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2nd International Conference on Machine Learning and Intelligent Systems Engineering, MLISE 2022

作者： Li, Yuantao Zhang, Ruizhi Wang, Jie Shi, Jiahao University Of Science And Technology Of China School Of Software Engineering Hefei China

ISBN: (数字)9781665492461

ISBN: (纸本)9781665492461

As an important indicator of economic development, house price prediction is a hot issue in the field of business and research in urban computing. However, due to a variety of influencing factors and sparse transaction records, how to construct a housing price prediction framework is still a challenging problem. However, the existing machine learning and deep learning methods lack consideration of multi-source factors. Therefore, this paper uses the method based on channel exchange network to solve the problem of urban house price prediction. This paper also considers the space-time factors, regional factors and housing price expectations. In this paper, a neural network framework based on channel switching network is designed to capture these factors, and the characteristics of different model training are fused through channel switching. © 2022 IEEE.

关键词： Data fusion

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Revisiting of AlphaStar

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IEEE TRANSACTIONS ON GAMES 2024年第2期16卷 317-330页

作者： Liu, Ruo-Ze Shen, Yanjie Yu, Yang Lu, Tong Nanjing Univ Natl Key Lab Novel Software Technol Nanjing 210019 Peoples R China

Research on StarCraft II (SC2) is considered important due to its similarity to real-life tasks and its potential to inspire game artificial intelligence design. However, the complexity of SC2 presents considerable challenges. In 2019, DeepMind proposed AlphaStar (AS), an agent that achieved Grandmaster level in SC2. Nevertheless, the reasons for AS's success remain unclear. In this article, we revisit AS by analyzing its technical details, implementation codes, and replays. We also propose the open-sourced mini-scaled AS's new versions to do ablation studies. We classify SC2 problems by difficulty level and suggest a research path for tackling them. We then identify several limitations of AS, such as its lack of strategic view, reasoning, scouting, changes in tactics, and planning. Our article also presents the first analysis of AS's replays. In conclusion, we emphasize that there is still a long way to solve the final SC2 problem.

关键词： Games Cameras Training Task analysis Chatbots Reinforcement learning Deep learning AlphaStar (AS) deep neural networks (DNNs) deep reinforcement learning (DRL) StarCraft (SC)

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Wearable-Based Human Emotion Inference System 2nd

Wearable-Based Human Emotion Inference System

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2nd EAI International Conference on Edge Computing and IoT: Systems, Management and Security, ICECI 2021

作者： Zhao, Zirui Zheng, Canlin College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9783031042300

Many emotion recognition methods which have been proposed today have different shortcomings. For example, some methods use expensive and cumbersome special-purpose hardware, such as EEG/ECG helmets, while others based on cameras and speech caused risk of privacy leakage. With the prosperous development and popularization of wearable devices, people tend to be equipped with multiple smart devices, which provides potential opportunities for lightweight emotional perception. Based on this, we take actions on developing universal portable system and multi-source wearable sensing technology devices. This paper designs an emotion recognition framework called MW-Emotion (Multi-source Wearable emotion recognition) featuring on low cost, universality, and portable commercial wearable devices to perceive multi-source sensing data and implement a system. It takes four basic emotions as the research object and implement an emotion recognition to explore deep context innovatively. The experimental results show that MW-Emotion has a recognition accuracy of 85.1% for person-dependent mode. The framework uses the method that different types of data are effectively fused through signal processing. We call it multimodal data fusion technology, which reduces the energy waste caused by data redundancy and effectively resists interference. © 2022, ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Emotion Recognition

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GMLN: Global-Local Multi-channel Learning Network for Spatiotemporal Prediction 5

GMLN: Global-Local Multi-channel Learning Network for Spatio...

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5th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2022

作者： Wang, Haoran Zhao, Zhe Zhang, Hongbo Shi, Jiahao University of Science and Technology of China School of Software Engineering Suzhou China

ISBN: (数字)9781665499163

ISBN: (纸本)9781665499163

Spatiotemporal prediction can serve a series of real-world applications such as urban transportation planning, public risk assessment, and air pollution control. However, this work is considered challenging due to the potential dynamic spatial and temporal dependency. Many existing methods treat one vertex vector as a whole in the learning process, ignoring that different features typically do not share the spatial dependency paradigm. In this paper, we propose an innovative spatiotemporal prediction framework called global-local multi-channel learning network (GMLN). To capture the respective spatial dependency of diverse features, we disassemble the feature dimension of vertex vectors to several channels and generate a global spatial graph to guide the information aggregation in each channel through a data-driven approach. Then, we fuse this global learning module with a GCN-based local dependency extraction component to model spatial dependencies from multiple perspectives. Finally, RNN-based temporal learning module is introduced to integrate long-range spatiotemporal information. We validate our model on PeMSD4 and experimentally prove that GMLN outperforms a range of baseline networks. © 2022 IEEE.

