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Spiral Fractal Compression in Transform Domains for Underwater Communication

Annals of Data Science 2024年第3期11卷 1003-1030页

作者： Selim, A. Taha, Taha E. El-Fishawy, Adel S. Zahran, O. Hadhoud, M.M. Dessouky, M.I. El-Samie, Fathi E. Abd El-Hag, Noha ERTU Cairo Egypt Department of Information Technology Faculty of Computers and Information Menoufia University Shebeen El-Kom32511 Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt The Higher Institute of Commercial Sciences Al mahalla Al kubra Algarbia31951 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh11671 Saudi Arabia

This paper presents a simplified fractal image compression algorithm, which is implemented on a block-by-block basis. This algorithm achieves a Compression Ratio (CR) of up to 10 with a Peak Signal-to-Noise Ratio (PSNR) as high as 35 dB. Hence, it is very appropriate for the new applications of underwater communication. The idea of the proposed algorithm is based on the segmentation of the image, first, into blocks to setup reference blocks. The image is then decomposed again into block ranges, and a search process is carried out to find the reference blocks with the best match. The transmitted or stored values, after compression, are the reference block values and the indices of the reference block that achieves the best match. If there is no match, the average value of the block range is transmitted or stored instead. The effect of the spiral architecture instead of square block decomposition is studied. A comparison between different algorithms, including the conventional square search, the proposed simplified fractal compression algorithm and the standard JPEG compression algorithm, is introduced. We applied the types of fractal compression on a video sequence. In addition, the effect of using the fractal image compression algorithms in transform domain is investigated. The image is transferred firstly to a transform domain. The Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) are used. After transformation takes place, the fractal algorithm is applied. A comparison between three fractal algorithms, namely conventional square, spiral, and simplified fractal compression, is presented. The comparison is repeated in the two cases of transformation. The DWT is used also in this paper to increase the CR of the block domain pool. We decompose the block domain by wavelet decomposition to two levels. This process gives a CR for block domain transmission as high as 16. The advantage of the proposed implementation is the simplicity of computation. We f

关键词： Discrete wavelet transforms

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A Framework for Democratizing Open-Source Decision-Making using Decentralized Autonomous Organization 6

A Framework for Democratizing Open-Source Decision-Making us...

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6th International Conference on Computing and Informatics, ICCI 2024

作者： Afifi, Khalifa H. Fouad, Khaled M. Asian, Heba K. Faculty of Information Technology and Computer Science Nile University Cairo Egypt Faculty of Computers and Artificial Intelligence Benha University Egypt Faculty of Computers and Engineering New Mansoura University Egypt Cairo Egypt Center of Informatics Science Faculty of Information Technology and Computer Science Nile University Cairo Egypt

ISBN: (纸本)9798350373875

The open Source Software (OSS) became the backbone of the most heavily used technologies, including operating systems, cloud computing, AI, Blockchain, Bigdata Systems, IoT, and many more. Although the OSS individual contributors are the primary power for developing the OSS projects, they do not contribute to the OSS project's decisionmaking as much as their contributions in the OSS Projects development. This paper proposes a framework to democratize the OSS Project's decision-making using a blockchain-related technology called Decentralized Autonomous Organization (DAO). Using DAO, contributors get incentive tokens as a reward in return for contributions. The earned tokens can be used in the process of decision-making governance. This governance model tends to allow OSS individual contributors to have a public voice in the OSS project's development roadmap in particular, and the OSS decision making governance in general. © 2024 IEEE.

关键词： Open source software

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Automated software design using Machine Learning With Natural Language Processing 14

Automated software design using Machine Learning With Natura...

