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Information technology and Computing (ICITCOM), International Conference on

作者： Laila Ma'rifatul Azizah Siti Nurul Aqmariah Bt. Mohd. Kanafiah Yessi Jusman Rafikha Aliana A. Raof Anani Aila Mat Zin Mohd Yusoff Bin Mashor Computer Engineering (Information Technology) University Malaysia Perlis Universitas Muhammadiyah Yyogyakarta Arau Perlis Malaysia Mechatronic Engineering Faculty of Electrical Engineering & Technology University Malaysia Perlis Arau Perlis Malaysia Electrical Engineering Faculty of Engineering Universitas Muhammadiyah Yogyakarta Yogyakarta Indonesia Computer Engineering Faculty of Electronic Engineerin & Technology University Malaysia Perlis Arau Perlis Malaysia Pathology Hospital Universiti Sains Malaysia Kubang Kerian Kelantan Malaysia Faculty of Electronic Engineering & Technology University Malaysia Perlis Perlis Malaysia

ISBN: (数字)9798350379839

ISBN: (纸本)9798350379846

Comprehensive analysis and improvement of adenocarcinoma images are essential for efficient medical diagnosis and treatment strategy. This study analyses the performance of three contrast enhancement techniques-H-Butterworth filtering, Contrast Limited Adaptive Histogram Equalization (CLAHE), and Histogram Equalization (HE). H-Butterworth filters enhance high-frequency components, which are ideal for emphasizing intricate structures, while CLAHE adapts locally to improve contrast without compromising global image characteristics. HE globally redistributes pixel intensities to enhance overall brightness and contrast, albeit potentially introducing artifacts. Using qualitative and quantitative analyses, this research systematically compares the efficacy of these methods in enhancing adenocarcinoma images, which are characterized by heterogeneous textures and structures. Findings indicate that H-Butterworth generally achieves superior results with the lowest MSE, the highest PSNR, and the highest SSIM compared to CLAHE and HE in improving overall image quality, especially in full-colour images (RGB). So, H-Butterworth can improve the image of adenocarcinoma. This study provides valuable insights for clinicians and researchers seeking optimal approaches to enhance diagnostic accuracy and treatment outcomes in adenocarcinoma imaging.

关键词： Image quality Histograms Image color analysis Statistical analysis Microscopy Brightness Adaptive equalizers Medical diagnosis Information technology Image reconstruction

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A hybrid optimization approach for securing cloud-based e-health systems

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Multimedia Tools and Applications 2025年第16期84卷 16525-16560页

作者： Altherwi, Abdulhadi Ahmad, Mohammad Tauheed Alam, Md. Moddassir Mirza, Hidayath Sultana, Nazia Pasha, Amjad Ali Sultana, Nishat Khan, Asif Irshad Alam, Md Mottahir Azim, Rezaul Department of Industrial Engineering College of Engineering and Computer Science Jazan University PO Box. 706 Jazan45142 Saudi Arabia College of Medicine King Khalid University Abha Saudi Arabia Department of Health Information Management and Technology College of Applied Medical Sciences University of Hafr Al-Batin Hafr Al-Batin Saudi Arabia Department of Electrical and Electronic Engineering College of Engineering and Computer Science Jazan University Jazan45142 Saudi Arabia Government Medical College Siddipet Ensanpalli Siddipet District Telangana502114 India Aerospace Engineering Department King Abdulaziz University Jeddah21589 Saudi Arabia Department of Business Administration Applied College Jazan University P. O. Box 706 Jazan45142 Saudi Arabia Department of Computer Science Aligarh Muslim University Uttar Pradesh Aligarh202002 India Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz Jeddah21589 Saudi Arabia Department of Physics University of Chittagong Chattogram4331 Bangladesh

