Volume-14 Issue-1, March 2024 – International Journal of Soft Computing and Engineering (IJSCE)

B809913020724

IJSCE Journal — Wed, 28 Aug 2024 06:12:50 +0000

The International Journal of Soft Computing and Engineering (IJSCE) has ISSN: 2231-2307 (online), an open-access, peer-reviewed, periodical bi-monthly international journal. This journal is published by Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) in January, March, May, July, September and November.The journal aims to publish high-quality peer–reviewed original articles in the area of Soft Computing and Engineering that covers Data Communication and Networking, Artificial Intelligence and Neural Networking, Image Processing and Recognition, Software Engineering and Project Management (SEPM), Computer Graphics and Multimedia (CGM), Data Mining, Cryptography and Network Security, Smart Computing and Information Processing, Internet of Things (IoT), Computation Intelligence and Analytics, Machine Learning (ML) and Knowledge Mining (KM), Operating System, Data Base Management System (DBMS), Data Structure and Algorithm (DSA), Object Oriented Analysis and Design (OOAD), and all interdisciplinary streams of Soft Computing and Engineering. #Addressing, Routing, Switching and Location Management #Broadband, Mobile, Wired, Wireless Internet #Networks: Adhoc and Sensor Networks, High Speed Networks, Mobile and #Wireless Networks #Network Architectures #Network Based Applications #Network Protocols #Network Operations & Management #Network Security Trust & Privacy #Cross Layer Design and Optimization #Internet and Web Applications #Network Measurement & Performance Analysis #Next Generation Internet & Web Architectures #Peer to Peer and Overlay Networks #QOS And Resource Management #Recent Trends & Developments in Computer Networks #Self-Organizing Networks and Networked Systems #Ubiquitous Networks #Virtual & Overlay Networks #Wireless Mesh Networks and Protocols #Wireless Multimedia Systems #Personal and Wearable Networks #Information-Centric Networking #Embedded Networks #Opportunistic Networking #Delay-Tolerant Networks #Cognitive Radio Networks #Vehicular Networks #Smart Grid Communications #Underwater Sensor Networks #Cyber-Physical Systems #Social Networks #Green Networking #Overlay and Peer-To-Peer Networks #Local-Area and Metropolitan-Area Networks #Storage-Area Networks #Routing and Transport Protocols #Big Data Networking #Cloud Computing and Networking #Software Defined Networking and Network Function Virtualization #Internet of Things #Link Technologies #Adaptive Networking Applications #Authentication, Authorization, Accounting #Security and Privacy #Cross-Layer Optimization #Multimedia and Real-Time Communication #Machine-To-Machine Communications for Smart Environments #Smart Cities #Network Traffic Characterization and Measurements #Network Management, Reliability and QoS #Performance Evaluation of Networks #Testbeds for Network Experiments #Network Coding #Optical and High-Speed Access Networks #High Performance Computing #Digital System and Logic Design #Networked-Driven Multicourse Chips #Information-Centric Networking #Opportunistic Networking #Mobile and Ubiquitous Networking #Big Data Networking #Cloud Computing and Networking #Software Defined Networking and Network Function Virtualization #Adaptive Networking Applications #Antenna and Communications Devices #Microstrip Antenna #Microwave #Radar and Satellite #Smart Antenna #MIMO Antenna #Wireless Communication #RFID Network and Applications #5G Communication #6G Communication #Neural Networks #Fuzzy Logic #Simulated Biological Evolution Algorithms (Like Genetic Algorithm) #Ant Colony Optimization(etc) #Reasoning and Evolution #Intelligence Applications #Computer Vision and Speech Understanding #Multimedia and Cognitive Informatics #Data Mining and Machine Learning Tools #Heuristic and Ai Planning Strategies and Tools #Computational Theories of Learning #Technology and Computing (Like Particle Swarm