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1st IEEE International Conference on Automation, Computing and Renewable systems, ICACRS 2022

作者： Chaudhari, Sachin Vasant Dhipa, M. Ayoub, Shahnawaz Gayathri, B. Siva, M. Banupriya, V. Department of Electronic and Computer Engineering Sanjivani College of Engineering Kopargaon Maharashtra Ahmednagar India Department of Biomedical Engineering Nandha Engineering College Perundurai Main Road Erode India Shri Venkateshwara University NH-24 Venkateshwara Nagar Rajabpur Gajraula Dist Uttar Pradesh Amroha India Department of Computer Science Bishop Heber College Affiliated to Bharathidasan University Trichy India Department of Civil Engineering Easwari Engineering College Tamilnadu Chennai India Department of Computer Science and Business Systems M. Kumarasamy College of Engineering Tamilnadu Karur India

ISBN: (纸本)9781665460842

Unmanned aerial vehicles (UAVs) are deliberated as a potential example of automated emergency tasks in dynamic marine environments. But the maritime transmission performances among UAVs and offshore platform becomes a crucial problem. The task planning problems of numerous UAVs are classified into two parts, route planning and task allocation problems, are different and interrelated from one another. Because of the complicated marine environments, both efficiencies of UAVs in an intelligent ocean are not acceptable. This study presents a Modified Aquila Optimization Algorithm based Route Planning Scheme (MAOA-RPS) for UAV networks. The presented MAOA-RPS technique is majorly concentrated on the detection of optimal routes for UAV data transmission. To attain this, the MAOA-RPS technique involves the incorporation of Levy flight (LF) with the traditional AOA. In addition, the optimal routes are chosen by the MAOA-RPS technique via a fitness value, which can be determined by many input parameters. For assessing the enhanced outcomes of the MAOA-RPS technique, we have performed a series of experiments. The comparison study revealed the improved performance of the MAOA-RPS technique under distinct metrics. © 2022 IEEE

关键词： Optimization

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Blockchain and Quantum-based Collaborative Communication Framework for Telehealth

Blockchain and Quantum-based Collaborative Communication Fra...

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International Conference on e-health Networking, Applications and Services (HealthCom)

作者： Harshal Gajjar Dirgha Jivani Chinmay Trivedi Rajesh Gupta Nilesh Kumar Jadav Sudeep Tanwar Ashit Kumar Dutta Joel J.P.C. Rodrigues Department of Computer Science and Engineering Institute of Technology Nirma University Gujarat India Department of Computer Science and Information Systems College of Applied Sciences AlMaarefa University Saudi Arabia Amazonas State University Manaus AM Brazil

ISBN: (数字)9798350350548

ISBN: (纸本)9798350350555

This paper introduces a novel telehealth communication system, designed to enhance the security and integrity of medical data exchange. In the rapidly evolving digital healthcare landscape, the protection of sensitive patient information is paramount. To address this, our system uniquely combines quantum cryptography, specifically the BB84 protocol, with blockchain technology, offering a dual-layered security framework. The Quantum Layer, underpinned by the BB84 protocol, establishes quantum-secure communication channels, effectively encrypting data exchanges between patients, doctors, and hospitals. This layer guarantees that medical information remains confidential and safe from potential quantum-level eavesdropping threats. The subsequent Blockchain Layer further strengthens the system by storing these encrypted communications in an immutable blockchain ledger. This approach not only secures the data against unauthorized alterations but also provides a transparent and permanent record of all transactions, thereby enhancing the auditability of medical communications.

关键词： Technological innovation Protocols Hospitals Telemedicine Communication channels Blockchains Electronic healthcare Quantum cryptography Protection Eavesdropping

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Neural Gas Counter Propagation Neural Network (NG CPNN): A Novel Model for Face Recognition

Neural Gas Counter Propagation Neural Network (NG CPNN): A N...

