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Crowd E-Home—A Crowd-Based Collaborative Decoration Platform

International Journal of Crowd Science 2022年第3期6卷 135-141页

作者： Ge, Rui Sun, Hongbo School of Computer and Control Engineering Yantai University Yantai264005 China

With the rapid development of Chinese urbanization and industrialization level, the Chinese real estate transaction area continues to grow, and the country's decoration industry is expanding. Due to the rapid expansion, the decoration industry has failed to establish a good industry order, and the current decoration industry has many problems, such as opaque information and low industrial efficiency. Traditional and Internet decoration companies have failed to solve these problems effectively. The purpose of this study is to build a new collaborative decoration platform to solve the shortcomings of the decoration industry and promote its healthy development. A crowd-based collaborative decoration platform called Crowd E-home is proposed. Based on the Building Information Modeling (BIM) of houses, the platform constructs collaborative intelligent digital models, which have the characteristics of evolution, coordination, multifaceted, and initiative. These models act as intermediate coordinators to complete the collaborative division of labor. This platform plays a role in matching multiparty transactions among consumers, designers, construction teams, material suppliers, and supervisors to solve the problem of the huge coordination costs of traditional decoration companies. It also breaks the space-time limit of consumer selection during the decoration process, improves the decision-making power of consumers, and meets consumer needs for personalized services. The collaborative concept of the platform and the application of BIM optimize the existing decoration industry chain, which transforms the traditional chain model into a star-shaped decoration closed-loop ecosystem. © The author(s) 2022.

关键词： Decision making

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Multimodal Sentiment Analysis Using BiGRU and Attention-Based Hybrid Fusion Strategy

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Intelligent Automation & Soft Computing 2023年第8期37卷 1963-1981页

作者： Zhizhong Liu Bin Zhou Lingqiang Meng Guangyu Huang School of Computer and Control Engineering Yantai UniversityYantai264005China

Recently,multimodal sentiment analysis has increasingly attracted attention with the popularity of complementary data streams,which has great potential to surpass unimodal sentiment *** challenge of multimodal sentiment analysis is how to design an efficient multimodal feature fusion ***,existing work always considers feature-level fusion or decision-level fusion,and few research works focus on hybrid fusion strategies that contain feature-level fusion and decision-level *** improve the performance of multimodal sentiment analysis,we present a novel multimodal sentiment analysis model using BiGRU and attention-based hybrid fusion strategy(BAHFS).Firstly,we apply BiGRU to learn the unimodal features of text,audio and *** we fuse the unimodal features into bimodal features using the bimodal attention fusion ***,BAHFS feeds the unimodal features and bimodal features into the trimodal attention fusion module and the trimodal concatenation fusion module simultaneously to get two sets of trimodal ***,BAHFS makes a classification with the two sets of trimodal features respectively and gets the final analysis results with decision-level *** on the CMU-MOSI and CMU-MOSEI datasets,extensive experiments have been carried out to verify BAHFS’s superiority.

关键词： Multimdoal sentiment analysis BiGRU attention mechanism features-level fusion hybrid fusion strategy

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Research on Selective Harmonic Elimination Pulse Width Modulation of Three-Level NPC Inverter Based on Adaptive Restart Genetic Algorithm

Research on Selective Harmonic Elimination Pulse Width Modul...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Tao Jing Yuehua Liang A. S. Maklakov A. A. Nikolaev School of Computer and Information Engineering Henan University Kaifeng Henan China Zhejiang Entive Smart Kitchen Appliance Co. Ltd. Shengzhou Zhejiang China Department of Automation and Control Moscow Polytechnic University Moscow Russia Department of Automated Electric Drive and Mechatronics Nosov Magnitogorsk State Technical University Magnitogorsk Russia

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

The harmonic elimination task of three-level neutral point clamped (3L-NPC) inverters is related to a complicated engineering optimization problem, which mainly involves constrained nonlinear transcendental equations with multiple solutions. In order to solve the problems of difficult initial value determination, slow convergence rates and susceptibility to local optima trapping in the process of using traditional numerical algorithms, This paper introduces a novel selective harmonic elimination pulse width modulation (SHEPWM) framework, enhanced by an adaptive restart genetic algorithm, to address the limitations of conventional optimization methods. By introducing the adaptive restart mechanism, the performance and robustness of the solution algorithm can be improved, so as to circumvent entrapment in local optima and secure the global optimum across the entire solution space. The simulation results show that there are divergent trends in the switching angles and the total harmonic distortion (THD) values of the output voltage obtained by the proposed method, but all of them can effectively eliminate the specified low-order harmonics. These findings verifies the practical applicability and solution diversity of the proposed method, as well as provides new ideas and methods for solving optimization problems in other engineering fields.

