Volume-9 Issue-3S, January 2020 – International Journal of Innovative Technology and Exploring Engineering (IJITEE)

C10920193S20

IJITEE Journal — Tue, 22 Aug 2023 11:28:23 +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 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 #Microwaves and Photonics #Microwave filter #Micro Strip antenna #Microwave Link design #Microwave oscillator #Frequency selective surface #Microwave Antenna #Microwave Photonics #Radio over Fibre #Optical Communication, #Optical Oscillator #Optical Link Design #Optical Phase Lock Loop #Optical Devices #Computation Intelligence and Analytics #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 #Energy Harvesting and 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Electroencephalogram based Brain Computer Interface System Analysis
Parth Agrawal¹, Parul Khanna², Beaulah Soundarabai P³, Niju P Joseph⁴

¹Parth Agrawal, CHRIST Deemed to be University, Bangalore (Karnataka), India.

²Parul Khanna, CHRIST Deemed to be University, Bangalore (Karnataka), India.

³Dr. Beaulah Soundarabai P, CHRIST Deemed to be University, Bangalore (Karnataka), India.

⁴Dr. Niju P Joseph, CHRIST Deemed to be University, Bangalore (Karnataka), India.

Open Access | Editorial and Publishing Policies | Cite | Zenodo | 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: Electroencephalogram is the study of electrical signals of the brain recorded using a mesh like structure containing electrodes that is placed on the scalp. The history of EEG dates more than a century back, when the brains of rabbits and monkeys were studied and almost 50 years later in the year 1924, the first ever brain activity of human was noted by famed psychiatrist and physiologist Hans Berger from Germany. EEG based systems that can communicate with the brain are categorized as Brain Computer Interface i.e. BCI. The electrodes read the brain signals, amplifies them in order to be studied more accurately by the machine send them to machine after converting it into digital form. With the recent changes in technology better electrodes are being used which can catch highly sensitive signals as well.[1][2] EEG based BCI systems can change the world for many people as it holds so much power if thought properly. This paper reviews the EEG functioning and some innovations in BCI and also proposes ideas about potential help for people suffering from hearing and speech impairment.

Keywords: Brain-Computer Interface, EEG, fMRI, BCI, EEG-fMRI Fusion, MEG.
Scope of the Article: Computer Science and Its Applications

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C10910193S20

IJITEE Journal — Tue, 22 Aug 2023 11:20:37 +0000

Outlier Detection: A Research and Modified Method Using Fuzzy Clustering
S. Rajalakshmi¹, P. Madhubala²

¹S. Rajalakshmi, Department of Computer Science, Government Arts College for women, Krishnagiri (Tamil Nadu), India.

²Dr. P. Madhubala, HOD, Department of Computer Science, DonBosco College, Dharmapuri (Tamil Nadu), India.

Abstract: Data mining is becoming increasingly popular in many application fields. Due to the advancement, Researchers show great interest to find unexpected behaviour over large amount of datasets. Outlier detection is studied extensively in data mining and developed for certain application domains, while others are generic in nature. It is one of the important and hottest topic in research which faces a series of new challenges. It occurs due to change in system behaviour, mechanical fault, human error, natural deviations and instrumental error. The purpose of this paper briefly provides a survey on outlier detection and a modified approach to detect outlier using Fuzzy clustering. Also, it provides a better understanding of different dimensions that applied in various substantive areas.

Keywords: Data Mining, Fuzzy Clustering, Outlier Detection.
Scope of the Article: Fuzzy Logics

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C10900193S20

IJITEE Journal — Tue, 22 Aug 2023 11:13:26 +0000

Leveraging Fintech for Sustainable Development in Emerging Economies – A Policy Perspective
Nisha Prakash¹, Madhvi Sethi²

¹Nisha Prakash, Research Scholar, Symbiosis International University, Pune (Maharashtra), India.

²Dr. Madhvi Sethi, Professor, Symbiosis Institute of Business Management SIBM, Bengaluru (Karnataka), India.

