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2nd IEEE International Conference on electronic engineering, ICEEM 2021

作者： Souror, Samia El-Fishawy, Nawal Badawy, Mohammed Menoufia University Faculty of Electronic Engineering Computer Science and Engineering Department Menouf Egypt

ISBN: (纸本)9781665418423

Cryptographic algorithms are playing an important role in the information security field. Strong and unbreakable algorithms provide high security and good throughput. The strength of any encryption algorithm is basically based on the degree of difficulty to obtain the encryption key by such cyber-attacks as brute. It is supposed that the bigger the key size, the more difficult it is to compute the key. But increasing the key size will increase both the computational complexity and the processing time of algorithms. In this paper, we proposed a reliable, effective, and more secure symmetric stream cipher algorithm for encryption and decryption called Symmetric Cipher based on Key Hashing Algorithm (SCKHA). The idea of this algorithm is based on hashing and splitting the encryption symmetric key. Hashing the key will hide the encrypted key to prevent any intruder from forging the hash code, and, thus, it satisfies the purpose of security, authentication, and integrity for a message on the network. In addition, the algorithm is secure against a brute-force attack by increasing the resources it takes for testing each possible key. Splitting the hashed value of the encryption key will divide the hashed key into two key chunks. The encryption process performed using such one chunk based on some calculations on the plaintext. This algorithm has three advantages that are represented in computational simplicity, security and efficiency. Our algorithm is characterized by its ability to search on the encrypted data where the plaintext character is represented by two ciphertext characters (symbols). © 2021 IEEE.

关键词： Computational efficiency

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Nonlinear Contact Behavior in MoS2 Field Effect Transistors at Cryogenic Temperature

Nonlinear Contact Behavior in MoS2 Field Effect Transistors ...

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International Conference on Solid-State and Integrated Circuit Technology

作者： Shihab Ahammed Mansun Chan Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Kowloon Hong Kong

ISBN: (数字)9798350361834

ISBN: (纸本)9798350361841

The performance of MoS 2 -based devices depends on contact resistance, influenced by the Schottky barrier. Typically, metal-contacted MoS 2 devices show non-ohmic behavior around 77 K due to excessive Schottky barrier height and wide depletion region, limiting carrier injection. This study explores n-type MoS 2 -based Ni-contacted field effect transistors from 300 K to 4 K to find out the behavior of carrier injection. We observe ohmic conduction from 300 K to 77 K due to the minimized Schottky barrier. The low SBH justifies the enhanced carrier injection, vital for reliable low-temperature operation. However, the transition from linear to nonlinear behavior below 77 K indicates the domination of contact resistance. This investigation provides critical insights into carrier injection at various temperatures, advancing the understanding of metal-TMD interfaces.

关键词： Resistance Performance evaluation Temperature distribution Schottky barriers Field effect transistors Cryogenics Contact resistance Ohmic contacts Sulfur Molybdenum

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CFReID: Continual Few-shot Person Re-Identification

arXiv

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arXiv 2025年

作者： Ni, Hao Gao, Lianli Zeng, Pengpeng Shen, Heng Tao Song, Jingkuan Center for Future Media School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Center for Future Media School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Department of Information Engineering and Computer Science Tongji University China