Optimization) #Intelligent System Architectures #Knowledge Representation #Bioinformatics #Natural Language Processing #Multiagent Systems #Supervised Learning #Unsupervised Learning #Deep Learning #Big Data and Ai Approaches #Reinforcement Learning #And Learning with Generative Adversarial Networks #Regression and Prediction #Problem Solving and Planning #Clustering #Classification #Neural Information Processing #Vision and Speech Perception #Heterogeneous and Streaming Data #Probabilistic Models and Methods #Reasoning and Inference #Marketing and Social Sciences #Knowledge Discovery #Web Mining #Information Retrieval #Design and Diagnosis #Game Playing #Streaming Data #Music Modelling and Analysis #Robotics and Control #Multi-Agent Systems #Active Vision and Robotic Systems #Architecture of Imaging and Vision Systems #Autonomous Vehicles #Character and Handwritten Text Recognition #Chemical and Spectral Sensitization #Chemistry of Photosensitive Materials #Coating Technologies #Coding and Transmission #Cognitive Aspects of Image Understanding #Color Imaging #Communication of Visual Data #Data Fusion from Multiple Sensor Inputs #Display and Printing #Document Image Understanding # Generation and Display #Holography #Image Analysis and Interpretation #Image Capturing #Image Databases #Image Generation #Image Manipulation #Image Permanence #Image Processing #Image Processing Applications #Image Processing: Coding Analysis and Recognition #Image Representation #Image Sensing #Imaging Systems and Image Scanning #Implementation and Architectures #Latent Image #Materials for Electro-Photography #Monitoring and Surveillance #Network Architecture for Real-Time Video Transport #New Visual Services Over ATM/Packet Network #Non-Impact Printing Technologies #Object Modeling and Knowledge Acquisition #Photoconductors #Photographic Emulsions #Photopolymers #Prepress and Printing Technologies #Processing and Analysis #Protocols for Packet Video #Remote Image Sensing #Retrieval and Multimedia #Scene Modeling #Signal-Processing Aspects of Image Processing #Storage and Transmission #Video Coding Algorithms and Technologies for ATM/P #Ethics of Software Engineering and Management #Software Life Cycles Development Models #Project Planning and Management #Software Requirements Analysis #Software Design Analysis #Software Testing and Integration #Software Implementation and Maintenance #Software Maintenance and Maintainability #Software Metrics or Attributes #Software Risk Assessment and Containment #Reliability #Software Quality and Quality Assurance #Software Cost Estimation #Object Oriented Developments #Object Oriented Metrics #Object Oriented Testing #Formal Notations #3D Reconstruction #Computer Animation #Computational Fabrication #Computational Geometry #Computational Photography #Computer Vision for Computer Graphics #Data Compression for Graphics #Geometric Modelling #Geometric Processing #HCI and Computer Graphics #Human Modelling #Image Analysis #Image Based Rendering #Image Processing #Machine Learning for Graphics #Medical Imaging #Pattern Recognition #Physically Based Modelling #Illumination and Rendering ethods #Robotics and Vision #Saliency Methods #Scientific Visualization #Shape and Surface Modelling #Shape Analysis and Image Retrieval #Shape Matching #Sketch-based Modelling #Solid Modelling #Stylized rendering #Textures #Virtual and Augmented Reality #Visual Analytics #Volume Rendering #Data Mining #Data Science #Big Data #Data Warehouse #Visualization #Security #Privacy #Big DaaS #Scalable Computing #Cloud Computing #Knowledge Discovery #Integration #Transformation #Information Retrieval #Social Data and Semantics #Mining Functions #Data Regression #Data Classification #Anomaly Detection #Data Clustering #Data Association #Data Regression #Data Cleaning #Feature Selection and Extraction #Data Mining Algorithms #Apriori #Decision Tree #Generalized Linear Models #K-Means #Minimum Description Length #Naive Bayes #Non-Negative Matrix Factorization #0-Cluster #Support Vector Machines #Data Preparation #Mining Unstructured Data #Artificial Intelligence #Future Directions and Challenges in Data Mining #Industrial Challenges in Data Mining #Cryptographic Protocols #Cryptography and Coding #Untrace-Ability #Privacy and Authentication #Key Management #Authentication #Trust Management #Quantum Cryptography #Computational Intelligence in Security #Artificial Immune Systems #Biological & Evolutionary Computation #Intelligent Agents and Systems #Reinforcement & Unsupervised Learning #Autonomy-Oriented Computing #Coevolutionary Algorithms #Fuzzy Systems #Biometric Security #Trust Models and Metrics #Regulation and Trust Mechanisms #Data Integrity #Models for Authentication #Trust and Authorization #Wireless Network Security #Information Hiding #Data & System Integrity #Access Control and Intrusion Detection #Intrusion Detection and Vulnerability Assessment #Authentication and Non-Repudiation #Identification and Authentication #Insider Threats and Countermeasures #Intrusion Detection & Prevention #Secure Cloud Computing #Security Information Systems Architecture and Design and Security Patterns #Security Management #Security Requirements (Threats, Vulnerabilities, Risk, Formal Methods, etc.) #Sensor and Mobile ad hoc Network Security #Service and Systems Design and QOS Network Security #System Security #Intrusion Detection #Secure end Systems #Secure Operating Systems #Data Base Security #Security Infrastructures #Security Evaluation #Software Security #Security and Privacy in Mobile Systems#Security and Privacy in Pervasive/Ubiquitous Computing #Security and Privacy in Web Services #Security and Privacy Policies #Security Area Control #Security Deployment #Security Engineering #Security for Grid Computing #Security in Distributed Systems #Network Security #Internet Security #Firewalls #Mobile Security #Security Agents #Protocols #Anti-Virus and Anti-Hacker Measures #Content Protection #Software Protection #Tamper Resistant Software #Electronic Commerce #Electronic Government #Health #Telecommunications #Mobility #Foundations #Privacy #Access Control #Authentication #Identification #Applied Cryptography #Formal Methods in Information Security #IoT & IoE & Edge Computing #Distributed Mobile Applications Utilizing IoT #Security, Privacy and Trust in IoT & IoE #Standards for IoT Applications #Ubiquitous Computing #Blockchain-enabled IoT Device and Data Security and Privacy #Application of WSN in IoT #Cloud Resources Utilization in IoT #Wireless Access Technologies for IoT #Mobile Applications and Services for IoT #Machine/ Deep Learning with IoT & IoE #Smart Sensors and Internet of Things for Smart City #Logic, Functional programming and Microcontrollers for IoT #Sensor Networks, Actuators for Internet of Things #Data Visualization using IoT #IoT Application and Communication Protocol #Big Data Analytics for Social Networking using IoT #IoT Applications for Smart Cities #Emulation and Simulation Methodologies for IoT #IoT Applied for Digital Contents #Soft Computing #Advance Ubiquitous Computing #Parallel Computing #Distributed Computing #Machine Learning #Information Retrieval #Expert Systems #Data Mining #Text Mining #Data Warehousing #Predictive Analysis #Data Management #Big Data Analytics #Big Data Security #Nature Inspired Computing #Reconfigurable Computing #Cloud, Cluster, Grid and P2P Computing #Biomedical Computing #Green Computing #Mobile Computing #Nano Ubiquitous Computing #Context Awareness and Personalization, Autonomic and Trusted Computing #Internet Computing #Sequential, Parallel and Distributed Algorithms and Data Structures #Approximation and Randomized Algorithms #Graph Algorithms And Graph Drawing #On-Line and Streaming Algorithms #Analysis of Algorithms and Computational Complexity #Algorithm Engineering #Web Algorithms #Exact And Parameterized Computation #Algorithmic Game Theory #Computational Biology #Foundations of Communication Networks #Computational Geometry #Discrete Optimization #Software Engineering Methodologies #Agent-based Software Engineering #Artificial Intelligence Approaches to Software Engineering #Component-based Software Engineering #Embedded and Ubiquitous Software Engineering #Aspect-based Software Engineering #Empirical Software Engineering #Search-Based Software Engineering #Automated Software Design and Synthesis #Computer-Supported Cooperative Work #Automated Software Specification #Reverse Engineering #Software Engineering Techniques and Production Perspectives #Requirements Engineering #Software Analysis, Design and Modelling #Software Maintenance and Evolution #Software Engineering Tools and Environments #Software Engineering Decision Support #Software Design Patterns #Software Product Lines #Process and Workflow Management #Reflection and Metadata Approaches #Program Understanding and System Maintenance #Software Domain Modelling and Analysis #Software Economics #Multimedia and Hypermedia Software Engineering #Software Engineering Case Study and Experience Reports #Enterprise Software, Middleware, and Tools #Artificial Intelligent Methods, Models, Techniques #Artificial Life and Societies #Swarm Intelligence #Smart Spaces #Autonomic Computing and Agent-Based Systems #Autonomic Computing #Adaptive Systems #Agent Architectures, Ontologies, Languages and Protocols #Multi-Agent Systems #Agent-Based Learning and Knowledge Discovery #Interface Agents #Agent-Based Auctions and Marketplaces #Secure Mobile and Multi-Agent Systems #Mobile agents #SOA and Service-Oriented Systems #Service-Centric Software Engineering #Service Oriented Requirements Engineering #Service Oriented Architectures #Middleware for Service Based Systems #Service Discovery and Composition #Service Level Agreements (Drafting, Negotiation, Monitoring and Management) #Runtime Service Management #Semantic web #Data Modelling, Mining and Data Analytics #Aggregation, Integration, and Transformation #Web and Text Mining #Data Mining Methods, Techniques, and Tools #Data Analytics Modelling and Algorithms #Patterns and Frameworks #Data Visualization #Knowledge Systems and Engineering #Knowledge Acquisition #Knowledge-based and Expert Systems #Knowledge Representation and Retrievals #Knowledge Engineering Tools and Techniques #Time and Knowledge Management Tools #Knowledge Modelling, Integration, Transformation, and Management #Uncertainty Knowledge Management #Knowledge Visualization #Mobile Computing and Mobile System Engineering #Mobile App Design and Development #Innovative Mobile Applications #Pervasive Computing #Mobile System Validation and Test Automation #Software & System Quality of Service #Soft Computing #Software and System Testing Methods #Quality Assurance Process, Standards, and Systems #Software Safety Systems #Software Test Automation and Tools #Software Dependability, Reliability, Scalability #Software & System Security #Software and System Security and Privacy #Mobile App Security and Privacy #Encryption Methods and Tools #Security Service Systems #Cloud, Sensor Cloud and Mobile Cloud Security #Mobile System Integrity, Security, And Fault Tolerance #Emergent Topics #Cloud Computing and Innovative Cloud-Based Application Systems #Mobile Cloud Computing and Application Services #Big Data Analytics Application Systems #Innovative Sensing Cloud and Systems #Large-Scale Cyber Systems #IoT and Smart City Application Systems #Big Data Quality Validation #Big Data Application Quality Services #Smart Learning and Innovative Education Systems #Learning Software Design Engineering #Smart Learning Methods and Environments #Online Learning Systems #Mobile Enabled Learning Systems and Tools #PhD Academic #Scopus #SCI #LatticeScience #Springer, #ScienceDirect #IEEE #Mendeley #Research #Scholarship #UGC #SSRN #ESCI #Science #Journal #Conference #SSRN #PubLons #PhD #Academic #Scopus #SCI #LatticeScience #Springer, #ScienceDirect #IEEE #Mendeley #Research #Scholarship #UGC #SSRN #LatticeScience #ESCI #Science #Journal #Conference #SSRN #PubLon

