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IEEE Networking Letters 2021年第3期3卷 138-141页

作者： Chiang, Yi-Han Zhu, Chao Lin, Hai Ji, Yusheng Department of Electrical and Information Systems Osaka Prefecture University Osaka599-8531 Japan School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China Information Systems Architecture Science Research Division National Institute of Informatics Tokyo101-8430 Japan

Keeping containers warm for prompt service responses and reducing warm containers for light-weight system management exhibit a fundamental tradeoff in serverless computing systems. In this letter, we investigate the problem of container warming control for serverless computing, and we formulate it as a Markov decision process (MDP). By observing that the value functions corresponding to the MDP are partially submodular, we show that the derived optimal policy is hysteretic and partially non-decreasing. Our numerical results show that the derived optimal policy exhibits a hysteretic structure, which can be realized via switching-up/-down thresholds in practice. © 2019 IEEE.

关键词： Hysteresis

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Prognostic Kalman Filter Based Bayesian Learning Model for Data Accuracy Prediction

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Computers, Materials & Continua 2022年第7期72卷 243-259页

作者： S.Karthik Robin Singh Bhadoria Jeong Gon Lee Arun Kumar Sivaraman Sovan Samanta A.Balasundaram Brijesh Kumar Chaurasia S.Ashokkumar Department of ECE College of Engineering and TechnologySRM Institute of Science and TechnologyVadapalaniChennai600026India Department of CSE Birla Institute of Applied Sciences(BIAS)BhimtalUttarakhand263136India Division of Applied Mathematics Wonkwang University460Iksan-DaeroIksan-SiJeonbuk54538Korea School of Computer Science and Engineering Vellore Institute of Technology(VIT)Chennai600127India Department of Mathematics Tamralipta MahavidyalayaWest Bengal721636India School of Computer Science and Engineering Center for Cyber Physical SystemsVellore Institute of Technology(VIT)Chennai600127India Indian Institute of Information Technology(IIIT) LucknowUttar Pradesh226002India Department of Computer Science and Engineering Saveetha School of EngineeringSIMATSChennai602105India

Data is always a crucial issue of concern especially during its prediction and computation in digital *** paper exactly helps in providing efficient learning mechanism for accurate predictability and reducing redundant data *** also discusses the Bayesian analysis that finds the conditional probability of at least two parametric based predictions for the *** paper presents a method for improving the performance of Bayesian classification using the combination of Kalman Filter and *** method is applied on a small dataset just for establishing the fact that the proposed algorithm can reduce the time for computing the clusters from *** proposed Bayesian learning probabilistic model is used to check the statistical noise and other inaccuracies using unknown *** scenario is being implemented using efficient machine learning algorithm to perpetuate the Bayesian probabilistic *** also demonstrates the generative function forKalman-filer based prediction model and its *** paper implements the algorithm using open source platform of Python and efficiently integrates all different modules to piece of code via Common Platform Enumeration(CPE)for Python.

关键词： Bayesian learning model kalman filter machine learning data accuracy prediction

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Absolute longitudinal distance measurement verification of a standard polystyrene nanoparticle near a surface in water by means of multi-wavelength evanescent field 22

Absolute longitudinal distance measurement verification of a...

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22nd International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2022

作者： Blattler, Aran Khajornrungruang, Panart Suzuki, Keisuke Baba, Akiyoshi Goto, Daiki Graduate School of Computer Science and System Engineering Mechanical Information Science and Technology Course Kyushu Institute of Technology Fukuoka Japan Department of Intelligent and Control Systems Advanced Mechanical Division Kyushu Institute of Technology Fukuoka Japan Center of Microelectronic System Kyushu Institute of Technology Fukuoka Japan School of Computer Science and System Engineering Advanced Mechanical Course Kyushu Institute of Technology Fukuoka Japan

