Volume-2 Issue-6, January 2013 – International Journal of Soft Computing and Engineering (IJSCE)

F1190112612

IJSCE Journal — Sat, 16 Oct 2021 09:48:01 +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

Using Naïve Bayes Classifier to Accelerate Constructing Fuzzy Intrusion Detection Systems
Mehran Amiri¹, Mahdi Eftekhari², Farshid Keynia³
¹Mehran Amiri, Computer engineering department of Science and Research branch of Islamic Azad University, Kerman, Iran.
²Mahdi Eftekhari, Computer engineering department of Science and Research branch of Islamic Azad University, Kerman, Iran.
³Farshid Keynia, Computer engineering department of Science and Research branch of Islamic Azad University, Kerman, Iran.
Manuscript received on January 01, 2013. | Revised Manuscript received on January 02, 2013. | Manuscript published on January 05, 2013. | PP: 453-459 | Volume-2, Issue-6, January 2013. | Retrieval Number: F1190112612/2013©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 Bayesian classifier is one of the most widely used classifiers which possess several properties that make it surprisingly useful and accurate. It is illustrated that performance of Bayesian learning in some cases is comparable with neural networks and decision trees. Bayesian theorem suggests a straight forward process which is not based on search methods. This is the major point which satisfies the marvelous time complexity of Bayesian classifier. At the other hand, constructing phase of fuzzy intrusion detection systems suffer from time consuming processes which are based on search methods. In this paper we propose a novel method to accelerate such processes using Bayesian inference. Experimental results show meaningful time reduction.
Keywords: Fuzzy intrusion detection systems, Naïve Bayes classifier, Rule`s consequent class, Time complexity.

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F1147112612

IJSCE Journal — Sat, 16 Oct 2021 07:30:55 +0000

SQL INJECTION Attacks in Web Application
Mihir Gandhi¹, JwalantBaria²
¹Mihir Gandhi, ME Student of Information Technology Parul Institute of Engg. & Tech. At.Baroda, Gujrat, India
²Jwalant Baria, ME Computer Science and Engineering Parul Institute of Engg. & Tech. At.Baroda, Gujrat, India.
Manuscript received on January 01, 2013. | Revised Manuscript received on January 02, 2013. | Manuscript published on January 05, 2013. | PP: 189-191 | Volume-2, Issue-6, January 2013. | Retrieval Number: F1147112612/2013©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: Databases are the first target of the attackers in Web Application Once your ID and PASSWORD are out there may be several misuse of it. These paper discuss about Advance SQL Injection (ASQLIA) first of all it identifies which type of attacks according to that prevention measures are suggested .Some New features are added to it Web Crawling ,Web Services and Advance SQL Injection (ASQLA)which will emphases more Security of Web Application. In short enhancing database security with the aspect of web developer is main aim of my paper.
Keywords: Cybercrime, hash function, encryption algorithm.SQL Injection, Tautology, SQLIA, Blind injection, piggy backing, PSIAW.

