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International Conference on Communications (COMM)

作者： Eugen Pop Daniela Gî fu Automatics and Industrial Informatics Department Faculty of Automatic Control and Computers University &#x201C Politehnica&#x201D of Bucharest R&#x0026 D Institute for Automation-IPA SA Bucharest Romania Institute of Computer Science of Romanian Academy - Iasi Branch Faculty of Computer Science of Alexandru Ioan Cuza University of Iasi Iasi Romania

E-business offers to economic agents the opportunity to increase the efficiency of their activity, promote and offer their products and services on a large and diversified market. Often a single service, separately, does not meet all the needs of various categories and groups of customers. In such a situation, service composition can provide more technical, commercial, informational facilities than each separate component service can offer. There are many web-based frameworks used for e-business, but still with limitations. The paper presents a Services Composition Framework and a wise algorithm for e-business models, based on REST and SOAP web services. It is intended to be used for the development of e-business models, comprising stock market exchange, e-commerce, e-banking, etc. The customers can access the framework services, through Smartphones, on mobile and wireless communication channels. Within a Quality-of-Service performance analysis of the e-business Service Composition Framework, the response time and throughput for multiuser access simultaneous requests were evaluated. A stock market exchange service is considered, as an e-business service example, while Bucharest Stock Exchange information is the digital content source for data transactions.

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High throughput event filtering: The interpolation-based DIF algorithm hardware architecture

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Microprocessors and Microsystems 2025年 117卷

作者： Marcin Kowalczyk Tomasz Kryjak Embedded Vision Systems Group Department of Automatic Control and Robotics Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering AGH University of Krakow Poland

In recent years, there has been rapid development in the field of event vision. It manifests itself both on the technical side, as better and better event sensors are available, and on the algorithmic side, as more and more applications of this technology are proposed and scientific papers are published. However, the data stream from these sensors typically contains a significant amount of noise, which varies depending on factors such as the degree of illumination in the observed scene or the temperature of the sensor. We propose a hardware architecture of the Distance-based Interpolation with Frequency Weights(DIF) filter and implement it on an FPGA chip. To evaluate the algorithm and compare it with other solutions, we have prepared a new high-resolution event dataset, which we are also releasing to the community. Our architecture achieved a throughput of 403.39 million events per second (MEPS) for a sensor resolution of 1280 × 720 and 428.45 MEPS for a resolution of 640 × 480. The averagevalues of the Area Under the Receiver Operating Characteristic (AUROC) index ranged from 0.844 to 0.999, depending on the dataset, which is comparable to the state-of-the-art filtering solutions, but with much higher throughput and better operation over a wide range of noise levels.

关键词： Dataset Denoising DVS FPGA High-throughput

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Pilot Study on Using Hybrid–Cascade Filtering on Brain Signals for the control Purposes

Pilot Study on Using Hybrid–Cascade Filtering on Brain Sign...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Mariusz Pelc Dariusz Mikołajewski Edward Jacek Gorzelańczyk Anna Wieczorek Henryk Racheniuk Adam Sudoł Kayhan Latifzadeh Luis A. Leiva Aleksandra Kawala-Sterniuk Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Institute of Computer Science Kazimierz Wielki University Bydgoszcz Poland Institute of Philosophy Kazimierz Wielki University Bydgoszcz Poland Faculty of Physical Education and Physiotherapy Opole University of Technology Opole Poland Faculty of Natural and Technical Sciences University of Opole Opole Poland Department of Computer Science University of Luxembourg Luxembourg Luxembourg

We present an initial study conducted on fNIRS signals using Hybrid-Cascade filters for the purpose of their quality improvement. Whilst many studies focus on filtering brain signals, so that their frequency domain properties would allow e.g. widely understood diagnostics, here we focus on the study of time-domain signal characteristics, which is relevant for potential control purposes. Taking into account various kinds of artifacts, we propose a novel cascade 1D Kalman filter to handle fNIRS signals.

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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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Applying Transformer-Based Neural Networks to Corpus Linguistic Data for Predictive Text Generation in Multilingual Environments

Applying Transformer-Based Neural Networks to Corpus Linguis...