ISBN: (纸本)9781998999118

In the wet semiconductor process, abrasive nanoparticles are widely used in the chemical mechanical polishing (CMP) process to polish wafer surfaces for high planarization. During polishing, nanoparticles move with a high-speed three-dimensional (3D) position in the solution. In the 3D particles's moving positions, Z is a perpendicular longitudinal distance between the surface to the nanoparticle that plays a significant role in polishing, which could not be measured by general microscopy without longitudinal scanning. To understand nanoparticle phenomena near-surface, we have proposed and developed the apparatus with real-time fastmotion tracking on optical multi-wavelength evanescent fields microscopy to measure the 3D motion of the nanoparticle in water without scanning. In euspen's 2020, we could verify the relative distance ?Z of nanoparticles in water, but the absolute distance Z is unknown yet. In this manuscript, we have therefore developed an invisible nano-step height in water to verify the absolute height Z of an individual nanoparticle. The invisible nano-step height in water is made from an optical resin with a refractive index of 1.35 that is close to a refractive index of water to avoid unnecessary light during experimental verification. The nano-step height was less than 100 nm on a glass surface, fabricated using nanoimprint lithography. Polystyrene f100 nm standard particles in water were used to verify the height Z. The results of height Z of nanoparticles could be measured less than 100 nm with the measurement uncertainty ±10 nm (2s), which is related to the interferometer result of the nano-step height. © European Society for Precision Engineering and Nanotechnology, Conference Proceedings - 22nd International Conference and Exhibition, EUSPEN 2022. All rights reserved.

关键词： Nanoparticles

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Safe Optimal Interactions Between Automated and Human-Driven Vehicles in Mixed Traffic with Event-Triggered Control Barrier Functions

Safe Optimal Interactions Between Automated and Human-Driven...

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American Control Conference (ACC)

作者： Anni Li Christos G. Cassandras Wei Xiao Division of Systems Engineering and Center for Information and Systems Engineering Boston University Brookline MA Computer Science and Artificial Intelligence Lab Massachusetts Institute of Technology

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper studies safe driving interactions between Human-Driven Vehicles (HDVs) and Connected and Automated Vehicles (CAVs) in mixed traffic where the dynamics and control policies of HDVs are unknown and hard to predict. In order to address this challenge, we employ event-triggered Control Barrier Functions (CBFs) to estimate the HDV model online, construct data-driven and state-feedback safety controllers, and transform constrained optimal control problems for CAVs into a sequence of event-triggered quadratic programs. We show that we can ensure collision-free interactions between HDVs and CAVs and demonstrate the robustness and flexibility of our framework on different types of human drivers in lane-changing scenarios while guaranteeing the satisfaction of safety constraints.

关键词： Road transportation Simulation Estimation Optimal control Transforms Robustness Real-time systems

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"I Don'tWant People to Look At Me Diferently': Designing User-Defined Above-the-Neck Gestures for People with Upper Body Motor Impairments

"I Don'tWant People to Look At Me Diferently': Designing Use...

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2022 CHI Conference on Human Factors in Computing systems, CHI 2022

作者： Zhao, Xuan Fan, Mingming Han, Teng School of Information Rochester Institute of Technology Rochester United States Guangzhou China Division of Integrative Systems and Design The Hong Kong University of Science and Technology Hong Kong Institute of Software Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781450391573

Recent research proposed eyelid gestures for people with upper-body motor impairments (UMI) to interact with smartphones without finger touch. However, such eyelid gestures were designed by researchers. It remains unknown what eyelid gestures people with UMI would want and be able to perform. Moreover, other above-the-neck body parts (e.g., mouth, head) could be used to form more gestures. We conducted a user study in which 17 people with UMI designed above-the-neck gestures for 26 common commands on smartphones. We collected a total of 442 user-defined gestures involving the eyes, the mouth, and the head. Participants were more likely to make gestures with their eyes and preferred gestures that were simple, easy-to-remember, and less likely to draw attention from others. We further conducted a survey (N=24) to validate the usability and acceptance of these user-defined gestures. Results show that user-defined gestures were acceptable to both people with and without motor impairments. © 2022 ACM.

关键词： Smartphones

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Impact of data balancing a multiclass dataset before the creation of association rules to study bacterial vaginosis

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Intelligent Medicine 2024年第3期4卷 188-199页

作者： Freddy de la Cruz-Ruiz Juana Canul-Reich Rafael Rivera-López Erick de la Cruz-Hernández Academic Division of Science and Technology of the Information Juárez Autonomous University of TabascoLa Esmeralda DistrictTabascoMexico Department of Systems National Technological Institute of MexicoTechnological Institute of VeracruzVeracruzMexico Multidisciplinary Academic Division of Comalcalco Juárez Autonomous University of TabascoTabascoMexico

