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Iraqi Journal for computer Science and Mathematics 2023年第1期4卷 204-210页

作者： Ahmed, Rasha I. Ali, Sura Mazin Computer science Dep. University of Technology-Iraq Baghdad Iraq Mustansiriyah University Baghdad Iraq

with the rapid spread of the use of video files cross the world before and during the pandemic, and the availability of capabilities and tools to create, store and transmit video files of high quality. The latest studies illustrate that video files are the highest data types that had been transmitted over the internet, during video transmission or broadcast from one point to the other or over the internet, videos may be damaged for several reasons, such as packet loss or jitter, in this paper, a proposed approach of Ridgelet transformation is presented to improve received video file quality, based on embedded watermark quality present in video frames. It is implemented by extracting three-color channels of video frames, i.e., Red (R), Green (G), and Blue (B). A selected watermark is included in blue channel (B) along with transmitting the video file from source to destination. However, the quality of watermark is measured with execution regarding watermark. Peak Signal-to-Noise Ratio (PSNR) and Mean Square Error (MSE) were adopted as measurement criteria. The evaluation results show interesting comparative values without noise, in comparison to applying salt, pepper, and Gaussian noise to video frames. © 2023 Iraqi Journal for computer Science and Mathematics. All rights reserved.

关键词： Mean square error

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Forecasting of Monkeypox Cases Using Optimized SARIMAX Based Model 3

Forecasting of Monkeypox Cases Using Optimized SARIMAX Based...

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3rd IEEE International Conference on Electronic Engineering, ICEEM 2023

作者： Elshabrawy, Mahmoud Eid, Marwa M. Abdelhamid, Abdelaziz A. El-Kenawy, El-Sayed M. Ibrahim, Abdelhameed Delta Higher Institute of Engineering and Technology Dept. of Communications & Electronics Mansoura Egypt Delta University for Science and Technology Faculty of Artificial Intelligence Mansoura35111 Egypt Ain Shams University Faculty of Computer and Information Sciences Dep. of Computer Science Cairo Egypt University Mansoura Faculty of Engineering Computer Engineering and Control Systems Dept. Egypt

ISBN: (纸本)9798350323511

This study presents a dipper-throated-based ant colony optimization (DTACO) with the Seasonal Auto-Regressive Integrated Moving Average with eXogenous factor (SARIMAX) model (DTACO+SARIMAX) to forecast monkeypox cases. The work optimizes the SARIMAX model using grid search cross-validation and fine-tunes its hyperparameters using DTACO to improve prediction accuracy. The suggested model's consistency and accuracy are considerable compared to previous studies. Comparisons with state-of-the-art models validate the proposed model's predictions. DTACO+SARIMAX can be used to control disease and monitor monkeypox. Healthcare organizations and governments can better manage and track the pandemic's course by offering accurate predictions, reducing public panic, and enabling effective pandemic planning. The Analysis of Variance (ANOVA) and Wilcoxon signed-rank tests are conducted on the proposed DTACO-SARIMAX model and compared models. © 2023 IEEE.

关键词： Ant colony optimization

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Design and Implementation of Minkowski Feature Selection for Machine Learning Techniques

Design and Implementation of Minkowski Feature Selection for...

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Information technology, Applied Mathematics and Statistics (ICITAMS), International Conference on

作者： Ekram Hakim Dhiah Al-Shammary Ahmed M. Mahdi Dep. Computer Science College of computer science and information technology University of Al-Qadisiyah Diwaniyah Iraq

ISBN: (数字)9798350335118

ISBN: (纸本)9798350335125

This paper proposes a design and implementation of a highly efficient feature selection based on Minkowski’s mathematical similarity for machine learning. Moreover, the development of the Minkowski feature selection can be general for intelligent datasets and machine learning. Intelligent optimizers and feature selection represent an advanced stage in machine learning and innovative computer applications by reducing the overall number of features to be included in the classification function process. This paper analyses Minkowski’s selection of best factors for EEG Bonn University data. Minkowski cancels the random movement and systematically limits the number of features and its point-to-point movement in order to promote exploration and reduce the probability of falling into stagnation. The main measures to analyze this research are Accuracy, precision, Recall, and F1score assessment. Moreover, the accuracy of Minkowski’s selection provided better classification results than some of the other approaches (100%)

关键词： Machine learning algorithms Limiting Machine learning computer applications Feature extraction Mathematical models Electroencephalography

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Improving Distribution Systems Maintenance Management, by Predicting Reliability Indices Using Fully Connected Neural Networks 12

Improving Distribution Systems Maintenance Management, by Pr...

