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Comparative Evaluation of Anomaly Detection Methods for Fraud Detection in Online Credit Card Payments 9th

Comparative Evaluation of Anomaly Detection Methods for Frau...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Thimonier, Hugo Popineau, Fabrice Rimmel, Arpad Doan, Bich-Lien Daniel, Fabrice Univ Paris Saclay CNRS CentraleSupelec Lab Interdisciplinaire Sci Numer F-91190 Gif Sur Yvette France

ISBN: (纸本)9789819745807;9789819745814

This study explores the application of anomaly detection (AD) methods in imbalanced learning tasks, focusing on fraud detection using real online credit card payment data. We assess the performance of several recent AD methods and compare their effectiveness against standard supervised learning methods. Offering evidence of distribution shift within our dataset, we analyze its impact on the tested models' performances. Our findings reveal that LightGBM exhibits significantly superior performance across all evaluated metrics but suffers more from distribution shifts than AD methods. Furthermore, our investigation reveals that LightGBM also captures the majority of frauds detected by AD methods. This observation challenges the potential benefits of ensemble methods to combine supervised, and AD approaches to enhance performance. In summary, this research provides practical insights into the utility of these techniques in real-world scenarios, showing LightGBM's superiority in fraud detection while highlighting challenges related to distribution shifts.

关键词： Imbalanced learning Anomaly detection Fraud detection

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The Barriers to AI Adoption in Supply Chains: Case of Moroccan Companies 7th

The Barriers to AI Adoption in Supply Chains: Case of Morocc...

引用

7th International Conference on Logistics Operations Management (GOL)

作者： Barakat, Ouafa Bouanba, Nouhayla Ibn Zohr Univ Natl Sch Business & Management Agadir 80000 Morocco

ISBN: (纸本)9783031686276;9783031686283

Artificial intelligence (AI) is quickly becoming one of the most important new technologies. Its adoption has tremendous potential for businesses. They can use it to increase profits, save costs in the supply chain, provide outstanding client service, and make their supply chains smarter. However, several companies find it difficult to fully realize all the advantages of this technology. This research aims to investigate the major barriers influencing the adoption of AI in Moroccan companies. In this paper, we used the qualitative approach to explore the main barriers to AI adoption in our country. Twenty semi-structured interviews were conducted with managers in Moroccan companies, and data analysis was conducted using the IRAMUTEQ analysis software in addition to content analysis. Our results will highlight six barriers to AI adoption related to two contexts: the technological and the organizational ones. These barriers are: training and assistance, complexity, funding, managerial support, technical capability and company size. We used TOE (Technological-Organizational- Environmental) theory to cluster our findings into the two adoption dimensions.

关键词： Artificial Intelligence Supply Chain Barriers Moroccan companies TOE theory

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Understanding the Impact of Internet Addiction on Impulse Buying: Exploring Task Orientation and Self-efficacy 9th

Understanding the Impact of Internet Addiction on Impulse Bu...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Fatmawati, Indah Vernanda, Fara Anindya Univ Muhammadiyah Yogyakarta Bantul Special Region Indonesia

ISBN: (纸本)9789819735556;9789819735563

This study examines the impact of task orientation and self-efficacy on impulsive purchasing behavior, with internet addiction as a mediating variable. In this study, the exogenous factors were task orientation and self-efficacy, with impulsive purchasing behavior as the endogenous variable. The Shopee online purchasing serves as the study's context. The authors used non-probability sampling, and questionnaires were distributed via Google Forms. The data was analyzed using structural equation modeling (SEM) AMOS Version 22 software. The findings indicate that task orientation and self-efficacy have a positive impact on internet addiction. Task orientation and self-efficacy also have positive effects on impulse buying. At the same time, internet addiction positively impacts impulse buying. Internet addiction mediates the relationship between task orientation and impulsive buying, as well as self-efficacy and impulse buying.

关键词： Task orientation Self-efficacy Internet addiction Impulse buying

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Object Detection and Tracking Approach for Traffic Monitoring 1

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Barekar, Praful, V Singh, Kavita R. Yeshwantrao Chavan Coll Engn Comp Technol Dept Nagpur Maharashtra India

