Volume-8 Issue-6S4, April 2019 – International Journal of Innovative Technology and Exploring Engineering (IJITEE)

F13210486S419

IJITEE Journal — Wed, 08 Nov 2023 07:35:33 +0000

The International Journal of Innovative Technology and Exploring Engineering (IJITEE) has ISSN: 2278-3075 (online), an open-access, peer-reviewed, periodical monthly international journal. This journal is published by Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) in January, February, March, April, May, June, July, August, September, October, November and December.The journal aims to publish high–quality peer–reviewed original articles in the area of Engineering and Technology that covers Computer Science and Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering and all interdisciplinary streams of Engineering and Technology. #Smart Computing and Information Processing #Signal and Speech Processing #Image Processing and Pattern Recognition #WSN#Artificial Intelligence and machine learning #Data mining and warehousing #Data Analytics #Deep learning #Bioinformatics #High Performance computing #Advanced Computer Networking #Cloud Computing #IoT #Parallel Computing on GPU #Human Computer Interactions #Recent Trends in Microelectronics and VLSI Design #Process & Device Technologies #Low-Power Design #Nanometer-Scale Integrated Circuits #Application specific ICs (ASICs) #FPGAs #Nanotechnology #Nano Electronics and Quantum Computing #3. Challenges of Industry and their Solutions, Communications #Advanced Manufacturing Technologies #Artificial Intelligence #Autonomous Robots #Augmented Reality #Big Data Analytics and Business Intelligence #Cyber Physical Systems (CPS) #Digital Clone or Simulation #Industrial Internet of Things (IIoT) #Manufacturing IoT #Plant Cyber Security #Smart Solutions – Wearable Sensors and Smart Glasses #System Integration #Small Batch Manufacturing #Visual Analytics #Virtual Reality #3D Printing # Internet of Things (IoT) #Internet of Things (IoT) & IoE & Edge Computing #Distributed Mobile Applications Utilizing IoT #Security, Privacy and Trust in IoT & IoE #Standards for IoT Applications #Ubiquitous Computing #Block Chain-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 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An Research to Enhance the Old Manuscript Resolution using Deep Learning Mechanism
Syed Nawaz Pasha¹, D. Ramesh², D. Kodhandaraman³, M D. Salauddin⁴

¹Syed Nawaz Pasha, Department of Computer Science & Engineering, S R Engineering College, Warangal, Telangana, India.

²D. Ramesh, Department of Computer Science & Engineering, S R Engineering College, Warangal, Telangana, India.

³Dr. D. Kodhandaraman, Department of Computer Science & Engineering, S R Engineering College, Warangal, Telangana, India.

⁴M D. Salauddin, Department of Computer Science & Engineering, S R Engineering College, Warangal, Telangana, India.

Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In this paper we address the problem of enhancing the resolution of old manuscripts as these will deteriorate over time. The manuscripts are of at most importance as they may contain sensitive and important imformation. Hence digital processing techniques play a crucial role to improve the quality of the manuscripts. We propose a standard deep learning mechanism that is conventional neural network (CNN) to enhance image resolution which will help to increase resolution of old manuscript .It not only increases the resolution but also tries to identify missing content using digit recognizer. We also compare the efficiency of our approach with the existing image enhancing techniques.

Keywords: Deep Learning, Conventional Neural Network, Image Enhancement, Digit Recognizer.
Scope of the Article: Deep Learning

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F13200486S419

IJITEE Journal — Wed, 08 Nov 2023 07:30:15 +0000

A Comprehensive Research on Video Imaging Techniques
Farooq Sunar Mahammad¹, Karthik Balasubramanian², T. Sudhakar Babu³, V. Madhu iswanatham⁴

¹Farooq Sunar Mahammad, School of Computing Science and Engineering, Vellore Institute of Technology, Vellore (TamilNadu), India.

²Karthik Balasubramanian, Process and Equipment Engineer, Micron Semiconductor Asia Operations Pte. Ltd., Singapore.

³T. Sudhakar Babu, Department of Electrical Power Engineering, Institute of Power Engineering, University Tenaga Nasional, Malaysia.

⁴V. Madhu Iswanatham, School of Computing Science and Engineering, Vellore Institute of Technology, Vellore (TamilNadu), India.

Abstract: In today’s world, Video imaging techniques are extremely important due to its manifold advantages as they contribute extensively to connectivity of people from one part of the world to another. In this constrain the authors focused to emphasize the numerous technologies available for video image process, highlights of the significant research works carried out in Video imaging techniques has been represented as a review article. Further the article will give the more information about latest techniques; it also summarizes the features of all works with respect to video imaging processing techniques. Hence, the objective of this work is to benefit scientists and new entrants in the field of Video imaging to get overview of the technologies.

