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A Privacy-Preserving Mechanism Based on Local Differential Privacy in Edge Computing

China Communications 2020年第9期17卷 50-65页

作者： Mengnan Bi Yingjie Wang Zhipeng Cai Xiangrong Tong School of Computer and Control Engineering Yantai UniversityYantai 264005China Department of Computer Science Georgia State UniversityAtlantaGA 30303USA

With the development of Internet of Things(IoT),the delay caused by network transmission has led to low data processing *** the same time,the limited computing power and available energy consumption of IoT terminal devices are also the important bottlenecks that would restrict the application of blockchain,but edge computing could solve this *** emergence of edge computing can effectively reduce the delay of data transmission and improve data processing ***,user data in edge computing is usually stored and processed in some honest-but-curious authorized entities,which leads to the leakage of users’privacy *** order to solve these problems,this paper proposes a location data collection method that satisfies the local differential privacy to protect users’*** this paper,a Voronoi diagram constructed by the Delaunay method is used to divide the road network space and determine the Voronoi grid region where the edge nodes are located.A random disturbance mechanism that satisfies the local differential privacy is utilized to disturb the original location data in each Voronoi *** addition,the effectiveness of the proposed privacy-preserving mechanism is verified through comparison *** with the existing privacy-preserving methods,the proposed privacy-preserving mechanism can not only better meet users’privacy needs,but also have higher data availability.

关键词： Io T edge computing local differential privacy Voronoi diagram privacy-preserving

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The Intelligent Systems of Skin Thickness in Measured by Optical Coherence Tomography

The Intelligent Systems of Skin Thickness in Measured by Opt...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Ardha Ardea Prisilla Mariya Nissar Gilang Titah Ramadhan Wei-Cheng Shen Hsu-Tang Cheng Ben-Yi Liau Yih-Kuen Jan Wen-Hung Chao Chih-Yang Lin Chi-Wen Lung Department of Digital Media Design Asia University Taichung Taiwan Department of Fashion Design LaSalle College Jakarta Jakarta Indonesia Department of Applied Science and Humanities Jamia Millia Islamia New Delhi India Department of Computer Science and Information Engineering Asia University Taichung Taiwan Department of Creative Product Design Asia University Taichung Taiwan Division of Plastic Surgery Asia University Hospital Taichung Taiwan Department of Automatic Control Engineering Feng Chia Asia University Taichung Taiwan Department of Kinesiology and Community Health University of Illinois Urbana USA Department of Mechanical Engineering National Central University Taoyuan Taiwan

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

This study investigates the intelligent systems to evaluate walking interventions on skin thickness using Optical Coherence Tomography (OCT). The walking durations of 10 and 20 min were conducted with participants wearing insoles providing 160 mmHg air pressure. Skin thickness in the stratum corneum (SC) and epidermis (ED) was measured at four-foot regions: the big toe (T1), first metatarsal (M1), second metatarsal (M2), and heel (HL). Results revealed a significant decrease in SC at HL after 20 min of walking. This finding suggests that prolonged walking with air-pressure insoles may reduce mechanical stress at HL and could contribute to preventing and managing diabetic foot ulcers.

关键词： Legged locomotion Optical coherence tomography Optical variables measurement Particle measurements Epidermis Intelligent systems Stress Thickness measurement Stress measurement Foot

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Two Improvements in Grover＇s Algorithm

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电子学报(英文版) 2008年第1期17卷 100-104页

作者： LI Panchi LI Shiyong Department of Control Science and Engineering Harbin Institute of Technology Harbin 150001 China Department of Computer Science and Engineering Daqing Petroleum Institute Daqing 163318 China

When the current Grover algorithm is applied to searching some targets in an unsorted quantum database, the differences of the significance for each target are not taken into consideration. When the targets are more than a quarter of the total items, the probability of finding targets rapidly falls with the increase of the targets, and when the targets are more than half of the total items, the algorithm will be invalidated. Aiming at these problems, firstly, an improvement based on the weighted targets is proposed in which each target is endowed a weight coefficient according to its significance. Using these different weight coefficients, we give a quantum superposition of all target states, which may make the probability for each target equal to its weight coefficient. Secondly, an improved phase matching is proposed in which two directions of phase rotation are same, and two magnitudes are determined by the inner product of the superposition of target states and the initial system state. When this inner product is more than 1/2, using the improved phase matching, The targets can be found with a probability of 100% and by the only one Grover iteration. Finally, the validity of these measures is validated by a simple searching example.

关键词： Grover算法相位匹配量子搜索量子计算

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Automated seizure diagnosis system based on feature extraction and channel selection using EEG signals

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Brain Informatics 2021年第1期8卷 1页

作者： Ein Shoka, Athar A. Alkinani, Monagi H. El-Sherbeny, A.S. El-Sayed, Ayman Dessouky, Mohamed M. Department of Computer Science and Engineering Faculty of Electronic Engineering Menoufia University Menouf Egypt Department of Computer Science and Artificial Intelligence College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf Egypt

Seizure is an abnormal electrical activity of the brain. Neurologists can diagnose the seizure using several methods such as neurological examination, blood tests, computerized tomography (CT), magnetic resonance imaging (MRI) and electroencephalogram (EEG). Medical data, such as the EEG signal, usually includes a number of features and attributes that do not contains important information. This paper proposes an automatic seizure classification system based on extracting the most significant EEG features for seizure diagnosis. The proposed algorithm consists of five steps. The first step is the channel selection to minimize dimensionality by selecting the most affected channels using the variance parameter. The second step is the feature extraction to extract the most relevant features, 11 features, from the selected channels. The third step is to average the 11 features extracted from each channel. Next, the fourth step is the classification of the average features using the classification step. Finally, cross-validation and testing the proposed algorithm by dividing the dataset into training and testing sets. This paper presents a comparative study of seven classifiers. These classifiers were tested using two different methods: random case testing and continuous case testing. In the random case process, the KNN classifier had greater precision, specificity, positive predictability than the other classifiers. Still, the ensemble classifier had a higher sensitivity and a lower miss-rate (2.3%) than the other classifiers. For the continuous case test method, the ensemble classifier had higher metric parameters than the other classifiers. In addition, the ensemble classifier was able to detect all seizure cases without any mistake. © 2021, The Author(s).

