iosr-JCE   Volume-25 ~ Issue-4 ~ July - Aug. 2023

Abstract:This Project Presents An Advanced Safety Charging Infrastructure Specifically Designed For Electric Cars, Showcasing A Comprehensive Solution That Combines Automation, Coordinated Control, And Cutting-Edge Safety Measures. By Developing And Demonstrating This Innovative System, We Address The Crucial Challenges Associated With Electric Vehicle (EV) Charging Services. The Primary Goal Of This Project Is To Provide Electric Vehicle Charging Station And Parking Garage Owners With An Advanced Solution That Not Only Ensures The Safety Of The Charging Process But Also Offers Significant Benefits In Terms Of Cost Savings And Operational Efficiency. Through The Integration Of Sophisticated.......

[1]. Https://Www.Lsp-International.Com/Surge-Protection-For-Electric-Mobility-Ev-Charger-Electrical-Vehicle/
[2]. Https://Www.Niti.Gov.In/Sites/Default/Files/2021-08/Handbookforevcharginginfrastructureimplementation081221.Pdf
[3]. Https://Www.Electrical-Installation.Org/Enwiki/Ev_Charging_-_Electrical_Installation_Design

Abstract: In The Financial Markets, Predicting Stock Prices Is Essential For Risk Management And Investing Strategies. The Long Short-Term Memory (LSTM) Algorithm And Deep Learning Techniques Are Used In This Study To Provide A Novel Method For Forecasting Nifty Stock Prices. The Study Makes Use Of A Broad Dataset From Yahoo Finance That Spans Five Years, From 2017 To 2023.Data Pre-Processing, Which Includes Data Cleansing, Normalisation, And Feature Engineering, Is The First Step In The Research Process. The Performance Of Elastic Net And LSTM, Two Distinct Stock Price Prediction Systems, Is Then Contrasted. Our Findings Show......

[1]. Brownlee, J. (2020). How to Develop LSTM Models for Time Series Forecasting. Machine Learning Mastery. Available online: Link
[2]. Hochreiter, S., & Schmidhuber, J. (1997). Long Short-Term Memory. Neural Computation, 9(8), 1735-1780.
doi:10.1162/neco.1997.9.8.1735
[3]. Karpathy, A. (2015). The Unreasonable Effectiveness of Recurrent Neural Networks. Andrej Karpathy Blog. Available online: Link
[4]. Liu, W., Luo, Y., & Wang, Z. (2020). Stock Price Prediction Based on LSTM Deep Learning Algorithm. International Journal of Online and Biomedical Engineering, 16(13), 104-115. doi:10.3991/ijoe.v16i13.17861
[5]. Nair, A., & Abraham, A. (2010). Stock Market Forecasting Using Hidden Markov Model: A New Approach. Expert Systems with Applications, 37(10), 7893-7897. doi:10.1016/j.eswa.2010.04.049

Abstract: In Contemporary Times, There Has Been A Notable Surge Of Interest In The Idea Of The Metaverse Within The Technological Sphere. In Essence, The Metaverse Represents A Virtual Domain That Runs Parallel To The Physical World And Can Be Accessed Through Digital Means. The Primary Objective Of This Composition Is To Delve Into The Prospective Opportunities That Retail Stores Can Leverage In The Metaverse And How This Digital Landscape Has The Potential To Revolutionize The Shopping Experience For Consumers. Through A Detailed Analysis, We Aim To Explore The Multifarious Advantages And Obstacles That Come With Operating A Retail Store In This Virtual Domain While Simultaneously Highlighting The Implications For Both Retailers And Consumers Alike.....

Keywords—Metaverse, Virtual, Retail Store

[1]. Https://Www.Tandfonline.Com/Doi/Abs/10.1080/0267257X.2013.835742
[2]. Https://Www.Ceeol.Com/Search/Article-Detail?Id=1049150
[3]. Https://Dergipark.Org.Tr/En/Pub/Jmv/Issue/71114/1126135
[4]. Https://Dl.Acm.Org/Doi/Abs/10.1145/3174910.3174952
[5]. Https://Venturebeat.Com/Datadecisionmakers/The-Metaverse-In-Retail-A-Game-Changer-Thats-Not-Ready-Yet/

Abstract: Books are knowledge fountains that also help the heart discover a way to use that knowledge wisely. You haven't found the proper book if you don't enjoy reading. With the amount of information available today, picking the right book is one of the most difficult challenges in gaining a thorough understanding of an idea.As a result, recommendation systems assist in navigating quickly and receiving important information.This study proposes a quick and user-friendly book recommendation system to assist readers in finding appropriate books. Based on the popularity filtering method, we applied data preprocessing and a collaborative filtering method. Finally, results based on online data are discussed..

