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5th International Conference on Advancements in Computational Sciences, ICACS 2024

作者： Tehsin, Sara Hassan, Ali Riaz, Farhan Nust Department of Computer and Software Engineering Islamabad Pakistan Hitec University Deparment of Computer Engineering Taxila Pakistan

ISBN: (纸本)9798350394764

Signature verification plays an important role in document authentication. The efficient and robust system is required for forgery detection in documents in the presence of distortion such as rotation, scaling and noise. This paper proposes a writer-dependent signature verification method, where hand-crafted features are fused with one-dimensional convolutional neural network features to cater different variance in the whole verification process. Proposed feature extraction methodology is validated by bagged ensemble learning technique in which machine learning classifier's decision is finalized based on majority voting. The effectiveness of the proposed signature verification approach has been evaluated across three distinct publicly accessible datasets. The outcomes highlight the versatility of this method. Moreover, the proposed system surpasses the performance of other pre-existing systems documented in the literature. © 2024 IEEE.

关键词： Learning systems

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A Virtual Reality Educational Tool for Complex Brain Anatomy 14

A Virtual Reality Educational Tool for Complex Brain Anatomy

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14th International Conference on Information and Communication Systems, ICICS 2023

作者： Alhmoudi, Shaikhah Alkatheri, Sumyah Alghafri, Shamma Idrais, Abdel Rahman Damseh, Rafat United Arab Emirates University Deparment of Computer and Software Engineering Al Ain United Arab Emirates Concordia University Deparment of Electrical and Computer Engineering Montreal Canada

ISBN: (纸本)9798350307870

Brain anatomy presents a unique pedagogical challenge in medical education due to its complex structures and the detailed intricacies inherent to various brain regions. Advanced imaging techniques such as computed tomography (CT), T1/T2 magnetic resonance imaging (MRI), and diffusion imaging provide 3D representations of these anatomical details, which require suitable tools and visualization setups to be taught efficiently to medical students. Machine learning and virtual reality have emerged as promising avenues for refining the visualization and reconstruction processes of these details. This paper delves into the integration of cutting-edge deep learning (DL) algorithms designed for the reconstruction of brain vascular trees and neural fiber tracts within an immersive virtual reality (VR) framework. Our proposed solution has the potential to improve brain anatomy education by serving as tool for illustrating subject-specific complex structures. The ensuing results underscore the viability and efficacy of our solution. © 2023 IEEE.

关键词： Virtual reality

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A Real-Time Valve Counting System Based On YOLOv8 8

A Real-Time Valve Counting System Based On YOLOv8

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8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024

作者： Celik, Muzeyyen Akar, Ferhat Bayilmis, Cuneyt Akgun, Devrim Rise Technology Consulting&Academy Mersin Turkey Aygaz Aş İstanbul Turkey Sakarya University Deparment of Computer Engineering Sakarya Turkey Sakarya University Deparment of Software Engineering Sakarya Turkey

ISBN: (纸本)9798331531492

In industry, human-dependent detection, counting and tracking of objects causes problems such as time loss, error and cost. computer vision and machine-learning methods are important solutions for automating these processes. In this study, a software has been developed to ensure accurate/accurate counting and tracking/recording of valves during the boxing process in companies engaged in cylinder production and filling. The developed software consists of the YOLOv8 algorithm for the detection and counting of the box and the valves in the box, a web application and API for reporting and monitoring processes. The valve detection and counting model based on the YOLOv8 algorithm was trained with the original data set on the local physical server. The performance evaluation showed that the YOLOv8 model was able to detect the valves with 96% accuracy. The implemented system contributes to optimising workflows in industrial processes by increasing efficiency and accuracy in valve counting. © 2024 IEEE.

关键词： Application programs

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A Real-Time Carboy Tracking and Counting System Based on YOLOv8 and ByteTrack

A Real-Time Carboy Tracking and Counting System Based on YOL...