Abstract: Technological advancements in the provision of financial services are transforming the economic landscape by providing opportunities for financial institutions, corporate sector, and consumers. Financial technologies (fintech) offer broader economic development and inclusive growth and facilitate international payments and remittances. Fintech applications, such as mobile wallets and crowdfunding that are hugely successful, especially in developing countries such as India, are examples of how simple technologies can enhance financial inclusion through the decentralized provision of payments, borrowings, and risk management. However, these innovations also create challenges for regulators. The emerging fintech models raise concerns on investor protection, adequacy of existing regulations and potential threats to financial stability, leading to questions on the policies and institutional framework required to tap into the benefits of these technologies securely. In this paper, we look at the landscape of fintech companies and their suitability for financing sustainable development. The paper also examines the policy and institutional frameworks required for the effective utilization of fintech for sustainable development. Fintech has the potential to involve the private sector to finance sustainable development and hence the paper would be of interest to policymakers, particularly in developing countries, as many struggles to bridge gaps in financing their sustainable development goals (SDGs).

Keywords: Blockchain, Fintech, Sustainable Development, Sustainable Finance.
Scope of the Article: Computational Economics

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C10890193S20

IJITEE Journal — Tue, 22 Aug 2023 11:05:43 +0000

Optimized Ensemble Weak Learner Tree Based Network Efficient Intrusion Detection and Alert System using Data Mining
K. Mohanapriya¹, M. Savitha Devi²

¹K. Mohanapriya, Guest Lecturer, Department of Computer Science, Government Arts College for Women, Krishnagiri (Tamil Nadu), India.

²Dr. M. Savitha Devi, Assistant Professor, Department of Computer Science, Periyar University Constituent College of Arts & Science, Harur (Tamil Nadu), India.

Abstract: The modern society accesses various network services through different devices. However, the services afford by the service provider faces various challenges and threats. The services are facing different network threats towards degrading the service performance or the entire network. Number of approaches discussed earlier to restrict the illegal access from malicious users which uses different properties in service level, packet level, user level features. However, they suffer to achieve higher performance in intrusion detection. To improve the performance in intrusion detection an novel tree based ensemble learner algorithm has been proposed in this paper. The method incorporates Random Forest and Random Trees, which are identified as NP complete. The method maintains the list of ensembles which are indexed under trees. At the classification, the Tabu Search algorithm has been used which measures the ensemble class weight (ECW) which has been used to perform classification. According to the result of intrusion detection, an alert has been generated to the administrator. The proposed algorithm improves the performance of intrusion detection.

Keywords: Network Intrusion Detection Systems (NIDS), Decision Trees, Random Forest, Random Trees, Ensemble Weak Learner Tree and Tabu Search (TS).
Scope of the Article: Data Mining

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C10880193S20

IJITEE Journal — Tue, 22 Aug 2023 10:58:13 +0000

Best Feature Selection using Modified Whale Optimization Algorithm for Prediction of Heart Disease
M. Geethanjali¹, P. Madhubala²

¹M. Geethanjali, Assistant Professor, Department of Computer Science, St.Joseph’s College of Arts and Science for Women, Hosur (Tamil Nadu), India.

²Dr. P. Madhubala, HEAD & Assistant Professor, Department of Computer Science, Don Bosco College, Dharmapuri (Tamil Nadu), India.

Abstract: Coronary illness is the confusion of heart and blood veins. It is hard for restorative specialists and specialists to foresee precise about coronary illness determination. Information science is the majorobject in primary expectation and takes care of huge information issues nowadays. This examination paper portrays the expectation of coronary illness in restorative area by utilizing information science. The same number of inquiries about done research identified with that issue however the exactness of expectation is yet should have been improved. Thus, this exploration centers on highlight choice methods and calculations where numerous coronary illness datasets are utilized for experimentation investigation and to appearance the precision development. In this work Modified Whale Optimization (MWOA) is utilized for highlight determination reason. By utilizing the Rapid digger as apparatus; Random Forest, (ANN), Decision Tree(DT) and Naive Bayes(NB) calculations are utilized as highlight choice procedures and improvement is appeared in the outcomes by demonstrating the exactness. From the proposed investigation the Artificial Neural Network grouping system is document better outcomes regarding Accuracy, Recall, Precision and F-measure.