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14th International Conference on computer and Knowledge engineering, ICCKE 2024

作者： Khedmatkon, Fahimeh Hossein Hasheminejad, Seyed Mohammad Malak, Jaleh Shoshtarian Department of Computer Engineering Faculty of Engineering Alzahra University Tehran Iran Information Technology Department Tehran University of Medical Sciences Tehran Iran

ISBN: (纸本)9798331511272

Designing is the most difficult task in software production and development. Researchers are trying to add automation to the software design and development process. This is because of the daily increase of demanding software production;the quality growth of automotive software design makes designers respond more quickly to the refreshed demands. One of the good designing methods is to use of data mining. In this research, the decision tree algorithm method is used to identify classes and detect relationships between classes automatically. The data input is the proposed method is the use case descriptions software and its output is the list of classes with relationships between them. This method has three 3 stages: First, the use case description scenarios are analyzed by natural language processing tools. In the next step, by setting rules, the data set is created, and then the decision tree algorithm is executed on the dataset. Output is the list of classes along with the type of relationship between them. Extracting of association relations one-to-one, one-to-many, and many-to-many and association relationships. ATM, CBS, GDP, and SC case studies have been used. In this research, an attempt has been made to provide a method that has better results than previous methods. The accuracy and F-score of proposed method on the ATM dataset are 90% and 0.93 which is a value of accuracy and F-score is better than similar research and has better results. ©2024 IEEE.

关键词： Input output programs

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Enhanced Modified Contrast Enhancement and Exposure Fusion: a visionary dehazing approach for clarity in hazy imagery

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Multimedia Tools and Applications 2025年 1-24页

作者： Ayoub, Abeer El-Shafai, Walid El-Samie, Fathi E. Abd Hamad, Ehab K. I. EL-Rabaie, El-Sayed M. Department of Electronics and Electrical Communication Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Prince Sultan University Riyadh11586 Saudi Arabia Electrical Engineering Department Faculty of Engineering Aswan University Aswan81542 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

In the field of image processing, haze is a type of atmospheric scattering that reduces contrast and clarity of images, frequently masking small details and far-off objects. It is mostly caused by microscopic airborne particles like smoke, dust, and water droplets that scatter incoming light. The scattered light, producing a hazy image, diminishes the direct light that reaches the camera sensor. Many image processing methods have been presened to solve this problem and lessen the impacts of haze. Usually, these methods work by determining how much haze is there in an image, and then using this information to get the image back to its assumed previous quality. In this work, we present the proposed Modified Contrast Enhancement and Exposure Fusion (MCEEF) technique. The MCEEF dehazing technique falls under the umbrella of enhancement-based dehazing techniques. In this technique, hazy frames or images undergo sharpening through a Smoothing-Sharpening Image Filter (SSIF) designed to accentuate the disparity between the haze and objects in images. Subsequently, Gamma Correction (GC) and Color Preserving Adaptive Histogram Equalization (CP-AHE) enhance the sharpened hazy images by augmenting their contrast. Dehazed images are then obtained by fusing the results of the CP-AHE- and GC-enhanced images. The MCEEF dehazing technique is aided with enhanced hazy images or frames as input for the dehazing process. Moreover, essential enhancement tools precede the MCEEF dehazing technique. These tools include homomorphic processing and Contrast Limited Adaptive Histogram Equalization (CLAHE), which are instrumental in controlling the dynamic range before the dehazing phase. In the proposed approach, a hazy image or frame is initially subjected to homomorphic processing, followed by the application of CLAHE, and finally, the MCEEF dehazing technique is employed. To demonstrate the effectiveness of the proposed approach, we apply it on both visible and Near Infrared (NIR) frames. We

关键词： Demulsification

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Multimodal Representation Learning Based on Personalized Graph-Based Fusion for Mortality Prediction Using Electronic Medical Records

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Big Data Mining and Analytics 2025年第4期8卷 933-950页

作者： Al-Dailami, Abdulrahman Kuang, Hulin Wang, Jianxin School of Computer Science and Engineering Central South University Hunan Provincial Key Lab on Bioinformatics Changsha410083 China Sana'a University Faculty of Computer and Information Technology Sana'a999101 Yemen

Predicting mortality risk in the Intensive Care Unit (ICU) using Electronic Medical Records (EMR) is crucial for identifying patients in need of immediate attention. However, the incompleteness and the variability of EMR features for each patient make mortality prediction challenging. This study proposes a multimodal representation learning framework based on a novel personalized graph-based fusion approach to address these challenges. The proposed approach involves constructing patient-specific modality aggregation graphs to provide information about the features associated with each patient from incomplete multimodal data, enabling the effective and explainable fusion of the incomplete features. Modality-specific encoders are employed to encode each modality feature separately. To tackle the variability and incompleteness of input features among patients, a novel personalized graph-based fusion method is proposed to fuse patient-specific multimodal feature representations based on the constructed modality aggregation graphs. Furthermore, a MultiModal Gated Contrastive Representation Learning (MMGCRL) method is proposed to facilitate capturing adequate complementary information from multimodal representations and improve model performance. We evaluate the proposed framework using the large-scale ICU dataset, MIMIC-III. Experimental results demonstrate its effectiveness in mortality prediction, outperforming several state-of-the-art methods. © 2018 Tsinghua University Press.

