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Selection of Rendezvous Points Using Fuzzy Logic for Mobile Data Collection in Wireless Sensor Networks

Selection of Rendezvous Points Using Fuzzy Logic for Mobile ...

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2024 International Conference on Knowledge engineering and Communication Systems, ICKECS 2024

作者： Raman, Ramakrishnan Kumar, Vikram Pillai, Biju G. Rabadiya, Dhaval Patre, Smruti Meenakshi, R. India Srv Media Pvt. Ltd India Biib Faculty of Management It & Business Analytics India Parul Institute of Technology Parul University Computer Science and Engineering Faculty of Engineering and Technology India India Chennai Institute of Technology Computer Science and Engineering India

ISBN: (纸本)9798350359688

Wireless Sensor Networks (WSNs) are a cornerstone of modern IoT applications, enabling data collection across various environments. The efficiency of these networks, however, is hampered by the limited energy resources of sensor nodes and the challenges inherent in mobile data collection. This paper proposes a novel approach to address these challenges through the strategic selection of rendezvous points (RPs) using fuzzy logic. Our method leverages the flexibility and decision-making process of fuzzy logic to evaluate and integrate multiple dynamic variables, including node energy levels, collector mobility patterns, and data priority, to dynamically determine optimal RPs. This approach not only facilitates efficient data transmission but also significantly conserves the energy of sensor nodes, thereby extending the network's lifespan. We present a comprehensive model incorporating a fuzzy inference system for RP selection, tailored to adapt to the changing conditions of WSNs. Through extensive simulations, our results demonstrate a marked improvement in network performance, showcasing reduced energy consumption and minimized data collection latency. The proposed fuzzy logic-based selection method offers a robust and adaptive solution to the challenges of mobile data collection in WSNs, promising enhanced efficiency and prolonged operational longevity of sensor networks. © 2024 IEEE.

关键词： Sensor nodes

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Optimizing Algorithms for Human Behavior Recognition: Single-Modality Spatiotemporal Convolutional Networks 11

Optimizing Algorithms for Human Behavior Recognition: Single...

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11th IEEE International Conference on Behavioural and Social Computing, BESC 2024

作者： Zhao, Rui Hao, Jutao Feng, Zhikun Wang, Xianzhi Prasad, Mukesh Huo, Huan School of Computer Science University of Technology Sydney Faculty of Engineering and IT Sydney Australia School of Electric Information Engineering Shanghai Dianji University Shanghai China School of Computer Science and Engineering Tianjin University of Technology Tianjin China

ISBN: (纸本)9798331531904

Behavior recognition constitutes a pivotal area of research within computer vision and serves as an integral technology in video surveillance and related domains, thereby possessing substantial research value. Convolutional neural networks (CNNs) have been proven to possess robust learning capabilities. However, due to the high complexity and variability of human behavior, recognizing human behaviors in videos remains challenging due to the difficulty of capturing useful features over long time series and the redundancy of multi-frame information. To address these issues and improve the utilization of continuous frame information, we have designed a cross-frame multiscale information fusion module. This module allows the backbone network to acquire multiscale temporal features from different frames, thereby reducing information redundancy across multiple frames while minimizing additional computational costs. Furthermore, to mitigate the problem of video temporal feature loss, we introduce an easily integrable attention mechanism module, the Easy-Attention Block. This module facilitates rapid capture of long-range dependencies, enabling the model to focus on the most relative parts of continuous video sequences and suppress irrelevant temporal information. Consequently, the model can extract more discriminative spatial-temporal features, thereby enhancing its efficiency in handling long sequence data. Experimental results express that this model can achieve high recognition accuracy and effectively extract the temporal features of video, suitable for real-time applications in critical infrastructure surveillance, which enhancing safety and reducing potential risks in energy power systems. © 2024 IEEE.

关键词： Spatio-temporal data

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Prospects of Explainability in the Hugging Face Hub Landscape 11

Prospects of Explainability in the Hugging Face Hub Landscap...

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11th Workshop on Software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2024

作者： Brdnik, Saša Heričko, Tjaša Faculty of Electrical Engineering and Computer Science University of Maribor Koroška cesta 46 Maribor Slovenia

Machine learning models are widely adopted in intelligent systems to support decision-making across various domains, such as healthcare, finance, and law enforcement. Despite their increasingly remarkable performance, the opacity of these models poses substantial challenges, particularly in the aspect of explainability. The Hugging Face Hub has become a pivotal repository for publicly available machine learning models, extensively reused in both academia and industry. This paper aims to address the imperative for explainability by analyzing the current state of inherent and non-augmented perceived explainability of machine learning models shared on the platform. By data mining the model registry and exploring the models’ documentation, the models were categorized based on five common classes of machine learning algorithms discussed and empirically investigated from end-users’ perspectives regarding explainability in existing works. Building on theoretical and user-centred empirical evidence from prior works focused on model performance and explainability, this work attempts to contextualize these two dimensions within the real-world distribution and popularity of models on the hub, thereby introducing a third dimension. Additionally, this work examines explainability through a three-tier categorization of models based on their explainability, i.e., non-, mediocrely-, and highly-explainable. The findings highlight the disproportionate prevalence of models built on deep neural networks, which are considered among the least explainable compared to those based on other classes of learning algorithms. © 2024 Copyright for this paper by its authors.

