Kotlin programming language. This paper shows that Kotlin Lab can significantly accelerate and simplify the development of complex scientific computer software in the JVM. The work compares Java based approaches with Kotlin ones, and illustrates the significant advantages of the enhanced flexibility of the Kotlin language. We illustrate that one of the more significant drawbacks of Java is its lack of operator overloading. Also, the nominal approach to functional programming of Java is not as flexible and convenient as the structural approach of Kotlin is. The paper presents the architecture of the KotlinLab environment, and the way that it exploits effectively the Kotlin JSR223 scripting implementation. The main concern of the KotlinLab enviroment is to exploit the potential of the Kotlin language in order to provide a rich and easy to use scientific programming environment. In this way the paper tries to highlight some important and advanced characteristics of the Kotlin language that provide important benefits to the programming experience. In particular, the Kotlin language is especially effective in building DSLs (Domain Specific Languages). At this domain, the paper illustrates the straightforward way to implement scientific operators.
A Generic Approach to Measuring the Ease of use of Modeling Languages
Modeling languages are artificially defined languages that are used to create models, i.e. abstract descriptions. They are used in particular in the context of software development to model sections of the real world. The development of new and the modification of existing modeling languages for the description of technical, organizational or business contexts does not decrease in spite of the existing diversity. On the one hand, requirements in the constantly changing environment of business and administration should be met again and again, on the other hand, one reason is to align existing modeling languages even more specifically to the addressees of the models. Determining the userfriendliness in terms of the usability of modeling languages has not been the aim of empirical evaluation studies so far. Most usability studies have evaluated applications, websites and technical products. The focus of research work on the usability of the modeling languages traditionally lies in the area of software-related and less of user-related requirements. The aim of this article is to create a framework for evaluating the usability of modeling languages. It is a contribution that elaborates the complex interrelationships of a usability study for modeling languages and creates a basis for subsequent empirical studies.
Enhancing the Performance of Hate Speech Classification Using Dimensionality Reduction Approach
In recent times most of the people are using online platforms for sharing their emotions. These emotions can be classified as a positive comment or as a negative comment. But these comments play an important role when comments are made in the form of reviews for any particular purpose. Today all the ecommerce websites, election parties and many other online business forums are predicting these reviews for evaluating the performance of their product or work. Many times people used to post hate speech on social media, so it is very much need that we must predict the hate speech for further improvement. Traditional machine learning algorithms are not able to accurately predict the hate speech. In this work we have applied dimensionality reduction approach for performing the classification of hate speech on the basis of which classifiers has improved the performance. The feature selection approached is done through Information Gain, Term frequency–Inverse Document frequency and Logistic Regression Cross Validation and we have achieved the F1 score of 0.81, 0.90 and 0.87 for the gradient boosting, random forest, and extreme gradient boosting classifiers respectively.
Copyright (c) 2021 International Journal of Computer Science & Programming languages
Review Study of Cloud Computing for Next Research Directions
Cloud computing (CC) is an advance technology in present time. This system is a available in remote location on internet. CC indicates four models like public, private, community and hybrid and provide five main services like infrastructure, platform, software, network and Identity based services. Three component of cloud computing like client, data center and database server used for application development. In this paper, briefly explain the introduction, components, models and services of cloud computing using different research papers for next research work.
Improving E-Banking Security via Biometric ATMS
Various banks of India have started using biometric ATM machines that are ATMS, as it has proven to be a better way of reducing the use of cards and is proving to be a channel for various banks to enlarge their reach to the rural and illiterate people. Union Bank of India started this by installing their first such ATM popularly known as “KISAN ATM” located at Siyasanga Branch at Tamil Nadu. Dena Bank took it forward by launching its biometric ATMS in Gujarat. Andhra bank has recently launched mobile accessed biometric ATMs, for both Hyderabad and Secunderabad. Further Corporation Bank has also launched “taking” biometric ATMs. The special characteristic of this ATM is that it can interact with farmers in their own native language.
Electricity consumption is the actual demand for energy produced by the current supply of electricity. In 2012, the gross electricity usage was 20,900 TWh, and it was 21,372 TWh in 2017. Electricity usage has been increasing rapidly, despite severe supply constraints caused by delays in the implementation of new capacity additions, decreased capacity utilization due to maintenance problems, the availability of coal and oil, and draught conditions (1979-80), which have simultaneously reduced the availability of hydropower and increased agricultural demand for elevator irrigation. Annual per capita electricity consumption serves as an important indicator of the production of electric power in a region. Generally speaking, as the industrialization process progresses quickly and declines rapidly when industrialization is completed or near completion, electricity demand increases faster. The same can be said for per capita annual electricity use. Due to this increase in demand of electricity it is very important that we use the electricity that we have very efficiently and economically. By the virtue of this project we have tried to optimize the way we consume electricity. This is achieved by designing an automated process which controls the intensity of light, temperature etc. of a room by counting the number of people inside the room. We prepared the model of a room which has electrical appliances like lights and fans just as any room. We have integrated a circuit which can control the switching of all the appliances in the room. With the help of IR sensors which are fit at the entrance and exit of the Room, we can count the number of people that are inside the Room. According to a pre specified amount of people to one set of appliances, we can determine the number of appliances we need to switch off/on. Hence, we can optimize the amount of electricity we use, by minimizing the usage.
