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

Abstract: As digital technologies evolve, so do the methods employed by cybercriminals to exploit vulnerabilities within browser and mobile environments. This paper explores advanced fraud threats such as VPN detection evasion, browser spoofing, mobile device factory resets, jailbroken phones, user-initiated app cloning, and Android emulators and tampering. We discuss how these threats are misused and outline advanced detection techniques to mitigate risks. The paper emphasizes the importance of implementing robust security measures to protect against sophisticated fraud tactics in browser, Android, and iOS platforms.

[1] Alshboul, A., & Omar, K. (2020). Vpn Traffic Detection Techniques: A Survey. *Ieee Access*, 8, 136879-136892.
[2] Maxmind. (2023). *Geoip2 Databases*. Retrieved From Https://Www.Maxmind.Com
[3] Nikiforakis, N., Et Al. (2013). Cookieless Monster: Exploring The Ecosystem Of Web-Based Device Fingerprinting. *Ieee Symposium On Security And Privacy*, 541-555.
[4] Owens, R., & Matthews, P. (2019). An Analysis Of Android Device Security: Android Vs. Ios. *Journal Of Information Security*, 10(2), 123-133.
[5] Ren, J., Et Al. (2016). Recon: Revealing And Controlling Pii Leaks In Mobile Network Traffic. *Acm Symposium On Systems And Information Security*, 361-372.

Abstract: This all-inclusive research paper plunges into the transformative nature of artificial intelligence (AI) in healthcare, emphasizing its ability to change patient care and administrative activities. The investigation examines systematically how AI technologies are creating major improvements towards patients' outcomes and enhanced operational efficiency within the healthcare systems. From diagnostics to personalized treatment plans and administrative tasks, AI is being integrated using sophisticated algorithms in numerous aspects of healthcare delivery....

[1] "The Potential For Artificial Intelligence In Healthcare." National Library Of Medicine, Https://Www.Ncbi.Nlm.Nih.Gov/Pmc/Articles/Pmc6616181/.
[2] Aiims Rajkot. "Harnessing Artificial Intelligence In Healthcare Education And Research: A Multifaceted Approach." Aiims Rajkot,
Https://Www.Aiimsrajkot.Edu.In/Sites/Default/Files/Inline-Files/Ai%20module%20aiims%20rajkot-rnessing%20artificial%20intelligence%20in%20healthcare%20education%20and%20research-A%20multifaceted%20approach%20%281%29.Pdf.
[3] "Ai In Healthcare." Foresee Medical, Https://Www.Foreseemed.Com/Artificial-Intelligence-In-Healthcare.
[4] "Artificial Intelligence In Healthcare: Past, Present And Future." Stroke And Vascular Neurology, Https://Svn.Bmj.Com/Content/2/4/230..

Abstract: Organ donation and transplantation represent critical components of modern medicine, offering life-saving solutions for individuals with organ failure. Despite advancements in medical practices, significant gender disparities exist within these processes, where women disproportionately contribute as donors while men are predominantly recipients. This study integrates an in-depth statistical analysis of data from major registries like the United Network for Organ Sharing (UNOS) and the Organ Procurement and Transplantation Network (OPTN), utilizing chi-square tests, logistic regression, multivariate analysis, and stratified sampling to elucidate these....

[1] Doe, J., & Smith, L. (2019). Gender Differences In Organ Donation: A Statistical Analysis Of Living And Deceased Donors. Journal Of Transplantation Research, 42(3), 215-230. Https://Doi.Org/10.1234/Jtr.2019.0321
[2] Lee, H., & Chang, Y. (2020). Socioeconomic Factors Influencing Organ Donation: A Global Perspective. International Journal Of Health Equity, 58(4), 987-1003. Https://Doi.Org/10.5678/Ijhe.2020.0458
[3] Organ Procurement And Transplantation Network (Optn). (2022). National Data On Organ Donation And Transplantation. Retrieved From Https://Optn.Transplant.Hrsa.Gov/Data/
[4] Thompson, R., & Garcia, M. (2017). Healthcare Biases In Organ Transplantation: An Evaluation Of Gender Disparities. Clinical Transplantation, 31(12), E13045. Https://Doi.Org/10.1111/Ctr.13045
[5] United Network For Organ Sharing (Unos). (2021). Gender Dynamics In Organ Transplantation: Annual Report. Retrieved From Https://Unos.Org.

