Volume-6 Issue-1, March 2016 – International Journal of Soft Computing and Engineering (IJSCE)

A2789036116

IJSCE Journal — Thu, 30 Sep 2021 10:18:09 +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

Performance Analysis of Different Classifiers for American Sign Language Recognition
Rajesh B. Mapari¹, Govind Kharat²
¹Prof. Rajesh B. Mapari, Department of Electronics & Telecommunication Engineering, Anuradha Engineering College, Chikhli, India.
²Prof. Govind Kharat, Principal, Sharadchandra Pawar College of Engineering, Otur, India
Manuscript received on February 09, 2016. | Revised Manuscript received on February 15, 2016. | Manuscript published on March 05, 2016. | PP: 90-95 | Volume-6 Issue-1, March 2016. | Retrieval Number: A2789036116/2016©BEIESP
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© The Authors. Published By: 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: American Sign Language alpha-numeric character recognition without using any embedded sensor, color glove or without the constraints of an environment is a really difficult task. This paper describes a novel method of static sign recognition using a leap Motion sensor by obtaining feature set based on hand position, distance and angle between different points of hand. A feature set is later trained and tested using different classifiers like MLP (Multilayer Perceptron), GFFNN (Generalized Feed forward Neural Network), SVM (Support Vector Machine). We have collected dataset from 146 people including students of age 20-22 years and few elders age between 28-38 who have performed 32 signs resulting in total dataset of 4672 signs. Out of this 90% dataset is used for training and 10% dataset is used for testing/Cross validation. we have got maximum classification accuracy as 90% on CV/testing dataset using MLP Neural Network.
Keywords: ASL, MLP, GFFNN, SVM.

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A2816036116

IJSCE Journal — Thu, 30 Sep 2021 10:12:51 +0000

Stock Market Prediction using Neural Networks
Vaibhav V. Shah¹, Smitkumar J. Mirani², Yashvardhan V. Nanavati³, Vishal Narayanan⁴, Sheetal I. Pereira⁵
¹Vaibhav V Shah Computer Engineering, K. J. Somaiya College of Engineering, Mumbai, India.
²Smitkumar J MiraniComputer Engineering, K. J. Somaiya College of Engineering, Mumbai, India.
³Yashvardhan V NanavatiComputer Engineering, K. J. Somaiya College of Engineering, Mumbai, India.
⁴Vishal Narayanan Computer Engineering, K. J. Somaiya College of Engineering, Mumbai, India.
⁵Prof. Sheetal I Pereira Computer Engineering, K. J. Somaiya College of Engineering, Mumbai, India.
Manuscript received on February 09, 2016. | Revised Manuscript received on February 15, 2016. | Manuscript published on March 05, 2016. | PP: 86-89 | Volume-6 Issue-1, March 2016. | Retrieval Number: A2816036116/2016©BEIESP
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© The Authors. Published By: 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: In this paper we present our efforts to predict the stock market using Artificial Neural Networks. We study different types of Neural Networks, their salient features along with the internal working of these networks and the various configurations that they can be run with. We go to comment on the advantages and disadvantages of these networks. Finally we select the one network with specific configurations and use it to predict the stock prices of a few selected companies from the National Stock Index. We achieve best case accuracy of 98% on the dataset.
Keywords: Artificial Neural Networks, Neurons, Back propagation algorithm, Prediction methods, Stock markets.