Research Paper on Speech Emotion Recognition
Communication is the key to clearly expressing your thoughts and ideas. Among all forms of communication, speech is the most preferred and powerful form of communication in human beings. The goal is to provide efficient and natural interaction between humans and computers. Enable computers to understand emotional states expressed by human subjects, so that personalized responses can be provided accordingly. Most studies in the literature focus on recognizing emotions from short, isolated sentences, which makes their practical application difficult. The main objective of being is to improve the man-machine interface. It can also be used to monitor a person's psychophysiological state on lie detectors. To realize a SER system, based on different classifiers and different feature extraction methods, it is developed. By discovering a way to remove random silence from the audio clip, we present a multi-faceted comparison between practical neural network approaches in the recognition of speech emotions. The aim of this study is to provide a study in the field of discrete recognition of speech emotions.
Application of Machine Learning and Blockchain Technology in Fighting against Pandemic
The COVID-19 epidemic has had a harmful effect on virtually every field of human life, as well as on diverse business markets and global regions. The flow of human activities has been halted for several months and is now being intentionally redefined in order to comply with guidelines and advice to deter the spread of the Coronavirus. Unlike other pandemics that the world has experienced in the past, the technological developments of the new century are a blessing that will play an important role in protecting humankind. In this context, new technologies such as Block-chain Technology (B.T) and Machine Learning (M.L) have arisen as possible alternatives in the battle against the coronavirus outbreak. In the one hand, Block-chain Technology will fight epidemic by allowing early identification of outbreaks, guarding patient privacy and guaranteeing a stable medical supply chain through epidemic surveillance. Machine Learning, on the other hand, provides clever ways to recognize signs initiated by coronavirus for treatment and aid in the drugs development.
Voice Assistant for Hospitality Management
One of the goals of Artificial Intelligence is the realization of natural dialogue between humans and machines. Lately, the discourse frameworks, otherwise called intelligent conversational frameworks are the quickest developing region in AI. Numerous organizations have utilized the discourse frameworks innovation to set up different sorts of Virtual Personal Assistants (VPAs) in light of their applications and regions, for example, Amazon’s Alexa, Microsoft’s Cortana, Google Assistant and Facebook’s M. However, in this proposal we are going to create a voice controlled virtual waiter. In the wake of the virus, keeping the new rules and regulations concerning the social distancing, we trying to find out new ways for the hospitality sector to recover from the lockdown. COVID-19 has affected every sector with the hospitality sector being the major one, hence it will be the last to recover. Once the situation normalizes it will take about 9-10 months at least for the industry to recuperate. Hence this proposed system, will work as a virtual waiter, so that we can place our orders, getting recommendations, and managing the bills. It will work just like a normal waiter, although in a more secure and healthy way.
Analysis on Lane Changing Prediction and Speed Control of an Autonomous Vehicle using Machine Learning
ABSTRACT Lane changing and speed control has always been a major concern regarding autonomous driving. In this paper we have discussed about the work done in lane changing & different approaches used in autonomous vehicle. DRL and DQN have shown very promising results. Also, somewhere KELM also beats the best rule-based machine learning algorithms. After taking a close look at each approach several methodologies have arrived for preparation and testing. In this paper we have compared the different models based on machine learning which includes using a Dataset from the cloud, using stimulators for designing & implementation and using real time external information using sensors. Also we have discussed about the challenges & future scope in autonomous driving. Keywords: Autonomous driving, lane change prediction, machine learning, speed control, autonomous vehicles.
Development of Football Result Prediction System
ABSTRACT The aim of this study was to design and implement an expert system for football results prediction. Three objectives guided the study. The method adopted in this study was the rapid application development (RAD) model, which was used to design and implement the logics and procedures of the system. The system was implemented with the PHP. The implementation platform is especially suited for server-side web development. The predicting system was structured on the following features; the login page, the head to head page, the predicting page and the result page. These components were developed and tested with field parameters. The developed system is a football result prediction system and as such will be used by football gamblers and football fans in their accurate prediction of football matches. This system can be used by users with basic skills in computer operations. It is recommended that the system should be used in line with the steps outlined in the documentation with related data, specified hardware and software. Keywords: Development, Football, Results, Prediction, System
Cyborgs: A Gateway to Enhanced Abilities
A cyborg short form "cybernetic organism”. Cyborgs were developed based on cybernetics that are half human beings and half robot beings. The scientific revolution in this area has proved to be an advantage to humans. Internal or externally organ damaged people and disabled people can use any robotic aid for proper living. Indeed due to medical reason, there are currently millions of human beings across the world equipped with prosthetic devices to restore lost functions or to enhance current senses to “beyond normal” levels of performance. This direction will continue to accelerate as the body becomes transformed into an information processing technology, which basically will require one’s sense of identity and what it means to be human. This paper reviews on the future direction of cyborgs and the meaning and conclusion of becoming more cyborg and less human in an age of rapid advances in the design and use of computing technologies.