关键词： Electroencephalography

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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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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

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Analytic estimation and numerical modeling of actively cooled thermal protection systems with nickel alloys

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Chinese Journal of Aeronautics 2014年第6期27卷 1401-1412页

作者： Wang Xinzhi He Yurong Zheng Yan Ma Junjun H. Inaki Schlaberg School of Energy Science and Engineering Harbin Institute of Technology Shanxi Blower (Group) Company Limited School of Control and Computer Engineering North China Electric Power University

Actively cooled thermal protection system has great influence on the engine of a hypersonic vehicle, and it is significant to obtain the thermal and stress distribution in the system. So an analytic estimation and numerical modeling are performed in this paper to investigate the behavior of an actively cooled thermal protection system. The analytic estimation is based on the electric analogy method and finite element analysis（FEA） is applied to the numerical simulation. Temperature and stress distributions are obtained for the actively cooled channel walls with three kinds of nickel alloys with or with no thermal barrier coating（TBC）. The temperature of the channel wall with coating has no obvious difference from the one with no coating, but the stress with coating on the channel wall is much smaller than that with no coating. Inconel X-750 has the best characteristics among the three Ni-based materials due to its higher thermal conductivity, lower elasticity module and greater allowable stress. Analytic estimation and numerical modeling results are compared with each other and a reasonable agreement is obtained.

关键词： Active cooling Electric analogy method Nickel alloys Thermal barrier coatings Thermal protection systems

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An ammonia coverage ratio observing and trackingcontroller: stability analysis and simulation evaluation

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science China(Information sciences) 2019年第6期62卷 54-71页

作者： Jinghua ZHAO Xun GONG Yunfeng HU Jinwu GAO Hong CHEN State Key Laboratory of Automotive Simulation and Control Jilin University (Campus Nanling) Department of Control Science and Engineering Jilin University (Campus Nanling) Computer College Jilin Normal University

In urea selective catalytic reduction（urea-SCR） systems, the ammonia coverage ratio is an important parameter for satisfying emission regulations. However, this parameter cannot be directly measured by onboard sensors. Most of observers and tracking controllers for the ammonia coverage ratio in the existing literature were designed separately and lacked an overall robustness analysis. In this paper, an observing and tracking controller（AOTC）, along with its overall design and stability analysis, is proposed under inputto-state stability（ISS） theory. The proposed AOTC strategy consists of a sliding mode observer based on NH3concentration dynamics and a tracking controller based on the observer dynamics. The stability is discussed considering the uncertainties about the conversion of urea to NH3and the cross-sensitivity of the NOxsensor, and the principle for adjusting the control parameters is provided. A few transient simulations are conducted to evaluate the effectiveness of the proposed AOTC strategy.

关键词： diesel emission control urea-SCR system nonlinear control sliding mode observer input-to-state stability

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Multi-objective process parameter optimization for energy saving in injection molding process

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Journal of Zhejiang University-science A(Applied Physics & engineering) 2012年第5期13卷 382-394页

作者： Ning-yun LU Gui-xia GONG Yi YANG Jian-hua LU College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing 210016 China Department of Control Engineering and Science Zhejiang University Hangzhou 310027 China School of Computer Science and Engineering Southeast University Nanjing 210096 China

This paper deals with a multi-objective parameter optimization framework for energy saving in injection molding *** combines an experimental design by Taguchi's method,a process analysis by analysis of variance(ANOVA),a process modeling algorithm by artificial neural network(ANN),and a multi-objective parameter optimization algorithm by genetic algorithm(GA)-based lexicographic *** and global Pareto analyses show the trade-off between product quality and energy *** implementation of the proposed framework can reduce the energy consumption significantly in laboratory scale tests,and at the same time,the product quality can meet the pre-determined requirements.

关键词： Injection molding process Energy saving Multi-objective optimization Genetic algorithm Lexicographic method

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Hybrid particle swarm cooperative optimization algorithm and its application to MBC in alumina production

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Progress in Natural science:Materials International 2008年第11期18卷 1423-1428页

作者： Shengli Song~(a,b) Li Kong~a Yong Gan~b Rijian Su~(a,b) a Department of control Scienee and engineering,Huazhong University oF science and Technology,Wuhan 430074,China b College of computer and Communication engineering,Zhengzhou University of Light Industry,Zhengzhou 450002,China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China College of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou 450002 China

An effective hybrid particle swarm cooperative optimization(HPSCO)algorithm combining simulated annealing method and sim- plex method is *** main idea is to divide particle swarm into several sub-groups and achieve optimization through coop- erativeness of different sub-groups among the *** proposed algorithm is tested by benchmark functions and applied to material balance computation(MBC)in alumina *** show that HPSCO,with both a better stability and a steady convergence,has faster convergence speed and higher global convergence ability than the single method and the improved particle swarm optimization *** importantly,results demonstrate that HPSCO is more feasible and efficient than other algorithms in MBC.

关键词： PSO Simulated annealing Simplex Cooperative optimization

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