关键词： Electronic health record

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Privacy-Secure and Decentralized Biometric Authentication Models Using Federated Learning Frameworks

Privacy-Secure and Decentralized Biometric Authentication Mo...

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2024 International Conference on System, Computation, Automation and Networking, ICSCAN 2024

作者： Mathivanan, P. Mahalakshmi, K. Anna University Faculty of Information and Communication Engineering Chennai India Kit - Kalaignarkarunanidhi Institute of Technology Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798331510022

A biometric identifier, in contrast to other identifiers used for authentication, is a quantitative evaluation of an individual's physical attributes that is successfully used to confirm or validate the identification. Because of its remarkable and consistent texture variation, iris recognition is thought to be the most dependable biometric recognition. Concerns about security, authentication, and identification are growing in importance across all domains as technology advances daily. High-security applications use these unique patterns for iris recognition. To increase the security of biometric applications without jeopardizing individual privacy, this research suggests a novel FL technique for privacy-preserving iris detection. Traditional biometric systems rely on centralised data storage and processing, which threatens data security and misuse. Federated Learning: decentralized model training that allows multiple federated clients (like mobile devices or edge servers) to collaboratively train a global model without sharing their raw iris data. We explore how this architecture can be applied to iris detection systems, maintaining accuracy while mitigating privacy risks. Our method ensures that iris features are learned locally on individual devices, and only encrypted model updates are shared with the central server. To strengthen privacy, we incorporate differential privacy and secure aggregation techniques to prevent data leakage during model training. Experimental results demonstrate the effectiveness of the proposed framework in maintaining high detection accuracy, low communication overhead, and robust privacy guarantees. © 2024 IEEE.

关键词： Federated learning

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Shared Parking Concept in the Smart City Environment 8th

Shared Parking Concept in the Smart City Environment

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8th International Congress on information and Communication technology, ICICT 2023

作者： Špitálová, Zuzana Mandová, Lucia Opatovský, Martin Faculty of Informatics and Information Technology Institute of Computer Engineering and Applied Informatics Slovak University of Technology Bratislava Slovakia

ISBN: (纸本)9789819930906

With the modern city infrastructure and increasing number of subjects in the traffic environment, there is a need for increased number of parking places. As the parking place is usually not used for a whole day, it could be shared with the others in the certain community. As it eliminates the useless driving due to the finding of free parking place, the traffic becomes more effective and produces less emissions. We designed the application for smart city environment, which helps to achieve the described situation. It consists of two parts, the frontend and backend. The data processed by the backend part can be further used for the city infrastructure improvements. The front-end part, designed in React Native, represents the graphical interface. The back-end part, designed in PostgreSQL, represents the database. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Smart city

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Protecting machine learning systems using blockchain: solutions, challenges and future prospects

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Multimedia Tools and Applications 2024年 1-28页

作者： Hajlaoui, Rejab Dhahri, Salah Mahfoudhi, Sami Moulahi, Tarek Alotibi, Gaseb Department of Computer and Informtion Sciences College of Computer Science and Engineering University of Hail Hail City Saudi Arabia Laboratory of Advanced Multifunctional Materials and Technological Applications Faculty of Science and Technology of Sidi Bouzid University of Kairouan Sidi Bouzid Tunisia Department of Information and Technology Management Mediterranean School of Business South Mediterranean University Tunis Tunisia Department of Information Technology College of Computer Qassim University Buraidah Saudi Arabia Department of Computers and Information Technology Alwajah College University of Tabuk Tabuk Saudi Arabia