An Innovative Approach: Sea Ice Types Classification Using Convolutional Neural Networks with DDDTDWT Filter
Venkata Kondareddy Gajjala¹, T.J. Naga Lakshmi²

¹Dr. Venkata Kondareddy Gajjala, Department of Computer science and Engineering, N.B.K.R Institute of Science and Technology, Tirupati, India.

²Dr. T.J. Naga Lakshmi, Professor, Department of Electronics and Communication Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, India.

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Studying sea ice and its interaction with climate change is crucial due to its significant impact on the environment, society, and global stability. The pressing need to address the underlying reasons for the rapid melting of Arctic and Antarctic sea ice is underscored by its adverse effects on the environment and society. In this proposed study, a Convolutional Neural Network (CNN) is utilized to predict ice types using data from the NSIDC DAAC Advanced Microwave Scanning Radiometer – Earth Observing System Sensor (AMSR-E) collection. This dataset contains parameters such as sea ice types and spans data products from June 2002, obtained from the NASA Data Centre. By employing hand-crafted features as input and a single layer of hidden nodes, the CNN used in this approach generates improved estimates of ice types, outperforming traditional image analysis methods. At each stage, ConvNets utilise diverse filter banks, feature extraction and pooling layers, and fully connected layers with basic activation functions, such as ReLU. This allows the network to build multifaceted hierarchies of features. The sea ice type estimates produced by the CNN are then compared with those obtained from passive microwave brightness temperature data using existing algorithms as well as a proposed CNN algorithm, resulting in an increased classification accuracy of 98.58%. This improvement is particularly notable in the reduction of the error rate, which has been effectively minimized from 3.01% without feature selection to 1.42% with infinite feature selection. When compared to existing algorithms, the CNN demonstrates superior performance. These findings underscore the impact of input patch size, CNN layer count, and input size on the model’s performance.

Keywords: Advanced Microwave Scanning Radiometer – Earth Observing System Sensor (AMSR-E), Convolutional Neural Network (CNN).
Scope of the Article: Computer Networks and Its Applications

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F451713060824

IJSCE Journal — Thu, 25 Jul 2024 07:19:25 +0000

Effectiveness in Collaborative Framework for Non-Invasive in AI Algorithms
Sandeep Kulkarni¹, B.Vijayendra Reddy²

¹Dr. Sandeep Kulkarni, Software Developer, Pune (Maharashtra), India.

²B.Vijayendra Reddy, Department of Computer Science Engineering, Lovely Professional University, Phagwara (Punjab), India.

Abstract: The topic of study and practice known as “privacypreserving machine learning (PPML)” focuses on developing methods and strategies that enable the training and application of machine learning models while protecting the privacy of sensitive data for convolutional neural networks and Machine learning algorithms. Garbled worlds” is a concept primarily used in the context of privacy-preserving machine learning (PPML). It refers to a technique used to protect the privacy of individual data points during the training process of machine learning models. Garbled worlds allow organizations or individuals to collaborate and train machine learning models using their combined datasets without sharing the raw data. This is particularly important in scenarios where data privacy regulations or concerns prohibit the sharing of sensitive information. By utilising garbled worlds, organisations can leverage the collective knowledge across multiple datasets while protecting the privacy of individuals whose data contributes to the training process. This technique helps strike a balance between data privacy and the utility of machine learning models in various applications. The effectiveness and adaptability of ABY3 (The mixed protocol framework for machine learning) enable users to select several cryptographic protocols based on their unique needs and limitations. In comparison to other safe multi-party computation frameworks, it minimizes computational and communication costs while maintaining a high level of security. The viability of our system is demonstrated by the enhanced benchmarking of the previously described algorithms in contrast to ABY3 [1]

Keywords: ABY3, MLaaS, GDPR, Homomorphic Encryption, Logistic Regression, Linear Regression, Convolution Neural Network.
Scope of the Article: Neural Networking

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D442813040424

IJSCE Journal — Tue, 28 May 2024 06:11:36 +0000

Zara Tech Trail: Futuristic Autonomous Robocart for Cutting-Edge Multi-Perspective Delivery System
Devendran M¹, Palaniappan P.L², Shanmuga Priya R³

¹Devendran M, Department of Artificial Intelligence and Data Science, Prince Dr. K.Vasudevan Collegeof Engineering and Technology, Chennai, India.

