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4th International Conference on Sustainable Expert systems, ICSES 2024

作者： Mohankumar, N. Manivannan, K.K. Babu, A. Ramesh Sampoornam, M. Maria Kovarasan, Rajesh Kambattan Srinivasan, C. Nagpur Campus Maharashtra Pune India Kcg College of Technology Department of Mechatronics Engineering Tamil Nadu Chennai India School of Computer Applications Vidya Vikas Institute of Engineering and Technology Karnataka Mysore India J.J College of Engineering and Technology Department of Information Technology Tamil Nadu Tiruchirappalli India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331540364

Various sectors continue to prioritize lone worker safety, which requires creative ways to provide quick support and monitoring. To safeguard lone workers, this paper introduces a new method that makes use of cloud-connected wearable devices that are coupled with Wireless Sensor Networks (WSNs). The system design relies on sensors embedded in wearable devices that can monitor a range of environmental elements as well as the vital signs of workers. A central cloud platform receives data in real-time via wireless communication from these devices and processes and analyzes it. The system may detect possible dangers or crises using smart techniques and immediately notify those who are supposed to react or the proper authorities. Cloud computing also makes it easy to store, analyze, and monitor large amounts of data over time, which is great for doing proactive risk assessments and improving safety standards. It demonstrates solution's capacity to improve lone worker safety, reduce reaction times, and mitigate hazards via simulations and actual deployment scenarios, efficacy and dependability. This growing body of knowledge on how to protect lone workers in various workplaces by using the power of IoT and cloud computing. © 2024 IEEE.

关键词： Cloud platforms

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Design and Implementation of Personal Smart Home system Based on Edge Computing Gate 5

Design and Implementation of Personal Smart Home System Base...

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5th International Conference on computer Engineering and Intelligent Control, ICCEIC 2024

作者： Xu, Fangqin Jiang, Yue Yang, Shun Liu, Yixuan Shanghai Publishing and Printing College Department of Information and Intelligent Engineering Shanghai China College of Communication and Art Design University of Shanghai for Science and Technology Shanghai China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China

ISBN: (纸本)9798331507992

With the advancements in IoT technology, cloud computing, and big data technology, smart living has become an integral part of people's lives. However, traditional intelligent data computing relies heavily on cloud services, which often suffer from issues such as slow response times and high energy consumption. To address these issues, this study introduces an edge computing architecture centered on gateways, serving as an intermediate layer between user devices and cloud servers. This architecture enables high-speed data processing, low-latency responses, and rapid end-to-end connections, making it suitable for most small-scale and personal smart home systems. © 2024 IEEE.

关键词： Smart homes

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Video2Reward: Generating Reward Function from Videos for Legged Robot Behavior Learning 27

Video2Reward: Generating Reward Function from Videos for Leg...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Zeng, Runhao Zhou, Dingjie Liang, Qiwei Liu, Junlin Li, Hui Huang, Changxin Li, Jianqiang Hu, Xiping Sun, Fuchun Artificial Intelligence Research Institute Shenzhen MSU-BIT University China College of Mechatronics and Control Engineering Shenzhen University China College of Computer Science and Software Engineering Shenzhen University China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Department of Computer Science and Technology Tsinghua University China

ISBN: (纸本)9781643685489

Learning behavior in legged robots presents a significant challenge due to its inherent instability and complex constraints. Recent research has proposed the use of a large language model (LLM) to generate reward functions in reinforcement learning, thereby replacing the need for manually designed rewards by experts. However, this approach, which relies on textual descriptions to define learning objectives, fails to achieve controllable and precise behavior learning with clear directionality. In this paper, we introduce a new video2reward method, which directly generates reward functions from videos depicting the behaviors to be mimicked and learned. Specifically, we first process videos containing the target behaviors, converting the motion information of individuals in the videos into keypoint trajectories represented as coordinates through a video2text transforming module. These trajectories are then fed into an LLM to generate the reward function, which in turn is used to train the policy. To enhance the quality of the reward function, we develop a video-assisted iterative reward refinement scheme that visually assesses the learned behaviors and provides textual feedback to the LLM. This feedback guides the LLM to continually refine the reward function, ultimately facilitating more efficient behavior learning. Experimental results on tasks involving bipedal and quadrupedal robot motion control demonstrate that our method surpasses the performance of state-of-the-art LLM-based reward generation methods by over 37.6% in terms of human normalized score. More importantly, by switching video inputs, we find our method can rapidly learn diverse motion behaviors such as walking and running. © 2024 The Authors.

