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Cyber Resilience (ICCR), International Conference on

作者： Haider Rasheed Abdulshaheed Yaseen Saadi Abbas Jamal F. Tawfeq Karamath Ateeq Saif. E. A. Alnawayseh Taher M. Ghazal Computer Engineering Techniques Department Baghdad College of Economic Sciences University Baghdad Iraq Electronic and Communications Engineering Department College of Engineering Al-Nahrain University Baghdad Iraq Department of Medical Instrumentation Technical Engineering Medical Technical College Al-Farahidi University Baghdad Iraq School of Computing Skyline University College University City Sharjah Sharjah UAE Department of Electrical Engineering College of Engineering Mutah University Al-Karak Jordan Computer Science Department Centre for Cyber Physical Systems Khalifa University Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia (UKM) Bangi Selangor Malaysia

ISBN: (数字)9798350394962

ISBN: (纸本)9798350394979

Providing quality healthcare services and promoting collaborative clinical research are easier and more efficient with electronic medical record (EMR) systems. All aspects of care are included in electronic health records. Data characterized by volume, variety, and velocity is what IBM defines as big data. Therefore, we evidently have a significant problem managing “big EMR data” from a volume, accuracy, and velocity perspective. Data misuse and patient safety are significant risks associated with poorly implemented EMR-based systems. Storage, access, and retrieval of big data are all aspects of security to consider. Location is another important aspect of secure data use, in addition to strong access control mechanisms. Researchers are investigating secure mobile data usage based on location after recent reports of illegal trade and theft of patient data over mobile devices. To improve work flow dynamics and efficiency, healthcare facilities are increasingly using mobile devices. In spite of this, mobile devices are becoming more and more common. A new technique for preventing EMR infiltration and manipulation by hackers using the cloud is presented in this article.

关键词： Cloud computing Hospitals Watermarking Big Data Mobile handsets Robustness Safety

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Comparison of Epilepsy Induced by Ischemic Hypoxic Brain Injury and Hypoglycemic Brain Injury using Multilevel Fusion of Data Features

arXiv

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arXiv 2024年

作者： Kadem, Sameer Sami, Noor Elaraby, Ahmed Alyousif, Shahad Jalil, Mohammed Altaee, M. Almusawi, Muntather Ghany, Ismaeel A. Kareem, Ali Kamil Kamalrudin, Massila Ftaiet, Adnan Allwi Dijlah University College Baghdad Iraq Department of Computer Engineering Techniques Mazaya University College Th Qar Iraq Department of Computer Science Faculty of Computer Science and Information South Valley University Qena Egypt Department Of Cybersecurity College of Engineering and Information Technology Buraydah Private Colleges Buraydah Saudi Arabia Department of Electrical and Electronic Engineering College of Engineering Gulf University Sanad26489 Bahrain Research centre Northampton University Faculty of Engineering Department of Electrical and Electronics Engineering University Drive Northampton NN1 5PH United Kingdom Department of Computer Science Alturath University College Baghdad Iraq Department of Medical Engineering Techniques Alfarahidi University Baghdad Iraq College of Technical Engineering The Islamic University Najaf Iraq Computer Technology Engineering College of Engineering Technology Al-Kitab University Iraq Department of Biomedical Engineering Al-Mustaqbal University College Hillah51001 Iraq Faculty of Information & Communication Technology Universiti Teknikal Malaysia Melaka Durian Tunggal Melaka75450 Malaysia Medical Instruments Engineering Techniques National University of Science and Technology Thi Qar Iraq

The study aims to investigate the similarities and differences in the brain damage caused by Hypoxia-Ischemia (HI), Hypoglycemia, and Epilepsy. Hypoglycemia poses a significant challenge in improving glycemic regulation for insulin-treated patients, while HI brain disease in neonates is associated with low oxygen levels. The study examines the possibility of using a combination of medical data and Electroencephalography (EEG) measurements to predict outcomes over a two-year period. The study employs a multilevel fusion of data features to enhance the accuracy of the predictions. Therefore this paper suggests a hybridized classification model for Hypoxia-Ischemia and Hypoglycemia, Epilepsy brain injury (HCM-BI). A Support Vector Machine is applied with clinical details to define the Hypoxia-Ischemia outcomes of each infant. The newborn babies are assessed every two years again to know the neural development results. A selection of four attributes is derived from the Electroencephalography records, and SVM does not get conclusions regarding the classification of diseases. The final feature extraction of the EEG signal is optimized by the Bayesian Neural Network (BNN) to get the clear health condition of Hypoglycemia and Epilepsy patients. Through monitoring and assessing physical effects resulting from Electroencephalography, The Bayesian Neural Network (BNN) is used to extract the test samples with the most log data and to report hypoglycemia and epilepsy patients non-invasively. The experimental findings demonstrate that the suggested strategy improves accuracy by 95.05% and reduces the error rate to 0.41 when comparing diseases. © 2024, CC0.

