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arXiv 2022年

作者： Wang, Xu Jin, Yi Cen, Yigang Wang, Tao Tang, Bowen Li, Yidong School Of Computer And Information Technology Beijing Jiaotong University Beijing China Computer Architecture Institute Of Computing Technology Chinese Academy Of Sciences Beijing China

Compared with traditional task-irrelevant downsampling methods, task-oriented neural networks have shown improved performance in point cloud downsampling range. Recently, Transformer family of networks has shown a more powerful learning capacity in visual tasks. However, Transformerbased architectures potentially consume too many resources which are usually worthless for low overhead task networks in downsampling range. This paper proposes a novel light-weight Transformer network (LighTN) for task-oriented point cloud downsampling, as an end-to-end and plug-and-play solution. In LighTN, a single-head self-correlation module is presented to extract refined global contextual features, where three projection matrices are simultaneously eliminated to save resource overhead, and the output of symmetric matrix satisfies the permutation invariant. Then, we design a novel downsampling loss function to guide LighTN focuses on critical point cloud regions with more uniform distribution and prominent points coverage. Furthermore, We introduce a feed-forward network scaling mechanism to enhance the learnable capacity of LighTN according to the expand-reduce strategy. The result of extensive experiments on classification and registration tasks demonstrates LighTN can achieve state-of-the-art performance with limited resource overhead. Copyright © 2022, The Authors. All rights reserved.

关键词： Energy efficiency

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Data Heterogeneity Challenge in Consumer Electronics: A Federated Learning Solution

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IEEE Transactions on Consumer Electronics 2025年

作者： Liu, Zhenyu Wu, Yunting Ge, Huanhuan Wang, Jinlong Lyu, Zhihan Qingdao University of Technology School of Information and Control Engineering Shandong Qingdao China School of Information and Control Engineering Innovation Institute for Sustainable Maritime Architecture Research and Technology Shandong Qingdao China School of Computer Science and Technology Xidian University Xi’an710126 China

Federated learning(FL) enables collaborative model training across consumer electronic devices while preserving data privacy. However, the non-independent and identically distributed nature of data in real-world scenarios significantly impacts personalization performance. To address this challenge, we propose pFedPKD, in this framework, we first employ model pruning to simplify the global model, thereby enhancing its adaptability and improving the efficiency of knowledge transfer between different electronics devices. Moreover, we introduce an attention-based knowledge transfer mechanism, which leverages knowledge distillation to transfer the attention map and predictions of the pruned global model to the local models, thus improving their generalization capability and performance. Extensive experiments on three datasets demonstrate that pFedPKD consistently outperforms state-of-the-art methods, achieving higher personalization accuracy and robustness under heterogeneous data distributions. This work provides an efficient solution for applying FL in consumer electronics, offering improved adaptability and resource efficiency. © 1975-2011 IEEE.

关键词： Knowledge transfer

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Automated Discovery of CEP Applications with Evolutionary Computing 25

Automated Discovery of CEP Applications with Evolutionary Co...

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Proceedings of the 19th ACM International Conference on Distributed and Event-based Systems

作者： Giulio Appetito Eric Medvet Vincenzo Gulisano Department of Civil Engineering and Computer Science Engineering (DICII) University of Rome Tor Vergata Roma Italy Department of Engineering and Architecture University of Trieste Trieste Italy Department of Computer Science and Engineering Chalmers University of Technology and University of Gothenburg Gothenburg Sweden

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Application of residual network in household waste classification

Application of residual network in household waste classific...

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Control, Electronics and computer technology (ICCECT), IEEE International Conference on

作者： Yutong Guo Jie Luo Weile Guo College of Computer Science and Cyber Security Oxford Brookes College Chengdu University of Technology Chengdu China College of Metallurgical Engineering Xi’an University of Architecture and Technology Xi’an China

With the acceleration of urbanization, the amount of garbage has skyrocketed. This makes the burden of sorting waste by manual means heavier and heavier, resulting in a large amount of waste accumulation. In this context, the classification of household garbage gradually received attention. In order to improve the efficiency of garbage classification, we should deal with the increasingly complicated garbage classification work and make garbage classification intelligent and efficient. In this paper, convolutional neural network intelligent algorithm is used to solve the classification problem of organic and inorganic garbage in daily life. The accuracy can reach 90.34% only with low sequence training. Compared with existing commonly used garbage classification and recognition algorithms, the proposed garbage classification and recognition algorithm has better recognition performance and is more suitable for widespread application.