In modern healthcare, cloud-based e-health technology offers substantial benefits but faces significant security challenges. Sensitive patient data is vulnerable to cyber threats during transmission and storage, potentially enabling unethical collaboration between healthcare professionals and cloud storage providers. This paper aims to develop a robust security framework that safeguards patient privacy and prevents unauthorized access to sensitive medical information in remote patient health monitoring systems. The study presents an Artificial Hybrid Optimization with an Attribute-Based Encryption (AHO-ABE) model. The model leverages cryptographic techniques and hybrid optimization to enhance data security. Specifically, whale optimization (WO) is used for efficient key generation, while sheep flock optimization (SFO) is employed for continuous network surveillance. Experimental results demonstrate that the AHO-ABE model significantly enhances data security, outperforming existing RPM-MEC, AID, AI-HCS, and IoT-HMS approaches. The model exhibits superior resilience against unauthorized access and data breaches, achieving a 5 ms execution time, 850 kbps throughput, 0.121 mJ energy usage, and 4 s latency. Combining cryptographic techniques with hybrid optimization algorithms, the AHO-ABE model provides a robust framework for safeguarding sensitive medical information. This approach ensures the integrity and confidentiality of patient data in remote healthcare settings, offering an effective solution against high-performance cyber attacks. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Diagnosis

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Comparison of Contrast Enhancement Methods in Adenocarcinoma Cancer Images

Comparison of Contrast Enhancement Methods in Adenocarcinoma...

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electronic and Electrical engineering and Intelligent System (ICE3IS), International Conference on

作者： Laila Ma'rifatul Azizah Siti Nurul Aqmariah Bt. Mohd. Kanafiah Yessi Jusman Rafikha Aliana A. Raof Anani Aila Mat Zin Mohd Yusoff Bin Mashor Computer Engineering (Information Technology) University Malaysia Perlis Universitas Muhammadiyah Yogyakarta Arau Perlis Malaysia Mechatronic Engineering Faculty of Electrical Engineering & Technology University Malaysia Perlis Arau Perlis Malaysia Electrical Engineering Faculty of Engineering Universitas Muhammadiyah Yogyakarta Yogyakarta Indonesia Computer Engineering Faculty of Electronic Engineerin & Technology University Malaysia Perlis Arau Perlis Malaysia Pathology Hospital Universiti Sains Malaysia Kubang Kerian Kelantan Malaysia Faculty of Electronic Engineering & Technology University Malaysia Perlis Perlis Malaysia

ISBN: (数字)9798350378368

ISBN: (纸本)9798350378375

This study quantifies the extent to which various image enhancement methods can improve the quality and visibility of adenocarcinoma cells on cytology slide images. The primary goal is to overcome the problems of low contrast and blurring inherent in microscopic imaging of such cells. The researchers analyzed the Partial Contrast, Contrast Limited Adaptive Histogram Equalization (CLAHE), and Histogram Equalization (HE) methods. Then, it was applied to a dataset of 418 cytology images, including benign and malignant adenocarcinoma cells. The results show that Partial Contrast offers the most superior performance. Partial contrast achieved the lowest Mean Squared Error (MSE) and the highest values in Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM). This method improves the overall brightness and contrast between light and dark areas of the image and maintains a better level of fine detail and structural integrity. Thus, Partial Contrast proved to be the best approach to improve the appearance of adenocarcinoma cells on cytology slides, offering better clarity and better contrast, which has great potential in improving the diagnosis of adenocarcinoma.

关键词： Measurement Histograms PSNR Image color analysis Microscopy Adaptive equalizers Indexes Intelligent systems Image enhancement Cancer

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Optimization Models and Educational Teaching Research in Agricultural Logistics System 2

Optimization Models and Educational Teaching Research in Agr...

