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European Conference on Optical Communication (ECOC)

作者： Adonis Bogris Kostas Sozos Stavros Deligiannidis George Sarantoglou Charis Mesaritakis Dept. of Informatics and Computer Engineering. Aghiou Spiridonos University of West Attica Athens Egaleo Greece Dept. of Information and Communication Systems Engineering University of the Aegean Karlovassi

ISBN: (数字)9781957171159

ISBN: (纸本)9781665475570

We review our recent work in machine learning and neuromorphic processing for the mitigation of transmission impairments at very high baud rates. Bidirectional recurrent neural networks and neuromorphic recurrent spectral slicers emerge as promising solutions for mid-term deployment in long-haul and short-reach communication systems respectively.

关键词： Recurrent neural networks Neuromorphic engineering Equalizers Europe Machine learning Optical fiber communication Complexity theory

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Multifunctional Switchable Filter Using Shorted Coupled-Line Sections 52

Multifunctional Switchable Filter Using Shorted Coupled-Line...

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52nd European Microwave Conference, EuMC 2022

作者： Shirazi, Minahil Chatzichristodoulou, David Quddious, Abdul Shoaib, Nosherwan Psychogiou, Dimitra Nikolaou, Symeon Vryonides, Photos Frederick Research Center Cyprus Pakistan Rf and Microwave Solutions Ltd Cyprus Kios Research and Innovation Center of Excellence University of Cyprus Cyprus School of Engineering University College Cork Ireland Tyndall National Institute Ireland Frederick University Dept. of Electrical and Computer Engineering and Informatics Cyprus

ISBN: (数字)9782874870699

ISBN: (纸本)9782874870699

This paper presents a novel multifunctional RF filter based on RF-switched parallel-coupled line sections. It demonstrates three different reconfigurable responses namely a bandpass filter (BPF) response, a bandstop filter (BSF) response and a dual-band (DBPF) response. Reconfigurability is realized by turning on and off four p-i-n diodes that are placed at specific locations and either connect or disconnect a uniform transmission line and shorted parallel coupled-line sections to the main RF signal path. To verify the validity of the proposed design, a switchable filter prototype is fabricated and measured. For the BPF response, the measured 3-dB fractional bandwidth (FBW) is 43.48 % (1.75-2.75 GHz) with a passband insertion loss of 0.8 dB. For the BSF response the measured 3-dB FBW is 36.52 % (1.90-2.74 GHz) with an in-band suppression level above 12 dB. Finally for the dual-band BPF response, the measured 3-dB FBWs of the two bands are 18.2% and 18.5% respectively. © 2022 European Microwave Association (EuMA).

关键词： Notch filters

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A Model for Intelligible Interaction Between Agents That Predict and Explain

arXiv

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arXiv 2023年

作者： Baskar, A. Srinivasan, Ashwin Bain, Michael Coiera, Enrico Dept. of Computer Science Information Systems BITS Pilani Goa Campus India Dept. of Computer Science Information Systems and APPCAIR BITS Pilani Goa Campus India School of Computer Science Engineering University of New South Wales Australia Centre for Health Informatics Macquarie University Sydney Australia

Machine Learning (ML) has emerged as a powerful form of data modelling with widespread applicability beyond its roots in the design of autonomous agents. However, relatively little attention has been paid to the interaction between people and ML systems. In this paper we view interaction between humans and ML systems within the broader context of communication between agents capable of prediction and explanation. We formalise the interaction model by taking agents to be automata with some special characteristics and define a protocol for communication between such agents. We define One- and Two-Way Intelligibility as properties that emerge at run-time by execution of the protocol. The formalisation allows us to identify conditions under which run-time sequences are bounded, and identify conditions under which the protocol can correctly implement an axiomatic specification of intelligible interaction between a human and an ML system. We also demonstrate using the formal model to: (a) identify instances of One- and Two-Way Intelligibility in literature reports on humans interacting with ML systems providing logic-based explanations, as is done in Inductive Logic Programming (ILP);and (b) map interactions between humans and machines in an elaborate natural-language based dialogue-model to One- or Two-Way Intelligible interactions in the formal model. © 2023, CC BY.