关键词： Robots

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The Improved Automotive Network Optimization Scheme Through Time Series Analysis Using AI/ML

The Improved Automotive Network Optimization Scheme Through ...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Gupta, Poonam Banerjee, Diptonil Manivasagam Sanskriti University Department of Management Uttar Pradesh Mathura India College of Engineering Teetthanker Mahaveer University Uttar Pradesh Moradabad India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350383348

The car industry is pressured to lessen its environmental impact and the cost of proudly owning and working a vehicle. Researchers have evolved a stepped-forward car network Optimization (ANO) scheme combining time collection analysis and synthetic intelligence/system studying (AI/ML) algorithms to combat those demanding situations. This scheme systematically optimizes the car network by detecting anomalies inside the time collection statistics collected from an array of sensors and producing a fixed of moves based totally on the ML version's techniques. This device carries dynamic automobile fashions and real-time riding statistics, including pace, acceleration, and strength consumption, to identify community anomalies and enhance strength efficiency. Furthermore, it additionally analyzes and classifies one-of-a-kind driving scenarios and uses AI/ML-based total optimization strategies to similarly decorate the device's ability to respond to one-of-a-kind road conditions and using behaviors. Moreover, the scheme allows for higher verbal exchange between automobile and infrastructure additives, reducing electricity waste and mitigating road risks. © 2024 IEEE.

关键词： automotive conditions Optimization pressure promising

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Automated Indonesian Essay Scoring and Holistic Feedback Using Bidirectional Encoder Representations for Transformers 8

Automated Indonesian Essay Scoring and Holistic Feedback Usi...

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8th International Conference on Electrical, Telecommunication and computer Engineering, ELTICOM 2024

作者： Amalia, Amalia Lydia, Maya Silvi Kadir, Rabiah Abdul Utami Tanjung, Faradhila Aulia Br Ginting, Dewi Sartika Gunawan, Dani Universitas Sumatera Utara Department of Computer Science Medan Indonesia Institute of Visual Informatics Universiti Kebangsaan Malaysia Selangor Malaysia Universitas Sumatera Utara Department of Information Technology Medan Indonesia

ISBN: (纸本)9798331531249

Developing an effective and accurate Automated Essay Scoring (AES) system for Indonesian essays involves overcoming several challenges, including limited datasets and issues related to grading efficiency and feedback generation. This study addresses these challenges by proposing an automated Indonesian essay grading and feedback system utilizing Bidirectional Encoder Representations from Transformers (BERT). The research employed a thorough process, including the translation of the ASAP dataset from the Kaggle competition titled 'The Hewlett Foundation' into Indonesian, analysis and refinement of the dataset to include only relevant features, and fine-tuning using the pre-trained IndoBERT embeddings. To assess the relevance between the essay prompts and student responses, text similarity methods were applied outside the fine-tuning process. The final score is derived from the combination of the fine-tuned score and the relevance score. The model achieved a perfect accuracy of 1 and a strong kappa score of 0.82 during training. The alignment of the final score predictions with human feedback is validated by a Quadratic Weighted Kappa (QWK) score of 0.9, indicating a high level of agreement. This demonstrates that the automated scoring system effectively matches human judgment, highlighting its efficacy in evaluating essay quality. © 2024 IEEE.

关键词： Feedback

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An Obstacle Detection Technique for Marine Intelligent Transportation system based on Maximum likelihood Method

An Obstacle Detection Technique for Marine Intelligent Trans...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Ma, Xin-Ming Song, Hai-Yan Yang, Chang-Yi Song, Xiao-Jun Gao, Dong-Xu Heilongjiang Institute of Technology School of Electrical and Information Engineering Harbin China National Penghu University of Science and Technology Department of Computer Science and Information Engineering Magong Taiwan Petro China Tarim Oil Field Company Korla China

ISBN: (纸本)9798350324174

Obstacle detection is a key technology for marine intelligent transportation system. In this paper, an obstacle detection technique for marine intelligent transportation system based on Maximum Likelihood (ML) processor is proposed. Different from most of the former source localization algorithms, our proposed algorithm explicitly makes use of both the horizontal L-Shaped array and the underwater acoustic propagation model to achieve a relatively high spatial resolution. Numerical simulations are presented to demonstrate the superior performance of our proposed algorithm. © 2023 IEEE.

关键词： Maximum likelihood

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Using Natural Language Processing for Biometric Identification Optimizatoin 3

Using Natural Language Processing for Biometric Identificati...

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3rd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Kumar, Bhupendra Nagpal, Amandeep Bisht, Yashwant Sreenivasgoud, Pulluri Qureshi, Kashif Lourens, Melanie Mangalmay Institute of Engineering Technology Computer Science Engineering Greater Noida India Lovely Professional University Phagwara India Uttaranchal University Uttaranchal Institute of Technology India SR University School of Sciences Warangal India Lingaya's Vidyapeeth Department of Computer Science Information Technology Haryana Faridabad India Durban University of Technology Deputy Dean Faculty of Management Sciences South Africa

ISBN: (纸本)9798350399264

The use of natural language processing (NLP) methods for assessing employee performance is examined in this research article. The paper suggests a technique for extracting pertinent information on work performance from employee-generated text data, such as emails, chats, and feedback surveys. The suggested approach makes use of NLP methods including topic modelling, sentiment analysis, and text classification to extract characteristics that may be utilized as performance indicators for employees. The study's findings imply that the suggested approach, when compared to more conventional assessment techniques, may provide a more comprehensive perspective of employee performance, and assist managers in reaching more informed conclusions about that performance. © 2023 IEEE.