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12th Smart Grid Conference, SGC 2022

作者： Tananaeifar, Mohammad-Hossein Alimadaday, Mahdis Ghadamgahi, SeyedMohammad-Mahdi Ghafourian-Nasiri, Mohammad Fereidunian, Alireza Amirkabir University of Technology Construction Engineering and Management Dep. Tehran Iran Tarbiat Modares University Industrial Engineering Dep. Tehran Iran Kharazmi University Computer Engineering Dep. Tehran Iran K. N. Toosi University of Technology Electrical Engineering Faculty Tehran Iran

ISBN: (纸本)9798350333961

Due to the increasing amount of industrial data worldwide, deep learning solutions have become extensively popular for preventive maintenance programs. Preventive maintenance reduces the costs of equipment failures, thus crafting detailed preventive maintenance programs are very effective. Neural networks are intelligent computing techniques inspired by biological neurons. Neural networks are one of the most common and practical machine learning algorithms that are utilized in many industrial applications. In this research, a fully connected neural network is developed to predict the systems reliability indices, i.e. the number of failures occurring in feeders and the amount of energy not served (ENS) in electricity distribution feeders. As a result, a data-driven improvement is provided for the preventive maintenance program. © 2022 IEEE.

关键词： Neural networks

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A Proposed Approach for Risk Planning and Management 25

A Proposed Approach for Risk Planning and Management

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25th International Arab Conference on Information technology, ACIT 2024

作者： Al Refai, Mohammed N. Al-Smadi, Yazan Al-Momani, Adai Jamhawi, Zeyad M. Otoom, Ahmed Ali Atoum, Issa Yaseen, Ahid Ababneh, Jafar Kanan, Mohammad Zarqa University Software Engineering Dep. Zarqa Jordan Zarqa University Department of Computer Science Zarqa Jordan Applied Science Private University Department of Computer Science Amman Jordan Applied Science Private University Department of Cyber Security Amman Jordan Philadelphia University Faculty of Information Technology Software Engineering Department Jordan Zarqa University Department of Cyber Security Zarqa Jordan University of Business and Technelogy Dep. of Industry Engineering Jeddah21432 Saudi Arabia

ISBN: (纸本)9798331540012

Project Risk management is the process of identifying, evaluating, avoiding, or reducing risks. Where there is no software project without risks existence are natural in the context of project planning and management. This study focuses on proposing an enhanced risk management approach where testing phases were added to make the risk management process more effective by proposing solutions to many mistakes and challenges that occur through dealing with risks. The proposed approach focuses on dealing with risks that cannot be easily defined, more accurate risk evaluation, planning, and managing risk coordinated with a contingency plan. © 2024 IEEE.

关键词： Project management

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Optimal Sampling Schedules for $h_{2}$ and $h_{\infty}$ State-Feedback Control

Optimal Sampling Schedules for $h_{2}$ and $h_{\infty}$ Stat...

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European Control Conference (ECC)

作者： Duarte J. Antunes João P. Hespanha Dep. of Mechanical Eng. Control Systems Technology Group Eindhoven University of Technology The Netherlands Dep. of Electrical and Computer Eng. University of California Santa Barbara CA USA

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

We consider a discrete-time linear system for which the control input is updated at every sampling time, but the state is measured at a slower rate. We allow the state to be sampled according to a periodic schedule, which dictates when the state should be sampled over a period. Given a desired average sampling interval, our goal is to determine sampling schedules that are optimal in the sense that they minimize the $h_{2}$ or the $h_{\infty}$ closed-loop norm, under an optimal state-feedback control law. Our results show that, when the desired average sampling interval is an integer, the optimal state sampling turns out to be evenly spaced. This result indicates that, for the $h_{2}$ and $h_{\infty}$ performance metrics, there is relatively little benefit to going beyond constant-period sampling.

关键词： Linear systems Schedules Europe Optimal scheduling Time measurement Feedback control

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Usage of Blockchain technology for Improving computer Security 25

Usage of Blockchain Technology for Improving Computer Securi...

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25th International Arab Conference on Information technology, ACIT 2024

作者： Almomani, Adai Al Refai Mohammed, N. Aburomman, Ahmad Alidmat, Omar Khair Alla Saber, Qotadeh Alshariedeh, Fuad Khouj, Mohammed Zarqa University Department of Computer Science Zarqa Jordan Zarqa University Software Engineering Dep. Zarqa Jordan Zarqa University Department of Data Science and A Zarqa Jordan Univeristy of Business and Technology Department of Electronic Enginnering Jeddah Saudi Arabia

ISBN: (纸本)9798331540012

Cyber threats have grown increasingly sophisticated, surpassing the capabilities of traditional security measures. Blockchain technology, with its decentralized and immutable structure, offers a potential solution to these challenges. This study examines the role of blockchain tools such as smart contracts, decentralized identity management, and secure data sharing in enhancing cybersecurity. A review of key literature and analysis of survey data from cybersecurity professionals demonstrate blockchain's effectiveness in improving data integrity, access control, and secure communications. The results show significant correlations between the adoption of blockchain technologies and the mitigation of threats like data breaches and unauthorized access. While blockchain presents promising advancements, scalability, regulatory barriers, and energy consumption remain challenges. The study provides valuable insights for researchers, practitioners, and policymakers on how blockchain can be integrated into modern cybersecurity strategies to create more secure digital environments. © 2024 IEEE.

