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9th International Conference on Mathematics and computers in Sciences and Industry, MCSI 2024

作者： Muntean, Emanuel Leba, Monica University of Petrosani Department of System Control and Computer Engineering Petrosani Romania

ISBN: (纸本)9798350377224

This paper conducts a comparative analysis of human torso posture estimation methodologies, focusing on an inertial measurement unit (IMU) sensor coupled with an Arduino UNO as a wearable approach, and Kinect V2, utilizing OpenCV for posture analysis. The core objective of this study is to ascertain which method yields greater precision in the estimation of human torso posture. The IMU sensor, characterized by its wearability, provides the distinct advantage of unobtrusiveness and the capability to record motion across diverse environments. Conversely, Kinect V2 leverages computer vision techniques to derive posture estimations from visual data in real-time. Through comprehensive experimentation, this research evaluates the accuracy of both methodologies by juxtaposing their posture estimation outcomes. The findings of this investigation aim to significantly contribute to the enhancement of human posture estimation systems, with wide-ranging implications for health, sports, and ergonomics. © 2024 IEEE.

关键词： Ergonomics

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Automatic segmentation, classification, and prediction of pelvic bone tumors using deep learning techniques

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Journal of engineering and Applied Science 2024年第1期71卷 214页

作者： Shouman, Mona Rahouma, Kamel Hussein Hamed, Hesham F. A. Computer and System Engineering Department Faculty of Engineering Minia University Minia Egypt Faculty of Engineering Minia University Minia Egypt College of Artificial Intelligence Russian University Cairo Egypt

MRI and CT images are widely utilized for detecting tumors in internal organs. However, accurately distinguishing tumors using these images only, poses a challenge. This demands human expertise to effectively mark tumors in a given MRI or CT image, which is time-consuming. In this study, MONAI Label and MONAI Dynamic U-Net (DynU-Net) were used to segment tumors in any given 3D CT image of the pelvic bone, aiming to assist radiologists further. This method helps to run the model without needing a GPU which is better than traditional approaches. In addition, a convolutional neural network (CNN) was used to classify the tumors as benign or malignant and to predict three grades of tumors (low, medium, and high). The use of CNN in classification and prediction gives higher results than other studies. A dataset of 178 3D CT picture images was employed to feed the networks with the help of Adam optimizer and Categorical cross-entropy. We employ a set of 3D CT scans because of their greater contrast and spatial resolution which is better used for pelvic bone tumors. The Dice similarity coefficient (DSC) and Hausdorff distance (HD) have been used to perform calculations in segmentation. The results show a DSC of 0.7660280 and an HD of 16.75480. A range of performance metrics, such as sensitivity, specification, and F1-score for classification and prediction methods, are used to evaluate the accuracy of the proposed system. The system has accuracy (99.4%) for classification and (97.8%) for prediction. These findings indicate that MONAI Label is effective for automatic segmentation of tumors in a given CT scan;with high accuracy. Moreover, CNN is useful for classification and prediction systems with high accuracy. However, achieving better results is possible with an abundance of training samples. © The Author(s) 2024.

关键词： computerized tomography

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2D Posture Estimation of Human Arm 9

2D Posture Estimation of Human Arm

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9th International Conference on Mathematics and computers in Sciences and Industry, MCSI 2024

作者： Rosca, Sebastian Daniel Leba, Monica Sibisanu, Remus University of Petrosani Department of System Control and Computer Engineering Petrosani Romania

ISBN: (纸本)9798350377224

Human pose estimation and automatic detection is a common task in Human-computer Interaction but especially more capitalized in human-robot interaction inspired from biological form of human anatomy to realize a biomimetic control. In this sense, using human pose estimation it can be realized the whole human body posture estimation using anatomical human joints detection as inputs for specialized algorithms to calculate it based on key points obtained from a person Kinematic tree using regression, generation or part relation as models to estimate the optimal position from video or even from image. In this paper we propose a solution to estimate of 2D human arm posture of a subject using image capture as input for advanced machine learning algorithms to determine the subject joints position used to control in biomimetic manner a simulation of human like robotic arm with six degrees of freedom as a computer-aided model in Matlab-Simulink based on forward kinematics. © 2024 IEEE.

关键词： MATLAB

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ARCHER:a ReRAM-based accelerator for compressed recommendation systems

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Frontiers of computer Science 2024年第5期18卷 147-160页

作者： Xinyang SHEN Xiaofei LIAO Long ZHENG Yu HUANG Dan CHEN Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabClusters and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China

Modern recommendation systems are widely used in modern data *** random and sparse embedding lookup operations are the main performance bottleneck for processing recommendation systems on traditional platforms as they induce abundant data movements between computing units and ***-based processing-in-memory(PIM)can resolve this problem by processing embedding vectors where they are ***,the embedding table can easily exceed the capacity limit of a monolithic ReRAM-based PIM chip,which induces off-chip accesses that may offset the PIM ***,we deploy the decomposed model on-chip and leverage the high computing efficiency of ReRAM to compensate for the decompression performance *** this paper,we propose ARCHER,a ReRAM-based PIM architecture that implements fully yon-chip recommendations under resource ***,we make a full analysis of the computation pattern and access pattern on the decomposed *** on the computation pattern,we unify the operations of each layer of the decomposed model in multiply-and-accumulate *** on the access observation,we propose a hierarchical mapping schema and a specialized hardware design to maximize resource *** the unified computation and mapping strategy,we can coordinatethe inter-processing elements *** evaluation shows that ARCHER outperforms the state-of-the-art GPU-based DLRM system,the state-of-the-art near-memory processing recommendation system RecNMP,and the ReRAM-based recommendation accelerator REREC by 15.79×,2.21×,and 1.21× in terms of performance and 56.06×,6.45×,and 1.71× in terms of energy savings,respectively.