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F1176112612

IJSCE Journal — Wed, 13 Oct 2021 08:41:44 +0000

Effect of Post-Deposition Annealing on Hydrogenated Amorphous Silicon Thin Films Grown At High Power by Pecvd
Aravind Kumar¹, Pawan Kumar², Parmender Kumar³, Kapil Malik⁴, P. N. Dixit⁵
¹Aravind Kumar, Department of Physics Kalindi College East Patel Nager New Delhi-110008., India.
²Pawan Kumar, Department of Physics Gurukula Kangri Vishwavidyalaya, Haridwar-249404, India.
³Parmender Kumar, Department of Physics Gurukula Kangri Vishwavidyalaya, Haridwar-249404, India.
⁴Kapil Malik, Department of Physics Gurukula Kangri Vishwavidyalaya, Haridwar-249404, India.
⁵P.N. Dixit, Plasma Processed Materials Group National Physical LaboratoryDr. K.S. Krishnan Road, New Delhi-110 012
Manuscript received on January 01, 2013. | Revised Manuscript received on January 02, 2013. | Manuscript published on January 05, 2013. | PP: 516-419 | Volume-2, Issue-6, January 2013. | Retrieval Number: F1176112612/2013©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 crystallization of hydrogenated amorphous silicon layers (a-Si:H) [1,2] deposited by plasma enhanced chemical vapor deposition (PECVD) is of great interest. Generally, laser or metals are used to induce crystallization in aSi:H films. We have found that films deposited at high rf power (> 0.2 W/cm2) by PECVD technique shows some crystallites embedded in a-Si:H matrix and their after its vacuum thermal annealing at 250 and 300 oC helps to further enhancement of crystallite size. These films were characterized using , UV-VIS spectrometry, Raman Spectra, of these films were measured as a function of temperature in the range of 300 oC to 250 oC.
Keywords: Amorphous silicon, Thin Films, Growth PECVD.

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F1246112612

IJSCE Journal — Wed, 13 Oct 2021 07:45:41 +0000

A New Method to Measure the Similarity between Features in Machine Learning using the Triangular Fuzzy Number
Hassan Nosrati Nahook¹, Mahdi Eftekhari²
¹Hassan Nosrati Nahook, Student of MSc Computers – AI, Computer Engineering Department, Science and Research Branch, Islamic Azad University, Kerman, Iran .
²Mahdi Eftekhari, Assistant Professor, Computer Engineering Department, Science and Research Branch, Islamic Azad University, Kerman, Iran.
Manuscript received on January 01, 2013. | Revised Manuscript received on January 02, 2013. | Manuscript published on January 05, 2013. | PP: 511-515 | Volume-2, Issue-6, January 2013. | Retrieval Number: F1246112612/2013©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 a new method to measure the similarity between features using fuzzy numbers. The proposed method uses the concept of geometry to calculate the degree of similarity between triangular fuzzy numbers defined on the features. We also prove some properties of the proposed similarity measure and use different data sets to compare the proposed method with existing methods. In the feature selection methods, the proposed similarity measure compared with other fuzzy similarity measures can be more efficient.
Keywords: Similarity Measure, Symmetrical or Asymmetrical Triangular Fuzzy Number, Features.

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F1173112612

IJSCE Journal — Wed, 13 Oct 2021 07:40:54 +0000

Multimodal Biometric system Fusion using Fingerprint and Iris with Fuzzy Logic
Mohamad Abdolahi¹, Majid Mohamadi², Mehdi Jafari³
¹Mohamad Abdolahi, Department of Computer, Science and Research branch, Islamic Azad University, Kerman, Iran.
²Majid Mohamadi, Department of Computer, Science and Research branch, Islamic Azad University, Kerman, Iran.
³Mehdi Jafari, Department of Computer, Science and Research branch, Islamic Azad University, Kerman, Iran.
Manuscript received on January 01, 2013. | Revised Manuscript received on January 02, 2013. | Manuscript published on January 05, 2013. | PP: 504-510 | Volume-2, Issue-6, January 2013. | Retrieval Number: F1173112612/2013©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: Single biometric systems have a variety of problems such as noisy data, non-universality, spoof attacks and unacceptable error rate. These limitations can be solved by deploying multimodal biometric systems. Multimodal biometric systems utilize two or more individual modalities, like face, iris, retina and fingerprint. Multimodal biometric systems improve the recognition accuracy more than uni-modal methods. In this paper, two uni-modal biometrics, iris and fingerprint are used as multi-biometrics and show using this biometrics has good result with high accuracy. Decision level is used for fusion and each biometric result is weighted for participate in final decision. Fuzzy logic is used for the effect of each biometric result combination.
Keywords: Fingerprint recognition, Iris recognition, , minutiae extraction, multi-biometric.