ISBN: (数字)9789819713233

ISBN: (纸本)9789819713226;9789819713233

In present day, many object detection algorithms are available. These computer vision-based object detection algorithms help to detect, locate and trace an object from an image or a video. It requires high speed and accuracy along with efficiency when it is concerned with real-time systems. In machine learning and computer vision, object detection is considered to be an essential research area, also widely implemented in various sectors such as robotic navigation and intelligent video. The traditional approach to object identification consists of the steps as partitioning, clustering, feature extraction and classification. The solution is dependent of manual annotation, which leads to increase in the cost of the algorithm. Due to the diversity of objects, multiple models are needed for feature detection. As a result, classical object detection algorithms have poor generalizability, low detection accuracy, slow operating rate and low robustness. Object detection strategies are widly categorized as one-step and two-step object detection strategies. We are presenting a comparative analysis on object detection algorithms from two categories, i.e. single shot feed forward object detection algorithms and region proposal-based object detection algorithms. Under single shot feed forward, YOLOv7 is being is used along with pretrained weights trained on MS-COCO dataset from scratch. On the contrary, Mask R-CNN is being used to compare with, with its pretrained weights. This study presents a comparative analysis of YOLOv7 and Mask R-CNN in the context of accuracy, memory footprint and processing speed by retraining the models on the dataset of images and videos obtained through real-time systems in constrained.

关键词： Object detection Object tracking YOLOv7 Mask R-CNN

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Explainable AI for Intrusion Detection systems: A Model Development and Experts' Evaluation

Explainable AI for Intrusion Detection Systems: A Model Deve...

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Intelligent systems Conference

作者： Durojaye, Henry Naiseh, Mohammad Bournemouth Univ Talbot England

ISBN: (纸本)9783031664274;9783031664281

This study sought to develop a transparent machine learning model for network intrusion detection that domain experts would trust for security decision-making. Intrusion detection systems using machine learning have shown promise but often lack interpretability, undermining user trust and deployment. A hybrid Random Forest/XGBoost classifier achieved over 99% accuracy and F1 score, outperforming previous literature. Post-hoc LIME explanations provided feature effect transparency. Nine domain experts from technical roles then evaluated the model's reliability, explainability, and trustworthiness through a standardised process. While over half found the model reliable, one-third expressed uncertainty. Responses on performance explanations and trustworthiness assessments also varied thus suggesting opportunities to strengthen reliability communications and consolidate diverse perspectives. To optimise user confidence and model deployment, refinements targeting consistent explainability across audiences were proposed. Overall, high predictive performance validated effectiveness, but variable viewpoints from evaluations indicated the need to bolster reliability and trust explanations. With continued iterative evaluation and enhancements, this research framework holds promise for developing interpretable machine learning solutions trusted for complex security decision-making.

关键词： Explainable AI Trustworthy AI Intrusion detection systems

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A First Experiment Towards Discomfort Assessment for Children with Cerebral Palsy Wearing an Exoskeleton

A First Experiment Towards Discomfort Assessment for Childre...

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Intelligent systems Conference (IntelliSys)

作者： Breux, Victor Vassilev, Andrea Godin, Christelle Mayer-Dalverny, Luca Groen, Brenda Kuijpers, Rosanne Keijsers, Noel Univ Grenoble Alpes CEA LETI MINATEC Campus Grenoble France Sint Maartens Dept Res & Innovat Nijmegen Netherlands Radboud Univ Nijmegen Donders Inst Brain Cognit & Behav Dept Sensorimotor Neuroscience Rehabil Radboud Univ Med Ctr Nijmegen Netherlands

ISBN: (纸本)9783031477171;9783031477188

Rehabilitation devices like exoskeletons may be useful to promote walking for children with cerebral palsy (CP). However, exoskeletons can generate discomfort to the children. The contribution of this paper is to propose a protocol adapted to children to simulate the wearing of an exoskeleton, and to develop a stress detection model for healthy children. This is a first step towards discomfort detection on CP children. Fifteen healthy children participated in three test conditions (fear of falling, fear of novelty, physical discomfort) through two independent measurement campaigns (2021 and 2022). Six children from 2021 were used on a machine learning model as training set and nine from 2022 constituted the test set. Only the fear of falling condition generated stress effectively on the children. Linear regression was used to detect stress with two heart rate features. The model achieved a balanced accuracy of 84.44% when applied on the test set.

关键词： Cerebral Palsy Children Exoskeleton Physiological features Stress detection Machine learning

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Simulation of 6-DOF Modular Arm-Z Manipulator in MATLAB Simulink 28th

Simulation of 6-DOF Modular Arm-Z Manipulator in MATLAB Simu...