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2nd IEEE International Conference on Advances in Computing, Communication and Applied Informatics, ACCAI 2023

作者： Karthick, S. Kumar, B. Anjanee Sethi, Puneet Singh, Niraj Kr Srivastava, Supriya Prasanth, P Vishnu Srm Institute of Science and Technology Department of Computer Science and Engineering Ghaziabad India Dadi Institute of Engineering and Technology Department of Electronic and Communication Engineering India Teerthanker Mahaveer University Moradabad India Amity University Amity Institute of Applied Sciences India Shoolini University Faculty of Management Sciences Solan India Mohan Babu University Tirupati India

ISBN: (纸本)9798350315905

A spic and span exhaustive disciplinesare logistics science. It is essential to the headway of the board and creation principles as well as the development of the public economy. To foster a powerful agricultural economy, the undertaking of developing new agricultural corporate substances is vital. The old techniques for agricultural item assembling and circulation are as of now not ready to fulfill the requirements of production network advancement and market informatization. To resolve the issues traditional strategies welcome, investigating new agricultural item creation and conveyance techniques is fundamental. By coordinating agricultural item store network assets, eliminating wasteful connections in the course of agricultural items, reducing expenses, accomplishing discernibility of agricultural items, and guaranteeing the quality and security of agricultural items, we make an advancement system for agricultural item supply chains, drove by enormous information specialist coops. Given this, this article proposes a model for a coordinated administration stage-based agricultural item store network, and it conducts broad research on the logistics activity rationale of the chain to give a hypothetical establishment and information support for the plan and improvement of the administration stage. © 2023 IEEE.

关键词： Supply chains

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Reflection on the energy graph-based visualisation approach to FDI of large-scale industrial systems

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IFAC-PapersOnLine 2023年第2期56卷 4094-4107页

作者： Kenneth R. Uren George van Schoor School of Electrical Electronic and Computer Engineering Faculty of Engineering North-West University Potchefstroom campus South Africa Unit for Energy and Technology systems Faculty of Engineering North-West University Potchefstroom campus South Africa

Modern industrial systems are complex and large-scale, constituting multiple components and interconnections. These components interact through material and energy interfaces. Energy can be considered as a universal quality that allows system characterisation across different physical domains (thermal-fluid, mechanical, electrical and chemical). Therefore, an energy representation of a system can be used as a basis for fault detection and diagnosis. In order to cope with representing complex interconnections of systems, graphs can assist in presenting the structure and attributes of the system components. This paper reviews FDI applications using energy and graph-theoretical methods and then focuses on a unique approach that combines the strengths of both approaches. It furthermore specifically exploits the attributed graph as mathematical formalism for characterising an industrial process in terms of energy. The graph formalism allows capturing energy characteristics while retaining the structural information, i.e. linking the energy attribute to a physical location in the process. This approach is named the energy graph-based visualisation approach. The contribution of this paper lies in the portrayal of the full research endeavour for the purposes of comparison and future reference. Two applications are presented to illustrate the usefulness of the approach namely a gas-to-liquids process and a practical heated two-tank system.

关键词： Energy visualisation large-scale industrial systems graph-based exergy

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Identification and Visualization of Spatial and Temporal Trends in Textile Industry

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computers, Materials & Continua 2023年第2期74卷 4165-4181页

作者： Umair Yousaf Muhammad Asif Shahbaz Ahmed Noman Tahir Azeem Irshad Akber Abid Gardezi Muhammad Shafiq Jin-Ghoo Choi Habib Hamam Department of Computer Science National Textile UniversityFaisalabad38000Pakistan Department of Computer Science and Software Engineering International Islamic UniversityIslamabad44000Pakistan Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea Faculty of Engineering Uni de MonctonMonctonNB E1A3E9Canada International Institute of Technology and Management Commune d’AkandaBPLibreville1989Gabon School of Electrical Engineering Department of Electrical and Electronic Eng.ScienceUniversity of JohannesburgJohannesburg2006South Africa Spectrum of Knowledge Production&Skills Development Sfax3027Tunisia

The research volume increases at the study rate,causing massive text *** to these enormous text corpora,we are drowning in data and starving for ***,recent research employed different text mining approaches to extract information from this text *** proposed approaches extract meaningful and precise phrases that effectively describe the text’s *** extracted phrases are commonly termed ***,these key phrases are employed to determine the different fields of study ***,these key phrases can also be used to determine the spatiotemporal trends in the various research *** this research,the progress of a research field can be better revealed through spatiotemporal bibliographic trend ***,an effective spatiotemporal trend extraction mechanism is required to disclose textile research trends of particular regions during a specific *** study collected a diversified dataset of textile research from 2011–2019 and different countries to determine the research *** data was collected from various open access ***,this research determined the spatiotemporal trends using quality *** research also focused on finding the research collaboration of different countries in a particular research *** research collaborations of other countries’researchers show the impact on import and export of those *** visualization approach is also incorporated to understand the results better.