Evolution of Immersive Technology: Journey of Computational Reality
ABSTRACT In this modern era, Technology is influencing the human life in every field that is making every single person able to harness actively the latest technical trend. It encourages the brisk pace development of creation of thrived form of actuality mixed with digitalized or computerized delusory world. Decades ago, Even the imagination of having a printed magazine and a mobile phone were just in thoughts. But today with the help of immersive technology development, we are having the imagination and tangibility connected with each other with a fine bridge created between the virtuality and reality. VR (Virtual Reality) and AR (Augmented Reality) are also the adequate appropriate technologies which have given an amazing definition to the human’s thoughts or the fantasies that were existing just in imagination. AR and VR have given a portrait model for the human’s illusory world with fantastic feature provided to live in that imaginary world too. This enhanced technology enables users to interact with virtual and real time applications and to bring out the natural experiences or feel to user. With the exuberance of practices of Ivan Sutherland in 1968 in the development of “a window of virtual world”, had served the biggest concept in the creation of VR and AR. This concept has created a major impact in the field of technology. From 3D games to the treatment of psychological disorders, from entertainment industry to education, VR has left no stone unturned. Snapchat, Google Lens and Google glass are the fine examples of the development of AR in a positive number. The games like Pokemon Go, Jurassic World Alive, Zombies Run, Harry Potter and many other have the feature with AR to facilitate the user to play with the characters of the popular games in their surroundings. Also, the Google lens and Google glass device were unveiled by Google. Google glass is a device with a pair of AR glasses that helps in different kind of experiences. Google lens uses AR for better navigation and searching the destination with a description provided for every place. Google maps, Gmail and Google+ and other several applications are working with AR. Proliferation of affordable hardware and software have made AR and VR more adored and feasible in many domains. In addition, the merging of AR and VR has led to MR (Mixed Reality), where a user can have both VR and AR experiences together. Even today the world is developing the combination of AR, VR and MR to be leading to XR (Extended Reality) for betterment of real time experiences. Now-a-days the business organizations are using these methods to boost the education of employees, as it is on peak, the investors might be very engaged towards immersive technology development. AR and VR are rooted in the technology deeply as they are having their fascinating global attraction and attention of users, developers and investors. Globally, AR and VR market in 2019 was estimated to be $16.8 Billion and by 2023 forecast, it will be almost at $34 Billion. Mainly Gaming and Entertainment holds 40.5 % of VR market share. Inclusively AR and VR both technologies are affecting Education, Military, Healthcare, Fashion industry, Entertainment, Heritage, Media, Sport, Business, etc. Today, almost each field is fragmented by the fragrance of the growth of immersive technology. This research is mainly focused to highlight the entire journey of growth of immersive technology. Here, the evolution of AR and VR in every field is salient point for the research with a futuristic approach and scope is determined in positive manner with the applications and impacts on human’s life. Keywords: Immersive Technology, Virtual Reality, Augmented Reality, Mixed Reality, Extended, Reality
A Peer Review of different techniques of Sentiment analysis and Methodology
ABSTRACT This paper provides an overview of various approaches that are mainly used for sentiment analysis. It focused on the description of the latest technology and tools introduced for this purpose. There are various algorithms thatare used for opinion mining. Sentiment analysis is used to extract opinionated information from various sources by applying different techniques such as Natural language processing technique (NLP), Computational Linguistics and Text Analysis. In this paper, we are going to discuss the different levels of sentiment analysis and different approaches for sentiment classification. In this paper, we discussed the different levels of sentiment and modern approach to analyze this. Keywords: Sentiment analysis, Machine learning, opinion extraction, sentiment analysis tools, feature level analysis
Context Aware Physical Activity Recognition Using Social Objects
Social Internet of Things (SIoT) is defined as social network of intelligent and smarter objects. The social objects namely smartphones, tablets, etc., have become part of our lives and have made life simpler and smarter. Smart objects on the other side have also made mankind lazy resulting in a sedentary lifestyle. Research in human physical activity recognition is not new and has attracted many new avenues in the recent past. In this paper, we have proposed a simple application that classifies human physical activities like sitting, standing, walking, jogging, climbing upstairs and downstairs using smartphones without the need of an external server or a personal computer. For the first time in literature, a smartphone is able to identify and classify the physical activities of the owner and notify the percentage of activeness and passiveness at regular time intervals. The triaxial accelerometer in the smartphone was used for data collection with the phone being carried in the subject’s trouser pocket/held near the hip region. Initially five different machine learning algorithms namely KStar, J48, Naïve Bayes, SMO, and Multilayer perception were used for classification using WEKA. Amongst them the J48 algorithm was chosen as the candidate for classification in the smartphone. The Weka.jar file was added to the smartphone’s library for this purpose. Periodically, the smartphone was able to notify the activities done by the owner along with the timestamp. Keywords: Machine learning, physical activity recognition, smartphone, social objects, triaxial accelerometer Cite this Article: A. Meena Kowshalya, M. Lincy, R. Suvarna. Context Aware Physical Activity Recognition Using Social Objects. International Journal of Computer Science and Programming Language. 2020; 6(1): 41–50p.