Machine learning-based systems have emerged as the primary means for achieving the highest levels of productivity and efficiency. They have become the most influential competitive factor for many technologies and business companies such as Cloud AI Companies (Google, Facebook…) and Health Care AI Companies (Tempus, Nanox …). However, privacy and security issues have become the biggest challenge facing all ML applications. These threats are known as Adversarial Machine Learning (AML). Their main goal is to maliciously manipulate training data and model parameters to obtain misleading results. To overcome these challenges, several research studies have proven that Blockchain, which relies on cryptographic technologies, constitutes a promising solution for securing ML applications. It provides high guarantees to make the system scalable, reliable and more secure. In this survey, we provide an overview of ML applications and the most hostile attacks they face. Then, we define the blockchain technique and its distinctive features. After that, we conduct a comprehensive and detailed survey of the latest and best blockchain-based research to address security issues in ML applications (integrity, confidentiality and availability). We analyze, compare and comment on all the proposed solutions. In the end, we discuss in detail the various challenges that hinder the adoption of blockchain technology and we extract the most important scientific trends that will serve as guidance and support for researchers in their future works. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Blockchain

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Development and Investigation of Vision System for a Small-Sized Mobile Humanoid Robot in a Smart Environment

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International Journal of Crowd Science 2025年第1期9卷 29-43页

作者： Abu-Jassar, Amer Tahseen Attar, Hani Amer, Ayman Lyashenko, Vyacheslav Yevsieiev, Vladyslav Solyman, Ahmed Department of Computer Science College of Information Technology Amman Arab University Amman11937 Jordan Faculty of Engineering Zarqa University Zarqa2000 Jordan College of Engineering University of Business and Technology Jeddah21448 Saudi Arabia Department of Media Systems and Technology Kharkiv National University of Radio Electronics Kharkiv61166 Ukraine Department of Electrical and Electronics Engineering Faculty of Engineering and Architecture Nişantaşı University Istanbul34398 Turkey

The conducted research aims to develop a computer vision system for a small-sized mobile humanoid robot. The decentralization of the servomotor control and the computer vision systems is investigated based on the hardware solution point of view, moreover, the required software level to achieve an efficient matched design is obtained. A computer vision system using the upgraded tiny-You Only Look Once (YOLO) network model is developed to allow recognizing and identifying objects and making decisions on interacting with them, which is recommended for crowd environment. During the research, a concept of a computer vision system was developed, which describes the interaction between the main elements, on the basis of which hardware modules were selected to implement the task. A structure of information interaction between hardware modules is proposed, and a connection scheme is developed, on the basis of which a model of a computer vision system is assembled for research, with the required algorithmic and software for solving the problem. To ensure the high speed of the computer vision system based on the ESP32-CAM module, the neural network was improved by replacing the Visual Geometry Group 16 (VGG-16) network as the base network for extracting the functions of the Single Shot Detector (SSD) network model with the tiny-YOLO lightweight network model, which made it possible to preserve the multidimensional structure of the network model feature graph, resulting in increasing the detection accuracy, while significantly reducing the amount of calculations generated by the network operation, thereby significantly increasing the detection speed, due to a limited set of objects. Finally, a number of experiments were carried out, both in static and dynamic environments, which showed a high accuracy of identifications. © The author(s) 2025.

关键词： Anthropomorphic robots

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Using Peer Grading to Improve the Objectivity of Grades in GUI Design Courses 65

Using Peer Grading to Improve the Objectivity of Grades in G...

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65th International Symposium ELMAR, ELMAR 2023

作者： Romic, Kresimir Leventic, Hrvoje Mandic, Laura Galic, Irena Faculty of Electrical Engineering Computer Science and Information Technology Osijek OsijekHR-31000 Croatia

ISBN: (纸本)9798350325126

This paper deals with examining the possibility of peer grading when ranking graphical user interface (GUI) design images. The assessment was made on real images created by students on a GUI design course. Students' assignments to design a graphical user interface were being subjected to pairwise comparison and ranking was made based on pairwise comparison matrix. Obtained students' ranking was compared to experts' opinion using Spearman's and Kendall's metrics. The results suggest the possibility of using students' peer to peer grades to obtain objective rank from their subjective comparisons. © 2023 IEEE.

关键词： Graphical user interfaces

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