关键词： Electroencephalography

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Optimum design of bearingless brushless DC motor modeling with dual loop controller using dragonfly optimizers

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e-Prime - Advances in Electrical engineering, electronics and Energy 2025年 11卷

作者： Kadhim, Qusay S. Swadi, Mahmood Mahdi, Ali Jafer Joodi, Mohanad Azeez Tuaimah, Firas Mohammed Mohammed, Moanes E. Abbas, Abbas Hafeth Salem, Mohamed Department of Electrical Engineering Techniques Al-Mussaib Technical College Al-Furat Al-Awsat Technical University Najaf 54001 Iraq Department of Electrical Engineering College of Engineering University of Baghdad Baghdad 10001 Iraq College of Information Technology Engineering Al-Zahraa University for Women Karbala 56001 Iraq Department of Electrical and Electronics Engineering University of Kerbala Karbala 56001 Iraq Department of Electrical Engineering University of Technology Iraq Libyan Authority for Scientific Research Tripoli Libya School of Electrical and Electronic Engineering Universiti Sains Malaysia (USM) Penang Nibong Tebal 14300 Malaysia

The article presents the optimal modeling of a Bearingless Brushless DC (BBLDC) motor with an enhanced controller, emphasizing a dual-loop control scheme for torque and suspension windings. The design aims to separate electromagnetic torque and radial suspension forces effectively. The proposal's focus consists of two contributions: firstly, the optimal design of the BBLDC motor;secondly, the application of the Dragonfly Algorithm (DA) for the improvement of the motor's control systems, resulting in reduced torque ripple, rapid and precise tracking, and elimination of overshoot. Comparative results illustrate the superior performance of this technique compared to typical Proportional Integral (PI) controllers, exhibiting quicker response times to reach a steady state and enhanced stability. © 2025 The Author(s)

关键词： Bearingless brushless dc motor Draganfly algorithm Optimized bldc motor drive radial suspension forces

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Designing a Novel Acoustic Communication System for High-Speed Underwater Data Transmission

Designing a Novel Acoustic Communication System for High-Spe...

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IoT, Communication and Automation Technology (ICICAT), International Conference on

作者： Kumbala Pradeep Reddy Kodali Anuradha Himanshu Sharma S. Ananthi Mohammed Al-Farouni Shekaina Justin Department of CSE CMR Institute of Technology Hyderabad Telangana India Department of CSE GRIET Bachupally Hyderabad Telangana India Department of Computer Engineering & Applications GLA University Mathura Department of EEE New Prince Shri Bhavani College of Engineering and Technology Chennai Tamil Nadu India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Electrical Engineering Department Hybrid Electric Vehicle Solar Energy Fuel Injection Control Princess Nourah Bint Abdulrahman University

ISBN: (数字)9798350368109

ISBN: (纸本)9798350368116

This research involves the description of the newly developed acoustic communication system that can improve high data rates in the underwater channel. The problems in the conventional underwater communication techniques are being solved in the proposed system with the help of integrating the latest modulation techniques, effective transducers, and signal processing algorithms. The effectiveness of the system in achieving studies details high data rates and reasonable signal integrity and flexibility to unfavorable underwater environments during simulations and field trials. The simulated studies point to a maximum of 500kbps and practical trials a maximum of 480 kbps plus higher energy efficiency than regular systems. It still suggests that there is a need to continue with the improvements on all these areas of system performance since the system was design for varied depths and water types though there is an indication that the system performance declines in turbulent conditions. They are beneficial to develop and improve the underwater communication techniques meant to have a positive impact on technological applications such as underwater robotics, environmental and oceanographic surveys. Hence, the successful implementation of this system can be regarded as a major breakthrough towards the resolution of the problems that arise with high-speed data transmission in undersea environment.

