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A Novel Self-Supervised Learning Network for Binocular Disparity Estimation

Computer Modeling in Engineering & Sciences 2025年第1期142卷 209-229页

作者： Jiawei Tian Yu Zhou Xiaobing Chen Salman A.AlQahtani Hongrong Chen Bo Yang Siyu Lu Wenfeng Zheng Department of Computer Science and Engineering Major in Bio Artificial IntelligenceHanyang UniversityAnsan-si15577Republic of Korea school of Electrical and Computer Engineering Louisiana State UniversityBaton RougeLA 70803USA Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11574Saudi Arabia school of Automation University of Electronic Science and Technology of ChinaChengdu610054China

Two-dimensional endoscopic images are susceptible to interferences such as specular reflections and monotonous texture illumination,hindering accurate three-dimensional lesion reconstruction by surgical *** study proposes a novel end-to-end disparity estimation model to address these *** approach combines a Pseudo-Siamese neural network architecture with pyramid dilated convolutions,integrating multi-scale image information to enhance robustness against lighting *** study introduces a Pseudo-Siamese structure-based disparity regression model that simplifies left-right image comparison,improving accuracy and *** model was evaluated using a dataset of stereo endoscopic videos captured by the Da Vinci surgical robot,comprising simulated silicone heart sequences and real heart video *** results demonstrate significant improvement in the network’s resistance to lighting interference without substantially increasing ***,the model exhibited faster convergence during training,contributing to overall performance *** study advances endoscopic image processing accuracy and has potential implications for surgical robot applications in complex environments.

关键词： Parallax estimation parallax regression model self-supervised learning Pseudo-Siamese neural network pyramid dilated convolution binocular disparity estimation

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Congruent Feature Selection Method to Improve the Efficacy of Machine Learning-Based Classification in Medical Image Processing

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 357-384页

作者： Mohd Anjum Naoufel Kraiem Hong Min Ashit Kumar Dutta Yousef Ibrahim Daradkeh Department of Computer Engineering Aligarh Muslim UniversityAligarh202002India College of Computer Science King Khalid UniversityAbha61413Saudi Arabia school of Computing Gachon UniversitySeongnam13120Republic of Korea Department of Computer Science and information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia Department of Computer Engineering and information College of Engineering in Wadi AlddawasirPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia

Machine learning(ML)is increasingly applied for medical image processing with appropriate learning *** applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for *** primary concern of ML applications is the precise selection of flexible image features for pattern detection and region *** of the extracted image features are irrelevant and lead to an increase in computation ***,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image *** process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel *** similarity between the pixels over the various distribution patterns with high indexes is recommended for disease ***,the correlation based on intensity and distribution is analyzed to improve the feature selection ***,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the ***,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of ***,the probability of feature selection,regardless of the textures and medical image patterns,is *** process enhances the performance of ML applications for different medical image *** proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected *** mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.

关键词： Computer vision feature selection machine learning region detection texture analysis image classification medical images

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A Multi-Stage Secure IoT Authentication Protocol

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Computer Systems Science & Engineering 2023年第4期45卷 459-481页

作者： Khalid Alhusayni Raniyah Wazirali Mousa AlAkhras Marwah Almasri Samah Alhazmi College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia king abdullah ii school for information technology The University of JordanAmman11942Jordan

The Internet of Things(IoT)is a network of heterogeneous and smart devices that can make decisions without human *** can connect millions of devices across the *** ability to collect information,perform analysis,and even come to meaningful conclusions without human capital intervention *** circumstances require stringent security measures and,in particular,the extent of *** applied in the IoT paradigm point out high-interest levels since enormous damage will occur if a malicious,wrongly authenticated device finds its way into the IoT *** research provides a clear and updated view of the trends in the IoT authentication *** the issues covered include a series of authentication protocols that have remained research gaps in various *** study applies a comparative evaluation of authentication protocols,including their strengths and ***,it forms the foundation in the IoT authentication field of *** that direction,a multi authentication architecture that involves secured means is proposed for protocol *** analysis can affect the security of the ***-Abadi-Needham(BAN)logic provides proof of the attainment of mutual ***3 simulator tool is used to compare the performance of the proposed protocol to verify the formal security offered by the BAN logic.

