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4th International Conference on Smart Electronics and Communication, ICOSEC 2023

作者： Godse, Shreyasi Verma, Sandhya Pandey, Shweta Aluvala, Srinivas Negi, Prafful Sahu, Mansi Law College Dehradun Uttarancchal University Dehradun India School of Computer Science and Artificial Intelligence Sr University Warangal India Uttaranchal Institute of Technology Uttarancchal University Dehradun India School of Life and Applied Sciences Uttaranchal University Dehradun India

ISBN: (纸本)9798350300888

Illegal insider trading detection and enforcement of insider trading laws is a challenging task that attracts the attention of regulators due to its serious harm to confidence of investors and sustainable development of financial markets. Due to the finite availability of resources, it's still very difficult for the regulators to book the offenders into the act of doing it. The paper focuses on the significance of having advanced technology in this area while it discusses the recent studies on insider trading detection. The author explicitly discusses the challenges faced in detection of financial crime by applying machine learning and data mining techniques. The paper also examines several market surveillance strategies that are used to protect financial markets. The primary goal of the study is to provide a thorough review of the potential effects of data mining and machine learning on market data and how to use them to ensure the integrity of financial markets. Furthermore, the author identifies some of the key challenges that currently exist and proposes potential solutions, such as integrating new tools and techniques with existing mechanisms to detect insider trading. Finally, the paper concludes with some recommendations that could be implemented in practice. © 2023 IEEE.

关键词： Data mining

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Rényi entropy of zeta urns

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Physical Review E 2023年第6期108卷 064108-064108页

作者： Piotr Bialas Zdzislaw Burda Desmond A. Johnston Institute of Applied Computer Science Jagiellonian University Ulica Lojasiewicza 11 30-348 Kraków Poland Faculty of Physics and Applied Computer Science AGH University of Krakow Aleja Mickiewicza 30 30-059 Kraków Poland School of Mathematical and Computer Sciences Heriot-Watt University Riccarton Edinburgh EH14 4AS United Kingdom

We calculate analytically the Rényi entropy for the zeta-urn model with a Gibbs measure definition of the microstate probabilities. This allows us to obtain the singularities in the Rényi entropy from those of the thermodynamic potential, which is directly related to the free-energy density of the model. We enumerate the various possible behaviors of the Rényi entropy and its singularities, which depend on both the value of the power law in the zeta urn and the order of the Rényi entropy under consideration.

关键词： Critical phenomena Information thermodynamics Phase transitions Zero-range process

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Exhilarating Growth in Education Through Artificial Intelligence

Exhilarating Growth in Education Through Artificial Intellig...

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2023 IEEE International Conference on Quantum Technologies, Communications, Computing, Hardware and Embedded Systems Security, iQ-CCHESS 2023

作者： Attri, Anant Verma, Sandhya Pandey, Shweta Chanti, Yerrolla Sahu, Mansi Balyan, Rajat Uttaranchal University Law College Dehradun Dehradun India Sr University School of Computer Science & Artificial Intelligence Warangal India Uttaranchal University School of Applied and Life Sciences Dehradun India Uttaranchal Institute of Technology Uttaranchal University Dehradun India

ISBN: (纸本)9798350314946

In the early decades of the 21st century, AI and statistical machine learning has subjugated the field and these technologies has proven highly successful in helping to solve challenging situations throughout academics and industry. The methodology used in this paper is studying the various research articles thus, draws the attention of the readers to know about how technology is affecting and revolutionizing the educational field across the world. The contribution of this study is showing the use of technology in the components of education like better universal success, learning process, clarity, skills and lifelong learning. In this paper it is also found that the technology can fill the gap between the traditional classroom and advanced learning. Some challenges regarding technological education are addressed in this paper such as data privacy and security, cost and resource constraint, ethical consideration and human centered approach. In conclusion, the advanced technology of AI and machine learning are enhancing the learning aspect and develops the curiosity to learn in a modern way but with due care and fairness. © 2023 IEEE.