关键词： Total harmonic distortion Voltage Switches Pulse width modulation Harmonic analysis Inverters Robustness Systems simulation Genetic algorithms Convergence

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Crowd-Based Traffic control Model and Simulation

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International Journal of Crowd Science 2024年第1期8卷 1-9页

作者： Wu, Dingding Sun, Hongbo Li, Zhihui School of Computer and Control Engineering Yantai University Yantai264005 China

With the development of modern science and economy, congestions and accidents are brought by increasing traffics. And to improve efficiency, traffic signal based control is usually used as an effective model to alleviate congestions and to reduce accidents. However, the fixed mode of existing phase and cycle time restrains the ability to satisfy ever complex environments, which lead to a low level of efficiency. To further improve traffic efficiency, this paper proposes a crowd-based control model to adapt complex traffic environments. In this model, subjects are deemed as digital selves who can perform actions in complex traffic environments, such as vehicles and traffic lights. These digital selves have their own control processing mechanisms, properties, and behaviors. And each digital self is continuously optimizing its behaviors according to its learning ability, road conditions, and information interactions from connections with the others. Without a fixed structure, the connections are diverse and random to form a more complex traffic environment, which may be connected or disappeared at any time with continues movements. Finally, feasibility and effectiveness of the crowd-based traffic control model is demonstrated by comparison with fixed traffic signal control model, indicating that the model can alleviate traffic congestion effectively. © The author(s) 2024.

关键词： Traffic congestion

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Part Deviation Correction Method Based on Geometric Feature Recognition

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International Journal of Crowd Science 2023年第3期7卷 113-119页

作者： Zhang, Guoqing Sun, Hongbo School of Computer and Control Engineering Yantai University Yantai264005 China

To realize the automatic loading process of parts, one of the core tasks is to identify the geometric contour of the part’s surface and the angular direction. Since the angular direction of each part is not the same when it arrives at the loading position, for example, there are two same types of parts with the same pattern, when they arrive at the loading position, the pattern on one part may be on the right side of the part surface, and the pattern on the other part may be on the left side of the part surface, the gripper of the mechanical arm needs to rotate above the parts in order to grab the parts during each loading process. If the rotation angle is wrong, there will be an impact between the gripper and the parts. Therefore, in order to solve the problem of different angles, this paper proposes a method of parts deviation correction based on geometric features. In this work, firstly, the acquired image is preprocessed, the image background is separated, and the geometric features of the parts are obtained. Then edge detection is used to obtain the set of edge pixels to obtain the contour in the image. Finally, the image moment and measurement model are used to output angular direction. Through 500 repeated detection experiments, the results show that this method can perform better angular direction correction. The maximum angular direction difference is 0.073°, which is 0.856° and 1.793° higher than the Least square method and Hough transform circle detection accuracy, respectively. The average detection time is 1.89 s and is 0.336 s and 1.39 s less than the Least square method and Hough transform circle detection, which meets the requirements of industrial applications. © The author(s) 2023.

关键词： Hough transforms

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Modeling and Verification of Simulation-Oriented Digital Selves

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International Journal of Crowd Science 2023年第2期7卷 87-96页

作者： Wang, Zhaotong Sun, Hongbo School of Computer and Control Engineering Yantai University Yantai264005 China

Networked life has now become one of our major life forms. In social networks, each individual has its own attributes and certain functions, which makes the current network present characteristics that the previous network did not have. The existing research believes that the structure and attributes of individuals in a network are the same, and they are in a single network at the same time. However, individuals in any social network may be in different networks at the same time and thus exhibit different behaviors, and such individuals are called digital selves. In this paper, we propose a simulation-oriented modeling method for digital selves, which allows them to be in multiple networks at the same time and to have their own decision-making mechanisms. The model consists of six parts, namely, pattern, affecter, decider, executor, monitor, and connector. After the verification of three simulation experiments, namely coevolutions, ecological structure evolution of an e-commerce market, and multi-information coevolution spreading, the model can be well applied in various scenarios, which verifies its feasibility and applicability. © The author(s) 2023.

关键词： Decision making

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A Crowd Equivalence-Based Massive Member Model Generation Method for Crowd Science Simulations

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International Journal of Crowd Science 2022年第1期6卷 23-33页

作者： Xing, Aoqiang Sun, Hongbo School of Computer and Control Engineering Yantai University Yantai264005 China

