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Analysis on D2D Heterogeneous Networks with State-Dependent Priority Traffic

computers, Materials & Continua 2023年第2期74卷 2981-2998页

作者： Guangjun Liang Jianfang Xin Linging Xia Xueli Ni Yi Cao Department of Computer Information and Cyber Security Jiangsu Police InstituteNanjingChina National and Local Joint Engineering Laboratory of Radio Frequency Integration and Microassembly Technology Nanjing University of Posts and TelecommunicationsNanjingChina School of Intelligent Engineering Nanjing Institute of Railway TechnologyNanjingChina Jiangsu Province Electronic Data Forensics and Analysis Engineering Research Center NanjingChina Department of Electrical and Computer Engineering University of WindsorWindsorONN9B 3P4Canada

In this work,we consider the performance analysis of state dependent priority traffic and scheduling in device to device(D2D)heterogeneous *** are two priority transmission types of data in wireless communication,such as video or telephone,which always meet the requirements of high priority(HP)data transmission *** there is a large amount of low priority(LP)data,there will be a large amount of LP data that cannot be *** situation will cause excessive delay of LP data and packet dropping *** order to solve this problem,the data transmission process of high priority queue and low priority queue is *** the priority jump strategy to the priority queuing model,the queuing process with two priority data is modeled as a two-dimensionalMarkov chain.A state dependent priority jump queuing strategy is proposed,which can improve the discarding performance of low priority *** quasi birth and death process method(QBD)and fixed point iterationmethod are used to solve the causality,and the steady-state probability distribution is further ***,performance parameters such as average queue length,average throughput,average delay and packet dropping probability for both high and low priority data can be *** simulation results verify the correctness of the theoretical ***,the proposed priority jump queuing strategy can significantly improve the drop performance of low-priority data.

关键词： Stochastic geometry queuing theory D2D heterogeneous networks quasi-birth and death process

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Passive On-Chip Nonlinear Optical Isolators with Built-in Laser Stabilization

Passive On-Chip Nonlinear Optical Isolators with Built-in La...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： White, Alexander D. Ahn, Geun Ho Van Gasse, Kasper Luhtaru, Richard Guo, Joel Morin, Theodore J. Lin, Chang Bowers, John E. Vučković, Jelena E. L. Ginzton Laboratory Stanford University StanfordCA United States Department of Electrical and Computer Engineering University of California Santa BarbaraCA United States

We demonstrate fully passive optical isolators in silicon nitride nanophotonics using the intrinsic Kerr nonlinearity. These devices serve to both stabilize and isolate on-chip lasers, reducing the linewidth of DFB la... 详细信息

ISBN: (纸本)9781957171395

关键词： Silicon nitride

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An Efficient Text Recognition System from Complex Color Image for Helping the Visually Impaired Persons

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computer systems Science & engineering 2023年第7期46卷 701-717页

作者： Ahmed Ben Atitallah Mohamed Amin Ben Atitallah Yahia Said Mohammed Albekairi Anis Boudabous Turki MAlanazi Khaled Kaaniche Mohamed Atri Department of Electrical Engineering College of EngineeringJouf UniversitySakakaSaudi Arabia Laboratory of Informatics Gaspard-MongeA3SIESIEE ParisCNRSGustave Eiffel UniversityFrance LETI ENISUniversity of SfaxSfaxTunisia Remote Sensing Unit College of EngineeringNorthern Border UniversityArarSaudi Arabia Laboratory of Electronics and Microelectronics(LR99ES30) University of MonastirTunisia Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySakakaSaudi Arabia College of Computer Sciences King Khalid UniversityAbhaSaudi Arabia

The challenge faced by the visually impaired persons in their day-today lives is to interpret text from *** this context,to help these people,the objective of this work is to develop an efficient text recognition system that allows the isolation,the extraction,and the recognition of text in the case of documents having a textured background,a degraded aspect of colors,and of poor quality,and to synthesize it into *** system basically consists of three algorithms:a text localization and detection algorithm based on mathematical morphology method(MMM);a text extraction algorithm based on the gamma correction method(GCM);and an optical character recognition(OCR)algorithm for text recognition.A detailed complexity study of the different blocks of this text recognition system has been *** this study,an acceleration of the GCM algorithm(AGCM)is *** AGCM algorithm has reduced the complexity in the text recognition system by 70%and kept the same quality of text recognition as that of the original *** assist visually impaired persons,a graphical interface of the entire text recognition chain has been developed,allowing the capture of images from a camera,rapid and intuitive visualization of the recognized text from this image,and text-to-speech *** text recognition system provides an improvement of 6.8%for the recognition rate and 7.6%for the F-measure relative to GCM and AGCM algorithms.

关键词： Text recognition system GCM AGCM OCR color images graphical interface

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Disentangling Spatio-Temporal Knowledge for Weakly Supervised Object Detection and Segmentation in Surgical Video

Disentangling Spatio-Temporal Knowledge for Weakly Supervise...