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F1250112612

IJSCE Journal — Wed, 13 Oct 2021 07:37:02 +0000

Solar Wind Hydro Hybrid Energy System Simulation
Kavitha Sirasani¹, S.Y. Kamdi²
¹Kavitha Sirasani, Pursuing M.tech in Energy, Management System from, Rajiv Gandhi College of Engg., Research & Technology, Chandrapur , Maharashtra.
²Subhash Y. Kamdi, Assistant Professor (Dept. of Electrical Engg.), Rajiv Gandhi college of Engg., Research & Technology, Chandrapur Maharashtra
Manuscript received on January 01, 2013. | Revised Manuscript received on January 02, 2013. | Manuscript published on January 05, 2013. | PP: 1-4 | Volume-2, Issue-6, January 2013. | Retrieval Number: F1250112612/2013©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 importance of hybrid systems has grown as they appeared to be the right solution for a clean and distributed energy production. So that new implementations of hybrid systems require special attention on analysis and modeling. This paper deals theoretical study of hybrid systems, based on renewable energy is the availability of models, which can be used to study the behavior of hybrid systems and most important, software simulation environments. In this paper we present several models which can be used for the simulation purposes of hybrid power systems.
Keywords: Hybrid energy system; Micro-hydro; Solar; Wind; Modeling; Simulation

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F1231112612

IJSCE Journal — Wed, 13 Oct 2021 07:33:36 +0000

Transmit Beamforming for Performance Enhancement of IEEE 802.16e Mobile WiMAX
Ekta Tiwari¹, Suchita Varade²
¹Ekta Tiwari, Electronics & communication Department, Priyadarshini College of Engineering, Nagpur, India
²Suchita Varade, Electronics & Communication Department,Priyadarshini College of Engineering, Nagpur, India
Manuscript received on January 01, 2013. | Revised Manuscript received on January 02, 2013. | Manuscript published on January 05, 2013. | PP: 493-499 | Volume-2, Issue-6, January 2013. | Retrieval Number: F1231112612/2013©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 aims at performance evaluation of mobile WiMAX system which uses multiple antenna technique such as space time block coding space time trellis coding with and without transmit beamforming for multiple transmit and multiple receive antennas. The mobile WiMAX system has been analyzed for modulation scheme such as mPSK along with different combination of multiple transmit and receive antenna. Computer simulations are done using MATLAB 7.10.The performance of the proposed system has been analyzed in terms of bit error rate (BER). Simulation results shows that the multiple antenna technique in combination with transmit beamforming improves the performance of mobile WiMAX system in terms of BER as number of transmitting antenna increases without increasing the transmit power and bandwidth.
Keywords: Mobile WiMAX, Multiple Input Multiple Output (MIMO),Space Time Block Code(STBC), Space Time Trellis Code(STTC), Transmit Beamforming.

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F1159112612

IJSCE Journal — Wed, 13 Oct 2021 07:25:05 +0000

Considering the effect of using JPEG images on accuracy results of radiology images and application programs
Mirzaei H.¹, Jafari M.², Mirshahi A.³
¹Mirzaei H., Department of Computer, Science and Research branch, Islamic Azad University, Kerman, Iran.
²Dr. Jafari M., Department of Computer, Science and Research branch, Islamic Azad university, Kerman, Iran.
³Dr. Mirshahi A., Department of Clinical Sciences, Faculty of Veterinary Medicine, Ferdowsi University of Mashhad (FUM), Mashhad, Iran.
Manuscript received on January 01, 2013. | Revised Manuscript received on January 02, 2013. | Manuscript published on January 05, 2013. | PP: 489-492 | Volume-2, Issue-6, January 2013. | Retrieval Number: F1159112612/2013©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: With hardware and software algorithms development, necessity of methods with accuracy and velocity are more attention. For example edge detection is one of the most important operations in machine vision and the main purpose of edge detection is reducing the volume of data with preserving main structure and original form of images. For these purpose the accuracy of edge detection with retrieval edges by minimum position error rate and losing edges is one of more important approach in recent decades. It is clear those raw images because of no losing many features than JPEG images have better results. In this research consider a simulation neural network program and compare three famous edge detection “Sobel, Prewitt, Canny” with raw images and shows efficiency on results.
Keywords: Medical image processing, Edge detection, Raw image, Neural network.