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science, engineering and Business for Sustainable Development Goals (SEB-SDG), International Conference on

作者： Kazeem Michael Olagunju Adeleye Samuel Falohun Alice Oluwafunke Oke Marion O. Adebiyi Directorate of Centre for Systems and Information Services Landmark University Omu-Aran Nigeria Department of Computer Engineering LAUTECH Ogbomoso Nigeria Department of Computer Science Landmark University Omu-Aran Nigeria

ISBN: (数字)9798350358155

ISBN: (纸本)9798350358162

The advent of biometric technology has enhanced security in various ways, especially by lowering the propensity for circumvention which was obtainable in traditional recognition measures such as the use of passwords, tokens, smart cards, PIN etc. Particularly facial recognition is currently a hot topic, which has evolved over time. A face recognition system is supposed to automatically recognize faces in pictures and videos by receiving a two-dimensional face image as input and comparing it to a predefined database of faces to outputs a discernible face image in the end. Despite the various algorithms used in face recognition, the problems of occlusion, light conditions and facial variation still persist. However, this study has implemented and presented Neural Gas Counter Propagation Neural Network (NG CPNN) as a novel model for face recognition *** implementation of model was carried out using 600 face images, pre-processed by histogram equalization, while face features were extracted by Principal Component Analysis. The novelty of NG CPNN was established by utilizing computational time, sensitivity, and accuracy as performance assessment measures at four distinct threshold values. The result shows computation time of 72.36s, accuracy of 96.25%, sensitivity of 98.33% at 0.8, 0.8, and 0.2 thresholds respectively. Finally, it was concluded based on empirical result and statistical evidence that NG-CPN is a novel model for face recognition. NG CPNN can be employed in access control systems, international borders, smartphone technology, and many more.

关键词： Analytical models Sensitivity Accuracy Face recognition Computational modeling Biological system modeling Neural networks

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Excess Mean Squared Error of Empirical Bayes Estimators

arXiv

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arXiv 2025年

作者： Ju, Yue Wahlberg, Bo Hjalmarsson, Håkan Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden Competence Centre for Advanced BioProduction by Continuous Processing AdBIOPRO Sweden

Empirical Bayes estimators are based on minimizing the average risk with the hyper-parameters in the weighting function being estimated from observed data. The performance of an empirical Bayes estimator is typically evaluated by its mean squared error (MSE). However, the explicit expression for its MSE is generally unavailable for finite sample sizes. To address this issue, we define a high-order analytical criterion: the excess MSE. It quantifies the performance difference between the maximum likelihood and empirical Bayes estimators. An explicit expression for the excess MSE of an empirical Bayes estimator employing a general data-dependent hyper-parameter estimator is derived. As specific instances, we provide excess MSE expressions for kernel-based regularized estimators using the scaled empirical Bayes, Stein’s unbiased risk estimation, and generalized cross-validation hyper-parameter estimators. Moreover, we propose a modification to the excess MSE expressions for regularized estimators for moderate sample sizes and show its improvement on accuracy in numerical simulations. Copyright © 2025, The Authors. All rights reserved.

关键词： Mean square error

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Modeling and analyzing a simple multi-stage supply chain using advance demand information

Modeling and analyzing a simple multi-stage supply chain usi...

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作者： Aoki, Hayato Tsumaya, Akira Graduate School of Computer Science and Systems Engineering Okayama Prefectural University 111 Kuboki Soja-shi Okayama719-1197 Japan Department of Systems Engineering Okayama Prefectural University 111 Kuboki Soja-shi Okayama719-1197 Japan

In a production system using advance demand information, the advance demand information is sent to an upstream company a certain period of time before production, and the firm-order information is sent just before production. Unfortunately, upstream companies are frequently burdened with excess inventory and late deliveries. Therefore, it is necessary to analyze the effect of the variable factors, such as demand fluctuation and the gap between the advance demand information and the firm-order information. The model was based on the following three steps. First, considering a supply chain consisting of four companies, suppliers can be classified into three types, according to the timing of the firm order and production. Second, the supply chain consists of a combination of three types of suppliers, depending on the timing of the sending firm order. Finally, the production-activity structure for each type of supplier was modeled. Then, they were formulated and implemented as an analysis simulator. Using this simulator, several case studies were investigated. As a result, it was confirmed that the bullwhip effect was increased by the sudden fluctuation of demand, especially when the demand increased. In addition, the supplier whose daily production numbers and stock quantity fluctuated was drastically changed by the gap between the advance demand information and the firm order was identified. © 2022 The Japan Society of Mechanical Engineers.

