iosr-JCE   Volume-26 ~ Issue-5 ~ Sep. - Oct. 2024

Abstract: Internet banking has become a crucial aspect of modern financial transactions, enabling customers to access their account information and perform various transactions from anywhere. Ensuring the security of these transactions is one of utmost importance, and this is where authentication protocols come into play. One such protocol is Kerberos, which is widely used for secure authentication in many applications, including internet banking. In this paper....

Keywords: Internet Banking, Cyber Security, Authentication, Kerberos, Multi factor authentication server, Replay attack..

[1] Martins, C., Oliveira, T. And Popovič, A., 2014. Understanding The Internet Banking Adoption: A Unified Theory Of Acceptance And Use Of Technology And Perceived Risk Application. International Journal Of Information Management, 34(1), Pp.1-13.
[2] Dhanalakshmi, R., Prabhu, C. And Chellappan, C., 2011. Detection Of Phishing Websites And Secure Transactions. Ijcns, 1(11), Pp.15-21
[3] Dodge, R.C., Carver, C. And Ferguson, A.J., 2007. Phishing For User Security Awareness. Computers & Security, 26(1), Pp.73-80.
[4] Gharaibeh, N., 2013. The Impact Of Customer Knowledge On The Security Of E-Banking. International Journal Of Computer Science And Security (Ijcss), 7(2), P.81.
[5] Council, F.F.I.E., 2005. Authentication In An Internet Banking Environment. Financial Institution Letter, Fil-103-2005. Washington, Dc: Federal Deposit Insurance Corp.(Fdic). Retrieved March, 18, P.2005.

Abstract: The use of technology in all parts of our lives has greatly increased in recent years, nowadays, people tend to search for everything online before they make decisions. However, looking for rental houses online is not common in Bangladesh, it is not because people do not want to, but because there are not many online platforms focusing on residential rentals. For the mentioned reason we developed a house rental finding web application using Laravel, Vue.js, and PHP-ML library. Laravel handles the backend whereas Vue.js manages the frontend, we utilized PHP Machine Learning Library's Linear Regression and K-Nearest Neighbours........

Keywords: K-Nearest Neighbors (K-NN), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Machine Learning (ML), JavaScript (JS), Hypertext Preprocessor (PHP).

[1] Afzal, S., Rouf, T., Qadir, S., & Shah, S. (2021). Online Rental Housing. "Journal Of Emerging Technologies And Innovative Research (Jetir)", 8(11). Retrieved From Https://Www.Jetir.Org
[2] Bproperty. (2018). "Bproperty." Retrieved From Https://Www.Bproperty.Com/Blog/Successful-Launch-Bproperty-Marketplace-Banani G. Gommans, H. P., Njiru, G. M., & Owange, A. N. (2014). Rental House Management System. "International Journal Of Scientific And Research Publications", 4(11). Retrieved From Www.Ijsrp.Org
[3] L. Laravel. (2023). "Laravel - The Php Framework For Web Artisans." Retrieved From Https://Laravel.Com
[4] N. Neehal, N. (2017). "Machine Learning Algorithm (1st Ed.)." Packt Publishing
[5] P. Php-Ml. (2021). "Php-Ml: Machine Learning Library For Php." Retrieved From Https://Php-Ml.Org

Abstract: Devika AI is an innovative open-source platform designed to revolutionize software development through AI-powered code generation. Leveraging advanced natural language processing (NLP), machine learning algorithms, and a modular architecture, Devika AI translates high-level human instructions into executable code across multiple programming languages. This paper presents a comprehensive overview of Devika AI's architecture, methodologies, and functionalities. We discuss its ability to improve developer productivity, reduce coding errors, and facilitate collaborative development. Experimental results demonstrate Devika AI's effectiveness in various coding tasks, highlighting its potential as a free and accessible alternative to proprietary AI coding assistants. The implications of Devika AI's adoption on the future of software development are also explored..

Keywords: Devika AI, Code Generation, Natural Language Processing, Open-Source Software, Machine Learning, Software Development Automation.

[1] J. Doe, "Ai-Powered Code Generation: A Comparative Study Of Devika Ai And Proprietary Tools," Ieee Transactions On Software Engineering, Vol. 45, No. 3, Pp. 231-245, March 2024.
[2] A. Smith, Open-Source Software Development: Principles And Practices, 3rd Ed., New York: Wiley, 2023.
[3] L. Chen, "Nlp Techniques In Ai-Driven Development Tools," Journal Of Artificial Intelligence Research, Vol. 17, No. 2, Pp. 102-118, February 2023.
[4] Devika Ai Official Documentation, "Getting Started With Devika Ai," Available: Https://Devika-Ai.Org/Docs.
[5] M. Kumar, "Impact Of Open-Source Collaboration On Ai Development," Proceedings Of The 2023 Ieee International Conference On Software Engineering, May 2023.

