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arXiv 2025年

作者： Li, Ke Liu, Fei Wang, Zhengkun Zhang, Qingfu School of System Design and Intelligent Manufacturing Southern University of Science and Technology China Department of Computer Science City University of Hong Kong Hong Kong

Recent advancements in Neural Combinatorial Optimization (NCO) have shown promise in solving routing problems like the Traveling Salesman Problem (TSP) and Capacitated Vehicle Routing Problem (CVRP) without handcrafted designs. Research in this domain has explored two primary categories of methods: iterative and non-iterative. While non-iterative methods struggle to generate near-optimal solutions directly, iterative methods simplify the task by learning local search steps. However, existing iterative methods are often limited by restricted neighborhood searches, leading to suboptimal results. To address this limitation, we propose a novel approach that extends the search to larger neighborhoods by learning a destroy-and-repair strategy. Specifically, we introduce a Destroy-and-Repair framework based on Hyper-Graphs (DRHG). This framework reduces consecutive intact edges to hyper-edges, allowing the model to pay more attention to the destroyed part and decrease the complexity of encoding all nodes. Experiments demonstrate that DRHG achieves state-of-the-art performance on TSP with up to 10,000 nodes and shows strong generalization to real-world TSPLib and CVRPLib problems. Copyright © 2025, The Authors. All rights reserved.

关键词： Combinatorial optimization

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NO reduction by carbon-based gases based on coal gasification fractions:NO reduction intermediate identification and kinetic analysis

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Frontiers of Environmental science & Engineering 2025年第3期19卷 175-189页

作者： Xiang Zhang Jian Tian Tanghui Hu Guangyong Yue Xianlong Liu Wen Zhou Xiaohong Liu Xinye Wang Ministry-of-Education Key Laboratory for the Green Preparation and Application of Functional Materials Hubei Engineering Research Center for Green Industrialization Technology of Industrial WasteSchool of Materials Science and EngineeringHubei UniversityWuhan 430062China Hubei Huda Tianshu New Energy Materials Industrial Research and Design Institute Co. Ltd.Wuhan 430062China Wuhan Tianshu Dust Removal Equipment Co. Ltd.Wuhan 430062China Engineering Laboratory for Energy System Process Conversion&Emission Control Technology of Jiangsu Province School of Energy and Mechanical EngineeringNanjing Normal UniversityNanjing 210042China

Combining pulverized coal gasifiers with cement kiln production is promising for application in low-cost and efficient NO *** paper presents a pulverized coal gasifier catalytic denitration technique and investigates the homogeneous reduction(by CO and CH_(4))and heterogeneous catalytic reduction(by coke,CaO,MgO,and Fe_(2)O_(3))of NO.A combination of Chemkin simulations and fixed-bed experiments is used to elucidate the reaction pathways and key intermediates of NO reduction by carbon-based *** addition,the activation energies for different catalyst combinations were analyzed via reaction *** results demonstrate that the presence of small amounts of O_(2) inhibits NO reduction by CO but promotes NO reduction by CH_(4).The NCO·radical is essential for the NO reduction process,and the generation of this radical depends on the CH_(4) cleavage intermediate and O·*** and Fe_(2)O_(3) exhibit more significant catalytic effects on NO reduction by carbon-based gases than the other catalysts *** presence of a small amount of O_(2) in the reacting gas mixtures facilitates the NO reduction *** activation energy is reduced to 1.02 kJ/mol,and the NO conversion reaches 99.80%when the catalyst is C+CaO+MgO+Fe_(2)O_(3) and the gas composition is CO+CH_(4)+O_(2).This work provides theoretical support and data recommendations for the use of pulverized coal gasifiers for the denitrification of cement kilns.

关键词： Carbon-based gas Catalytic denitration Coke Kinetic analysis Reaction mechanism

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Estimation of Indoor Space Temperature Distribution Using Heat Maps

Estimation of Indoor Space Temperature Distribution Using He...