关键词： Supply chains

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Adaptive Varying Contention Window MAC Protocol Based on Underwater Acoustic Propagation Delay

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IEEE Sensors Journal 2023年第13期23卷 15019-15031页

作者： Guo, Yongan Obaidat, Mohammad S. Guo, Jing Wu, Tin-Yu Tey, Fu Jie Engineering Research Center of Health Service System Based on Ubiquitous Wireless Networks Ministry of Education College of Telecommunications and Information Engineering Nanjing210003 China The King Abdullah II School of Information Technology University of Jordan Amman11942 Jordan The School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China Amity University UP Noida201301 India Nanjing University of Posts and Telecommunications College of Telecommunications and Information Engineering Nanjing210003 China National Pingtung University of Science and Technology Department of Management Information Systems Pingtung912301 Taiwan National Taiwan University of Science and Technology Department of Electrical Engineering Taipei106335 Taiwan

Underwater acoustic wave propagation time delay and fluctuations are much greater than radio waves. However, many of the protocols used for underwater acoustic networking and communication are designed according to the principles of terrestrial wireless communication networks, failing to give full consideration to utilizing the underwater acoustic propagation and its time delay variation. For this reason, this article proposes an adaptive varying contention window media access control (AVCW-MAC) protocol based on propagation delay. The protocol uses AVCW random backoff mechanism to differently set up the CW of each node based on the different propagation delays from each underwater sensor node to the cluster head node to improve the channel utilization. In addition, to avoid excessive difference in the CW of each node, the backoff factors K1 and K2 are introduced in the AVCW random backoff mechanism to improve the fairness of nodes' accessing the channel. Simulation results show that for the same amount of sensor nodes, the AVCW-MAC protocol has significantly improved network throughput and decreased average end-to-end latency when compared to legacy CW-MAC protocols. © 2001-2012 IEEE.

关键词： Underwater acoustics

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Contracting Skeletal Kinematic Embeddings for Anomaly Detection

SSRN

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SSRN 2023年

作者： Flaborea, Alessandro D’Amely di Melendugno, Guido Maria D’Arrigo, Stefano Sterpa, Marco Aurelio Sampieri, Alessio Galasso, Fabio Department of Computer Science Sapienza University of Rome Italy Department of Computer Control and Management Engineering Sapienza University of Rome Italy Department of Earth Sciences and Forecasting Research Center Prevention and Control of Geological Risks

Detecting the anomaly of human behavior is paramount to timely recognizing endangering situations, such as street fights or elderly falls. However, anomaly detection is complex, since anomalous events are rare and because it is an open set recognition task, i.e., what is anomalous at inference has not been observed at training. We propose COSKAD, a novel model which encodes skeletal human motion by an efficient graph convolutional network and learns to COntract SKeletal kinematic embeddings onto a latent hypersphere of minimum volume for Anomaly Detection. We propose and analyze three latent space designs for COSKAD: the commonly-adopted Euclidean, and the new spherical-radial and hyperbolic volumes. All three variants outperform the state-of-the-art, including video-based techniques, on the ShangaiTechCampus, the Avenue, and on the most recent UBnormal dataset, for which we contribute novel skeleton annotations and the selection of human-related *** source code and dataset will be released upon acceptance. © 2023, The Authors. All rights reserved.

关键词： Kinematics

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The Task of Parametric Identification the Interval Models with Nonlinear Parameters 12

The Task of Parametric Identification the Interval Models wi...

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12th International Conference on Advanced computer Information Technologies, ACIT 2022

作者： Dyvak, Mykola Pukas, Andriy Manzhula, Volodymyr Kasatkina, Natalia Komar, Myroslav Zabchuk, Vadym West Ukrainian National University Department of Computer Science Ternopil Ukraine State Inst. 'Institute of Environmental Geochemistry of the National Academy of Sciences of Ukraine' Department of Civil Defense and Innovation Kyiv Ukraine West Ukrainian National University Department of Information Computer Systems and Control Ternopil Ukraine

ISBN: (数字)9781665410502

ISBN: (纸本)9781665466479

The paper formulates the parametric identification problem of static objects' interval models of as a finding solutions problem of interval nonlinear algebraic equations system in the optimization problem's form with nonlinear and discrete goal function and linear constraints on a continuous set. For the first time the parametric identification method of static objects' interval models based on the interval data analysis is offered and proved. In contrast to the existing ones, the developed method is based on the computational procedures with the self-organization and self-adaptation elements by analogy with the artificial bee colony algorithms. The proposed approach to the models' construction with guaranteed prognostic properties is characterized by lower procedures' time complexity for building such models. © 2022 IEEE.