关键词： Data privacy

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Advancements in Upper Body Exoskeleton: Implementing Active Gravity Compensation with a Feedforward Controller

arXiv

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arXiv 2023年

作者： Hussain, Muhammad Ayaz Iossifidis, Ioannis Institute of Computer Science Ruhr West University of Applied Science Mülheim an der Ruhr Germany The Iossifidis-Lab Institute of Computer Science Ruhr West University of Applied Sciences Mülheim an der Ruhr45479 Germany

In this study, we present a feedforward control system designed for active gravity compensation on an upper body exoskeleton. The system utilizes only positional data from internal motor sensors to calculate torque, employing analytical control equations based on Newton-Euler Inverse Dynamics. Compared to feedback control systems, the feedforward approach offers several advantages. It eliminates the need for external torque sensors, resulting in reduced hardware complexity and weight. Moreover, the feedforward control exhibits a more proactive response, leading to enhanced performance. The exoskeleton used in the experiments is lightweight and comprises 4 Degrees of Freedom, closely mimicking human upper body kinematics and three-dimensional range of motion. We conducted tests on both hardware and simulations of the exoskeleton, demonstrating stable performance. The system maintained its position over an extended period, exhibiting minimal friction and avoiding undesired slewing. © 2023, CC BY-NC-SA.

关键词： Degrees of freedom (mechanics)

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AI-Integrated Sensor Data Analytics for Real-Time Decision-Making in Wireless Sensor Networks

AI-Integrated Sensor Data Analytics for Real-Time Decision-M...

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Machine Learning and Autonomous Systems (ICMLAS), International Conference on

作者： Wasim Haidar SK Wilfred Blessing N. R Sudhakar Kumar Chaubey Zahid Mehmood Kavitha S. J Sutherlin Subitha G College of Computing and Information Sciences University of Technology and Applied Sciences Salalah Sultanate of Oman College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Sultanate of Oman College of Computing and Information Sciences University of Technology and Applied Sciences Shinas Sultanate of Oman Department of Computer Science and Engineering Vels Institute of Science Technology and Advanced Studies Chennai Tamil Nadu India Department of Computer Science and Engineering Stella Mary's College of Engineering Aruthenganvilai India

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505752

The study compares the performance of Wireless Sensor Networks (WSNs) with 20, 30, 40, and 50 nodes in real-time AI-enhanced sensor analytics using the AODV routing protocol. All configurations showed a consistent Packet Delivery Ratio (PDR) of 100%. However, the end-to-end delay increased slightly from 0.2 sec (20 nodes) to 0.3 sec (30, 40, 50 nodes), indicating that larger networks result in longer paths. Throughput decreased from 2560 bps at 20 nodes to 1706.67 bps in larger configurations, probable due to network congestion. Energy efficiency also decreased as the number of nodes increased, suggesting higher energy consumption per transmission.

关键词： Wireless sensor networks Data analysis Smart cities Decision making Throughput Routing protocols Real-time systems Energy efficiency Delays Predictive maintenance

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Role of Artificial Intelligence in Criminal Investigation

Role of Artificial Intelligence in Criminal Investigation

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2023 IEEE International Conference on Quantum Technologies, Communications, Computing, Hardware and Embedded Systems Security, iQ-CCHESS 2023

作者： Singh, Vinayak Dixit, Abhiranjan Pandey, Shweta Kumar, Bura Vijay Pachouri, Vikrant Sahu, Mansi Uttarancchal University Law College Dehradun Dehradun India Sr University School of Computer Science and Artificial Intelligence Warangal India Uttarancchal University Uttaranchal Institute of Technology Dehradun India Uttarancchal University School of Life & Applied Sciences Dehradun India

ISBN: (纸本)9798350314946

With the advent of technology, criminals are developing more sophisticated methods for criminal activities and the use of Artificial intelligence (AI) has the capacity to address this phenomenon. The role of AI in improving the effectiveness of criminal investigation is discussed in the present study as intelligent scrutiny of crime allows the law enforcement bodies to understand the vast dynamics of criminal activities and it provides potential answers about why how and when about occurrence of crime. Four such technologies-crime prediction, facial recognition, video investigation and neuroimaging are very much into use by criminal investigation bodies. In the current study the use of AI with these technologies in criminal investigation is focused upon. At last, there is always some scope for improvement and the same applies to the use of AI, regarding this the discussion and suggestions are mentioned in this study so that artificial intelligence can be better applied to criminal investigation methods and as this field is in a state of development further research and studies are recommended to derive the maximum benefits from technology. © 2023 IEEE.

关键词： Brain mapping

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Intervention of Artificial Intelligence in Education to Reduce Illiteracy Rate 3

Intervention of Artificial Intelligence in Education to Redu...