Keywords: P2P Video Streaming, Real Time Video Streaming, Non-Real Time Video Streaming.
Scope of the Article: Computer Science and Its Applications

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F13190486S419

IJITEE Journal — Wed, 08 Nov 2023 07:22:47 +0000

Detection of Collinearity Effects on Explanatory Variables and Error Terms in Multiple Regressions
Alhassan Umar Ahmad¹, U.V. Balakrishnan², Prem Shankar Jha³

¹Alhassan Umar Ahmad, Department of Mathematics, Basic Science and Research Sharda University, Greater, Noida.

²U.V Balakarishnan, Department of Mathematics, Basic Science and Research Sharda University, Greater, Noida.

³Prem Shankar Jha, Department of Mathematics, Basic Science and Research Sharda University, Greater, Noida.

Abstract: In this work we investigates the effects and consequences of multicollinearity on both standard error and explanatory variables in multiple regression, the correlation between X1 to X6 (independent variables) measure their individual effect and performance on Y (Response variable) and it is carefully observes how those explanatory variables intercorrelated with one another and to the response variable. There are many procedures available in literature for detecting presence, degree and severity of multicollinearity in multiple regression analysis here we used correlation analysis to discover it is presence; we use variance inflation factors, tolerance level, indices number, eigenvalues to access fluctuation and influence of multicollinearity present in the model. Multicollinearity was discovered in this research work with a severe proportion using arrays of correlation analysis procedure which affects the performance of the explanatory variables present in the model by making it less independent and more redundant as it should not be. Collinearity inflates variance of estimates and brings change in direction and signs of the co-efficient of the estimates leading to unrealistic erroneous inference, wrong interpretation and instability among the predictor variables. standard error is discover to be slightly height which directly affect the accuracy and precision of the final result from the analysis, it bring type 1 error during and after the hypothesis testing and finally undermined the overall inference of the entire analysis interest and is in good agreements with the finding of Complete elimination of collinearity is not possible but in this work we reduce it is degree of intensity to enhance the performance of independent variables and error term in the model.

Keywords: Multicollinearity, Predictor Variable, Standard Error and Multiple Regression.
Scope of the Article: Applied Mathematics and Mechanics

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F13180486S419

IJITEE Journal — Wed, 08 Nov 2023 07:17:25 +0000

Enhancing Reusability and Measuring Performance Merits of Software Component using Data Mining
G. Maheswari¹, K. Chitra²

¹G. Maheswari, Assistant Professor, Mangayarkarasi College of Arts and Science for Women, Madurai (TamilNadu), India.

²K. Chitra, Assistant Professor, Government Arts College, Melur, Madurai (TamilNadu), India.

Abstract: In software industry, it is necessary to reduce time and efforts in software development. Software reusability is an important measure to improve development and quality of software. Enhancing reusability will reduce delivery time of software products, decreases the development labor, software defects and cost of the development process. Software reuse is the best solution factor to acquire the existing knowledge from software warehouse. Measuring the reusability level of the software is essential to achieve the goals of reuse. Data mining is the process of extracting useful patterns and analyzing data sets from large data sets. The reusability of a software component chooses the right measurement and enhances the preventability of an application for reuse. The software metrics are used as quantitative measures to establish and evaluate the components. In this paper, measuring the software reusability using some classification algorithms on a specific software reuse data set is discussed. The system is implemented using R data mining tool and performance of the automation system is developed for reusability prediction like precision, recall, f-measure. The experimental result shows that the model can be effectively used for efficient, accurate, quicker and economic identification of reusable components from the existing software resources. This paper seeks to provide comparative analysis of H-SOM and Naïve Bayes algorithm classifiers of Dengue datasets.

Keywords: Software Reusability, Data Mining, Classification, Reusability Prediction, Hierarchical-SOM, Naïve Bayes.
Scope of the Article: Classification

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F13170486S419

IJITEE Journal — Wed, 08 Nov 2023 07:12:41 +0000

A Research on Security, Privacy Issues and Privacy Preserving Techniques – Big Data
G. Rama Devi¹, Y. Rajesh Babu²

¹G. Rama Devi, Assistant Professor, Department of Computer Science and Engineering, Vasireddy Venkatadri Inst. of Tech., Guntur, Andhra Pradesh, India.

²Y. Rajesh Babu, Assistant Professor,, Department of Computer Science and Engineering, Priyadarshini Institute of Engineering and Technology, Andhra Pradesh, India.