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IEEE Workshop on Applications of computer Vision (WACV)

作者： Guiqiu Liao Matjaz Jogan Sai Koushik Eric Eaton Daniel A. Hashimoto Department of Surgery PCASO Laboratory University of Pennsylvania Department of Electrical and Systems Engineering University of Pennsylvania Department of Computer and Information Science University of Pennsylvania

ISBN: (数字)9798331510831

ISBN: (纸本)9798331510848

Weakly supervised video object segmentation (WSVOS) enables the identification of segmentation maps without requiring extensive annotations of object masks, relying instead on coarse video labels indicating object presence. WSVOS in surgical videos is, however, more challenging due to the complex interaction of multiple transient objects, such as surgical tools moving in and out of the surgical field. In this scenario, state-of-the-art WSVOS methods struggle to learn accurate segmentation maps. We address this problem by introducing ViDeo Spatio-Temporal disentanglement Networks (VDST-Net), a framework to disentangle complex spatio-temporal object interactions using semi-decoupled knowledge distillation to predict high-quality class activation maps (CAMs). A teacher network is designed to help a temporal-reasoning student network resolve activation conflicts, as the student leverages temporal dependencies when specifics about object location and timing in the video are not provided. We demonstrate the efficacy of our framework on a challenging surgical video dataset where objects are, on average, present in less than 60% of annotated frames, and compare our method to state-of-the-art methods on surgical data and on a public dataset commonly used to benchmark WSVOS. Our method outperforms state-of-the-art techniques and generates accurate segmentation masks under video-level weak supervision. Our code is available at: https://***/PCASOlab/VDST-net.

关键词： Accuracy Weak supervision Surgery Object segmentation Object detection Streaming media Real-time systems Timing Object recognition Transient analysis

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The Efficient Cluster Head Selection for NarrowBand Internet of Things

The Efficient Cluster Head Selection for NarrowBand Internet...

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

作者： Huang, Shih-Yun Lee, Shou-Yu Wu, Tin-Yu Chang, Yao-Chung Chao, Han-Chieh Tunghai University Department of Computer Science Taichung Taiwan National Pingtung University of Science and Technology Department of Management Information Systems Taiwan National Taitung University Department of Computer Science and Information Engineering Taitung Taiwan National Dong Hwa University Department of Electrical Engineering Hualien Taiwan

ISBN: (纸本)9798350324174

The future of 5G will focus on massive machine-type communication (mMTC), and many applications will be based on this application and gradually mature. These applications include smart cities, e-health, and the Internet of Vehicles (IoV). In addition, the Narrowband Internet of things (NB-IoT) is a critical technology in mMTC. NB-IoT can bring many benefits, such as efficient bandwidth use and long-distance transmission. However, although NB-IoT has many advantages, issues such as throughput, energy consumption, and security still need to be solved. In order to effectively solve these problems, the choice of cluster heads is very important. Considering that the energy consumption of the CH will be more severe than that of other devices, which will also shorten the network;therefore, we will focus on the dynamic cluster head selection. To solve this problem, we introduced the concept of the pseudo-rigid body into this paper and proposed a method similar pseudo-rigid body to determine the CHs;at the same time, we also defined the maximum range of each cluster. The experimental results show that the proposed method can dynamically select the CH and increase the network lifetime. © 2023 IEEE.

关键词： Internet of things

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Detecting Pain During Cognitive Tasks via Visibility Graphs of Cortical Signals

Detecting Pain During Cognitive Tasks via Visibility Graphs ...

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IEEE International Symposium on Biomedical Imaging

作者： Ashwini Subramanian Laleh Najafizadeh Department of Electrical and Computer Engineering Integrated System and NeuroImaging Laboratory Rutgers University

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Detecting pain is critical for developing adaptive systems in clinical and assistive settings, allowing for timely interventions. This work presents an approach to detect the presence of physical pain during the performance of cognitive tasks from cortical signals. Cortical signals from the motor and prefrontal cortices are acquired using functional near in-frared spectroscopy (fNIRS) during two cognitive tasks, per-formed in the absence and presence of physical pain. Visibil-ity graphs (VGs) of these signals are constructed, and graph metrics of averaged clustering coefficient $(C)$ and edge den-sity $(D)$ are extracted. Statistical analysis reveals differences in these metrics for graphs corresponding to tasks performed under no-pain (NP) versus with-pain (WP) conditions, partic-ularly for signals obtained from the motor cortex. The graph metrics were then used as features to a support vector machine (SVM), achieving an accuracy exceeding 80% in distinguishing between tasks performed with and without pain. Our findings suggest that metrics from VGs of cortical sig-nals may serve as potential biomarkers for pain during cog-nitive tasks. This approach could be especially beneficial for non-verbal patients using assistive brain-computer interfaces.

关键词： Measurement Support vector machines Deep learning Pain Statistical analysis Image edge detection Motors Feature extraction Complexity theory Functional near-infrared spectroscopy

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Transforming Electroluminescence Images to Current-Voltage (IV) Curves Using Deep Learning 52

Transforming Electroluminescence Images to Current-Voltage (...

