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arXiv 2024年

作者： Jordan, Jardi Martinez Stiber, Michael Computing and Software Systems Division School of Science Technology Engineering and Mathematics University of Washington Bothell BothellWA98011 United States

Emergency Services Communication systems (ESCS) are evolving into Internet Protocol based communication networks, promising enhancements to their function, availability, and resilience. This increase in complexity and cyber-attack surface demands better understanding of these systems’ breakdown dynamics under extreme circumstances. Existing ESCS research largely overlooks simulation and the little work that exists focuses primarily on cybersecurity threats and neglects critical factors such as non-stationarity of call arrivals. This paper introduces a robust, adaptable graph-based simulation framework and essential mathematical models for ESCS simulation. The framework uses a representation of ESCSes where each vertex is a communicating finite-state machine that exchanges messages along edges and whose behavior is governed by a discrete event queuing model. Call arrival burstiness and its connection to emergency incidents is modeled through a cluster point process. Model applicability is demonstrated through simulations of the Seattle Police Department ESCS. Ongoing work is developing GPU implementation and exploring use in cybersecurity tabletop exercises. © 2024, CC BY.

关键词： Queueing theory

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Face matching system in multi-pose changing scene 6

Face matching system in multi-pose changing scene

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6th IEEE International Conference on Intelligent Computing and Signal Processing, ICSP 2021

作者： Liu, Qianqian Beijing University of Technology Beijing Engineering Research Center for IoT Software and Systems Beijing China

ISBN: (纸本)9780738143705

Due to the emergence of deep learning, face recognition has made remarkable achievements. But in the traditional video surveillance scene, because the monitoring object is not controlled and the face posture changes frequently, the actual face image may be a negative face image, which greatly reduces the accuracy of face recognition. And the traditional monitoring system does not have an automatic warning function, which wastes a lot of human resources. This paper focuses on the realization of a real-time and efficient face matching system in multi-pose changing scenes. The system mainly uses the MTCNN algorithm for face detection and alignment and uses a generative confrontation network to make face positive to eliminate the influence of posture change. The feature extraction network uses lightweight MobileFaceNet as the backbone network for feature extraction, and the feature comparison is carried out by cosine similarity. Experiments show that the multi-pose face matching system can greatly improve the speed of feature extraction, and has good accuracy, real-time, and robustness. © 2021 IEEE.

关键词： Face recognition

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Core-shell structured BN/SiO_(2)nanofiber membrane featuring with dual-effect thermal management and flame retardancy for extreme space thermal protection

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Science Bulletin 2025年第5期70卷 722-732页

作者： Duo Pan Ziyuan Han Junting Lei Yutao Niu Hu Liu Sunmi Shin Chuntai Liu Zhanhu Guo State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentNational Engineering Research Center for Advanced Polymer Processing TechnologyZhengzhou UniversityZhengzhou 450001China Key Laboratory of Multifunctional Nanomaterials and Smart Systems Advanced Materials DivisionSuzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhou 215123China Department of Mechanical Engineering College of Design and EngineeringNational University of SingaporeSingapore 117575Singapore Mechanical and Construction Engineering Faculty of Engineering and EnvironmentNorthumbria UniversityNewcastle Upon TyneNE18STUK

With the rapid progress of aerospace frontier engineering,the extreme space thermal environment has brought severe challenges to astronauts’space suits,putting forward higher requirements for thermal protection *** this basis,a unique core-shell structured hexagonal boron nitride(h-BN)/silicon dioxide(SiO_(2))nanofiber membrane(HS)was prepared using the coaxial electrospinning method,of which both the thermal insulation SiO_(2)nanofiber cortex and the passive radiation cooling(PRC)h-BN nanofiber core make it a promising dual-effect thermal management ***,when the amount of h-BN is 0.9 g,the resultant HS(HS0.9)exhibits astonishing low thermal conductivity of 0.026 W m−1 K−1 and high reflectivity and emissivity of exceeding 90%over an extremely wide *** expected dual-effect thermal management performance enables the HS to have an ideal cooling effect under both high sunlight intensity and strong light *** addition,HS also shows excellent flame retardant performance arising from the excellent high-temperature stability of h-BN and SiO_(2).What is more,the tensile strength of HS0.9 was also significantly increased from 0.42 to 7.2 MPa by encapsulating polyimide through vacuum ***,the research results of this work provide innovative highlights for high-temperature protection in daily life and even extreme space environments.