关键词： recommendation system ReRAM processing-in-memory embedding layer

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Online Queue-Aware Service Migration and Resource Allocation in Mobile Edge Computing

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 8063-8078页

作者： Du, An Jia, Jie Chen, Jian Wang, Xingwei Huang, Ming Northeastern University School of Computer Science and Engineering Engineering Research Center of Security Technology of Complex Network System Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110819 China Northeastern University School of Computer Science and Engineering Shenyang110819 China

Mobile edge computing (MEC) integrated with Network Functions Virtualization (NFV) helps run a wide range of services implemented by Virtual Network Functions (VNFs) deployed at MEC networks. This emerging paradigm offers flexible edge resource management for Internet Service Providers (ISPs) and improves service satisfaction of diverse applications. However, a critical challenge lies in processing extremely unpredictable and bursty traffic flow, especially in event-trigger sensing tasks. In this paper, we study queue-aware service migration and resource allocation in an MEC network, where different devices with different arrival patterns request different network services. To this end, we first formulate a novel long-term operation cost minimization problem subject to the stability of multiple queues by adopting a simultaneous migration scheme and determining resource allocation dynamically. To address the problem efficiently, we propose an online control framework to make decisions without any prior system information. We first adopt the Lyapunov optimization technique to decompose the long-term optimization problem into multi-per-slot subproblems. Then, we adopt a decoupled optimization algorithm based on the coordinate descent method and augmented Lagrangian method to solve the offline mixed integer non-linear programming (MINLP) subproblems. Extensive results reveal that the proposed online optimization framework can efficiently balance queue stability and cost consumption. © 1967-2012 IEEE.

关键词： Mobile edge computing

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Towards a robust solution to mitigate all content-based filtering draw-backs within a recommendation system

International Journal of Systematic Innovation

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International Journal of systematic Innovation 2023年第7期7卷 89-111页

作者： Stitini, Oumaima Kaloun, Soulaimane Bencharef, Omar Computer and system engineering laboratory Cadi Ayyad University Marrakesh Morocco

Recommendation systems deliver a method to simplify the user’s desire. Recommendation systems are now commonly used on the Internet. It helps suggest items in various categories, including e-commerce, medical, education, tourism, and industrial. The electronic commerce sector has taken a big place in our daily lives as an active research tool, which helps people find what they are looking for. This paper presents a new contribution based on the combination of different algorithms to find a suitable solution to all the drawbacks of content-based recommender systems. The main contribution of this research lies in how to solve each problem and move on to the next. This paper describes an Ideal Solution Mitigating Content Disadvantages based on Three Phases called ISMCD_3P. Experiments show that the algorithm can propose an appropriate solution to solve all the problems of content-based filtering. Experimentations operating on real datasets are used to estimate the efficacy of our strategy. © (2023). All Rights Reserved.

关键词： Content-based filtering drawbacks Limited content Over-specialization Serendipity Sparsity

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A Fully LTPS-TFT-Based Bi-Directional Biomedical Interface Circuit for Large-Area Healthcare Applications

IEEE Journal on Flexible Electronics

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IEEE Journal on Flexible Electronics 2025年第12期3卷 526-532页

作者： Zhang, Hanbo Lou, Yuqing Zhang, Zhihang Li, Yongfu Rokhan, Fakhrul Wang, Guoxing Zhao, Jian Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai200240 China Universiti Putra Malaysia Faculty of Engineering Department of Computer and Communication System Engineering Selangor Serdang43400 Malaysia

This paper proposed a fully LTPS-TFT-based bi-directional biomedical pixel interface with integrated a high linearity stimulator and a high-performance bio-potential sensing front-end circuit to amplify and digitize biological signals for high robustness data transmission. All circuits are designed and manufactured under a 3-μm LTPS process. We demonstrated the experiment in saline using the stimulator circuit to simulate stimulation inside the organism, achieving stimulation with different average currents under different duty cycles. The proposed front-end circuit has a gain of 40 dB. The referred input voltage noise of the entire signal chain is 86.2 μV/√Hz, and the ENOB is 9.13 bits at an input of 0.5 mVPP. Simultaneously conducting statistical testing on 20 chips has achieved a 1.05 dB SNDR standard deviation. Finally, we use a function signal generator to simulate the input signals of ECoG, ECG, and EOG, then use front-end circuits to read and reconstruct them to demonstrate that the proposed pixel interface can correctly read common biomedical signals for healthcare applications. © 2022 IEEE.

