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Digital Twin technology of Human-Machine Integration in Cross-Belt Sorting System

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Chinese Journal of Mechanical engineering 2024年第2期37卷 195-212页

作者： Yanbo Qu Ning Zhao Haojue Zhang School of Mechanical engineering University of Science and Technology BeijingBeijing 100083China institute of Microelectronics of the Chinese Academy of Sciences Beijing 100029China Wayzim technology Co. LtdWuxi 214108China business School Beijing Technology and Business UniversityBeijing 100048China

The Chinese express delivery industry processes nearly 110 billion items in 2022,averaging an annual growth rate of 200%.Among the various types of sorting systems used for handling express items,cross-belt sorting systems stand out as the most ***,despite their high degree of automation,the workload for operators has intensified owing to the surging volume of express *** the era of Industry 5.0,it is imperative to adopt new technologies that not only enhance worker welfare but also improve the efficiency of cross-belt *** a balance between efficiency in handling express items and operator well-being is *** twin technology offers a promising solution in this respect.A realization method of a human-machine integrated digital twin is proposed in this study,enabling the interaction of biological human bodies,virtual human bodies,virtual equipment,and logistics equipment in a closed loop,thus setting an operating *** technologies in the proposed framework include a collection of heterogeneous data from multiple sources,construction of the relationship between operator fatigue and operation efficiency based on physiological measurements,virtual model construction,and an online optimization module based on real-time *** feasibility of the proposed method was verified in an express distribution center.

关键词： Industry 5.0 Cross-belt sorting system Human-machine integrated Digital twin Online optimization

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Agricultural Investment Project Decisions Based on an Interactive Preference Disaggregation Model Considering Inconsistency

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Computer Modeling in engineering & Sciences 2024年第6期139卷 3125-3146页

作者： Xingli Wu Huchang Liao Shuxian Sun Zhengjun Wan business School Sichuan UniversityChengdu610064China National institute of Measurement and Testing technology Chengdu610021China

Agricultural investment project selection is a complex multi-criteria decision-making problem,as agricultural projects are easily influenced by various risk factors,and the evaluation information provided by decisionmakers usually involves uncertainty and *** literature primarily employed direct preference elicitation methods to address such issues,necessitating a great cognitive effort on the part of decision-makers during evaluation,specifically,determining the weights of *** this study,we propose an indirect preference elicitation method,known as a preference disaggregation method,to learn decision-maker preference models fromdecision *** enhance evaluation ease,decision-makers merely need to compare pairs of alternatives with which they are familiar,also known as reference *** linguistic preference relations are employed to account for the presence of incomplete and uncertain information in such pairwise *** address the inconsistency among a group of decision-makers,we develop a pair of 0-1mixed integer programming models that consider both the semantics of linguistic terms and the belief degrees of ***,we conduct a case study and comparative *** reveal the effectiveness of the proposed model in solving agricultural investment project selection problems with uncertain and inconsistent decision information.

关键词： Multiple criteria analysis preference disaggregation inconsistency probability linguistic preference relation investment project selection

Deep Guided Attention Network for Joint Denoising and Demosaicing in Real Image

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Chinese Journal of electronics 2024年第1期33卷 303-312页

作者： Tao ZHANG Ying FU Jun ZHANG School of Computer Science and technology Beijing Institute of Technology Advanced Reasearch institute of Multidisciplinary Science Beijing Institute of Technology

Denoising(DN) and demosaicing(DM) are the first crucial stages in the image signal processing pipeline. Recently, researches pay more attention to solve DN and DM in a joint manner, which is an extremely undetermined inverse problem. existing deep learning methods learn the desired prior on synthetic dataset, which limits the generalization of learned network to the real world data. Moreover, existing methods mainly focus on the raw data property of high green information sampling rate for DM, but occasionally exploit the high intensity and signalto-noise(SNR) of green channel. In this work, a deep guided attention network(DGAN) is presented for real image joint DN and DM(JDD), which considers both high SNR and high sampling rate of green information for DN and DM, respectively. To ease the training and fully exploit the data property of green channel, we first train DN and DM sub-networks sequentially and then learn them jointly, which can alleviate the error accumulation. Besides, in order to support the real image JDD, we collect paired raw clean RGB and noisy mosaic images to conduct a realistic dataset. The experimental results on real JDD dataset show the presented approach performs better than the state-of-the-art methods, in terms of both quantitative metrics and qualitative visualization.

