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Quadratic stabilisation of switched affine systems

Journal of Control and Decision 2020年第1期7卷 1-23页

作者： Minqing Xiao Guisheng Zhai Chi Huang College of Mathematics and Informatics Fujian Key Laboratory of Mathematical Analysis and ApplicationFujian Normal UniversityFuzhouPeople’s Republic of China Department of Mathematical Sciences College of Systems Engineering and ScienceShibaura Institute of TechnologyTokyoJapan Department of Computer Science and Technology School of Economic Information EngineeringSouthwestern University of Finance and EconomicsChengduPeople’s Republic of China

Minqing Xiao received the *** from Chongqing University,Chongqing,China,in *** is currently a Professor with the College of Mathematics and Informatics,Fujian Normal University,Fuzhou,*** current research interests include robust control/filter theory,delta operator systems,networked control systems,and switched systems;Guisheng Zhai received his *** from Fudan University,China,in 1988,and he received his *** ***,both in system science,from Kobe University,Japan,in 1993 and 1996,*** two years of industrial experience,*** moved to Wakayama University,Japan,in 1998,and then to Osaka Prefecture University,Japan,in *** held visiting professor positions at University of Notre Dame from August 2001 to July 2002,and at Purdue University from March 2016 through February *** April 2010,he joined the faculty board of Shibaura Institute of technology,Japan,where he currently is a full Professor of Mathematical *** research interests include large scale and decentralised control systems,robust control,switched systems and switching control,networked control and multi-agent systems,neural networks and signal processing,*** is on the editorial board of several academic journals including IET Control Theory&applications,International Journal of Applied Mathematics and computer science,Journal of Control and Decision,and Frontiers of Mechanical *** is a Senior Member of IEEE,a member of ISCIE,SICE,JSST and JSME.

关键词： Switched affine systems(SAS) switched uncertain affine systems(SUAS) quadratic stabilisation convex combination state-dependent switching output-dependent switching convergence set LMIs norm bounded uncertainties

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A Multi-Task Based Deep Learning Framework for MRI Couinaud Segmentation

SSRN

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SSRN 2023年

作者： Miao, Dong Zhao, Ying Ren, Xue Dou, Meng Yao, Yu Xu, Yiran Cui, Yingchao Liu, Ailian Chengdu Institute of Computer Application Chinese Academy of Sciences Sichuan Chengdu610200 China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing101408 China Department of Radiology The First Affiliated Hospital of Dalian Medical University Liaoning Dalian116000 China Dalian Engineering Research Center for Artificial Intelligence in Medical Imaging Liaoning Dalian116000 China School of Medical Imaging Dalian Medical University Liaoning Dalian116044 China

Bacground and Objectibve: The delineation of the liver into Couinaud segments constitutes an essential aspect of preoperative planning in hepatic surgery, given its complexity and the significantBacground and Objectibve: The delineation of the liver into Couinaud segments constitutes an essential aspect of preoperative planning in hepatic surgery, given its complexity and the significant anatomical variations present. Accurate segmentation underpins the customization of operative techniques, critically influencing the minimization of postoperative complications and the preservation of liver ***: This research introduces a novel approach to automating this segmentation by identifying seven key landmarks within the liver anatomy using portal venous phase images of contrast enhanced magnetic resonance imaging (CE-MRI). Through a multi-task learning framework, we synchronized the detection of landmarks with the segmentation process, which led to an accurate and robust delineation of the Couinaud ***: To validate the capability of our model comprehensively, we included a test dataset with multiple patient types—those with normal liver, diffuse liver diseases, and localized liver lesions—under varied imaging conditions encompassing two field strengths, two devices, and two contrast agents. Our model achieved an average Dice Similarity Coefficient (DSC) of 85.29%, which is 3.12% higher than the other best-performing ***: In conclusion, our research presents a pioneering automated approach for segmenting the liver into Couinaud segments through CE-MRI, correlating landmark detection with segmentation to enhance surgical planning precision. This method promises improved clinical outcomes by accurately adapting to anatomical variability and reducing potential postoperative complications anatomical variations present. © 2023, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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Latent Regression and Ordination Risk of Infectious Disease and Climate

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Procedia computer science 2021年 179卷 25-32页

作者： Rezzy Eko Caraka Rung Ching Chen Youngjo Lee Prana Ugiana Gio Arif Budiarto Bens Pardamean College of Informatics Chaoyang University of Technology 168 Jifong East Road Wufong Dist. Taichung City 41349 Taiwan (R.O.C.). Department of Statistics College of Natural Science Seoul National University Gwanak-gu Seoul 08826 Korea Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Department of Mathematics Universitas Sumatera Utara Medan 20222 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Indonesia.

