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共 2526 条记录，以下是61-70 订阅

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Development of a Real-Time Wireless Multi-Node Metal Pipeline Localization System via Bluetooth Link

Development of a Real-Time Wireless Multi-Node Metal Pipelin...

引用

2024 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2024

作者： Jiang, Bing Choi, Byungkeun Kuk, Gahee Park, Hangue Kim, Jeonghee Utah Tech University Dept. of Electrical and Computer Engineering St. GeorgeUT United States Hanyang University Dept. of Electronic Engineering Seoul Korea Republic of SungKyunKwan University Dept. of Biomedical Engineering Dept. of Intelligent Precision Healthcare Convergence Dept. of Meta Bio-health Suwon-si Korea Republic of Texas A & M University Dept. of Elect. and Comp. Engineering College StationTX United States Hanyang University Dept. of Biomedical Engineering Dept. of Artificial Intelligence Dept. of AI Semiconductor Seoul Korea Republic of

ISBN: (纸本)9798331530839

Several efforts have been approached to minimize the limitations and risks associated with current methods of locating underground pipelines in construction projects, especially during excavation operations. Traditional methods rely on flags to mark the general location of pipelines, which can be imprecise and lead to accidents. Excavation damage is a significant cause of pipeline failures, resulting in injuries, fatalities, and financial losses. To address these issues, we have been studied to accurately locate the underground ferromagnetic pipeline using magnetic anomaly detection approach using multi-dimensional magnetic sensor array using a smart external magnetic interference cancellation algorithm under the lab-based setting. To expand the successful approach in the actual construction setting, we proposed the development of a smart, real-time, wireless multi-node sensor system that uses magnetic anomaly detection algorithm on a custom smartphone app. This system aims to improve the accuracy of pipeline location detection during excavation, thereby reducing the potential for accidents and enhancing safety on construction sites. We have successfully designed and assembled the multi-node metal pipeline localization system via BLE. By attaching three modules on the excavator bucket, we were able to collect the sensor data using a custom-designed app and estimate the distance from the pipe. © 2024 IEEE.

关键词： construction collision magnetic anomaly detection multi-array magnetic sensors underground pipeline localization

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Design and Evaluation of a Low-profile Haptic Interface Based on Surface electrical Nerve Stimulation 1

Design and Evaluation of a Low-profile Haptic Interface Base...

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1st IEEE Conference on Telepresence, Telepresence 2024

作者： Jakes, Rachel S. Mesias, Luis Santos, Veronica J. Fu, Michael J. Tyler, Dustin J. Cwru Dept. of Biomedical Engineering United States Dept. of Mechanical and Aerospace Engineering United States United States Cwru Dept. of Electrical Computer and Systems Engineering United States The MetroHealth System Dept. of Physical Medicine & Rehabilitation United States Advanced Platform Technology Center Dept. of Va Northeast Ohio Healthcare System United States

ISBN: (纸本)9798331528249

Haptic feedback in telepresence applications is vital for remote task performance and object manipulation. To maximize telepresence capabilities, haptic systems need to be integrated with immersive telepresence interfaces such as virtual reality, which offer benefits such as improved spatial awareness and operator mobility. Compatibility with the mobility of these systems and their built-in optical hand tracking require low-profile wearable interfaces. Further, for full functional benefits, haptic systems must be able to elicit spatially congruent sensation without impeding operator movement and physical object interactions. In this paper, we describe the design of a lightweight, compact, and adaptable surface electrical nerve stimulation-based haptic interface. We demonstrate its capacity to consistently generate spatially congruent sensation on the all five fingertips without occlusion, as well as its compatibility with headset-based optical hand tracking. © 2024 IEEE.

关键词： Haptic interfaces

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Increasing the RES Hosting Capacity of the Cyprus Distribution System

Increasing the RES Hosting Capacity of the Cyprus Distributi...