Background Bacterial vaginosis is a polymicrobial syndrome in which the homeostasis exerted by the Latobacillus species that protect the vaginal mucosa has been *** study explored the data balancing process with the intention of improving the quality of association *** article aimed to balance the unbalanced multiclass dataset to improve association rule *** A dataset with 201 observations and 58 variables was analyzed.A preconstructed dataset was *** authors collected the data between August 2016 and October 2018 in Tabasco,*** study population comprised sexually active women ages 18 to 50 who underwent gynecological inspection at the infectious and metabolic diseases research laboratory at the Universidad Juarez Autonoma de *** determine the best κ-value,the random-forest algorithm was used and the balancing was performed with the synthetic minority over-sampling technique(SMOTE),random over-sampling examples(ROSE),and adaptive syntetic sampling approach for imbalanced learning(ADASYN)*** Apriori algorithm created the rules and to select rules with statistical significance,the ***(),***(),and ***()functions and quality metric Fisher’s exact tes were *** biological validation was carried out by the expert(bacteriologist).Results The ADASYN algorithm at K=9 the out of the bag(OOB)error was zero,this was the best𝐾-*** the balancing process the ADASYN algorithm show best the *** the dataset balanced with ADASYN,the apriori algorithm created the association rules and the selection with the quality metric Fisher’s exact test,and the biological validation reported 13 ***-bacteria Atopobium vaginae,Gardnerella vaginalis,Megasphaera filotipo 1,Mycoplasma hominis and Ureaplasma parvum were detected by the apriori algorithm from the balanced *** Balancing may improve the creation of association rules to efficiently model the bacteria that cause bac

关键词： Bacterial vaginosis Data balancing Random forest Synthetic minority over-sampling technique

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Sensor Fault Detection and Isolation in Autonomous Nonlinear systems Using Neural Network-Based Observers

Sensor Fault Detection and Isolation in Autonomous Nonlinear...

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European Control Conference (ECC)

作者： John Cao M. Umar B. Niazi Matthieu Barreau Karl Henrik Johansson Division of Decision and Control Systems Digital Futures KTH Royal Institute of Technology Stockholm Sweden Department of Electrical Engineering and Computer Science Laboratory for Information & Decision Systems Massachusetts Institute of Technology Cambridge MA USA

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This paper presents a novel observer-based approach to detect and isolate faulty sensors in nonlinear systems. The proposed sensor fault detection and isolation (s-FDI) method applies to a general class of nonlinear systems. Our focus is on s-FDI for two types of faults: complete failure and sensor degradation. The key aspect of this approach lies in the utilization of a neural network-based Kazantzis-Kravaris/Luenberger (KKL) observer. The neural network is trained to learn the dynamics of the observer, enabling accurate output predictions of the system. Sensor faults are detected by comparing the actual output measurements with the predicted values. If the difference surpasses a theoretical threshold, a sensor fault is detected. To identify and isolate which sensor is faulty, we compare the numerical difference of each sensor measurement with an empirically derived threshold. We derive both theoretical and empirical thresholds for detection and isolation, respectively. Notably, the proposed approach is robust to measurement noise and system uncertainties. Its effectiveness is demonstrated through numerical simulations of sensor faults in a network of Kuramoto oscillators.

关键词： Uncertainty Fault detection Noise Observers Numerical simulation Sensor systems Sensors

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Enhancement of Security in IoT using Secure Hash Cryptography Algorithm with Double Encryption (SHCA-DE) 9

Enhancement of Security in IoT using Secure Hash Cryptograph...

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9th International Conference on Communication and Electronics systems, ICCES 2024

作者： Uganya, G. Rajalakshmi, D. Vangapandu, Ramarao Dinesh, M. Giri, Jayant Odeh, Mahmoud Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Ece Chennai India Srm Institute of Science and Technology Department of Data Science and Business Systems Kattankulathur Chennai India Vignan's Institute of Engineering for Women Department of Computer Science and Engineering Vishakhapatnam India Saveetha University Department of Vlsi Microelectronics Saveetha School of Engineering Chennai India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India Lovely Professional University Division of Research and Development Phagwara India Zarqa University Faculty of Information Technology Department of Cyber Security Zarqa Jordan University of Business and Technology Jeddah Saudi Arabia

