- Electronics
Author Archives: vikaspatanker
Computer Science
UncategorizedLatest Research Topic for computer science are:
Data Mining include analysis of large amount of unorganized data in form of text files, image, tabular data, etc. Here further classification of this is done by working in specific area of research such as
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Web Mining:
Here website related information like page content optimization can be done by using its features of web log, web content, web structure.
Web Page Prediction: This comes under web mining where web log is use for understanding the user behavior on the website, in this step page content was also used. Some algorithm like Ant colony, markov modal, etc are use for the same.
Web Page Ranking: In this work website various pages are analyzed for ranking the pages of the site by using methods of google rank, linear rank, page rank etc.
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Text Mining:
Here documents are either arrange, summarized, fetch, etc by using pattern or Term feature.
Content Retrieval / Document Retrieval / Information Retrieval: In this work text files are either arrange in specific order OR fetch list of files based on the query of user.
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Temporal Mining:
Here analysis done on the basis of time stamp where various information are summarized as per there happening and there causes.
Event Activity Happening: In this work events are proposed with there probability where chance of data going was done.
Nature Prediction: Large amount of information gather from the satellite images for predicting the glacier movements, galaxy analysis.
Dataset Available for Research in Computer Science are
- Adult Dataset (code 101): for pattern recognition, privacy preserving mining, Description: It contain 32560 number of session with 11 fields where attribute contain both number and textual data. To Get Data / Download Data Send Request
- Information Retrieval Dataset (code 102): Its an collection of images which contain 1000 images of ten category like people, elephant, bus, etc. where each subcategory have 100 images. This dataset is use for image retrieval, fetching, clustering, etc. To Get Data / Download Data Send Request
- Text File Classification (code 103): In this dataset small set of text files are collect where 1000 text file contain article on hockey different worldcup debate. This dataset is used for text mining such as classification of text files, fetching of relevant document as per user query, conclusion / abstract creation, disputant identification, etc. To Get Data / Download Data Send Request
- Tax Relation Dataset (code 104): In this dataset tax payer relations are present with company details, transaction between them, individual relations, here dataset is used in generating association rules, Tax evasion identification, Transaction identification for business, etc. To Get Data / Download Data Send Request
- Brain Tumor Segmentation Dataset (code 105): In this dataset 50 images with there ground truth were present, so dataset has 100 images. Image have skull, brain and tumor section. Hence scholar can segment image into three class. To Get Data / Download Data Send Request
- Jaffe Images (code 106): In order to study the expression of the face this set of dataset is very helpful where seven emotion are expressed by 11 Japaneses girls. Here this dataset used for image fragmentation, expression recognition, face recognition, etc. To Get Data / Download Data Send Request
- Chess Dataset (code 107): This dataset is collection of 76 items where 3196 number of transactions are present, its an set of numeric id of the frequent items purchase by the store. This is used for Association Rule Mining, Privacy Preserving, FP-Tree, etc. To Get Data / Download Data Send Request
- Image Watermarking (code 108): in this dataset standard set of images are present both in color and gray format, with two size 256×256 and 512×512 name of those images are mandrilla, lena, etc. This is used for image watermarking, cryptography, encryption, decryption, etc. To Get Data / Download Data Send Request
- Character Recognition (code 109): Its an collection of images for identifying the character present in the hand expression used by dumb people. This is used in image processing for shape identification. To Get Data / Download Data Send Request
- Object Detection (code 110): In this dataset few set of video are present where people perform various action such as running, walking, jumping, etc. To Get Data / Download Data Send Request
- Web Log (code 111): In this dataset web log of famous nasa site was present with there complete path of various random surfer, it contain 10000 sessions in the dataset in text file. To Get Data / Download Data Send Request
- Twitter Sentiment (code 112): Here one can get sentiment of the tweets done by the user on different emotions. This can be used in sentiment analysis, classification, emotion identification, etc. To Get Data / Download Data Send Request
- Geosptial Tagging (code 113): Here as per the geographical co-ordination various set of image are tag by specifying its longitude and latitude value. This is used in geographical location based learning, etc. To Get Data / Download Data Send Request
