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An Implementation of Multiscale Line Detection and Mathematical Morphology for Efficient and Precise Blood Vessel Segmentation in Fundus Images

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Computers, Materials & Continua 2024年第5期79卷 2565-2583页

作者： Syed Ayaz Ali Shah Aamir Shahzad Musaed Alhussein Chuan Meng Goh Khursheed Aurangzeb Tong Boon Tang Muhammad Awais Department of Electrical and Computer Engineering COMSATS University IslamabadAbbottabad CampusAbbottabad22060Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Faculty of Information and Communication Technology University Tunku Abdul RehmanKampar CampusKampar31900Malaysia Centre for Intelligent Signal and Imaging Research University Teknologi PETRONASBandar Seri IskandarPerak32610Malaysia School of Computing Sciences University of East AngliaNorwichNR47TJUK

Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood *** task is particularly challenging when dealing with color fundus images due to issues like non-uniformillumination,low contrast,and variations in vessel appearance,especially in the presence of different ***,the speed of the retinal vessel segmentation system is of utmost *** the surge of now available big data,the speed of the algorithm becomes increasingly important,carrying almost equivalent weightage to the accuracy of the *** address these challenges,we present a novel approach for retinal vessel segmentation,leveraging efficient and robust techniques based on multiscale line detection and mathematical *** algorithm’s performance is evaluated on two publicly available datasets,namely the Digital Retinal Images for Vessel Extraction dataset(DRIVE)and the Structure Analysis of Retina(STARE)*** experimental results demonstrate the effectiveness of our method,withmean accuracy values of 0.9467 forDRIVE and 0.9535 for STARE datasets,aswell as sensitivity values of 0.6952 forDRIVE and 0.6809 for STARE ***,our algorithmexhibits competitive performance with state-of-the-art ***,it operates at an average speed of 3.73 s per image for DRIVE and 3.75 s for STARE *** is worth noting that these results were achieved using Matlab scripts containing multiple *** suggests that the processing time can be further reduced by replacing loops with *** the proposed algorithm can be deployed in real time *** summary,our proposed system strikes a fine balance between swift computation and accuracy that is on par with the best available methods in the field.

关键词： Line detector vessel detection localization mathematical morphology image processing

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A Distributionally Robust Optimization Scheduling Model for Regional Integrated Energy Systems Considering Hot Dry Rock Co-Generation

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1387-1404页

作者： Hao Qi Mohamed Sharaf Andres Annuk Adrian Ilinca Mohamed A.Mohamed College of Electrical and New Energy China Three Gorges UniversityYichang443002China Department of Industrial Engineering College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia Institute of Forestry and Engineering Estonian University of Life SciencesTartu51006Estonia Department of Mechanical Engineering école de Technologie SupérieureMontréalQC H3C 1K3Canada Electrical Engineering Department Faculty of EngineeringMinia UniversityMinia61519Egypt

Hot dry rock(HDR)is rich in reserve,widely distributed,green,low-carbon,and has broad development potential and *** this paper,a distributionally robust optimization(DRO)scheduling model for a regionally integrated energy system(RIES)considering HDR co-generation is ***,the HDR-enhanced geothermal system(HDR-EGS)is introduced into the ***-EGS realizes the thermoelectric decoupling of combined heat and power(CHP)through coordinated operation with the regional power grid and the regional heat grid,which enhances the system wind power(WP)feed-in ***,peak-hour loads are shifted using price demand response guidance in the context of time-of-day ***,the optimization objective is established to minimize the total cost in the RIES scheduling cycle and construct a DRO scheduling model for RIES with *** simulating a real small-scale RIES,the results show that HDR-EGS can effectively promote WP consumption and reduce the operating cost of the system.

关键词： Energy harvesting integrated energy systems optimum scheduling time-of-use pricing demand response geothermal energy

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Synergistic Swarm Optimization Algorithm

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2557-2604页

作者： Sharaf Alzoubi Laith Abualigah Mohamed Sharaf Mohammad Sh.Daoud Nima Khodadadi Heming Jia Faculty of Computer Sciences and Informatics Amman Arab UniversityAmman11953Jordan Computer Science Department Al Al-Bayt UniversityMafraq25113Jordan Department of Electrical and Computer Engineering Lebanese American UniversityByblos13-5053Lebanon Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan MEU Research Unit Middle East UniversityAmman11831Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains MalaysiaPulau Pinang11800Malaysia School of Engineering and Technology Sunway University MalaysiaPetaling Jaya27500Malaysia Department of Industrial Engineering College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia College of Engineering Al Ain UniversityAbu Dhabi112612United Arab Emirates Department of Civil and Architectural Engineering University of MiamiCoral Gables1251USA School of Information Engineering Sanming UniversitySanming365004China