关键词： Urban transportation

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An empirical study of ChatGPT-related projects and their issues on GitHub

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EXPERT SYSTEMS WITH APPLICATIONS 2025年 267卷

作者： Lin, Zheng Zhang, Neng Liu, Chao Zheng, Zibin Sun Yat Sen Univ Sch Software Engn Zhuhai Peoples R China Cent China Normal Univ Sch Comp Sci Wuhan Peoples R China Chongqing Univ Sch Big Data & Software Engn Chongqing Peoples R China

Due to its powerful capabilities in natural language understanding and content generation, ChatGPT has received widespread attention since its launch in 2022. An increasing number of ChatGPT-related projects (that enhance the capabilities of ChatGPT, develop applications by calling ChatGPT APIs, etc.) are being released on GitHub and have sparked widespread discussions. However, GitHub does not provide a detailed classification of these projects to help users effectively explore interested projects. Additionally, the issues raised by users for these projects cover various aspects, e.g., installation, usage, and updates. It would be valuable to help developers prioritize more urgent issues and improve development efficiency. Unfortunately, there is currently no research focused on understanding the categories and issues of ChatGPT-related projects. To fill this gap, we retrieved 71,244 projects from GitHub using the keyword 'ChatGPT' and selected the top 200 representative projects with the highest numbers of stars as our dataset. By analyzing the project descriptions, we identified three primary categories of ChatGPT-related projects, namely ChatGPT Implementation & Training, ChatGPT Application, ChatGPT Improvement & Extension. We further built a classifier for automatically categorizing projects based on the 200 manually annotated projects. Next, we applied a topic modeling technique to 23,609 issues of those projects and identified ten issue topics, e.g., model reply and interaction interface. We analyzed the popularity, difficulty, and evolution of each issue topic within the three project categories and further proposed a method for recommending solutions for open issues by summarizing the pull requests associated with closed issues. Our main findings are: (1) The increase in the number of projects within the three categories is closely related to the development of ChatGPT;and (2) There are significant differences in the popularity, difficulty, and evolutionar

关键词： Empirical study ChatGPT GitHub Open-source project Categorization Topic modeling

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Performance Modeling and Analysis of a de Bruijn Graph Based Local Assembly Kernel on Multiple Vendor GPUs

Performance Modeling and Analysis of a de Bruijn Graph Based...

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2024 Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Lindsey, LeAnn M. Ding, Nan Deslippe, Jack Awan, Muaaz University of Utah Kahlert School of Computing Salt Lake CityUT United States Lawrence Berkeley National Laboratory Computational Research Division BerkeleyCA United States Lawrence Berkeley National Laboratory NERSC Division BerkeleyCA United States

ISBN: (纸本)9798350355543

Bioinformatics workloads differ significantly from traditional scientific computing and AI workloads because they consist primarily of integer-only operations and string comparisons rather than floating-point operations. The underlying algorithms usually have low arithmetic intensity, irregular memory access patterns, and non-deterministic workloads. Local Assembly is an essential step in large-scale genome assembly software and is typically implemented using de Bruijn graphs. This paper examines the performance, portability, and productivity of a local assembly GPU kernel from a metagenome assembly pipeline implemented using hash table data structures on NVIDIA, AMD, and Intel GPUs. We focus on the challenges of achieving portability while maintaining performance for a complex bioinformatics GPU kernel that relies on hardware-specific optimizations. In this paper, we evaluate the local assembly kernel's performance and portability across different GPU architectures, identify performance bottlenecks, and propose modifications in existing tools and methods for performance modeling and analysis of integer-heavy bioinformatics application kernels. © 2024 IEEE.

关键词： CUDA de Bruijn Graph genome assembly HIP performance modeling portability SYCL

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On the Implications of Human-Paper Interaction for software Requirements Engineering Education 34

On the Implications of Human-Paper Interaction for Software ...

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34th International Conference on software Engineering and Knowledge Engineering, SEKE 2022

作者： Kamthan, Pankaj Department of Computer Science and Software Engineering Concordia University Montreal Canada

ISBN: (纸本)1891706543

It is broadly accepted that requirements engineering is one of the most important phases of a software project, and requires tools to be effective. For a variety of reasons, paper as a tool has lasted for millennia and remains ubiquitous. This paper makes a case for a contextual, conscientious, and evidence-based use of paper in a competency-oriented approach to software requirements engineering education (REE). It argues that the prophecies for the obsolescence of paper are premature, there are unique benefits in the use of paper, and the decision to use paper should be based on [0, 1] rather than (0, 1). In this regard, a need-centered conceptual model for human-paper interaction is proposed. The characteristics of paper that make it historically unique are reported and the affordances of paper relevant to REE are discussed. The REE-related activities that benefit from viewing paper as a boundary object and using different types of paper are highlighted and illustrated by means of examples. In advocating polyliteracy, the potential for a convergence of paper and digital media towards a harmonic coexistence is underscored. © 2022 Knowledge Systems Institute Graduate School. All rights reserved.

