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Delivering Improved Care through Remote Health Monitoring Systems by Using Microservices. Case Study: Fall Detection Encompassed into Connected Care

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Delivering Improved Care through Remote Health Monitoring Sy...

International Conference on control Systems and Computer Science (CSCS)

作者： Marilena Ianculescu Adriana Alexandru Ionuţ-Emanuel Giura Ana-Mihaela Vasilevschi Communication Digital Applications and Systems Department National Institute for Research and Development in Informatics Bucharest Romania Doctoral School of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania Counselors Department National Institute for Research and Development in Informatics Târgovişte Romania Faculty of Electrical Engineering Electronics and Information Technology Târgovişte Romania Valahia University of Târgovişte Târgovişte Romania

Based on today’s modern technologies, patient care can be provided remotely, in a connected way, being, at the same time, personalized, patient-centered and proactive. Such an approach can be achieved using Remote Health Monitoring Systems (RHMS). In case of elderly people, dramatic permanent deteriorations of their health status can be caused by falls. The seniors’ health and life style monitoring and the detection and/or prevention of falls can be done by such RHMS, an example being the RO-SmartAgeing system developed inside “Non-invasive Monitoring System and Health Assessment of the Elderly in a Smart Environment (RO-SmartAgeing)” research project. The paper presents the problem of using microservices for optimizing the architecture and functionalities of RO-SmartAgeing system, and the way in which the problems of ensuring the security of patient data can be solved.

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Semi-Global Consensus Problems of Discrete-Time Multi-Agent Systems in the Presence of Input Constraints

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Journal of Shanghai Jiaotong university(Science) 2020年第3期25卷 288-298页

作者： WANG Jian SHI Liangren Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China Shanghai Key Laboratory of Navigation and Location-Based Services Shanghai Jiao Tong UniversityShanghai 200240China Academy of Information Technology and Electrical Engineering Shanghai Jiao Tong UniversityShanghai 200240China

This paper studies the consensus problems of the discrete-time multi-agent systems (MASs) in the presence of input saturation constraints over directed communication *** kinds of consensus problems,of the leaderless consensus problem with no leader agent and the containment control problem with multiple leader agents,are investigated in this *** gain feedback consensus algorithms based on the improved discretetime parametric algebraic Riccati equation (ARE) are proposed to solve the consensus *** the MAS without any leader,the trajectories of all agents converge together when the communication networks contain a directed spanning *** the MAS with multiple leaders,the trajectories of all follower agents converge to the convex hull spanned by the leader agents when there is at least one leader agent which is trackable for each follower *** examples are provided to verify the theoretical results.

关键词： leaderless consensus containment control discrete-time low gain input saturation

Unveiling the Ultimate Radiation- and Corrosion-Resistant Cr-Based Coatings Through Structured Regulation and Optimized Composition

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SSRN

SSRN 2023年

作者： Wang, Renda Daghbouj, Nabil Yu, Ping Li, Peng Meng, Fanping Cammarata, Antonio Li, Bingsheng Polcar, Tomas Zhang, Xinghang Huang, Qing Ge, Fangfang Engineering Laboratory of Advanced Energy Materials Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China Department of Control Engineering Faculty of Electrical Engineering Czech Technical University in Prague Technická 2 Prague 6160 00 Czech Republic School of Electronics and Information Engineering Ningbo University of Technology Ningbo315211 China University of Chinese Academy of Sciences Beijing100049 China Advanced Energy Science and Technology Guangdong Laboratory Huizhou516000 China State Key Laboratory for Environment-friendly Energy Materials Southwest University of Science and Technology Mianyang621010 China School of Materials Engineering Purdue University West LafayetteIN47907 United States

Advanced materials capable of withstanding high radiation levels at elevated temperatures are essential for the development of next-generation fission and future fusion energy technologies. However, current structural materials, despite their potential, deteriorate under the harsh radiation environment, leading to irreversible microstructure degradation. In this context, we have designed CrAlSiN, which features a vein-like nanochannel structure embedded within amorphous layers. We subjected this material to helium (He) irradiation, followed by annealing and oxidation processes. Under extreme conditions, this composition demonstrates the absence of bubble formation, negligible hardening, exceptional thermal stability, and oxidation resistance. Through density functional theory (DFT) simulations, we have clarified that the improved radiation tolerance is primarily attributed to the presence of nitrogen (N) atoms. These N atoms facilitate a significant rearrangement of ions surrounding vacancies, leading to the formation of new bonds with N atoms. This phenomenon preserves the vein-like structure and results in the elimination of vacancies. Consequently, this mechanism prevents the formation of sites that could trap He atoms. These findings provide the groundwork for a conceptual framework that paves the way for designing the next generation of structural alloys engineered to exhibit enhanced radiation tolerance. © 2023, The Authors. All rights reserved.