关键词： Underwater communication Acoustic communication (telecommunication) System performance Modulation Signal processing algorithms Energy efficiency Data models Robots Optimization Thermal stability

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Multimodal graph representation learning for robust surgical workflow recognition with adversarial feature disentanglement

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Information Fusion 2025年 123卷

作者： Bai, Long Ma, Boyi Wang, Ruohan Wang, Guankun Cui, Beilei Jiang, Zhongliang Islam, Mobarakol Min, Zhe Lai, Jiewen Navab, Nassir Ren, Hongliang Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong Chair for Computer Aided Medical Procedures Technical University of Munich Munich Germany Department of Biomedical Engineering University of Toronto Toronto Canada Center for Computational and Molecular Biology Brown University Providence United States UCL Hawkes Institute University College London London United Kingdom School of Control Science and Engineering Shandong University Jinan China

Surgical workflow recognition is vital for automating tasks, supporting decision-making, and training novice surgeons, ultimately improving patient safety and standardizing procedures. However, data corruption can lead to performance degradation due to issues like occlusion from bleeding or smoke in surgical scenes and problems with data storage and transmission. Therefore, a robust workflow recognition model is urgently needed. In this case, we explore a robust graph-based multimodal approach to integrating vision and kinematic data to enhance accuracy and reliability. Vision data captures dynamic surgical scenes, while kinematic data provides precise movement information, overcoming limitations of visual recognition under adverse conditions. We propose a multimodal Graph Representation network with Adversarial feature Disentanglement (GRAD) for robust surgical workflow recognition in challenging scenarios with domain shifts or corrupted data. Specifically, we introduce a Multimodal Disentanglement Graph Network (MDGNet) that captures fine-grained visual information while explicitly modeling the complex relationships between vision and kinematic embeddings through graph-based message modeling. To align feature spaces across modalities, we propose a Vision-Kinematic Adversarial (VKA) framework that leverages adversarial training to reduce modality gaps and improve feature consistency. Furthermore, we design a Contextual Calibrated Decoder, incorporating temporal and contextual priors to enhance robustness against domain shifts and corrupted data. Extensive comparative and ablation experiments demonstrate the effectiveness of our model and proposed modules. Specifically, we achieved an accuracy of 86.87% and 92.38% on two public datasets, respectively. Moreover, our robustness experiments show that our method effectively handles data corruption during storage and transmission, exhibiting excellent stability and robustness. Our approach aims to advance automated surgi

关键词： Transplantation (surgical)

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Investigative Study on Routing Protocols in Flying Ad Hoc Networks Environment

Investigative Study on Routing Protocols in Flying Ad Hoc Ne...

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International Conference on engineering Technology and their Applications (IICETA)

作者： Mustafa Hamid Hassan Ali Hashim Abbas Mohammed Hasan Mutar Mohammed Ahmed Jubair Sami Abduljabbar Rashid Ahmed Jamal Ahmed Mohammed I. Habelalmateen Aymen Mohammed L. Audah Department of Computer Technical engineering College of Information Technology Imam Ja’afar Al-Sadiq University Al-Muthanna Iraq Department of Computer Engineering Techniques Al-Maarif University College Al-Anbar Iraq Department of Computer Technical Engineering College of Technical Engineering Islamic University Najaf Iraq engineering technical college Al-Farahidi University Baghdad Iraq Wireless and Radio Science Centre (WARAS) Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia Batu Pahat Malaysia

ISBN: (数字)9781665472159

ISBN: (纸本)9781665472166

In recent years, new networking paradigms such as Vehicular Ad Hoc Network (VANET), Flying Ad-hoc Networks (FANETs), and SEANETs have emerged as a result of Mobile Ad-Hoc Networks (MANETs). UAVs are gaining popularity as they are used in large-scale real-time applications. When UAVs are linked together, they form a FANET, which works collectively and in the most efficient manner possible. FANETs are designed to be used in a wide range of missions and rapidly changing scenarios. As a result, given the nature of the applications and services used to deploy UAVs, efficient routing protocols are essential. Other routing protocols, on the other hand, have been developed to date, each with its own set of limitations. This research investigates the AODV, DSDV, and AOMDV routing protocols in the context of a FANET. In terms of delay, the DSDV exceeds the other protocols, whereas the AOMDV outperforms the others in terms of average TP and PDR.

关键词： Simulation Vehicular ad hoc networks Routing protocols Real-time systems Delays Mobile nodes AODV

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Early check in to evaluate the segmentation for skin lesions based on modern swarm intelligence system.

Early check in to evaluate the segmentation for skin lesions...