²Palaniappan P. L, Department of Artificial Intelligence and Data Science, Prince Dr. K. Vasudevan College of Engineering and Technology, Chennai, India.

³Shanmuga Priya R, Department of Artificial Intelligence and Data Science, Prince Dr. K. Vasudevan College of Engineering and Technology, Chennai, India.

Abstract: The autonomous delivery system presented in this project utilises a RoboCart equipped with GPS navigation to transport products from their source to their destination seamlessly. The system, powered by electric charging, ensures timely and secure delivery to end customers, featuring a specialised hand gripper for precise and careful product handling. Designed for diverse applications, including commercial purposes and personal use, as well as various industries such as hotels, this fully autonomous cart incorporates a password-enabled security feature to ensure user verification. Positioned as a cutting-edge technological solution, this project aims to effectively address the last-mile delivery challenge, presenting the potential to reduce delivery times and contribute to societal benefits significantly. The success of this initiative holds the promise of substantial positive impacts on Society.

Keywords: Autonomous, GPS Navigation, Electric, Product Handling, Password, Last Mile, Societal Benefits
Scope of the Article: Autonomous Vehicles

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A362314010324

IJSCE Journal — Thu, 28 Mar 2024 10:05:58 +0000

Power Demand Forecasting Using ANN and Prophet Models for the Load Despatch Center in Andhra Pradesh, India
Damini Swargam¹, Mahitha Natte², Durga Aparajitha Javvadi³, Vamsi Krishna Chaitanya Aray⁴, Venkata Rama Santosh Rachuri⁵, Sreedhar Reddy Veguru⁶

¹Damini Swargam, Assistant Executive Engineer, Department of Andhra Pradesh State Load Despatch Center, Transmission Corporation of Andhra Pradesh Limited, Vijayawada (Andhra Pradesh), India.

²Mahitha Natte, Assistant Executive Engineer, Department of Andhra Pradesh State Load Despatch Center, Transmission Corporation of Andhra Pradesh Limited, Vijayawada (Andhra Pradesh), India.

³Durga Aparajitha Javvadi, Statistical Officer, Department of Andhra Pradesh State Load Despatch Center, Transmission Corporation of Andhra Pradesh Limited, Vijayawada (Andhra Pradesh), India.

⁴Vamsi Krishna Chaitanya Aray, Assistant Executive Engineer, Department of Andhra Pradesh State Load Despatch Center, Transmission Corporation of Andhra Pradesh Limited, Vijayawada (Andhra Pradesh), India.

⁵Venkata Rama Santosh Rachuri, Deputy Executive Engineer, Department of Andhra Pradesh State Load Despatch Center, Transmission Corporation of Andhra Pradesh Limited, Vijayawada (Andhra Pradesh), India.

⁶Sreedhar Reddy Veguru, Executive Engineer, Department of Andhra Pradesh State Load Despatch Center, Transmission Corporation of Andhra Pradesh Limited, Vijayawada (Andhra Pradesh), India.

Abstract: This paper uses various data variables to develop and analyze ANN and Prophet models for power demand forecasting in Andhra Pradesh, India. The electricity power consumption in Andhra Pradesh was about 51,756.000 GWh in 2021. Currently, there is a great emphasis on saving power. Power Demand Forecasting is creating significant interest, and various models, such as artificial neural networks combined with other techniques based on real-life phenomena, are being used and tested. These models have become an essential part of the power and energy sector. This paper examines specific time-series analysis methods and deep learning techniques for short-term power demand forecasting. This paper also analyses and compares the results between the Prophet and ANN models to predict power demand in Andhra Pradesh, India. Our results comparatively revealed the model’s appropriateness for the problem. Both models performed well in three performance metrics: accuracy, generalization, and robustness. However, the AI model exhibits better accuracy than Prophet for the historical dataset. The time taken for model fitting is also comparatively less for the AI models. The forecast accuracy of the electricity was in the range of 95 to 97.65.

Keywords: Demand Forecasting, Weather, Time Series Analysis, Prophet, Keras, TensorFlow
Scope of the Article: Neural Networks

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