- SAR Image (Code 114): In this dataset set of SAR image is present with different time span for the study of ice / snow precipitation, melting rate, etc. Here researcher can use this for segmentation, rate identification, etc. To Get Data / Download Data Send Request
- Wisconsin Breast Cancer (code 1014): Its an numeric value dataset used for identifying the cluster of data which tends towards breast cancer. This dataset is implement for pattern recognition, binary classification testing techniques, etc. To Get Data / Download Data Send Request
IJSRET Volume 3 Issue 6, November-2017
Archive Volume 3 Issue 6An Approach for Trusted Computing of Load Balancing in Cloud Environment
Authors: Manoj Kumar Selkare, Vimal Shukla
Abstract: Cloud computing is a novel approach in order to use the resource of computing where these resources may be hardware or software. This facility is delivered as a service in the communication network. This facility known as cloud, which occurred from the use of a service as a cloud, which is an abstraction for the complex infrastructure system containing diagrams. Services of cloud computing involve trusted remote user data, and computer software. This paper proposed to an approach to efficient load balancing in cloud computing
Low Power Three Input XOR Gate For Arithmetic And Logical Operation
Authors:Ms. Poojashree Sahu, Mr. Ashish Raghuwanshi
Abstract: With advancement of microelectronics technology scaling, the main objective of design i.e. low power consumption can be easily acquired. For any digital logic design the power consumption depends on; Supply voltage, number of transistors incorporated in circuit and scaling ratios of the same. As CMOS technology supports inversion logic designs; NAND & NOR structures are useful for converting any logic equation into physical level design that comprises of PMOS and NMOS transistors. In similar way, logic can be implemented in other styles as well, with the difference in number of transistors required. The conventional CMOS design for three input XOR logic can be possible with 10 or more than 10 transistors, with the methodology discussed in this paper, the same design for three inputs XOR logic can be made possible with 16 transistors. The proposed methodology consists of transmission gate and systematic cell design methodology (SCDM). This design consumes 45% (35%) less power dissipation than that of conventional LPHS-FA and SCDM based XO10 XOR logic design with CMOS technology. Since the design for XOR logic, is useful for variety of applications such as Data encryption, Arithmetic circuits, Binary to Gray encoding etc. the XOR logic has been selected for design. The design explained in this paper is simulated with 130nm technology.
Low Read Power Delay Product Based Differential Eight Transistor SRAM cell
Authors: Ms. Jaya Sahu,Mr. Ashish Raghuwanshi
Abstract: SRAM is designed to provide an temporary storage for Central Processing Unit and replace Dynamic systems that require very low power consumption. Low power SRAM design is critical aspect since it takes a large fraction of total power and die area in high performance processors. This paper include the work on eight transistor SRAM cell that of smaller read power delay product due to cascading of pull offers 28% (74%) smaller read ‘0’ (‘1’) than exiting 7T. The SRAM cell read and cycle is characterized at 45nm technology using SPICE EDA tool.
A Robust Classification Algorithm for Multiple Type of Dataset
Authors:M.Tech. Scholar Afshan Idrees, Prof. Avinash Sharma
Abstract: With the increase in different internet services number of users are also increasing. Although while taking service user may be on risk for sharing data. So this work focus on increasing the security of the user data while taking classification service. Here algorithm provide robustness by encrypting the data and send to server, while server classify the data in encrypted form. One more security issue is that instead of transferring whole encrypted data, features are extract from the data first then encrypt and send to server for classification. Here proposed work successfully classify all type of user data in form of text, image, numeric.
An Unsupervised TLBO Based Drought Prediction By Utilizing Various Features
Authors:M.Tech. Scholar Shikha Ranjan Patel, Prof. Priyanka Verma
Abstract: Agricultural vulnerability is generally referred to as the degree to which agricultural systems are likely to experience harm due to a stress. In this work, an existing analytical method to quantify vulnerability was adopted to assess the magnitude as well as the spatial pattern of agricultural vulnerability to varying drought conditions. Based on the standardized precipitation index (SPI) was used as a measure of drought severity. A number of features including normalized difference vegetation index (NDVI), vegetation condition index (VCI), and SPI will be use for classification. Here proposed modal use Teacher Learning Based Optimization genetic approach for classify the different location present in geospatial dataset. By use of this TLBO approach prior knowledge is not required. Experiment results shows that proposed work is better as compare to previous work.