Extraction of Lip Contour and Geometric Lip Features for Audio-Visual Phoneme Recognizer
This paper presents a lip contour extraction method to extract geometric lip features for audio-visual phoneme recognizer (AVPR). In the first stage of the lip contour extraction technique, Viola-Jones algorithm is applied to each frame of the video to detect the face portion. We segmented the image into rectangular blocks and considered a fixed number of rows and columns to get the region which contains mouth portion. Region of interest (ROI) is calculated based on colour ratio thresholding and largest connected region detection. The elliptic shape guided fuzzy clustering is applied to the combination of green and weighted colour planes for lip segmentation. However, the boundary of the segmented lip is not smooth. Therefore, we propose a refinement method for smoothing the boundary of the segmented lip to get an accurate lip contour. The experimental results performed on GRID audio-visual database work very efficiently for lip contour extraction. The performance of the female speakers (segmented error (SE) = 7.3%, overlap (OL) = 92.7%) is better than male speakers (SE = 10.6%, OL = 87.8%). Each phoneme is modelled by using 10-states Hidden markov model (HMM) with 32 Gaussian mixtures. The phonemes are represented by symbols of international phonetic alphabet. This HMM based audio-visual phoneme recognizer can recognize 31 phonemes and the non speech event; silence (sil) and short pause (sp). By experimental analysis, we have shown the effectiveness of the geometrical lip features in phoneme recognition task under noisy condition. Keywords: Elliptic shape guided fuzzy clustering, phoneme recognizer, polynomial fitting, region of interest Cite this Article: Salam Nandakishor, Debadatta Pati. Extraction of Lip Contour and Geometric Lip Features for Audio-Visual Phoneme Recognizer. International Journal of Computer Science and Programming Language. 2020; 6(1): 25–33p.
Target Selection of Customers for Communication Service Providers using K-Means Clustering and Back propagation Artificial Neural Network
This paper proposes a design for development of computational model for intelligent selection of telecom services meant for telecom customers. Computational model makes use of data mining and soft computing techniques in order to train the system for providing the services to the customers according to their past usage pattern. Historical call usage data of various customers was used to categorize them into five clusters referring to five different telecom service schemes using K-means clustering algorithm. Consequently, soft computing techniques such as neural network were implemented to train the system. Database from a specific city and a commonly used telecom service provider was taken. Keywords: Clustering, data mining, neural network, k-means, soft computing, telecommunication services Cite this Article: Md Iqbal. Target Selection of Customers for Communication Service Providers using K-Means Clustering and Back propagation Artificial Neural Network. International Journal of Computer Science and Programming Language. 2020; 6(1): 34–40p.
A Breakthrough in the Early Diagnosis of Alzheimer’s Disease
Alzheimer’s disease (AD) is the most common form of senile dementia affecting the growing ageing population around the world. Clinically, it was proved that there is a progressive decline in cognition, memory, and social functioning due to deposition of different types of protein in the brain. The patients with Alzheimer’s have poor intuition and frequently impute early symptoms of forgetfulness to normal ageing. The conventional methods are inadequate to make an exact diagnosis with specificity and sensitivity of the disease. Therefore a reliable, validated and economical tool should be developed for making the disease diagnosis. In this paper, we have made a breakthrough for diagnosing the disease at its earlier stage. At first, a psychometric assessment of the patients is made with the help of cognitive examination (CE) tool that is developed using C sharp. Recently, under certain investigations, neurological degradation occurred in the retina of the eye as well as the brain. After interviewing the patients with the help of CE tool, they were sent to optical coherence tomography (OCT) scanning for obtaining the retinal nerve fiber loss (RNFL) of AD patients. The scanned OCT images were analysed with the help of the proposed tool developed using Marr-Morlet wavelet networks (MMWNs). For obtaining a double verification of the diagnosis process, the patients were again sent to magnetic resonance imaging (MRI) scanning. The obtained MRI images were again analysed with MMWNs. Thus, predicting the disease through double verification can provide a better system for diagnosing the disease at its earlier stage. Keywords: Alzheimer’s, CE tool, early diagnosis, OCT, MMWNs, MRI, RNFL Cite this Article: Sandeep C.S., Sukesh Kumar A., K. Mahadevan, P. Manoj. A Breakthrough in the Early Diagnosis of Alzheimer’s Disease. International Journal of Computer Science and Programming Language. 2020; 6(1): 1–12p.
Wi-Fi Enabled Security System with Camera
In the world of Internet of Things, when we have all the technologies to revolutionize our life, it is a great idea to develop a system which can be controlled and monitored from anywhere. There are many types of good security systems and cameras out there for home security, but they are much expensive so we build a low-cost simple Arduino-based intruder alert system, which not only alert us through a voice module but also saves the picture of intruder to the cloud when it detects any. A PIR sensor is used to detect the presence of any intruder and an Arduino camera module is used to capture the images when the presence is detected. Whenever anyone or an intruder comes in the range of PIR sensor, PIR sensor triggers the Arduino camera. Arduino triggers the Arduino camera to click the picture of intruder and save it. After this, an email is sent which contains the message notifying the intrusion and the image is send to the webpage created containing the date and time of the intrusion using a Wi-Fi module. Keywords: IoT, camera, Arduino Uno, Wi-Fi module, alert system Cite this Article: Nandu Vijayan, Sheethal Joy, Vysakh S., Vrinda S. Vijay, Anu Philip Mathew. Wi-Fi enabled Security System with Camera. International Journal of Computer Science and Programming Language. 2019; 5(2): 26–32p.
