iosr-JCE   Volume-25 ~ Issue-2 ~ Mar. - Apr. 2023

Abstract: Current advancements in the communication over networks and e-commerce section have led to considerable raise in the usage of credit cards for all type of transactions, including those conducted online and even in traditional stores. But duplicitous credit card communications have steadily increased, causing commercial institutions to lose a lot of money on yearly basis which reduces the turn-over. The creation of efficient fraud detection techniques is essential to minimize these losses; yet, doing so is difficult as it is extremely uneven in nature because of the majority of credit card datasets. Furthermore, utilizing traditional data mining algorithms for credit card fraudulent revealing is ineffective owing to its architecture, which entails a fixed mapping of variables from input sets with the output set of vectors. Using a Ensembles of Neural Network (NN) classifiers......

Key Word: Catboost; credit card; data imbalance; ensemble learning; risk analysis; meta-heuristics

[1]. S.C. Dubey, K.S. Mundhe and A.A. Kadam, "Credit Card Fraud Detection using Artificial Neural Network and Backpropagation", in Proc. ICICCS, Rasayani, India, pp. 268–273, 2020.
[2]. T. Martin, "Credit Card Fraud: The Biggest Card Frauds in History". 2022, [Online]. Available: https://www.uswitch.com/credit-cards/guides/credit-card-fraud-the-biggest-card-frauds-in-history
[3]. X. Zhang, Y. Han, W. Xu, Wang, Q. HOBA, "A novel feature engineering methodology for credit card fraud detection with a deep learning architecture", Information Sciences, vol 557, no. 10, pp. 302–316, 2019.
[4]. Y. ssaghir, R. Taher, R. M.S.Haque, Hacid, H. Zeineddine, "An experimental study with imbalanced classification approaches for credit card fraud detection", IEEE Access, vol. 7, pp. 93010–93022, 2019.
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Abstract: Clinical trials are experiments in humans, they must be conducted follow certain establishedstandards in order to protect the rights, safety and well-being of the participants. Monitoringpatientsafetyduringclinicaltrialsisacriticalcomponentthroughoutthedrugdevelopmentlife -cycle.Pharmaceuticalsponsorsmustworkproactively and collaboratively with all stakeholders to ensure a systematic approach tosafety monitoring. The regulatory landscape has evolved with increased requirements forriskmanagementplans,riskevaluationandminimizationstrategies.Astheindustrytransitionsfrompas sivetoactivesafetysurveillanceactivities,therewillbegreaterdemandformorecomprehensiveandinnov ativeapproachesthatapplyquantitativemethods to accumulating data from all sources, ranging from the discovery and preclinicalthrough clinical and post-approval stages. Statistical methods, especially those based on theBayesian framework, are important tools to help provide objectivity and rigor to the safetymonitoringprocess..

Key Word: clinical trial; safety monitoring; Data and Safety MonitoringBoard (DSMB);sequentialprobabilityratiotest (SPRT);Bayesianmethods

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Abstract: Generative AI has revolutionized the way we create and manipulate digital content, including the creation of highly realistic virtual humans. This paper provides a comprehensive overview of the recent advancements in generative AI and its applications in creating realistic virtual humans. We first delve into the concept of generative AI and its capabilities in generating unique images and manipulating existing media. We then discuss the various techniques and methods used in creating AI-generated virtual humans, including 3D face reconstruction. Furthermore, the paper delves into the current challenges and ethical considerations surrounding the field, providing valuable insights for researchers and practitioners in the field. The paper also explores the various applications of AI-generated virtual humans in industries such as gaming, entertainment, and education.

Key Word: omputer Generative Art and Music, Computer generating content, GANs, Generative Adversarial Net-Works, AI-generated mediaomputer Generative Art and Music, Computer generating content, GANs, Generative Adversarial Net- Works, AI-generated mediaC

[1]. X.-Y. Guo, Z.-Q. He, H. Duan, F.-H. Lin, G.-H. Zhang, X.-H. Zhang,
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[3]. J. Lin, Y. Yuan, and Z. Zou, ―Meingame: Create a game character face from a single portrait,‖ in Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 1, 2021, pp. 311–319.
[4]. R. Zatserkovnyi, ―3d head model estimation from a single photo,‖ 2021. [4] N. Yuksel, H. R. B¨ orkl¨ u, H. K. Sezer, and O. E. Canyurt, ―Review¨ of artificial intelligence applications in engineering design perspective,‖ Engineering Applications of Artificial Intelligence, vol. 118, p. 105697, 2023.
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Abstract: Background:Technological advances bring about all kinds of changes. One example is in the field of education, by utilizing technology, it allows online learning activities to occur. Since the announcement of the policy by the government to limit activities outside the home due to the surge in positive cases of the Covid virus, it has resulted in many schools, madrasahs, universities and Islamic boarding schools being closed. This causes activities to be carried out online. The policy has reaped a lot of public opinions expressed through social media, especially Twitter. To interpret these opinions, an analytical method called sentiment analysis is needed. Materials and Methods: Therefore, sentiment analysis is one of the solutions to overcome the problem in the automatic grouping of opinions......