Optimizing Material Management through Advanced System Integration, Control Bus, and Scalable Architecture
Authors:RamaKrishna Manchana
Abstract:This paper presents an advanced approach to material management by leveraging modern system integration techniques and scalable microservices architecture. The proposed solution addresses the limitations of traditional monolithic systems by introducing microservices, control bus mechanisms, and event-driven designs that enhance operational efficiency and scalability. By utilizing advanced integration patterns, including synchronous and asynchronous services, the system improves real-time data processing and decision-making capabilities. This document outlines the technical architecture, key components, integration designs, and implementation strategies that underpin a robust and adaptable material management system, demonstrating significant improvements in scalability, performance, and responsiveness.
DOI: 10.61137/ijsret.vol.3.issue6.200
Optimizing Healthcare Data Warehouses for Future Scalability: Big Data and Cloud Strategies
Authors:Srinivasa Chakravarthy Seethala
Abstract:Healthcare organizations generate vast amounts of data, driven by regulatory compliance, patient care needs, and advances in medical technology. Legacy data warehouses, while central to healthcare data management, often struggle to accommodate escalating data volumes, new data types, and real-time processing demands. This paper presents strategic insights into leveraging Big Data and cloud computing to modernize healthcare data warehouses for future scalability. We examine technical approaches, review cloud and Big Data integration techniques, and propose a roadmap for healthcare data scalability, addressing concerns of security, compliance, and data interoperability.
IJSRET Volume 3 Issue 5, September-2017
Volume 3 Issue 5MANET, Evolutionary Algorithm, Email System, encryption scheme, journal entries, international journal of current research
Secret Sharing Schemes over MANET to Avoid Cheater Participation [102-109]
Author: Nisha Bharti, Hansa Acharya
Web URL Classification and Malicious Activities: A Review [110-115]
Author: Anshika Bansal
Malicious Web URL Classification using Evolutionary Algorithm [116-199]
Author: Anshika Bansal
Attack over Email System: Review [200-206]
Author: Anuradha Kumari, Nitin Agrawal, Umesh Lilhore
Encryption Scheme for Mobile Ad Hoc Networks: A Survey [207-209]
Author: Neha Dwivedi, Dr. Rajesh Shukla
Evolutionary Algorithm Based Optimized Encryption Scheme for Mobile Ad-Hoc Network [210-216]
Author: Neha Dwivedi, Dr. Rajesh Shukla
MANET, Evolutionary Algorithm, Email System, encryption scheme, journal entries, international journal of current research
MANET, Evolutionary Algorithm, Email System, encryption scheme, journal entries, international journal of current research
IJSRET Volume 3 Issue 4, July-2017
UncategorizedEfficient and Scalable Multiple Class Classification: A Review[76-79]
Author: Tarun Yadav
An Approach to Detect Malicious URL through Selective Classification[80-84]
Author: Ghanshyam Sen, Himanshu Yadav, Anurag Jain
Use of LC-Filters to Protect Equipment from Electromagnetic Pulse: Is it Real Necessity or “Bisiness as Usual”?[85-89]
Author: Vladimir Gurevich
Pilot Tone based Winner Filtering Approach for Carrier Channel Offset Estimation in OFDM Systems[90-95]
Author: Shweta Sharma, Minal Saxena
Node Replacement and Alternate Path based Energy Efficient Routing Protocol for MANET[96-101]
Author: Nehalastami, Hansa Acharya
IJSRET Volume 3 Issue 3, May-2017
UncategorizedAuthor: Neelam Kushwaha, Dharmendra Kumar Singh
Encrypted and Unencrypted Computation for Abstract Machine [59-62]
Author: Thripthi.P.Balakrishnan, Mr. S.Vijayanand, Dr. T. Senthil Prakash
Software Defined Visibility using REST API [63-66]
Author: Sindhu T, Shilpa Biradar
Battery Power Aware LAR Protocol for Mobile Ad-Hoc Network [67-69]
Author: Tarun Yadav
LAR Protocol over Mobile Ad-Hoc Network: Survey [70-75]
Author: Jasmeen Akhter, Akhilesh Shukla
Resilient Hybrid Middleware Frameworks: Automating Tomcat, JBoss, And WebSphere Governance Across Unix/Linux Enterprise Infrastructures
Authors: Sambasiva Rao Madamanchi