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1st International Multi-Disciplinary Conference Theme: Sustainable Development and Smart Planning, IMDC-SDSP 2020

作者： Aljanabi, Mohanad Abed, Jameel Kadhim Ajel, Ahmed R. Mohammed, Jabbark Department of Electrical Power Techniques Engineering Technical College /AL-Mausaib Al-Furat Al-Awsat Technical University Najaf Iraq Department of Medical Instrumentation Techniques Engineering Electrical Engineering Technical College Middle Technical University Baghdad1022 Iraq Department of Control and Automation Engineering Electrical Engineering Technical College Middle Technical University Baghdad1022 Iraq Department of Communication Engineering University of Technology Baghdad Iraq

ISBN: (纸本)9781631902611

In recent years, the incidence of skin lesions has been one of the most rapidly increasing of all commonly occurring cancers. This deadliest form of melanoma must be detected early to be effectively treated. Because of the trouble and objectivity of human clarification, a significant research field has developed around the computerized examination of dermoscopy images. One reason to apply swarm intelligence systems is that an optimal solution can be advanced with a sensible computational application. This work introduces an artificial bee colony technique (ABC), distinctions, and applications. The planned ABC is a more suitable algorithm and one that requires smaller amounts of factors that need to be adjusted in comparison to other modern artificial swarm intelligence techniques (MASITs) for distinguishing unhealthy in skin tumor lesions. In these swarm's intelligence optimization algorithms have been positively executed for melanoma problems and provided extraordinary results guidance to better prediction and investigation of the skin cancer lesions. The experimental outcomes propose that the planned process proficient a developed accuracy associated to the ground truth (GT) used skin lesions’ dermatology. So, we will be able to use these in a future study with different databases. © 2020 EAI.

关键词： Dermatology

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Improvement method for cervical cancer detection: A comparative analysis

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Oncology Research 2021年第5期29卷 365-376页

作者： NUR AIN ALIAS WAN AZANI MUSTAFA MOHD AMINUDIN JAMLOS AHMED ALKHAYYAT KHAIRUL SHAKIR AB RAHMAN RAMI QMALIK Faculty of Electrical Engineering&Technology Universiti Malaysia PerlisUniCITI Alam CampusSungai ChuchuhPadang BesarPerlis02100Malaysia Advanced Computing(AdvCOMP) Centre of ExcellenceUniversiti Malaysia Perlis(UniMAP)Pauh Putra CampusArauPerlis02600Malaysia Faculty of Electronic Engineering&Technology Universiti Malaysia PerlisUniCITI Alam CampusSungai ChuchuhPadang BesarPerlis02100Malaysia Department of Computer Technical Engineering College of Technical EngineeringThe Islamic UniversityNajaf54003Iraq Department of Pathology Hospital Tuanku FauziahKangarPerlis02000Malaysia Medical Instrumentation Techniques Engineering Department Al-Mustaqbal University CollegeBabylonHillah51001Iraq

Cervical cancer is a prevalent and deadly cancer that affects women all over the *** affects about 0.5 million women anually and results in over 0.3 million *** of this cancer was previously done manually,which could result in false positives or *** researchers are still contemplating how to detect cervical cancer automatically and how to evaluate Pap smear ***,this paper has reviewed several detection methods from the previous researches that has been done *** paper reviews pre-processing,detection method framework for nucleus detection,and analysis performance of the method *** are four methods based on a reviewed technique from previous studies that have been running through the experimental procedure using Matlab,and the dataset used is established Herlev *** results show that the highest performance assessment metric values obtain from Method 1:Thresholding and Trace region boundaries in a binary image with the values of precision 1.0,sensitivity 98.77%,speciﬁcity 98.76%,accuracy 98.77%and PSNR 25.74%for a single type of ***,the average values of precision were 0.99,sensitivity 90.71%,speciﬁcity 96.55%,accuracy 92.91%and PSNR 16.22%.The experimental results are then compared to the existing methods from previous *** show that the improvement method is able to detect the nucleus of the cell with higher performance assessment *** the other hand,the majority of current approaches can be used with either a single or a large number of cervical cancer smear *** study might persuade other researchers to recognize the value of some of the existing detection techniques and offer a strong approach for developing and implementing new solutions.