Real-world surveillance systems are dynamically evolving, requiring a person Re-identification model to continuously handle newly incoming data from various domains. To cope with these dynamics, Lifelong ReID (LReID) has been proposed to learn and accumulate knowledge across multiple domains incrementally. However, LReID models need to be trained on large-scale labeled data for each unseen domain, which are typically inaccessible due to privacy and cost concerns. In this paper, we propose a new paradigm called Continual Few-shot ReID (CFReID), which requires models to be incrementally trained using few-shot data and tested on all seen domains. Under few-shot conditions, CFREID faces two core challenges: 1) learning knowledge from few-shot data of unseen domain, and 2) avoiding catastrophic forgetting of seen domains. To tackle these two challenges, we propose a Stable Distribution Alignment (SDA) framework from feature distribution perspective. Specifically, our SDA is composed of two modules, i.e., Meta Distribution Alignment (MDA) and Prototype-based Few-shot Adaptation (PFA). MDA aligns seen and unseen distributions through a prior distribution and employs meta-learning to simulate the training-testing process, enabling the model to perform domain adaptation with few-shot data in new domains. PFA incorporates a prototype anchor loss to enhance the learning signals, and utilizes prototype-guided feature learning to stabilize the source domain feature distribution while learning discriminative features, aiming to mitigate catastrophic forgetting. To support the study of CFReID, we establish an evaluation benchmark for CFReID on five publicly available ReID datasets. Extensive experiments demonstrate that our SDA can enhance the few-shot learning and anti-forgetting capabilities under few-shot conditions. Notably, our approach, using only 5% of the data, i.e., 32 IDs, significantly outperforms LReID’s state-of-the-art performance, which requires 700 to 1,000 IDs. So

关键词： Zero-shot learning

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An Attention-PiDi-UNet and Focal Active Contour loss for Biomedical Image Segmentation

An Attention-PiDi-UNet and Focal Active Contour loss for Bio...

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2022 RIVF International Conference on Computing and Communication Technologies, RIVF 2022

作者： Trinh, Minh-Nhat Nham, Do-Hai-Ninh Pham, Van-Truong Tran, Thi-Thao School of Electrical and Electronic Engineering Hanoi University of Science and Technology Department of Automation Engineering Hanoi Viet Nam School of Applied Mathematics and Informatics Hanoi University of Science and Technology Hanoi Viet Nam

ISBN: (纸本)9781665461665

Biomedical image analysis has been of paramount importance in modern computer vision recently. While up-to-date procedures have notched up success in medical imaging, there is still necessity to optimise the network and the loss function. Motivated by the PiDiNet architecture and the Active Contour methods, we propose a new Attention-PiDi-UNet architecture and a new Focal Active Contour loss. Our proposed method is evaluated on the three popular datasets: the MRI cardiac ACDC dataset (3-D images), the Skin Lesion ISIC 2018 dataset and the PH2 dataset (both in 2-D images). Several experiments have comfirmed our proposed method effectiveness with outstanding segmentation results. © 2022 IEEE.

关键词： Magnetic resonance imaging

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Smart Cost-based Charging Profile Management and Optimisation for Multiple Electric Vehicles in Power Grids

Smart Cost-based Charging Profile Management and Optimisatio...

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International Conference on Power electronics Systems and Applications (ICPESA)

作者： Muhamad Danish Karlin Bin Mohamed Isa Huajun Wang Rui Liang Tenghao Ji Yajie Jiang Kaiwen Chen School of Electrical and Electronic Engineering Nanyang Technological University Singapore Department of Electrical and Electronic Engineering Hong Kong Polytechnic University Hong Kong China Department of Electrical and Computer Engineering University of Michigan Ann Arbor USA

ISBN: (数字)9798350365801

ISBN: (纸本)9798350365818

With the advent of the Internet-of-Things (IoT) and smart grid, further optimisation potential can be explored from the load side in the field of power management. it opens more opportunities for load management to be done in a more granular fashion. In this work, one method for smart load management of electric vehicle (EV) charging profile is proposed. More specifically, this is done by scheduling the charging sessions during periods of lower electricity spot prices. This results in lower EV charging costs. The resilience of the power grid is also strengthened by shifting the EV charging loads to a period of lower electricity demand. This optimised charging scheme is applied in a multi-EV system in MATLAB. The optimisation results are provided to verify the efficacy of the proposed charging scheme.

关键词： Costs Electricity Power system management Load management Electric vehicle charging Power electronics Smart grids

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Heart Disease Risk Assessment and Prediction: A Robust Ensemble Approach with Extra Tree Classifier 2

Heart Disease Risk Assessment and Prediction: A Robust Ensem...