关键词： h-BN/SiO_(2)nanofiber membrane Core-shell structure Passive radiative cooling Thermal insulation Flame retardancy

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Feature and Performance Comparison of FaaS Platforms 14

Feature and Performance Comparison of FaaS Platforms

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14th IEEE International Conference on software engineering and Service Science, ICSESS 2023

作者： Ma, Penghui Shi, Peichang Yi, Guodong College of Computer Science National University of Defense Technology National Key Laboratory of Parallel and Distributed Processing Changsha410073 China College of Computer Science National University of Defense Technology Key Laboratory of Software Engineering for Complex Systems Changsha410073 China Xiangjiang Lab Changsha410073 China School of Advanced Interdisciplinary Studies Hunan University of Technology and Business Changsha410073 China

ISBN: (纸本)9798350336269

With serverless computing offering more efficient and cost-effective application deployment, the diversity of serverless platforms presents challenges to users, including platform lock-in and costly migration. Moreover, due to the black box nature of function computing, traditional performance benchmarking methods are not applicable, necessitating new studies. This article presents a detailed comparison of six major public cloud function computing platforms and introduces a benchmarking framework for function computing performance. This framework aims to help users make comprehensive comparisons and select the most suitable platform for their specific needs. © 2023 IEEE.

关键词： Benchmarking

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A Pedestrian Trajectory Prediction Network Based on Trajectory Conditional Visual Attention 6

A Pedestrian Trajectory Prediction Network Based on Trajecto...

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6th International Conference on Algorithms, Computing and Artificial Intelligence, ACAI 2023

作者： Tian, Xiaojie Lin, Ruoxi Yang, Shimeng Li, Kaiju Yin, Guangqiang Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen518110 China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu610051 China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610051 China Kashgar Municipal Committee of Xinjiang Kashi844000 China

ISBN: (纸本)9798400709203

Pedestrian trajectory prediction task can increase artificial intelligence's understanding of human behavior perception and intention, and is widely used in traffic management, service robots, automatic driving and other fields, which has great research value and significance. Although there is more and more research on pedestrian trajectory prediction tasks, pedestrian trajectory prediction is still a very challenging task due to the uncertainty of pedestrian will and the complexity of interaction in the complex real scene. Most of the research focus on the interaction between the target pedestrian and other pedestrians, which has great computational cost in the crowded pedestrian scene. We proposed CDCNet, by observing the historical track of pedestrians, and using the Conditional Dual Coordinated Attention to obtain the information that pedestrians pay attention to when moving forward, so that the network pays attention to the information around pedestrians instead of the content in the entire video, so that the network can also have a lower computing cost under the crowded pedestrian scene. Our experiments on five publicly available datasets show that CDCNet has good predictive efficiency and advanced performance. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Trajectories

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Cross-Modality Prompts: Few-Shot Multi-Label Recognition With Single-Label Training

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IEEE Transactions on Multimedia 2025年 27卷 3023-3033页

作者： Ding, Zixuan Zhou, Zihan Chen, Hui Hao, Tianxiang Xiong, Yizhe Zhao, Sicheng Zhang, Qiang Han, Jungong Xidian University State Key Laboratory of Electromechanical Integrated Manufacturing of High-Performance Electronic Equipments Xi'an710071 China Xidian University Center for Complex Systems School of Mechano-Electronic Engineering Xi'an710071 China Tsinghua University School of Software Beijing100190 China Tsinghua University Beijing National Research Center for Information Science and Technology Beijing100190 China Tsinghua University Department of Automation Beijing100190 China

Few-shot multi-label recognition (FS-MLR) presents a significant challenge due to the need to assign multiple labels to images with limited examples. Existing methods often struggle to balance the learning of novel classes and the retention of knowledge from base classes. To address this issue, we propose a novel Cross-Modality Prompts (CMP) approach. Unlike conventional methods that rely on additional semantic information to mitigate the impact of limited samples, our approach leverages multimodal prompts to adaptively tune the feature extraction network. A new FS-MLR benchmark is also proposed, which includes single-label training and multi-label testing, accompanied by benchmark datasets constructed from MS-COCO and NUS-WIDE. Extensive experiments on these datasets demonstrate the superior performance of our CMP approach, highlighting its effectiveness and adaptability. Our results show that CMP outperforms CoOp on the MS-COCO dataset with a maximal improvement of 19.47% and 23.94% in mAPharmonic for 5-way 1-shot and 5-way 5-shot settings, respectively. © 1999-2012 IEEE.