Abstract: This article examines the orchestration of Tomcat, JBoss, and WebSphere across hybrid Unix/Linux infrastructures, emphasizing the role of automation in creating resilient middleware frameworks. It explores the challenges of heterogeneous environments, including fragmentation, manual administration, compliance demands, and security risks. The discussion highlights how governance can be embedded into middleware provisioning, patching, and monitoring through tools such as Puppet, Chef, Ansible, Nagios, Zabbix, and Tripwire. Case studies from finance, telecommunications, healthcare, and government demonstrate how automated middleware governance improves resilience, compliance, and efficiency in mission-critical operations. The article also addresses challenges such as configuration drift, cultural resistance, and scalability while offering best practices for mitigation. Looking ahead, it identifies future directions including AI-driven predictive monitoring, cloud-native middleware orchestration, continuous compliance, and sustainability integra This article examines the transformation of enterprise governance from a compliance-centric model to a cognition-driven framework enabled by artificial intelligence. It highlights the limitations of traditional governance approaches, which focus on static audits and regulatory adherence, and explores how AI can enhance oversight by providing real-time anomaly detection, predictive compliance, and dynamic policy enforcement. Linux and Solaris, long recognized for their robust security and auditing capabilities, are positioned as ideal platforms for building AI-augmented governance systems that integrate intelligence, automation, and transparency. The discussion presents an architectural blueprint that layers AI engines and automation workflows over existing governance features, ensuring adaptability across hybrid IT environments. Challenges such as AI bias, ethical considerations, and data privacy are addressed alongside practical applications in finance, healthcare, telecommunications, and the public sector. Beyond technical benefits, the article demonstrates the strategic value of cognitive governance in reducing compliance costs, enhancing resilience, and fostering innovation.
DOI: http://doi.org/10.5281/zenodo.16925705
From Compliance To Cognition: Reimagining Enterprise Governance With AI-Augmented Linux And Solaris Frameworks
Authors: Sambasiva Rao Madamanchi
Abstract: This article examines the orchestration of Tomcat, JBoss, and WebSphere across hybrid Unix/Linux infrastructures, emphasizing the role of automation in creating resilient middleware frameworks. It explores the challenges of heterogeneous environments, including fragmentation, manual administration, compliance demands, and security risks. The discussion highlights how governance can be embedded into middleware provisioning, patching, and monitoring through tools such as Puppet, Chef, Ansible, Nagios, Zabbix, and Tripwire. Case studies from finance, telecommunications, healthcare, and government demonstrate how automated middleware governance improves resilience, compliance, and efficiency in mission-critical operations. The article also addresses challenges such as configuration drift, cultural resistance, and scalability while offering best practices for mitigation. Looking ahead, it identifies future directions including AI-driven predictive monitoring, cloud-native middleware orchestration, continuous compliance, and sustainability integra This article examines the transformation of enterprise governance from a compliance-centric model to a cognition-driven framework enabled by artificial intelligence. It highlights the limitations of traditional governance approaches, which focus on static audits and regulatory adherence, and explores how AI can enhance oversight by providing real-time anomaly detection, predictive compliance, and dynamic policy enforcement. Linux and Solaris, long recognized for their robust security and auditing capabilities, are positioned as ideal platforms for building AI-augmented governance systems that integrate intelligence, automation, and transparency. The discussion presents an architectural blueprint that layers AI engines and automation workflows over existing governance features, ensuring adaptability across hybrid IT environments. Challenges such as AI bias, ethical considerations, and data privacy are addressed alongside practical applications in finance, healthcare, telecommunications, and the public sector. Beyond technical benefits, the article demonstrates the strategic value of cognitive governance in reducing compliance costs, enhancing resilience, and fostering innovation.
