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IEEE Transactions on Artificial Intelligence 2024年第7期5卷 3728-3742页

作者： Tang, Yiming Gao, Jianwei Pedrycz, Witold Hu, Xianghui Xi, Lei Ren, Fuji Hu, Min Hefei University of Technology Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei230601 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6R 2V4 Canada Hefei University of Technology School of Computer and Information Hefei230601 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Polish Academy of Sciences Systems Research Institute Warsaw00-901 Poland Istinye University Research Center of Performance and Productivity Analysis Istanbul34010 Turkey Southeast University School of Computer Science and Engineering Nanjing211189 China University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu611731 China

At present, there exist some problems in granular clustering methods, such as lack of nonlinear membership description and global optimization of granular data boundaries. To address these issues, in this study, revolving around the parabolic granular data, we propose an overall architecture for parabolic granular modeling and clustering. To begin with, novel coverage and specificity functions are established, and then a parabolic granular data structure is proposed. The fuzzy c-means (FCM) algorithm is used to obtain the numeric prototypes, and then particle swarm optimization (PSO) is introduced to construct the parabolic granular data from the global perspective under the guidance of principle of justifiable granularity (PJG). Combining the advantages of FCM and PSO, we propose the parabolic granular modeling and optimization (PGMO) method. Moreover, we put forward attribute weights and sample weights as well as a distance measure induced by the Gaussian kernel similarity, and then come up with the algorithm of weighted kernel fuzzy clustering for parabolic granularity (WKFC-PG). In addition, the assessment mechanism of parabolic granular clustering is discussed. In summary, we set up an overall architecture including parabolic granular modeling, clustering, and assessment. Finally, comparative experiments on artificial, UCI, and high-dimensional datasets validate that our overall architecture delivers a good improvement over previous strategies. The parameter analysis and time complexity are also given for WKFC-PG. In contrast with related granular clustering algorithms, it is observed that WKFC-PG performs better than other granular clustering algorithms and has superior stability in handling outliers, especially on high-dimensional datasets. © 2020 IEEE.

关键词： Fuzzy clustering

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Importance of Blackbody in Everyday Infrared Thermography 32nd

Importance of Blackbody in Everyday Infrared Thermography

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32nd International Conference on Organization and technology of Maintenance, OTO 2023

作者： Glavaš, Hrvoje Faculty of Electrical Engineering Computer Science and Information Technology Osijek University of Osijek Kneza Trpimira 2b Osijek31000 Croatia

ISBN: (纸本)9783031514937

Infrared thermography is a method of detecting thermal radiation, which is then associated with corresponding temperature values. Infrared thermal infrared cameras, like other measuring devices, must undergo a factory and periodic calibration process. The calibration is performed using blackbodies. This paper analyzes the practical application of the blackbody in the calibration of infrared thermal camera. Two infrared thermal cameras Flir E6 and Hikmicro M30 were calibrated with a Voltcraft IRS -350 blackbody. The calibration results are presented in tabular form, while the effect of the blackbody uncertainty on the overall measurement uncertainty is presented in graphical form. Since blackbodies are prohibitively expensive for most thermographers due to their price, calibration guidelines are provided to users when a blackbody is not available and the accuracy of the camera needs to be verified. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Calibration

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Energy Efficiency Enhancement in a Small Industrial Facility 32nd

Energy Efficiency Enhancement in a Small Industrial Facility

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32nd International Conference on Organization and technology of Maintenance, OTO 2023

作者： Kljajić, Ružica Kraus, Zorislav Fekete, Krešimir Marić, Predrag Faculty of Electrical Engineering Computer Science and Information Technology Osijek University of Osijek Kneza Trpimira 2b Osijek31000 Croatia

ISBN: (纸本)9783031514937

Small industrial utilities, connected to the distribution grid, can cause various disturbances that need to be eliminated or mitigated. Due to the complexity of the system and the large number of motors, industrial consumers may have problems with the voltage deviations caused by the excessive amount of reactive energy which is a natural consequence of their operation and construction. Since industrial consumers have to pay for both active and reactive power delivered from the grid, the goal is to reduce those costs as well as to reduce feeder loadings. Delivered energy can be reduced by installing compensation devices or by connecting photovoltaic power plant, which would produce active and reactive energy at the point of consumption. This paper analyzes the power flows and voltage conditions of a small industrial facility in three scenarios: the basic scenario, the second scenario with built-in compensation devices and in the third scenario with integrated photovoltaic power plant. For all three scenarios, power flow analysis is performed and results are presented in the form of tables and graphically. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Energy efficiency