关键词： Inductive logic programming (ILP)

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Non-Invasive Device for Hearing Rehabilitation

Non-Invasive Device for Hearing Rehabilitation

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E-Health and Bioengineering Conference (EHB)

作者： Daniela Goldan Mihai Aron Teofil Ilie Ursache Gladiola Petroiu Cristian Rotariu Dept. of Biomedical Sciences Faculty of Medical Bioengineering Grigore T. Popa University of Medicine and Pharmacy of Iasi Iași Romania Dept. of Automatic Control and Applied Informatics Faculty of Automatic Control and Computer Engineering Gheorghe Asachi Technical University Iași Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Hearing loss impacts over 5% of the world's population, a percent rising due to aging populations, noise exposure, and chronic health conditions. To address this, we developed a non-invasive hearing device designed for individuals with hearing challenges that limit the use of hearing aids. The proposed device integrates a set of Bluetooth headphones with a smartphone, that process the ambient sound in real time through a software application and delivers to the hear impaired patient via bone conduction, bypassing traditional auditory pathways. Laboratory tests confirmed that the proposed device effectively replicates auditory perception. The developed device offers an accessible and user-friendly alternative to patients who cannot use traditional hearing aids.

关键词： Irrigation Noise Auditory system Ear Receivers Hearing aids Propagation losses Real-time systems Software Testing

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Graph Neural Networks for IoT Data Aggregation Scheduling

Graph Neural Networks for IoT Data Aggregation Scheduling

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IEEE Symposium on Network Operations and Management

作者： Van-Vi Vo Syed M. Raza Duc-Tai Le Moonseong Kim Hyunseung Choo Convergence Research Institute Sungkyunkwan University Suwon South Korea Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon South Korea College of Computing and Informatics Sungkyunkwan University Suwon South Korea Dept. of IT Convergence Software Seoul Theological University Bucheon South Korea

ISBN: (数字)9798350327939

ISBN: (纸本)9798350327946

Data aggregation is an important approach in IoT sensor networks since it reduces data transfer while also preserving energy and bandwidth. This research investigates the challenge of time-efficient data aggregation in wireless sensor networks, which is critical in military, civilian, and industrial applications. Effective data aggregation algorithm design and optimization are required for quick and interference-free data collection. Machine learning has received attention for outperforming classical heuristic techniques. The research presents the first Graph Neural Network (GNN) model for data aggregation in IoT sensor networks, which incorporates Graph Attention Networks (GATs) and fully connected layers. The GNN-based model learns network topology and node attributes, creating node embeddings and correcting sensor node transmitting time slots. With a centralized training procedure and adapted execution for network size change, the proposed approach achieves satisfactory performance compared to the heuristic algorithm.

关键词： Training Adaptation models Wireless sensor networks Machine learning algorithms Job shop scheduling Network topology Machine learning

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Cardiac Condition Detection Model Using Alexnet and Time-Frequency Representation of ECG Signals

Cardiac Condition Detection Model Using Alexnet and Time-Fre...

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E-Health and Bioengineering Conference (EHB)

作者： Mihai Aron Teofil Ilie Ursache Gladiola Petroiu Cristian Rotariu Dept. of Biomedical Sciences Grigore T. Popa University of Medicine and Pharmacy of Iasi Faculty of Medical Bioengineering Iaşi Romania Dept. of Automatic Control and Applied Informatics Gheorghe Asachi Technical University Faculty of Automatic Control and Computer Engineering Iaşi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Cardiac conditions are one of the leading causes of death worldwide. To address this, we designed a model that can detect cardiac conditions from a patient's electrocardiogram (ECG). This will convert the 1D ECG signal into a 2D scalogram using wavelet transforms with Morlet wavelets. With the help of a network based on the AlexNet convolutional neural network, it distinguishes between a normal ECG signal and one indicative of arrhythmia or congestive heart failure. The resulting model performs well, achieving a classification accuracy of 92.20% and providing a robust approach for detecting cardiac conditions.

关键词： Wavelet transforms Training Time-frequency analysis Accuracy Biological system modeling Electrocardiography Predictive models Congestive heart failure Convolutional neural networks Biomedical engineering

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Light up that Droid! On the Effectiveness of Static Analysis Features against App Obfuscation for Android Malware Detection

arXiv

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arXiv 2023年

作者： Molina-Coronado, Borja Ruggia, Antonio Mori, Usue Merlo, Alessio Mendiburu, Alexander Miguel-Alonso, Jose The Dept. of Computer Architecture and Technology University of the Basque Country UPV/EHU Donostia Spain The Dept. of Computer Science and Artificial Intelligence University of the Basque Country UPV/EHU Donostia Spain The Dept. of Informatics Bioengineering Robotics and Sytems Engineering University of Genoa Genoa Italy The CASD - Centre for Advanced Defense Studies Rome Italy