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2nd International engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2023

作者： Talukder, Simul Hasan Mondal, Sohag Kumar Aljaidi, Mohammad Sulaiman, Rejwan Bin Islam, Taminul Bangladesh Atomic Energy Regulatory Authority Dhaka Bangladesh Electrical and Electronic Engineering Khulna University of Engineering and Technology Khulna Bangladesh Khulna Bangladesh Zarqa University Faculty of Information Technology Department of Computer Science Zarqa Jordan School of Computer Science and Technology Northumbria University Tayne United Kingdom Southern Illinois University Department of Computer Science CarbondaleIL United States

ISBN: (纸本)9798350373363

Heart disease remains a formidable global health challenge, affecting countless individuals and placing a substantial strain on healthcare systems worldwide. Various factors, including exercise, diabetes, age, gender, dietary habits, weight, height, and even emotional well-being, influence an individual's cardiac health. Detecting heart disease early and making precise predictions regarding its risk factors are pivotal in assessing, managing, and preventing its occurrence, ultimately leading to improved patient outcomes. In this research, a range of promising preprocessing techniques and a meticulously tuned ensemble of ten machine learning models, including Extra Trees (ET), Decision Trees (DT), Random Forest (RF), Logistic Regression (LR), Extremely Gradient Boosting (EGB), AdaBoost (AB), Support Vector Machine (SVM), Ridge Classifier (RC), Light Gradient Boosting (LGB), and Gradient Boosting (GB), were employed to analyze a publicly available heart assessment dataset. The models' robustness was assessed through a rigorous 10 k-fold validation process. Seven comprehensive evaluation metrics, encompassing accuracy, AUC, precision, recall, F1 Score, kappa, MCC, were used to gauge the models' performance and reliability. Impressively, ET model outshone the rest, achieving the highest accuracy (0.9559 ± 0.0006), AUC (0.9870 ± 0.0003), precision (0.9262 ± 0.0012), recall (0.9847 ± 0.0012), F1 Score (0.9546 ± 0.0006), kappa (0.9119 ± 0.0012), MCC (0.9135 ± 0.0012), and showcasing the lowest standard deviation. © 2023 IEEE.

关键词： Adaptive boosting

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Fundamental Limits of Doppler Shift-Based, ToA-Based,and TDoA-Based Underwater Localization

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IEEE/CAA Journal of Automatica Sinica 2023年第7期10卷 1637-1639页

作者： Zijun Gong Cheng Li Ruoyu Su Hong Kong University of Science and Technology(Guangzhou) IOT ThrustGuangzhou 511400 Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyHong Kong 999077China Faculty of Engineering and Applied Science Memorial University of NewfoundlandNewfoundland A1B 3X5Canada School of Internet of Things Nanjing University of Posts and TelecommunicationsNanjing 210003China

Dear Editor,This paper is concerned with the underwater localization based on acoustic signals. Specifically, we will focus on the search of an underwater target that can constantly broadcast a beacon signal, such as a black box. Common measurements for localization are Doppler shift [1], time of arrival(ToA) [2]–[4], time difference of arrival(TDoA) [5], [6], angle of arrival(AoA) [7], etc.

关键词： TDoA ToA underwater

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The Intersection of Genetics and Neuroimaging: A Systematic Review of Imaging Genetics in Neurological Disease for Personalized Treatment

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Journal of Molecular Neuroscience 2025年第2期75卷 1-26页

作者： Mashhour, Mahinaz A. Youssef, Ibrahim Wahed, Manal Abdel Mabrouk, Mai S. Biomedical Engineering Department Misr University for Science and Technology Giza Egypt Systems and Biomedical Engineering Department Cairo University Giza Egypt Center for Informatics Science (CIS) School of Information Technology and Computer Science Nile University Giza Egypt