关键词： Training Visualization Inverse problems Green products Noise reduction Pipelines Signal processing

Investigating the inflow into a granular bed using a locally resolved method

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Particuology 2024年第2期85卷 89-101页

作者： Maximilian Brommer Maik Scharnowski enric Illana Mahiques Siegmar Wirtz Viktor Scherer Ruhr University Bochum Institute of Energy Plant TechnologyUniversitätsstraβe 15044780BochumGermany

Discrete element Method-Computational Fluid Dynamics(DeM/CFD)simulations of industrial-scale granular systems employ spatial averaging(porous media approach)for the fluid-particle interaction in the whole domain,which can lead to poor accuracy,for instance at flow inlets,as local particle bulk morphology is not *** paper presents an approach where the interstitial flow in crucial areas with large gradients can be resolved locally in an otherwise unresolved domain,so that a mixed resolved-unresolved method is *** a generic example to show the feasibility and performance of the new approach,the inflow of ambient air into a flat-bottom hopper through a narrow orifice is *** an experimental setup,the vertical profile of the pressure decay through the inlet and across the packing is chosen for com-parison with respective *** obtained with the conventional porous media method and the locally resolved approach are compared to these experiments for varying volume flow rates and for two different particle *** of different size as well as dodecahedrons are *** is found that although averaging methods already provide good approximations,the locally resolved method can improve the result especially when conventional drag laws are not applicable due to wall effects or if large velocity gradients exist.

关键词： DeM/CFD Packed bed Pressure drop

experimental study on influence of blade angle and particle size on particle mechanics on a batch-operated single floor of a multiple hearth furnace

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Particuology 2024年第2期85卷 224-240页

作者： Max Kriegeskorte Nikoline Hilse Phil Spatz Viktor Scherer institute for energy Plant technology(LeAT) Ruhr University BochumUniversitätsstraβe 15044780 BochumGermany

In industry,multiple hearth furnaces are used for the thermal treatment of particulate *** current contribution concentrates on the experimental analysis of particle mechanics for a batch-operated single floor of a multiple hearth *** particles are agitated on the circular floor by a single,rotating rabble arm equipped with three flat rabble blades of 10 mm *** blade angle,defined as the angle,which the blade is inclined against the tangential direction,is varied from 0°to 90°.A single layer of spherical polyoxymethylene(POM)particles with three different diameters(5,10 and 20 mm)is placed on the *** analyze the results,two parameters have been extracted from image analysis when the bed of particles is agitated,first,the area not covered by particles and second,the frequency distribution of the mean distance among the *** particle free surface area increases with the inclination of the *** evolution of the particle free surface area differs for the different particle *** general,the maximum particle free area for all blade angles is the largest for the 5 mm particles followed by the 20 mm *** the 10 mm particles,the particle free surface area starts for a blade angle of 0°at larger values than for the 20 mm particles but the values fall below the values for the 20 mm particles for larger blade *** reason for this behavior is discussed in *** mean distance among the particles is a parameter characterizing the length scales dominating the effects on the *** frequency distribution of the mean distance among particles provides infor-mation about the morphology of the particle bulk,for example,whether the free surface area is inter-spersed with particles.

关键词： Hearth furnace floor Particle movement Spherical particles Particle free surface area Mean distance among particles

HeN:a novel hybrid explainable neural network based framework for robust network intrusion detection

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Science China(Information Sciences) 2024年第7期67卷 72-90页

作者： Wei WeI Sijin CHeN Cen CHeN Heshi WANG Jing LIU Zhongyao CHeNG Xiaofeng ZOU School of Computer Science and engineering Xi'an University of TechnologyShaanxi Key Laboratory for Network Computing and Security Technology School of Computer Science and technology Wuhan University of Science and Technology School of Future technology South China University of Technology Shenzhen Research institute of Hunan University School of Computer Science Hunan University of Technology and Business institute for Infocomm Research (I2R) Agency for Science Technology and Reseach (A*STAR)

With the rapid development of network technology and the automation process for 5G, cyberattacks have become increasingly complex and threatening. In response to these threats, researchers have developed various network intrusion detection systems(NIDS) to monitor network traffic. However, the incessant emergence of new attack techniques and the lack of system interpretability pose challenges to improving the detection performance of NIDS. To address these issues, this paper proposes a hybrid explainable neural network-based framework that improves both the interpretability of our model and the performance in detecting new attacks through the innovative application of the explainable artificial intelligence(XAI)method. We effectively introduce the Shapley additive explanations(SHAP) method to explain a light gradient boosting machine(Light GBM) model. Additionally, we propose an autoencoder long-term short-term memory(Ae-LSTM) network to reconstruct SHAP values previously generated. Furthermore, we define a threshold based on reconstruction errors observed during the training phase. Any network flow that surpasses the specified threshold is classified as an attack flow. This approach enhances the framework's ability to accurately identify attacks. We achieve an accuracy of 92.65%, a recall of 95.26%, a precision of 92.57%,and an F1-score of 93.90% on the dataset NSL-KDD. experimental results demonstrate that our approach generates detection performance on par with state-of-the-art methods.