Malware authors have seen obfuscation as the mean to bypass malware detectors based on static analysis features. For Android, several studies have confirmed that many anti-malware products are easily evaded with simple program transformations. As opposed to these works, ML detection proposals for Android leveraging static analysis features have also been proposed as obfuscation-resilient. Therefore, it needs to be determined to what extent the use of a specific obfuscation strategy or tool poses a risk for the validity of ML malware detectors for Android based on static analysis features. To shed some light in this regard, in this article we assess the impact of specific obfuscation techniques on common features extracted using static analysis and determine whether the changes are significant enough to undermine the effectiveness of ML malware detectors that rely on these features. The experimental results suggest that obfuscation techniques affect all static analysis features to varying degrees across different tools. However, certain features retain their validity for ML malware detection even in the presence of obfuscation. Based on these findings, we propose a ML malware detector for Android that is robust against obfuscation and outperforms current state-of-the-art detectors. © 2023, CC BY-NC-SA.

关键词： Static analysis

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Automatic Parkinson's tremor assessment with data analysis from daily activities 6

Automatic Parkinson's tremor assessment with data analysis f...

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6th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2021

作者： Fiska, Vasiliki Gakilazou, Vasiliki Katertsidis, Nikolaos Tzallas, Alexandros T. Giannakeas, Nikolaos Tsipouras, Markos G. Dept. of Electrical and Computer Engineering Univ. of Western Macedonia Kozani Greece Dept. of Informatics and Telecommunications Univ. of Ioannina Arta Greece Science and Technology Park of Epirus UNIVEYE IKE Ioannina Greece

ISBN: (纸本)9781665427425

A new approach for the assessment of motor symptoms caused by Parkinson's disease (PD), based on data recorded using a smart mobile phone, is presented in this manuscript. Data were obtained from the online platform ***, and were analyzed based on machine learning techniques to produce a comprehensive physician report, presenting motor symptoms in everyday life. The idea of this study is to equip PD patients with a smartphone, which will monitor signals in real time for a period of time in order to enhance the medical diagnosis routine of a physician, providing information about the overall picture of the patient's motor condition, resulting in the provision of individualized treatment to the patient. © 2021 IEEE

关键词： Patient treatment

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Enhanced Alzheimer's disease and Frontotemporal Dementia EEG Detection: Combining lightGBM Gradient Boosting with Complexity Features

Enhanced Alzheimer's disease and Frontotemporal Dementia EEG...

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Annual IEEE Symposium on computer-Based Medical Systems

作者： Andreas Miltiadous Katerina D. Tzimourta Vasileios Aspiotis Theodora Afrantou Markos G. Tsipouras Nikolaos Giannakeas Euripidis Glavas Alexandros T. Tzallas Dept. of Informatics and Telecommunications University of Ioannina Kostakioi Arta Greece Dept. of Electrical & Computer Engineering University of Western Macedonia Kozani Greece Faculty of Medicine University of Ioannina Ioannina Greece Dept. of Neurology AHEPA University Hospital Aristotle University of Thessaloniki Thessaloniki Greece

Alzheimer's disease and Frontotemporal dementia are the two most reported dementia cases. They both are neurodegenerative disorders without cure while existing treatments only halt their progress. Thus, early detection is of crucial importance. In this work, we utilize electroencephalographic signals of AD and FTD patients and propose a classification pipeline to distinguish them from healthy signals. This pipeline consists of Independent Component Analysis as a preprocessing stage, the extraction of time, frequency and complexity features, feature elimination through importance ranking and finally classification through utilizing Gradient Boosting Decision Trees. The proposed methodology achieved 92.27% F1 score in the Dementia versus Control problem, 83.06% in the AD versus Control and 80.67% in the FTD versus Control.

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Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface

Optical Evanescent Field for Direct Observation of Sub-100nm...

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Robotics, engineering, Science, and Technology (RESTCON), International Conference on

作者： Panart Khajornrungruang Thitipat Permpatdechakul Keisuke Suzuki Aran Blattler Yutaka Terayama Daiki Goto Pipat Phaisalpanumas Natthaphon Bun-Athuek Amornphun Phunopas Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Mechanical Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Mechanical Information Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Production and Robotics Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Mechanical Science and Technology Course Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Industiral Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Mechanical Engineering Technology College of Industrial Technology King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes.

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