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2024 International Conference on Artificial Intelligence, Metaverse and Cybersecurity, ICAMAC 2024

作者： Akar, Ferhat Berber, Sezer Koca, Oğuzhan Bayılmış, Cüneyt R&D AYGAZ A.Ş. İstanbul Turkey Software Department Rise Technology Mersin Turkey Deparment of Computer Engineering Sakarya University Sakarya Turkey

ISBN: (纸本)9798350353488

In industrial processes, the accurate detection, counting, and classification of objects are crucial for the efficiency of production lines. However, when these processes are performed manually, human errors and time loss can occur. In this study, a YOLOv8-based system was developed to separate carboys based on their expiration dates, count solid carboys, and detect carboys containing foreign matter at the Pürsu Water Factory. The system, which processes real-time video streams, integrates YOLOv8 for object detection, tracking, and counting. Additionally, the performances of the DeepSORT and ByteTrack algorithms were compared for object tracking. The results show that ByteTrack performed faster and more stably than DeepSORT. The YOLOv8-based model achieved 98% accuracy, and ByteTrack worked at a higher FPS than DeepSORT, thereby improving the efficiency of the production line. This study presents an in-depth analysis of the system's accuracy, speed, and overall performance. © 2024 IEEE.

关键词： Object detection

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Ensemble Learning for Offline Signature Verification using Fused Deep Features

Ensemble Learning for Offline Signature Verification using F...

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International Conference on Advancements in Computational Sciences (ICACS)

作者： Sara Tehsin Ali Hassan Farhan Riaz Department of Computer and Software Engineering NUST Islamabad Pakistan Deparment of Computer Engineering HITEC university Taxila

Signature verification plays an important role in document authentication. The efficient and robust system is required for forgery detection in documents in the presence of distortion such as rotation, scaling and noise. This paper proposes a writer-dependent signature verification method, where hand-crafted features are fused with one-dimensional convolutional neural network features to cater different variance in the whole verification process. Proposed feature extraction methodology is validated by bagged ensemble learning technique in which machine learning classifier’s decision is finalized based on majority voting. The effectiveness of the proposed signature verification approach has been evaluated across three distinct publicly accessible datasets. The outcomes highlight the versatility of this method. Moreover, the proposed system surpasses the performance of other pre-existing systems documented in the literature.

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A Virtual Reality Educational Tool for Complex Brain Anatomy

A Virtual Reality Educational Tool for Complex Brain Anatomy

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International Conference on Information and Communication Systems (ICICS)

作者： Shaikhah Alhmoudi Sumyah Alkatheri Shamma Alghafri Abdel Rahman Idrais Rafat Damseh Deparment of Computer and Software Engineering United Arab Emirates University Al Ain UAE Deparment of Electrical and Computer Engineering Concordia University Montreal Canada

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A Real-Time Valve Counting System Based On YOLOv8

A Real-Time Valve Counting System Based On YOLOv8

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International Artificial Intelligence and Data Processing Symposium (IDAP)

作者： Müzeyyen Çelik Ferhat Akar Cüneyt Bayılmış Devrim Akgün Rise Technology Consulting&Academy Mersin Turkey AYGAZ AŞ İstanbul Turkey Deparment of Computer Engineering Sakarya University Sakarya Türkiye Deparment of Software Engineering Sakarya University Sakarya Türkiye

ISBN: (数字)9798331531492

ISBN: (纸本)9798331531508

关键词： Performance evaluation Accuracy software algorithms Production Machine learning Valves software Real-time systems Servers Monitoring

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Ethiopic Cryptography: An Efficient Hybrid Encryption Algorithm for Reducing Cybersecurity Attack 11th

Ethiopic Cryptography: An Efficient Hybrid Encryption Algori...