AADHAAR-based E-voting using raspberry Pi
An Aadhaar-based electronic voting system is to avoid multiple votes and provides more secure voting system in India. In this arrangement, a booth will be created. Here, the first process to create a webpage, all the information’s of every voters and candidates uploaded in the created webpage. The second process is take place at time of voting. The fingerprint is scanned by using fingerprint scanner. If the given fingerprint is matched with information in the webpage, the name of the voter will be displayed in the LCD display. At the same time, IVR provides voice message. Then the ballot list will display according to the address of voter. After submitting the vote the Aadhaar will block from server. IVR allows voters to interact with electronic voting machine via a keypad. Keywords: fingerprint scanner, IVR, electronic voting, LCD display, keypad Cite this Article: Alan Roy, Sandra Satheesan, Sruthimol C.S., Steni Mariam Stephen, Joby John. AADHAAR-based E-voting using raspberry Pi. International Journal of Computer Science and Programming Language. 2019; 5(2): 1–7p.
Today with the rapid advancement in technology, electronics devices contain not only million-gate chips, but number of such chips also increased on a single platform termed as the system-on-chip (SoC). So the integration requires some attention because of the constraints like area, power, speed, etc. Processing cores on a single chip keep increasing with the current rate of advancements. Communication networks in such scenario are becoming highly important. Specialized buses ease the on-chip interconnection networks. In the SoC development, design reusability are used for interconnecting components with the buses. Design engineer standardizes the bus for future reuse around their particular modules. This eases the integration and reusability of module into new design, based around the same standard bus. In this paper, we give an insight of popular on-chip bus-based communication networks such as AMBA (advanced microcontroller bus architecture), core connect, wishbone, etc. The buses are characterized in respect to network topology, arbitration method, bus-width, and data transfers types. Keywords: On-chip interconnection network, on-chip bus, on-chip communication protocol, SoC, AMBA (advanced microcontroller bus architecture) Cite this Article: Rajiv Kumar Singh, Rajni Gupta. Communication on Chip. International Journal of Computer Science and Programming Language. 2019; 5(2): 8–12p.
LPG Gas Leakage Detection and Home Safety
LPG gas leakage detection and home safety detects the LPG gas leakage. If the LPG gas level crosses a certain value, then it sends SMS to the user using the GSM electronic equipment. Also, the LPG detector system activates the buzzer to alert the person near to the system and at constant time relay is turned on. We have connected LPG device on to the analog input pins of the Arduino Uno board. Due to some negligence, there may be LPG gas outflow which might cause live accidents. GSM-based mostly Arduino LPG detector will avoid such things by alert SMS to the owner and by turning on buzzer/siren at constant time. Keywords: Arduino, MQ5 sensor, buzzer, LCD, relay, GSM module Cite this Article: Fadhil Nizar, Prince Abraham, Reegun Joseph Gonsalvas, Sarath Jayagopal, Aswathi Gopan. LPG Gas Leakage Detection and Home Safety. International Journal of Computer Science and Programming Language. 2019; 5(2): 18–26p.
Comparative Study of Interchip Communication Protocols
The goal of this paper is to carry out a comparative analysis of the design and specification of these interchip communication protocols. This paper includes ancient job of other scientists and provides a knowledge of the benefits and disadvantages of certain protocols. Keywords: intellectual property core, serial communication, serial peripheral interface, SoC, UART Cite this Article: Vimal Kumar Verma, Pooja Saxena. Comparative study of interchip communication protocols. International Journal of Computer Science and Programming Language. 2019; 5(2): 13–17p.
Smart Waste Management Using WSN and IoT
Abstract - Speedy increase in population, has LED to the improper waste management in cities leading to enhanced pests and spreading of diseases. Nowadays, the Garbage Collecting Vehicle (GCV) collects the waste twice or thrice in a week. So, the problem is over flowing of wastages on the roads. Hence, to beat this limitation, during this paper a theme on sensible waste management mistreatment Wireless detector Networks (WSN) and IoT (Internet of Things) is projected. The garbage bins are deployed with sensors and are networked along mistreatment WSN. The sensors deployed within the garbage bins collect the information for each determined interval. Once the brink is reached, it raises asking to the ground-controlled approach (Garbage Collector Agent). This agent collects the requests of all the stuffed vehicles and communicate mistreatment IoT framework. The experimental simulation is done in proteus tool. A hardware model is developed for the projected framework. Analysis of the projected theme provides higher leads to waste management. Keywords- Wireless detector Networks, sensible Waste Management, Garbage Collection. Cite this Article: Nayan Chotalia. Smart Waste Management Using WSN and IoT. International Journal of Computer Science and Programming Language. 2019;5(1) 31–37p.