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Emerging Smart Computing and Informatics (ESCI), Conference on

作者： Taufikin Myagmarsuren Orosoo Manikandan Rengarajan Gulnaz Fatma Dilyorjon Yuldashev I Infant Raj IAIN Kudus Indonesia Mongolian National University of Education Mongolia Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India University College Al Ardah Jazan University Jazan Saudi Arabia Automatic Control and Computer Engineering Department Turin Polytechnic University in Tashkent Tashkent Uzbekistan Department of CSE K. Ramakrishnan college of Engineering Trichy Tamil Nadu India

In the subject of corpus linguistics, this study explores the use of transformer-based neural networks to the problems of predictive text production in multilingual contexts. The Transformer architecture presents a viable framework for natural language processing problems because of its reputation for capturing complex patterns and long-range dependencies in sequential data. The research employs a two-phase approach, whereby the Transformer is first pre-trained using a variety of multilingual corpora. This helps the model learn representations that are independent of language, which makes it easier for it to adapt to various linguistic circumstances. The model is then fine-tuned using language-specific datasets to improve its ability to produce linguistically nuanced and contextually appropriate text. The study looks into how different model architectures, training methods, and hyperparameters affect how well the suggested multilingual predictive text generation system performs. Evaluation measures are used to evaluate the model's performance in several languages, including linguistic diversity measurements, BLEU scores, and perplexity. The overall accuracy, calculated across all languages, stands at 80.3%, indicating the model's robust cross-lingual generalization and its effectiveness in capturing diverse linguistic nuances The efficacy and generalization of Transformer-based models are improved across a wide range of languages to handle linguistic diversity.

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FPGA Implementation of SIMON-128 Cryptographic Algorithm Using Artix-7

arXiv

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arXiv 2023年

作者： Ghayoula, Ridha Fattahi, Jaouhar Smida, Amor Gmati, Issam El Pricop, Emil Ziadia, Marwa Unit of Research in High Frequency Electronic Circuits and Systems University of Tunis El Manar Tunis2092 Tunisia Department of Electrical and Computer Engineering Laval University Quebec Canada Department of Computer Science and Software Engineering Laval University Quebec Canada Department of Medical Equipment Technology College of Applied Medical Sciences Majmaah University Majmaah11952 Saudi Arabia College of Engineering Al Gunfudha Umm Al Qura University Saudi Arabia Automatic Control Computers and Electronics Department Petroleum-Gas University of Ploiesti Romania

FPGA is a hardware architecture based on a matrix of programmable and configurable logic circuits thanks to which a large number of functionalities inside the device can be modified using a hardware description language. These functionalities must often be secured especially when the context is sensitive (military, banking, medical, legal, etc.). In this paper, we put forward an efficient implementation of SIMON’s block cipher algorithm using Xilinx Vivado 2018.2. The proposed design is analyzed through simulation on Xilinx Artix-7. A prototype of our design is implemented using the xc7a35tcsg324-1 FPGA chip. Performance and results are discussed. © 2023, CC BY.

关键词： Field programmable gate arrays (FPGA)

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Hyperbolic embedding model for a class of microrna-disease networks

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2020年第1期82卷 219-230页

作者： Angelescu, Radu Dobrescu, Radu Department of Automatic Control and Industrial Informatics Faculty of Auto matic Control and Computer Science University "Politehnica" of Bucharest Romania

The main goal of this paper is to study the embedding of networks in a form that can be used in differential programming. We prove that certain networks have better embeddings in an appropriate metric space and provide a numerically stable embedding solution. We generate embeddings for the disease-microRNA network. © 2020, Politechnica University of Bucharest. All rights reserved.

关键词： RNA

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Fast projection onto convex smooth constraints

arXiv

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arXiv 2021年

作者： Usmanova, Ilnura Kamgarpour, Maryam Krause, Andreas Levy, Kfir Yehuda Automatic Control Laboratory D-ITET ETH Zürich Switzerland Department of Electrical and Computer Engineering University of British Columbia Canada Department of Computer Science ETH Zürich Switzerland Viterby Department of Electrical & Computer Engineering Technion - Israel Institute of Technology

The Euclidean projection onto a convex set is an important problem that arises in numerous constrained optimization tasks. Unfortunately, in many cases, computing projections is computationally demanding. In this work, we focus on projection problems where the constraints are smooth and the number of constraints is significantly smaller than the dimension. The runtime of existing approaches to solving such problems is either cubic in the dimension or polynomial in the inverse of the target accuracy. Conversely, we propose a simple and efficient primal-dual approach, with a runtime that scales only linearly with the dimension, and only logarithmically in the inverse of the target accuracy. We empirically demonstrate its performance, and compare it with standard baselines. © 2021, CC BY.