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Automated Titration of SO2 in the Winery Environment: Conceptual Design and Proof of Concept 1

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32nd International Conference on Organization and technology of Maintenance, OTO 2023

作者： Keser, Tomislav Miling, Robert Miličević, Davorin Blažević, Damir Faculty of Electrical Engineering Computer Science and Information Technology Osijek University of Osijek Kneza Trpimira 2b Osijek31000 Croatia

ISBN: (数字)9783031514944

ISBN: (纸本)9783031514937

The wine production industry competes every day for better product quality, same time lowering production costs. As product quality strongly relies on winemaker expertise and quality of raw materials, lower production costs are tightly related to the automation level of whole production process. One of parameter that significantly influences on the wine quality is sulphur-oxide based compound in its free form which is measurable using process so called titration of SO (sulphur oxide titration). Currently the state of titration measurement automation highly correlates to the scale of production and only the biggest winemakers have some sort of automated titration devices. Such devices are not suitable for small or medium winemakers due their high costs, either of purchase of measurement services. This paper proposes, make conceptual development and evaluate functionality for an automated titration device for SO compounds in winemaking industry which is suitable for small and medium winemakers and does not break their banks. The concept elaborates and deduce setup for distributed wine supplying, conditioning of the measurement device and metrology of the measurement. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Titration

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RS485 Network Design and Maintenance in Food Processing Industry: A Winery Application 1

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32nd International Conference on Organization and technology of Maintenance, OTO 2023

作者： Kovačević, Ivana Matić, Tomislav Keser, Tomislav Miling, Robert Faculty of Electrical Engineering Computer Science and Information Technology Osijek University of Osijek Kneza Trpimira 2b Osijek31000 Croatia

ISBN: (数字)9783031514944

ISBN: (纸本)9783031514937

The communication networks are widely in use in every aspect of our life, making our environment compliable to the ever-present IoT oriented technocratic society. Good and quality communication enables reliable and representative data transportation service which provides interoperability of various data-processing systems. Majority of industrial processes have some sort of communication topologies used for interconnection of various subsystems, required by their specific operation principles, and often works in harsh and electrically and mechanically unpleasant environment. Presence of electromagnetic noises, electric discharges, strong and high alternating magnetic fields, mechanical and chemical stresses, also environmentally caused impacts on data transportation scheme, cause data corruption and lowers availability and reliability of such network. This paper deals with the problem of design, implementation and verification of RS485 based communication network for multi-nodal data exchange in winery cellars. The wine cellar represents exceptionally harsh environment in aspects of environmental chemical and electrical related conditions. The paper proposes optimal topology among multi-nodal communication devices for an experimental cellar setup, and develop communication protocol for efficient data exchange. Furthermore, a strategy for successful maintenance is also presented through in-protocol and nodal-oriented topology integration. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Wine

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An Advanced Tactile-Haptic Controller for Smart Home 32nd

An Advanced Tactile-Haptic Controller for Smart Home

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32nd International Conference on Organization and technology of Maintenance, OTO 2023

作者： Radić, Miloš Keser, Tomislav Blažević, Damir Faculty of Electrical Engineering Computer Science and Information Technology Osijek University of Osijek Kneza Trpimira 2b Osijek31000 Croatia

ISBN: (纸本)9783031514937

A smart home philosophy strongly relies on a technical principle of automatization almost every aspect of today’s way of living. Sole automation of does not only manage system processes in household, or living environment in general, but all adjacent systems and corresponding subsystems which helps to maintain system-in-whole in operational state. From control of environmental temperature, air conditioning, lighting, utility control, etc., all existing "smart" systems predominantly control actuation part of smart home. Very miniscule "smart" systems do manage and serve human-machine interaction part of it and, if are made "smart", they rely on solutions that utilizes some sort of existing ICT technologies that are mainly optimized for communication and visual presentation, not for in-situ smart home interaction. This paper deals with the problem of development of a tactile-haptic solution for control of smart home specific subsystem and that utilize IoT platform, giving feel and user experience similar to traditional one in form of an advanced switch with regulation ability. Tactile commanding with haptic feedback is presented and applied in smart home temperature regulation. Finally, an IoT platform solution is developed, tactile-haptic relation investigated with optimal solution established, and its functionality is verified as well as is proven in real time environment. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Air conditioning