Abstract: The adoption of electric vehicles as a means of vehicle type that can replace the traditional internal combustion engine vehicles has led to the improvement of the battery technology and power management systems. However, there is still one of the most important concerns that can be stated: the reliability and effectiveness of the charging and discharging of EV. There are consequences of faulty charging and these include; degradation of the battery, low vehicle performance, and risks of fire or overheating.
AI has thus been utilized to enhance the dependability of EV systems especially in the aspects of fault detection and warning systems. Therefore, due to its feature of analyzing huge data and giving out the likely occurrence of certain....

[1] Liamgchen & Kawenyenwong, (2020). Ai-Based Fault Diagnosis In Electric Vehicle Charging Systems: From A Deep Learning Perspective. Jour. Power Sources, 482 (1), P. 87-102.
[2] Gupta, A. And Shen, P. , ", (2019). A Case Was Made With An Example Of Electric Vehicle Charge Cycles Anomaly Detection Through Machine Learning. 10 (4), Pp. 456-470 Ieee Transactions On Smart Grid.
[3] Kumar, R. , Patel, S. And Lee, J. , (2020). Cnn Based Fault Diagnosis Of Electric Vehicle Batteries. Ijepem International Journal Of Electrical Power & Energy Systems (2019) 118, 278–291 10. 1016/J. Ijepes. 2019. 118. 278.
[4] Lin, X. And Zhang, Y,(2020). Random Forests For Fault Detection In Electric Vehicles: A Real Time Approach. Ieee Transactions On Transportation Electrification, 6(2), Pp. 430–440.
[5] Wang, Z. , Li, H. And Zhao, M. , (2019). Svm In Fault Diagnosis For Ev Bms: Systematic Review. Journal Of Energy Storage 23(2), 167–181.

Abstract: A. Initial Investment Solar Power: Sensor technology doesn't really vary a great deal in each cell, so you don't need to purchase a card specifically for each phone. But you do have to learn how to administer multiple cards. Solar photovoltaic (PV) panels costs declined more than 80 percent over the past decade, and are now more affordable for residential and commercial customers. The government of developing countries including India has introduced several subsidies and incentives to mitigate further financial burden of solar installation. Capital subsidies, tax rebates and accelerated depreciation....

[1] Boyle, G. (2004). Renewable Energy: Power For A Sustainable Future. Oxford University Press.
[2] Tester, J. W., Drake, E. M., Driscoll, M. J., Golay, M. W., & Peters, W. A. (2005). Sustainable Energy: Choosing Among Options. Mit Press.
[3] International Energy Agency (Iea). (2020). World Energy Outlook 2020. Iea Publishing. Https://Www.Iea.Org/Reports/World-Energy-Outlook-2020
[4] International Renewable Energy Agency (Irena). (2019). Renewable Power Generation Costs In 2019. Irena. Https://Www.Irena.Org/Publications/2020/Jun/Renewable-Power-Costs-In-2019
[5] Timilsina, G. R., & Shah, K. U. (2016). Solar Energy: Markets, E.

Abstract: Résumé Cette étude explore l'importance de l'intégration de la prise de décision basée sur les données (data-driven decision making) et de l'analyse prédictive pour l'optimisation de la performance et la gestion proactive des risques dans les entreprises congolaises modernes. L'accent est mis sur la sous-utilisation des données dans les processus décisionnels et l'impact de cette lacune sur la performance des entreprises en République Démocratique du Congo (RDC). L'analyse examine comment la transformation digitale, à travers des outils tels que les ERP (Enterprise Resource Planning), les CRM (Customer Relationship Management) et les plateformes de Business...

[1] Davenport, T. H., & Harris, J. G. (2007). La Compétition Par L'analyse : La Nouvelle Science De La Victoire. Presses De La Harvard Business Review.
[2] Provost, F., & Fawcett, T. (2013). La Science Des Données Pour Les Affaires : Ce Que Vous Devez Savoir Sur L'exploration Des Données Et La Pensée Analytique Des Données. O'Reilly Media.
[3] Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Intelligence D'affaires Et Analyse : Des Mégadonnées A Un Grand Impact. MIS Quarterly, 36(4), 1165-1188.
[4] Brynjolfsson, E., & Mcafee, A. (2014). L'âge De La Seconde Machine : Travail, Progrès Et Prospérité A Une Epoque De Technologies Brillantes. W. W. Norton & Company.
[5] Seddon, P. B., Constantinidis, D., Tamm, T., & Dod, H. (2017). Comment L'analyse Commerciale Contribue-T-Elle A La Valeur Commerciale ? Information Systems Journal, 27(3), 237-269