Global warming arising from climate change can increase the spread of deadly diseases. Effort is needed to develop a set of policies for the government to stem or reduce health risks from global warming. The purpose of this paper is to examine more detail and comprehensively about the relationship among climate and event disease count in Taiwan using the partial least square latent regression model. The results obtained that of the 17 types of diseases in Taiwan, that has the most significant loading factor is Amoebiasis, Malaria and Chikungunya. At the same time, climate variables that have the biggest most significant factor are Number day with max temp more than 30, Number day Temp more than 25, and Rainfall PH. Cronbach’s Alpha infectious disease 0.9696 and climate 0.2813. At the same time, the value of Dillon Goldstein’s rho infectious disease 0.974 and climate 0.6404, respectively.

关键词： Disease Counts Climate Latent PLS Regression

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Digital Forensics Investigation and Incident Response in Internet of Things (IoT-DFIR): Challenges and Models 9

Digital Forensics Investigation and Incident Response in Int...

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9th International Conference on Wireless and Telematics, ICWT 2023

作者： Ahdan, Syaiful Zaki Hamidi, Eki Ahmad Riskiono, Sampurna Dadi Negara, Ridha Muldina Mayasari, Ratna Ramadona, Suci Nurhayati, Ade Sucipto, Adi Jupriyadi Nurkahfi, Galih Nugraha Farahiyah, Dzata Naseer, Muchammad Universitas Teknokrat Indonesia Faculty of Engineering & Computer Science Lampung35132 Indonesia Uin Sunan Gunung Djati Bandung Electrical Engineering Department Bandung40614 Indonesia School of Electrical Engineering Telkom University Bandung40257 Indonesia Elearical Engineering Study Program Politeknik Caltex Riau Riau28265 Indonesia Institut Teknologi Telkom Jakarta Faculty of Engineering Jakarta11710 Indonesia Bandung40135 Indonesia Universitas Islam Indonesia Yogyakarta Faculty of Industrial Technology Yogyakarta55584 Indonesia Sekolah Tinggi Teknologi Bandung Informatics Department Bandung40235 Indonesia

ISBN: (纸本)9798350305029

Many different industries are currently making substantial use of the Internet of Things (IoT). IoT is the process through which electronic devices communicate with their surrounding virtual environment by continuously exchanging data via sensors. Due to increased IoT security concerns, digital forensic investigators now possess greater knowledge and abilities to investigate IoT devices. IoT-DigFor are required in terms of cybercrime due to the rapid growth in the number of electronic devices and the collection and consumption of enormous amounts of data. IoT systems with billions of devices have produced a significant amount of evidence, which presents a significant challenge to digital investigators and practitioners who must connect with IoT devices to conduct fast and thorough investigations into cybercrimes. This article presents detailed information about forensics in the IoT environment. The IoT forensic paradigm and the challenges that design-based security requirements and IoT system security offer for IoT-DigFor are covered in great detail at the beginning of the article. © 2023 IEEE.

关键词： Internet of things

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CONVERGENCE SPEED AND APPROXIMATION ACCURACY OF NUMERICAL MCMC

arXiv

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arXiv 2022年

作者： Cui, Tiangang Dong, Jing Jasra, Ajay Tong, Xin T. School of Mathematics Monash University Australia Graduate School of Business Columbia University United States Applied Mathematics and Computational Science Program Computer Electrical Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Saudi Arabia Department of Mathematics National University of Singapore Singapore

When implementing Markov Chain Monte Carlo (MCMC) algorithms, perturbation caused by numerical errors is sometimes inevitable. This paper studies how perturbation of MCMC affects the convergence speed and Monte Carlo estimation accuracy. Our results show that when the original Markov chain converges to stationarity fast enough and the perturbed transition kernel is a good approximation to the original transition kernel, the corresponding perturbed sampler has similar convergence speed and high approximation accuracy as well. We discuss two different analysis frameworks: ergodicity and spectral gap, both are widely used in the literature. Our results can be easily extended to obtain non-asymptotic error bounds for MCMC estimators. We also demonstrate how to apply our convergence and approximation results to the analysis of specific sampling algorithms, including Random walk Metropolis and Metropolis adjusted Langevin algorithm with perturbed target densities, and parallel tempering Monte Carlo with perturbed densities. Finally we present some simple numerical examples to verify our theoretical claims. Copyright © 2022, The Authors. All rights reserved.