关键词： Internet of Things(IoT) security authentication BAN logic sensor networks

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Road scene analysis for determination of road traffic density

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Frontiers of Computer Science 2014年第4期8卷 619-628页

作者： Omar AL-KADI Osama AL-KADI Rizik AL-SAYYED Ja'far ALQATAWNA king abdullah lI school for information technology University of Jordan Amman 11942 Jordan College of Engineering and Computer Science Australian National University Canberra ACT 0200 Australia

Road traffic density has always been a concern in large cities around the world, and many approaches were developed to assist in solving congestions related to slow traffic flow. This work proposes a congestion rate estimation approach that relies on real-time video scenes of road traffic, and was implemented and evaluated on eight different hotspots covering 33 different urban roads. The approach relies on road scene morphology for estimation of vehicles average speed along with measuring the overall video scenes randomness acting as a frame texture analysis indicator. Experimental results shows the feasibility of the proposed approach in reliably estimating traffic density and in providing an early warning to drivers on road conditions, thereby mitigating the negative effect of slow traffic flow on their daily lives.

关键词： road congestion image texture local binary pattern scene morphology

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Unique Characteristics of Vertical Carbon Nanotube Field-effect Transistors on Silicon

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Nano-Micro Letters 2014年第3期6卷 287-292页

作者： Jingqi Li Weisheng Yue Zaibing Guo Yang Yang Xianbin Wang Ahad A.Syed Yafei Zhang Nanofab King Abdullah University of Science and Technology Key Laboratory for Thin Film and Microfabrication technology of the Ministry of Education School of Electronics Information and Electrical Engineering Shanghai Jiao Tong University

A vertical carbon nanotube field-effect transistor(CNTFET) based on silicon(Si) substrate has been proposed and simulated using a semi-classical theory. A single-walled carbon nanotube(SWNT) and an n-type Si nanowire in series construct the channel of the transistor. The CNTFET presents ambipolar characteristics at positive drain voltage(Vd) and n-type characteristics at negative Vd. The current is significantly influenced by the doping level of n-Si and the SWNT band gap. The n-branch current of the ambipolar characteristics increases with increasing doping level of the n-Si while the p-branch current decreases. The SWNT band gap has the same influence on the p-branch current at a positive Vd and n-type characteristics at negative Vd. The lower the SWNT band gap, the higher the current. However, it has no impact on the n-branch current in the ambipolar characteristics. Thick oxide is found to significantly degrade the current and the subthreshold slope of the CNTFETs.

关键词： Carbon Nanotube Field-effect Transistors Semi-classical Simulation

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Extending Auditing Models to Correspond with Clients’ Needs in Cloud Environments

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International Journal of Communications, Network and System Sciences 2016年第9期9卷 347-360页

作者： Rizik M. H. Al-Sayyed Esam Y. Al-Nsour Laith M. Al-Omari Department of Business information technology King Abdullah II School for Information Technology The University of Jordan Amman Jordan Department of Computer Science King Abdullah II School for Information Technology The University of Jordan Amman Jordan Department of Computer information Systems King Abdullah II School for Information Technology The University of Jordan Amman Jordan

The user control over the life cycle of data is of an extreme importance in clouds in order to determine whether the service provider adheres to the client’s pre-specified needs in the contract between them or not, significant clients concerns raise on some aspects like social, location and the laws to which the data are subject to. The problem is even magnified more with the lack of transparency by Cloud Service Providers (CSPs). Auditing and compliance enforcement introduce different set of challenges in cloud computing that are not yet resolved. In this paper, a conducted questionnaire showed that the data owners have real concerns about not just the secrecy and integrity of their data in cloud environment, but also for spatial, temporal, and legal issues related to their data especially for sensitive or personal data. The questionnaire results show the importance for the data owners to address mainly three major issues: Their ability to continue the work, the secrecy and integrity of their data, and the spatial, legal, temporal constraints related to their data. Although a good volume of work was dedicated for auditing in the literature, only little work was dedicated to the fulfillment of the contractual obligations of the CSPs. The paper contributes to knowledge by proposing an extension to the auditing models to include the fulfillment of contractual obligations aspects beside the important aspects of secrecy and integrity of client’s data.

关键词： Auditing Public Audibility Dynamic Data Auditing Spatial Control Temporal Control Logging Data Contractual Obligations

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Improving Association Rules Accuracy in Noisy Domains Using Instance Reduction Techniques

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Computers, Materials & Continua 2022年第8期72卷 3719-3749页

作者： Mousa Al-Akhras Zainab Darwish Samer Atawneh Mohamed Habib College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia king abdullah ii school for information technology The University of JordanAmman11942Jordan Faculty of Engineering Port Said UniversityPort Said42523Egypt