关键词： Classification (of information)

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Assessing Biological Responses of Saccharomyces Cerevisiae to Low-Frequency Electromagnetic Fields: Insights and Implications 15

Assessing Biological Responses of Saccharomyces Cerevisiae t...

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15th International Conference Elektro, ELEKTRO 2024

作者： Bajtos, Marek Radil, Roman Janousek, Ladislav Dang, Nhat University of Zilina Faculty of Electrical Engineering and Information Technology Department of Electromagnetic and Biomedical Engineering Zilina Slovakia University of Colorado Boulder Department of Electrical Computer and Energy Engineering BoulderCO United States

ISBN: (纸本)9798350372359

This study investigates the biological effects of Low-Frequency Electromagnetic Fields (LF-EMF) on Saccharomyces cerevisiae yeast cells, an essential model organism in biological research. To achieve controlled exposure, the exposure system ensuring uniform exposition while maintaining identical cultivation conditions for both exposed and control samples is used. To evaluate the impact of LF-EMF, yeast cell growth and proliferation were quantified using a Bürker chamber before and after exposure. Our findings reveal statistically significant differences between the exposed and control samples, suggesting a potential biological response to LF-EMF. The present research offers valuable insights into the effects of LF-EMF on biological cells, contributing to the broader understanding of electromagnetic field's impact on living organisms. Furthermore, the proposed exposure system provides a reliable platform for future bioelectromagnetic research, facilitating health risk assessments and investigations into the therapeutic potential of LF-EMF exposure. © 2024 IEEE.

关键词： Electromagnetic fields

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Challenges of Extended Reality technology in Higher Education: A Review

International Journal of Emerging Technologies in Learning

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International Journal of Emerging Technologies in Learning 2023年第14期18卷 39-50页

作者： Obeidallah, Randa Al Ahmad, Ayat Qutishat, Duha Department of Computer Information System Faculty of Prince Al-Hussein Bin Abdallah II for Information Technology The Hashemite University Zarqa Jordan Department of Computer Science and Applications Faculty of Prince Al-Hussein Bin Abdallah II for Information Technology The Hashemite University Zarqa Jordan Department of Information Technology Faculty of Prince Al-Hussein Bin Abdallah II for Information Technology The Hashemite University Zarqa Jordan

Extended reality is proposed as a means to deliver qualitative material to students in higher education institutions. The usage of this technology has increased due to Covid-19 lock down. This paper aims to categorize the challenges encountered by literature that deployed extended reality (XR) in higher education during and after the lockdown. However, the number of available articles addressing these challenges is limited, with a total number of 40 articles obtained from dimensions’ dataset. In this study, bibliometric analysis is used to highlight the number of publications, citations, and authors in this field. Thematic analysis with inductive reasoning is applied to extract the primary challenge themes mentioned in 23 articles. After reviewing the eligible articles;we categorized the challenges into three main themes: Teacher, Student, and technology. © 2023 by the authors of this article. Published under CC-BY.

关键词： Augmented reality

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Bilateral Coupled Epsilon Negative Metamaterial for Dual Band Wireless Communications

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computers, Materials & Continua 2022年第4期71卷 1263-1281页

作者： Md Mhedi Hasan Mohammad Tariqul Islam Md Moniruzzaman Mohd Hafiz Uddin Norsuzlin Binti Mohd Sahar Md Samsuzzaman Department of Electrical Electronic and Systems Engineering Faculty of Engineering and Built EnvironmentUniversiti Kebangsaan MalaysiaSelangor43600Malaysia Space Science Centre Institute of Climate ChangeUniversiti Kebangsaan MalaysiaSelangor43600Malaysia Department of Computer and Communication Engineering Faculty of Computer Science and EngineeringPatuakhali Science and Technology UniversityPatuakhali8602Bangladesh

This work presents a dual band epsilon negative(ENG)metamaterial with a bilateral coupled split ring resonator(SRR)for use in C and X band wireless communication *** traditional split-ring resonator(SRR)has been amended with this engineered *** proposed metamaterial unit cell is realized on the 1.6 mm thick FR-4 printed media with a dimension of 10×10 *** resonating patch built with a square split outer *** interlinked inner rings are coupled vertically to the outer ring to extend its electrical length as well as to tune the resonance *** simulation is performed using CST studio suite 2019 to design and performance *** transmission coefficient(S21)of the proposed unit cell and array configuration exhibits two resonances at 6.7 and 10.5 GHz with wide bandwidth extended from 4.86 to 8.06 GHz and 10.1 to 11.2 GHz,*** permittivity is noted at frequencies between 6.76–9.5 GHz and 10.5–12 GHz,consecutively,with near-zero refractive index and *** optimal EMR value depicts the compactness of the proposed *** 1×2,2×2 and 4×4 arrays are analyzed that shows similar response compared to the unit *** results of the 2×2 array shows the close similarity of S21 response as compared to *** observed properties of the proposed unit cell ascertain its suitability for wireless communications by enhancing the gain and directivity of the antenna system.

关键词： Metamaterial epsilon negative near-zero index split ring resonator wireless communications

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