关键词： Text mining spatiotemporal trend research collaboration

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A Look at The 3GPP Standard's Current Positioning of 5G Networks

A Look at The 3GPP Standard's Current Positioning of 5G Netw...

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2023 Al-Sadiq International Conference on Communication and Information technology, AICCIT 2023

作者： Khalaf, Mohammed S. Wahab, Aeizaal Azman A. Al-Wzwazy, Haider A Al-Khaleefa, Ahmed Salih Alazzawi, Murtadha A. Almohamadi, Mohammed Universiti Sains Malaysia School of Electrical & Electronic Engineering Pulau Pinang Malaysia Halfaya Oilfield Division Maysan Iraq University of Misan Faculty of Education Department of Physics Maysan Iraq Department of Computer Techniques Engineering Baghdad Iraq Imam Ja'afar Al-Sadiq University College of Information Technology Department of Computer Technical Engineering Al-Muthanna Iraq

ISBN: (纸本)9798350341881

Here, we depict the ongoing 3GPP Delivery 16 particularly for situating in 5G organizations, which is currently being developed. To address the issues of an extensive variety of administrative, business, and modern use cases, the detail indicates situating signals, estimations, methods, and framework engineering. Accordingly, when contrasted with what was beforehand conceivable with LTE, 5G essentially advances situating capacities. Utilizing 3GPP reenactment situations that have been settled upon, the demonstrative situating execution is assessed, and it is found that the 90 percentile precision goes from a couple of meters to a couple of decimeters, contingent upon the procedures and suppositions utilized. © 2023 IEEE.

关键词： 5G mobile communication systems

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DeepSVDNet:A Deep Learning-Based Approach for Detecting and Classifying Vision-Threatening Diabetic Retinopathy in Retinal Fundus Images

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computer Systems Science & engineering 2024年第2期48卷 511-528页

作者： Anas Bilal Azhar Imran Talha Imtiaz Baig Xiaowen Liu Haixia Long Abdulkareem Alzahrani Muhammad Shafiq College of Information Science and Technology Hainan Normal UniversityHaikou571158China Department of Creative Technologies Air UniversityIslamabadPakistan School of Life Science and Technology University of Electronic Science and Technology of China UESTCChengduChina School of Science and Technology University of Management and Technology UMTLahorePunjabPakistan Faculty of Computer Science&Information Technology Al Baha UniversityAl BahaSaudi Arabia School of Information Engineering Qujing Normal UniversityQujingChina

Artificial Intelligence(AI)is being increasingly used for diagnosing Vision-Threatening Diabetic Retinopathy(VTDR),which is a leading cause of visual impairment and blindness ***,previous automated VTDR detection methods have mainly relied on manual feature extraction and classification,leading to *** paper proposes a novel VTDR detection and classification model that combines different models through majority *** proposed methodology involves preprocessing,data augmentation,feature extraction,and classification *** use a hybrid convolutional neural network-singular value decomposition(CNN-SVD)model for feature extraction and selection and an improved SVM-RBF with a Decision Tree(DT)and K-Nearest Neighbor(KNN)for *** tested our model on the IDRiD dataset and achieved an accuracy of 98.06%,a sensitivity of 83.67%,and a specificity of 100%for DR detection and evaluation tests,*** proposed approach outperforms baseline techniques and provides a more robust and accurate method for VTDR detection.

关键词： Diabetic retinopathy(DR) fundus images(FIs) support vector machine(SVM) medical image analysis convolutional neural networks(CNN) singular value decomposition(SVD) classification

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Multi-Access Edge Computing Using Intelligent Mobile User Resource Allocation In 6G

Multi-Access Edge Computing Using Intelligent Mobile User Re...