关键词： Cervical cancer Detection Pap smear Images

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2-D GCANet Applied to Denoise 1-D EEG Signals in Online Remote Teaching Scenarios

Journal of Network Intelligence

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Journal of Network Intelligence 2023年第4期8卷 1289-1302页

作者： Huang, Ting-Qing Wang, Chuan-Sheng Chen, Zhao-Qi Zhang, Fu-Quan Meng, Xiang-Long Grau, Antoni Chen, Yang Huang, Jing-Wei College of Computer and Control Engineering Minjiang University Fuzhou University Town No. 200 Xiyuangong Road Fuzhou China Department of Automatic Control Technical Polytechnic University of Catalonia Autonomous Region of Catalonia Barcelona Spain College of Computer and Big Data Fuzhou University Fuzhou University Town No. 2 Wulong Jiangbei Avenue Fuzhou China Digital Media Art Key Laboratory of Sichuan Province Sichuan Conservatory of Music No. 2 Wannianchang Street Chenghua District Sichuan Province Chengdu City China Fuzhou Technology Innovation Center of intelligent Manufacturing information System Minjiang University Fuzhou University Town NO. 200 Xiyuangong Road Fuzhou China Fujian Province University No. 599 Quanxiu Road Juyuanzhou Ecological Civilization District Fujian Province Fuzhou City China College of Electronic Engineering Shandong University of Science and Technology No. 579 Qianwangang Road Huangdao District Qingdao China School of Mechanical and Automotive Engineering Fujian University of Technology No. 33 Xuefu South Road University New District Fujian Province Fuzhou City China

When EEG signals are used to assess the level of student engagement in online teaching tasks, they are often interfered by noise. It is a challenge to effectively remove these noises. Currently, deep learning methods have been applied to the field of EEG denoising. However, existing methods still have some problems. The denoised signals still have obvious noise residue, or the original EEG signals are damaged, and the model fitting speed is too slow. Image dehazing, as a typical denoising task in the field of image enhancement, has achieved great success in recent years. Therefore, inspired by advanced models in this field, we introduce CNN into EEG denoising tasks. In this paper, we take GCANet, an excellent image enhancement model, as an example. The dilated convolutions and gate fusion subnetworks included in GCANet enable more efficient EEG signal denoising. The results demonstrate that the proposed model effectively reduces noise while preserving essential features. Furthermore, in comparison to other state-of-the-art models, our proposed model exhibits enhanced robustness and faster convergence, as evidenced by achieving lower loss values after five epochs. Its good performance provides a new development idea for the field of EEG denoising. © 2023, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Image enhancement

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Ranking Based Routing Protocol for Residual Energy Estimation in Wireless Sensor Network Based IoT Network

Ranking Based Routing Protocol for Residual Energy Estimatio...

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International Conference on engineering Technology and their Applications (IICETA)

作者： Sami Abduljabbar Rashid Ahmed Jamal Ahmed Mustafa Hamid Hassan Ali Hashim Abbas Mohammed I. Habelalmateen Mohammed Ahmed Jubair L. Audah Waleed Al-Azzawi Department of Computer Engineering Techniques Al-Maarif University College Al-Anbar Iraq Department of Computer Technical engineering College of Information Technology Imam Ja’afar Al-Sadiq University Al-Muthanna Iraq Department of Computer Technical Engineering College of Technical Engineering Islamic University Najaf Iraq Wireless and Radio Science Centre (WARAS) Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia Batu Pahat Malaysia Medical technical college Al-Farahidi University Baghdad Iraq

ISBN: (数字)9781665472159

ISBN: (纸本)9781665472166

Internet of Things (IoT) is widely involved in environmental monitoring. IoT network has a limited energy supply which impacts the network’s lifetime. At present, limited energy is a challenging factor due to limited energy availability. IoT performance is improved with the RPL routing protocol for effective route establishment. With an effective energy harvesting scheme IoT network, residual energy can be improved. Typically, energy harvesting with conventional RPL routing protocol is ineffective. To withstand the limitation associated with energy harvesting in IoT networks with the incorporation of RPL routing is essential. To achieve this, this paper presented an Energy Harvesting Ranked Whale optimization (EHRWO) is developed. Initially, the proposed model utilizes the optimal route establishment with EHRWO with improved security. The operation of EHRWO is performed for static and dynamic operation of the network. The developed work estimates the node energy, harvest energy, routing performance, and distance. Based on the optimization of the whale optimal path is estimated for the transmission of data. With a ranking based approach optimal path for data transmission will be computed. The simulation results expressed the proposed work performance of the parameters such as energy consumption and packet delivery ratio.

关键词： Energy consumption Wireless sensor networks Estimation Whales Routing Routing protocols Whale optimization algorithms

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