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CIRED 2024 Vienna Workshop

作者： Therapontos, Phivos Konstantinou, Rafail Charalambous, Charalambos A. Aristidou, Petros Electricity Authority of Cyprus Nicosia Cyprus University of Cyprus Department of Electrical and Computer Engineering Nicosia Cyprus Dept. of Electrical & Computer Engineering & Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (纸本)9781837242672

The Renewable Energy Sources (RES) penetration in the power system of Cyprus has dramatically increased over the last years. As a result, the system is already facing significant challenges limiting the RES hosting capacity of the Distribution Network (DN). The major limitation factors are network congestion and voltage security. In this paper, alternative solutions for increasing the RES hosting capacity in DNs are reviewed, and a methodology is introduced to evaluate their effectiveness. More specifically, different inverter settings and an advanced centralised voltage control from power transformers are used to mitigate voltage-related issues, while network reinforcements and upgrading the operating voltage are considered for further increase in hosting capacity. The solutions and evaluation methodology are tested using a real MV network of the Cyprus distribution system and the strategic plan of the Cyprus Distribution System Operator (DSO) for maximizing RES hosting capacity is outlined. © The Institution of engineering & Technology 2024.

关键词： Distribution transformers

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Development of the Low-Cost Lightweight Exoskeleton System that Enables Social Interaction Activities in Quadriplegic Patients

Development of the Low-Cost Lightweight Exoskeleton System t...

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2024 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2024

作者： Irava, Bernard A. Aichelmann, Kevin J. Jiang, Bing Cho, Hyunsang Park, Hangue Kim, Jeonghee Texas A & M University Dept. of Engineering Technology and Industrial Distribution College StationTX United States Utah Tech University Dept. of Electrical and Computer Engineering St. GeorgeUT United States Hanyang University Dept. of Electronic Engineeringz Seoul Korea Republic of SungKyunKwan University Dept. of Biomedical Engineering Dept. of Intelligent Precision Healthcare Convergence Dept. of Meta Bio-health Suwon-si Korea Republic of Texas A & M University College Station Dept. of Elect. and Comp. Engineering TX United States Hanyang University Dept. of Electronic Engineering Dept. of Biomedical Engineering Dept. of Artificial Intelligence Dept. of AI Semiconductor Seoul Korea Republic of

ISBN: (纸本)9798331530839

Improving the quality-of-life of quadriplegic patients is the most important feature for assistive technology. Despite the availability of advanced assistive technologies and robotic exoskeleton systems, their high cost, invasiveness, and usefulness can make them difficult to incorporate into daily activities. Our research group have developed a tracer-free Multifunctional intraORal Assistive technology (MORA) to enable various input modalities through tongue motions to access computers, wheelchairs, and smartphones. We now approach the development of a wearable robotic sleeve that uses the MORA system to allow a quadriplegic user to control their arm. Our design, the Kinematically Assistive Robotic Arm (KARA), focused on low-cost (less than $500), is an easy-to-mount exoskeleton device that can aid the user physically express within social interactions, thus ultimately benefiting their emotional and mental recovery as well as rehabilitation effects. In this study, we introduce our preliminary robotic exoskeleton system with electrical, mechanical, and software designs. We validated our system by performing four social interaction activities: thumbs up, point finger, raise hand, and hand shacking tasks, using the KARA system. As a results of this validation, the KARA system was able to perform all four tasks with a time deviation of 3.39% and a performance accuracy of 90%. This exoskeleton system can provide a tool to control their paralyzed limbs for social interaction activities with their intention. This system can be easily mounted on the wheelchair and ultimately applied to the tracer-free tongue-based assistive technology for the quadriplegic patients to improve the quality-of-life. © 2024 IEEE.

关键词： Assistive technology

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Smart Mattress Pad for Tracking Pressure Injuries in the Geriatric Population

Smart Mattress Pad for Tracking Pressure Injuries in the Ger...

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2023 IEEE MIT Undergraduate Research Technology Conference, URTC 2023

作者： Parvaresh-Rizi, Arianne Wojnilo, Olivia J. Confessore, Joseph Mankodiya, Kunal Solanki, Dhaval Dept. of Electrical Computer and Biomedical Engineering University of Rhode Island KingstonRI United States

ISBN: (纸本)9798350308600

Medical technologies are transforming healthcare, yielding significant advantages. However, detecting pressure injuries in the elderly remains a challenge without efficient monitoring devices. In response, we introduced a novel pressure-sensitive mattress pad, discreet and user-friendly, catering to the geriatric demographic. Enabling continuous monitoring, this device facilitates timely interventions and improves patient outcomes, holding promise to elevate the quality of life for at-risk elderly individuals. This device also empowers caregivers and medical practitioners with these critical insights, as it lays the foundation for timely interventions, tailored treatment plans, and ultimately, improved patient outcomes. © 2023 IEEE.