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Annual Conference of Industrial Electronics Society

作者： Emiri Hayashi Ayu Sonoda Akihito Nishikawa Hiroaki Nishi Graduate School of Science and Technology Keio University Yokohama Japan Department of System Design Faculty of Science and Technology Keio University Yokohama Japan

In recent years, there has been an increasing demand for accurate measurement of the spatial dispersion of air temperature in air conditioning control for indoor environments. This spatial dispersion of temperature is caused by the unevenness of air conditioning equipment, local temperature gradients due to human activities, and local heat exchange with outdoor air, all of which hinder the provision of a comfortable environment. This issue requires resolution in various fields, including the agricultural sector, where it can negatively impact crop growth. To address this issue, it is necessary to measure air temperature at multiple points, although the number of sensors that can be installed is typically limited, and the temperature at a single point is typically used as a representation of the temperature in the space. Additionally, heat maps using infrared array sensors can acquire temperature distribution in a narrow area; however, they cannot directly determine air temperature as they only measure the surface temperature of an object. Therefore, we propose a deep learning-based method that utilizes both heat maps acquired from infrared array sensors and air temperature data obtained from environmental sensors to estimate air temperature. We evaluate its effectiveness by varying the experimental environment, the model structure, and the resolution and number of heat maps added as input. Furthermore, we assess the usefulness of utilizing a Graphics Processing Unit (GPU), which is a cost-effective solution that can be installed on low-resolution sensors and edge devices. The outcomes indicate that the proposed model can attain an estimation accuracy of under 1 mean squared error (MSE) in approximately 200 seconds, while also exhibiting practical feasibility for deployment on edge devices, including residential abodes and agricultural premises.

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Human-Computer Interaction and Knowledge Transfer: Study of E-Learning Achievement 7

Human-Computer Interaction and Knowledge Transfer: Study of ...

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7th International Conference of Computer and Informatics Engineering, IC2IE 2024

作者： Alamsyah, Doni Purnama Othman, Norfaridatul Ahkmaliah Kerta, Johan Muliadi Morika, Doni Ramdhani, Yudi Bina Nusantara University Binus Business School Creativepreneurship Department Jakarta Indonesia Universiti Teknikal Malaysia Melaka Department of Management Technology Melaka Malaysia Bina Nusantara University School of Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University School of Design Design Interior Department Jakarta Indonesia Satu University Information System Program Bandung Indonesia

ISBN: (纸本)9798331505530

Human-computer interaction influences the effectiveness of e-learning knowledge transfer, so it is necessary to pay attention to user engagement and achievement. The aim of this research is to examine the factors that support e-learning knowledge transfer through achievement and user engagement (self-efficacy, self-confidence, self-esteem). The research method was carried out by surveying e-learning users, namely students, data from students was collected through quantitative questionnaires. The data is then processed using the SmartPLS tool through two tests, namely the PLS Algorithm and Boostrapping. The model was tested using inner and outer tests, and the data was analyzed based on the research hypothesis design. Student interactions with e-learning influence several behaviors that can support e-learning knowledge transfer performance. The research results prove that student e-learning achievement has a positive impact on e-learning knowledge transfer. Several supporting factors play a role in increasing e-learning achievement, namely self-efficacy, self-confidence and self-esteem of students. However, the supporting factors for students are only self-efficacy and self-confidence which are directly able to increase e-learning knowledge transfer. It is known that students who are less able to respect themselves in interacting with e-learning are unable to support knowledge transfer. The rules of human-computer interaction play a role in supporting e-learning knowledge transfer, studies on user behavior need to be considered, especially self-efficacy and self-confidence to support online learning academic performance. © 2024 IEEE.

关键词： Knowledge transfer

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LLM-Driven Neighborhood Search for Efficient Heuristic design

LLM-Driven Neighborhood Search for Efficient Heuristic Desig...