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A2813036116

IJSCE Journal — Thu, 30 Sep 2021 10:06:49 +0000

Comparison of Responses of the PI and the Fuzzy Logic Controlled Closed Loop DPFC Systems
S. Vadivel¹, B. Baskaran²
¹S. Vadivel, Department of Electrical Engg., Annamalai University, Annamalainagar-608002.
²Dr. B. Baskaran, Department of Electrical Engg., Annamalai University, Annamalainagar-608002.
Manuscript received on February 09, 2016. | Revised Manuscript received on February 15, 2016. | Manuscript published on March 05, 2016. | PP: 82-85 | Volume-6 Issue-1, March 2016. | Retrieval Number: A2813036116/2016©BEIESP
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© The Authors. Published By: 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: The proposed work deals with comparison of the PI and the fuzzy logic controlled closed loop DPFC systems. The voltage across the load decreases due to the addition of extra load and the load voltage are restored back to normal value by using closed loop system. The ability of closed loop system to bring the voltage and reactive power back to the set value is represented in this paper. The simulation studies for open loop and closed loop systems are performed on a standard ten bus radial test system.
Keywords: DPFC – Distributed power flow control, DVR – Dynamic Voltage Regulator, ESS – Steady State Error, FACTS – Flexible AC Transmission System, Q – Reactive Power, STATCOM – Static Compensator, Ts – Settling Time, UPFC – Unified power flow control, V – Voltage, VAR – Voltage Ampere Reactive, VP – Peak Over Shoot Voltage.

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A2809036116

IJSCE Journal — Thu, 30 Sep 2021 10:02:36 +0000

Vehicle Classification Algorithm using Size and Shape
Samuel A. Daramola¹, Abdulkareem Ademola²
¹Associate Prof. Samuel. A Daramola, Department of Electrical and Information Engineering, Covenant University Canaan-Land Ota, Nigeria.
²Engr. Ademola Abdulkareem, Department of Electrical and Information Engineering, Covenant University Canaan-Land Ota, Nigeria.
Manuscript received on February 09, 2016. | Revised Manuscript received on February 15, 2016. | Manuscript published on March 05, 2016. | PP: 78-81| Volume-6 Issue-1, March 2016. | Retrieval Number: A2809036116/2016©BEIESP
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© The Authors. Published By: 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: Automatic classification of vehicles into different classes based on their sizes and shapes is very useful for traffic control and toll collection process. Effective intelligent transportation system that incorporates vehicle classification technique is needed in many cities to prevent road accident and traffic congestion caused by illegal movement of vehicles. This work presents method of getting structural information from detected vehicle images and then uses it to classify vehicles into different classes. The technique involves extraction of contour features from vehicle images side view using morphological operations. The extracted features were combined and used to generate feature vector that serve as input data to vehicle classification algorithm based on Euclidean distance measure. Impressive result was achieved from the proposed vehicle classification method.
Keywords: Vehicle, Shape, Size, Features, Boundary, Classification.

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A2807036116

IJSCE Journal — Thu, 30 Sep 2021 09:58:46 +0000

Cyber Education: A Need of the Time
Parveen Sadotra¹, Chandrakant Sharma²
¹Parveen Sadotra, Certified Ethical Hacker, Jammu (J&K), India.
²Dr. Chandrakant Sharma, Assistant Professor, Career Point University, Kota (Rajasthan), India.
Manuscript received on February 09, 2016. | Revised Manuscript received on February 15, 2016. | Manuscript published on March 05, 2016. | PP: 74-77 | Volume-6 Issue-1, March 2016. | Retrieval Number: A2807036116/2016©BEIESP
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© The Authors. Published By: 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: In the last two decades Internet has changed our lives in a great way. Almost everything is dependent on internet. Vast use of internet has created a new kind of threat to human civilization. Dependency of our day to day work in cyber world has become indispensable in present time. This revolution of internet has made our life much easy on one hand but at the other hand we need to be very much cautious. If we are not familiar of the pros and cons of the cyber world it may cost a huge loss sometimes to even life. So it is the need of time that every one of this earth should educated well about this beautiful cyber world along with all the security aspects and it needs a well-planned strategy to achieve 100 % cyber literacy.
Keywords: Cyber Education, Cyber Security, Cyber Theft, Cyber World, Literacy