关键词： Zero-shot learning

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Research and development of an information system for speech recognition based on neural network algorithms metrics 4

Research and development of an information system for speech...

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4th IEEE International Conference on Smart Information systems and Technologies, SIST 2024

作者： Kanashev, Maksat Mukasheva, Assel Yedilkhan, Didar Rakhmetulaeva, Sabina Gnatyuk, Sergiy Nazym, Mirambayeva Almaty University of Power Engineering and Telecommunications Almaty Kazakhstan The School of Information Technology and Engineering Kazakh-British Technical University Almaty Kazakhstan The Department of Computer Engineering Astana IT University Astana Kazakhstan The Department of Information Systems International University of Information Technologies Almaty Kazakhstan The Faculty of Cybersecurity Computer and Software Engineering National Aviation University National Aviation University Kyiv Ukraine

ISBN: (纸本)9798350374865

This article examines the parameters of speech recognition in audio recordings containing a variety of phrases uttered by different people with different accents and intonations. The aim of the study is to evaluate the recognition speed, the accuracy of audio-to-text conversion and resource consumption when using SpeechRecognition and Levenshtein libraries. During the analysis, the above libraries were used to record and recognize audio files, as well as to calculate the distance between two lines and determine the recognition accuracy. The findings of this study can be useful for improving speech recognition systems and creating more adaptive and efficient solutions for audio data processing. The results of comparing the accuracy of speech recognition models are recorded in JSON format, after which, using the matplotlib library, they are visualized as graphs, comparing the speed and accuracy of recognition. Visualization of data in this way contributes to their improvement and more effective integration into educational systems. In conclusion, the authors emphasize the prospects for further development of speech recognition technologies in different fields. © 2024 IEEE.

关键词： Audio recordings

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A Lightweight Deep Learning-Based Model for Tomato Leaf Disease Classification

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Computers, Materials & Continua 2023年第12期77卷 3969-3992页

作者： Naeem Ullah Javed Ali Khan Sultan Almakdi Mohammed S.Alshehri Mimonah Al Qathrady Eman Abdullah Aldakheel Doaa Sami Khafaga Department of Software Engineering University of Engineering and TechnologyTaxila4400Pakistan Department of Computer Science Faculty of PhysicsEngineeringand Computer ScienceUniversity of HertfordshireHatfieldAL109ABUK Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Departments of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Tomato leaf diseases significantly impact crop production,necessitating early detection for sustainable *** Learning(DL)has recently shown excellent results in identifying and classifying tomato leaf ***,current DL methods often require substantial computational resources,hindering their application on resource-constrained *** propose the Deep Tomato Detection Network(DTomatoDNet),a lightweight DL-based framework comprising 19 learnable layers for efficient tomato leaf disease classification to overcome *** Convn kernels used in the proposed(DTomatoDNet)framework is 1×1,which reduces the number of parameters and helps in more detailed and descriptive feature extraction for *** proposed DTomatoDNet model is trained from scratch to determine the classification success rate.10,000 tomato leaf images(1000 images per class)from the publicly accessible dataset,covering one healthy category and nine disease categories,are utilized in training the proposed DTomatoDNet *** specifically,we classified tomato leaf images into Target Spot(TS),Early Blight(EB),Late Blight(LB),Bacterial Spot(BS),Leaf Mold(LM),Tomato Yellow Leaf Curl Virus(YLCV),Septoria Leaf Spot(SLS),Spider Mites(SM),Tomato Mosaic Virus(MV),and Tomato Healthy(H).The proposed DTomatoDNet approach obtains a classification accuracy of 99.34%,demonstrating excellent accuracy in differentiating between tomato *** model could be used on mobile platforms because it is lightweight and designed with fewer *** farmers can utilize the proposed DTomatoDNet methodology to detect disease more quickly and easily once it has been integrated into mobile platforms by developing a mobile application.