关键词： Nonlinear equations

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Real-time Stream Processing in IoT Environments

Real-time Stream Processing in IoT Environments

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International Conference on science Technology engineering and Management (ICONSTEM)

作者： P. Rajasekar Rupali Shekar Bhosale Indhumathi C Sandeep K V Prasanthi Kumari N Rajendiran M Department of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Kattankulathur Tamil Nadu India Department of Electronics and Telecommunication Engineering Bharati Vidyapeeth Institute of Technology Navi Mumbai Maharashtra India Department of Computer Science and Business Systems RMK College of Engineering and Technology Puduvoyal Tamil Nadu India Department of Electronics & Telecommunication Engineering Dayananda Sagar College of Engineering Bengaluru Karnataka India School of Computer Sciences University of Petroleum and Energy Studies Dehradun Uttarakhand 248007 India Department of Computer Science and Engineering Panimalar Engineering College Chennai Tamil Nadu India

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

New IoT devices generate massive real-time data. Fast, real-time stream processing is needed for IoT data insight extraction. There are pros and downsides to real-time stream processing for the Internet of Things (IoT). This article analyzes present methods and technologies. The inquiry begins with large-scale, real-time IoT data analysis. Real-time analytics and bulk processing limits are important for IoT decision-making. We then investigate IoT stream processing frameworks, methodologies, and systems' complexity. We explore Internet of Things technology selection and tradeoffs between scalability, accuracy, latency, and real-time processing system scalability. It covers real-time stream processing system design and deployment and risk mitigation. Case studies and use cases highlight real-time IoT stream processing. Healthcare, smart city, and industrial IoT operational efficiency and proactive decision-making improve with real-time data. Finally, the report suggests the Internet of Things real-time stream processing research. New IoT data analytics protocols, methods, and technologies are highlighted. We teach real-time stream processing to IoT academics, practitioners, and decision-makers. They could then develop more efficient and scalable IoT data stream optimization solutions.

关键词： Privacy Data analysis Protocols Smart cities Scalability Decision making Real-time systems

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Phase chimera states on nonlocal hyperrings

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Physical Review E 2024年第2期109卷 L022201-L022201页

作者： Riccardo Muolo Thierry Njougouo Lucia Valentina Gambuzza Timoteo Carletti Mattia Frasca Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo 152-8552 Japan Department of Mathematics University of Namur B5000 Namur Belgium naXys Namur Institute for Complex Systems University of Namur B5000 Namur Belgium Faculty of Computer Science University of Namur B5000 Namur Belgium Department of Electrical and Electronic Engineering University of Buea P.O. Box 63 Buea Cameroon Department of Electrical Electronics and Computer Science Engineering University of Catania 95125 Catania Italy Istituto di Analisi dei Sistemi ed Informatica “A. Ruberti” IASI-CNR 00185 Roma Italy

Chimera states are dynamical states where regions of synchronous trajectories coexist with incoherent ones. A significant amount of research has been devoted to studying chimera states in systems of identical oscillators, nonlocally coupled through pairwise interactions. Nevertheless, there is increasing evidence, also supported by available data, that complex systems are composed of multiple units experiencing many-body interactions that can be modeled by using higher-order structures beyond the paradigm of classic pairwise networks. In this work we investigate whether phase chimera states appear in this framework, by focusing on a topology solely involving many-body, nonlocal, and nonregular interactions, hereby named nonlocal d-hyperring, (d+1) being the order of the interactions. We present the theory by using the paradigmatic Stuart-Landau oscillators as node dynamics, and we show that phase chimera states emerge in a variety of structures and with different coupling functions. For comparison, we show that, when higher-order interactions are “flattened” to pairwise ones, the chimera behavior is weaker and more elusive.

关键词： Chimera states Collective behavior in networks Dynamics of networks Pattern formation Synchronization Synchronization transition

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