关键词： Constrained optimization

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Semi-supervised active transfer learning for fetal ECG arrhythmia detection

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computer Methods and Programs in Biomedicine Update 2023年 3卷

作者： Mohebbian, Mohammad Reza Marateb, Hamid Reza Wahid, Khan A. Department of Electrical and Computer Engineering University of Saskatchewan Saskatoon S7N 5A9 SK Canada Biomedical Engineering Department Engineering Faculty University of Isfahan Isfahan Iran Biomedical Engineering Research Centre (CREB) Automatic Control Department (ESAII) Universitat Politècnica de Catalunya-Barcelona Tech (UPC) Barcelona Spain

Deep learning has demonstrated excellent results for ECG anomaly detection, wherein most approaches used supervised learning. The requirement of thousands of manually annotated samples is a concern for state-of-the-art anomaly detection systems, especially for fetal ECG (FECG), and currently, there is not a publicly available FECG dataset annotated for each FECG beat. In this paper, we offer a modified active learning technique based on transfer learning, calibration probability, and autoencoder-based sampling to reduce number of samples requires to annotate. In this regard, we used 25,000 s of recording from 47 patients from the MIT-BIH Arrhythmia Database to train a deep learning model to detect anomalies in non-fetus subjects. Then we used the unlabeled Non-Invasive Fetal ECG Arrhythmia Database (NIFEA DB) of 26 subjects to fine-tune the trained model to fine-tune the trained model based on active learning to detect anomalies in binary form for fetal. A variational autoencoder is trained on all data (adult and fetal ECG), and clustering is applied to latent features extracted from data after dimension reduction. Then, the sampling process of active learning selected samples from different clusters with low confidence to cover all data distribution. Moreover, a probability calibration based on mc-dropout and isotonic regression is used to calibrate confidences, helping to select reliable low-confidence samples. Various ablation studies were performed to show the influence of autoencoder-based sampling, calibration, and transfer learning, which showed that the proposed method could achieve 92% accuracy using 399 training samples. In contrast, other methods required more training samples to reach the same level of accuracy without calibration or an autoencoder and clustering approach or training without active learning. The study also found that transfer learning significantly impacted faster convergence and that the proposed active learning approach was more effect

关键词： Active learning Anomaly Arrhythmia FECG Transfer learning

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Cybersecurity Threat Detection in the Behavior of IoT Devices: Analysis of Data Mining Competition Results

Cybersecurity Threat Detection in the Behavior of IoT Device...

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Federated Conference on computer Science and Information Systems (FedCSIS)

作者： Michał Czerwiński Marcin Michalak Piotr Biczyk Błażej Adamczyk Daniel Iwanicki Iwona Kostorz Maksym Brzęczek Andrzej Janusz Marek Hermansa Łukasz Wawrowski Artur Kozłowski QED Software Warsaw Poland Faculty of Mathematics University of Warsaw Warsaw Poland Łukasiewicz Research Network - Institute of Innovative Technologies EMAG Katowice Poland Department of Computer Networks and Systems Silesian<file://Silesian> University of Technology Gliwice Poland Faculty of Automatic Control Electronics and Computer Science Silesian<file://Silesian> University of Technology Gliwice Poland EFIGO sp. z o.o. Katowice Poland

The paper discusses a data science competition centered around the development of an anomaly detection system for IoT devices. The competition utilized a unique environment that allowed for the operation and monitoring of real IoT devices, including scheduling of attacks on these devices. The environment was used to collect the data, which included both normal and attack-induced behavior of IoT devices. The paper presents the background of the competition, the top models submitted, and the competition results. The paper also includes a discussion about restrictions related to the use of synthetic attack data as input for constructing anomaly detection systems.

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