Imaging genetics is one of the important keys to precision medicine that leads to personalized treatment based on a patient’s genetics, phenotype, or psychosocial characteristics. It deepens the understanding of the mechanisms through which genetic variations contribute to neurological and psychiatric disorders. This systematic review overviews the methods and applications of imaging genetics in the context of neurological diseases, mentioning its potential role in personalized medicine. Following PRISMA guidelines, this review systematically analyzes 28 studies integrating genetic and neuroimaging data to explore disease mechanisms and their implications for precision medicine. Selected research included multiple neurological disorders, including frontotemporal dementia, Alzheimer’s disease, bipolar disorder, schizophrenia, Parkinson’s disease, and others. Voxel-based morphometry was the most common imaging technique, while frequently examined genetic variants included APOE, C9orf72, MAPT, GRN, COMT, and BDNF. Associations between these variants and regional gray matter loss (e.g., frontal, temporal, or subcortical regions) suggest that genetic risk factors play a key role in disease pathophysiology. Integrating genetic and neuroimaging analyses enhances our understanding of disease mechanisms and supports advancements in precision medicine. © The Author(s) 2025.

关键词： Imaging genetics Neurological diseases Precision medicine Radiogenomics Voxel-based morphometry

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Video integrity verification based on blockchain 2

Video integrity verification based on blockchain

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2nd IEEE International Conference on electronic engineering, ICEEM 2021

作者： Kamal, Randa Hemdan, Ezz El-Din El-Fishway, Nawal Menoufia University Department of Computer Science and Engineering Faculty of Electronic Engineering Menouf Egypt

ISBN: (纸本)9781665418423

with the existence of the new revolution of software techniques, tampering with the videos became easier than ever. For retaining the integrity of the captured scenes, novel methods are required. Blockchain is now one of the most interesting integrity verification techniques. Blockchain provides trust among the participant nodes;"users"without the need of a trusted third party. In this paper, we propose a new blockchain-based framework for integrity verification of videos. In the proposed framework, the scene is captured and hashed in its original state and the captured frame;"video frame"is stored as a reference frame. The hash value, frame name, and timestamp of the capturing time are stored in a CSV file. The genesis block of a permissioned blockchain is created with this data. Other frames are captured for the same scene every predefined period and hashed. If the new hash value is identical to the reference hash, then the new frame is deleted to preserve storage space, and the metadata of the frame is stored in the same CSV file. If the hash values are not identical, then the name of the frame is changed to the timestamp of the capturing time, the frame then is propagated to all participant nodes, an email is sent to a predefined mail to take the appropriate action, and finally, a new block will be created with the new metadata. The proposed system ensures the integrity of the captured videos, ease to use and robustness. © 2021 IEEE.

关键词： Blockchain

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Semimetal Alloy Contact with Low Resistivity and Enhanced Thermal Budget for MoS2 FETs

Semimetal Alloy Contact with Low Resistivity and Enhanced Th...

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International Conference on Solid-State and Integrated Circuit Technology

作者： Kwok-Ho Wong Mansun Chan Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Kowloon Hong Kong

ISBN: (数字)9798350361834

ISBN: (纸本)9798350361841

The issue of thermal instability in Bismuth (Bi) contacts hinders the reliability of high-performance molybdenum disulfide (MoS 2 ) transistors in practical applications. Here we present a new method using a semimetal alloy to improve the thermal stability and contact resistance of MoS 2 transistors. Through this approach, the devices with TiBi alloy contacts withstand the backend-of-the-line (BEOL) processes, maintaining a high on-state current after 1 hour of 400 °C annealing. Bi-alloy contacts hold promise for improving MoS 2 -based electronic devices, contributing to future developments in semiconductor technology.

关键词： Performance evaluation Annealing Thermal resistance Field effect transistors Metals Bismuth Circuit stability Sulfur Molybdenum Thermal stability

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