Keywords: Heart Disease Prediction, Feature Selection, Modified Whale Optimization (MWOA), Random Forest, Artificial Neural Network (ANN), Decision Tree (DT) and Naive Bayes (NB).
Scope of the Article: Regression and Prediction

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C10870193S20

IJITEE Journal — Tue, 22 Aug 2023 10:47:23 +0000

An Empirical Research on Service-Oriented Architecture (SOA) for Data Exchange in BIGDATA Systems
T. Lavanya

T. Lavanya, Head, Department of Computer Science, Govt. Arts College for Women, Krishnagiri (Tamil Nadu), India.

Abstract: Service-Oriented Architecture is a method for scheming dealing and organizing systems that represent eco-friendly business functionality. The objective of this study is to find out the critical success factors that need to implement SOA in BIG DATA systems. Our study aimed at classifying these erroneous performs in execution of SOA. The acceptance of SOA has interested creators to text its requests and applications. The analysed results would be very useful for researchers who would like to implement SOA with BIG DATA systems. SOA lead numerous advantages such as value-added flexibility and appropriate alignment among processes as well as reduced cost of integration and maintenance. Generally, BIG DATA anxieties large-volume, composite, rising figures groups with numerous, self-directed sources. BIG DATA claims where data gathering has grownup extremely and is elsewhere the aptitude of usually used software utensils to detention, accomplish and development within the rise [1]. The greatest essential task for the BIG DATA applications is to discover the large volumes of data and excerpt valuable material or information for upcoming actions. The main purpose of this study is to identify the important factors that are needed to implement SOA in BIG DATA systems. Zhang and Yang suggests a reengineering approach which will restructure the legacy systems that leads to SOA by considering of an organization. This paper also express various challenges of SOA and identify the problems that improve SOA based services for data exchange in BIG DATA systems.

Keywords: SOA, BIG DATA Systems (BDS), Legacy Systems, Web Services.
Scope of the Article: Big Data Quality Validation

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C10860193S20

IJITEE Journal — Tue, 22 Aug 2023 10:40:57 +0000

A Model for Predicting Human Depression using Machine Learning Algorithm
J. Shanthalakshmi Revathy¹, N. Uma Maheswari², S. Sasikala³

¹J. Shanthalakshmi Revathy, Assistant Professor, Department of Computer Science and Engineering, Velammal College of Engineering and Technology, Madurai (Tamil Nadu), India.

²N. Uma Maheswari, Professor, Department of Computer Science and Engineering, PSNA college of Engineering and Technology, Dindigal (Tamil Nadu), India.

³S. Sasikala, Assistant Professor, Department of Computer Science and Engineering, Velammal College of Engineering and Technology, Madurai (Tamil Nadu), India.

Abstract: In recent days people share their images in many social media and also they are not certain about the privacy. This leads to many issues. In light of these incidents, a tool is needed for providing access control method during user’s file sharing. To do that, Adaptive Privacy Policy Prediction (A3P) system is proposed for setting the privacy parameters to their images. The image data, user’s social context and their meta data are used in the privacy setting preferences. The author proposed a two-stage framework for determining and setting the existing privacy policy in accordance to the user’s history over the website. The proposed solution depends on the image categories and the social features of the user. Also, it depends on the user’s privacy data and the relevant features. From the experimental and simulation results it is proved that the privacy preservation is one of the important task in internet applications.

Keywords: Adaptive Privacy Policy Prediction, Privacy Preference.
Scope of the Article: Machine Learning

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C10850193S20

IJITEE Journal — Tue, 22 Aug 2023 10:33:43 +0000

An Optimized Technique for Sharing Air Quality Index Using Cloud Technology
N. Vallileka¹, S. Jai Ganesh², Nimmathi Satheesh³, R. SivaKumar⁴, N. Muthu Lakshmi⁵

¹N. Vallileka, Department of Computer Applications, PSNACET, Dindigul (Tamil Nadu), India.

²S. Jai Ganesh, Department of Computer Applications, PSNACET, Dindigul (Tamil Nadu), India.

³Nimmathi Satheesh, Department of Computer Applications, PSNACET, Dindigul (Tamil Nadu), India.