How ICT helps in E-Waste Management System
Abstract- The generation and acquisition of electronic equipment is growing fast, becoming one of the most complex waste systems for the modern world to face. The e-waste environmental that stakeholders in both developed and developing countries should deal with a proper e-waste management system. The purpose of this paper is to analyze and manage the flow in an e-waste management system. Technology can provide visibility on the electronic waste. Considering the social, environmental and health impact of e-waste and sanitation, e-waste management system was launched. The paper presents how ICT helps to manage the e-waste management system. Keywords: e-waste management; ICT Cite this Article: Shubham Y. Pawaskar, Maharshi J. Patil. How ICT Helps in E-Waste Management System. International Journal of Computer Science and Programming Language. 2019;5(1) 17–23p.
GREEN COMPUTING: An Approach to Green IT
Abstract: Green computing can also be termed as Go-Green practice that assists lessening the carbon foot-print. Green computing facilitates us to a secure, safe and sound environment for the mankind. With rising energy cost and growing environmental concerns, GREEN COMPUTING is receiving more and more attention. . Software and system architectures (in terms of concurrency patterns) play a crucial role in both computing and telecommunication systems, and they have been analyzed for performance, reliability, maintainability, and security. Yet, little work on analysis based on the amount of energy that the CPU/processor will consume has been reported. Since most communication systems have to run 24/7 (e.g., most server farms, servers in a cloud computing infrastructure), the energy consumption of a system based on a specific software architecture is of great importance. Green Computing practices entail crafting, mechanizing, employing and disposing of computers proficiently with negligible impact on the atmosphere. Keywords: Green Computing; green initiatives; e-waste; Virtualization: sleep and hibernate component. Cite this Article: Mayank Kothari. Green Computing: An Approach to Green IT. International Journal of Computer Science and Programming Language. 2019;5(1) 24–30p.
A Study of Understanding among Metropolitan Students about Deep Web
ABSTRACT Beyond the content of Internet that can be accessed easily lies another layer – much larger layer– of material that cannot be accessed through a traditional online search. As experts have said, “searching the Internet today can be compared to throwing a net across the surface of the ocean”. While a great many things may be caught in the net, there is still a wealth of information that is deep, and therefore, missed. This deep region of the Internet, or the Deep Web, is characterized by the unknown – unknown size, space, content, and users. The furthest ends of the Deep Web, known as the Dark Web, contain content that has been intentionally concealed. The main objective of this paper is to explore the Deep Web, its content, and challenges and risk associated with it. Keywords: anonymity, Deep Web, Dark Web, illegal activities, surface web Cite this Article: Abhishek Shrivastav, Alok L. Singh. A Study of Understanding among Metropolitan Students about Deep Web International Journal of Computer Science and Programming Language. 2019;5(1) 1–8p.
Impetus by Information Technology for Sustainable Agriwaste Management through Biogas Reactors
ABSTRACT Development of sustainable solutions to the problems associated with agriwaste management is the need of the hour. These wastes have immense potential to be converted into fuels that act as renewable sources of energy. Conversion of agricultural residues to biogas is an ideal remedy. However, the complex nature of the microbial populations carrying out this conversion leads to gaps in understanding the biochemical process. This limits our potential to improve the performance and efficiency of the process. In this study, we have reviewed the applications of Information Technology and Bioinformatics in unveiling the interplay of bacteria in a biogas reactor, which can fill the gaps. Keywords: agriwaste management, biogas, metagenomics, methanogens Cite this Article: Aparna Deshmukh, Shweta Sharma. Impetus by Information Technology for Sustainable Agriwaste Management Through Biogas Reactors. International Journal of Computer Science and Programming Language. 2019;5(1) 9–14p.
Text Region Detection Techniques for Natural Scene Images-A Review
Abstract The natural scene images tend to contain lot of information that can guide the persons navigating on the roads. Therefore understanding the text present in these images has become an area of active research. But the task of text region detection is a challenging task when text is to be detected from images that are captured from natural scenes. These images have varying font size, orientation, scripts, the text may be faded or blurred, the image may suffer from intensity in homogeneity and the text region may be occluded or may be missing. All these factors make the text region detection task difficult but interesting. Over the last two decades several methods for text region detection from natural scene images have been proposed, but till date no benchmark has been established that can accurately do this detection. The MSER based text region detection approach has been widely used, but it also fails if the text regions are blurred. In the presented work the various state of the art text region detection techniques proposed so far have been compared. The strengths and weaknesses of the techniques has been analyzed and based upon them the possible future directions has been proposed, so as to formulate a robust text region detection technique that overcomes the drawbacks of the existing techniques. Keywords: Text Region Detection, Natural Scene Images, Survey
An Extensive Survey for Examining Pigmented Skin Lesions and Detection of Melanoma Skin Cancer through Computer Vision
Abstract Melanoma Skin cancer being the most life-threatening cancer has a rapid increase in its incidence rates in the last two decades. It is curable if it gets detected at an earlier stage. Thus making investigation of pigmented skin lesions for diagnosing malignant melanoma is essential for saving lives. This paper presents a comprehensive survey of the ongoing strategies for investigation of pigmented skin sores and diagnosis of melanoma through computer vision. The techniques already proposed to accomplish these errands are identified and reviewed. Additionally a common approach followed for skin lesion analysis is also presented briefly. And on the basis of the literature reviewed, we tend to conclude that the door is still open in this field and in future research can be carried out to optimize and enhance the accuracy of the segmentation process as well as for improving the classification outcomes. Keywords- Melanoma, Pigmented Skin Lesion, Dermoscopy, Segmentation, Classification.