关键词： Inverse problems

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Accessible Authentication Using Keyword Search through Homomorphic Encryption

Accessible Authentication Using Keyword Search through Homom...

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Interdisciplinary Humanitarian Conference for Sustainability (IIHC), International

作者： Vipul Vekariya Manjunath. R Jasmeen Gill M Gopianand Avneesh Kumar Amaresh Jha Department of CSE PIET Parul University Vadodara Gujarat India Department of Data Science & Mathamatics Jain (Deemed to be University) Bangalore India Department of CSE RIMT University Mandi Godindgarh India Department of Computer Applications PSNA College of Engineering and Technology Dindigul Department of Computer Application Galgotias University Greater Noida Uttar Pradesh India School of Modern Media UPES Dehradun

Data storage presents substantial issues due to concerns about data security and privacy. In this study, we provide a search-based, interoperable, verified public key cryptography system. The searchability is significantly improved by our recommended method, which allows the cloud servers to create invert crypto indexes while needing a query trap and leveraging asymmetric cryptography developed by van Vries, Miller, Showing different, and Vaikuntanathan. Contrarily, the recommended method offers a brand-new permitted dataset built on the inversion decryption scheme and shows how it may be used to evaluate the thoroughness and correctness of serps. Additionally, using the provided method, many users may do encrypted searches on cryptography. Finally, it is shown that the offered technique is secure utilizing the approximate-GCD problem. The experiment's results showed that the proposed technique had less computational complexity than the methods currently in use.

关键词： Data privacy Runtime Keyword search Memory Public key cryptography Generators Servers

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Correction: Shielding effectiveness performance of polyaniline-NiFe2O4:Cu composites for sub-8 GHz applications

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Optical and Quantum Electronics 2023年第9期55卷 1-2页

作者： Şahin, Ethem İlhan Emek, Mehriban Ibrahim, Jamal Eldin F. M. Yumuşak, Görkem Kartal, Mesut Advanced Technology Research and Application Center Adana Alparslan Türkeş Science and Technology University Adana Turkey Department of Physics Computer Technologies Golbasi Vocational School Adiyaman University Gölbaşi Adıyaman Turkey Department of Materials Technology University of Bahri Khartoum Sudan Institute of Ceramic and Polymer Engineering University of Miskolc Egyetemvaros Miskolc Hungary Department of Metallurgical and Materials Engineering Marmara University Göztepe Istanbul Turkey Department of Electronics and Communication Engineering İstanbul Technical University Maslak Istanbul Turkey

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Mathematical representation of emotion using multimodal recognition model with deep multitask learning

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2020年第12期140卷 1343-1351页

作者： Harata, Seiichi Sakuma, Takuto Kato, Shohei Computer Science Program Department of Engineering Graduate School of Engineering Nagoya Institute of Technology Gokiso-cho Showa-ku Nagoya-city Aichi466-8555 Japan Frontier Research Institute for Information Science Nagoya Institute of Technology Gokiso-cho Showa-ku Nagoya-city Aichi466-8555 Japan

To emulate human emotions in robots, the mathematical representation of emotion is important for each component of affective computing, such as emotion recognition, generation, and expression. In a method that learns DNN from unimodality and represents emotions by vectors of continuous values (Emotional Space), the acquired Emotional Space is likely to depend on the modality, and considering the number of dimensions of Emotional Space is necessary. In this study, we aim at the acquisition of modality independent Emotional Space. We propose a method of acquiring Emotional Space by integrating multimodalities on a DNN and combining the emotion recognition task and unification task of Emotional Space of each modality. Through the experiments with audio-visual data, we confirmed in various dimensions of Emotional Space that there are differences in Emotional Space acquired from unimodality, and the proposed method can acquire a modality independent Emotional Space. We also investigated the compatibility of the recognition and the unification score by changing the number of dimensions of Emotional Space. Finally, we indicate the proposed method can acquire sufficient Emotional Space with a small number of dimensions, such as five or six dimensions, under this paper's experimental conditions. © 2020 The Institute of Electrical Engineers of Japan.

