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Machine Learning and Autonomous Systems (ICMLAS), International Conference on

作者： Tanvi Khonde Sneha Patle Shreya Talvekar Jahnavi Hajbe Department of Computer Science and Design Faculty of Engineering and Technology Wardha Maharashtra

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505752

A virtual chatbot assistant is an interactive application designed to simulate human-like communication and respond to user inquiries promptly. It focuses on building an interesting user interface and putting simple conversational logic into practice; this article presents the development of a chatbot using HTML, CSS, and JavaScript. Developers can make these fundamental web technologies useful in the creation of accessible and user-friendly chatbot systems for any kind of application. The literature indicates that chatbot technology is under development, which includes the merging of AI and natural language processing to enhance the capabilities of conversations. This handbook is an invaluable tool in making useful chatbots by linking the needs of the users with contemporary online technology.

关键词： Virtual assistants Scalability Buildings Prototypes Speech recognition User interfaces Chatbots Real-time systems User experience Artificial intelligence

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Enhancing Efficiency in Public Transport: Remote Based Surveillance of Sensor for Animals Near Railway Track

Enhancing Efficiency in Public Transport: Remote Based Surve...

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International Conference on Trends in Electronics and Informatics (ICEI)

作者： Jaiganesh M Dhivya. P Shalini R Sujan Prabu KB Vignesh U Raghul KB Department of Computer Science and Design Karpagam College of Engineering Coimbatore India

ISBN: (数字)9798331544607

ISBN: (纸本)9798331544614

In order to prevent accidents, security precautions are becoming increasingly important in railway networks. The presence of impediments on the tracks is one factor that might cause catastrophic accidents. An ultrasonic (US) sensor and a vision system would create a multi-sensory obstruction that would alert the surveillance system to the presence of impediments, thereby preventing accidents. When a trustworthy and secure setting is required, the use of a multi-sensory system is employed. After the data is collected from the barriers and the vision system, it is analyzed. This method may be used to determine whether there are any impediments on the rails and to gather data about objects in motion using the vision system. The DC motor is started using the relay driver circuit when the device receives power. The train can detect the track break with the help of two infrared sensors that are mounted ahead of it. A signal proportional to the rail's position will be output by each sensor. Both sensors provide a consistent output if the track location is normal. A flaw exists on the side of the sensor if it fails to meet the output condition. As a warning, the sensor will sound an alert and relay the data to an Android application on a smartphone over an IoT-based GSM connection. When an ultrasonic sensor detects an obstruction on the track, the Arduino project sends a signal to a nearby station over the Internet of Things (IoT) with the help of a GSM modem. Using a GSM modem, the position of this rail will be automatically sent to every station.

关键词： GSM Rails Machine vision Surveillance Modems Rail transportation Internet of Things Relays Accidents Global Positioning System

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Visual-Language Collaborative Representation Network for Broad-Domain Few-Shot Image Classification 24

Visual-Language Collaborative Representation Network for Bro...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Guo, Qianyu Ren, Jieji Wang, Haofen Wu, Tianxing Ge, Weifeng Zhang, Wenqiang Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University Shanghai China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China College of Design and Innovation Tongji University Shanghai China School of Computer Science and Engineering Southeast University Nanjing China School of Computer Science Fudan University Shanghai China Engineering Research Center of AI & Robotics Ministry of Education Academy for Engineering & Technology Fudan University Shanghai China

ISBN: (纸本)9798400706868

Visual-language models based on CLIP have shown remarkable abilities in general few-shot image classification. However, their performance drops in specialized fields such as healthcare or agriculture, because CLIP's pre-training does not cover all category data. Existing methods excessively depend on the multi-modal information representation and alignment capabilities acquired from CLIP pre-training, which hinders accurate generalization to unfamiliar domains. To address this issue, this paper introduces a novel visual-language collaborative representation network (MCRNet), aiming at acquiring a generalized capability for collaborative fusion and representation of multi-modal information. Specifically, MCRNet learns to generate relational matrices from an information fusion perspective to acquire aligned multi-modal features. This relationship generation strategy is category-agnostic, so it can be generalized to new domains. A class-adaptive fine-tuning inference technique is also introduced to help MCRNet efficiently learn alignment knowledge for new categories using limited data. Additionally, the paper establishes a new broad-domain few-shot image classification benchmark containing seven evaluation datasets from five domains. Comparative experiments demonstrate that MCRNet outperforms current state-of-the-art models, achieving an average improvement of 13.06% and 13.73% in the 1-shot and 5-shot settings, highlighting the superior performance and applicability of MCRNet across various domains. © 2024 ACM.

关键词： Visual languages

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LLM-Project: Automated engineering Task Planning via Generative AI and WBS Integration 14

LLM-Project: Automated Engineering Task Planning via Generat...