关键词： Adversarial machine learning

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Radar Backscatter Communication with Vibrating Surfaces 7

Radar Backscatter Communication with Vibrating Surfaces

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7th IEEE MTT International Conference on Microwaves for Intelligent Mobility, ICMIM 2024

作者： Pessing, Carlos Domnik, Christoph Meuleners, Michael Degen, Christoph Faculty of Electrical Engineering and Computer Science Hochschule Niederrhein - University of Applied Sciences Krefeld47805 Germany

ISBN: (纸本)9783800763641

This paper presents a method of backscatter communication. Backscatter communication is a technology whereby a signal reflected back to the source is utilized to transmit information. An FMCW radar operating in the 60 GHz band with maximum bandwidth of 4 GHz is employed to this purpose. In this experiment the radar signal is modulated using a vibrating surface. The vibrating surface is generated by a licence plate attached to a loudspeaker. Encoding of the signal involves information in the form of a bit sequence. If this concept is applied, for example, in traffic scenarios, it can enable communication between road users. The experiments have shown that the radar correctly recognizes the bit sequence, thereby making information transfer possible. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Backscattering

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Capability Testing of Layered Specimens in Plane Strain Compression Method 14th

Capability Testing of Layered Specimens in Plane Strain Comp...

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14th International Conference on Technology of Plasticity, ICTP 2023

作者： Szőke, Dániel Gy. Kölüs, Martin L. Borbély, Richárd Béres, Gábor J. GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemét6000 Hungary

ISBN: (纸本)9783031409196

This study presents the experimental results of layer-compression tests in plane strain state as well as the role of the obtained parameters on the simulated thinning tendency of a cylindrical deep drawn part. The work hardening law has a special importance in numerical simulations, thus it is mostly expected to be known over a large range of deformation. Tensile test, which counts as a fundamental method for material characterization, is therefore often complemented by other experiments, such as hydraulic bulge test, or plane strain compression test in sheet metal forming. The main drawbacks of the plane strain compression test are the lateral tool misalignment, the stress concentration at the tool edges and the undesirable effect of the friction. The thinner the applied sheets, the first two things are more pronounced due to the geometrical constraints that ensure the plane strain state. To overcome these disadvantages, layered specimens were investigated with rounded-edge tools in the present research. Our results show that the shear contribution in the compression zone can be effectively reduced by two- or three-layered sheets, with a minimum of two times higher deformation than it occurs in tension. Besides, a better lubricant condition is also easier to achieve in the multi-layered arrangement. The effect of the obtained work hardening parameters is also briefly outlined using numerical simulations and the Taguchi method. It was initially observed that none of the hardening parameters have more significance on thinning than others. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Strain hardening

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Development of a Nail-based Application for the Detection of Disease using Image Processing 2

Development of a Nail-based Application for the Detection of...

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2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Gote, Pradnyawant M. Kumar, Praveen Dhale, Trishul Mishra, Gaurav Vedprakash Faculty of Engineering and Technology Department of Computer Science & Design Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Computer Science & Medical Engineering Maharashtra Wardha442001 India Jawaharlal Nehru Medical College Department of Radiodiagnosis Maharashtra Wardha442001 India

ISBN: (纸本)9798331528713

Disease diagnosis using non-invasive techniques is a key determinant in the improvement of outcomes in patients and the enhancement of precautionary health measures. The study focuses on the design and development of a nail-based detection application employing image processing techniques to detect diseases such as systemic disease, fungal disease, Leukonychia (White spots on nails) and Paronychia (Nail bed infection) through analysis of the patterns of the fingernails and other related symptoms. The developed system integrates several techniques, comprising a customized imaging application, a user-friendly interface, and software for real-time image processing and disease classification. A variety of algorithms proposed for image processing, such as Median filtering, Sobel Mask and HOG features, are designed to extract important features from nail images and then use machine learning models that match these features against a database of established markers of various diseases. Comprehensive testing utilizing an annotated dataset of nail images demonstrated the system's accuracy in classifying certain diseases, further showcasing its potential for possible usage as a proficient tool for early disease diagnosis. Thus, this application is easy to use, user-friendly interface, and provides advancements in diagnosing diseases both in clinical settings and in the comfort of one's home. The incorporation of this technology into routine clinical practice might facilitate the possibility of early diagnosis and early intervention, which could improve patient outcomes and reduce healthcare system burdens. © 2024 IEEE.

关键词： Median filters

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A Review on the Role of Microrobots and Nanorobots used in Healthcare Domain 6

A Review on the Role of Microrobots and Nanorobots used in H...

