Volume-5, Issue-2, May 2015 – International Journal of Soft Computing and Engineering (IJSCE)

B2618055215

IJSCE Journal — Fri, 01 Oct 2021 09:06:45 +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

Perturb and Observe (P&O) and Incremental Conductance (INC) MPPT Algorithms for PV Panels
H. Mohssine¹, H. Bouhouch², F. Debbagh3, M. Kourchi⁴¹Hassan Mohssine, Professor, High School of Technology, Lasime Laboratory, Agadir, Morocco.
²Houcine Bouhouch, Professor, High School of Technology, Agadir Morocco.
³Fouad Debbagh, Professor, LPSCM Laboratory, Marrakech Morocco.
⁴Mustapha Kourchi, Professor, High School of Technology, Agadir Morocco.
Manuscript received on April 17, 2015. | Revised Manuscript received on April 28, 2015. | Manuscript published on March 05, 2015. | PP: 123-126 | Volume-5, Issue-2, May 2015. | Retrieval Number: B2618055215 /2015©BEIESP
Open Access | Ethics and Policies | Cite
©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 work we present a study on the comparison between two MPPT algorithms: Perturb and Observe (P&O) and Incremental Conductance (INC). We base our approach on the difference between computed results using an adapter bloc Buck DC-DC converter. The MPPT algorithms are combined with it to complete the PV simulation system. We show that the MPPT control with both P & O and INC keeps the system power operating point at its maximum. For this purpose the conventional P&O, the converter input reference voltage is perturbed in fixed steps until the maximum power is reached. However, depending on the step size, the system operating point will oscillate around the MPP resulting in a loss of energy.
Keywords: Photovoltaic (PV), Maximum Power Point Tracking (MPPT), Perturb and Observe (P&O), Incremental Conductance (INC).

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B2622055215

IJSCE Journal — Fri, 01 Oct 2021 08:55:40 +0000

The Brand Extension Strategy: An Analysis
Shubha Agarwal¹, Govind Narain Bajpai²¹Dr. Shubha Agarwal, Assoc. Prof., Department of Management, Seth Sriniwas Agarwal Institute of Management, Kanpur, Uttar Pradesh, India.
²Govind Narain Bajpai, Asst. Prof., Department of Management, Seth Sriniwas Agarwal Institute of Management, Kanpur, Uttar Pradesh, India.
Manuscript received on April 15, 2015. | Revised Manuscript received on April 28, 2015. | Manuscript published on March 05, 2015. | PP: 121-122 | Volume-5, Issue-2, May 2015. | Retrieval Number: B2622055215 /2015©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: Branding has emerged as a top management priority in the last decade due to the growing realization that brands are one of the most valuable intangible assets that firms have. This paper identifies some of the influential work in the branding area, highlighting what has been learned from an academic perspective on important topics such as brand positioning, brand integration, brand equity measurement, brand growth, and brand management. It is also discussed how branding and society affect each other. Based on the knowledge of how branding theories have been developed as dependent variables of each other and the society, we are able to form a better understanding of the past, the present, and the future of branding.
Keywords: Top management priority, most valuable intangible assets, branding area, brand positioning, brand integration, brand equity measurement, brand growth.

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B2612055215

IJSCE Journal — Fri, 01 Oct 2021 08:50:51 +0000

A Survey to Justify the Need for Carpooling
Sweta¹, Sushmitha Reddy I², Maddipatla Mounika³, Priyanka Agrawal⁴, Pallavi G. B⁵¹Sweta, Department of Computer Science and Engineering, B.M.S. College of Engineering, Bangalore, India.
²Sushmitha Reddy I, Department of Computer Science and Engineering, B.M.S. College of Engineering, Bangalore, India.
³Maddipatla Mounika, Department of Computer Science and Engineering, B.M.S. College of Engineering, Bangalore, India.
⁴Priyanka Agrawal, Department of Computer Science and Engineering, B.M.S. College of Engineering, Bangalore, India.
⁵Pallavi G. B, Asst. Prof., Department of Computer Science and Engineering, B.M.S. College of Engineering, Bangalore, India.
Manuscript received on April 20, 2015. | Revised Manuscript received on April 28, 2015. | Manuscript published on March 05, 2015. | PP: 117-120 | Volume-5, Issue-2, May 2015. | Retrieval Number: B2612055215/2015©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 India people mostly prefer road transportation to move around places. The increasing number of vehicle on road lead to several issues as congestion, environmental degradation and energy problems. Research and development have been progressively done in this field to reduce the environmental degradation and for the better utilization of fossil fuels. Different approaches and techniques to solve these issues emerged which address fields of emission reduction, increase efficiency of vehicle, energy alternative, decrease the road density with care of safety and comfort, etc. In this paper survey on these emerging drifts and elaborate on one of the ways to reduce the vehicular density and emission, we have identified carpooling as one such solution to provide user, flexibility in time, enjoyable, efficient and safe ride.
Keywords: Drivers, Efficiency, GHG emission, HOV [high occupancy vehicle], Passenger, Road density, Safety.