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The Amalgamation of Federated Learning and Explainable Artificial Intelligence for the Internet of Medical Things: A Review

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Recent Advances in computer science and Communications 2024年第4期17卷 1-19页

作者： Govardanan, Chemmalar Selvi Murugan, Ramalingam Yenduri, Gokul Gurrammagari, Deepti Raj Bhulakshmi, Dasari Kandati, Dasaradharami Reddy Supriya, Yarradoddi Gadekallu, Thippa Reddy Rathore, Rajkumar Singh Jhaveri, Rutvij School of Information Technology and Engineering Vellore Institute of Technology Tamil Nadu Vellore632014 India Department of Computer Science Cardiff School of Technologies Cardiff Metropolitan University Llandaff Campus Western Avenue CardiffCF5 2YB United Kingdom Department of Computer Science and Engineering School of Technology Pandit Deendayal Energy University Gujarat Gandhinagar382007 India Lovely Professional University Phagwara India College of Information Science and Engineering Jiaxing University 314001 China Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon Zhongda Group Zhejiang Province HaiyanCounty Jiaxing City314312 China

The Internet of Medical Things (IoMT) has emerged as a paradigm shift in healthcare, integrating the Internet of Things (IoT) with medical devices, sensors, and healthcare systems. From peripheral devices that monitor vital signs to remote patient monitoring systems and smart hospitals, IoMT provides a vast array of applications that empower healthcare professionals. However, the integration of IoMT presents numerous obstacles, such as data security, privacy concerns, interoperability, scalability, and ethical considerations. For the successful integration and deployment of IoMT, addressing these obstacles is essential. Federated Learning (FL) permits collaborative model training while maintaining data privacy in distributed environments like IoMT. By incorporating Explainable Artificial Intelligence (XAI) techniques, the resulting models become more interpretable and transparent, enabling healthcare professionals to comprehend the underlying decision-making processes. This integration not only improves the credibility of Artificial Intelligence models but also facilitates the detection of biases, errors, and peculiar patterns in the data. The combination of FL and XAI contributes to the development of more privacy-preserving, trustworthy, and explainable AI systems, which are essential for the development of dependable and ethically sound IoMT applications. Hence, the aim of this paper is to conduct a literature review on the amalgamation of FL and XAI for IoMT. © 2024 Bentham science Publishers.

关键词： Decision making

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RIS-Aided MIMO Downlink Transmission for Ultradense LEO Satellite-Terrestrial Networks

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IEEE Internet of Things Journal 2025年第11期12卷 15304-15318页

作者： Zhang, Xin Qin, Xiaohan Zhang, Zitian Cai, Lin X. Zhou, Haibo Zhuang, Weihua Nanjing University School of Electronic Science and Engineering Nanjing210023 China Zhejiang Gongshang University School of Information and Electronic Engineering Hangzhou310018 China Illinois Institute of Technology Department of Electrical and Computer Engineering ChicagoIL60616 United States University of Waterloo Department of Electrical and Computer Engineering WaterlooONN2L 3G1 Canada

Ultradense low-Earth orbit (LEO) satellite-terrestrial network (ULSN) has evolved as a new paradigm to provide ubiquitous and high-capacity communications in next generation wireless networks. However, the direct LEO satellite broadband connectivity faces significant challenges in urban environments due to the masking effect, which limits the reliability and availability of communication links in ULSNs. To address this, reconfigurable intelligent surface (RIS) is emerging as a promising solution in ULSNs. In this article, we investigate RIS-aided downlink data transmission in urban environments of multiusers in ULSNs. We set up a mixed-integer programming (MIP) model for maximizing the sum rate of terrestrial users in ULSNs. To solve the complex MIP problem, we propose a two-phase joint optimization algorithm with a deep learning phase and an alternative optimization (AO) phase. In the deep learning phase, a deep neural network (DNN) algorithm is employed to obtain the optimal user association matrix based on the positions of terrestrial users and LEO satellites. Then in the AO phase, successive convex approximation is utilized to transform the nonconvex subproblems of beamforming and RIS phase design into convex formulations and iteratively solve them. Simulation results demonstrate that the proposed algorithm outperforms other baseline algorithms. © 2014 IEEE.