Abstract: Neural Machine Translation (NMT) is a state of the art of machine translations that uses neural network models to translate text from one language to another. Unlike traditional machine translation methods, which rely on statistical models and rule-based systems, NMT leverages the power of deep learning, specifically using techniques such as recurrent neural networks (RNNs), long short-term memory networks (LSTMs), or more recently, transformers. Neural Machine Translation represents a significant dive forward in the field of automatic translation, leveraging.....

Keywords: Machine translation, Neural network, Architectures of neural network, Data set, Bangla-English language pair, BLEU score

[1] Jordi Armengol‐Estapé, Marta R. Costa‐Jussà (2021), Semantic And Syntactic Information For Neural Machine Translation - Injecting Features To The Transformer. Https://Doi.Org/10.1007/S10590-021-09264-2
[2] Zhixing Tan, Shuo Wang, Et Al. (2020). Neural Machine Translation: A Review Of Methods, Resources, And Tools. Www.Keaipublishing.Com/En/Journals/Ai-Open
[3] Philipp Koehn (2017). Neural Machine Translation. Arxiv:1709.07809v1
[4] Brown, T. B., Mann, B., Ryder, N., Et Al. (2020). Language Models Are Few-Shot Learners. *Arxiv Preprint Arxiv:2005.14165*.
[5] Vaswani, A., Shazeer, N., Parmar, N., Et Al. (2017). Attention Is All You Need. *Advances In Neural Information Processing Systems*, 5998-6008..

Abstract: Background: Indeed, Object-Oriented Programming (OOP) has emerged as one of the major fundamental paradigms in today's world of software development as it contains principles that enhance modularity, reusability, and maintainability of software. This article explores deeper into some of the facets of OOP aspects as exhibited in some of the most frequently used programming languages ranging from Java, Python, C++, and C# with an intent of offering.....

Keywords: Object-Oriented Programming, Encapsulation, Inheritance, Polymorphism, Abstraction.

[1] Adetiba, E., Adeyemi-Kayode, T. M., Akinrinmade, A. A., Moninuola, F. S., Akintade, O. O., Badejo, J. A., Obiyemi, O. O., Thakur, S. & Abayomi, A. (2021). Evolution Of Artificial Intelligence Programming Languages - A Systematic Literature Review. Journal Of Computer Science, 17(11), 1157-1171. Https://Doi.Org/10.3844/Jcssp.2021.1157.1171
[2] Asha R. M., Kavana M. D., Parvathy S. J., Shreelakshmi C M., (2017) Object-Oriented Programming And Its Concepts. International Journal For Scientific Research & Development| 5(9) 840-842.
[3] Fawzi A., & Amjad M., A., (2017) Comparative Study On The Effect Of Multiple Inheritance Mechanism In Java, C++, And Python On Complexity And Reusability Of Code. International Journal Of Advanced Computer Science And Applications 8(6) 109-116.
[4] Goel, B. M.; Bhatia, P. K Analysis Of Reusability Of Object-Oriented System Using Ck Metrics. International Journal Of Computer Applications, 2012, Vol. 60, No. 10, Pp 32-36.
[5] Gupta A.; Dashore P. An Approach To Analyse Software Reusability Of Object Oriented Code. International Journal Of Research In Science & Engineering, 2017, Volume 3, Issue 1..

Abstract: Finding new ways to manage water resources becomes even more relevant today, as the growing demand for food globally combines with challenges like climate change and water scarcity. This research paper attempts to discover the automated water regulation systems that utilize advanced technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and data interpretation to upgrade irrigation practices and boost sustainable resource management. By using sensors that keep the soil moisture and the environmental conditions in check, accurate modifications can be made to the irrigation being provided. Keeping a check can help reduce water wastage by up to 30% and increase crop yield by an average of 15%. This study amplifies the productivity of smart meters and....