关键词： Patient treatment

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On the Quantization of Recurrent Neural Networks for Smiles Generation 48

On the Quantization of Recurrent Neural Networks for Smiles ...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Durao, Adriano Arrais, Joel P. Ribeiro, Bernardete Falcao, Gabriel Instituto de Telecomunicações Portugal University of Coimbra Dept. of Electrical and Computer Engineering Portugal Cisuc Portugal University of Coimbra Dept. of Informatics Engineering Portugal

ISBN: (纸本)9781728163277

This paper focuses on the effects of applying quantization during training to Recurrent Neural Networks (RNNs) used in Simplified Molecular-Input Line-Entry System (SMILES) generation, a form of line notation for molecular information used in the development of pharmaceutical drugs, from the PubChem database. It offers the flexibility to choose the precision used by the model, by defining the number of bits at each layer. The RNNs are the focus of the current study, by comparing the performance of three of the most used algorithms, Simple RNN, Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). The models were trained on a selection of SMILES. By exploiting the QK-eras library, quantization performance was compared to their floating-point equivalent for several combinations of parameters. The goal of the testing program developed is to generate a large number of novel SMILES, facilitating the process of Drug Discovery which is traditionally long, and thus very expensive and difficult. By understanding how the behavior of quantized networks deviates from the regular model, in relation to the parameters used, we are able to control the process of choosing whether to quantize a model and to which degree it becomes more or less efficient. In this study, we observed good performance even for 4-bit models making use of LSTM and GRU layers, the same way we concluded that Simple RNN quantization does not compensate the effort. © 2023 IEEE.

关键词： Drug Discovery Gated Recurrent Unit Long Short-Term Memory Quantization Recurrent Neural Networks

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ULung:A Novel Approach for Lung Image Segmentation 6

ULung:A Novel Approach for Lung Image Segmentation

引用

6th International Conference on Computing and informatics, ICCI 2024

作者： Pal, Osim Kumar Roy, Shuvasish Modok, Anup Kumar Teethi, Tajmihir Islam Sarker, Siddhartha Kumer Dept. of Biomedical Engineering University of Kragujevac Kragujevac34000 Serbia Dept. of Electrical and Electronic Engineering American International University-Bangladesh Dhaka Bangladesh Dept. of Computer Science and Engineering Daffodil International University Ashulia Savar Bangladesh Dept. of Space Communication and Navigation Technology BSMRAAU Old Airport Dhaka Bangladesh

ISBN: (纸本)9798350373875

ULung is an innovative medical technology used for segmenting medical images in pulmonary diagnostics. It introduces a modified approach to analyzing and understanding pulmonary conditions. ULung employs cutting-edge deep learning and image processing techniques to isolate intricate characteristics in medical lung images properly. The model uses advanced convolutional neural network architecture as UNet layer stricture to detect abnormalities and delineate anatomical regions reliably. ULung exhibits versatility in handling various lung ailments after extensive training using diverse datasets. The innovative methodology ensures enhanced segmentation performance, enhancing diagnostic precision and expediting medical evaluations. The advent of ULung has greatly enhanced medical imaging, providing clinicians with a potent tool for precise and expeditious lung evaluation. ULung is an impressive advancement in medical image segmentation that can revolutionize standards in respiratory healthcare due to its robustness and adaptability. The model's accuracy achieved using EfficientNetV2 is 99 %, while its precision and recall rates are 98% and 96 %, respectively. The model achieves a Mean Intersection over Union (MeanloU) of 91.48% after the 14th epoch. © 2024 IEEE.

关键词： Image segmentation

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Ethogram-Based Personalization of Human Activity and Agility from Radar μ D Signatures

Ethogram-Based Personalization of Human Activity and Agility...

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2024 IEEE-EMBS International Conference on biomedical and Health informatics, BHI 2024

作者： Kurtoglu, Emre Salehin, Sultanus Amin, Moeness G. Kan, Irene P. McKay, Michelle A. Gurbuz, Sevgi Z. The University of Alabama Dept. of Electrical and Computer Engineering United States Villanova University Dept. of Electrical and Computer Engineering United States Villanova University Dept. of Psychological and Brain Sciences United States College of Nursing Villanova University United States

ISBN: (纸本)9798350351552

Radar has garnered great interest for remote health monitoring due to its ambient operation, effectiveness in the dark, and inability to make visual recordings of private scenes/faces. However, the current state-of-the-art in human activity recognition (HAR) focuses on the classification of persistent gaits, such as walking, and ignores the transitions between activities. The characterization of a person's ability to transition between postural states is highly individual and influenced by the person's physical and mental health. This paper presents a personalized, ethogram-based approach to HAR, which jointly characterizes the agility of transitions in addition to activity classification. We develop a multi-input multi-task learning (MIMTL) approach to simultaneously classify both human activity and agility. Our proposed approach yields accuracies of over 98% and 90% for the joint characterization tasks. Various interventions affecting gait are applied to show how the proposed approach can lead to agility-based detection of changes in gait. © 2024 IEEE.