关键词： Requirements engineering

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Coordinated control of decarbonization efficiency and oxygen absorption rate in Ruhrstahl–Heraeus degasser based on mechanism model and BP neural network

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Journal of Iron and Steel Research International 2025年第3期32卷 606-618页

作者： Lu-heng Jiang Min Wang Jia-qi Zhao Cheng Yao Li-dong Xing Xin-gang Ai State Key Laboratory of Advanced Metallurgy University of Science and Technology BeijingBeijing100083China Technical Support Centre for Prevention and Control of Disastrous Accidents in Metal Smelting University of Science and Technology BeijingBeijing100083China Institute of Research of Iron&Steel Zhangjiagang215600JiangsuChina School of Materials and Metallurgy University of Science and Technology LiaoningAnshan114051LiaoningChina

A mathematical model of the decarburization reaction zone was established for the Ruhrstahl–Heraeus (RH) forced oxygen blowing decarburization process by Matlab R2022b software. For the problem of inaccurate prediction due to the large variation range of oxygen absorption rate under different process conditions, we statistically analyzed the main factors affecting the oxygen absorption rate. The backpropagation neural network was used to train and predict the oxygen absorption rate and was used to calculate the RH decarburization reaction zone model. We designed and developed a mathematical modeling software with process control of decarburization in RH degasser, which can realize the change of operating process parameters in the dynamic prediction process. The optimized mathematical model has more than 95% of the furnaces whose absolute error in calculation of carbon content is within ± 5 × 10^(−6), more than 90% of the heats whose relative error in calculation of oxygen content is within ± 15%, and the average absolute error of calculation of oxygen content is 26.4 × 10^(−6). Finally, we studied the influence of oxygen blowing timing, oxygen blowing volume and initial oxygen content on the forced decarburization process.

关键词： Ruhrstahl-Heraeus degasser Mathematical model Forced decarburization Oxygen absorption rate Process control

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A Quantum Group Signature Based on Quantum Walk in d Dimensions 22

A Quantum Group Signature Based on Quantum Walk in d Dimensi...

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6th International Conference on High Performance Compilation, Computing and Communications, HP3C 2022

作者： Qian, Yunxiao Yu, Haoyang School of Software Engineering University of Science and Technology of China Hefei China

ISBN: (纸本)9781450396295

In this paper, a group signature scheme based on quantum walk for quantum messages is proposed. Our scheme uses long step quantum walk-based teleportation and modified quantum one-time pad to authenticate the quantum messages respectively. In our scheme, the signer in a group signs the quantum messages by quantum walk-based teleportation and modified quantum one-time pad. The verifier can verify the signature via quantum walk-based teleportation while the group manager verifies the signature and identifies the signer via modified quantum one-time pad. The security analysis shows that the scheme can reach the properties of group signature. Compared to the teleportation via EPR pairs or Bell-like states, quantum walks are more flexible and use less measurement resources. Quantum teleportation via long-step quantum walk is more secure than that via one-step quantum walk in previous related works. The scheme can apply to arbitrary finite dimensional quantum systems and can also be possible to realize in practice. © 2022 ACM.

关键词： Quantum optics

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A Multiobjective Evolutionary Multitasking Algorithm Based on Decomposition and Multiple Knowledge Transfer 4

A Multiobjective Evolutionary Multitasking Algorithm Based o...

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4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022

作者： Wu, Zhongjian Zhu, Qingling Chen, Jianyong Shenzhen University College of Computer Science and Software Engineering Shenzhen China

ISBN: (数字)9781665459822

ISBN: (纸本)9781665459822

Multiobjective evolutionary multitasking (MOEMT) has become very popular in recent years, as this kind of methods aims to solve a set of multiobjective optimization problems (MOPs) simultaneously, which has been validated to be more promising than the traditional way that solves MOPs separately. However, most existing studies of MOEMT solve the MOP as a whole and use one single knowledge transfer strategy for solving all tasks, which is not so efficient as the MOP could be further decomposed into a set of subproblems and needs different strategies for knowledge transfer. To solve this problem, this paper suggests a new MOEMT algorithm (MOEMTA) based on decomposition and multiple knowledge transfer (MOEMTA-DM). First, the decomposition method is used to transform an MOP in each task into a set of subproblems, and the subproblems with greater performance improvement are chosen. Then their associated solutions will be selected to run multiple knowledge transfer strategies via both implicit and explicit ways, which can share the useful search experience between tasks. This way, computational resources can be adaptively assigned to speed up the solving of all tasks and the effect of knowledge transfer among all tasks can be improved. The effectiveness of the proposed algorithm was verified by studying benchmark multitasking MOPs (MTMOPs). Experimental results showed the proposed algorithm is more effective than other compared MOEMT algorithms. © 2022 IEEE.

关键词： Multiobjective optimization

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