关键词： CNN deep learning DTomatoDNet tomato leaf disease classification smart agriculture

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Tightly-Coupled Lidar-Based Lifelong Mapping using Wheels and a MEMS Gyroscope for Mobile Robots in Dynamic Environment 24

Tightly-Coupled Lidar-Based Lifelong Mapping using Wheels an...

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3rd International Symposium on Robotics, Artificial Intelligence and Information engineering, RAIIE 2024

作者： Hu, Lizhi Chen, Huilin Li, Xiang Lu, Wei Zhao, Yifan Hu, Songyu Navigation and Localization Algorithm Department Zhejiang HuaRay Technology Co. Lt. Hangzhou China Software Research and Development Center Zhejiang HuaRay Technology Co. Lt. Hangzhou China State Key Laboratory of Fluid Power and Mechatronic Systems College of Mechanical Engineering Zhejiang University Hangzhou China

ISBN: (纸本)9798400718311

Localization and mapping technology of mobile robots is important in production and warehousing. The changing warehousing environment always result in poor accuracy and robustness of the mobile robot's localization. It is necessary to detect the degree of environmental changes and update the map. This paper proposes a novel lifelong mapping method fusing measurements from the lidar, wheels and a MEMS gyroscope, which can create a reliable map corresponding to the current working environment. Firstly, we use the wheels and gyroscopes measures for pre-integration to provide relative motion constraints, while integrating wheels and gyroscopes to provide initial pose for lidar matching. We also establish lidar odometry by submaps to provide another type of relative motion constraints. The absolute constraints are obtained by matching the lidar measurements with prior map. These three types of constraints are optimized in a factor graph. At the same time, during the process of updating the map, detect newly added artificial markers such as reflective columns or strips, and update them into the map timely. Then, in order to delete redundant lidar data keyframes for building map, we propose a determine redundancy method based on submaps. Finally, we propose a method for calculating the degree of map changes, which can update the map timely. Experimental results prove that our method can establish higher quality maps, optimize lidar external parameters timely during the mapping process, delete redundant lidar keyframes more efficiently, and update the current environmental map more accurately and timely. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Gyroscopes

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Recommender System for Configuration Management Process of Entrepreneurial software Designing Firms

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Computers, Materials & Continua 2021年第5期67卷 2373-2391页

作者： Muhammad Wajeeh Uz Zaman Yaser Hafeez Shariq Hussain Haris Anwaar Shunkun Yang Sadia Ali Aaqif Afzaal Abbasi Oh-Young Song University Institute of Information Technology Pir Mehr Ali Shah Arid Agriculture UniversityRawalpindi46000Pakistan Department of Software Engineering Foundation University IslamabadIslamabad44000Pakistan Department of Electrical Electronics and Telecommunication EngineeringUniversity of Engineering and TechnologyLahore54000Pakistan School of Reliability and Systems Engineering Beihang UniversityBeijing100191China Department of Software Sejong UniversitySeoul05006South Korea

The rapid growth in software demand incentivizes software development organizations to develop exclusive software for their customers *** problem is addressed by the software development industry by software product line(SPL)practices that employ feature ***,optimal feature selection based on user requirements is a challenging ***,there is a requirement to resolve the challenges of software development,to increase satisfaction and maintain high product quality,for massive customer needs within limited *** this work,we propose a recommender system for the development team and clients to increase productivity and quality by utilizing historical information and prior experiences of similar developers and *** proposed system recommends features with their estimated cost concerning new software requirements,from all over the globe according to similar developers’and clients’needs and *** system guides and facilitates the development team by suggesting a list of features,code snippets,libraries,cheat sheets of programming languages,and coding references from a cloud-based knowledge management ***,a list of features is suggested to the client according to their needs and *** experimental results revealed that the proposed recommender system is feasible and effective,providing better recommendations to developers and *** provides proper and reasonably well-estimated costs to perform development tasks effectively as well as increase the client’s satisfaction *** results indicate that there is an increase in productivity,performance,and quality of products and a reduction in effort,complexity,and system ***,our proposed system facilitates developers and clients during development by providing better recommendations in terms of solutions and anticipated ***,the increase in productivity and satisfaction level maximizes the benefits and usability of SPL in the

关键词： Feature selection recommender system software reuse configuration management

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