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14th IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems, CYBER 2024

作者： Zhen, Yue Bi, Sheng Tang, Shuo Lu, Xing-Tong Pan, Wei-Qin Shi, Hai-Peng Chen, Zi-Rui Fang, Yi-Shu Wang, Xin-Meng South China University of Technology School of Computer Science and Engineering Guang Zhou510006 China University of Washington Human Centered Design and Engineering Seattle98195 United States Northeastern University Khoury College of Computer Sciences Boston02115 United States

ISBN: (纸本)9798331506056

We propose and implement a task planning system that integrates a series of validated robotic instructions, deep learning models, and demonstration cases, into a larger structure using the Work Breakdown Structure (WBS) which is commonly used in engineering project management. By organizing these small-scale solutions in a sequence based on temporal and resource dependencies, we use simulations and evaluation functions to select the optimal structure as the Standard Operating Procedure (SOP). These SOPs are then used to train a generative AI, enabling it to mimic human experts in generating high-level structures according to real-world needs and perform minor parameter generalizations to address issues involving temporal dependencies, spatial relationships, and resource allocation. The generated high-level structures are gradually transformed into low-level operations to execute actual tasks. The system records the execution results for automatic or manual analysis, and the feedback is used to continuously improve the generative AI's output. Our work lays the foundation for further research on the innovative application of combining generative AI with WBS data in robotic task planning. https://***/NOMIzy/LLM-Project. © 2024 IEEE.

关键词： Resource allocation

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Adaptive Group Personalization for Federated Mutual Transfer Learning 41

Adaptive Group Personalization for Federated Mutual Transfer...

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41st International Conference on Machine Learning, ICML 2024

作者： Xu, Haoqing Shen, Dian Wang, Meng Wang, Beilun School of Computer Science and Engineering Southeast University Nanjing210096 China Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education China College of Design and Innovation Tongji University Shanghai China

Mutual transfer learning aims to improve prediction with knowledge from related domains. Recently, federated learning is applied in this field to address the communication and privacy concerns. However, previous clustered federated learning (CFL) solutions lack theoretical guarantee of learnability recovery and require time-consuming hyper-parameter tuning, while centralized mutual transfer learning methods lack adaptability to concept drifts. In this paper, we propose the Adaptive Group Personalization method (AdaGrP) to overcome these challenges. We adaptively decide the recovery threshold with a nonparametric method, adaptive threshold correction, for tuning-free solution with relaxed condition. Theoretical results guarantee the perfect learnability recovery with the corrected threshold. Empirical results show AdaGrP achieves 16.9% average improvement in learnability structure recovery compared with state-of-the-art CFL baselines. Copyright 2024 by the author(s)

关键词： Federated learning

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An Electromyography Experiment of the Impact of Food Color and Temperature on Psychological Dynamics in Anorexia Nervosa

An Electromyography Experiment of the Impact of Food Color a...

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2023 International Symposium on World Ecological design, ISWED 2023

作者： Lou, Jiacheng Xu, Ziyu Yao, Yousheng He, Caihong Zheng, Junpeng Ying, Fangtian School of Industrial Design Hubei University of Technology China Faculty of Humanities and Arts Macau University of Science and Technology China Hexiangning College of Art and Design Zhongkai University of Agriculture and Engineering China Operations Management Center Guangzhou Wanqu Cooperative Institute of Design China College of Computer Science and Technology Zhejiang University China

ISBN: (纸本)9781643685069

Our study endeavors to explore the influence of food color and temperature on the psychological well-being of individuals with anorexia nervosa. Employing electromyography stimulation experiments and concurrently monitoring psychological and physiological indicators, we seek to elucidate the relationships between multi-sensory experiences and the mental health of anorexia nervosa patients. The results reveal that variations in food color and temperature significantly impact emotions, appetite, and the autonomic nervous system of individuals with anorexia nervosa, presenting novel perspectives for enhancing their psychological health. © 2024 The Authors.

关键词： Diseases

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An inverse design method for supercritical airfoil based on conditional generative models

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Chinese Journal of Aeronautics 2022年第3期35卷 62-74页

作者： Jing WANG Runze LI Cheng HE Haixin CHEN Ran CHENG Chen ZHAI Miao ZHANG Shanghai Aircraft Design and Research Institute Shanghai 200436China School of Aerospace Engineering Tsinghua UniversityBeijing 100084China Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China

Inverse design has long been an efficient and powerful design tool in the aircraft *** this paper,a novel inverse design method for supercritical airfoils is proposed based on generative models in deep learning.A Conditional Variational Auto Encoder(CVAE)and an integrated generative network CVAE-GAN that combines the CVAE with the Wasserstein Generative Adversarial Networks(WGAN),are conducted as generative *** are used to generate target wall Mach distributions for the inverse design that matches specified features,such as locations of suction peak,shock and aft *** and quantitative results show that both adopted generative models can generate diverse and realistic wall Mach number distributions satisfying the given *** CVAE-GAN model outperforms the CVAE model and achieves better reconstruction accuracies for all the samples in the ***,a deep neural network for nonlinear mapping is adopted to obtain the airfoil shape corresponding to the target wall Mach number *** performances of the designed deep neural network are fully demonstrated and a smoothness measurement is proposed to quantify small oscillations in the airfoil surface,proving the authenticity and accuracy of the generated airfoil shapes.