关键词： Image segmentation

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Advancement in piezoelectric nanogenerators for acoustic energy harvesting

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Microsystems & Nanoengineering 2024年第6期10卷 21-54页

作者： Fandi Jean Muhammad Umair Khan Anas Alazzam Baker Mohammad Department of Computer and Information Engineering Khalifa UniversityAbu Dhabi 12778UAE System on Chip Lab Khalifa UniversityAbu Dhabi 12778UAE Department of Mechanical Engineering Khalifa UniversityAbu Dhabi 12778UAE

The demand for sustainable energy sources to power small electronics like IoT devices has led to exploring innovative solutions like acoustic energy harvesting using piezoelectric nanogenerators(PENGs).Acoustic energy harvesting leverages ambient noise,converting it into electrical energy through the piezoelectric effect,where certain materials generate an electric charge in response to mechanical stress or *** review paper provides a comprehensive analysis of the advancements in PENG technology,emphasizing their role in acoustic energy *** begin by discussing the essential principles of piezoelectricity and the design considerations for nanogenerators to optimize energy capture from sound *** discussion includes a detailed examination of various piezoelectric materials,such as polyvinylidene fluoride(PVDF),lead zirconate titanate(PZT),and zinc oxide(ZnO)nanowires,which are known for their superior piezoelectric properties.A critical aspect of this review is the exploration of innovative structural designs and resonance devices that enhance the efficiency of *** delve into the mechanisms and benefits of using Helmholtz resonators,quarter-wavelength tubes,and cantilever beams,which are instrumental in amplifying acoustic signals and improving energy conversion *** device’s design parameters and operational principles are scrutinized to highlight their contributions to the *** review addresses practical applications of PENGs in various *** monitoring systems,wearable electronics,and medical devices stand to benefit significantly from the continuous and sustainable power supplied by *** applications can reduce reliance on batteries and minimize maintenance by harnessing ambient acoustic energy,leading to more efficient and longer-lasting *** the promising potential of PENGs,several challenges remain,including material degradation,efficiency limitations,and integrating these devices i

关键词： piezoelectric ambient integrating

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Unlocking the Potential of Large Language Models in Legal Discourse: Challenges, Solutions, and Future Directions 6

Unlocking the Potential of Large Language Models in Legal Di...

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6th International Conference on Intelligent Computing in Data Sciences, ICDS 2024

作者： Kaoutar, M'Rhar Chaima, Ben Jaafar Omar, Bencharef Outmane, Bourkoukou Cadi Ayyad University Computer and System Engineering Laboratory FSTG Marrakesh Morocco

ISBN: (纸本)9798350351200

The rise of Large Language Models (LLMs) has been remarkable, especially exemplified by the achievements of systems such as ChatGPT and Google's Bard. Both specialized and general users are warmly embracing these potent tools, indicating their increasing integration into everyday life. Nevertheless, challenges persist in their widespread adoption, particularly within specialized fields where they necessitate meticulous fine-Tuning and access to high-quality data. Additionally, their lack of interpretability further complicates matters, often relegating them to the status of 'black boxes'. Within the legal domain, LLMs harbor transformative potential but encounter obstacles due to legal hallucinations. This research delves into these hallucinations through a distinct set of legal queries pertaining to Canadian tax law, drawing comparisons between state-of-The-Art LLMs. Its objective is to illuminate their efficacy in legal discourse and specialized domains, capitalizing on their broad knowledge base. The research advocates for fine-Tuning as a potential solution, stressing the significance of domain-specific LLMs and delineating methods for their development. This includes considerations such as dataset curation, preprocessing techniques, model selection, and adherence to regulatory requirements, encompassing the creation of domain-specific vocabularies. Practical implementation entails the generation of domain-specific LLMs tailored for legal tasks such as research, information retrieval, and question answering. Despite inherent limitations, the study proposes avenues for enhancement and underscores the significance of LLMs utilization in legal services. This contributes to the evolution of natural language processing technology within the legal realm. © 2024 IEEE.

关键词： Natural language processing systems

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Body Language Recognition system for Communication Quality Enhancement

Body Language Recognition System for Communication Quality E...

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2024 International Conference on E-Mobility, Power Control and Smart systems, ICEMPS 2024

作者： Maharasi, M. Nandhini, V. Trisha, I. Rajalakshmi Engineering College Computer Science and Business System Thandalam Chennai India

ISBN: (纸本)9798350394399

The development of computer vision technology in recent days, enhanced the human-computer interface (HCI) systems in a broad spectrum. The recent developments of human computer interfacing such as Augmented reality applications, gesture-based control devices, robotic assistants, patient health care monitoring systems considers human body pose estimation as important process involved in it. The growth of neural computing and artificial intelligence (AI) models plays an optimum role in development of HCI and pose estimation. The presented study considers various existing challenges in body language recognition systems and its role in communication quality enhancement. The comprehensive study considers existing state of art approaches and its drawbacks, challenges, technology, tool in terms of achieving better accuracy and formulated a robust human pose estimation model using machine learning technology. The suggested architecture and solutions derived from the proposed method are well explored in the article. © 2024 IEEE.

关键词： Augmented reality

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