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The evolution of inharmonicity and noisiness in contemporary popular music

arXiv

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arXiv 2024年

作者： Deruty, Emmanuel Meredith, David Lattner, Stefan Sony Computer Science Laboratories 6 rue Amyot Paris75005 France Department of Architecture Design and Media Technology Aalborg University Rendsburggade 14 Aalborg9000 Denmark

Much of Western classical music relies on instruments based on acoustic resonance, which produce harmonic or quasi-harmonic sounds. In contrast, since the mid-twentieth century, popular music has increasingly been produced in recording studios, where it is not bound by the constraints of harmonic sounds. In this study, we use modified MPEG-7 features to explore and characterise the evolution of noise and inharmonicity in popular music since 1961. We place this evolution in the context of other broad categories of music, including Western classical piano music, orchestral music, and musique concrète. We introduce new features that distinguish between inharmonicity caused by noise and that resulting from interactions between discrete partials. Our analysis reveals that the history of popular music since 1961 can be divided into three phases. From 1961 to 1972, inharmonicity in popular music, initially only slightly higher than in orchestral music, increased significantly. Between 1972 and 1986, this rise in inharmonicity was accompanied by an increase in noise, but since 1986, both inharmonicity and noise have moderately decreased. In recent years (up to 2020), popular music has remained much more inharmonic than popular music from the 1960s or orchestral music involving acoustic resonance instruments. However, it has become less noisy, with noise levels comparable to those of orchestral music. We relate these trends to the evolution of music production techniques. In particular, the use of multi-tracking may explain the higher inharmonicity in popular music compared to orchestral music. We illustrate these trends with analyses of key artists and *** Codes 68T05, 42C40 © 2024, CC BY.

关键词： Background noise

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An Auto-Parallel Method for Deep Learning Models Based on Genetic Algorithm 29

An Auto-Parallel Method for Deep Learning Models Based on Ge...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Zeng, Yan Huang, Chengchuang Ni, Yijie Zhou, Chunbao Zhang, Jilin Wang, Jue Zhou, Mingyao Xue, Meiting Zhang, Yunquan Hangzhou Dianzi University School of Computer Science and Technology Hangzhou310018 China Ministry of Education Key Laboratory for Modeling and Simulation of Complex Systems Hangzhou310018 China Data Security Governance Zhejiang Engineering Research Center Hangzhou310018 China Hangzhou Dianzi University School of ITMO Joint Institute Hangzhou310018 China Institute of Computer Network Information Center of the Chinese Academy of Sciences Beijing100086 China HuaWei China Institute of Computing Technology of the Chinese Academy of Sciences State Key Laboratory of Computer Architecture Beijing100086 China

ISBN: (纸本)9798350330717

As the size of datasets and neural network models increases, automatic parallelization methods for models have become a research hotspot in recent years. The existing auto-parallel methods based on machine learning or graph algorithms still have issues with search efficiency and applicability. This paper proposes an automatic parallel method based on a dual-population genetic algorithm, TGA, which transforms model partitioning and placement into an integer linear programming problem and constructs a cost model to evaluate the solution. The solution space is built using the neural network's dataflow graph and device cluster's topology, and the dual-population genetic algorithm is used to search for the optimal model parallel strategy. Experiments with various models show that the proposed method can improve single-step execution time by up to 42% compared to the Baechi method and up to 37.7% compared to the Hierarchical method. © 2023 IEEE.

关键词： Auto-Parallel Distributed machine learning Genetic algorithm Integer linear programming Model parallelism

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Calligraphy's Reflective Expression: Intelligent Chinese Calligraphy Affective and Style Recognition

Calligraphy's Reflective Expression: Intelligent Chinese Cal...

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International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC

作者： Baixi Xing Yanhong Pan Qimeng Chen Xinjie Song Kaiqi Wang Yuehan Shi Industrial Design Institute Zhejiang University of Technology Hangzhou China School of Design and Architecture Zhejiang University of Technology Hangzhou China College of Computer Science and Technology Hangzhou Dianzi University Hangzhou China

Calligraphy expresses people's inner mood and reflects their self-cultivation. Style and emotion plays a key role in calligraphy artistry. Consequently, we applied intelligent technology to analyze the emotion and artistic style recognition of Chinese calligraphy artworks. A dataset of 5,000 calligraphy images was established, including art works over seventy renowned Chinese calligraphists. We compared several deep-learning methods to build the best model. The results show that the optimal model achieves an accuracy of 0.9319 with MobileNet in calligraphy emotion recognition, while it achieves the best accuracy of 0.972 in calligraphy font style recognition, and the highest classification accuracy of 0.943 in calligraphy artist's style recognition respectively using ResNet50. Finally, an intelligent Chinese calligraphy emotion and style exploration application are developed based on the optimal model.

