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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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Localization of Dengue Virus Likelihood Using Image Processing Technique 6

Localization of Dengue Virus Likelihood Using Image Processi...

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6th IEEE International Conference on Emerging Smart Computing and Informatics, ESCI 2024

作者： Hosen, Md. Mahbub Islam, Md. Rahatul Tabassum, Faria Tonni, Syeda Thamina Noor, Malik Mohammad Nafiur Rahman, Shahid Northern University of Bangladesh Dept. of Computer Science and Engineering Dhaka Bangladesh Kyushu Institute of Technology Dept. of Human Intelligence Systems Wakamatsu Kitakyushu Japan Bangladesh University of Engineering and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh Bangladesh Advance Robotics Research Center Human Intelligence Lab Dhaka Bangladesh Canadian University of Bangladesh Dept. of Electrical and Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798350306613

The Aedes mosquito, found in tropical areas, transmits, and causes dengue fever. The spread of the dengue fever virus from an infected Aedes mosquito bite typically takes between three and fifteen days to manifest itself clinically as dengue fever symptoms. Early and automated detection of this illness will reduce the occurrence of outbreaks and facilitate the digitization of the system. Our primary objective is to identify regions at high risk for dengue fever using limited image data through the utilization of sophisticated machine learning and image processing methods. This work showcases the application of transfer learning algorithms for the timely identification of regions at risk for dengue mosquito infestation, particularly in situations where obtaining early data on dengue outbreaks is challenging. The experiments included images of 2150 dengue-positive data sets and 1440 dengue-negative data sets. We used AI and image classifiers Yolo V4 Tin, Tensor Flow, Google Colab, etc. for the training data set, and the system makes predictions with a 99.63% accuracy rate. Our system has some unique attributes;it not only detects the percentage of dengue probability but also the specific dengue-prone location on the submitted image. © 2024 IEEE.

关键词： aedes mosquito dengue-prone image processing yolo v4 tiny

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Synergizing Measurement Science and Artificial Intelligence in Smart Agriculture

Synergizing Measurement Science and Artificial Intelligence ...

引用

2023 IEEE International Conference on Big Data, BigData 2023

作者： Lamonaca, Francesco Carni, Domenico Luca University of Calabria Dept. of Computer Science Modelling Eletctronics and Systems Engineering Arcavacata di Rende Italy

ISBN: (纸本)9798350324457

This paper would provide a comprehensive review of the synergistic integration of measurement science and artificial intelligence (AI) in the realm of smart agriculture. As agriculture undergoes a transformative phase toward precision and data-driven practices, the paper explores the critical role of measurement science in providing accurate data, while AI processes and analyzes this data to facilitate intelligent decision-making in smart agricultural systems. © 2023 IEEE.

关键词： Artificial Intelligence Distributed Measurement System Measurement Smart Agriculture

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AirWave: Enhancing UAV Connectivity in Cellular Networks through an Integrated Simulation Framework

AirWave: Enhancing UAV Connectivity in Cellular Networks thr...

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2024 IEEE International Conference on Big Data and Machine Learning, ICBDML 2024

作者： Zor, Emirhan Taskiran, Yusuf Dael, Fares A. Shayea, Ibraheem Rzayeva, Leila Syzdykova, Zuleikha Istanbul Technical University Electronic and Communication Engineering Istanbul Turkey İzmir Bakirçay University Management Information Systems İzmir Turkey Astana IT University Dept. of Intelligent Systems and Cybersecurity Astana Kazakhstan Astana IT University Dept. of Computer Engineering Astana Kazakhstan

ISBN: (纸本)9798350374100

This study presents AirWave, an innovative modeling framework tailored to address the challenges associated with integrating Unmanned Aerial Vehicles (UAVs) into 5G and future cellular networks. With the rising prominence of UAVs across various industries, ensuring uninterrupted connectivity and efficient mobility management within cellular networks becomes paramount. AirWave offers a comprehensive simulation environment, amalgamating network and physics simulations using ns-3 for network simulation, Gazebo for physics simulation, and integrating PX4 autopilot for realistic UAV flight dynamics. This framework facilitates in-dept. investigations into UAV mobility and handover management, including a trajectory optimization technique based on reinforcement learning for cellular-connected drones. Extensive simulations demonstrate the versatility and effectiveness of AirWave, showcasing notable improvements in UAV range, connectivity, and management within cellular networks. These findings hold significant promise for advancing research and practical applications in UAV communications. © 2024 IEEE.

关键词： Reinforcement learning

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A Power Quality Event Classifier Based on Convolutional Neural Network

A Power Quality Event Classifier Based on Convolutional Neur...