关键词： Electronic health record

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Efficient Boxing Punch Classification: Fine-Grained Skeleton-based Recognition Made Light 5

Efficient Boxing Punch Classification: Fine-Grained Skeleton...

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5th International Conference on computer Vision and Computational Intelligence, CVCI 2024

作者： Baghel, Vipul Rithihas, Nagisetti Sarvanan, M. Srinivasan, Babji Hegde, Ravi Sadananda Dept. of Electrical Engineering IIT Gandhinagar Gujarat India Dept. of Electronics and Communication Engineering IIT Kharagpur West Bengal India Dept. of Applied Mechanics and Biomedical Engineering IIT Madras Tamil Nadu India

ISBN: (数字)9781510680067

ISBN: (纸本)9781510680050

Sports analytics is a field of study that utilizes camera and sensor data to monitor the athlete’s performance and health to optimize the player's strategy and increase the success rate. Coaches rely on analytics to scout opponents and optimize play calls in gameplay. With the advancement in artificial intelligence, accessible and in-dept. data collection has been enabled. The well-grounded technique for performance evaluation in sports analytics is Human Pose Estimation (HPE). Our focus is on real-time action recognition in combat sports like boxing. Existing state-of-the-art deep learning models are heavily parameterized, so can’t be used in real-time in any low-end devices. Apart from this, fine-grained classification in highly dynamic activities in sports are typically performed using sensors only. Our proposed Machine Learning based pipeline provides real-time fine-grained solution for 14 boxing punch types of classification using RGB video only. Our approach includes the implementation of three novel and generalized motion dynamics features that encode velocity as well as acceleration of the pose sequences., 1) Unified-Axis Angular Encoding (UAE), 2) 2D Motion Dynamics Descriptors (2DMDD), 3) Fifth-order Angular Encoding (FAE). We employed classical machine learning algorithms I.e., Support Vector Machine (SVM), Random Forest (RF), and K Nearest Neighbours (KNN) to make a lightweight model and test it on YouTube videos. The average accuracies of pipeline using the proposed features are found to be 55%, 92% and 84% for UAE, 2DMDD, and FAE respectively. Using KNN, we have achieved 99% accuracy on 10-fold cross-validation by using FAE features. © 2024 SPIE.

关键词： computer vision

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Context-aware Container Orchestration in Serverless Edge Computing

Context-aware Container Orchestration in Serverless Edge Com...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Guan, Peiyuan Chen, Chen Chen, Ziru Cai, Lin X. Hao, Xing Taherkordi, Amir University of Oslo Dept. of Informatics Oslo Norway University of Cambridge Dept. of Computer Science and Technology Cambridge United Kingdom Illinois Institute of Technology Dept. of Electrical and Computer Engineering Chicago United States Northwest Univesity School of Information Science and Technology Xi'an China

ISBN: (纸本)9798350351255

Adopting serverless computing to edge networks benefits end-users from the pay-as-you-use billing model and flexible scaling of applications. This paradigm extends the boundaries of edge computing and remarkably improves the quality of services. However, due to the heterogeneous nature of computing and bandwidth resources in edge networks, it is challenging to dynamically allocate different resources while adapting to the burstiness and high concurrency in serverless workloads. This article focuses on serverless function provisioning in edge networks to optimize end-to-end latency, where the challenge lies in jointly allocating wireless bandwidth and computing resources among heterogeneous computing nodes. To address this challenge, We devised a context-aware learning framework that adaptively orchestrates a wide spectrum of resources and jointly considers them to avoid resource fragmentation. Extensive simulation results justified that the proposed algorithm reduces over 95% of converge time while the end-to-end delay is comparable to the state of the art. © 2024 IEEE.

关键词： Quality of service

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