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Stationary, continuous, and discrete wavelet-based approach for secure medical image transmission

Research on Biomedical engineering 2023年第1期39卷 167-178页

作者： Sayah, Moad Med Redouane, Kafi Med Amine, Khaldi Electrical Engineering Laboratory Department of Electronics Faculty of Sciences and Technology University of Kasdi Merbah Ouargla30000 Algeria Computer Science Department Faculty of Sciences and Technology University of Kasdi Merbah Ouargla30000 Algeria

Purpose: Watermarking is one of the techniques used to protect multimedia data, and images in particular, from malicious attacks by inserting a signature into these images. However, traditional watermarking schemes encounter limitations for sensitive images such as medical images. Methods: In this work, a robust and blind watermarking approach is proposed to secure medical images exchanged in telemedicine. Marking medical images allows precise authentication of the patient and avoids confusing scans and thus avoiding diagnostic errors that can have serious consequences. In this approach, the frequency content of the image is acquired using three different transforms. Schur decomposition is then applied to the low-frequency sub-bands. Finally, the obtained upper triangular matrix values are modifier to integrate the watermark bits. Result and conclusion: Imperceptibility and robustness experimental results show that the proposed methods adequately maintain a significant quality of watermarked images and are remarkably robust against several conventional attacks. Indeed, the average peak signal-to-noise ratio (PSNR) obtained is 44.90 dB which proves that the integration process generates few distortions to the original image. For the robustness, the obtained results show that the watermark is resistant to the most common attacks used in watermarking with a normalized cross correlation rate higher than 0.9 for the majority of the attacks. © 2023, The Author(s), under exclusive licence to The Brazilian Society of Biomedical engineering.

关键词： Discrete wavelet transforms

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Different architectures of thin film bilayers based on TiO2 and CuO for green hydrogen generation

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International Journal of Hydrogen Energy 2025年 136卷 1073-1085页

作者： Banaś-Gac, Joanna Radecka, Marta Llobet, Eduard Partyka-Jankowska, Ewa Zakrzewska, Katarzyna Faculty of Computer Science Electronics and Telecommunications AGH University of Krakow Krakow Poland Faculty of Materials Science and Ceramics AGH University of Krakow Krakow Poland Department of Electronic Electrical and Automatic Engineering Rovira i Virgili University Tarragona Spain SOLARIS National Synchrotron Radiation Centre Jagiellonian University Krakow Poland

Green hydrogen becomes one of the most important of all other forms due to ecological issues, described in directives requiring the transformation to energy sources with the lowest possible carbon footprint. The application of the PhotoElectrochemical Cell where hydrogen is produced with the direct use of solar energy is the best solution. Bilayer and multilayered systems based on CuO, especially in combination with TiO2 seem to be the most frequently studied of all heterostructured nanomaterials when considering green hydrogen generation. The interface created between rough surface of CuO and smooth TiO2 surface ensures the highest photocurrent when the top layer is of about 150 nm. For CuO(top)/TiO2 heterojunction characterized by rough/rough interface, photoeletrochemical performance also improves with increasing thickness of the top layer up to 100 nm. The cathodic character of the photocurrent is observed for both TiO2(top)/CuO and CuO(top)/TiO2 bilayers. © 2025 The Authors

关键词： Solar energy

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The Importance of Including Sustainable Development Goals (SDGs) in the Educational Process of Engineers and electrical Engineers 65

The Importance of Including Sustainable Development Goals (S...

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65th IEEE Annual International Scientific Conference on Power and electrical engineering of Riga Technical University, RTUCON 2024

作者： Patlins, Antons Institute of Industrial Electronics Electrical Engineering and Energy Riga Technical University Faculty of Computer Science Information Technology and Energy Riga Latvia

ISBN: (纸本)9798350365771

The integration of Sustainable Development Goals (SDGs) into the educational process of engineers and electrical engineers is pivotal for fostering a sustainable future. This paper discusses the significance of embedding SDGs in engineering education and presents methodologies for incorporating these goals into various study subjects. The study explores current trends, proposes innovative pedagogical approaches, and provides practical recommendations for educators and institutions. The outcomes suggest that incorporating SDGs not only enhances the relevance of engineering education but also equips future engineers with the necessary skills and mindset to address global sustainability challenges. © 2024 IEEE.

关键词： Sustainable development goals

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Deep Learning Algorithms for EEG-Based Driver Drowsiness Detection: A Comparative Investigation 10

Deep Learning Algorithms for EEG-Based Driver Drowsiness Det...