关键词： Oxidation resistance

Radiomics model based on computed tomography images for prediction of radiation-induced optic neuropathy following radiotherapy of brain and head and neck tumors

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Heliyon 2025年第1期11卷 e41409页

作者： Nafchi, Elham Raiesi Fadavi, Pedram Amiri, Sepideh Cheraghi, Susan Garousi, Maryam Nabavi, Mansoureh Daneshi, Iman Gomar, Marzieh Molaie, Malihe Nouraeinejad, Ali Department of Radiation Sciences Faculty of Allied Medicine Iran University of Medical Sciences Tehran Iran Department of Radiation Oncology School of Medicine Iran University of Medical Science Tehran Iran Department of Information Technology Faculty of Electrical and Computer Engineering University of Tehran Tehran Iran Radiation Biology Research Center Iran University of Medical Sciences Tehran Iran Radiation Oncology Research Center (RORC) Cancer Institute Tehran University of Medical Sciences Tehran Iran Department of Clinical Oncology Haft-e-Tir Hospital Iran University of Medical Science Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Department of Optometry and Vision Science School of Rehabilitation Tehran University of Medical Science Tehran Iran

Purpose: We aimed to build a machine learning-based model to predict radiation-induced optic neuropathy in patients who had treated head and neck cancers with radiotherapy. Materials and methods: To measure radiation-induced optic neuropathy, the visual evoked potential values were obtained in both case and control groups and compared. Radiomics features were extracted from the area segmented which included the right and left optic nerves and chiasm. We integrated CT image features with dosimetric and clinical data subsequently, ranked 5 supervised ML models Bernoulli Naive Bayes, Decision Tree, Gradient Boosting Decision Trees, K-Nearest Neighbor, and Random Forest on 4 input datasets to predict radiation-induced visual complications classifiers by implementing 5-fold cross-validation. The F1 score, accuracy, sensitivity, specificity, and area under the ROC curve were compared to access prediction capability. Results: radiation-induced optic neuropathy affected 31 % of the patients. 856 radiomic characteristics were extracted and selected from each segmented area. Decision Tree and Random Forest with the highest AUC (97 % and 95 % respectively) among the five classifiers were the most powerful algorithms to predict radiation-induced optic neuropathy. Chiasm with higher sensitivity and precision was able to predict radiation-induced optic neuropathy better than right or left optic nerve or combination of all radiomic features. Conclusion: We found that combination of radiomic, dosimetric, and clinical factors can predict radiation-induced optic neuropathy after radiation treatment with high accuracy. To acquire more reliable results, it is recommended to conduct visual evoked potential tests before and after radiation therapy, with multiple follow-up courses and more patients. © 2024 The Authors

关键词： Computed tomography Machine learning Radiation-induced optic neuropathy Radiomics Visual evoked potential

Krasovskii and Shifted Passivity Based Output Consensus

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arXiv 2022年

作者： Kawano, Yu Cucuzzella, Michele Feng, Shuai Scherpen, Jacquelien M.A. Graduate School of Advanced Science and Engineering Hiroshima University Higashi-Hiroshima739-8527 Japan Department of Electrical Computer and Biomedical Engineering University of Pavia PV Pavia27100 Italy School of Automation Nanjing University of Science and Technology Nanjing210094 China Jan C. Willems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Groningen9747 AG Netherlands

Motivated by current sharing in power networks, we consider a class of output consensus (also called agreement) problems for nonlinear systems, where the consensus value is determined by external disturbances, e.g., power demand. This output consensus problem is solved by a simple distributed output feedback controller if a system is either Krasovskii or shifted passive, which is the only essential requirement. The effectiveness of the proposed controller is shown in simulation on an islanded DC power network. Copyright © 2022, The Authors. All rights reserved.

关键词： Nonlinear systems

Three-dimensional solitons in Rydberg-Dressed cold atomic gases with spin-orbit coupling

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arXiv 2023年

作者： Zhao, Yuan Hu, Heng-Jie Zhou, Qian-Qian Qiu, Zhang-Cai Xue, Li Xu, Si-Liu Zhou, Qin Malomed, Boris A. Laboratory of Optoelectronic Information and Intelligent Control Hubei University of Science and Technology Xianning437100 China School of Biomedical Engineering and Medical Imaging Xianning Medical College Hubei University of Science and Technology Xianning437100 China School of Electronic and Information Engineering Hubei University of Science and Technology Xianning437100 China Research Center of Nonlinear Science School of Mathematical and Physical Sciences Wuhan Textile University Wuhan430200 China Department of Physical Electronics School of Electrical Engineering Faculty of Engineering Tel Aviv Univesity P.O.B. 39040 Ramat Aviv Tel Aviv Israel Instituto de Alta Investigación Universidad de Tarapacá Casilla 7D Arica Chile

We present numerical results for three-dimensional (3D) solitons with symmetries of the semi-vortex (SV) and mixed-mode (MM) types, which can be created in spinor Bose-Einstein condensates of Rydberg atoms under the action of the spin-orbit coupling (SOC). By means of systematic numerical computations, we demonstrate that the interplay of SOC and long-range spherically symmetric Rydberg interactions stabilize the 3D solitons, improving their resistance to collapse. We find how the stability range depends on the strengths of the SOC and Rydberg interactions and the soft-core atomic radius. Copyright © 2023, The Authors. All rights reserved.