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52nd IEEE Photovoltaic Specialist Conference, PVSC 2024

作者： Byford, Brandon K. Braid, Jennifer L. Boucheron, Laura E. King, Bruce Klipsch School of Electrical and Computer Engineering New Mexico State University Las CrucesNM88003 United States Photovoltaic Systems Evaluation Laboratory Sandia National Laboratories AlbuquerqueNM87123 United States

ISBN: (纸本)9781665464260

System health monitoring is an essential task in the operation and maintenance of any photovoltaic (PV) system. Typically, electroluminescence (EL), thermal imaging, and current-voltage (IV) curve analyses are used to analyze PV modules with each providing unique insights into system health. While it is relatively easy to acquire an EL or thermal image of a panel in-situ, acquisition of IV curves requires electrical disconnection of the panel from the array and either removal to a solar simulator or characterization and correction for the incident solar spectrum and intensity. In this work we show that, with the use of a transfer-learned Swin transformer model, we can predict accurate IV curves from EL images. Extracting single diode equation parameters from the predicted IV curves yielded an error less than 1% ± 1% for the maximum power point (MPP), short-circuit current Isc, open-circuit voltage Voc and photocurrent I. The series resistance Rs and number of series cells nNsVth denoted as N were predicted with errors of 5% ±7% and 3% ±2%, respectively. Prediction of the shunt resistance Rsh and dark current Io yielded larger errors, likely due to sensitivity to small changes in the IV curve. © 2024 IEEE.

关键词： Thermography (imaging)

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A Bi-Level Optimization Approach to Joint Trajectory Optimization for Redundant Manipulators

arXiv

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arXiv 2024年

作者： Fried, Jonathan Paternain, Santiago The Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute United States

In this work, we present an approach to minimizing the time necessary for the end-effector of a redundant robot manipulator to traverse a Cartesian path by optimizing the trajectory of its joints. Each joint has limits in the ranges of position, velocity and acceleration, the latter making jerks in joint space undesirable. The proposed approach takes this nonlinear optimization problem whose variables are path speed and joint trajectory and reformulates it into a bi-level problem. The lower-level formulation is a convex subproblem that considers a fixed joint trajectory and maximizes path speed while considering all joint velocity and acceleration constraints. Under particular conditions, this subproblem has a closed-form solution. Then, we solve a higher-level subproblem by leveraging the directional derivative of the lower-level value with respect to the joint trajectory parameters. In particular, we use this direction to implement a Primal-Dual method that considers the path accuracy and joint position constraints. We show the efficacy of our proposed approach with simulations and experimental results. Copyright © 2024, The Authors. All rights reserved.

关键词： Trajectories

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Chatbot and its Impact on the Retail Industry 3

Chatbot and its Impact on the Retail Industry

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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Tatikonda, Reshmi Kempanna, M. Thatikonda, Ramya Bhuvanesh, A. Thota, Ragupathi Keerthanadevi, R. Department of Computer Information Systems University of the Central Missouri Warrensburg United States Department of AI and ML Bangalore Institute of Technology Bengaluru India Department of Information Technology University of the Cumberlands Williamsburg United States Department of Electrical and Electronics Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli India Department of Information Technology Jawaharlal Technological University Hyderbad India Department of Computer Science and Engineering PSN College of Engineering and Technology Tirunelveli India

ISBN: (纸本)9798331527549

This study explores the transformative potential of chatbots in the retail industry, highlighting their role in enhancing customer engagement, optimizing business processes, and revolutionizing the nature of retail interactions. Through a comprehensive review of existing literature and case studies, the paper delves into the cognitive processes underlying human-chatbot interactions and examines their impact on customer experience, satisfaction, and loyalty. Chatbots serve a wide array of operational functions, including inventory management, automated order processing, data-driven analytics, and employee training. These functionalities streamline workflows, improve efficiency, and maximize resource utilization. The paper further explores the innovative applications of chatbots, including AI-driven personalization, conversational commerce, and seamless integration with emerging technologies. By analyzing both the current applications and challenges of chatbot technology in retail, the study uncovers the exciting opportunities they present for shaping the future of retail by fostering more personalized, efficient, and interactive customer experiences. © 2025 IEEE.

关键词： Inventory control

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Fast and Accurate Interrogation of Vernier Effect-based Optical Fiber Sensors Enabled by Machine Learning

Fast and Accurate Interrogation of Vernier Effect-based Opti...

引用

CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Zhu, Chen Huang, Jie Research Center for Optical Fiber Sensing Zhejiang Laboratory Hangzhou311100 China Department of Electrical and Computer Engineering Missouri University of Science and Technology RollaMO65409 United States

The possibility of employing a light source with a small wavelength bandwidth (35 nm) and a coarsely resolved spectrometer (~166 pm) for the interrogation of a Vernier effect-based high-sensitivity optical fiber senso... 详细信息

关键词： Spectrometers

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