Abstract: Information, which is not a fear till 2000, was the precept criteria for man or woman regarding safety and protection a brief time later. these days enormous measure of information is being created for always it is a check to deal with it. it is being used by numerous groups to take large options from the beyond facts to interrupt down thefuture. This tremendous diploma of facts is referred to as as huge statistics. in spite of the fact that there are numerous common calculations in presence, for giving safety and safety in large records it’s miles attending to be tough because of its traits (quantity, range and Veracity). This paper demonstrates the investigation of common techniques handy, troubles to protection and safety of big records and protection saving processes like anonymization, randomization, differential safety, word and assent and so on.

Keywords: Big Data, Data Privacy and Security Challenges, Privacy Preserving Techniques.
Scope of the Article: Computer Science and Its Applications

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F13160486S419

IJITEE Journal — Wed, 08 Nov 2023 07:06:10 +0000

Research on Achieving Data Security with the Cloud Computing Adoption Framework
R. Adhi Lakshmi¹, P. Priyadharshini², R. Bhaskaran³

¹R. Adhi Lakshmi, Assistant Professor, Department of Information Technology, PSNA College of Engineering & Technology Dindigul (TamilNadu), India.

²P. Priyadharshini, Assistant Professor, Assistant Professor, Department of Information Technology, PSNA College of Engineering & Technology Dindigul (TamilNadu), India.

³R. Bhaskaran, Associate Professor, Assistant Professor, Department of Information Technology, PSNA College of Engineering & Technology Dindigul (TamilNadu), India.

Abstract: Offering perpetual statistics safety for petabytes of facts is important for handed on enrolling. A ordinary overview on cloud safety imparts that the safety of customers’ records has the maximum lifted need and moreover challenge. We acquire this need in order to accomplish with a manner of thinking this is succesful, adoptable and all around made. consequently, this paper has constructed up a device known as Cloud Computing Adoption Framework (CCAF)which has been modified for verifying cloud information. This paper clears up the chart, device for deduction and regions within the CCAF to make certain statistics safety. CCAF is outlined through using the framework route of action depending on the fundamentals and the execution confirmed up thru the CCAF multi-layered protection. while you do not forget that our records center has 10 petabytes of data, there can be splendid challenge to provide nonstop safety and detach. We use business agency manner Modeling Notation (BPMN) to mirror how information is getting used. using BPMN redirection allows us to assess the picked protection introductions in advance than showed execution. outcomes show that an opportunity to assume duty for security break may have a few spot inside the extent of 50 and 100 twenty 5 hours. The server farms have skilled problems of brisk increase within the data. as an example, in a server broaden that the lead writer used to art work with, properly ordered option of 100 terabytes of statistics modified into elegant this proposes greater safety is needed to guarantee all statistics is particularly ensured inside the squeezing a hundred twenty five hours. This paper has correspondingly tested that CCAF multi-layered protection can ensure statistics coherently and it has 3 layers of safety: 1) firewall and get admission to govern; 2) personality affiliation and obstruction adjusting movement and 3) joined encryption. To avow CCAF, this paper has gotten a deal with on techniques of proper hacking assessments required with attack trying out with 10,000 Trojans and pollutions. The CCAF multi-layered security can rectangular 9,919 illnesses and Trojans which can be beaten like a burst and the staying ones may be disengaged or disconnected. The tests seem paying little admire to the way in which that the diploma of blockading can decrease for steady aggregate of ailments and Trojans, 90 seven. forty three percent of them can be restricted. Our CCAF multi-layered safety has a humdrum of 20 percentage ideal execution over the single layered manner of thinking which can simply block7, 438 defilements and Trojans.

Keywords: CCAF Cloud Computing Adoption Framework, BPMN Agency Technique Modeling Notation, ABE Characteristic Based Encryption.
Scope of the Article: Community Information Systems

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F13150486S419

IJITEE Journal — Wed, 08 Nov 2023 06:58:27 +0000

N-Way Segment Hashing for Scalable Subspace Clustering Accession in Big Data
T. Gayathri¹, D. Lalitha Bhaskari²

¹T. Gayathri, Department of Computer Science and Engineering, Shri Vishnu Engineering College for Women, Bhimavaram, Andhra Pradesh, India.

²Lalitha Bhaskari, Department of Computer Science & Software Engineering, Andhra University College of Engineering, Andhra University, Visakhapatnam, Andhra Pradesh, India.

Abstract: A major quantity of data so flighty that makes them hard to method by means of on-certainties the burden up gadgets and traditional data adapting to bundles are delineated with the asset of the articulation “huge realities”. on this paper, manner section hashing device is hooked up to play out an adjusted subscale computation to hold a key suitable approaches from the conspicuous evidence of monotonous associations. a good way to execute the computation, MADELON enlightening document with size 500 and a parallel technique has been balanced on this paper. The advent of the proposed estimation is indicated with the aid of examinations the usage of varied detachment measures and hash work region sizes. The results verify that the proposed computation is proper for purchasing finished with packing even the over the pinnacle size records.