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A2806036116

IJSCE Journal — Thu, 30 Sep 2021 09:54:02 +0000

Intuitionistic Fuzzy Tree Center-Based Clustering Algorithm
Amit R. Khaparde¹, M. M. Raghuwanshi², L. G. Malik³
¹Prof. Mr. Amit Khaparde, Ph.D. Research Scholar Department of Computer Science and Engineering, GHRCE, Nagpur and Faculty of RGCER, Nagpur, Maharashtra, India.
²Dr. M. M. Raghuwanshi, Professor, Department of Computer Technology, YCCE, Nagpur, Maharashtra, India.
³Dr. L. G. Malik, Professor, Department of Computer Science and Engineering , GHRCE, Nagpur, Maharashtra, India
Manuscript received on February 09, 2016. | Revised Manuscript received on February 15, 2016. | Manuscript published on March 05, 2016. | PP: 70-73 | Volume-6 Issue-1, March 2016. | Retrieval Number: A2806036116/2016©BEIESP
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© The Authors. Published By: 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: Here, we presented, the use of differential evolution algorithm in industrial applications. The differential evolution algorithm is widely used to solve direct, continuous space optimizations problems. The application of DE is present in almost all fields of engineering problems. One real life problem, from the field of electronic engineering name frequency modulation for sound waves synthesis is used to show the efficiency of differential evolution algorithm. The results are further evaluated on the parameter name success rate and success performance , they shows that the DE have very fast convergence rate and having ability to solve the given problem
Keywords: Evolutionary algorithm, sound waves, multi-model problem

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A2805036116

IJSCE Journal — Thu, 30 Sep 2021 09:49:12 +0000

Improved Design of Obstacle Avoidance Robot using three Ultrasonic Sensors and ATMEGA328P Microcontroller
Mukesh Kumar Dey
Mukesh Kumar Dey, School of Electronics and Communication Engineering (SENSE), VIT University, Vellore, India.
Manuscript received on February 09, 2016. | Revised Manuscript received on February 15, 2016. | Manuscript published on March 05, 2016. | PP: 66-69 | Volume-6 Issue-1, March 2016. | Retrieval Number: A2805036116/2016©BEIESP
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© The Authors. Published By: 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: This paper proposes an alternative design for a cost effective and simplified version of the obstacle avoidance robot using three ultrasonic sensors. It also provides a dynamic algorithm which directs the robot to navigate smoothly in different environments, avoiding obstacles. The main objective of this paper is to improve the accuracy of the robot in detection and avoidance of obstacles at various angles. The paper talks about the design of the robot which is followed by the working principle of sensors and algorithm for the microcontroller. The paper finally makes a detailed explanation of the code for the obstacle avoidance strategy and draws a conclusion based on the designed robot.
Keywords: ATMEGA328P, Binary Logic, HC-SR04, Dynamic algorithm. I

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A2800036116

IJSCE Journal — Thu, 30 Sep 2021 09:45:11 +0000

Intuitionistic Fuzzy Tree Center-Based Clustering Algorithm
G. Thamizhendhi¹, R. Parvathi²
¹G. Thamizhendhi, Department of Mathematics, Vellalar College for Women, Erode, Tamilnadu, India.
²R. Parvathi, Department of Mathematics, Vellalar College for Women, Erode, Tamilnadu, India.
Manuscript received on February 09, 2016. | Revised Manuscript received on February 15, 2016. | Manuscript published on March 05, 2016. | PP: 50-65 | Volume-6 Issue-1, March 2016. | Retrieval Number: A2800036116/2016©BEIESP
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© The Authors. Published By: 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: In this paper, the concepts of distance, eccentricity, radius, diameter and center of an intu-itionistic fuzzy tree are defined. Some of the domination parameters like independent domina-tion, connected domination and total domination on intuitionistic fuzzy trees are investigated. The procedure for intuitionistic fuzzification for numerical data set is proposed. Further, in-tuitionistic fuzzy tree center-based clustering algorithm is designed. The e ectiveness of the algorithm is checked with a numerical dataset and compared with two existing clustering meth-ods.
Keywords: Intuitionistic fuzzy tree, distance, eccentricity, center, connected domination, connec-tivity, clustering