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F1248112612

IJSCE Journal — Wed, 13 Oct 2021 07:21:19 +0000

Evaluating Teachers Ranking using Fuzzy AHP Technique
Hota H. S.¹, Sirigiri Pavani², P. V. S. S. Gangadhar³
¹Dr. Hota H.S., Assistant Professor, GGV, Bilaspur (C.G.), India.
²Sirigiri Pavani, AssistantProfessor, CMD College, Bilaspur (C.G.), India.
³P.V.S.S. Gangadhar, NIC, Rayagada (Odissa), India.
Manuscript received on January 01, 2013. | Revised Manuscript received on January 02, 2013. | Manuscript published on January 05, 2013. | PP: 485-489 | Volume-2, Issue-6, January 2013. | Retrieval Number: F1248112612/2013©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: Teachers are the backbone of any educational institution and responsible for quality education, a good teacher can produce good student but Indian institutions are very poor in terms of quality teachers, in spite of having well qualified faculty members in their institutions. There is always a question mark about quality teaching. A teacher with good academic records may not necessarily be a good teacher hence there should be a reliable technique to evaluate teachers quality for financial and administrative decision making .An institute management can take proper decision about teachers after choosing best teacher in their institution and also assign new responsibilities based on their quality. Fuzzy AHP is a multi criteria decision making technique which is frequently used to find out ranking and can be applied to find out teachers ranking ,the quality of teacher is fuzzy in nature hence fuzzy AHP approach can better deal with this situation and finally decide ranking of the teachers based on the multiple conflicting criteria of the teachers. A teacher may have many qualities like communication ability, knowledge level ,interaction with students etc. but all these qualities are qualitative not quantitative which is little bit difficult to deal with traditional theory .Fuzzy logic can be used to deal this type of problem . In this research work fuzzy logic based MCDM method: fuzzy AHP is used to decide the ranking of teacher for further decision making. Data of small sample size of teachers are collected from educational institution.
Keywords: Fuzzy analytical hierarchy process (FAHP), Multi criteria decision making (MCDM).

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F1203112612

IJSCE Journal — Wed, 13 Oct 2021 07:16:45 +0000

A New Methodology to Compensate Stiction in Pneumatic Control Valves
S. Sivagamasundari¹, D. Sivakumar²
¹S.Sivagamasundari, Dept. of Electronics and Instrumentation Engg., Annamalai University, Annamalai Nagar, Tamil Nadu, India.
²D.Sivakumar, Dept. of Electronics and Instrumentation Engg. Annamalai University, Annamalai Nagar, Tamil Nadu, India.
Manuscript received on January 01, 2013. | Revised Manuscript received on January 02, 2013. | Manuscript published on January 05, 2013. | PP: 480-484 | Volume-2, Issue-6, January 2013. | Retrieval Number: F1203112612/2013©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: Industrial surveys reported that, almost one third of poorly performing control loops are caused by nonlinearities present in the control valves, one of which is static friction. The effect of this nonlinearity is usually observed as oscillations in process variable. Since industrial plants include numerous interacting loops, the oscillations will be propagated to the entire system. Doubtlessly, repairing the faulty valves will be the only solution to this problem, which is possible only during process shut down. But, as shutting down the process to isolate the faulty valve for maintenance purposes is not economical, this solution does not count as the primary one. So, there is a need for a method to compensate the destructive effect of the stiction phenomenon in the control valve, especially when maintenance is not available. This paper focuses on existing compensation issues, followed by a proposal of a new model-based compensation approach for the stiction nonlinearity present in control valves. Performance of this method is validated by both simulation and laboratory data.
Keywords: Pneumatic control valve, stiction, Stick band, stiction compensation, knocker.

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