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B2609055215

IJSCE Journal — Fri, 01 Oct 2021 08:41:56 +0000

An Energy-Efficient, Delay-Aware, Lifetime-Balancing and Data Collection Protocol for Heterogeneous Wireless Sensor Networks
Merina Devi Hemam¹, N.V. Uma Reddy²¹Merina Devi Hemam, PG student, M.Tech. (DEC), Department of ECE. AMCEC, Bangalore, India.
²N. V. Uma Reddy, Assoc. Prof., Department of ECE, AMCEC, Bangalore, India.
Manuscript received on April 14, 2015. | Revised Manuscript received on April 28, 2015. | Manuscript published on March 05, 2015. | PP: 113-116 | Volume-5, Issue-2, May 2015. | Retrieval Number: B2609055215/2015©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 technique that is used in this paper is to make it more simpler for wireless sensor networks problem .To make the energy more efficient a protocol is used that is called EDAL. It is rebuilt from the existing system called OVR which uses NP-hard algorithm. To make more prominent a centralized heuristic is design to make the computational overhead more smaller and to detect the dead nodes. As it has some limitation distributed heuristic is design which is the best for large scale networks.
Keywords: Power consumption, delay, energy efficient, heuristic algorithm, wireless sensor networks.

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C2295074314

IJSCE Journal — Fri, 01 Oct 2021 08:37:15 +0000

First Passage Monte-Carlo Simulation for Charge Distribution and Capacitance
Aditya Kumar Singh¹, Apurva Anand², Anindya Sundar Das³¹Aditya Kumar Singh, Department of ECE, ICFAI University, Jharkhand, Ranchi. India.
²Apurva Anand, Department of ECE, BIT Mesra, Ranchi, Jharkhand, India.
³Anindya Sundar Das, Department of Physics, Sidho-Kanho-Birsha University, Purulia, West Bengal, India.
Manuscript received on April 17, 2015. | Revised Manuscript received on April 26, 2015. | Manuscript published on March 05, 2015. | PP: 109-112 | Volume-5, Issue-2, May 2015. | Retrieval Number: C2295074314/2015©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: A novel scheme has been studied and demonstrated for Monte Carlo simulations of diffusion-reaction processes. The new algorithm skips the traditional small diffusion hops and propagates the diffusing particles over long distances through a sequence of super-hops, one particle at a time. By partitioning the simulation space into non- overlapping protecting domains each containing only one or two particles, the algorithm factorizes the N-body problem of collisions among multiple Brownian particles into a set of much simpler single-body and two-body problems. Efficient propagation of particles inside their protective do- mains is enabled through the use of time-dependent Green’s functions (propagators) obtained as solutions for the first-passage statistics of random walks. The resulting Monte Carlo algorithm is event-driven and asynchronous; each Brownian particle propagates inside its own protective domain and on its own time clock. The algorithm reproduces the statistics of the underlying Monte-Carlo model exactly. The new algorithm is efficient at low particle densities, where other existing algorithms slow down severely. Thus we have analyzed the application of this algorithm in the charge distribution and the capacitance detection.
Keywords: Monte Carlo Simulation, Charge distribution, capacitance, Markov chain.