关键词： explainable artificial intelligence light gradient boosting machine machine learning network intrusion detection Shapley additive explanation hybrid explainable neural network (HeN)

Distributed Region Tracking and Perimeter Surveillance for Second-Order Multi-Agent Systems in Star-Shaped Sets

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Journal of Systems Science & Complexity 2024年第5期37卷 1995-2020页

作者： SHANG Juan MO Lipo MI Rongxin CAO Xianbing School of Mathematics and Statistics Beijing Technology and Business UniversityBeijing 100048China The Department of Foundation Shijiazhuang Institute of Railway TechnologyShijiazhuang 050041China School of Computer and Artificial Intelligence Beijing Technology and Business UniversityBeijing 100048China Research Centre for Agri-Product Quality Traceability Beijing Technology and Business UniversityBeijing 100048China Coordination Center of China National Computer Network Emergency Response Technical TeamBeijing 100029China

This paper investigates region tracking and perimeter surveillance of second-order multiagent systems,where all agents move within a star-shaped ***,by coordination transformations,the region tracking problem is converted from the star-shaped sets to a circular *** authors employ communication and collaboration to complete region tracking and perimeter surveillance tasks,and then revert back to the star-shaped set by using inverse ***,the authors propose a distributed control strategy based on attractive and interaction potential functions,under which all agents can quickly track a given circular region and move around the ***,the authors validate the effectiveness and performance advantages of the proposed method through simulation experiments.

关键词： Distributed control multi-agent systems star-shaped sets target tracking

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Low-temperature graphitization of lignin via Co-assisted electrolysis in molten salt

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Green energy & environment 2024年第9期9卷 1449-1458页

作者： Shijie Li Wei-Li Song Xue Han Qingqing Cui Yan-li Zhu Shuqiang Jiao institute of Advanced Structure technology Beijing Institute of Technology State Key Laboratory of Advanced Metallurgy University of Science and Technology Beijing State Key Laboratory of explosion Science and technology Beijing Institute of Technology

The ever-growing energy demand and environmental issues have stimulated the development of sustainable energy ***,an efficient and environmentally friendly electrochemical transformation technology was proposed to prepare highly graphitized carbon materials from an abundant natural resource-lignin （LG）.The preparation process mainly includes pyrolytic carbonization of raw LG material and electrochemical conversion of amorphous carbon ***,with the assistance of Co catalyst,the graphitization degree of the products was significantly improved,in which the mechanism was the removal of heteroatoms in LG and the rearrangement of carbon atoms into graphite ***,tunable microstructures （nanoflakes） under catalytic effects could also be observed by controlling the electrolytic *** with the products CN1 （without catalyst） and CN5 （with 10%catalyst）,the specific surface area are 158.957 and202.246 m2g-1,*** used as the electrode material for lithium-ion batteries,CN5 delivered a competitive specific capacity of～350 m Ah g-1（0.5 C） compared with commercial *** strategy proposed in this work provides an effective way to extract value-added graphite materials from lignin and can be extended to the graphitization conversion of any other amorphous carbon precursor materials.

关键词： Lignin Graphitic carbon electrochemical conversion Lithium-ion batteries

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Multi-Objective equilibrium Optimizer for Feature Selection in High-Dimensional english Speech emotion Recognition

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Computers, Materials & Continua 2024年第2期78卷 1957-1975页

作者： Liya Yue Pei Hu Shu-Chuan Chu Jeng-Shyang Pan Fanli business School Nanyang Institute of TechnologyNanyang473004China School of Computer and Software Nanyang Institute of TechnologyNanyang473004China College of Computer Science and engineering Shandong University of Science and TechnologyQingdao266590China Department of Information Management Chaoyang University of TechnologyTaichung413310Taiwan

Speech emotion recognition(SeR)uses acoustic analysis to find features for emotion recognition and examines variations in voice that are caused by *** number of features acquired with acoustic analysis is extremely high,so we introduce a hybrid filter-wrapper feature selection algorithm based on an improved equilibrium optimizer for constructing an emotion recognition *** proposed algorithm implements multi-objective emotion recognition with the minimum number of selected features and maximum ***,we use the information gain and Fisher Score to sort the features extracted from ***,we employ a multi-objective ranking method to evaluate these features and assign different importance to *** with high rankings have a large probability of being ***,we propose a repair strategy to address the problem of duplicate solutions in multi-objective feature selection,which can improve the diversity of solutions and avoid falling into local *** random forest and K-nearest neighbor classifiers,four english speech emotion datasets are employed to test the proposed algorithm(MBeO)as well as other multi-objective emotion identification *** results illustrate that it performs well in inverted generational distance,hypervolume,Pareto solutions,and execution time,and MBeO is appropriate for high-dimensional english SeR.

关键词： Speech emotion recognition filter-wrapper high-dimensional feature selection equilibrium optimizer multi-objective