Crowd phenomena are widespread in human society, but they cannot be observed easily in the real world, and research on them cannot follow traditional ways. Simulation is one of the most effective means to support studies about crowd phenomena. As modelbased scientific activities, crowd science simulations take extra efforts on member models, which reflect individuals who own characteristics such as heterogeneity, large scale, and multiplicate connections. Unfortunately, collecting enormous members is difficult in reality. How to generate tremendous crowd equivalent member models according to real members is an urgent problem to be solved. A crowd equivalence-based massive member model generation method is proposed. Member model generation is accomplished according to the following steps. The first step is the member metamodel definition, which provides patterns and member model data elements for member model definition. The second step is member model definition, which defines types, quantities, and attributes of member models for member model generation. The third step is crowd network definition and generation, which defines and generates an equivalent large-scale crowd network according to the numerical characteristics of existing networks. On the basis of the structure of the large-scale crowd network, connections among member models are well established and regarded as social relationships among real members. The last step is member model generation. Based on the previous steps, it generates types, attributes, and connections among member models. According to the quality-time model of crowd intelligence level measurement, a crowd-oriented equivalence for crowd networks is derived on the basis of numerical characteristics. A massive member model generation tool is developed according to the proposed method. The member models generated by this tool possess multiplicate connections and attributes, which satisfy the requirements of crowd science simulations well. T

关键词： Data models Numerical models Level measurement Task analysis Standards

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COVID-19 Spread Simulation in a Crowd Intelligence Network

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International Journal of Crowd Science 2022年第3期6卷 117-127页

作者： Shan, Linzhi Sun, Hongbo School of Computer and Control Engineering Yantai University Yantai264005 China

In this paper, the Crowd Intelligence Network Model is applied to the simulation of epidemic spread. This model combines the multi-layer coupling network model and the two-stage feedback member model to study the epidemic spread mechanisms under multiple-scene intervention. First, this paper establishes a multi-layer coupled network structure based on the characteristic of Social Network, Information Network, and Monitor Network, namely, the Crowd Intelligence Network structure. Then, based on this structure, the digital-self model, which has a multiple-scene effect and two-stage feedback structure, is designed. It has an emotional state and infection state quantified by using attitude and self-protection levels. This paper uses the attitude level and self-protection level to quantify individual emotions and immune levels, and discusses the impact of individual emotions on epidemic prevention and control. Finally, the availability of the Crowd Intelligence Network Model on the epidemic spread is verified by comparing the simulation trend with the actual spread trend of COVID-19. © The author(s) 2022.

关键词： COVID-19

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An Energy-Aware RIoT System: Analysis, Modeling and Prediction in the SUPERIOT Framework

arXiv

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arXiv 2025年

作者： Bocus, Mohammud J. Häkkinen, Juha Fontes, Hélder Drzewiecki, Marcin Qiu, Senhui Eder, Kerstin Piechocki, Robert School of Computer Science University of Bristol Bristol United Kingdom Circuits and Systems Research Unit University of Oulu Oulu Finland MpicoSys Embedded Pico Systems Sp. z o. o. Gdynia Poland Faculty of Electrical and Control Engineering Gdańsk University of Technology Gdansk Poland INESC TEC Porto Portugal Faculty of Engineering University of Porto Porto Portugal

his paper presents a comprehensive analysis of the energy consumption characteristics of a Silicon (Si)-based Reconfigurable IoT (RIoT) node developed in the initial phase of the SUPERIOT project, focusing on key operating states, including Bluetooth Low Energy (BLE) communication, Narrow-Band Visible Light Communication (NBVLC), sensing, and E-ink display. Extensive measurements were conducted to establish a detailed energy profile, which serves as a benchmark for evaluating the effectiveness of subsequent optimizations and future node iterations. To minimize the energy consumption, multiple optimizations were implemented at both the software and hardware levels, achieving a reduction of over 60% in total energy usage through software modifications alone. Further improvements were realized by optimizing the E-ink display driving waveform and implementing a very low-power mode for non-communication activities. Based on the measured data, three measurement-based energy consumption models were developed to characterize the energy behavior of the node under: (i) normal, unoptimized operation, (ii) low-power, software-optimized operation, and (iii) very low-power, hardware-optimized operation. These models, validated with new measurement data, achieved an accuracy exceeding 97%, confirming their reliability for predicting energy consumption in diverse configurations. © 2025, CC BY.

关键词： Digital storage

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Rejection of nonharmonic disturbances for a class of uncertain nonlinear systems with nonlinear exosystems

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Science China(Information Sciences) 2013年第3期56卷 190-201页

作者： JIANG Yuan LIU ShuTang WANG RuLiang School of Information Engineering Nanchang Hangkong University School of Control Science and Engineering Shandong University School of Computer and Information Engineering Guangxi Teachers Education University

This paper proposes an asymptotic rejection algorithm for rejecting exotic disturbances in nonlinear *** produced by nonlinear exosystems are nonharmonic and periodic.A new internal model is proposed to deal with these ***,an adaptive output feedback controller is designed to ensure that the system’s state variables asymptotically converge to zero,and disturbances can be completely *** proposed algorithm has various applications,such as active vibration *** proposed algorithm is demonstrated to completely reject the nonharmonic periodic disturbances produced by a van der Pol oscillator.

关键词： disturbance rejection adaptive control nonharmonic periodic signal van der Pol oscillator global stability

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