关键词： Conditional Variational AutoEncoder(CVAE) Deep learning Generative Adversarial Networks(GAN) Generative models Inverse design Supercritical airfoil

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Afra: An Eclipse-Based Tool with Extensible Architecture for Modeling and Model Checking of Rebeca Family Models 1

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10th IPM International Conference on Fundamentals of Software engineering, FSEN 2023

作者： Khamespanah, Ehsan Sirjani, Marjan Khosravi, Ramtin School of Electrical and Computer Engineering University of Tehran Tehran Iran School of Computer Science Reykjavik University Reykjavik Iceland School of Innovation Design and Engineering Mälardalen University Västerås Sweden

ISBN: (数字)9783031424410

ISBN: (纸本)9783031424403

Afra is an Eclipse-based tool for the modeling and model checking of Rebeca family models. Together with the standard enriched editor, easy to trace counter-example viewer, modular temporal property definition, exporting a model and its transition system to some other formats facilities are features of Afra. Rebeca family provides actor-based modeling languages which are designed to bridge the gap between formal methods and software engineering. Faithfulness to the system being modeled, and the usability of Rebeca family languages help in ease of modeling and analysis of the model, together with the synthesis of the system based on the model. In this paper, architectural decisions and design strategies we made in the development of Afra are presented. This makes Afra an extensible and reusable application for the modeling and analysis of Rebeca family models. Here, we show how different compilers can be developed for the family of languages which are the same in general language constructs but have some minor differences. Then we show how the model checking engine for these different languages is designed. Despite the fact that Afra has a layered object-oriented design and is developed in Java technology, we use C++ codes for developing its model checking for the performance purposes. This decision made the design of the application even harder. © 2023, IFIP International Federation for Information Processing.

关键词： Model checking

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A Multi-Task Learning Framework for Joint Sub-Nyquist Wideband Spectrum Sensing and Modulation Recognition

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China Communications 2025年第1期22卷 128-138页

作者： Dong Xin Stefanos Bakirtzis Zhang Jiliang Zhang Jie Department of Electronic and Electrical Engineering University of SheffieldSheffield S102TNUnited Kingdom Department of Computer Science and Technology University of CambridgeCambridge CB21TNUnited Kingdom College of Information Science and Engineering Northeastern UniversityShenyang 110819China Ranplan Wireless Network Design Ltd. Cambridge CB233UYUnited Kingdom

The utilization of millimeter-wave frequencies and cognitive radio(CR)are promising ways to increase the spectral efficiency of wireless communication ***,conventional CR spectrum sensing techniques entail sampling the received signal at a Nyquist rate,and they are not viable for wideband signals due to their high *** paper expounds on how sub-Nyquist sampling in conjunction with deep learning can be leveraged to remove this *** this end,we propose a multi-task learning(MTL)framework using convolutional neural networks for the joint inference of the underlying narrowband signal number,their modulation scheme,and their location in a wideband *** demonstrate the effectiveness of the proposed framework for real-world millimeter-wave wideband signals collected by physical devices,exhibiting a 91.7% accuracy in the joint inference task when considering up to two narrowband signals over a wideband ***,the proposed data-driven approach enables on-the-fly wideband spectrum sensing,combining accuracy,and computational efficiency,which are indispensable for CR and opportunistic networking.

关键词： automated modulation classification cognitive radio convolutional neural networks deep learning spectrum sensing sub-Nyquist sampling

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The Leaky Radiation of Gap in Aircraft and Its Influence on Interference-Path-Loss 11

The Leaky Radiation of Gap in Aircraft and Its Influence on ...

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11th IEEE Asia-Pacific Conference on Antennas and Propagation, APCAP 2023 - Proceedings

作者： Hu, Yueyun Liang, Xiaoliang Chen, Jie Xue, Chunhua Comac Shanghai Aircraft Design & Res Inst Shanghai201210 China Guangxi University of Science & Technology School of Computer Science & Communication Engineering Guangxi545006 China

ISBN: (纸本)9798350326277

As the high speed growth of the internet and communication industry, the Portable Electronic Device (PED) such as mobile-phone become more important than ever. Allowing using PEDs on board becomes a name card of airlines. However, the leakage of PEDs' emission has potential threaten to the safety of navigation, which must be eliminated according to the regulations of Civil Aviation. In this paper, the leaky radiation of cargo gap is studied at the Very High Frequency range (VHF range), and some guides to weaken the leakage are provided. © 2023 IEEE.

关键词： Interference Path Loss (IPL) leaky antenna Portable Electronic Device (PED)

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