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11th EAI International Conference on Advancement of Science and Technology, ICAST 2023

作者： Akele, Tadesse Birara Bahiru, Tadesse Kebede Molla, Tibebu Legesse Fentie, Shambel Dessale Belay, Tadesse Destaw Marye, Almaz Yemataw Getaneh, Mersha Derese Department of Information System Kombolcha Institute of Technology Wollo University Kombolcha Ethiopia Department of Information Technology Kombolcha Institute of Technology Wollo University Kombolcha Ethiopia Deparment of Software Engineering Kombolcha Institute of Technology Wollo University Kombolcha Ethiopia Department of Computer Science Kombolcha Institute of Technology Wollo University Kombolcha Ethiopia

ISBN: (纸本)9783031641503

Cryptography is an essential tool in ensuring the security of data during network communication. Network and service providers prioritize data security to ensure secure data exchanges. Ethiopic cryptography is a unique encryption method that utilizes the Amharic language, prevalent in Ethiopia. Unlike Latin alphabets, Amharic consists of 287 characters, making decryption challenging. The encryption process involves converting the text to Amharic and then mapping it to a pair of randomly chosen two-bit English alphabets, creating an intermediate cipher. The Ethiopic cryptography algorithm employs a hybrid approach, using the RSA algorithm for secure key exchange and the Advanced Encryption Standard algorithm for text confidentiality. The algorithm comprises three phases—translation, mapping, and encryption—contributing to its effectiveness in securing data over the network. Decryption requires familiarity with the Amharic language and mapping details. The algorithm demonstrates a stronger avalanche effect (97%) in comparison with Blowfish and DES. The algorithm is proposed and evaluated using the design science research methodology, and its performance is validated through simulation using MATLAB and BunnaScript tools, considering factors like the avalanche effect, time complexity, and memory consumption. The evaluation shows that the suggested solution operates faster, requires lesser time for data encryption, and uses less memory than other methods in use. Overall, the proposed Ethiopic cryptography algorithm proves to be an efficient and effective method for securing data during network communication, offering stronger text confidentiality and an improved avalanche effect. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： MATLAB

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A Real-Time Carboy Tracking and Counting System Based on YOLOv8 and ByteTrack

A Real-Time Carboy Tracking and Counting System Based on YOL...

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Artificial Intelligence, Metaverse and Cybersecurity (ICAMAC), International Conference on

作者： Ferhat Akar Sezer Berber Oğuzhan Koca Cüneyt Bayılmış R&D AYGAZ A.Ş İstanbul Turkey Software Department Rise Technology Mersin Turkey Deparment of Computer Engineering Sakarya University Sakarya Türkiye

ISBN: (数字)9798350353488

ISBN: (纸本)9798350353495

关键词： Accuracy Object detection Streaming media Solids Real-time systems Recording Servers Reliability Streams Testing

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Improved Sequencing Heuristic DSDV Protocol Using Nomadic Mobility Model for FANETS

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computers, Materials & Continua 2022年第2期70卷 3653-3666页

作者： Inam Ullah Khan Muhammad Abul Hassan Muhammad Fayaz Jeonghwan Gwak Muhammad Adnan Aziz Department of Electronic Engineering Isra University(SEAS)Islamabad44000Pakistan Department of Computing and Technology Abasyn University Peshawar25000Pakistan Deparment of Computer Engineering Jeju National UniversityJejuKorea Department of Software Korea National University of TransportationChungju27469Korea Department of Biomedical Engineering Korea National University of TransportationChungju27469Korea Department of AI Robotics Engineering Korea National University of TransportationChungju27469Korea Department of IT&Energy Convergence(BK21 FOUR) Korea National University of TransportationChungju27469Korea

Most interesting area is the growing demand of flying-IoT mergers with smart ***,aerial vehicles,especially unmanned aerial vehicles(UAVs),have limited capabilities for maintaining node energy *** order to communicate effectively,IoT is a key element for smart *** improving network performance,routing protocols can be deployed in flying-IoT to improve latency,packet drop rate,packet delivery,power utilization,and average-end-to-end ***,in literature,proposed techniques are verymuch complex which cannot be easily implemented in realworld *** issue leads to the development of lightweight energyefficient routing in flying-IoT *** paper addresses the energy conservation problem in *** paper presents a novel approach for the internet of flying vehicles using DSDV ***-DSDV gives the notion of bellman-ford algorithm consisting of routing updates,information broadcasting,and stale *** shows optimal results in comparison with other contemporary routing *** mobility model is utilized in the scenario of flying networks to check the performance of routing protocols.

关键词： Flying-IoT DSR smart cities UAV’s FANETS

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