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2023 IEEE International Conference on Big Data, BigData 2023

作者： Lamonaca, Francesco Carni, Domenico Luca University of Calabria Dept. of Computer Science Modelling Eletctronics and Systems Engineering Arcavacata di Rende Italy

ISBN: (纸本)9798350324457

This article introduces a novel and accurate automatic classifier for Power Signal (PS) alterations. The efficient detection and accurate classification represent crucial steps in developing an automatic power quality (PQ) measurement system, which has become essential in contemporary settings. The objective of this article is to enhance alteration classification accuracy. This is accomplished by combining the Hilbert-Huang transform (HHT) and convolutional neural network (CNN). The HHT is employed to extract PS features and is resilient to the non-stationarity introduced by alterations. Meanwhile, the CNN is adept.at extracting information from the bidimensional characteristics of PS features and is robust against noise. Numerical tests demonstrate promising results showing high classification accuracy also in the case of PSs affected by high level of noise. © 2023 IEEE.

关键词： Classifier CNN Convolutional Neural Network Distributed Measurement systems Hilbert-Huang transform Measurement Measurement System Power Quality Power Signal

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Signal Processing Techniques from Accelerometers on Railway Transport Based on the Wavelet Transform

Signal Processing Techniques from Accelerometers on Railway ...

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2024 Conference of Young Researchers in Electrical and Electronic engineering, ElCon 2024

作者： Boronakhin, Alexander M. Bolshakova, Alexandra V. Klionskiy, Dmitry M. Larionov, Daniil Yu. Shalymov, Roman V. Saint Petersburg Electrotechnical University 'LETI' Faculty of Information Measurement and Biotechnical Systems Dept. of Laser Measurement and Navigational Systems Saint Petersburg Russia Saint Petersburg Electrotechnical University 'LETI' Dept. of Laser Measurement and Navigational Systems Saint Petersburg Russia Saint Petersburg Electrotechnical University 'LETI' Dept. of Information Systems Dept. of Software Engineering and Computer Applications Saint Petersburg Russia

ISBN: (纸本)9798350360646

Railway transport safety is directly connected with the condition of railway tracks and also the condition of railway wheels' surface. One of the main reasons for abnormal situations on railways are various defects such as irregularities of a railway track. Thus, we need to estimate the length of short and impulse irregularities. It is also important to carry out joint analysis of vibration acceleration signals recorded by accelerometers in order to study types and sizes of railway track irregularities. © 2024 IEEE.

关键词： continuous wavelet transform discrete wavelet transform irregularity of railway track vibration acceleration signal vibration movement wavelet scalogram

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Feature Relevance in NAT Detection Using Explainable AI 28

Feature Relevance in NAT Detection Using Explainable AI

引用

28th IEEE Symposium on computers and Communications, ISCC 2023

作者： Nassar, Reem Elhajj, Imad H. Kayssi, Ayman Salam, Samer American University of Beirut Dept. of Electrical and Computer Engineering Beirut Lebanon Cisco Systems Beirut Lebanon

ISBN: (纸本)9798350300482

Network Address Translation (NAT) was developed to overcome the IPv4 address exhaustion problem. NAT allows multiple devices on a local network to share a single public IP address. However, NAT can result in communication concerns, security flaws, network administration issues, and difficulties locating network faults. This paper addresses the limitations of existing NAT detection techniques through adoption of an innovative machine learning-based approach. The NAT detection model achieves promising results by utilizing novel traffic features. The current techniques used in NAT detection face challenges in terms of explainability and transparency. To address this issue, our proposed method integrates explainable artificial intelligence (XAI) techniques to increase the transparency and interpretability of NAT detection models, thereby improving their efficiency and effectiveness. The results obtained from explain ability highlight the significance of incorporating new features in NAT detection. Furthermore, explainable results indicate that the presence of NAT is closely correlated with specific features. © 2023 IEEE.

关键词： Transparency

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Facial Shape-Based Eyeglass Recommendation Using Convolutional Neural Networks

Facial Shape-Based Eyeglass Recommendation Using Convolution...

