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ECG Signal-Based Feature Identification of Obstructive Sleep Apnea Using Dual-Tree Complex Wavelet Transform and Adaptive Neuro-Fuzzy Inference System 2

ECG Signal-Based Feature Identification of Obstructive Sleep...

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2nd Jordanian International Biomedical engineering Conference, JIBEC 2024

作者： Bassam, Al-Naami Al-Zaben, Awad Visconti, Paolo De Fazio, Roberto Rawash, Yahia The Hashemite University Engineering Faculty Biomedical Engineering Department Zarqa Jordan Yarmouk University Hijjawi Faculty For Engineering Technology Biomedical Systems and Medical Informatics Department Jordan University of Salento Lecce Italy University of Salento Dept. of Innovation Engineering Lecce Italy Hashimaite University Engineering Faculty Biomedical Engineering Department Jordan Center for Biomolecular Nanotech. IIT Dept. of Innovation Engineering Arnesano Italy

ISBN: (纸本)9798331539542

Obstructive sleep apnea (OSA) is a common disease that affects a large number of people around the world. It could be prevented if diagnosed early, but many cases go undetected due to the cost and limitations of home overnight polysomnography (PSG) systems. In this research, we propose a new diagnostic method for detecting the OSA disease using a feature extraction and classification approach from the electrocardiograph (ECG) signal only. The ECG can be easily extracted at home in a comfortable and minimally invasive way by anyone;then, the Dual-Tree Complex Wavelet Transform (DTCWT) is used to denoise the ECG signal. Five features were extracted, and the classification process was performed using the Adaptive Neuro Fuzzy Inference System (ANFIS). © 2024 IEEE.

关键词： Sleep research

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Encryption Algorithm for Securing Non-Disclosure Agreements in Outsourcing Offshore Software Maintenance

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Computers, Materials & Continua 2022年第11期73卷 3827-3845页

作者： Atif Ikram Masita Abdul Jalil Amir Bin Ngah Nadeem Iqbal Nazri Kama Azri Azmi Ahmad Salman Khan Yasir Mahmood Assad Alzayed Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala TerengganuMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Department of Software Engineering Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Advanced Informatics Department Razak Faculty of Technology and InformaticsUniversiti Teknologi Malaysia54100Kuala LumpurMalaysia Computer Science and Information Systems Department College of Business Studies Public Authority for Applied Education and Training(PAAET)AdailiyaKuwait

Properly created and securely communicated,non-disclosure agreement(NDA)can resolve most of the common disputes related to outsourcing of offshore software maintenance(OSMO).Occasionally,these NDAs are in the form of *** the work is done offshore,these agreements or images must be shared through the Internet or stored over the *** breach of privacy,on the other hand,is a potential threat for the image owners as both the Internet and cloud servers are not void of *** article proposes a novel algorithm for securing the NDAs in the form of *** an agreement is signed between the two parties,it will be encrypted before sending to the cloud server or travelling through the public network,the *** the image is input to the algorithm,its pixels would be scrambled through the set of randomly generated rectangles for an arbitrary amount of *** confusion effects have been realized through an XOR operation between the confused image,and chaotic ***,5D multi-wing hyperchaotic system has been employed to spawn the chaotic vectors due to good properties of chaoticity it *** machine experimentation and the security analysis through a comprehensive set of validation metric vividly demonstrate the robustness,defiance to the multifarious threats and the prospects for some real-world application of the proposed encryption algorithm for the NDA images.

关键词： Non-disclosure agreement encryption decryption secret key chaoticmap confusion diffusion

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Optimizing ERP Deployment with Intelligent Tutoring systems

Optimizing ERP Deployment with Intelligent Tutoring Systems

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International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Santo Fernandi Wijaya Jansen Wiratama Ririn Ikana Desanti Information Systems Department Faculty of Engineering and Informatics Universitas Multimedia Nusantara Banten Indonesia

ISBN: (数字)9798331507022

ISBN: (纸本)9798331507039

The rapid digital transformation in industries has made Artificial Intelligence (AI) an essential tool for improving the accuracy and speed of strategic decision-making, ultimately enhancing company performance. Using Enterprise Resource Planning (ERP) systems is crucial and necessary for automating business operations toward digitalization. However, many companies still face challenges with technological innovation, leading to ERP implementation failures. While previous research has addressed Critical Success Factors (CSF) for ERP success, further empirical studies are needed, particularly from a technological adoption perspective, emphasizing the role of Intelligent Tutoring systems (ITS). ITS can analyze data and predictive capabilities to boost productivity and support faster, more accurate decision-making for management. This research employed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), conducted experimental testing with respondents, and processed data using the Smart-PLS method to identify critical factors. This research results in developing an intelligent tutoring systems model to measure and provide recommendations for improvement to achieve successful ERP implementation in a company.