⁴R. SivaKumar, Department of Chemistry, PSNACET, Dindigul (Tamil Nadu), India.

⁵N. Muthu Lakshmi, TCS, Bangalore (Karnataka), India.

Abstract: This paper studies the sharing the messages of Air Quality Index (AQI) in Metropolitan areas. AQI specifies the percentage of pollutants mixed in air which creates problem in health. The pollutants level in the AQI values is between 0 to 500. Air pollution sensors are used to monitor the air pollution for outdoor environments and the cloud technology is used to display to public via private cloud. Prototype was developed with the aim to create awareness and public engagement in restoring the environment back to its healthy state. Using the prototype, the users can interact with the environment sensors in the field of view to access and visualize latest and historic environment measurements.

Keywords: AQI, Air Quality Index, Mobile Communication, Cloud with AQI, Air pollution Sensors.
Scope of the Article: Innovative Sensing Cloud and Systems

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C10840193S20

IJITEE Journal — Tue, 22 Aug 2023 10:24:19 +0000

Removing Speckle Noise in Synthetic Aperture Radar Images using Linear Filters
D. Suresh¹, S. Manimekalai², V. Nandakumar³, N. Dhanalakshmi⁴

¹Dr. D. Suresh, Assistant Professor, Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Dindigul (Tamil Nadu), India.

²S. Manimekalai, Assistant Professor, Department of English, PSNA College of Engineering and Technology, Dindigul (Tamil Nadu), India.

³V. Nandakumar, Assistant Professor, Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Dindigul (Tamil Nadu), India.

⁴Dr. N. Dhanalakshmi, Assistant Professor, Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Dindigul (Tamil Nadu), India.

Abstract: Speckle is a granular aggravation, typically demonstrated as a multiplicative noise that influences Synthetic aperture radar (SAR) pictures, just as every single cognizant picture. In the course of the most recent three decades, a few techniques have been proposed for the decrease of spot, or despeckling, in SAR pictures. The examination begins with the linear filtering, non-linear filtering, adaptive filtering, and hybrid filtering. In spite of the fact that the old style straight separating strategies have lower execution similarly, the hybridization between them beats than the as of late proposed techniques. Be that as it may, the cautious determination of such filters and their impacting request exceptionally influences the presentation of such filtering methodologies. In this paper, Hybrid filtering is proposed for SAR despeckling, which involves the improved variants of frost, median and mean filters. The presentation of the proposed framework is broke down and contrasted and the as of late SAR despeckling strategies. The outcomes demonstrate that the hybrid filters are focused as they can despeckle the SAR pictures superior to the current methods.

Keywords: Speckle Noise, SAR Images, Despeckling, NLM.
Scope of the Article: Image Security

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C10830193S20

IJITEE Journal — Tue, 22 Aug 2023 10:11:17 +0000

Sentiment Analysis Based Product Selection for Enhancing E-Commerce
P. Sudhakaran¹, M. Jaiganesh²

¹Dr. P. Sudhakaran, Professor, Department of CSE, SRM TRP Engineering College, Trichy (Tamil Nadu), India.

²M. Jaiganesh, Assistant Professor, Department of CSE, SRM TRP Engineering College, Trichy (Tamil Nadu), India.

Abstract: One of the fast growing, developing and highly used technology in various computing industries is data mining. Sentiment or opinion mining is a kind of data mining, where it follows the major processes of natural language processing. Nowadays, sentiment analysis meets a high demand. In this paper, it is aimed to consider the problems of sentiment analysis such as classification on opinion and attribute words, because it is the basic problem of sentiment analysis. This paper aimed to use one of the popular machine learning algorithms as Multi-Class Support Machine algorithm for classifying sentiment polarity with detailed description. The proposed method is implemented in Python software and experimented on onlineproduct-reviews data taken from Amazon.com. Sentence level and opinion level classification is obtained with promised outcomes. From the results it is noted that the proposed method outperforms than the existing method such as Naïve Bayes and Random Forest algorithms.

Keywords: Sentiment Analysis, Opinion Mining, E-Commerce, Polarity Classification, Machine Learning Algorithms, Customer Review Data, Amazon Data.
Scope of the Article: Software Product Lines

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