A Review of Railway Time Table Scheduler using Genetic Algorithm
Abstract: Scheduling the train is a major issue in front railways. Planning implies designation of assets that falls in NP hard class of issue. Booking the trains with the goal that they land at right time is a major errand for the representatives of railways. It is vital to plan the train accurately as it is an extremely delicate issue related with customers. Scheduling takes many months and subsequent to thinking about a few criticisms, it is fixed. We propose a strategy that will make the booking assignment relatively less demanding by utilizing a Genetic Algorithm. We can make a program that utilizes hereditary calculation to do the booking undertaking. Keywords: Genetic Algorithm, Crossover, Chromosome, Time table.
Off-grid rural electrification in Karnataka state of India: Technology options, modeling method
Abstract- Energy deficiency is one of the key enigmas impacting the livelihood of millions of poverty stricken people throughout the world. It is quite evident that electrification of rural areas can improve the standard of education, health conditions, living and empowering the youth of the nearby population. Census of India reveals that about 19706 of numbers of villages are still unelectrified in the state. Electrification of these villages/hamlets of remote hills using renewable energy resources in off-grid mode is a feasible option compared to uneconomical grid extension. The mean annual daily solar radiation of 4.5-7 kWh/m2/day through the year,solar radiation with 300 sunny days in a year, enormous forest foliage, crop residue, and animal waste and mean annual wind speed of 4.5-5.4m/s in some places of the state. The present study comprises the utilization of single technology based system such as small hydro, biomass, biogas, solar and small wind turbines etc. and also aggregated technology, depending on the availability of the resources in the present locality. A methodological framework has been established to avail the demand and resources assessment of the area. Keywords: Single technology based system, Integrated Renewable energy system, hybrid energy system and small hydro power system.
A Review on Cloud Computing and its Functionality
Abstract: The Cloud computing develops as another processing worldview which intends to give dependable, tweaked and QoS ensured dynamic registering conditions for end-clients. In this paper, we ponder the Cloud computing worldview from different angles, for example, definitions, unmistakable highlights, and empowering advancements. This paper brings a presentation survey on the Cloud computing and give the cutting edge of Cloud computing advancements. Keywords: Cloud Computing, Grid Computing, Cyberinfrastructure, Distributed Computing
Harmonic Reduction In Distribution System Using Hybrid Filter
This paper presents harmonic reduction in distribution system using hybrid filter to improve power quality, now a days we are using non liner loads in distribution system, these non liner loads are creating the power quality problems, reduction of voltage are increase the voltage ,to improve the power quality we different types of methods are their in that main is the active and passive filter in this project proposing the hybrid filter both active and passive filter compare with conventional methods by using this hybrid filter it reduce the harmonics and improve the power quality, in active power filter it has the voltage source inverter (VSI), and storage as an active and then passive filter, the result of the proposed filter improve the power quality in distribution system, the converter has been simulated in MATLAB/Simulink platform.
Power Quality Improvement by Using Facts Devices with a Fuzzy Logic Controlling Technique
This paper is proposed to improve the power quality in distribution system using the unified power quality compensator (UPQC).The UPQC contains shunt and series converter with DC link. The shunt converter removes current harmonics initiating from non-linear load side and series Converter mitigates voltage sag or swell initiating from supply side. The DC link control strategy based on fuzzy logic controller by proposing UPQC which has the superior capability of mitigating the effects of voltage sag/swell and suppressing the load current harmonics under the distorted supply conditions.
Reactive power control using STATCOM in distribution system
This paper present an analysis of compensation algorithms applied to a STATCOM which uses three single-phase Half bridge converters sharing the same DC-bus voltage. The STATCOM is applied to three-phase four wire system, performing harmonic current suppression, reactive power compensation and power factor improvement. The synchronous reference frame based controller was used to generate the sinusoidal compensating current references. In addition, load unbalances compensation is also carried out.