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2024 International Conference Automation

作者： Jarek, Michal Zawalski, Krzysztof Falkowski, Piotr Zawidzka, Ela Zawidzki, Machi Ind Res Inst Automat & Measurements PIAP Warsaw Poland Warsaw Univ Technol Warsaw Poland Inst Fundamental Technol Res PAN Warsaw Poland

ISBN: (纸本)9783031782657;9783031782664

Arm-Z is a concept of a hyper-redundant manipulator based on linearly joined sequence of congruent units. Each unit has only one degree of freedom (1-DOF) - the twist relative to the previous unit. This paper presents the approach to design of modular robotic manipulator based on computer simulations. The approach is rather standard nowadays, however, it is applied to rather unique robotic system. The CAD model of the module structure for a manipulator with 6 degrees of freedom and respective Denavit-Hartenberg notation are presented. Simulink - a MATLAB-based graphical programming environment was used to determine the torques of individual modules. The results of three simulations are presented and discussed. Finally, based on critical observations, the drive and gear for the module of Arm-Z system were selected.

关键词： Simulation Robotic arm Manipulator Arm-Z MATLAB Simulink

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Multimodal Face and Ear Recognition Using Feature Level and Score Level Fusion Approach

Multimodal Face and Ear Recognition Using Feature Level and ...

引用

International Conference on Artificial Intelligence: Theory and Applications (AITA)

作者： Resmi, K. R. Joseph, Amitha George, Bindu Christ Deemed Univ Bengaluru India Santhigiri Coll Thodupuzha Kerala India

ISBN: (纸本)9789819984756;9789819984763

Recent years have seen a significant increase in attention in multimodal biometric systems for personal identification especially in unconstrained environments. This paper presents a multimodal recognition system by combining feature level fusion of ear and profile face images. Multimodal biometric systems by combining face and ear can be used in an extensive range of applications because we can capture both the biometrics in a non-intrusive manner. Local texture feature descriptor, BSIF is used to extract discriminative features from biometric templates. Feature level and score level fusion is experimented to improve the performance of the system. Experimental results on different public datasets like GTAV, FEI, etc., show that the proposed method gives better performance in recognition results than individual modality.

关键词： Multimodal biometrics Face Ear Feature level fusion Score level fusion BSIF

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Complexity Classification of Complex-Weighted Counting Acyclic Constraint Satisfaction Problems 1

引用

Computing Conference

作者： Yamakami, Tomoyuki Univ Fukui Fac Engn 3-9-1 Bunkyo Fukui 9108507 Japan

ISBN: (数字)9783031622731

ISBN: (纸本)9783031622755;9783031622731;9783031622724

We study the computational complexity of counting constraint satisfaction problems (#CSPs) whose constraints assign complex numbers to Boolean inputs when the corresponding constraint hypergraphs are acyclic. These problems are called acyclic #CSPs or succinctly, #ACSPs. We wish to determine the computational complexity of all such #ACSPs when arbitrary unary constraints are freely available. Depending on whether we further allow or disallow the free use of the specific constraint XOR (binary disequality), we present two complexity classifications of the #ACSPs according to the types of constraints used for the problems. When XOR is freely available, we first obtain a complete dichotomy classification. On the contrary, when XOR is not available for free, we then obtain a trichotomy classification. To deal with an acyclic nature of constraints in those classifications, we develop a new technical tool called acyclic-T-constructibility or AT-constructibility, and we exploit it to analyze a complexity upper bound of each #ACSPs.

关键词： Auxiliary pushdown automata #LOGCFL Counting constraint satisfaction problem #ACSP Complexity classification Acyclic hypergraph Acyclic-T-constructibility

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Machine Learning Control by Symbolic Regression for the Extended Optimal Control Problem of Robot Group

Machine Learning Control by Symbolic Regression for the Exte...

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Intelligent systems Conference (IntelliSys)

作者： Diveev, Askhat Russian Acad Sci Fed Res Ctr Comp Sci & Control Vavilova Str 44-2 Moscow 11933 Russia

ISBN: (纸本)9783031477171;9783031477188

The extended optimal control problem is considered. In the problem, it is necessary to find such an optimal control function so that it not only solves the optimal control problem, that is, it ensures the achievement of the terminal state with the optimal value of the quality criterion for the considered mathematical model of the control object under consideration, but and this control function was implemented in the control system of the real object. This means that the control function should depend on the vector of the state space, and the optimal solution must retain the property of optimality under small perturbations of the found solution. To solve this problem machine learning control by symbolic regression is used. In the extended optimal control problem, the problem statement of stabilization system synthesis for movement along the optimal trajectory is included. Solving the synthesis problem is performed by symbolic regression, the network operator method. At the solving the synthesis problem a domain of initial conditions is considered instead of one point of initial state. This provides small sensitivity found solution to perturbations of initial states. The example of solving the extended optimal control problem with phase constraints for two quadcopters is presented.

关键词： Optimal control Machine learning Symbolic regression Robot group Control synthesis

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