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Analysis of Banking and Financial Sector Services Using Artificial Intelligence (AI) 1

8th International Conference on Information System Design and Intelligent Applications, ISDIA 2024

作者： Isavnin, Alexey Kosorukova, Irina Madaminov, Inomjon Laxmi Lydia, E. Satapathy, Suresh Department of Business-Informatics and Mathematical Methods in Economics Naberezhnye Chelny Institute KFU Kazan Federal University Naberezhnye Chelny Russia Department of Corporate Finance and Corporate Governance Financial University under the Government of the Russian Federation Moscow Russia Department of Accounting and Auditing Urgench State University Urgench Uzbekistan Department of Computer Science and Engineering Vignan’s Institute of Information Technology Visakhapatnam530049 India School of Computer Engineering KIIT Deemed to be University Bhubaneswar India

ISBN: (数字)9789819748921

ISBN: (纸本)9789819748914

This research proposes the assessment of banking and financial services using AI to monitor how banks apply AI approaches and the feedback they receive from customers. In order to better track, anticipate, and react to customer behavior, the financial information generated by the growing utilization of digital pay and banking can be mined by banks and other financial institutions. Based on research, secondary sources are reviewed to ascertain the data used in banking and financial services. A methodical survey is designed to gather the main information clients have regarding AI applications. The study is that private banks and other financial institutions use a variety of artificial intelligence (AI) services to better serve their clients and ensure that they are happy with their financial services, as some clients are not happy with banking services. Additionally, the results indicated that clients would be more committed to banking and financial services representatives by providing creative preparation for the advancement of AI practices in the workplace. © The Author(s).

关键词： Decentralized finance

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On a Cyclometric Modification of the Chua System 6

On a Cyclometric Modification of the Chua System

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6th IEEE International Conference and Workshop Obuda on Electrical and Power Engineering, CANDO-EPE 2023

作者： Nagy, Balint Joos, Antal Kovari, Attila Institute of Computer Engineering University of Dunaujvaros Department of Mathematics Dunaujvaros Hungary Institute of Electrophysics Obuda University Kandó Kálmán Faculty of Electrical Engineering Department of Natural Sciences Budapest Hungary Budapest Business University Faculty of Finance and Accountancy Department of Applied Quantitative Methods Budapest Hungary Institute of Digital Technology Eszterházy Károly Catholic University Faculty of Computer Science Eger Hungary Institute of Engineering University of Dunaújváros Department of Natural Sciences Dunaujvaros Hungary John von Neumann University Gamf Faculty of Engineering and Computer Science Kecskemét Hungary

ISBN: (纸本)9798350328752

Chaos is not only a unique chapter in the theory of dynamical systems but also a useful one with many applications in the field of communications. In this work a cyclometric modification of the well-known example of chaotic systems, the modified differential equations describing the behavior of the Chua-circuit is investigated. The results obtained can be applied in the encryption methods of the implementation of different communication channels like machine-machine or cognitive one. © 2023 IEEE.

关键词： Chaotic systems

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Machine Learning for Energy Load Prediction and its Interpretation 11

Machine Learning for Energy Load Prediction and its Interpre...

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11th IEEE International Conference on Intelligent Systems, IS 2022

作者： Charytanowicz, Malgorzata Olwert, Anna Radziszewska, Weronika Jarnicka, Jolanta Gajowniczek, Krzysztof Zabkowski, Tomasz Brozyna, Jacek Mentel, Grzegorz Matejko, Grzegorz Research Institute Pas Center for Methods of Data Analysis Systems Warsaw Poland Research Institute Pas Department of Computer Science Systems Warsaw Poland Research Institute Pas Center for Computer Modelling Systems Warsaw Poland Warsaw University of Life Sciences Institute of Information Technology Warsaw Poland Rzeszow University of Technology Department of Quantitative Methods Rzeszów Poland Polskie Towarzystwo Cyfrowe Lublin Poland

ISBN: (纸本)9781665456562

This paper refers to real-life data on energy consumption from three companies, connected to a medium voltage grid. The companies use single-, two-, or three-zone tariffs and the general characteristic of their activity is comparable. The input dataset contains hourly electricity consumption recorded from January 2020 to December 2020. The independent variables used for the study include weather, time-dependent factors, and aggregated energy factors. We perform the prediction of consumption using three methods: naive, multiple regression, and extreme gradient boosting regression. The performance of the methods is compared based on the MSE, RMSE, MAE, and MAPE metrics. The study shows that the scores achieved for the extreme gradient boosting method are higher than for the multiple regression. To gain the interpretability of the energy load forecasting and feature analysis the Shapley additive explanations method is used for the best model. As a result, a ranking of the most important factors is created. It shows the importance of aggregated energy factors and weather conditions while placing daylight and season at the bottom of the ranking. © 2022 IEEE.

