iosr-JCE   Volume-25 ~ Issue-5 ~ Sep - Oct. 2023

Abstract: The proliferation of the Internet of Things (IoT) has ushered in a new era of connectivity and automation, revolutionizing industries and enhancing everyday lives. However, the rapid growth and widespread adoption of IoT devices have also exposed an alarming landscape of cybersecurity threats that challenge the security and integrity of these interconnected ecosystems. This research paper delves into the intricate web of cybersecurity threats that loom over the IoT and explores the vulnerabilities that contribute to their proliferation. In this study, we provide an in-depth analysis of various cybersecurity threats that target IoT devices and networks, ranging from.......

Key Word: Internet of Things; Cybersecurity; Attack, Vulnerabilities

[1]. Altulaihan, E.; Almaiah, M.A.; Aljughaiman, A. Cybersecurity Threats, Countermeasures And Mitigation Techniques On The Iot: Future Research Directions. Electronics 2022, 11, 3330. Https:// Doi.Org/10.3390/Electronics11203330program (NCEP) Expert Panel On Detection, Evaluation, And Treatment Of Highblood Cholesterol In Adults (Adult Treatment Panel III) Finalreport. Circulation. 2002;106(25, Article 3143).
[2]. El Hakim, Ahmed. (2018). Internet Of Things (Iot) System Architecture And Technologies, White Paper..
10.13140/RG.2.2.17046.19521.
[3]. Sidhu S, Mohd BJ, Hayajneh T. Hardware Security In Iot Devices With Emphasis On Hardware Trojans. Journal Of Sensor And Actuator Networks. 2019; 8(3):42. Https://Doi.Org/10.3390/Jsan8030042
[4]. Dr. Shikha Gupta, Vaama Nikam, Tanay Mukadam, Prathmesh Deshmukh, Prathamesh Bhanse. Cyber Security For Internet Of Things, IJRASET, Volume 10 Issue X, Oct 22, ISSN 2321-9853.
[5]. Phillip Williams, Indira Kaylan Dutta, Hisham Daoud, Magdy Bayoumi, A Survey On Security In Internet Of Things With A Focus On The Impact Of Emerging Technologies, Internet Of Things, Volume 19, 2022, 100564, ISSN 2542-6605,.

Abstract: Forex trading plays an indispensable role in the financial market, and the profit reaped through it are high. The benefits made are subject to the volume exchanged and the currencies in which it is exchanged. Prediction of overseas change rate is quite tough due to the fact of its irregular and nonlinear data. There are many parameters which affect the forex rate prediction like the inflation rates, economic growth, interest rates, government and employment data which makes the prediction of forex rate difficult. The accuracies obtained using forex prediction algorithms had to be significantly improved for monetary gains.......

Key Word: Forex, ARIMA Model, Forex Prediction, Artificial Neural network (ANN), Backpropagation

[1]. Ramadhani, I., Jondri, & Rismala, R. (2016). Prediction of multi-currency exchange rates using correlation analysis and backpropagation. 2016 International Conference on ICT For Smart Society (ICISS). doi:10.1109/ictss.2016.7792850
[2]. Ranjit, S., Shrestha, S., Subedi, S., & Shakya, S. (2018). Foreign Rate Exchange Prediction Using Neural Network and Sentiment Analysis. 2018 International Conference on Advances in Computing, Communication Control and Networking
(ICACCCN).doi:10.1109/icacccn.2018.8748819
[3]. Dr. S. Kumar Chandar, Dr. M. Sumathi and Dr S. N. Sivanandam, "Foreign Exchange Rate Forecasting", Vol 9(8), Indian Journal of Science and Technology, 2016
[4]. Ananya Narula, Chandra Bhanu Jha and Ganapati Panda, Development and Performance Evaluation of Three Novel Prediction Models for Mutual Fund NAV Prediction, Annual Research Journal of Symbiosis Centre for Management Studies, Pune, Vol. 3, April 2015, pp. 227–238
[5]. Wang, S., Tang, Z., & Chai, B. (2016). Exchange rate prediction model analysis based on improved artificial neural network algorithm. 2016 International Conference on Communication and Electronics Systems (ICCES). doi:10.1109/cesys.2016.7889912.