关键词： Deep neural networks

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CKD-TransBTS: Clinical Knowledge-Driven Hybrid Transformer with Modality-Correlated Cross-Attention for Brain Tumor Segmentation

arXiv

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arXiv 2022年

作者： Lin, Jianwei Lin, Jiatai Lu, Cheng Chen, Hao Lin, Huan Zhao, Bingchao Shi, Zhenwei Qiu, Bingjiang Pan, Xipeng Xu, Zeyan Huang, Biao Liang, Changhong Han, Guoqiang Liu, Zaiyi Han, Chu The School of Computer Science and Engineering South China University of Technology Guangzhou510006 China The Department of Radiology Guangdong Provincial People’s Hospital Guangdong Academy of Medical Sciences Guangzhou510080 China Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application Guangdong Provincial People’s Hospital Guangdong Academy of Medical Sciences Guangzhou510080 China The Department of Computer Science and Engineering The Hong Kong University of Science and Technology Clear Water Bay Hong Kong

Brain tumor segmentation (BTS) in magnetic resonance image (MRI) is crucial for brain tumor diagnosis, cancer management and research purposes. With the great success of the ten-year BraTS challenges as well as the advances of CNN and Transformer algorithms, a lot of outstanding BTS models have been proposed to tackle the difficulties of BTS in different technical aspects. However, existing studies hardly consider how to fuse the multi-modality images in a reasonable manner. In this paper, we leverage the clinical knowledge of how radiologists diagnose brain tumors from multiple MRI modalities and propose a clinical knowledge-driven brain tumor segmentation model, called CKD-TransBTS. Instead of directly concatenating all the modalities, we re-organize the input modalities by separating them into two groups according to the imaging principle of MRI. A dual-branch hybrid encoder with the proposed modality-correlated cross-attention block (MCCA) is designed to extract the multi-modality image features. The proposed model inherits the strengths from both Transformer and CNN with the local feature representation ability for precise lesion boundaries and long-range feature extraction for 3D volumetric images. To bridge the gap between Transformer and CNN features, we propose a Trans&CNN Feature Calibration block (TCFC) in the decoder. We compare the proposed model with five CNN-based models and six transformer-based models on the BraTS 2021 challenge dataset. Extensive experiments demonstrate that the proposed model achieves state-of-the-art brain tumor segmentation performance compared with all the competitors. © 2022, CC BY.

关键词： Brain

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Cyber-Physical Threat Identification for Smart Systems

Cyber-Physical Threat Identification for Smart Systems

引用

Communication, Computing and Energy Efficient Technologies (I3CEET), International Conference on

作者： Kumaran U J. Angeljulie Yogendra Kumar Madhav Dua Anita Soni Mohammed I. Habelalmateen Department of CSE Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Department of Cyber Security Karpagam Academy of Higher Education Coimbatore Department of Electrical Engineering GLA University Mathura India Department of Computer Application Chandigarh Engineering College Chandigarh Group of Colleges Mohali Punjab India Department of Computer Science & Engineering IES Institute of Technology and Management IES University Bhopal M.P. India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Computers Techniques Engineering College of Technical Engineering The Islamic University of Al Diwaniyah Al Diwaniyah Iraq

ISBN: (数字)9798331541583

ISBN: (纸本)9798331541590

The constantly evolving nature of technology, the discovery of new vulnerabilities that are frequently disregarded, the variety of ways that users use their devices and perceive the threat of cyberattacks make today's Internet of Things (IoT)-based connected home challenging to secure. It's also possible for there to be a physical space breach, similar to one that occurs over the phone. Its effects are not limited to the internet. 8 In this situation, intrusion detection cannot rely only on validated models that are consistent across time and applicable to all users. 10 Introducing MAGPIE, the first intrusion detection system designed with smart homes in mind. It can automatically adjust its decision function based on anomaly classification models to a range of scenarios that may occur in a smart home, including the addition of new devices, the automation of rules, and human interaction. This is achieved by combining non-stationary multi-armed pirate reinforcement learning with a novel statistical cluster-based adjustment method. 17. MAGPIE assigns the sets of hyper parametric parameters of the underlying 18 isolation forest nonlinear anomaly classifiers based on the 19 cluster profile scores of its output. The outcomes of an experimental assessment carried out in a real home show that MAG21 PIE has remarkable accuracy because of two more innovations: it applies the models that show the highest level of precision in each scenario by taking into account data from both virtual and physical sources and by detecting human presence. Since the assessment datasets and the software are publicly available, MAGPIE may benefit from future advancements in autonomous and reinforcement learning technology. It may also be updated utilizing other data sources in the case that attacks and intelligent home settings change.

关键词： Technological innovation Accuracy Soft sensors Intrusion detection Reinforcement learning Smart homes TCPIP Smart systems Data models Telecommunication computing

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