Keywords—Recommendation system,Popularity filtering,Collaborative filtering

[1]. Kurmashov, Nursultan & Latuta, Konstantin & Nussipbekov, Abay. (2015). Online Book Recommendation System. 1-4. 10.1109/ICECCO.2015.7416895.
[2]. Su, Xiaoyuan & Khoshgoftaar, Taghi. (2009). A Survey Of Collaborative Filtering Techniques. Adv. Artificial Intellegence. 2009. 10.1155/2009/421425.
[3]. Linden, Greg & Smith, B. & York, J.. (2003). Linden G, Smith B And York J: 'Amazon.Com Recommendations: Item-To-Item Collaborative Filtering', Internet Comput. IEEE, , 7. Internet Computing, IEEE. 7. 76 - 80. 10.1109/MIC.2003.1167344.
[4]. Sariki, Tulasi & Kumar, B.G.. (2018). A Book Recommendation System Based On Named Entities. Annals Of Library And Information Studies. 65. 77-82.
[5]. Sariki, Tulasi & Kumar, G. (2022). An Aggrandized Framework For Enriching Book Recommendation System AN AGGRANDIZED FRAMEWORK FOR ENRICHING BOOK RECOMMENDATION SYSTEM. Malaysian Journal Of Computer Science. 35. 111-127. 10.22452/Mjcs.Vol35no2.2

Abstract:The challenges of elections in Nigeria have led to the introduction of a technological device called the Bimodal Voter Accreditation System (BVAS). This however didn t usher in the needed free and fair elections due to the compromise of the security and the outright absence of some security features that would have made the device difficult and almost impossible for intruders to attack. The researchers took time to elu cidate on the challenges, features and likely security breaches. They went further in the research to opine some solutions which in their own view would help solve the issue of security and engender free and fair election if all other factors are held cons tant.

Keywords—Bimodal Voter Accreditation System (BVAS), Election, voter accreditation, INEC, Biometric voter accreditation

[1] Ali , Guma , Mussa Ally Dida , And Anael Elikana Sam . (2020). Two Factor Authentication Scheme For Mobile Money : A Review
Of Threat Models And Countermeasures Future Internet 12, No. 10: 160. Https://Doi.Org/10.3390/Fi12100160
[2]. Anbu Malar , M . B . B ., & Prabhu , J . (2021). Trust Based Authentication Scheme (Tbas) For Cloud Computing Environment With
Kerberos Protocol Using Distributed Controller And Prevention Attack. International Journal Of Pervasive Computing And
Communications , 17(1), 78 88. Https://Doi.Org/10.1108/ IJPCC 03 2020 0009
[3]. Bowyer , K W ., And Burge , M J . (2016) Handbook Of Iris Recognition ; Springer : Berlin , Germany
[4] De Luca , A .; Lindqvist , J . (2015) : Is Secure And Usable Smartphone Authentication Asking Too Much? Computer2015 ,48, 64 68.
[5]. Ellison , N . B . & Boyd, D. (2013). Sociality Through Social Network Sites . In Dutton , W . H . Ed .), The Oxford Handbook Of Internet
Studies . Oxford : Oxford University Press , P p. 151 172.

Abstract: Customer turnover is a global issue that has an impact on the banking business. This study aims to raise knowledge of whether a customer is likely to switch banks depending on requested services. The several ensemble machine learning algorithms namely, Ada-Boost (AD), Random Forest (RF), Light Gradient Boosted Machine (LGB), and CatBoost (CT) combined to make the proposed technique for our research called Super learner. The study compared the super learner that comes from ensembles to the one produced under the combination and configuration of weaker learners machine learning models precisely, Decision Tree (DT), K Nearest Neighbours (KNN), Support.......