Keywords: Subspace, F1-Measure, Clustering, CLIQUE, INSCY, SUBCLU, N-Way Segmented Hashing.
Scope of the Article: Computer Science and Its Applications

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F13140486S419

IJITEE Journal — Wed, 08 Nov 2023 06:51:42 +0000

Cluster Interfaced Objective Function for Decision Tree Classifiers for Mining Data with Uncertainty
S. Chidambaranathan

S. Chidambaranathan, Department of Ministry Corporate Affairs, Palaymkottai Tamil Nadu, India. St. Xavier’s College, Palaymkottai Tamil Nadu, India.

Abstract: Ordinary desire tree classifiers artwork with recognized and specific information esteems. In late data amassing strategies, apparent diploma of developments are unsure. The unsure characteristics, in nearly all programs, have greater results on the informational index on records grouping and desire tree develops. Vulnerability want to be dealt with correctly. Vulnerability occurs due to facts staleness, some silly estimations, estimation and quantization errors. Vulnerability of an statistics factor is spoken to as some distance as one of a kind capabilities. typically unsure records are disconnected via the usage of measurable subsidiaries (eg., suggest, present day deviation, center and so forth.,). complete statistics of the information element improves the exactness of choice tree classifier (e.g., possibility Density feature (PDF)). In this paper, the proposed work is made to enhance the pruning of desire tree classifier calculation by means of grouping with separation limits and dividing of questionable danger move esteems. Bunching methods increment the rate of desire tree improvement and restriction the pruning time to more noteworthy degree. Separation limit grouping system, works based on the criteria of lower and upper bounds distances of the uncertain attributes values. Partitioning is done with objective function introduced on probability distribution based on the density levels. Objective function introduced evaluates the discrete value of the uncertain data item. Experiments are planned to conduct performance evaluation of heart disease diagnosis and prediction from UCI repository data sets.

Keywords: Objective Function, Decision Tree Classifiers, Cluster Interface, Uncertainty.
Scope of the Article: Classification

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F13130486S419

IJITEE Journal — Wed, 08 Nov 2023 06:47:11 +0000

Low Power and Area Efficient Full Adder using GDI and 2T XNOR
Radhika P¹, Aswathi Gopan²

¹Radhika P, P.G. Scholar, Department of Electronics and Communication Mangalam College of Engineering, Ettumanoor, Kottayam, Kerala, India.

²Aswathi Gopan, Assistant Professor, Department of Electronics and Communication, Mangalam College of Engineering, Ettumanoor, Kottayam, Kerala, India.

Abstract: This paper portrays plan of low electricity and vicinity gifted based complete viper utilising GDI approach. Full snake utilizes 2T XNOR entryway utilizing skip transistor cause. In full viper, low power utilization and least unfold deferral are done via skip transistor rationale and door dissemination enter technique. GDI applied for low energy computerized combinational circuits gives lower in power, deferral and sector of the circuits by means of preserve up the low multifaceted nature of the motive layout. GDI based AND or potentially is utilized. Skip transistor approach lower the amount of transistors. The proposed snake reduced parameters, as an example, manipulate usage, postponement or power-defer object. Undertaking results display that, within the proposed snake eleven. Seventy eight% decreased in power usage and 16.05% in spread defer while contrasted and present viper. The proposed snake is orchestrated utilising CADENCE 5.1.0 EDA device and reenacted using ghost virtuoso.

Keywords: Full Adder; Gate Diffusion Input(GDI)Technique; Pass Transistor Logic(PTL); 2T XNOR; CADENCE tool.
Scope of the Article: Communication

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F13120486S419

IJITEE Journal — Wed, 08 Nov 2023 06:40:20 +0000

Research on Virtual Servers Based Distributed Database System
Sonali Vyas

Sonali Vyas, Assistant Professor, Amity Institute of Information Technology, Amity University, Rajasthan. India.

Abstract: Huge amount of datasets are generated in various fields of science and technology. The data is growing rapidly and not static. To handle various types of datasets and queries needs well-organized distributed database systems. In this paper, a distributed database system architecture, analysis and implementation is presented which is developed on the basis of virtualized environment. The architecture of system uses data clustering, SQMD mechanism, web services and virtualization techniques. The scalability of architecture is shown by using it on various chemical structures. The performance results of queries are presented.

Keywords: Virtual Database, SQMD, Distributed Database System, Virtual Servers.
Scope of the Article: Evolutionary Computing and Intelligent Systems

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