DOI: http://doi.org/10.5281/zenodo.16925705
IJSRET Volume 3 Issue 2, March-2017
UncategorizedComparative Study on Pilot Tone based Approach for Channel Offset Estimation in OFDM Systems [25-28]
Author: Raghvendra Sharma, Saurabh Pandey, Anubhav Sharma
Community Detection on Social Media: A Review [29-33]
Author: Sweta Rai, Shubha Chaturvedi, Chetan Agarwal
Survey on Energy-Efficient Wireless Sensor Networks[34-38]
Author: Krishna Kant Sharma, Prof. Shivendra Dubey, Prof. Mukesh Dixit
Efficient and Scalable Multiple Class Classification using Bee Colony based Probabilistic Approach[39-44]
Author: Tarun Yadav
Real-Time Transferring of Optimized Levels with Carbon and Nitrogen Gases[45-49]
Author: K. Susitra, K. Vijayalakshmi, P.N Jeipratha
Enhancing IoT Biometrics Systems Using Aspect-Oriented Programming and Java Frameworks
Author: Vinayak Ashok Bharadi
IJSRET Volume 3 Issue 1, January-2017
UncategorizedAn Assessment of Location Aided Routing Protocol over MANET [1-5]
Author: Ankit Navgeet Joshi, Shivendra Dubey, Mukesh Dixit
Carrier Frequency Offset Estimation in OFDM Systems: Review [6-9]
Author: Padmaja Nagle, Prof. Nitin Lonbale
DFT Based Pilot tone Approach for Carrier Frequency Offset Estimation in OFDM Systems [10-15]
Author: Padmaja Nagle, Prof. Nitin Lonbale
Cloud Allocation Strategies for Load Balancing: Review [16-20]
Author: Shalini Bairagi, Prof. Vipin Verma
An Assessment of Handle Noise in Digitization of Historical Document [21-24]
Author: Anand Singh Rajput, Saurabh Pandey, Anubhav Sharma
Enhancing IoT Security and Performance Using Aspect- Oriented Programming in Java Applications
Author: Rajesh S. Bansode
Increasing Students’ Interest in Mathematics: A Teaching Quality That Connects Mathematics to Real-Life Problems
Authors:-Abhijit Sadashiv Patil
Abstract-Students’ enthusiasm in mathematics is largely influenced by their math professors’ capacity to relate the subject to real-world issues. In order to increase students’ interest in mathematics, the current study aims to determine what aspects they would want to see their math teachers enhance. Using a random sample technique, the study chose ten (10) high schools and 1,263 students from different subject areas to answer a structured questionnaire about factors that influence students’ interest in mathematics. The study examined the impact of teachers’ capacity to relate mathematics to real-world issues on students’ interest in the subject using principal component analysis and multiple linear regression analysis. According to the study, 57.4% of students’ interest in mathematics is predicted by teachers’ capacity to relate mathematics to real-world problems, which may be divided into two main components (p<0.001). The components utilized to connect mathematics to real-world problems were evaluated and their relative importance index was calculated. According to the study, when math teachers set aside quality time for pupils to do class exercises, they would be more engaged in the subject. The study also discovered that students' interest in mathematics is largely influenced by the teacher's capacity to connect mathematics to other topic areas. According to the study's findings, teachers' capacity to relate mathematics to real-world issues is crucial to the growth of students' interest in the subject.
