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Identification of EEG Features of Transcranial Electrical Stimulation (tES) Based on eXplainable Artificial Intelligence (XAI)

Identification of EEG Features of Transcranial Electrical St...

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Metrology for Extended Reality, Artificial Intelligence and Neural engineering (MetroXRAINE), IEEE International Conference on

作者： Pasquale Arpaia Lidia Ammendola Maria Cropano Matteo De Luca Anna Della Calce Ludovica Gargiulo Giacomo Lus Luigi Maffei Daniela Malangone Nicola Moccaldi Simona Raimo Elisabetta Signoriello Paolo De Blasiis Dep. of Electrical Engineering and Information Technology (DIETI) University of Naples Federico II Naples Italy II Neurological Clinic Multiple Sclerosis Center University of Campania “Luigi Vanvitelli” Naples Italy Dep. of Advanced Medical and Surgery Science Second Division of Neurology University of Campania “Luigi Vanvitelli” Naples Italy Dep. of Medical and Surgical Sciences “Magna Graecia” University of Catanzaro Catanzaro Italy University of Basilicata Potenza Italy University of Campania “Luigi Vanvitelli” Naples Italy

ISBN: (数字)9798350378009

ISBN: (纸本)9798350378016

Electroencephalographic (EEG) features of transcranial Electrical Stimulation (tES) effects in Multiple Sclerosis (MS) patients were identified. Machine Learning and eXplainable Artificial Intelligence (XAI) algorithms were the used methods for the EEG feature selection. Current tES-based treatments lack of adaptivity to their effects on individuals. Real-time modification of electrical stimulation parameters based on the trend of specific EEG features may represent a new perspective in terms of personalized medicine for MS patients. This preliminary study aimed to identify EEG features reflecting the effect of tES treatment. Ongoing analyses are exploring the correlation between the identified EEG features and the expected clinical outcomes. Five MS patients underwent non-pharmacological treatment combining Theory of Mind (ToM) training with tES or sham treatment. Pre-and post-treatment variation in EEG features were assessed both in Eyes Opened (EO) and Eyes Closed (EC) conditions. In particular, absolute and relative power across six frequency bands, and Posterior Dominant Rhythm (PDR) amplitude and frequency were explored. The Sequential Feature Selection (SFS) algorithm in combination with Support Vector Machine (SVM) classifier identified (i) difference of absolute powers in high beta band in T3 channel, (ii) difference of absolute powers in gamma band in T3 channel, and (iii) difference of absolute powers in gamma band in O2 channel in EO condition, and (i) difference of absolute powers in gamma band in T3 channel, (ii) difference of absolute powers in gamma band in C4 channel, and (iii) difference of PDR amplitude in O2 channel in EC condition as the most discriminating tES from sham treatment (67.5 % accuracy in EO and 83.33 % in EC conditions, respectively). The SHapley Additive exPlanations (SHAP) algorithm highlighted PDR amplitudes in O2 and O1 as most informative features.

关键词： Support vector machines Training Accuracy Machine learning algorithms Explainable AI Precision medicine Electrical stimulation Feature extraction Electroencephalography Classification algorithms

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eXplainable Artificial Intelligence Improves EEG-Based Cognitive Workload Assessment Induced by Fine Motor Activity in Neurosurgeons

eXplainable Artificial Intelligence Improves EEG-Based Cogni...

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Metrology for Extended Reality, Artificial Intelligence and Neural engineering (MetroXRAINE), IEEE International Conference on

作者： Pasquale Arpaia Matteo De Luca Anna Della Calce Giovanni Carone Nicolò Castelli Dunja Duran Ludovica Gargiulo Nicola Moccaldi Marco Nalin Alessandro Perin Salvatore Piccolo Cosimo Puttilli Elisa Visani Dep. of Electrical Engineering and Information Technology (DIETI) University of Naples Federico II Naples Italy Fondazione IRCCS Istituto Neurologico Carlo Besta Milan Italy ab medica S.p.A. Cerro Maggiore (MI) Italy

ISBN: (数字)9798350378009

ISBN: (纸本)9798350378016

Cognitve workload associated with fine motor activity in neurosurgeons was monitored by using a wearable electroen-cephalographic (EEG) device. The most informative EEG features were selected by means of an explainable Artificial Intelligence (XAI) algorithm. XAI represents a promising novel approach in this application field and offers new opportunities for extracting information from EEG data beyond traditional statistical and Machine Learning-based methods. Six neurosurgeons performed the Purdue Pegboard Test (PPT) at two difficulty levels related to low or high cognitive load. EEG signals were acquired with an eight dry electrode device. Absolute powers in six different frequency bands of interest were explored. Three most involved EEG features resulted from SHapley Additive exPlanations (SHAP) methods, namely absolute power in delta band on C3 and Fz channels and the absolute power in theta band on Fz. Summary plots showed a decrease of the three identified EEG features in the high cognitive load task. These findings demonstrate the potential of Artificial Intelligence-supported wearable EEG solutions to monitor cognitive load over time, to track the cognitive load of trainee neurosurgeons and to design adaptive training courses.