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2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

作者： Rifat, Rakib Hossain Siddique, Sunzida Das, Laxmi Rani Haque, Mohd Ariful Brac University Dept. of Computer Science and Engineering Mohakhali Dhaka1212 Bangladesh Daffodil International University Dept. of Computer Science and Engineering Dhaka Bangladesh Noakhali Science and Technology University Dept. of Computer Science and Telecommunication Engineering Sonapur Bangladesh Clark Atlanta University Dept. of Cyber-Physical Systems AtlantaGA United States

ISBN: (纸本)9781665430654

Eyeglasses are not only used to protect our vision and prevent dust from getting into our eyes. Additionally, glass that fits properly can give a person an elegant appearance. However, people often find it difficult to choose eyeglasses that fit their face shape;to address this issue, we have proposed a novel architecture in this paper. In order to do this, we created a pipeline that can recommend eyeglasses based on the form of the eyes using multiple transfer learning architecture to predict the face shape from a given image. We utilized InceptionV4 [17], InceptionV3[18], Vit Small [12], DenseNet121 [10], ResNet50 [9], and VGG16 [16] to predict the facial shape from the image and achieve a test accuracy of 75%. We used 5500 photos with five different face shapes (Heart, Oblong, Oval, Round, Square) for this experiment, and two distinct datasets were gathered from Kaggle [2] and GitHub [1]. By simply uploading the photograph to our recommendation system, our proposed solution can assist users in selecting the appropriate eyewear. © 2023 IEEE.

关键词： CNN DenseNet121 Eye Glass InceptionV3 InceptionV4 ResNet50 Trasnfer Learning VGG16 Vit Small

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A Generalizable Machine Learning Model for NAT Detection

A Generalizable Machine Learning Model for NAT Detection

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2023 International Conference on Intelligent Computing, Communication, Networking and Services, ICCNS 2023

作者： Nassar, Reem Elhajj, Imad H. Kayssi, Ayman Salam, Samer American University of Beirut Dept. of Elecrtical and Computer Engineering Beirut Lebanon Cisco Systems Beirut Lebanon

ISBN: (纸本)9798350339291

Network Address Translation (NAT) aimed originally at resolving the issue of IPv4 address exhaustion. NAT allows multiple devices on a local network to share a single public IP address. This enables efficient utilization of the limited number of public IP addresses and allows devices on a local network to connect to the internet. However, NAT can lead to communication problems, security vulnerabilities, difficulties in network management, and challenges in identifying network issues. This paper proposes a novel approach for NAT detection using machine learning that overcomes the limitations of traditional NAT detection methods by building a generalizable model. The proposed method incorporates techniques to achieve generalization in the presence of obfuscation, a technique used by attackers to evade detection. The experimental results show the superiority of the proposed method over existing NAT detection techniques in terms of accuracy and generalization, even in the presence of obfuscation. A decline in the classification F1 score below 70% is observed when traffic data has multiple features obfuscated and when environment changes. To tackle this issue, transfer learning was applied to enhance the model's efficiency and effectiveness. Transfer learning resulted in more promising results in new network environments and in case of obfuscation. © 2023 IEEE.

关键词： Internet protocols

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A Novel Architecture of CXL Protocol Data Link Layer for Low Latency Memory Access

A Novel Architecture of CXL Protocol Data Link Layer for Low...

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2023 International Conference on Microelectronics, ICM 2023

作者： Mohamed, Basma H. Hany, Esmail El-Tahawy, Mahmoud Abdel-Salam, Mohamed El-Kharashi, M. Watheq Safar, Mona Ain Shams University Computer and Systems Engineering Dept. Cairo Egypt Siemens Eda Cairo Egypt

ISBN: (纸本)9798350380828

With the increase in memory-intensive applications, there is a need to provide low latency paths for memory access and coherent caching between host processors and storage devices. This paper proposes a novel architecture for the Data Link Layer of Compute Express Link (CXL) protocol, as defined in CXL Specification Revision 2.0. The architecture presented here contains the transmission and reception chains, which ensures the reliable conveyance of the packets between two CXL components using the CXL protocol. This paper explains how the proposed architecture ensures reliable data conveyance, responses and requests, through the addition of a 16-bit Cyclic Redundancy Check (CRC) to each 512-bit FLow control unIT (FLIT) in the transmitter side, and how the packets are processed in receiver side. The architecture is intended to have simple implementation in addition to having minimum datapath delays. The whole architecture is designed using HDL then verified using test-benches for different protocol scenarios to make sure that the functionality of the system is achieved. In addition, the whole design is synthesized using United Microelectronics Corporation (UMC) 130 nm [1] and Taiwan Semicomductors Manufactor Company (TSMC) 28 nm [2] technologies to get the maximum achieved frequency and calculate the corresponding power and area. The proposed hardware implementation manages to work up to 1 GHz using TSMC 28 nm technology and 438.59 MHz using UMC 130 nm technology. Its estimated dynamic and leakage power consumption by UMC 130 nm technology at 1 GHz are 95.3698 mW and 171.17 mW, respectively. In addition, its area cost extracted after synthesis is 242124.8 μ m2. © 2023 IEEE.

关键词： Microelectronics

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