Abstract: Loan business is one of the major income sources for bank. Loan default problem is a major issue for loan business. Loans, specifically whether borrowers repay the loan or default on it, have a significant impact on a bank's profitability. By anticipating loan defaulters, the bank is able to reduce its non-performing assets. Three primary predictive analytics techniques—I Data Collection, II Data Cleaning, and III Performance Assessment—are used to research the prediction of loan defaulters. Experimental investigations reveal that when it comes to loan forecasting, the KNN model performs better than the Decision tree model..

Key Word: Machine learning, Loan prediction, Banking, Decision tree, KNN

[1] Shraddha R. Nikam And Ashwini S. Kadam, - "Prediction For Loan Approval Using ML Algorithm," International Research Journal Of Engineering And Technology, April 2021.
[2] T.M. Luong, Harald Scheule & Nitya Wanzare, - "Impact Of Mortgage Soft Information In Loan Pricing On Default Prediction Using Machine Learning," International Review Of Finance, September 2022.
[3] Baodong Li, - "Online Loan Default Prediction Model Based On Deep Learning Neural Network," Hindawi Computational Intelligence And Neuroscience, August 2022.
[4] Weidong Chen & Yiheng Li, - "Entropy Method Of Constructing A Combined Model For Improving Loan Default Prediction: A Case Study In China," Journal Of The Operational Research Society, December 2019.
[5] T. Aditya Sai Srinivas, Somula Ramasubbareddy, And K.Govinda, - "Loan Default Prediction Using ML Techniques," Innovations In Computer Science And Engineering, March 2022.

Abstract: Smart phones is an essential tool for communication and have become an integral part of our daily lives due to quick advancements in technology. In India today, it is difficult for people to locate and employ close professionals to perform repairs and to provide maintenance service for their house and workplaces. Newcomers to the city are also faced with the challenge of not being able to find a good worker nearby due to the absence of such a system. It is crucial to create a platform that can use cutting-edge technological advancements to provide an intuitive and usable interface for both technical......

Key Word: Smart Phones, communication, maximise, cutting-edge, expertise

[1]. Beginning ASP.NET 4 In C# 2010 - Matthew Macdonald
[2]. .Net Framework With C#-Sweeta Bansal
[3]. SQL Server 2008 Bible -Paul Nielsen And Mike White
[4]. Www.Codeproject.Com
[5]. Www.W3school.Com/Aspnet/.

Abstract: In a world of fierce competition and continuous technological evolvement, computers occupy the primary niche in all sectors. One such pioneer of programming is Ada Lovelace, who not only contributed to the creation of basic computer programs but also put forth the incredible potential of computers. Therefore, computers have been influencing our everyday lives over the last 60 years, but not many know that the idea of this machine emerged almost 200 years ago. The underrepresentation of women in computers is a topic that dominates articles. It is frequently thought that women are less capable and not very inclined to work in the computer industry. But the truth is that computers began as a female-dominated....

[1]. Vehviläinen, "Gender And Computing In Retrospect: The Case Of Finland, In Ieee Annals Of The History Of Computing, Vol. 21, No. 02, Pp. 44–511, 1999.
[2]. Denise Gürer, 2002, Pioneering Women In Computer Science, Sigcse Bull. 34, 2 (June 2002), 175–180
Https://Doi.Org/10.1145/543812.543853
[3]. Martinez, Michael, And Lori Cameron, "The Epic Journey Of Women In Computing: Advances, Setbacks, And An Uncertain Future, Ieee Computer Society, May 13, 2023, Www.Computer.Org/Publications/Tech-News/Research/History-Of-Women-Programmers-In-Computing-Gender.
[4]. Saujani, Reshma. "Closing The Gender Gap In Science And Technology. United Nations, Www.Un.Org/En/Un-Chronicle/Closing-Gender-Gap-Science-And-Technology-0. Accessed August 1, 2023.
[5]. Sydell, L. (2017, August 10). Colleges Have Increased Women's Computer Science Majors. What Can Google Learn? Npr. Https://Www.Npr.Org/Sections/Alltechconsidered/2017/08/10/542638758/Colleges-Have-Increased-Women-Computer-Science-Majors-What-Can-Google-Learn

Abstract: The Water Purifier Service Supervision Mobile Application is an innovative solution designed to streamline the supervision and management of water purifier services. This mobile application empowers users to conveniently monitor, schedule, and track the maintenance and servicing of their water purifiers, ensuring the continuous supply of safe and clean water for drinking. It's crucial to have access to clean, safe drinking water. for maintaining public health and well-being. Regular maintenance and servicing of water purifiers are crucial to ensure optimal performance and water quality. However, keeping track of service schedules and coordinating with service providers can be challenging for users.....