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LawLuo: A Multi-Agent Collaborative Framework for Multi-Round Chinese Legal Consultation

arXiv

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arXiv 2024年

作者： Sun, Jingyun Dai, Chengxiao Luo, Zhongze Chang, Yangbo Li, Yang College of Computer and Control Engineering Northeast Forestry University Faculty of Information and Communication Technology Universiti Tunku Abdul Rahman College of Architecture and Arts Design Shijiazhuang Tiedao University

Legal Large Language Models (LLMs) have shown promise in providing legal consultations to non-experts. However, most existing Chinese legal consultation models are based on single-agent systems, which differ from real-world legal consultations, where multiple professionals collaborate to offer more tailored responses. To better simulate real consultations, we propose LawLuo, a multi-agent framework for multi-turn Chinese legal consultations. LawLuo includes four agents: the receptionist agent, which assesses user intent and selects a lawyer agent;the lawyer agent, which interacts with the user;the secretary agent, which organizes conversation records and generates consultation reports;and the boss agent, which evaluates the performance of the lawyer and secretary agents to ensure optimal results. These agents’ interactions mimic the operations of real law firms. To train them to follow different legal instructions, we developed distinct fine-tuning datasets. We also introduce a case graph-based RAG to help the lawyer agent address vague user inputs. Experimental results show that LawLuo outperforms baselines in generating more personalized and professional responses, handling ambiguous queries, and following legal instructions in multi-turn conversations. Our full code and constructed datasets will be open-sourced upon paper acceptance. © 2024, CC BY.

关键词： Modeling languages

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Automatic visual inspection system based on LCD screen 4

Automatic visual inspection system based on LCD screen

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4th IEEE International Conference on Civil Aviation Safety and Information technology, ICCASIT 2022

作者： Han, Juntao Xue, Hao Tang, Haitong Wu, Ting Ye, Yantong Li, Jingyang Jiangsu University of Science and Technology Computer Science Jiangsu Zhenjiang212028 China Jiangsu University of Science and Technology Institute of Telecommunication Jiangsu Zhenjiang212028 China Jiangsu University of Science and Technology Institute of Shenlan Jiangsu Zhenjiang212028 China Jiangsu University of Science and Technology Institute of Civil Engineering and Architecture Jiangsu Zhenjiang212028 China

ISBN: (数字)9781665467667

ISBN: (纸本)9781665467667

In the face of traditional detection technology, the efficiency is low, the accuracy is poor, the degree of human influence is large, and the cost is high;the key technologies in the automatic detection system in foreign markets are not disclosed to the public, and will not be provided to other companies for use, which is difficult to popularize and use on a large scale. External conditions;the machine vision-based LCD screen dead pixel detection system designed and developed in this paper integrates the advantages of high integration, low cost, high efficiency and high accuracy, which greatly meets the needs of the domestic mobile phone market and can be widely used in China. Major mobile phone manufacturers and LCD screen manufacturers. The system supporting automatic control platform designed and developed in this paper can meet the quality inspection of LCD screens of various sizes, and can also be invested in the maintenance of LCD screens of various electronic products to detect whether there are dead pixels on the mobile phone screen. © 2022 IEEE.

关键词： computer vision

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Boosting Solar Energy Production of a Building using New Architectural Design

Boosting Solar Energy Production of a Building using New Arc...

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Computational Intelligence and Sustainable Engineering Solutions (CISES), International Conference on

作者： Ladan Khalvati Zahra Ebrahimi Sheykhshabani Afshin Balal Negin Arbabzadeh Department of Design Texas Tech University Lubbock USA Architecture Department Pars Institute of Art and Architecture Tehran Iran Department of Electrical and Computer Engineering Texas Tech University Lubbock USA College of Architecture Iran University of Science and Technology Tehran Iran

Fossil fuels and air pollution are significant problems nowadays, causing many countries to increase their investments in renewable energy development. As the world's energy demand grows, governments are looking into and developing alternative energy sources like solar energy. Solar energy is one of the most promising solutions to address the above problem. In addition, the development of sustainable design in architecture has become a crucial factor in the construction industry as the world faces the challenges of climate change and diminishing fossil fuel reserves. Architects are now seeking innovative ways to incorporate sustainable and renewable energy sources into their designs. Solar energy, as a sustainable and clean energy source, has gained significant attention in recent years. It offers an opportunity to reduce the dependence on non-renewable energy sources and lower carbon emissions. Additionally, the use of solar technology in architectural designs can enhance the aesthetic appeal of buildings while providing energy efficiency. Building-integrated photovoltaic systems have emerged as a popular solution that allows for the integration of photovoltaic cells into the structure of buildings. In this paper, a new architectural design for a building in Tehran is proposed, which leads to the increase of generated solar energy. Needless to say, the designs must be beautiful to look at, functional, and good for the environment. Grasshopper and rhino are utilized to demonstrate the design. In addition, System Advisor Model (SAM) is implemented to study the economic analysis of the solar photovoltaic system planted on the building. The simulation result indicates that with the new design, the power production is increased from 21437 kWh to 69484 kWh. In addition, by using the proposed system in comparison with fossil fuel power plants, a huge amount of air pollution is will be removed from the air.

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