关键词： Integer programming

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A secure quantum homomorphic encryption ciphertext retrieval scheme

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Soft Computing 2025年第3期29卷 1497-1509页

作者： Cheng, Zhen-Wen Chen, Xiu-Bo Xu, Gang Chang, Yan Miao, Li-Hua Yang, Yi-Xian Wang, Ya-Lan School of Data and Computer Science Shandong Women’s University Jinan250300 China Information Security Center State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China School of Information Science and Technology North China University of Technology Beijing100144 China School of Cybersecurity Chengdu University of Information Technology Chengdu610225 China Huawei Technologies Co. Ltd Shenzhen518129 China Department of Computer Science Faculty of Engineering and Physical Sciences University of Surrey Surrey GuildfordGU2 7XH United Kingdom

In a recent paper (Gong et al. Quantum Inf Process 19:3, 2020), a novel ciphertext retrieval scheme based on the Grover algorithm and quantum homomorphic encryption was presented. In this scheme, when the server performs the operation of marking the solution on the user’s encrypted state in the Grover iteration, it needs to remove many gate-errors generated in the homomorphic evaluation of the T gate. And the server could judge this specific solution from the quantum circuit of marking the solution. It makes this scheme unable to achieve the low-cost and secure ciphertext retrieval. Therefore, we improve the Gong et al.’s scheme and propose a secure quantum homomorphic encryption ciphertext retrieval scheme. In our scheme, the trusted third party is introduced to cooperate with the server to execute the Grover algorithm. In each Grover iteration, the trusted third party can quickly mark the solution on the plaintext state, encrypt the marked state, and transmit it to the server. Then the server performs the remaining operations of this Grover iteration on the encrypted state. The trusted third party finally decrypts the iterated state. This cooperative approach ensures that the number of auxiliary qubits required and extra quantum gates executed in our scheme are lower than the Gong et al.’s scheme. By analyzing the security of our scheme, we confirm that the server and the trusted third party will not be informed of this solution. Thus, our scheme realizes the secure ciphertext retrieval with low computational overhead. We utilize IBM’s Qiskit framework to simulate our scheme, and the experimental result shows that our scheme is correct. It is worth noting that the low-cost and secure ciphertext retrieval will play a crucial role in modern information security and privacy protection. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Ciphertext

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Enhancing Septic Shock Detection through Interpretable Machine Learning

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computer Modeling in engineering & sciences 2024年第12期141卷 2501-2525页

作者： Md Mahfuzur Rahman Md Solaiman Chowdhury Mohammad Shorfuzzaman Lutful Karim Md Shafiullah Farag Azzedin Department of Information and Computer Science King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Department of Electrical and Computer Engineering North South UniversityDhaka1229Bangladesh Department of Computer Science Taif UniversityTaif21974Saudi Arabia College of Applied Arts and Technology Seneca PolytechnicTorontoM2J 2X5Canada Department of Control&Instrumentation Engineering King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia

This article presents an innovative approach that leverages interpretable machine learning models and cloud computing to accelerate the detection of septic shock by analyzing electronic health *** traditional methods,which often lack transparency in decision-making,our approach focuses on early detection,offering a proactive strategy to mitigate the risks of *** integrating advanced machine learning algorithms with interpretability techniques,our method not only provides accurate predictions but also offers clear insights into the factors influencing the model’s ***,we introduce a preference-based matching algorithm to evaluate disease severity,enabling timely interventions guided by the analysis *** innovative integration significantly enhances the effectiveness of our *** leverage a clinical health dataset comprising 1,552,210 Electronic Health Records(EHR)to train our interpretable machine learning models within a cloud computing *** techniques like feature importance analysis and model-agnostic interpretability tools,we aim to clarify the crucial indicators contributing to septic shock *** transparency not only assists healthcare professionals in comprehending the model’s predictions but also facilitates the integration of our system into existing clinical *** validate the effectiveness of our interpretable models using the same dataset,achieving an impressive accuracy rate exceeding 98%through the application of oversampling *** findings of this study hold significant implications for the advancement of more effective and transparent diagnostic tools in the critical domain of sepsis management.

关键词： Sepsis prediction machine learning cloud computing

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