关键词： Surveys Productivity Technological innovation Accuracy Decision making Prototypes Companies Artificial intelligence Testing Systematic literature review

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On the Gains of On-Device and Hybrid AI: A Qualitative Study

On the Gains of On-Device and Hybrid AI: A Qualitative Study

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International Workshop on Research and Education in Mechatronics (REM)

作者： Marco Wagner Ansgar Meroth Engineering Informatics Engineering Faculty Heilbronn University Heilbronn Germany Automotive Systems Engineering Engineering Faculty Heilbronn University Heilbronn Germany

ISBN: (数字)9798331505974

ISBN: (纸本)9798331505981

Artificial Intelligence has gained a lot of attention in both the academic and industrial community. While its many benefits are indisputable, the systems built on AI come with some drawbacks as well. Many of these drawbacks are tied to the fact that cloud-computing plays a major role in deploying AI-based systems and services. In this paper, an alternative approach, namely on-device AI and especially its extension hybrid AI are categorized, discussed and compared in order to give both researchers and practitioners some useful guardrails on the way towards more personalized, sustainable and stable systems.

关键词： Mechatronics Education Artificial intelligence

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Gamification Model for the Affective Commitment of the Technology Team in a Financial Institution

Gamification Model for the Affective Commitment of the Techn...

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International Conference on Computational Intelligence and Communication Networks (CICN)

作者： Daniel-Antonio Farías-Güich Ciro Rodriguez Faculty of Systems Engineering and Informatics National University of San Marcos Lima Peru

ISBN: (数字)9798331505264

ISBN: (纸本)9798331505271

This research explores the application of a gamification model as a tool to reduce the deficit in affective commitment within an IT Squad from the Technology Tribe of a financial entity in Lima, Peru. Issues negatively impacting the team's performance were identified, such as lack of communication, interpersonal conflicts, and lack of recognition, among others. The gamification model proposed in this research was designed with the aim of increasing motivation, improving interpersonal relationships, and fostering more effective collaboration, based on theories about gamification models and organizational commitment, as well as using role-playing games as a tool to develop social skills. The results of the research showed a 25% increase in the affective commitment of the IT Squad, concluding that the application of a gamification model is a viable strategy to improve the performance of IT workers.

关键词： Training Computational modeling Role playing games Collaboration Games Communication networks Computational intelligence

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Vehicle type recognition: a case study of MobileNetV2 for an image classification task 28th

Vehicle type recognition: a case study of MobileNetV2 for an...

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28th International Conference on Knowledge Based and Intelligent information and engineering systems, KES 2024

作者： Kobiela, Dariusz Groth, Jan Hajdasz, Michal Erezman, Mateusz Gdansk University of Technology Faculty of Electronics Telecommunications and Informatics Department of Software Engineering Gabriela Narutowicza 11/12 Gdansk80-233 Poland Gdansk University of Technology Faculty of Electronics Telecommunications and Informatics Department of Algorithms and Systems Modelling Gabriela Narutowicza 11/12 Gdansk80-233 Poland Gdansk University of Technology Faculty of Electronics Telecommunications and Informatics Gabriela Narutowicza 11/12 Gdansk80-233 Poland

The goal of the research was to demonstrate the full data science lifecycle through a use case of the MobileNetv2 model for vehicle image classification task using various validation and test sets, each with different difficulty level. Diverse model variations were employed, each designed to recognize images of ground vehicles and classify them into one of five possible classes: car, truck, motorcycle, bicycle, or bus. In terms of validation accuracy, the highest results were obtained by the model trained with uniformly designed train and val sets (with data normalization and augmentation), where train set also contained validation set. This model also obtained the highest accuracy results on both test sets. The superiority of MODEL 3 BASELINE is confirmed by other metrics as well: test loss, f1-score, AUC and confusion matrices (for both test sets). Results between MODEL 1 BASELINE and MODEL 2 BASELINE differed according to the test set 1 and 2 and other metrics and it was not possible to declare the superiority of one method of datasets preparation over another (original class distribution [no data normalization and no data augmentation] versus uniformly designed [with data normalization and augmentation]). The article also presents challenges and findings - the problems, key issues, and their solutions that arose during the process of data collection and tagging, as well as the preparation and evaluation of the model. © 2024 The Authors.

关键词： Classification (of information)

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Mode Division Multiplexing Bidirectional Transmission System using Double Clad Fiber for Mobile In-Building Solutions 46

Mode Division Multiplexing Bidirectional Transmission System...