This research paper presents a novel optimization method called the Synergistic Swarm Optimization Algorithm(SSOA).The SSOA combines the principles of swarmintelligence and synergistic cooperation to search for optimal solutions efficiently.A synergistic cooperation mechanism is employed,where particles exchange information and learn from each other to improve their search *** cooperation enhances the exploitation of promising regions in the search space while maintaining exploration ***,adaptive mechanisms,such as dynamic parameter adjustment and diversification strategies,are incorporated to balance exploration and *** leveraging the collaborative nature of swarm intelligence and integrating synergistic cooperation,the SSOAmethod aims to achieve superior convergence speed and solution quality performance compared to other optimization *** effectiveness of the proposed SSOA is investigated in solving the 23 benchmark functions and various engineering design *** experimental results highlight the effectiveness and potential of the SSOA method in addressing challenging optimization problems,making it a promising tool for a wide range of applications in engineering and *** codes of SSOA are available at:https://***/matlabcentral/fileexchange/153466-synergistic-swarm-optimization-algorithm.

关键词： Synergistic swarm optimization algorithm optimization algorithm metaheuristic engineering problems benchmark functions

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Scientific Elegance in NIDS: Unveiling Cardinality Reduction, Box-Cox Transformation, and ADASYN for Enhanced Intrusion Detection

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Computers, Materials & Continua 2024年第6期79卷 3897-3912页

作者： Amerah Alabrah Department of Information Systems College of Computer and Information Sciences King Saud UniversityRiyadh11451Saudi Arabia

The emergence of digital networks and the wide adoption of information on internet platforms have given rise to threats against users’private *** intruders actively seek such private data either for sale or other inappropriate ***,national and international organizations have country-level and company-level private information that could be accessed by different network ***,the need for a Network Intruder Detection System(NIDS)becomes essential for protecting these networks and *** the evolution of NIDS,Artificial Intelligence(AI)assisted tools and methods have been widely adopted to provide effective ***,the development of NIDS still faces challenges at the dataset and machine learning levels,such as large deviations in numeric features,the presence of numerous irrelevant categorical features resulting in reduced cardinality,and class imbalance in multiclass-level *** address these challenges and offer a unified solution to NIDS development,this study proposes a novel framework that preprocesses datasets and applies a box-cox transformation to linearly transform the numeric features and bring them into closer *** reduction was applied to categorical features through the binning ***,the class imbalance dataset was addressed using the adaptive synthetic sampling data generation ***,the preprocessed,refined,and oversampled feature set was divided into training and test sets with an 80–20 ratio,and two experiments were *** Experiment 1,the binary classification was executed using four machine learning classifiers,with the extra trees classifier achieving the highest accuracy of 97.23%and an AUC of *** Experiment 2,multiclass classification was performed,and the extra trees classifier emerged as the most effective,achieving an accuracy of 81.27%and an AUC of *** results were evaluated based on training,testing,and total time,and a com

关键词： Adaptive synthetic sampling class imbalance features cardinality network security over sampling

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An Intelligent MCGDM Model in Green Suppliers Selection Using Interactional Aggregation Operators for Interval-Valued Pythagorean Fuzzy Soft Sets

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1829-1862页

作者： Rana Muhammad Zulqarnain Wen-Xiu Ma Imran Siddique Hijaz Ahmad Sameh Askar School of Mathematical Sciences Zhejiang Normal UniversityJinhua321004China Department of Mathematics and Statistics University of South FloridaTampaFL 33620-5700USA School of Mathematical and Statistical Sciences North-West UniversityMafikeng CampusMmabatho2735South Africa Department of Mathematics University of SargodhaSargodha40100Pakistan Section of Mathematics International Telematic University UninettunoCorso Vittorio Emanuele IIRoma00186Italy Near East university Operational Research Center in HealthcareNicosia/Mersin99138Turkey Department of Statistics and Operations Research College of ScienceKing Saud UniversityRiyadh11451Saudi Arabia

Green supplier selection is an important debate in green supply chain management(GSCM),attracting global attention from scholars,especially companies and *** frequently search for new ideas and strategies to assist them in realizing sustainable *** of the speculative character of human opinions,supplier selection frequently includes unreliable data,and the interval-valued Pythagorean fuzzy soft set(IVPFSS)provides an exceptional capacity to cope with excessive fuzziness,inconsistency,and inexactness through the decision-making *** main goal of this study is to come up with new operational laws for interval-valued Pythagorean fuzzy soft numbers(IVPFSNs)and create two interaction operators-the intervalvalued Pythagorean fuzzy soft interaction weighted average(IVPFSIWA)and the interval-valued Pythagorean fuzzy soft interaction weighted geometric(IVPFSIWG)operators,and analyze their *** operators are highly advantageous in addressing uncertain problems by considering membership and non-membership values within intervals,providing a superior solution to other ***,specialist judgments were calculated by the MCGDM technique,supporting the use of interaction AOs to regulate the interdependence and fundamental partiality of green supplier assessment ***,a statistical clarification of the planned method for green supplier selection is presented.