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3rd International Conference on Sentiment Analysis and Deep Learning, ICSADL 2024

作者： Negi, Prerna Shrivastava, V.K. Pandey, Shweta Chythanya, Kanegonda Ravi Negi, Prafful Gupta, Manish School of Applied and Life Sciences Uttaranchal University Dehradun India Uttaranchal University LCD Division of Research and Innovation Dehradun India School of Computer Science and Artificial Intelligence SR University Warangal India Uttaranchal Institute of Technology Uttaranchal University Dehradun India Lovely Professional University Punjab India

ISBN: (纸本)9798350396157

Artificial Intelligence (AI) can speed up the progress, provide novel teaching and learning techniques, and address some of the largest issues in education. It combines cognition, machine learning, interaction of human and computer, storage of data, recognition of emotion, and decision making to make machines think and act like humans. Digitalization is a process that involves orientation, digital preparation, interactive presence, teamwork, follow-up and performance, reflection and motivation, and examination evaluation. Technology Enhanced Learning (TEL) is being developed to help students in their academic pursuits with AI-supported time and task planning (AI4TTP). AI can be used to influence people in a variety of ways, such as through chatbots, e-Assessment, and anti-cheating systems. Learning analytics (LA) is a new area that aims to improve education and instruction by assessing raw information analytically and identifying trends to recognize behaviour of students, anticipate learner actions, and present quick feedback. Individualized instruction is tailored to each learner's individualized learning inclinations. There has been discussion of suggestions based on the analysis. © 2024 IEEE.

关键词： Virtual reality

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Split-net: Dual transformer encoder with splitting scene text image for script identification

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Pattern Recognition Letters 2025年 196卷 100-108页

作者： Ayush Roy Shivakumara Palaiahnakote Umapada Pal Cheng-Lin Liu Department of Computer Science and Engineering State University of New York Buffalo United States School of Science Engineering and Environment University of Salford Manchester United Kingdom Computer Vision and Pattern Recognition Indian Statistical Institute Kolkata India State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation of the Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

Script identification is vital for understanding scenes and video images. It is challenging due to high variations in physical appearance, typeface design, complex background, distortion, and significant overlap in the characteristics of different scripts. Unlike existing models, which aim to tackle the script images utilizing the scene text image as a whole, we propose to split the image into upper and lower halves to capture the intricate differences in stroke and style of various scripts. Motivated by the accomplishments of the transformer, a modified script-style-aware Mobile-vision Transformer (M-ViT) is explored for encoding visual features of the images. To enrich the features of the transformer blocks, a novel Edge Enhanced Style Aware Channel Attention Module (EESA-CAM) has been integrated with M-ViT. Furthermore, the model fuses the features of the dual encoders (extracting features from the upper and the lower half of the images) by a dynamic weighted average procedure utilizing the gradient information of the encoders as the weights. In experiments on three standard datasets, MLe2e, CVSI2015, and SIW-13, the proposed model yielded superior performance compared to state-of-the-art models.

关键词： Image coding

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KUKA Robot Language Parser for Product Adaptive Manufacturing

KUKA Robot Language Parser for Product Adaptive Manufacturin...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Robert Rosenstock Tim Wrütz Rolf Biesenbach Faculty of Electrical Engineering and Computer Science Bochum University of Applied Sciences Bochum Germany Institute for Automation and Industry 4.0 Bochum University of Applied Sciences Bochum Germany

The work reported in this paper enables to upload and activation of new programs to KUKA industrial robots during active operation, which would not be possible normally. By doing this it is possible to program those robots offline resulting in increased flexibility for modern manufacturing. The programs could be placed on work pieces to form a work-piece-driven production. Comparable projects increased the capabilities of robot programming by avoiding the KUKA Robot Language using high-level programming languages. Those approaches have proven themselves in the field of research. Nevertheless, this work tries a completely different approach by enabling offline programming and switching between programs while maintaining KRL the most used robot programming language for KUKA robots.

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Random allocation models in the thermodynamic limit

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Physical Review E 2023年第6期108卷 064107-064107页

We discuss the phase transition and critical exponents in the random allocation model (urn model) for different statistical ensembles. We provide a unified presentation of the statistical properties of the model in the thermodynamic limit, uncover relationships between the thermodynamic potentials, and fill some lacunae in previous results on the singularities of these potentials at the critical point and behavior in the thermodynamic limit. The presentation is intended to be self-contained, so we carefully derive all formulas step by step throughout. Additionally, we comment on a quasiprobabilistic normalization of configuration weights, which was considered in some recent studies.

关键词： Classical statistical mechanics Phase diagrams Phase transitions Phase transitions by order Specific phase transitions Zero-range process

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