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46th International Conference on Telecommunications and Signal Processing, TSP 2023

作者： Mohamed, Ahmed S. Udvary, Eszter Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Networked Systems and Services BudapestH-1111 Hungary ELKH-BME Information Systems Research Group Budapest1117 Hungary

ISBN: (纸本)9798350303964

This paper shows the conceptual model of the possibility of simultaneously transmitting data and power on the same optical fiber by adopting the Power Over Fiber PWoF concept and Mode Division Multiplexing MDM. MDM is the data transmission multiplexing scheme of choice where two modes of light are considered;one mode carries the downlink, while the other mode carries the uplink information. Adopting the PWoF, remote devices can be powered by the optical energy transferred on the same optical fiber. Double Clad Fibers DCF are introduced as the transmission medium. DCF consists of the core, which is a few-mode fiber core capable of handling the two needed modes, the inner cladding which has a relatively large diameter and is capable of handling the optical power, and the outer cladding. The proposed system can reduce the complexity and the operations cost, suitable to be used in In-Building Solutions IBS. © 2023 IEEE.

关键词： Transmissions

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DOA-Estimations-Based 3D Geolocations Using Factor Graphs 11

DOA-Estimations-Based 3D Geolocations Using Factor Graphs

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2023 IEEE 11th International Conference on Information, Communication and Networks, ICICN 2023

作者： Qian, Shen Cheng, Meng Kanagawa University Faculty of Informatics Department of Applied Systems and Mathematics Yokohama Japan Shanghai Normal University The College of Information Mechanical and Electrical Engineering Shanghai China

ISBN: (纸本)9798350314014

This paper proposes direction of arrival (DOA)-estimation-based three-dimensional (3D) positioning techniques using factor graphs. The multiple signal classification (MUSIC), root-MUSIC, and estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithms are used to estimate the DOA of the signals received by multiple sensors. A factor graph (FG) detector updates and refines the measured DOA for obtaining the target positions. Since only the mean and the variance of the DOA are needed for the factor graph process, the burden of the data transmission of the uplink from the sensors to the fusion center and the complexity of the positioning is reduced significantly. The effectiveness of the proposed method is demonstrated through simulations. No matter which DOA estimation method is used, MUSIC, root-MUSIC, or ESPRIT, FG algorithms achieve higher positional accuracy compared to the linear least square (LS) positioning solution in terms of the root mean square error (RMSE). © 2023 IEEE.

关键词： Multiple signal classification

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Deep learning-based blood pressure measurement on a low-power microcontroller 14

Deep learning-based blood pressure measurement on a low-powe...

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14th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2023

作者： Tóth, Bálint Torma, Szabolcs Nagy, Ákos Szegletes, Luca Department of Measurement and Information Systems Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary

ISBN: (纸本)9798350325652

Blood pressure is one of the most vital signals characterizing the health status of the human body. Based on this physiological data, many current and future diseases can be detected. Therefore, having a device that can continuously measure blood pressure without a cuff or medical intervention would be highly beneficial. This study aims to investigate noninvasive blood pressure measurement with the help of a low-power microcontroller, namely STM32F446RE. These measuring methods are based on deep neural networks and utilize externally measured photoplethysmography (PPG) and electrocardiogram (ECG) signals. The performance of the proposed models is compared to similar solutions from the literature and inspected for memory usage and runtime. The results of this work show that a convolutional layer-based model can be used for proper blood pressure estimation in such an energy-efficient device. © 2023 IEEE.

关键词： Blood pressure

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A novel approach to predicting liquefaction-induced settlements using Kolmogorov–Arnold Networks (KANs)

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Discover Geoscience 2024年第1期2卷 1-14页

作者： Karakaş, Seyidcem Garanti BBVA Payment Systems İstanbul Turkey Faculty of Computer and Informatics Engineering Istanbul Technical University Istanbul Turkey

Soil liquefaction refers to the loss of strength and bearing capacity of soil under dynamic loads. Structures built on liquefied soils experience settlement. In this study, the newly developed Kolmogorov–Arnold Networks (KAN) method, an innovative artificial neural network technique, was utilized to predict liquefaction-induced settlement. The KAN method, which extends beyond the traditional Multi-Layer Perceptron (MLP) approach, was compared with the Random Forest method for benchmarking purposes. Using data derived from laboratory and field studies, models were constructed using both methods, and their performances were analyzed. According to the results, the KAN model outperformed the RF model in terms of R2, MAE, MSE, and RMSE metrics. Additionally, the feature importance analysis on the KAN model identified cyclic stress ratio (csr) and corrected SPT blow count (n1_60) as the most significant variables. These results underscore the potential of the KAN method in enhancing predictive accuracy and reliability in geotechnical applications, paving the way for its broader acceptance and implementation in real-world scenarios.

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