关键词： Solitons

Quantized Distributed Gradient Tracking Algorithm with Linear Convergence in Directed Networks

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arXiv 2021年

作者： Xiong, Yongyang Wu, Ligang You, Keyou Xie, Lihua The Department of Automation Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China The Department of Control Science and Engineering Harbin Institute of Technology Harbin150001 China The School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore

Communication efficiency is a major bottleneck in the applications of distributed networks. To address the problem, the problem of quantized distributed optimization has attracted a lot of attention. However, most of the existing quantized distributed optimization algorithms can only converge sublinearly. To achieve linear convergence, this paper proposes a novel quantized distributed gradient tracking algorithm (Q-DGT) to minimize a finite sum of local objective functions over directed networks. Moreover, we explicitly derive lower bounds for the number of quantization levels, and prove that Q-DGT can converge linearly even when the exchanged variables are respectively quantized with 3 quantization levels. Numerical results also confirm the efficiency of the proposed algorithm. Copyright © 2021, The Authors. All rights reserved.

关键词： Efficiency

Characterization of State-Preparation Uncertainty in Quantum Key Distribution

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Physical Review Applied 2023年第1期19卷 014048-014048页

作者： Anqi Huang Akihiro Mizutani Hoi-Kwong Lo Vadim Makarov Kiyoshi Tamaki Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha 410073 People’s Republic of China Graduate School of Engineering Science Osaka University Toyonaka Osaka 560-8531 Japan Department of Electrical & Computer Engineering and Department of Physics Centre for Quantum Information and Quantum Control (CQIQC) University of Toronto Toronto Ontario M5S 3G4 Canada Department of Physics University of Hong Kong Pokfulam Hong Kong Quantum Bridge Technologies Inc. 100 College Street Toronto Ontario M5G 1L5 Canada Russian Quantum Center Skolkovo Moscow 121205 Russia Shanghai Branch National Laboratory for Physical Sciences at Microscale and CAS Center for Excellence in Quantum Information University of Science and Technology of China Shanghai 201315 People’s Republic of China NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow 119049 Russia Faculty of Engineering University of Toyama Gofuku 3190 Toyama 930-8555 Japan

To achieve secure quantum key distribution, all imperfections in the source unit must be incorporated in a security proof and measured in the lab. Here we perform a proof-of-principle demonstration of the experimental techniques for characterizing the source phase and intensity fluctuation in commercial quantum key distribution systems. When we apply the measured phase-fluctuation intervals to the security proof that takes into account fluctuations in the state preparation, it predicts a key distribution distance of over 100km of fiber. The measured intensity fluctuation intervals are, however, so large that the proof predicts zero key, indicating a source improvement may be needed. Our characterization methods pave the way for a future certification standard.

关键词： Fluctuations & noise Optical quantum information processing Quantum cryptography Quantum engineering Quantum state engineering

CVM-Cervix: A Hybrid Cervical Pap-Smear Image Classification Framework Using CNN, Visual Transformer and Multilayer Perceptron

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arXiv 2022年

作者： Liu, Wanli Li, Chen Xu, Ning Jiang, Tao Rahaman, Md Mamunur Sun, Hongzan Wu, Xiangchen Hu, Weiming Chen, Haoyuan Sun, Changhao Yao, Yudong Grzegorzek, Marcin Microscopic Image and Medical Image Analysis Group College of Medicine and Biological Information Engineering Northeastern University Shenyang China Liaoning Petrochemical University Fushun China School of Control Engineering Chengdu University of Information Technology Chengdu China Shengjing Hospital China Medical University Shenyang China Suzhou Ruiqian Technology Company Ltd. Suzhou China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Department of Electrical and Computer Engineering Stevens Institute of Technology Hoboken United States Institute of Medical Informatics University of Luebeck Luebeck Germany

Cervical cancer is the seventh most common cancer among all the cancers worldwide and the fourth most common cancer among women. Cervical cytopathology image classification is an important method to diagnose cervical cancer. Manual screening of cytopathology images is time-consuming and error-prone. The emergence of the automatic computer-aided diagnosis system solves this problem. This paper proposes a framework called CVM-Cervix based on deep learning to perform cervical cell classification tasks. It can analyze pap slides quickly and accurately. CVM-Cervix first proposes a Convolutional Neural Network module and a Visual Transformer module for local and global feature extraction respectively, then a Multilayer Perceptron module is designed to fuse the local and global features for the final classification. Experimental results show the effectiveness and potential of the proposed CVM-Cervix in the field of cervical Pap smear image classification. In addition, according to the practical needs of clinical work, we perform a lightweight post-processing to compress the model. Copyright © 2022, The Authors. All rights reserved.

关键词： Image classification