关键词： Cybersecurity

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Ultra-Low Power SRAM-PUF for IoT Devices Based on CNTFETs

Ultra-Low Power SRAM-PUF for IoT Devices Based on CNTFETs

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Microelectronics (IICM), Iranian International Conference on

作者： Alireza Shafiei Mehrnaz Monajati Dep. of Electrical and Computer Engineering Graduate University of Advanced Technology Kerman Iran

With the rapid advancement of artificial intelligence and machine learning in Industry 4.0 and cyber-physical systems, security poses a significant challenge for humans. To address this, Physical Unclonable Functions (PUFs) have emerged as a promising and lightweight solution for securing IoT devices. The demand for low-power and secure crypto-devices has become critical in the context of the Internet of Things (IoT) and its emerging technologies. Although IoT has enabled battery-powered devices to transmit sensitive data, it has also introduced issues of high power consumption and security vulnerabilities. In this paper, we propose an investigation into the use of adiabatic logic with carbon nanotube field-effect transistors (CNTFETs) for designing lightweight IoT devices that tackle these challenges. This computing platform offers potential benefits in terms of security and energy efficiency for IoT applications.

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The Realization Factors of Taiwan's Low Altitude Airspace Economy and UAM: Analysis and Evaluation 20

The Realization Factors of Taiwan's Low Altitude Airspace Ec...

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20th IEEE International Conference on e-Business Engineering, ICEBE 2024

作者： Wu, Tung-Ling Kung, Chih-Ming Lin, Guan-Ting Tsai, Kuen-Yu Meng, Guang-Yun Huang, Yu-Che Cheng, Wan-Shu Institute of Transportation at Ministry of Transportation and Communications Taiwan Shin Chin Univeristy Kaohsiung Campus Dep. of Information Technology&Communication Taiwan Providence University Dep. of Computer Science and Information Management Taichung Taiwan National Taiwan Univeristy Department of Electrical Engineering Taipei Taiwan Executive Officer Center for Research on High-Performance Remote Sensing and Urban Informatics Ntu Taiwan

ISBN: (纸本)9798350365856

Low altitude airspace economy applications will be of highly effective in a wide range of civil activities and will be a critical element in the smart cities of the future. In view of the main features of unmanned aerial vehicle (UAV), such as automatic piloting system, access to uninhabited areas, low cost compared to road and manned aircraft, shorter delivery time, and the ability to carry heavy payloads, it is important to recognize that UAVs can be used for a wide range of civil activities. With the development of these applications in full swing around the world, in addition to advanced communications technology and other related infrastructure, business demand and a favorable investment climate, clarity, definiteness and feasible regulations in the Taiwanese environment are also essential. Based on the premise of local economic strength, the technical level of the telecommunication industry, and commercial demands, Taiwan should establish a rational standard for the UAV regulatory system as soon as possible, so as to facilitate the development of UAM and to ensure the international competitiveness of the related technologies for market development © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Gradual Divergence for Seamless Adaptation: A Novel Domain Incremental Learning Method

arXiv

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arXiv 2024年

作者： Jeeveswaran, Kishaan Arani, Elahe Zonooz, Bahram Dep. of Mathematics and Computer Science Eindhoven University of Technology Netherlands Wayve Technologies Ltd London United Kingdom

Domain incremental learning (DIL) poses a significant challenge in real-world scenarios, as models need to be sequentially trained on diverse domains over time, all the while avoiding catastrophic forgetting. Mitigating representation drift, which refers to the phenomenon of learned representations undergoing changes as the model adapts to new tasks, can help alleviate catastrophic forgetting. In this study, we propose a novel DIL method named DARE, featuring a three-stage training process: Divergence, Adaptation, and REfinement. This process gradually adapts the representations associated with new tasks into the feature space spanned by samples from previous tasks, simultaneously integrating task-specific decision boundaries. Additionally, we introduce a novel strategy for buffer sampling and demonstrate the effectiveness of our proposed method, combined with this sampling strategy, in reducing representation drift within the feature encoder. This contribution effectively alleviates catastrophic forgetting across multiple DIL benchmarks. Furthermore, our approach prevents sudden representation drift at task boundaries, resulting in a well-calibrated DIL model that maintains the performance on previous tasks. 1 © 2024, CC BY-SA.

关键词： Learning systems

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