关键词： Training Performance evaluation Explainable AI Cognitive load Motors Electroencephalography Time measurement Neurosurgery Biomedical monitoring Monitoring

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Enhancements to the 5G-NR 2-Step RACH: an Unsourced Multiple Access Perspective

Enhancements to the 5G-NR 2-Step RACH: an Unsourced Multiple...

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IEEE Conference on Standards for Communications and Networking (CSCN)

作者： Patrick Agostini Jean-Francois Chamberland Federico Clazzer Johannes Dommel Gianluigi Liva Andrea Munari Krishna Narayanan Yury Polyanskiy Slawomir Stanczak Zoran Utkovski Fraunhofer Heinrich-Hertz-Institut Berlin Germany Dep. of Electrical and Computer Engineering College Station Texas A&M University TX USA German Aerospace Center (DLR) Inst. of Communications and Navigation Wessling Germany Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge MA USA

ISBN: (数字)9798331507428

ISBN: (纸本)9798331507435

The ever increasing demand for massive connectivity, combined with the specific characteristics of machinegenerated wireless traffic, is pushing the existing solutions for device registration and data transfer beyond their operational limits. In this paper, we target specifically the 3GPP 5G New Radio random access channel, proposing some enhancements inspired by recent research results in the field of unsourced multiple access (UMAC). Aiming to enable massive grant-free connectivity for large machine-type and Internet of things terminals, we focus on modifications of the two-step random access procedures originally introduced in 3GPP Release 16. By means of simulations, we show that remarkable gains in both energy and spectral efficiency can be attained while retaining a strong resemblance to the legacy protocol.

关键词： Wireless communication Fading channels Protocols Spectral efficiency Simulation New Radio 3GPP Internet of Things Standards Signal to noise ratio

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The search of the path MTU with QUIC

The search of the path MTU with QUIC

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2021 Workshop on the Evolution, Performance and Interoperability of QUIC, EPIQ 2021 - Part of CoNEXT 2021

作者： Völker, Timo Tüxen, Michael Rathgeb, Erwin P. FH Münster Uni. of Appl. Sciences Dep. of Electrical Engineering and Computer Science NRW Steinfurt Germany University of Duisburg-Essen Computer Networking Technology Group NRW Essen Germany

ISBN: (纸本)9781450391351

A data sender in an IP based network is only capable to efficiently use a network path if it knows the packet size limit of the path, i.e., the Path Maximum Transmission Unit (PMTU). The IETF recently specified a PMTU discovery framework for transport protocols like QUIC. This paper complements this specification by presenting a search algorithm. In addition, it defines several metrics and shows results of analyses for the algorithm with various PMTU candidate sequences using these metrics. We integrated the PMTU discovery with our algorithm into a QUIC simulation model. This paper describes the integration and presents measurements obtained by simulations. © 2021 ACM.

关键词： Learning algorithms

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Next Generation Image Watermarking via Combined DWT-SVD Technique

Next Generation Image Watermarking via Combined DWT-SVD Tech...

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Cyber Resilience (ICCR), International Conference on

作者： Qais Al-Na'amneh Ammar Almomani Ahmad Nasayreh Khalid M.O. Nahar Hasan Gharaibeh Rabia Emhamed Al Mamlook Mohammad Alauthman Department of Cyber Security Applied Science Private University Amman Jordan School of Computing Skyline University College Sharjah United Arab Emirates I. T. department AlHuson University College AlBalqa Applied University Irbid Jordan Department of Computer Sciences Yarmouk University Irbid Jordan Faculty of Information Technology Computer Sciences Yarmouk University Irbid Jordan Dep. of Business Administration Trine University Indiana USA Dep.of Mechanical and Industrial Engineering University of Zawia Tripoli Libya Department of Information Security Faculty of Information Technology University of Petra Amman Jordan