Keywords—Customer churn, Machine Learning

[1]. Z. Wen, J. Yan, L. Zhou, Y. Liu, K. Zhu, Z. Guo, Y. Li, And F. Zhang, "Customer Churn Warning With Machine Learning," In The Euro-China Conference On Intelligent Data Analysis And Applications. Springer, 2018, Pp. 343–350.
[2]. R. A. De Lima Lemos, T. C. Silva, And B. M. Tabak, "Propension To Customer Churn In A Financial Institution: A Machine Learning Approach," Neural Computing And Applications, Pp. 1–18, 2022.
[3]. Pwc, "Retail Banking 2020 Evolution Or Revolution?" 2020. [Online]. Available:
Https://Www.Pwc.Com/Gx/En/Banking-Capital-Markets/Banking-2020/Assets/Pwc-Retail-Banking-2020-Evolution-Or-Revolution.Pdf
[4]. Z. Wen, J. Yan, L. Zhou, Y. Liu, K. Zhu, Z. Guo, Y. Li, And F. Zhang, "Customer Churn Warning With Machine Learning," In The Euro-China Conference On Intelligent Data Analysis And Applications. Springer, 2019, Pp. 343–350.
[5]. A. Sharma And P. Kumar Panigrahi, "A Neural Network Based Approach For Predicting Customer Churn In Cellular Network Services," International Journal Of Computer Applications, Vol. 27, Pp. 26–31, 08 2011.

Abstract: This paper presented a critical study of file-less malware attacks and the detection techniques for mitigating these attacks on computer systems or software platforms. The study started by presenting an overview of file-less malwares, types of the file-less malwares that can be encountered and various techniques adopted in detecting and tackling the challenges posed by file-less malwares. The work studied signature-based technique, behavior-based technique, heuristic methods, IoT-based methods and machine learning methods. Further in the work, we introduced adversarial......

Keywords—File-less Malware, Machine Learning, LOLBins, LOLScripts, Adversarial Perturbation

[1]. Fortinet.Com (2023), Top 20 Most Common Types Of Cybersecurity Attacks. Online At
Https://Www.Fortinet.Com/Resources/Cyberglossary/Types-Of-Cyber-Attacks Accessed May, 2023.
[2]. Patten D., (2017) The Evolution To File-Less Malware (2017). Http://Www.Infosecwriters.Com/Papers/Dpatten File-Less.Pdf.
[3]. Kumar S, Dohare U, Kumar K, Prasad Dora D, Naseerqureshi K, Kharel R (2019) Cybersecurity Measures For Geocasting In Vehicular Cyber Physical System Environments. IEEE Internet Things J 6(4):5916–5926.
Https://Doi.Org/10.1109/ JIOT.2018.2872474
[4]. Living Off The Land Binaries And Scripts - (Lolbins And Lolscripts) (2019). Https://Github.Com/LOLBAS-Project/LOLBAS
[5]. Sudhakar R. And Kumar S. (2020) "An Emerging Threat File-Less Malware: A Survey And Research Challenges" Cybersecurity: Https://Doi.Org/10.1186/S42400-019-0043-X

Abstract: Security is a fundamental need for both nations and individuals. Day by day, more and more security systems are incorporating emerging technology. Particularly, security cameras are essential. However, keeping track of all the security cameras would not be practical or sustainable. Smart security systems are required as a result. The necessity of developing intelligent security systems employing image processing methods for incident prevention cannot be overstated. In this work, images from two security cameras are analyzed, and an intelligent security system is created that, when a potentially harmful picture is identified in the image, takes the appropriate safeguards.

Keywords: Image processing; Intelligent Security System; Security

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[2]. M. Smids, Background Subtraction For Urban Traffic Monitoring Using Webcams, Master Thesis, Universiteit Van Amsterdam, Fnwi, 2006.
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[4]. R. Collins, O. Amidi, T. Kanade, An Active Camera System For Acquiring Multiview Video. In: Proc. Ieee International. Conf. 2002, Image Processing.
[5]. Saif K. Jarallah And Sawsen Abdulhadi Mahmood," Query-Based Video Summarization System Based On Light Weight Deep Learning Model", International Journal Of Intelligent Engineering And Systems, Vol.15, No.6,Pp 247-262, 2022

Abstract: The Smart Campus Surveillance-Based Guidance System is a project designed to enhance the security and guidance of students on university campuses using advanced surveillance technologies. Our system employs a combination of smart technologies and physical infrastructure to provide improved services, decision-making, and sustainability. Our project aims to address the problem of students wandering around the campus, getting lost, and missing classes, which can lead to academic and social problems. The system monitors students' movements and guides them to their respective classrooms using a real-time guidance system. The front-end and back-end of the system are designed using........