关键词： Energy utilization

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BAYESDIFF: ESTIMATING PIXEL-WISE UNCERTAINTY IN DIFFUSION VIA BAYESIAN INFERENCE 12

BAYESDIFF: ESTIMATING PIXEL-WISE UNCERTAINTY IN DIFFUSION VI...

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12th International Conference on Learning Representations, ICLR 2024

作者： Kou, Siqi Gan, Lei Wang, Dequan Li, Chongxuan Deng, Zhijie Qing Yuan Research Institute SEIEE Shanghai Jiao Tong University China Gaoling School of Artificial Intelligence Renmin University of China China Beijing Key Laboratory of Big Data Management and Analysis Methods China School of Computer Science Fudan University China Shanghai Artificial Intelligence Laboratory China

Diffusion models have impressive image generation capability, but low-quality generations still exist, and their identification remains challenging due to the lack of a proper sample-wise metric. To address this, we propose BayesDiff, a pixel-wise uncertainty estimator for generations from diffusion models based on Bayesian inference. In particular, we derive a novel uncertainty iteration principle to characterize the uncertainty dynamics in diffusion, and leverage the last-layer Laplace approximation for efficient Bayesian inference. The estimated pixel-wise uncertainty can not only be aggregated into a sample-wise metric to filter out low-fidelity images but also aids in augmenting successful generations and rectifying artifacts in failed generations in text-to-image tasks. Extensive experiments demonstrate the efficacy of BayesDiff and its promise for practical applications. Our code is available at https://***/karrykkk/BayesDiff. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Pixels

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Human-Factor focused Application of STPA to Remotely driven Vehicles

Human-Factor focused Application of STPA to Remotely driven ...

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Public Safety Technology (WFPST), IEEE World Forum on

作者： Ole Hans Krystian Radlak Jürgen Adamy Department of Control Methods and Intelligent Systems Technical University of Darmstadt Düsseldorf Germany Institute of Computer Science Warsaw University of Technology Warsaw Poland

ISBN: (数字)9798350329148

ISBN: (纸本)9798350329155

This paper presents an analysis of the safety aspects of a Remote Driving System (RDS) using the System-Theoretic Process Analysis (STPA) methodology. The focus is on the human Remote Driver (RD) within the RDS, considering losses and system-level hazards associated with the human-in-the-loop scenario which focuses on the RD actions related to the change in Steering Wheel Angle (SWA). The STPA methodology is applied to identify Unsafe Control Actions (UCA) related to the change in SWA command, resulting in the identification of numerous Causal Factors (CF) that may lead to hazardous scenarios. Several UCAs and CFs are identified that provide information on potential hazards and risks associated with remote driving technology. Based on a selected UCA where the RD does not change the SWA when the road network requires lateral movement, 25 potential loss scenarios were identified and presented in this paper. The results of this work can contribute to the understanding of potential risks and the development of safety mitigation measures in the context of RDS which need to be validated in further research.

关键词： Roads Prevention and mitigation Wheels Hazards Public security Human in the loop Behavioral sciences

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Brain Storm Optimization based directional sensors deployment for coverage of targets 3

Brain Storm Optimization based directional sensors deploymen...

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3rd International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Balaji, S. Rajkumar, S. Sharma, Shekhar Yadav, Aditi Vellore Institute of Technology Division of Mathematics Sas Chennai India Boston University Department of Computer Science BostonMA United States IIM Ahmedabad Department of Production and Quantitative Methods India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

Sensors are used in various areas and have numerous applications including military surveillance, weather monitoring, maritime communication etc. Most of the applications need the multimedia sensors with directional sensing range of the sensors to perform advance task. Additionally, there are some constraints on the targets namely Q-constraints, such that each target must be covered by different number of sensors. The crucial issue in this case is deployment of minimum number of multimedia sensors to satisfy the Q-constraints. The optimization of the placement of the sensors can result in reduced number of sensors needed for the coverage of the specified targets. In this paper, the placement of the sensors is optimized using the Brain Storm Optimization Algorithm (BSO) which is inspired by the human brainstorming process. BSO algorithm efficiently designed for the considered problem to identify the optimal position of the sensors. The performance of the proposed algorithm is verified by simulation results, which performs better than the random deployment of the sensors. © 2022 IEEE.

关键词： Storms

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Current Trends in Artificial Intelligence for Educational Advancements

Current Trends in Artificial Intelligence for Educational Ad...