Social Networks: Controlling Privacy of Photograph Sharing
Photograph sharing is an appealing element which promotes Online Social Networks (OSNs). Tragically, it might announce clients' safety on the off chance that they are allowed to post, remark, and label a photograph freely. We endeavor to address this issue and concentrate the situation when a client shares a photograph containing people other than himself/herself (named co-photograph for short). To avert conceivable protection spillage of a photograph, we plan a component to empower every person in a photograph know about the posting action and take an interest in the basic leadership on the photograph posting. For this reason, we require a productive facial acknowledgment (FR) framework that can perceive everybody in the photograph. Be that as it may, all the more requesting protection setting may restrain the quantity of the photographs freely accessible to prepare the FR framework. To manage this quandary, our component endeavors to use clients' private photographs to outline a customized FR framework particularly prepared to separate conceivable photograph co-proprietors without releasing their protection. We likewise build up a dispersed consensus-based technique to decrease the computational many-sided quality and secure the private preparing set. We demonstrate that our framework is better than other conceivable methodologies as far as acknowledgment proportion and effectiveness. Our component is objectified as a proof of idea of Android application on Facebook. The controller law distribution is begun by the special join process, in which the likelihood of a client. An interfacing with a client B is relative to the quantity of B's current associations. demonstrate the previews of the contact system and fan arrange in YA, separately. We see a few hubs don't have either fans or contacts, while a couple of hubs have a substantial degree.
A Survey Paper on APT (Advanced Persistent Threat) in Cloud Security
A survey research on an Advanced Persistent Threat (APT) aimed attack on a specific target that compromise with their system and receives information about that target. The target can comprise of a person, an organization or a business. The threats of the corresponding targets are usually the governments and military organizations. The word threat doesn’t represent any malware involved, because an APT comprises of several different attacks. APTs are referred as cyberattacks which have been well sophisticated executed and well- resourced adversaries that target specific companies and governments, usually involving a long term campaign targeting with different steps. To a noteworthy extent, the academic community usually ignores these threats and hence objective approach to the APT issue is lacking. In this paper, we present the results of various studies done on APT that characterize, distinguish and attack model and analyze techniques that have been seen in APT attacks. We also compute some non- conventional counter measures highlighting APT in the directions for future research.
Banking Sector involves a lot of transactions for their day to day operation and they have now realized that their main disquietude is how to detect fraud as early as possible. Due to fulsome advancement in technology, it is imperative for bank to save its money from fraud. The primary motive of this paper is to represent technologies that can be redounding to detect credit card fraud. These technologies will help to diagnose the credit card fraud and give the acquiescent result. The use of these techniques will help to distinguish the credit card transactions generally into two types as legitimate and fraudulent transactions. These techniques are generally based on the Supervised and Unsupervised Learning. The approach on which we are working is based on Unsupervised, in which we train our network so that it is able to detect fraudulent transactions.
Clustering deals with finding a structure in a collection of unlabeled data. Data stream mining is the process of extracting knowledge structures from continuous, rapid data records. As big data are referring to terabytes of data and clustering algorithms are come with high computational costs, the question is how to cope with this problem and how to deploy clustering techniques to big data and get the results in a reasonable time. Clustering helps to visually analyze the data and also assists in decision making. In this paper, we have discussed some big data mining clustering techniques and also provide a comparison among them.
Data Governance of e-Governance Applications : A study on e-Counselling System of Odisha
Day-to-day, the number of e-Governance applications are increasing. Now, the success rate of e-Governance applications has crossed 30% with the past record of success from 15% to 20%. With this increased number of good governance applications, there are numerous challenges during implementation of e-Governance projects. One of the major challenges is data management. It is experienced that, due to the failure at any stages of implementation, the complete project is failing. Particularly due to erroneous data the end result is not successful and many issues are cropped out. The objective of this paper is to analyse and suggest a data governance approach to make the e-Governance applications successful. Further, it emphasizes on the data mining of error free data for providing transparent course of action for the benefit of the end users. In fact, the objective of any e-Governance project is to provide better and efficient services to the common men at their door step. Here, one of the e-Governance applications, that is e-Counselling project, implemented by Government of Odisha since 2010 is taken up for the study. Consequently, it gives an approach for all other e-Governance applications for better and effective Data Governance.
Data Mining for Biological and Environmental Problems
: In the past(Earlier), most of the researchers used data mining techniques in many area. A lot of amounts of data have been collected from various scientific domains such as Geo sciences, Astronomy, Meteorology, Geology and Biological sciences. Data mining techniques and tools used by researchers and scientist in biological and environmental problems also. In biological science data mining used in sequences alignment is based on the fact that all living organisms are related by evolution.ntal science data mining concept used in predicting data such as earthquakes and landslide etc. This Research paper highlights on the wide survey of Protein sequences, (DNA, RNA) sequences, cancer prediction, Relational and semantic data mining for biomedical research area. Health care data, multiagent framework for bio data mining, predicting earthquakes, landslide and spatial data in distributed data mining algorithms and tools.
5Th-generation mobile networks (5G) stand for the next major phase of mobile telecommunications standards beyond the current 4G/IMT-Advanced standards. 5G has speeds further what the present 4G can provide. From generation 1 to 2.5G and from 3 to 5G this world of telecommunication has seen a number of advancement along with improved performance with every passing day. This fast change in mobile computing gives us change our day to day life that is way we work, interact, learn, etc. This paper also highlights on all preceding generations of mobile communication along with fifth generation technology. The development of 5G technologies is a cornerstone f o r realizing breakthroughs in the transformation of ICT network infrastructure. Ultra- broadband and intelligent-pipe network features that achieve near- instantaneous, “zero distance” connectivity between people and connected machines – no matter where they are – are just the first step. In this paper also we discuss architecture, waveform concept, requirements, etc.