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A2802036116

IJSCE Journal — Thu, 30 Sep 2021 09:37:47 +0000

I2C Master Protocol Implementation in VHDL for Data Acquisition from CDC
Pavan Kumar K¹, Daniel Raju Paga², V. Bagyaveereswaran³
¹Pavankumar K, Department of Control and Automation, SELECT, Vellore Institute of Technology, Vellore, Tamil Nadu-632014, India.
²Daniel Raju Paga, Department of Control and Automation, SELECT, Vellore Institute of Technology, Vellore, Tamil Nadu-632014, India.
³Prof. V. Bagyaveereswaran, Department of Control and Automation, SELECT, Vellore Institute of Technology, Vellore, Tamil Nadu-632014, India
Manuscript received on February 09, 2016. | Revised Manuscript received on February 11, 2016. | Manuscript published on March 05, 2016. | PP: 43-49 | Volume-6 Issue-1, March 2016. | Retrieval Number: A2802036116/2016©BEIESP
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© The Authors. Published By: 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: Communication between devices plays an important role in data acquisition. Proper selection of communication method or protocols is an important task. For any process, hardware and software components are used to perform many tasks like controlling the process and actuators, data conversion, data acquisition etc. A large amount of hardware or software components cannot be used for data acquisition. A proper and efficient approach is intended to be made such that they are used in least possible numbers, also keeping in mind that the different existing devices are compatible without any major modifications. This paper presents an approach to acquire data through I2C protocol in an efficient way. The AD7746 which is capacitance to digital convertor uses I2C protocol for providing the digital data. The digitized information is acquired from the AD7746 by a FPGA which is designed using modular flow method.
Keywords: AD7746, FPGA, I2C protocol, Master, FSM, Serialdata communication.

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A2799036116

IJSCE Journal — Thu, 30 Sep 2021 09:14:49 +0000

Investigating Pre-Construction Planning in the Construction Industry of Kenya: Practitioners Perspective
Cyrus Babu Ong`ondo
Ong`Ondo Babu Cyrus, Department of Construction Management, Jomo Kenyatta University of Agriculture & Technology (JKUAT). Juja, Kenya.
Manuscript received on January 09, 2016. | Revised Manuscript received on January 21, 2016. | Manuscript published on March 05, 2016. | PP: 38-42 | Volume-6 Issue-1, March 2016. | Retrieval Number: A2799036116/2016©BEIESP
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© The Authors. Published By: 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: The subject of pre-construction planning is central to the success of project controls and performance during the implementation of construction projects. However, projects have been failing pointing to the need to relook at the planning for projects implementation. In the construction industry of Kenya, performances challenges during projects implementation is a chronic problem. Projects do not achieve their planned cost, time and quality objectives among other performance measures. This study sought to investigate pre-construction planning in the construction industry of Kenya, with emphasis on its adequacy. This cross-sectional research adopted a mixed-method design consisting of analysis of a questionnaire survey administered to active 95No. (NCA1, NCA2 and NCA3) contractors selected by way of stratified random sampling. A similar approach was also used to select 92No.Consultants with a response rate of 54.73% and 46.73% respectively. In addition, 11No.practitioners wereinterviewed in the currentstudy. Data analysis techniques employed include descriptive statistics and thematic analysis.The study established five (5No.) issues that need to be given careful attention when planning for projects implementation. The issues in order of importance include; Clarity of Scope Statement (RII=0.896), Clarity of performance benchmarks (RII=0.865), Competency of the project team (RII=0.0.682), Clarity of roles definition (RII=0.764) and Contractors selection criteria (RII=0.726). The study concludes by compiling views of the practitioners on what they consider good practice in improving the pre-construction planning practice. The study recommends the use of the good-practice checklist developed for better projects performance.
Keywords: Pre-construction planning, construction industry, good-Practice checklist, Kenya.

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