ISBN: (数字)9798350394962

ISBN: (纸本)9798350394979

Personal computers and the Internet are used in different areas and are easier to use. Most data is easy to transmit and duplicate in digital format, and being tampered with and stolen easily leads to issues for content owners and service providers. The Paper describes a secure (tampering-resistant) method for watermarking images for protection and authentication and digital media like audio, video, and multimedia data, and a combination of singular value decomposition (SVD) and Discrete wavelet transform (DWT) for insertion watermark by MATLAB to increase accuracy, simplicity, and flexibility Readability, secure robustness, and imperceptibility the visibility of the image. The proposed algorithm consists of three main steps: Firstly, we decomposed the original image into four sub-bands and the original watermark. Secondly, embed the watermark in the LL sub-band by replacing the singular value for the watermark. Finally, embed a watermark in the other three sub-bands by adding LL values for a watermark in each sub-band in the original image.

关键词： Resistance PSNR Watermarking Transforms Streaming media Robustness Real-time systems

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Alert system with IoT Techniques for Stray Children

Alert system with IoT Techniques for Stray Children

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Cybernetics and Innovations (ICCI), International Conference on

作者： Patiyuth Pramkeaw Thittaporn Ganokratanaa Thidarat Pinthong Napathsorn Kitprasert Media Technology Program King Mongkut's University of Technology Thonburi Bangkok Thailand Applied Computer Science Program King Mongkut's University of Technology Thonburi Bangkok Thailand Dep. of Business Information Management Phetchaburi Rajabhat University Phetchaburi Thailand

The purpose of this research was to design, produce and evaluate a stray child warning system. The device has been designed by using 2 ESP8266 boards to receive signals as specified. The system will notify the information via Line Notify to let users know how far the board that acts as a Client is from the board that acts as an Access Point. Expressed in meters (m) in the notification line notify process. The test results of the system in terms of signal transmission between the Access Point and the Client can work well. Buzzer speaker and LED notification light according to the specified distance every time. Notifications to LINE Notify to mobile phones can be done every time.

关键词： Meters Pediatrics Technological innovation LED lamps Alarm systems Turning Mobile handsets

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Performance Monitoring and Controlling of Multicore Shared-Memory Parallel Processing Systems 3

Performance Monitoring and Controlling of Multicore Shared-M...

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3rd information technology to Enhance e-Learning and Other Application, IT-ELA 2022

作者： Haji, Lailan M Zeebaree, Subhi R. M. Ageed, Zainab Salih Ahmed, Omar M. Sadeeq, Mohammed A. M. Shukur, Hanan M. University of Zakho Faculty of Science Computer Science Dep. Duhok Iraq Technical College of Engineering Duhok Polytechnic University Energy Eng. Dept. Duhok Iraq College of Science Nawroz University Computer Science Dept. Duhok Iraq Zakho Technical Institute Duhok Polytechnic University Information Technology Dept. Duhok Iraq Technical College of Administration Duhok Polytechnic University ITM Dept. Duhok Iraq Al-Kitab University Computer Engineering Dept. Kirkuk Iraq

ISBN: (纸本)9798350334968

The field of research known as 'parallel processing' examines architectural and algorithmic methods for increasing the efficiency and other desirable qualities (such as cost-effectiveness and reliability) of computers by exploiting many forms of concurrency. The development of multi-core CPUs has opened the door to novel strategies for boosting system performance via parallelism. Increasing the number of concurrent threads greatly affects the time cost. While increased parallelism might reduce calculation time, the associated synchronization costs would likely be prohibitive for most applications. In this article, we'll go through the first half of the process, which involves gathering requirements and designing a prototype;the second half, which involves monitoring and managing a program that can run on a wide range of multicore system architectures, including those with (2, 4, and 8 CPUs). A shared-memory parallel processing method was proposed and built to show off the system's full potential. The implications of multi-core systems on overall program execution time and parallel processing in shared-memory systems provide the backbone of this investigation. © 2022 IEEE.

关键词： Cost effectiveness

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The Influence of Applying Digital Toolkits to Assist 3D Software Development on Individual Work Performance and Perceived Stress

The Influence of Applying Digital Toolkits to Assist 3D Soft...

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International Conference on Applied System Innovation (ICASI)

作者： Wen-Chuan Wu Ming-Han Lee Dep. of Computer Science and Information Engineering National Ilan University Yilan City Taiwan R.O.C. Master Program of E-Learning for Multimedia and Network Communications National Ilan University Yilan City Taiwan R.O.C.