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6th Parul International Conference on engineering and Technology, PICET 2024

作者： Kumar, Shravan Kumar, Praveen Kumar, Rajan Kumar, Mukesh Kumar, Dhiraj Kumar, Gulshan Department of Computer Science and Design Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research Maharashtra Wardha India Department of Computer Science and Medical Engineering Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research Maharashtra Wardha India

ISBN: (纸本)9798350369748

Advanced technology such as microrobots and nanorobots have the potential to completely transform the healthcare industry. These tiny robotic devices provide fine control for a range of biological applications since they operate at the micro and nanoscales. This review explores the various healthcare uses, fabrication ideas, and design concepts of microrobots and nanorobots. It specifically looks at their works in tissue engineering, minimally invasive surgery, and targeted drug administration. Aiming to harness the transformative impact of these emerging technologies in healthcare, research and practitioners can recive significant insights from the discussion of challenges and future directions in the sector. Design-wise, microrobots and nanorobots display a range of configurations suited to particular uses, such as payload delivery systems, sensing capabilities, and propulsion mechanisms. © 2024 IEEE.

关键词： Microrobots

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Iot - Enabled Technologies for Sustainable Smart Agriculture and their Comprehensive Survey

Iot - Enabled Technologies for Sustainable Smart Agriculture...

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2023 International Conference on Artificial Intelligence and Smart Communication, AISC 2023

作者： Santosh, S. Raghavendra, R. Deemed-to-be University Faculty of Engineering and Technology Jain Department of Computer Science and Engineering Bangalore India Deemed to Be University Department of Computer Science and IT Jain Bangalore India

ISBN: (纸本)9798350322309

Both the quality and amount of food demanded have increased, necessitating agricultural technology and intensification. Agricultural innovation is booming thanks to the Internet of Things, or IoT, is a cutting-edge technology. Research institutions and scientific organizations are creating IoT-based goods and solutions to solve a range of agricultural concerns. This study offers a thorough literature assessment by examining IoT technology and their current applications in a range of farming-related businesses. The comprehensive reviews of the literature conducted for this study were entirely based a review of the literature publications published in government publications during the previous ten years. Carefully selected articles from a wide variety have been arranged into courses. The major objective gathers all pertinent studies on IoT agricultural applications, sensors/devices, communication protocols, and community types. Additionally, it addresses the main problems and challenges that are the focus of modern agricultural research. © 2023 IEEE.

关键词： Internet of things

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Knowledge Editing in Language Models via Adapted Direct Preference Optimization

Knowledge Editing in Language Models via Adapted Direct Pref...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Rozner, Amit Battash, Barak Wolf, Lior Lindenbaum, Ofir Faculty of Engineering Bar Ilan University Israel School of Computer Science Tel Aviv University Israel

ISBN: (纸本)9798891761681

Large Language Models (LLMs) can become outdated over time as they may lack updated world knowledge, leading to factual knowledge errors and gaps. Knowledge Editing (KE) aims to overcome this challenge using weight updates that do not require expensive retraining. We propose treating KE as an LLM alignment problem. Toward this goal, we introduce Knowledge Direct Preference Optimization (KDPO), a variation of the Direct Preference Optimization (DPO) that is more effective for knowledge modifications. Our method is based on an online approach that continually updates the knowledge stored in the model. We use the current knowledge as a negative sample and the new knowledge we want to introduce as a positive sample in a process called DPO. We also use teacher-forcing for negative sample generation and optimize using the positive sample, which helps maintain localized changes. We tested our KE method on various datasets and models, comparing it to several cutting-edge methods, with 100 and 500 sequential edits. Additionally, we conducted an ablation study comparing our method to the standard DPO approach. Our experimental results show that our modified DPO method allows for more refined KE, achieving similar or better performance compared to previous methods. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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Negative Impact of Approximated Signed Addition on Power Reduction

Negative Impact of Approximated Signed Addition on Power Red...

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2023 International Symposium on Devices, Circuits and Systems, ISDCS 2023

作者： Hama, Hiroyuki Ukezono, Tomoaki Sato, Toshinori Graduate School of Engineering Fukuoka University Department of Electronics Engineering and Computer Science Fukuoka Japan Faculty of Engineering Fukuoka University Department of Electronics Engineering and Computer Science Fukuoka Japan

ISBN: (纸本)9798350315042

This paper presents evaluation results of a power- efficient JPEG compression circuit utilizing approximate computing. To achieve power efficiency, we replace summations in Discrete Cosine Transform (DCT) with approximate additions that follow Carry-Maskable Adder (CMA) [1]. We evaluate both the quality of the compressed images and the power consumed by the circuit. However, we observed unexpected results where power consumption increased despite the use of approximation, contradicting our expectations. Our detailed investigations revealed that the addition of negative values in 2's complement representation led to an increased wasted power consumption. Although reports on investigations related to power reduction through approximate computing offer valuable insights for researchers in this field, they are often difficult to find. This paper shows the reasons why power reduction could not be achieved in this specific case study. © 2023 IEEE.

关键词： Discrete cosine transforms

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