Key words: Water, Purifier, Service, Mobile, Application.

[1]. Rangan, V. Kasturi, And Mona Sinha. "Hindustan Unilever's' Pureit'Water Purifier." Harvard Business School, Harvard (9-511-067) (2011). [2]. Chun, Yoon-Young, And Kun-Mo Lee. "Environmental Impacts Of The Rental Business Model Compared To The Conventional Business Model: A Korean Case Of Water Purifier For Home Use." The International Journal Of Life Cycle Assessment 22 (2017): 1096-1108. [3]. Zhou, Kun, Peng Zhao, And Fei Hu. "Research On Product Service System Design Based On Activity And Function—Take The Household Water Purifier As An Example." Procedia CIRP 83 (2019): 495-500. [4]. Hammer, Donald A., And Robert K. Bastian. "Wetlands Ecosystems: Natural Water Purifiers." Constructed Wetlands For Wastewater Treatment: Municipal, Industrial And Agricultural 5 (1989). [5]. Yin, Lihua, Et Al. "Waterpurifier: A Scalable System To Prevent The DNS Water Torture Attack In 5G-Enabled Siot Network." Computer Communications 199 (2023): 186-195.

Abstract: Background: Ranubedali is a village in Ranuyoso District, Lumajang Regency, East Java Province. Ranubedali Village has many potentials, starting from tourism, namely Lake Ranubedali tourism, and several other commodities, including coconut, avocado, and bananas. Most of the livelihoods of the residents of Ranubedali Village are farmers and traders. Ranubedali Tourism experienced its heyday in 2018-2019 with a significant increase in the number of visitors and increasing every day. However, the Covid-19 pandemic decreased tourists, so Ranubedali tourism was empty of visitors. Significant decrease in visitors to 50%. Based on the evaluation results, in 2022....

Key Word: Tourism Management. Tourist Management System. Prototyping Models.

[1]. Wall, G., & Nuryanti, W. (2014). Marketing Challenges And Opportunities Facing Indonesian Tourism. Marketing Issues In Pacific Area Tourism, 69-84. [2]. Shortt, G. (1994). Education And Training For The Indonesian Tourism Industry. Hospitality & Tourism Educator, 6(2), 79-79. [3]. Zulkarnain, L., & Abdullah, O. (2014). Indonesian Tourism Sector: A Potential Sector That Has Not Been Optimized. Australian Journal Of Basic And Applied Sciences, 8(23), 286-290. [4]. Jaelani, A. (2017). Halal Tourism Industry In Indonesia: Potential And Prospects. International Review Of Management And Marketing, 7(3), 25-34. [5]. Sabale, R. G., & Dani, A. R. (2012). Comparative Study Of Prototype Model For Software Engineering With System Development Life Cycle. IOSR Journal Of Engineering, 2(7), 21-24.

Abstract: The project's goal is to create a machine learning model that can classify the numerous sign language hand movements used for spelling. Classification on machine learning methods are taught on a set of image data in this user-independent model, and testing is done on an entirely other set of data. Because the pre-processing time was less when depth photographs were used for the image dataset, they produced better results than some of the earlier work. The datasets are subjected to the application of numerous machine learning methods, including convolution neural network (CNN). The CNN model is pre-trained on the image net dataset in an effort to improve its accuracy.....

Key Word: convolution neural network (CNN), Tensor flow, Sign Language (SL), SciPy, Support Vector Machine (SVM), Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA).