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10th IEEE Information Technology International Seminar, ITIS 2024

作者： Hasan, Md Mahmudul Mahfuj Hossain, Mirza Sulaiman, Norizam Islam, Md Nahidul Khandaker, Sayma Universiti Malaysia Pahang Al-Sultan Abdullah Faculty of Electrical and Electronics Engineering Technology Pahang Malaysia Jashore University of Science and Technology Department of Computer Science and Engineering Jashore Bangladesh

ISBN: (纸本)9798331521295

Due to the significant variability in electroencephalogram (EEG) signals across individuals and recording sessions, developing a calibration-free system for detecting driver drowsiness presents a considerable challenge. While numerous deep learning techniques have been employed to analyze EEG signals for this purpose, most existing studies rely on deep learning models with limited success in accurately detecting drowsiness. In this research, we explored the application of five deep learning algorithms such as Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Gated Recurrent Units (GRU), and Long Short-Term Memory (LSTM), to improve the detection of driver drowsiness. Our applied models achieve detection accuracies of 73.46% for ANN, 80.09% for CNN, 65.74% for RNN, 83.95% for GRU, and 77.62% for LSTM across 11 subjects, outperforming conventional baseline approaches and state-of-the-art deep learning methods. Notably, the GRU model demonstrated superior accuracy in recognizing drowsiness from EEG signals compared to other applied models. © 2024 IEEE.

关键词： Convolutional neural networks

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Factors Influencing Knowledge Sharing in Prison: A Review and AHP Analysis 6

Factors Influencing Knowledge Sharing in Prison: A Review an...

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6th International Conference on computer and Informatics engineering, IC2IE 2023

作者： Imandeka, Ejo Hidayanto, Achmad Nizar Suhartanto, Heru Pidanic, Jan University of Indonesia Faculty of Computer Science Depok Indonesia University of Pardubice Faculty of Electrical Engineering and Informatics Pardubice Czech Republic

ISBN: (纸本)9798350345162

Knowledge sharing has been recognized as the most critical factor in successful knowledge management. Knowledge sharing in prison is a complicated topic that frequently faces resource restrictions, stigma and isolation, communication hurdles, and other security concerns. Moreover, resources for knowledge sharing in a secure environment are still few. This research investigates the critical factors for knowledge sharing in prisons. This research uses the Kitchenham approach with five reputable publishers from 2018 to 2023. There are 1284 articles in the initial phase and 25 in the final phase. Critical factors were ranked using Analytical Hierarchy Process (AHP) with the Triple-helix approach to the representatives of academics, policymakers, and the community in the Indonesian context. The critical knowledge-sharing factors are leadership support, organizational culture, organizational structure, incentives, and individual beliefs. However, acknowledging the critical factors can aid in improving the knowledge-sharing system in prison and changing the criminal justice system. © 2023 IEEE.

关键词： analytic hierarchy process critical factors knowledge sharing prison

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Analysis and Modeling of the Hybrid Vessel's electrical Power System

Analysis and Modeling of the Hybrid Vessel's Electrical Powe...

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2024 IEEE Power and Energy Society General Meeting, PESGM 2024

作者： Mosselaar, Matthijs Malbasic, Zoran Fu, Aihui Lekic, Aleksandra Delft University of Technology Faculty of Electrical Engineering Mathematics and Computer Science Delft Netherlands Power conversion & hybrid solutions Alewijnse Netherlands

With the maritime industry poised on the cusp of a hybrid revolution, the design and analysis of advanced vessel systems have become paramount for engineers. This paper presents AC and DC electrical hybrid power system models in ETAP, the simulation software that can be adapted to engineer future hybrid vessels. These models are also a step towards a digital twin model that can help in troubleshooting and preventing issues, reducing risk and engineering time. The testing of the models is focused on time domain analysis, short-circuit currents, and protection & coordination. The models are based on actual vessels and manufacturer parameters are used where available. © 2024 IEEE.

关键词： Short circuit currents

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ParaGnosis: A Tool for Parallel Knowledge Compilation 29th

ParaGnosis: A Tool for Parallel Knowledge Compilation

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29th International Symposium on Model Checking Software, SPIN 2023, co-located with European Joint Conferences on Theory and Practice of Software, ETAPS 2023

作者： Dal, Giso H. Laarman, Alfons Lucas, Peter J. F. Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede Netherlands Leiden Institute of Advanced Computer Science Leiden University Leiden Netherlands

ISBN: (纸本)9783031321566

ParaGnosis (https://***/10.5281/zenodo.7312034, https://***/badge/latestdoi/560170574, Alternative url: https://***/gisodal/paragnosis, Demo url: https://***/gisodal/paragnosis/blob/main/*** ) is an open-source tool that supports inference queries on Bayesian networks through weighted model counting. In the knowledge compilation step, the input Bayesian network is encoded as propositional logic and then compiled into a knowledge base in decision diagram representation. The tool supports various diagram formats, including the Weighted-Positive Binary Decision Diagram (WPBDD) which can concisely represent discrete probability distributions. Once compiled, the probabilistic knowledge base can be queried in the inference step. To efficiently implement both steps, ParaGnosis uses simulated annealing to split the knowledge base into a number of partitions. This further reduces the decision diagram size and crucially enables parallelism in both the compilation and the inference steps. Experiments demonstrate that this partitioned approach, in combination with the WPBDD representation, can outperform other approaches in the knowledge compilation step, at the cost of slightly more expensive inference queries. Additionally, the tool can attain 15-fold parallel speedups using 64 cores. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Bayesian networks

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Sprayer System on Autonomous Farming Drone Based on Decision Tree

Sprayer System on Autonomous Farming Drone Based on Decision...