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B2624055215

IJSCE Journal — Fri, 01 Oct 2021 07:45:19 +0000

What Affects the Memory
Etleva Beliu¹, Ermira Pajaj²¹Etleva Beliu, Ph.D. Department of Mathematical Engineering, Faculty of Mathematical Engineering and Physical Engineering (FME&PhE), University Polytechnic of Tirana, Tirana, Albania.
²Ermira Pajaj, Mother Tereza Hospital, Neurology Department, Tirana, Albania.
Manuscript received on April 18, 2015. | Revised Manuscript received on April 28, 2015. | Manuscript published on March 05, 2015. | PP: 105-108 | Volume-5, Issue-2, May 2015. | Retrieval Number: B2624055215 /2015©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: Physical exercise affects our body on multiple fronts. It increases heart rate, which means more blood pumped to the brain. It also helps the body release some hormones, that participate in aiding and providing a nourishing environment for the growth of brain cells. Physical exercise training can modify hippocampal and medial temporal lobe volumes. Both of these regions are involved in memorization. The aim of this study is to analyze the effect of physical exercise, of smoking, and using alcohol on the memorizing ability. By using the questionnaires and face-to-face interviews, data is collected from around 300 people of both genders. They have an age range of 15 – 20 years old and are from different schools in Albania ; namely in Tirana and the outskirts of Tirana, in Durres, in Shkodra, Gjirokastra and Vlora. They are asked to read 40 words in 5 minutes and then are tested to see how many of them they can memorize. The questionaire includes demographic information such as age, gender and birth city and questions to measure their lifestyle. In the lifestyle area it is asked about the smoking habbit, alcohol consumption, eating and exercise frequency. The data is analized using SPSS. A normalization of number of memorized words is done. Then, this modified variabel is analized using stepwise multiple regression. The most important independent variables of this model are exercise frequency and alcohol consumption. Exercise frequency is organized in three groups: those who train 0-2 days a week, Level Group 1 (LG1); those who train 3-4 days a week (LG2); and the ones that train more than 4 days a week (LG3). The method of MANOVA shows that there is a statistically obvious increase between two consecutive levelgroups. But there is a very significant difference between the number of memorized words of LG1 and LG2. This research provides evidence that physical exercise and alcohol consumation affect memory.
Keywords: Memory, BDNF molecule, hippocampus, exercise frequency, alcohol consumption, stepwise multiple regression, and MANOVA.

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B2614055215

IJSCE Journal — Fri, 01 Oct 2021 07:39:13 +0000

Decision Tree Approach for Classification of Satellite Imagery
Havyas V B¹, Choodarathnakara A L², Thribhuvan R³, Chethan K S⁴¹Prof. Havyas V B, Department of Electronics & Communication Engineering, Government Engineering College, Kushalnagar, Kodagu, INDIA.
²Prof. A L Choodarathnakara, Department of Electronics & Communication Engineering, Government Engineering College, Kushalnagar, Kodagu, IND IA.
³Prof. Thribhuvan R, Department of Electronics & Communication Engineering, Coorg Institute of Technology, Ponnampet, Kodagu, INDIA.
⁴Prof. Chethan K S, Department of Electronics & Communication Engineering, PESIT, Bangalore, INDIA.
Manuscript received on April 20, 2015. | Revised Manuscript received on April 28, 2015. | Manuscript published on March 05, 2015. | PP: 101-104 | Volume-5, Issue-2, May 2015. | Retrieval Number: B2614055215/2015©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: Various practical systems capable of extracting descriptive decision making knowledge from data have been developed and evaluated. Techniques that represent knowledge about classification tasks in the form of decision trees are focused on. A sample of techniques is sketched, ranging from basic methods of constructing decision trees to ways of using them non-categorically. Some characteristics that suggest whether a particular classification task is likely to he amenable or otherwise to tree-based methods are discussed. Many urban land cover types show spectral similarity in remote sensing data. Further, the finer the spatial resolution of the data, the larger is the number of detectable subclasses within classes. This high within-class spectral variance of some classes results in multimodal distribution of spectra and may decrease their spectral separability. Hence, the existing traditional hard classification techniques which are parametric type do not perform well on high resolution data in the complex environment of the urban area as they expect datasets to be distributed normally. The aim of this paper is to investigate a non-parametric classifier as an alternative approach to classify an image data of a semi urban area.
Keywords: Remote Sensing, Image Classification, Parametric Classifier, Non-parametric and Decision Tree Classifier.