ISBN: (数字)9798350394924

ISBN: (纸本)9798350394931

Digital content industry, encompassing areas such as digital games, computer animation, digital audio-visual applications, and digital art, plays a pivotal role in today's and future developmental trends. Maya 3D software stands out as a crucial development tool in these domains. However, the multitude of built-in tools in Maya 3D can lead to overly complex interfaces, impacting development efficiency for software developers. To address this issue, this paper designs a digital toolkit for Maya 3D software, presented in a Menu Bar format. This toolkit offers features like naming, sorting, categorization, and automatic saving to JSON files for future use. Through a crossover experimental design, this paper investigates the impact of this proposed toolkit on 3D software developers' individual work performance, work engagement, and stress perception. Results shows a significant positive influence of that toolkit on software developers, particularly in enhancing work performance. It means that the proposed digital toolkit effectively improves the performance of software developers' work and reduces their stress during the software development process.

关键词： Industries Technological innovation Three-dimensional displays Market research Software Stress Software development management

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Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning

arXiv

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arXiv 2025年

作者： Abdullah, Abdulhady Abas Taher Karim, Sarkhel H. Ahmed, Sara Azad Tariq, Kanar R. Rashid, Tarik A. Artificial Intelligence and Innovation Centre University of Kurdistan Hewler Erbil Iraq Computer Science Department College of Science University of Halabja Kurdistan Region Iraq Computer Engineering Dep Komar University of Science and Technology Iraq Information Technology Department Technical College of Informatics Sulaimani Polytechnic University Sulaymaniyah Iraq

Speaker diarization, a core problem in speech processing, entails partitioning a given audio stream according to the speakers. Even though progress has been made in the development of the models for high-resource languages, there is still a set of specific difficulties in going through a similar process for low-resource languages such as Kurdish: there are very few annotated datasets available;the language has dialects;speakers use code-switching a lot. These challenges are met in this study by training the Wav2Vec 2.0 SSL model on a Kurdish dataset prepared for this purpose. Thanks to transfer learning, it was possible to transfer multilingual representations learnt in other languages to the phonetic and acoustic features of Kurdish speech. The general Diarization Error Rate (DER) was reduced by 7.2%, and the cluster purity increased by 13% when compared to the baseline algorithm. They show that making improvements in any state-of-the-art model can help in enhancing the performance of under-resourced languages. Implications of this work include transcription services for Kurdish-language media programs, as well as speaker segmentation in multilingual call centers, teleconferencing, and videoconferencing systems. Therefore, this work demonstrates that self-supervised and transfer techniques can improve speaker diarization for Kurdish and other low-resource languages with diverse features. The approach provides a base for building effective diarization systems in other understudied languages, which remains essential for speech technology’s equity. © 2025, CC BY.

关键词： Speech enhancement

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Comparison of Traditional ML Algorithms for Energy Consumption Prediction Models

Comparison of Traditional ML Algorithms for Energy Consumpti...

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2022 IEEE Future Networks World Forum (FNWF)

作者： Rebeca Estrada Víctor Asanza Danny Torres Irving Valeriano Daniel Alvarado Information Technology Center & Electrical Eng. and Computer Science Dep. Escuela Superior Politécnica del Litoral Guayaquil Ecuador Electrical Eng. and Computer Science Dep. Escuela Superior Politécnica del Litoral Guayaquil Ecuador Information Technology Center Escuela Superior Politécnica del Litoral Guayaquil Ecuador Mechanical and Production Sciences Eng. Dep. Escuela Superior Politécnica del Litoral Guayaquil Ecuador

Data centers consume a large amount of energy to meet the increasing demand for IT infrastructure and software due to the IT equipment and cooling infrastructure involved. Therefore, it is necessary to have energy consumption control strategies for DC computer equipment that will allow infrastructure upgrades to reduce energy consumption and to meet the requirement of Green IT. In this way, energy consumption is reduced and the use of technological resources can be optimized. In this paper, we propose to evaluate several traditional Machine Learning algorithms as prediction models using three different temporal windows (i.e. minute, hour and day) taking into account several features such as voltage, energy, frequency, current, power, power factor, and temperature. A comparison of the root square mean error (RMSE) during the validation stage is carried out in order to select the most appropriate algorithm for each time window. In addition, running times are calculated to determine the feasibility of the selected algorithms. Moreover, the suitable predictive model can be the key to the ensure a fair distribution of the workload among the different servers in a Datacenter.

关键词： Energy consumption Data centers Machine learning algorithms Temperature Computational modeling Predictive models Prediction algorithms

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