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2024 International Conference on Artificial Intelligence and Mechatronics System, AIMS 2024

作者： Sitompul, Erwin Gubarda, Muhammad Radiga Sihombing, Poltak Simarmata, Tualar Turnip, Arjon University Faculty of Electrical Engineering Cikarang Indonesia Padjadjaran University Department of Electrical Engineering Sumedang Indonesia Universitas Sumatera Utara Dept. of Computer Science Medan Indonesia Universitas Padjadjaran Faculty of Agriculture Sumedang Indonesia Universitas Padjadjaran Department of Electrical Engineering Sumedang Indonesia

ISBN: (纸本)9798350350524

Agriculture in Indonesia faces various challenges, including inequality of productivity in various regions. One of the proposed solutions is the utilization of drones to increase the efficiency of the agricultural watering process. Machine learning technology is also used in classifying drone sprayers. This study used the decision tree method to classify the strength of watering with an accuracy rate of 98.9%. The classification analysis is based on measurements of the drone's altitude, wind speed and speed sensors. The results of this study contribute to improving precision control on agricultural watering using drones, opening up opportunities for significant productivity improvement in Indonesia's agricultural sector. © 2024 IEEE.

关键词： Decision trees

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An Efficient Hash Computing Unit for Kyber Algorithm 15

An Efficient Hash Computing Unit for Kyber Algorithm

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15th IEEE International Conference on ASIC, ASICON 2023

作者： Wei, Hongshuai Zhang, Yuejun Zhang, Huihong Wang, Yang Yuan, Tengfei Wang, Chengjie Wang, Pengjun Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo315211 China Wenzhou University College of Electrical and Electronic Engineering Wenzhou325035 China

ISBN: (纸本)9798350312980

In the post-quantum Kyber algorithm, the Hash computation directly affects the processing speed of key generation, noise polynomial, and key exchange processes. To address the issues of multiple types of Hash computations, complex variables, and high resource consumption, this paper proposes an efficient Hash computation unit. The proposed scheme first establishes independent data interaction units through the sponge construction, achieving higher parallelism by combining the logically merged Keccak-1600 permutation function. Subsequently, the central binomial distribution sampling and optimized rejection sampling are integrated into the Hash unit, resulting in a compact and highly flexible Hash computation unit. Finally, the scheme is tested and verified under the Taiwan Semiconductor Manufacturing Company (TSMC) 65nm process. The proposed method consumes only 36.4K equivalent logic gates, and experimental results show that the Hash computation cycle is reduced by up to 30%, rejection sampling cycle by 16%, making it more efficient compared to related implementations. © 2023 IEEE.

关键词： CRYSTALS-KYBER hash computation unit quantum-resistant cryptography sampler sponge

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A Data-Driven Probabilistic Power Flow Analysis Considering Voltage-Dependent Loads 24

A Data-Driven Probabilistic Power Flow Analysis Considering ...

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24th EEEIC International Conference on Environment and electrical engineering and 8th I and CPS Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2024

作者： Zandrazavi, Seyed Farhad Shafie-Khah, Miadreza Pashaei, Meysam Arias, Nataly Bañol Soeiro, Thiago Batista School of Technology and Innovations University of Vaasa Vaasa Finland University of Twente Faculty of Electrical Engineering Mathematics and Computer Science Enschede Netherlands

ISBN: (纸本)9798350355185

Probabilistic power flow analysis (PPFA) stands as a promising method for assessing the steady-state performance of distribution networks (DNs) amidst uncertainties associated with renewable energy sources, particularly wind power units (WPUs). However, the reliability of the PPFA results hinges significantly on the accuracy of the power flow model. This paper proposes a new approach to PPFA that integrates voltage-dependent load (VDL). Although incorporating VDL in PPFA formulation enhances the precision of the model, it introduces additional computational complexity due to the introduction of new nonlinear terms into the optimization problem. Therefore, initially, a dataset of wind speed measurements is fitted to a Weibull probability distribution function (PDF). Subsequently, a new nonlinear model is developed, which integrates Monte Carlo (MC) simulation along with the specified PDF for PPFA, accounting for VDL effects. Finally, the proposed model is efficiently convexified using Newton's generalized binomial theorem, piecewise linearization, and appropriate approximations to extract the corresponding linear programming (LP) model. This LP model is then tested on a modified WPU-integrated 33-bus DN, revealing that the inclusion of VDL significantly influences the PPFA results. A comparative analysis between PPFA models with and without VDL incorporation illustrates that overlooking VDL can lead to underestimation of power losses and voltage drops in the analysis. © 2024 IEEE.

关键词： Load flow optimization

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