[1] C.T. Yang, S.T. Chen, J.C. Liu, Et Al. "On Construction Of An Energy Monitoring Service Using Big Data Technology For The Smart Campus,"Cluster Computing, Vol.23, No.1, Pp.265-288, March, 2020.
[2] I. Yaqoob, I.A.T. Hashem, A. Ahmed, Et Al. "Internet Of Things Forensics: Recent Advances, Taxonomy, Requirements, And Open Challenges," Future Generation Computer Systems, Vol.92, Pp.265- 275, March, 2019.
[3] Y. Lin, J. Yang, Z. Lv, Et Al. "A Self-Assessment Stereo Capture Model Applicable To The Internet Of Things",
Sensors, Vol.15, No.8, Pp. 20925-20944, 2015.
[4] J. Li, G. Feng, W. Wei, "Psotrack: A RFID-Based System For Random Moving Objects Tracking In Unconstrained Indoor Environment" IEEE Internet Of Things Journal, 2018, Vol.5, No.6, Pp.4632-4641.
[5] W. Wei W, M. Guizani M, S.H. Ahmed Et Al. "Guest Editorial: Special Section On Integration Of Big Data And Artificial Intelligence For Internet Of Things", IEEE Transactions On Industrial Informatics, Vol. 16, No.4, Pp.2562-2565, 2020.
[6] M. Noura, M. Atiquzzaman, M. Gaedke. "Interoperability In Internetof Things: Taxonomies And Open Challenges," Mobile Networks And Applications, Vol.24, No.3, Pp.796-809, July, 2019.

Abstract: A kind of biometric recognition called vein identification systems uses vascular architecture to identify people. One of these approaches is identification based on hand-wrist vein pattern. Hand-wrist vein pictures acquired from persons utilizing an infrared light source with a wavelength of 850 nm were segmented in this research by running them through several image processing techniques. The scale-independent feature transformation (SURF) approach was used to extract critical points from segmented pictures. The SURF approach produces characteristics such as rotation, camera angle, ambient light intensity, and so on........

Keywords: Hand-wrist identification, infrared vein imaging, feature extraction, and surfing

[1]. J. M. Cross And C. L. Smith, "Thermographic Imaging Of The Subcutaneous Vascular Network Of The Back Of The Hand For Biometric Identification", Proceedings Of The 29th International Carnahan Conference On Security Technology, Institute Of Electrical And Electronics Engineers, 20-35, 1995.
[2]. Sang-Kyun Im, Hyung-Man Park, Young-Woo Kim, Sang-Chan Han, Soo-Won Kim, Chul-Hee Kang, And Chang-Kyung Chung, "An Biometric Identification System By Extracting Hand Vein Patterns", Journal Of The Korean Physical Society, 38(3): 268-272, March 2001.
[3]. Faruk Boyraz And Mustafa Zahid. "Development Of A Low-Cost Microcomputer-Based Vein Imaging System." Infrared Physics And Technology, Vol. 98, Pp. 27-35, 2019.
[4]. M. Z., Boyraz, O. F., Akgul, A., And Hussain, I. Dorsal Hand Vein Image Encryption On A Microcomputer. 2019 Ieee Access, 7, 60850-60867.
[5]. "Finger Vein Recognition Based On Finger Crease Location," Z. Lu, S. Ding, And J. Yin, Journal Of Electronic Imaging, Vol. 25, No. 4, P. 043004, Nov. 2016.

Abstract: Artificial intelligence is a fairly new and transformative technology. There are a lot of mixed opinions in the general public around this technology. This study was conducted to analyze the effects of increasing use of AI on people working in the technology industry. Preliminary findings suggest that AI has significantly impacted the sector, enhancing efficiency, automating repetitive tasks, and generating new job roles. However, concerns related to job security, skill requirements, and ethical implications of AI are also highlighted. This study adds to the previous research on the....

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