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Congress on Evolutionary Computation

作者： Zhuoliang Xie Fei Liu Zhenkun Wang Qingfu Zhang Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology & School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China Department of Computer Science City University of Hong Kong Hong Kong China

ISBN: (数字)9798331534318

ISBN: (纸本)9798331534325

Handcrafting heuristics often demands extensive domain knowledge and significant development effort. Recently, heuristic search powered by large language models (LLMs) has emerged as a new approach, offering enhanced automation and promising performance. Existing methods rely on an evolutionary computation (EC) framework with carefully designed prompt strategies. However, the large heuristic search space poses significant challenges for these EC-based methods. This paper proposes a simple yet effective LLM-driven Heuristic Neighborhood Search (LHNS) paradigm to iteratively search in the heuristic neighborhood in a principled way for efficient heuristic design. Three distinct methods are designed under this neighborhood search paradigm and demonstrated on three widely studied problems. Results indicate that LHNS exhibits very competitive performance and surpasses existing EC-based methods in efficiency. It also demonstrates sufficient robustness in the absence of problem-specific knowledge regarding the target problem. The efficiency and robust adaptability make it a practical new solution for efficient heuristic design.

关键词： Automation Large language models Evolutionary computation Search problems Robustness

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Evaluation of Communication Overhead for Distributed Deep Learning for Local Data Privacy

Evaluation of Communication Overhead for Distributed Deep Le...

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Annual Conference of Industrial Electronics Society

作者： Yuma Okuda Akihito Nishikawa Hiroaki Nishi Graduate School of Science and Technology Keio University Yokohama Japan Department of System Design Faculty of Science and Technology Keio University Yokohama Japan

In recent years, there has been growing interest in using big data for machine learning applications. However, as data are often distributed across multiple clients, privacy and physical limitations can make it difficult to aggregate and use these data on centralized servers. Federated learning and split neural networks enable machine learning models to be built without requiring the aggregation of distributed data. These methods have received increased attention in the industrial sector as a means of eliminating impediments to privacy preservation in data sharing across various institutions, such as smart factories. One critical aspect of implementing such methods in practice is analyzing the time variation of traffic and estimating the throughput required for operationalizing machine learning. Previous studies have formulated traffic characteristics without considering packet overhead and measured only the total traffic and the throughput per iteration; such an approach is inadequate from a traffic monitoring perspective. To address these issues, this study conducted an empirical investigation of traffic patterns under realistic conditions, with a particular focus on quantifying traffic and latency. The results of this study suggest that due to the dynamic nature of throughput, it is essential to measure traffic using time units that can accommodate the temporal variability of traffic.

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Layer-7 and 5-Tuple Information Analysis Framework for Providing Positional Flexibility In Location Determination for Service Provision

Layer-7 and 5-Tuple Information Analysis Framework for Provi...

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Annual Conference of Industrial Electronics Society

作者： Yuri Sato Yohei Namba Hiroaki Nishi Graduate School of Science and Technology Keio University Kanagawa Japan Department of System Design Faculty of Science and Technology Keio University Kanagawa Japan

In a smart community, which is an initiative to create an efficient regional society by leveraging information and communications technology (ICT), various data exchanges and data processing are performed. Owing to the demand for network transparency in data processing, packet rewriting is required at network edges. In the packet rewriting process, packets need to be analyzed after obtaining the necessary permissions. A conventional method for packet analysis is using a 5-tuple. While this method can analyze packets by a service user, it cannot analyze packets by a service. Moreover, service provision needs to take place at the appropriate locations with respect to the privacy level, and service provision locations need to be flexible enough to change even subsequent to the commencement of services. To address this issue, there is a need to enable positional flexibility in determining the location for service provision between the data source and cloud. In this study, assuming that the permission to analyze packets had been obtained within the smart community, we implemented a framework that could analyze not only 5-tuple but also layer-7 (L7) information and rewrite packet contents based on the analysis results. The process performed at the edge first analyzed the header of the incoming packet to determine whether the packet was subject to L7 information analysis. If the packet was subject to analysis, the L7 information was analyzed to determine whether the packet was subject to rewriting. A packet subject to rewriting were rewritten and forwarded accordingly. For this series of packet process, we used the Data Plane Development Kit (DPDK), a tool that could speed up packet processing. The framework was applied to the anonymization process, and the delay due to the anonymization process was 0.195 ms. With this framework, it is possible to achieve the packet content rewriting process at any point between the IoT device and the cloud by modifying the location of the

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Microstructure and mechanical properties of tib2/ al-si composites fabricated by electron beam rapid manufacture 21st

Microstructure and mechanical properties of tib2/ al-si comp...