Association rules’learning is a machine learning method used in finding underlying associations in large *** intentionally or unintentionally present,noise in training instances causes overfitting while building the classifier and negatively impacts classification *** paper uses instance reduction techniques for the datasets before mining the association rules and building the *** reduction techniques were originally developed to reduce memory requirements in instance-based *** paper utilizes them to remove noise from the dataset before training the association rules *** experiments were conducted to assess the accuracy of association rules with different instance reduction techniques,namely:DecrementalReduction Optimization Procedure(DROP)3,DROP5,ALL K-Nearest Neighbors(ALLKNN),Edited Nearest Neighbor(ENN),and Repeated Edited Nearest Neighbor(RENN)in different noise *** show that instance reduction techniques substantially improved the average classification accuracy on three different noise levels:0%,5%,and 10%.The RENN algorithm achieved the highest levels of accuracy with a significant improvement on seven out of eight used datasets from the University of California Irvine(UCI)machine learning *** improvements were more apparent in the 5%and the 10%noise *** RENN was applied,the average classification accuracy for the eight datasets in the zero-noise test enhanced from 70.47%to 76.65%compared to the original *** average accuracy was improved from 66.08%to 77.47%for the 5%-noise case and from 59.89%to 77.59%in the 10%-noise *** confidence was also reported in building the association rules when RENN was *** above results indicate that RENN is a good solution in removing noise and avoiding overfitting during the construction of the association rules classifier,especially in noisy domains.

关键词： Association rules classification instance reduction techniques classification overfitting noise data cleansing

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Four Sliding Windows Pattern Matching Algorithm (FSW)

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Journal of Software Engineering and Applications 2015年第3期8卷 154-165页

作者： Amjad Hudaib Rola Al-Khalid Aseel Al-Anani Mariam Itriq Dima Suleiman Department of Computer information Systems King Abdullah II School for Information Technology The University of Jordan Amman Jordan Department of Business information technology King Abdullah II School for Information Technology The University of Jordan Amman Jordan

This paper presents an efficient pattern matching algorithm (FSW). FSW improves the searching process for a pattern in a text. It scans the text with the help of four sliding windows. The windows are equal to the length of the pattern, allowing multiple alignments in the searching process. The text is divided into two parts;each part is scanned from both sides simultaneously using two sliding windows. The four windows slide in parallel in both parts of the text. The comparisons done between the text and the pattern are done from both of the pattern sides in parallel. The conducted experiments show that FSW achieves the best overall results in the number of attempts and the number of character comparisons compared to the pattern matching algorithms: Two Sliding Windows (TSW), Enhanced Two Sliding Windows algorithm (ETSW) and Berry-Ravindran algorithm (BR). The best time case is calculated and found to be??while the average case time complexity is??.

关键词： Pattern Matching FWS Enhanced Two Sliding Windows Algorithm RS-A Fast Pattern Matching Algorithm

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Enhancing ERS-A Algorithm for Pattern Matching (EERS-A)

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Journal of Software Engineering and Applications 2015年第3期8卷 143-153页

作者： Dima Suleiman Mariam Itriq Aseel Al-Anani Rola Al-Khalid Amjad Hudaib Department of Business information technology King Abdullah II School for Information Technology The University of Jordan Amman Jordan Department of Computer information Systems King Abdullah II School for Information Technology The University of Jordan Amman Jordan

Pattern matching is a very important topic in computer science. It has been used in various applications such as information retrieval, virus scanning, DNA sequence analysis, data mining, machine learning, network security and pattern recognition. This paper has presented a new pattern matching algorithm—Enhanced ERS-A, which is an improvement over ERS-S algorithm. In ERS-A, two sliding windows are used to scan the text from the left and the right simultaneously. The proposed algorithm also scans the text from the left and the right simultaneously as well as making comparisons with the pattern from both sides simultaneously. The comparisons done between the text and the pattern are done from both sides in parallel. The shift technique used in the Enhanced ERS-A is the four consecutive characters in the text immediately following the pattern window. The experimental results show that the Enhanced ERS-A has enhanced the process of pattern matching by reducing the number of comparisons performed.

关键词： Pattern Matching Enhanced Two Sliding Windows Algorithm RS-A Fast Pattern Matching Algorithm Enhanced RS-A

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Load Balancing for Hex-Cell Interconnection Network

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International Journal of Communications, Network and System Sciences 2016年第4期9卷 98-116页

作者： Saher Manaseer Ahmad Alamoush Osama Rababah Department of Computer Science King Abdullah II School for Information Technology The University of Jordan Amman Jordan Department of Business information technology King Abdullah II School for Information Technology The University of Jordan Amman Jordan

The hex-cell is one of the interconnection networks used for parallel systems. The main idea of the hex-cell is that there are hexagon cells that construct the network;each one of those cells has six nodes. The performance of the network is affected by many factors one of the factors as load balancing. Until the moment of writing of this paper, there is no load balancing algorithm for this network. The proposed algorithm for dynamic load balancing on hex-cell is based on Tree Walking Algorithm (TWA) for load balancing on tree interconnection network and the ring all to all broadcast.

关键词： Hex-Cell Load Balancing Tree Walking

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