IJSRET Volume 2 Issue 6, November-2016
UncategorizedDetection and Classification of One Conductor Open Faults in Parallel Transmission Line using Artificial Neural Network [139-146]
Author: A.M. Abdel-Aziz, B. M. Hasaneen, A. A. Dawood
Ant Colony based Optimized Authentication Mechanism for Vehicular Ad Hoc Networks [147-150]
Author: Priyanka Rathore, Pankaj Kawadakar
Network Lifetime Enhancement in Mobile Ad-Hoc Network: A Review [151-154]
Author: Ashok Kumar Yadav, Ravendra Ratan Singh
Ant Colony Based Optimized Encryption Scheme for Network-Coded Mobile Ad-Hoc Networks [155-159]
Author: Garima Boriya, Anubhav Sharma
Linear-Regression Based Node Relocation Scheme for Energy Efficient Wireless Sensor Network [160-164]
Author: Rishank Rathore, Mr. Akhilesh Bansiya
Review on BAT Algorithm in IDS for Optimization [165-168]
Author: Aliya Ahmad, Bhanu Pratap Singh Senger
AI-Driven Data Warehouse Modernization in the Healthcare Sector: A Blueprint for Efficiency Modernizing Legacy Data Warehouses with AI-Enhanced Workflows/strong>
Authors:-Srinivasa Chakravarthy Seethala
Abstract-The healthcare industry is at a pivotal moment in terms of data management. Legacy data warehouses, which once served the sector’s needs, are now proving inefficient in an era of rapid technological advancements. This article proposes a framework for modernizing these legacy systems with Artificial Intelligence (AI) technologies, particularly AI-enhanced Extract, Transform, Load (ETL) workflows. These technologies have the potential to significantly improve data quality, operational efficiency, and scalability, especially in key areas such as Electronic Health Records (EHRs), Medical Imaging, Hospital Management, and Medical Research. Additionally, AI enables predictive analytics, offering healthcare organizations the ability to anticipate patient needs and optimize resource allocation. This paper explores the challenges healthcare organizations face, the benefits of AI-driven solutions, and best practices for implementation.
DOI: 10.61137/ijsret.vol.2.issue6.135
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IJSRET Volume 2 Issue 5, September-2016
UncategorizedDBSCAN: An Assessment of Density Based Clustering and It’s Approaches [109-113]
Author: Karuna Kant Tiwari, Virendra Raguvanshi, Anurag Jain
An Genetic Based Fuzzy Approach for Density Based Clustering by Using K-Means [114-120]
Author: Karuna Kant Tiwari, Anurag Jain
Review of Channel Estimation over Orthogonal Frequency Division Multiplexing in Communication System [121-125]
Author: Sonali L. Raulkar, Akant Raghuwanshi
A CFD Analysis of a Wind Turbine Blade Design at Various Angle of Attack and Low Reynolds Number [126-132]
Author: Raju Kumar, Priyanka Jhawar, Sanjay Kalraiya
A Survey: Analytics of Web Log File through Map Reduce and Hadoop [133-138]
Author: Chetan Sharma, Arun Jhapate
Aspect-Oriented Programming in Spring: Enhancing Code Modularity and Maintainability
Authors:-RamaKrishna Manchana
Abstract-Aspect-Oriented Programming (AOP) in Spring allows for the modularization of cross-cutting concerns such as logging, security, and transaction management, improving code maintainability and reducing duplication. This paper explores AOP concepts, implementation details, and practical use cases, specifically focusing on the Common Logger and Global Exception Handler.
DOI: 10.61137/ijsret.vol.2.issue5.126
Visionary Approach In Corporate Sector Of Internet Of Things
Authors: Prabal Kumar Joshi
Abstract: Internet banking is one of the unavoidable advancements in the Information technology revolution. The advancement of Information technology and the Internet led the way to the evolution of internet banking. Internet banking connects the customers and the bank through the Internet to access certain services provided by the bank. It is the application of technological advancements for bestowing the available financial information resources in electronic form. This technology advancement also renders opportunities for banks to quickly and efficiently deliver specific services to the customers at anytime from anywhere without the physical visit of consumers at the bank locations
DOI: http://doi.org/10.5281/zenodo.17019115
Enhancing Customer Experiences With AI-Enhanced Salesforce Bots While Maintaining Compliance In Hybrid Unix Environments
Authors: Ravichandra Mulpuri
Abstract: The growing demand for personalized, efficient, and secure customer interactions has accelerated the adoption of AI-enhanced Salesforce bots across industries. These bots integrate natural language processing, machine learning, and CRM intelligence to streamline engagement while adapting to user needs in real time. Their deployment in hybrid Unix environments provides enterprises with a balance of stability, scalability, and flexibility. However, ensuring compliance with global regulations such as GDPR, HIPAA, and PCI DSS remains a central challenge. This review explores the role of AI-powered Salesforce bots in enhancing customer experiences, examines compliance strategies within hybrid Unix systems, and highlights ethical, operational, and organizational considerations. Future directions emphasize the importance of compliance-by-design, secure integration, and industry-specific applications, positioning AI-driven bots as transformative tools in enterprise digital ecosystems.
DOI: http://doi.org/10.5281/zenodo.17189840