Key Word: Sentiment Analysis; Naïve bayes; Support Vector Machine; K-fold Cross Validation

[1]. FahrurRozi, S. Hadi Pramono, and E. Achmad Dahlan, ―Implementasi Opinion Mining (Analisis Sentimen) Untuk Ekstraksi Data Opini Publik Pada Perguruan Tinggi,‖ J. EECCIS, vol. 6, no. 1, pp. 37–43, 2012.
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Abstract: Autism is a neuro-developmental disorder. Its common characteristics are challenges with social skills, lack of communication skill, speech and nonverbal communication problem and repetitive behaviors. One of the major characteristics of autistic children is that they do not want to interact with others. They prefer to be alone. If the parents leave to their child alone as they like and not take treatment, care and monitored, the problem persists, increasing day by day and becomes incurable. This is why children need to be cared for and monitored very carefully to overcome this problem. When an autistic child is treated sincerely without feeling burdened, their mental development is accelerated. When it comes to teaching autistic children, human annoyance, alienation,......

Key Word: Autistic Child, ASD, Social Skills, Neurodevelopmental Disorder

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Abstract: Accidents caused by uneven road conditions canharm drivers, passengers, and pedestrians. Monitoring the state of the roads is essential to creating a network of safe and enjoyable mobility. Road accidents are affected by a number of variables, including speeding, reckless driving, and poor road conditions. Accidents that happen through no fault of the motorist happen rather frequently. One of the main contributing causes to theseincidents is bad road conditions. Due to the rising number of potholes, accident rates are rising year after year. Because road maintenance is typically performed manually, it takes a long time, involves effort, and is prone to human mistake. Since potholes are one of the main cause of accidents, it is crucial to identify and categorise them using......

Key Word: YOLO, Deep Learning, Image Processing, Pothole Detection

[1]. A. A. Alhussan, D. S. Khafaga, E. -S. M. El-Kenawy, A. Ibrahim, M. M. Eid and A. A. Abdelhamid, "Pothole and Plain Road Classification Using Adaptive Mutation Dipper Throated Optimization and Transfer Learning for Self Driving Cars," in IEEE Access, vol. 10, pp. 84188-84211, 2022.
[2]. Nhat-Duc Hoang, "An Artificial Intelligence Method for Asphalt Pavement Pothole Detection Using Least Squares Support Vector Machine and Neural Network with Steerable Filter-Based Feature Extraction," Advances in Civil Engineering, vol. 2018, 2018, pp. 1- 12.
[3]. Byeong-ho Kang and Su-il Choi, "Pothole detection systemusing 2D LiDAR and camera", International Conference on Ubiquitous and Future Networks (ICUFN), 2017, pp. 744-746, IEEE.
[4]. Kumar, A., Chakrapani, Kalita, D. J. and Singh, V. P. , "A Modern Pothole Detection technique using Deep Learning," International Conference on Data, Engineering and Applications (IDEA), 2020, pp. 1-5, IEEE.
[5]. R. Fan, U. Ozgunalp, Y. Wang, M. Liu and I. Pitas, "Rethinking Road Surface 3-D Reconstruction and Pothole Detection: From Perspective Transformation to Disparity Map Segmentation," in IEEE Transactions on Cybernetics, vol. 52, no. 7, pp. 5799-5808, July 2022.

Abstract: Family conflicts and violence cases in Kenya is on increase on daily basis. These cases emanate from disagreement among the family members who suffer silently with their personal problems due to difficulties of accessing family therapy for resolution of disputes at homes. Kenya has about 100 psychiatrists and most of them are in major cities in the country (Meyer &Ndetei, 2015). Every forty seconds, an individual commit suicide (Word Health Organization, 2019). Despite the increased vices among families, Kenya's health information system currently does not address particular conditions related to mental health and its interventions monitoring (Ministry of Health Kenya, 2020).......

Key Word: YFamily conflicts, Family therapy, Conflict resolution

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[3]. Meyer, A. C., &Ndetei, D. 2016. Providing sustainable mental health care in Kenya: a demonstration project. In Providing Sustainable Mental and Neurological Health Care in Ghana and Kenya: Workshop Summary. National Academies Press (US).
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