[1]. Joyeeta Singh, K. D. Indian Sign Language Recognition Using Eigen Value Weighted Euclidean Distance Based Classification Technique. International Journal Of Advanced Computer Science And Applications 4, 2 (2013). Neha V. Tavari, P. A. V. D.
[2]. Indian Sign Language Recognition Based On Histograms Of Oriented Gradient. International Journal Of Computer Science And Information Technologies 5, 3 (2014), 3657–3660.
[3]. Padmavathi. S, Saipreethy.M.S, V. Indian Sign Language Character Recognition Using Neural Networks. Ijca Special Issue On Recent Trends In Pattern Recognition And Image Analysis, Rtpria (2013).
[4]. Sakshi Goyal, Ishita Sharma, S. S. Sign Language Recognition System For Deaf And Dumb People. International Journal Of Engineering Research Technology 2, 4 (April 2013).
[5]. Vijay, P.K., Et Al., Recent Developments In Sign Language Recognition: A Review. International Journal On Advanced Computer Engineering And Communication Technology,2012.1(2):P.21-26.

Abstract: This paper focuses on basic types of cyber security and provides solutions and precautions for current cyber threats. The Current world walks hand in hand with Technology and network connections and Cyber Security helps us to work with it effectively and securely. Important data files will get used in the wrong way by hackers if we don't provide security to it. Cyber Security is essential not only in government and military areas but also in IT sectors, private companies, banks and in your day today life. An important data like it can be sensitive information, personal information, financial details can get illegal access without Cyber security. Currently in cyber security the trending topics are Automotive Hacking, Mobile is new target, Insider Threats, Remote Working......

Key Word: Cyber Security, Information, IT, Cyber Crime, Internet

[1]. Deborah Golden And Irfan Saif, ―The Future Of Cyber Survey 2019‖, Deloitte, 2019,
Https://Www2.Deloitte.Com/Us/En/Pages/Advis Ory/Articles/ Future-Of-Cyber-Survey.Html Https://Www2.Deloitte.Com/Content/ Dam/Deloitte/Covid19 2.
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Abstract: This comprehensive research investigates the utilization of cutting-edge Machine Learning (ML) techniques within the realm of gynecology. To assess the efficacy of our ML model, designed for forecasting weight gain during pregnancy, we adopt a multi-label approach. Our dataset comprises records from 50 expectant mothers who received care at a private hospital in Chennai. We employ three distinct classification algorithms: the J48 algorithm, a decision tree-based classifier, and Naive Bayes, to categorize the data into various classes. Our results showcase the exceptional performance of these algorithms. Specifically, the J48 algorithm, assessed through 10-fold cross-validation, achieves an impressive accuracy rate of 88%, a Kappa statistic of 0.8069, and exhibits minimal......

[1]. Geng, Y., Liang, P., Zhang, X., & Liu, X. (2019). Predicting Gestational Weight Gain Of Pregnant Women With Machine Learning Algorithms And Gynecological Care. BMC Pregnancy And Childbirth, 19(1), 85
[2]. Kumar, A., Lai, Y. H., & Hsu, W. C. (2017). Predicting Birth Weight Using Machine Learning Algorithms And Gynecological Care. International Journal Of Health Care Quality Assurance, 30(10), Pp. N807–818.
[3]. Lai, Y. H., Hsu, W. C., & Kumar, A. (2018). Predicting Birth Weight Of Newborns Using Machine Learning Algorithms And Gynecological Care. International Journal Of Health Care Quality Assurance, 31(4), 477–489.
[4]. Mwangi, E. W., Ndunda, E. N., & Muturi, P. M. (2017). Gestational Care And Predicting Birth Weight Of Newborns. Journal Of The National Medical Association, 109(2), Pp.105–110.
[5]. A.B.M. Shawkat Ali And Saleh A. Wasimi (2009). Data Mining Methods And Techniques, Cengage Learning India Private Limited, India.

Abstract: In mathematics, the search for exact formulas giving all the prime numbers, certain families of prime numbers or the n-th prime number has generally proved to be vain, which has led to contenting oneself with approxi- mate formulas [7]. The purpose of this article is to give a simple function to produce the list of all prime numbers. And then I give a generalization of this result and we show a link with the quantum mechanics and the attraction of black Holes. And I give a new proof of lemma 1 which gave a proof of the Riemann hypothesis [4].
Finally another excellent new proof o f the Riemann hypothesisis given and I deduce the proof of Hilbert Polya's conjecture.

Keywords : Prime Number, number theory, distribution of prime numbers, the law of prime numbers, the Gamma function, the Mertens function, quan- tum mechanics, black Holes, holomorphic function, Hilbert-Polya's conjec- ture, the Riemann hypothesis

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