[1] Gonçalves, R., Soares, J. J. M., And Lima, R. M. F. "An Iot-Based Framework For Smart Water Supply Systems Management." Future Internet, Vol. 12, No. 114, 2020.
Https://Doi.Org/10.3390/Fi12070114
[2] Karamoutsou, A., And Psilovikos, A. "Deep Learning For Water Resource Management: A Case Study On Kastoria Lake." Water Resources Management, 2022. Https://Doi.Org/10.3390/W13233364
[3] Ministry Of Housing And Urban Affairs. "Part A, Chapter – 14: Automation Of Water Supply System." 2021.
Https://Mohua.Gov.In/Upload/Uploadfiles/Files/Part-A-Chapter-14-Automation-Of-Water-Supply-System%281%29.Pdf.
[4] Olsson, Gustaf. "Urban Water Supply Automation–Today And Tomorrow." AQUA—Water Infrastructure, Ecosystems And Society 70.4 (2021): 420-437.
Https://Doi.Org/10.2166/Aqua.2020.115
[5] Soares Ascenção, Érico, Et Al. "Applications Of Smart Water Management Systems: A Literature Review." Water 15.19 (2023): 3492.

Abstract: A neurological condition known as an autism spectrum disorder (ASD) profoundly impacts an individual's lifelong ability to engage and interact with others. ASD is an illness that can be recognized at early stages in a person's life and is often classified as a "behavioral disease" due to the presence of numerous symptoms that frequently manifest within the first two years of life, as per what most people believe about autism theory, these challenges typically emerge during childhood and endure into adolescence and adulthood [1].
In response to the growing popularity of medical diagnosis, machine learning techniques [2] are used to help doctors.....

Keywords: Autism, Convolutional neural network (CNN); Artificial Neural Network (ANN); K- Nearest Neighbors (KNN); Logistic Regression (LR); Support Vector Machine (SVM) [5].

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Abstract: The fashion industry is one of the most globalized sectors, featuring a complex and widespread supply chain. Often, clothing is designed in one country, produced in another, and then distributed and sold across multiple international markets. This global scope and complexity necessitate an agile approach to supply chain management. Agile supply chains are engineered to be flexible, responsive, and adaptable, enabling companies to swiftly respond to shifts in consumer demands and market conditions. By adopting agile principles, fashion companies can more effectively navigate the intricacies of global operations, ensuring that products reach the appropriate markets at the right time, thereby sustaining competitiveness and meeting consumer expectations in a fast-paced industry.

[1] Daly, L., Towers, N., & Lambert, S. (2004). Lean Or Agile: A Solution For Supply Chain Management In The Textiles And Clothing Industry.
[2] Oksanen, L. (2023). Agile Fashion Retail: Exploring The Enablers And Challenges In Agile Procurement And Supply Chain Management.
[3] Uman, R., & Sommanawat, K. Strategic Flexibility, Manufacturing Flexibility, And Firm Performance Under The Presence Of An Agile Supply Chain: A Case Of Strategic Management In The Fashion Industry.
[4] Banerjee, A. (2020) Agile Supply Chain Management.
[5] Çelikkol, Ş., Yikilmaz, İ., & Sağbaş, M. (2021) Agile Supply Chain Management.

Abstract: Plant diseases are becoming more common, which is a serious threat to profitability of agriculture worldwide and requires the creation of reliable and efficient disease detection technologies. This work uses machine learning (ML) and deep learning (DL) approaches to give an extensive assessment of previous research on plant leaf disease identification. We examine and evaluate the many approaches used in the last several research, emphasizing the advantages, disadvantages, and useful uses of each. The study covers both sophisticated deep learning designs.....

Keywords: Convolution Neural Network, Deep Learning Machine Learning, Plant Disease Detection, Support Vector Machine

[1] P. Chaitanya Reddy, R. M. S. Chandra, P. Vadiraj, M. Ayyappa Reddy, T. R. Mahesh, And G. Sindhu Madhuri, "Detection Of Plant Leaf-Based Diseases Using Machine Learning Approach," In 2021 Ieee International Conference On Computation System And Information Technology For Sustainable Solutions (Csitss), 2021.
[2] D. Mishra, A. Pandey, Deepanshu, And V. Sharma, "Plant Image Disease Detection Using Deep Learning," In 2023 4th International Conference On Smart Electronics And Communication (Icosec), 2023.
[3] M. Belmir, W. Difallah, And A. Ghazli, "Plant Leaf Disease Prediction And Classification Using Deep Learning," In 2023 International Conference On Decision Aid Sciences And Applications (Dasa), 2023.
[4] Shruti Et Al., "Plant Leaf Disease Detection Using Machine Learning," In 2023 1st International Conference On Circuits, Power And Intelligent Systems (Ccpis), 2023.

Abstract: The rise of digital media and the widespread use of social platforms have transformed the way information is disseminated globally. While this has significantly enhanced the speed and reach of news distribution, it has also contributed to the proliferation of misinformation, commonly referred to as "fake news." The impact of such misinformation is profound, influencing public opinion, eroding trust in media institutions, and undermining democratic processes. As a result, there is an urgent need for systems capable of detecting and mitigating the spread of fake news....

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