ISBN: (纸本)9798350377972

The 'Internet of things' is the developing technology to transfer the world into smart innovation. 'IoT' security is the most problematic issue in recent applications due to its properties including 'centralized architecture', 'limited capacity devices', and 'ambiguity'. So, blockchain with 'IoT' applications provides secure data communication compared to traditional 'IoT' applications. Blockchain is a recent growing technology that has features including 'decentralized structure', 'transparency', 'immutable records', 'increased capacity', and 'quick backtracks'. The 'cryptography hash algorithm' is very important to provide secure data transmission. It converted the different size input to fixed-size unalterable output to enhance the security. But still, it needs efficient algorithm to secure data transmission with safeguard of private key. The objective of this paper is to propose a secure hash cryptography algorithm with double encryption (SHCA-DE) to protect the private key message. Then, this proposed algorithm has been analyzed with MD5, SHA-256, and SHA3-512. From this analysis, the SHA3-512 performs well with proposed algorithm. © 2024 IEEE.

关键词： Encryption algorithms

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Satellite Image Analysis in Health Care—A Systematic Review 1

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2nd International Conference on Advances in Data-driven Computing and Intelligent systems, ADCIS 2023

作者： Pawar, Bhushan Prakash, Vijay Garg, Lalit Galdies, Charles Buttigieg, Sandra Calleja, Neville Department of Computer Information Systems Faculty of Information and Communication Technology University of Malta MSD Msida2080 Malta Environmental Management and Plan Division Institute of Earth Systems University of Malta Msida Malta Faculty of Health Sciences University of Malta Msida Malta Faculty of Medicine and Surgery University of Malta Msida Malta Department of Computer Science Graphics Era Hill University Dehradun India

ISBN: (数字)9789819995219

ISBN: (纸本)9789819995202

Rapid urbanization, population expansion, and escalating pollution levels have given rise to novel environmental concerns that demand the application of creative, analytical methodologies and diverse data sources. To ensure efficient urban ecological management, it is crucial to consider three levels of phenomena: the environmental system, the physical environment, and the regional surroundings. Utilizing remote sensing data is a viable avenue for enhancing the global environment due to its convenient accessibility and ability to measure crucial physical features regularly. The primary objective of this research study is to ascertain and evaluate suitable methods for analyzing satellite imagery in the healthcare context. The study’s aims encompass examining the diverse array of tools accessible in the market, scrutinizing the characteristics of each device, exploring research papers that have employed these tools, and classifying the tools into open-source and commercial classifications. This study emphasizes the parameters associated with feature extraction and picture enhancement in satellite imagery, as these factors hold significant importance in the analysis of images. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Remote sensing

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A Review of Satellite Image Analysis Tools 4th

A Review of Satellite Image Analysis Tools

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4th International Conference on Recent Trends in Machine Learning, IoT, Smart Cities, and Applications, ICMISC 2023

作者： Pawar, Bhushan Prakash, Vijay Garg, Lalit Galdies, Charles Buttigieg, Sandra Calleja, Neville Department of Computer Information Systems Faculty of Information and Communication Technology University of Malta MSD Msida2080 Malta Department of Computer Science and Engineering Graphics Era Hill University Dehradun India Environmental Management and Plan Division Institute of Earth Systems University of Malta Msida Malta Faculty of Health Sciences University of Malta Msida Malta Faculty of Medicine and Surgery University of Malta Msida Malta

ISBN: (纸本)9789819994410

The rapid growth of urban areas, population, and pollution presents a significant environmental challenge. Addressing these challenges requires innovative analytical approaches and data sources. This study focuses on the three-scale phenomena of the environmental system, physical environment, and regional surroundings, considering their implications on a global network scale. Remote sensing data, with its easy accessibility, offers new toolkits and methods to improve the global environment. It provides self-consistent measurements of vital physical attributes and surpasses traditional data sources regarding accuracy, efficiency, and coverage of larger geographical areas. This study aims to identify and analyze appropriate satellite image analysis tools for healthcare. The study objectives include studying available tools, analyzing their features, categorizing tools into open-source and commercial categories, and providing recommendations. This study emphasizes feature extraction and image enhancement parameters, which are crucial for image analysis. Further, this study provides a functional overview of various commercial and open-source satellite image analysis tools and suggests suitable tools for healthcare applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Geographic information systems

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