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Sciences and Techniques of Automatic Control and computer engineering MI-STA, IEEE International Maghreb Meeting of the Conference on

作者： Mamoon M. Saeed Rashid A. Saeed Rania A. Mokhtar AbdulGuddoos S. A. Gaid Zeinab E. Ahmed Mohammed S. Elbasheir Department of Communications and Electronics Engineering Faculty of Engineering University of Modern Sciences (UMS) Yemen Department of Electrical and Electronic Engineering Faculty of Engineering Taif University Altaif Saudi Arabia Department of Computer Engineering College of Computers and Information Technology Taif University Taif Saudi Arabia Dept. of Communication & Computer Engineering Faculty of Engineering & Information Technology Taiz University Taiz Yemen Department of Electrical and Computer International Islamic University Malaysia Malaysia School of Electronic Engineering Sudan University of Science and Technology Khartoum Sudan

ISBN: (数字)9798350372632

ISBN: (纸本)9798350372649

Edge computing plays a crucial role in the advancement of Beyond 5G (B5G) and 6G networks. The substantial growth in network traffic and computational requirements necessitates the implementation of multi-access edge computing (MEC) as a viable solution. MEC aims to bring the capabilities of cloud computing closer to end-users by integrating them into the radio access network (RAN). This research introduces an optimal approach to connect mobile users with MEC hosts and access points, effectively distributing radio and computing resources to individual mobile users. The objective is achieved by lowering the total user transmit power while abiding by latency constraints in both the communication and computation phases, using the Grey Wolf Optimization technique (GWO). A comparison to alternative smart techniques demonstrates the effectiveness of the suggested approach

关键词： 6G mobile communication Analytical models Cloud computing Multi-access edge computing Computational modeling Conferences Telecommunication traffic

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Hybrid Convtranslstm for Spatio-Temporal Classification: Identifying Early Parkinson's Disease from Gait Patterns

SSRN

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SSRN 2025年

作者： Mahali, Muhammad Izzuddin Avian, Cries Putro, Nur Achmad Sulistyo Prakosa, Setya Widyawan Leu, Jenq-Shiou Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taiwan Department of Electronics and Informatics Engineering Faculty of Engineering Universitas Negeri Yogyakarta Indonesia Department Electrical Engineering Faculty of Engineering Universitas Brawijaya Indonesia Department of Computer Science and Electronics Faculty of Mathematics and Natural Sciences Universitas Gadjah Mada Indonesia

Parkinson's disease (PD) is a prevalent neurodegenerative disorder that affects motor function and impacts millions worldwide. Early diagnosis and precise staging of PD are critical for effective management and timely intervention. Traditional gait analysis focuses on lower limb movement to differentiate between moderate and advanced PD stages;however, integrating upper and lower limb dynamics offers a more comprehensive approach to distinguishing early-stage PD from *** study introduces a novel spatio-temporal model that integrates CNN, Transformer, and BiLSTM layers to classify PD based on the Hoehn and Yahr (H&Y) score. The architecture captures both spatial and temporal dependencies in gait patterns, with a CNN serving as the primary spatial feature extractor, utilizing a temporal-focused kernel, and augmented by a Transformer to enhance temporal feature learning. Additionally, a BiLSTM module is incorporated to effectively capture complex spatio-temporal gait dynamics across all modules. For data augmentation, sliding windows of 500, 800, and 1200 samples were employed, and the model's performance was rigorously assessed through 3-fold and 5-fold cross-subject *** included accuracy, F1-score, recall, precision, and a voting-based confidence score, while t-SNE visualization provided insights into spatio-temporal feature differentiation. The model demonstrated high performance, achieving optimal accuracy of 0.90 and an average confidence score of 0.97 with a 1200-sample window in 5-fold validation. These findings highlight the potential of a spatio-temporal approach incorporating upper and lower limb characteristics in gait analysis as a robust method for PD multi-class classification, supporting early and effective PD diagnosis from raw IMU signals. © 2025, The Authors. All rights reserved.

关键词： Neurodegenerative diseases

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