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B2617055215

IJSCE Journal — Fri, 01 Oct 2021 07:33:23 +0000

A Novel Method for Analysis of EEG Signals Using Brain Wave Data Analyzer
Apeksha Rani H. M¹, Prathibha Kiran²¹Apeksha Rani H M, 4th Sem, M.Tech (Signal Processing), AMCEC, Bengaluru, India.
²Mrs. Prathibha Kiran, Asst. Prof., Department of E&C, AMCEC, Bangalore, India.
Manuscript received on April 20, 2015. | Revised Manuscript received on April 28, 2015. | Manuscript published on March 05, 2015. | PP: 98-100 | Volume-5, Issue-2, May 2015. | Retrieval Number: B2617055215/2015©BEIESP
Open Access | Ethics and Policies | Cite
©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 present day research allow us to develop a new class of bioengineering control devices and robots to provide daily life assistance to handicapped and elderly people. This proposed method describes how the brain activity is measured using mind wave EEG signal data transmission device. The brain electric signal are measured by EEG (Electroencephalograph) which shows a demand for better accuracy and stability and facilitates the graphical illustration of spatial features of electric brain activity. It provides a very promising technology for physically disabled people who are unable to access their hands and in this paper we will discuss briefly how the data acquisition can be done by using biosensor.
Keywords: EEG, Mind wave, Biosensor.

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B2615055215

IJSCE Journal — Fri, 01 Oct 2021 07:28:55 +0000

Classification and Categorization of Blood Infection Using Fuzzy Inference System
Harsh Khatter¹, Anjali Jain², Poonam Pandey³¹Mr. Harsh Khatter, Department of Computer Science, ABES Engineering College, Ghaziabad, India.
²Ms. Anjali Jain, IT Department, U.P Technical University, ABES Engineering Collge, Ghaziabad, India.
³Ms. Poonam Pandey, Department of Computer Science, ABES Engineering College, Ghaziabad, India.
Manuscript received on April 15, 2015. | Revised Manuscript received on April 26, 2015. | Manuscript published on March 05, 2015. | PP: 95-97| Volume-5, Issue-2, May 2015. | Retrieval Number: B2615055215/2015©BEIESPP
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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: From last few decades the human body infections and diseases are growing in exponential manner. As per the medical report, in every three months a new infection or viral comes in existence with some new explode to effect the human race. To test whether the infection is in body or not, Blood tests are the common methods. Most of the diseases are beyond the doctor’s study or some recently spread virus infected the blood or human body. In such cases doctors use to give the treatment of other disease having same symptoms or same blood test cases. In this paper we are trying to make such a system which will spread awareness among doctors about the infections. The proposed system will work on the basis of fuzzy logic and neural network with the help of inference engine and its rules. The simulation will be done using Matlab. The proposed approach of using fuzzy logic and inferences with neural networks training in blood samples on real test cases of blood report is a novel idea.
Keywords: About four key words or phrases in alphabetical order, separated by commas.

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B2613055215

IJSCE Journal — Fri, 01 Oct 2021 07:22:44 +0000

The Corresponding Options of TCP Variants for Fairness Problem in AD HOC Networks
Alem Čolaković¹, Tarik Čaršimamović²¹M. Sc. Alem Čolaković, System Engineer, Faculty of Traffic and Communications, University of Sarajevo, Bosnia and Herzegovina.
²Dr. Tarik Čaršimamović, Assistant to Exeucitve Director for Business Development, BH Telecom JSC Sarajevo, Bosnia and Herzegovina.
Manuscript received on April 16, 2015. | Revised Manuscript received on April 28, 2015. | Manuscript published on March 05, 2015. | PP: 86-94 | Volume-5, Issue-2, May 2015. | Retrieval Number: B2613055215/2015©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 ad hoc network is a continuously self-configuring and decentralized network where nodes communicate with each other without the fixed network infrastructure or centralized administration. TCP (Transmission Control Protocol) is a connection-oriented transport protocol that provides a reliable exchange of data streams. Implementation of TCP in wireless networks has many challenges such as the issues of the efficiency and TCP fairness problem. The fairness means that network nodes (users or applications) are receiving a fair share of overall resources. In this paper, we study the problem of maintaining the fairness for TCP connections in ad hoc networks. Our research has been made to present the TCP fairness problem in MANET (ad hoc mobile networks) while considering the sending and receiving of traffic. Achieving fairness in these networks is a challenge due to specific characteristics of an ad hoc environment and it is necessary to adapt TCP for ad hoc networks. The primary goal of this paper is to present fairness in ad hoc networks using combinations of different TCP variants and routing protocols. We evaluated the results of our research by using the proper simulation method.
Keywords: Ad hoc, MANET, VANET, TCP, fairness.

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