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21st Chinese Materials Conference, CMC 2020

作者： Yang, Qingfeng Xia, Cunjuan Li, Xianfeng Wang, Haowei Liao, Nan Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610213 China The State Key Laboratory of Metal Matrix Composites Shanghai Jiaotong University Shanghai200240 China

ISBN: (纸本)9783035717389

Bulky sample was fabricated by electron beam rapid manufacture (EBRM) technology, in which Ф1.6 mm wire of in-situ TiB2/Al-Si compositeswas selected as deposition metal, following byT6 heat treatment. The microstructure and mechanical properties of the bulky sample before and afterheat treatment were analyzed. Experimental results showed that the microstructure parallel to the weld was similar to that perpendicular to the weld. The microstructure of the as-deposited sample consisted of columnar and equiaxed grains, in which siliconwas distributed along the grain boundary and the grain size was about 30 μm. Besides, some TiB2 particles converged at the grain boundary. After T6 heat treatment, the average grain size of the sample *** average hardness of the sample was increased to 114.65 HV from 46.55 HV, an increase of 146%. The tensile strength of the sample increased to 326.66MPafrom 143.97 MPa, but the elongationdecreased compared with that of the as-deposited state. The tensile test showed that the mechanical properties of TiB2/Al-Si composites formed by electron beam rapid manufacture were isotropic before and after heat treatment. © 2021 Trans Tech Publications Ltd, Switzerland.

关键词： Electron beams

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Few-shot gearbox fault diagnosed based on meta-learning and time convolution network

Few-shot gearbox fault diagnosed based on meta-learning and ...

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2022 Chinese Automation Congress, CAC 2022

作者： Dai, Yuan Ou, Yanghui Hu, Junwei Ping, Zuowei Xu, Xinghua Zhang, Yong Wuhan University of Science and Technology School of Information Science and Engineering Wuhan China Wuhan Second Ship Design and Research Institute Wuhan China Naval University of Engineering National Key Laboratory of Science and Technology on Vessel Integrated Power System Wuhan China

ISBN: (纸本)9781665465335

In order to resolve the problem that the traditional fault diagnosis methods can not accurately diagnose under complex working conditions and few fault data, a fault diagnosis method based on meta-learning and time convolution network (TCN) is proposed in this paper. Firstly, Ensemble Empirical Mode Decomposition-Independent Component Analysis (EEMDICA) is used to denoise the original signals under different working conditions, and the acquired signals are randomly sampled to form meta tasks according to the meta-learning protocol. Through the TCN model training, the priori knowledge is obtained by optimizing the initialization parameters. The knowledge is used to improve accuracy in unforeseen condition tasks. Finally, simulation experiments are carried out on the gearbox dataset. The results indicate that the method has advantages in solving the fault classification problem of few shot gearbox under complex working conditions. © 2022 IEEE.

关键词： Empirical mode decomposition

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Insights into Dissolved Oxygen Dependent Crack Initiation Mechanism of 316ln Stainless Steel Fatigue Tested in High-Temperature Pressurized Water

SSRN

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SSRN 2024年

作者： Qiao, Yufei Li, Hui Tan, Jibo Liu, Daoping Zhang, Ziyu Wu, Xinqiang Ke, Wei CAS Key Laboratory of Nuclear Materials and Safety Assessment Liaoning Key Laboratory for Safety and Assessment Technique of Nuclear Materials Institute of Metal Research Chinese Academy of Sciences Shenyang110016 China School of Materials Science and Engineering University of Science and Technology of China Hefei230026 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China China

The corrosion fatigue behavior of 316LN SS hollow specimen was investigated in high-temperature pressurized water at different dissolved oxygen (DO) concentrations ( © 2024, The Authors. All rights reserved.

关键词： Corrosion fatigue

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