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Decision Aid sciences and Application (DASA), International Conference on

作者： Abdallah M. A. Al-Tarawneh Reem AbdElkareem AlOmoush Tanveer ul Islam Jamshaid Iqbal Janjua Tahir Abbas Anaum Ihsan Clinical Psychology Al-Ahliyya Amman University Amman Jordan Department of Curricula and Methods of Teaching Faculty of Educational Sciences Yarmouk University Jordan Department of Computer Science TIMES Institute Multan Pakistan Al-Khawarizmi Institute of Computer Science University of Engineering & Technology (UET) Lahore Pakistan

ISBN: (数字)9798350369106

ISBN: (纸本)9798350369113

The focus of this paper is the integration of artificial intelligence (AI) within the educational field including but not limited to, adaptive learning, teaching evaluation, online learning environments, and individualized instruction. The authors investigate the positive role of AI in enhancing teaching performance and the quality of students' learning experiences. The study aims to demonstrate what role AI may play in the course of education development and practice improvement. It also sheds light on the limitations AI will have in the realm of education, such as accessibility, data ownership, and ethical issues. The paper does not contain only the limitations but the opportunities for this technology as well and describes how AI could be effectively incorporated into education, subsequently providing insights into the evolution of AI-based educational transformation.

关键词： Ethics Adaptive learning Education Learning (artificial intelligence) Market research Artificial intelligence

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Pharmaceutical Supply chain Risk Assessment During COVID-19 Epidemic

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IFAC-PapersOnLine 2022年第10期55卷 2203-2208页

作者： W Daoud BenAmor A Labella H Moalla Frikha L Martínez López Quantitative Methods Economic and Computer Sciences department Higher Institute of Industrial Management of Sfax Tunisia. Computer Science Department University of Jaén Spain.

The global health products supply chain is negatively influenced by the COVID-19 pandemic. Moreover, the risks in the pharmaceutical supply chain (PSC) have increased. Assessment and mitigation risks in PSC are essential issues to control and counter these risks. In this study, a 2-Tuple ARAS-BWM approach, which combines ARAS and BWM methods under linguistic 2-Tuple environment, is proposed to evaluate and address various risks to the best mitigation strategies in the pharmaceutical industry in Tunisia during COVID-19. Noted that the main risk identified in the PSC is related to supply and suppliers and its best mitigation strategy is reducing risk.

关键词： 2-Tuple BWM 2-Tuple linguistic environment ARAS COVID-19 Pharmaceutical supply chain risk assessment risk mitigation strategy

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Multyperson Health Monitoring Wireless Network 30

Multyperson Health Monitoring Wireless Network

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30th Telecommunications Forum, TELFOR 2022

作者： Shevchuk, Bohdan Ivakhiv, Orest Kochan, Roman National Academy of Sciences of Ukraine Glushkov Institute of Cybernetics Department of Numerical Methods Optimization Kyiv03187 Ukraine Lviv Polytechnic National University Computer Technology Automation and Metrology Institute Lviv Ukraine Lviv Polytechnic National University Lviv Ukraine University of Bielsko-Biala Department of Computer Science and Automatics Bielsko-Biala Poland

ISBN: (数字)9781665472739

ISBN: (纸本)9781665472739

Methodological and algorithmic bases of the local-regional and global wireless networks operation for functional states of people long-term monitoring, processing, encoding, encrypting and transmitting samples of monitoring signals and video data frames using a signaling approach are proposed. The technology is focused on evidence-based monitoring of the condition of operators of various human-machine complexes, athletes and healthy people in order to prevent various diseases. © 2022 IEEE.

关键词： Wireless networks

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Leveraging Artificial Intelligence in Online Educational Platforms to Enhance Continuous Professional Development in the Teaching Profession 2

Leveraging Artificial Intelligence in Online Educational Pla...

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2nd International Conference Computational and Characterization Techniques in Engineering and sciences, IC3TES 2024

作者： Amankulovich, Khujakulov Sherzod Tokhirovich, Mannabov Javlon Bakhridinovich, Kadirov Tulkin Kuvandikovich, Taylakov Umid Ananth, Christo Kumar, T. Ananth Samarkand Regional National Center for Training Teachers in New Methods Uzbekistan Uzbekistan Samarkand Agroinnovations and Research University Uzbekistan Samarkand State University Uzbekistan&Adjunct Faculty Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Avadi Chennai India Ifet College of Engineering Computer Science and Engineering Tamilnadu India

ISBN: (纸本)9798350364699

To keep up with the dynamic nature of the modern classroom, teachers must have access to online learning platforms for professional development purposes. This investigation looks at how these platforms can be used to improve teachers' skills, make information sharing easier, and open doors to CPD opportunities. This study examines the relationship between online resources and methods to demonstrate how digital tools have an impact on teacher training and professional development by leveraging AI. It also draws attention to the fact that these platforms are helping with information-methodological support for teachers as well as the ongoing reforms in our nation. Incorporating empirical observations and case studies, the analysis demonstrates how effective online platforms are in fostering a collaborative and innovative environment for professional learning. Digital transformation has the potential to radically alter how teachers obtain professional development, and this study emphasizes that fact. This will enable teachers to effectively address the demands of modern classrooms. © 2024 IEEE.

关键词： Contrastive Learning

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