关键词： Interval-valued Pythagorean fuzzy soft set IVPFSIWA operator IVPFSIWG operator MCGDM SCM

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RPL-Based IoT Networks under Decreased Rank Attack:Performance Analysis in Static and Mobile Environments

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Computers, Materials & Continua 2024年第1期78卷 227-247页

作者： Amal Hkiri Mouna Karmani Omar Ben Bahri Ahmed Mohammed Murayr Fawaz Hassan Alasmari Mohsen Machhout Physic Department Electronics and Micro-Electronics LaboratoryFaculty of Sciences of MonastirMonastir5000Tunisia Department of Science and Technology College of RanyahTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

The RPL(IPv6 Routing Protocol for Low-Power and Lossy Networks)protocol is essential for efficient communi-cation within the Internet of Things(IoT)*** its significance,RPL’s susceptibility to attacks remains a *** paper presents a comprehensive simulation-based analysis of the RPL protocol’s vulnerability to the decreased rank attack in both static andmobilenetwork *** employ the Random Direction Mobility Model(RDM)for mobile scenarios within the Cooja *** systematic evaluation focuses on critical performance metrics,including Packet Delivery Ratio(PDR),Average End to End Delay(AE2ED),throughput,Expected Transmission Count(ETX),and Average Power Consumption(APC).Our findings illuminate the disruptive impact of this attack on the routing hierarchy,resulting in decreased PDR and throughput,increased AE2ED,ETX,and *** results underscore the urgent need for robust security measures to protect RPL-based IoT ***,our study emphasizes the exacerbated impact of the attack in mobile scenarios,highlighting the evolving security requirements of IoT networks.

关键词： RPL decreased rank attacks mobility random direction model

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Explainable Conformer Network for Detection of COVID-19 Pneumonia from Chest CT Scan: From Concepts toward Clinical Explainability

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Computers, Materials & Continua 2024年第1期78卷 1171-1187页

作者： Mohamed Abdel-Basset Hossam Hawash Mohamed Abouhawwash S.S.Askar Alshaimaa A.Tantawy Faculty of Computers and Informatics Zagazig UniversityZagazig44519Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Statistics and Operations Research College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

The early implementation of treatment therapies necessitates the swift and precise identification of COVID-19 pneumonia by the analysis of chest CT *** study aims to investigate the indispensable need for precise and interpretable diagnostic tools for improving clinical decision-making for COVID-19 *** paper proposes a novel deep learning approach,called Conformer Network,for explainable discrimination of viral pneumonia depending on the lung Region of Infections(ROI)within a single modality radiographic CT ***,an efficient U-shaped transformer network is integrated for lung image ***,a robust transfer learning technique is introduced to design a robust feature extractor based on pre-trained lightweight Big Transfer(BiT-L)and finetuned on medical data to effectively learn the patterns of infection in the input ***,this work presents a visual explanation method to guarantee clinical explainability for decisions made by Conformer *** evaluation of real-world CT data demonstrated that the diagnostic accuracy of ourmodel outperforms cutting-edge studies with statistical *** Conformer Network achieves 97.40% of detection accuracy under cross-validation *** model not only achieves high sensitivity and specificity but also affords visualizations of salient features contributing to each classification decision,enhancing the overall transparency and trustworthiness of our *** findings provide obvious implications for the ability of our model to empower clinical staff by generating transparent intuitions about the features driving diagnostic decisions.

关键词： Deep learning COVID-19 multi-modal medical image fusion diagnostic image fusion

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Adaptation of Federated Explainable Artificial Intelligence for Efficient and Secure E-Healthcare Systems

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Computers, Materials & Continua 2024年第3期78卷 3413-3429页

作者： Rabia Abid Muhammad Rizwan Abdulatif Alabdulatif Abdullah Alnajim Meznah Alamro Mourade Azrour Department of Computer Science Kinnaird College for WomenLahorePakistan College of Science and Engineering University of DerbyDerbyDE221GBUK Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia STI Laboratory IDMS TeamFaculty of Sciences and TechniquesMoulay Ismail University of MeknèsMeknesMorocco

Explainable Artificial Intelligence(XAI)has an advanced feature to enhance the decision-making feature and improve the rule-based technique by using more advanced Machine Learning(ML)and Deep Learning(DL)based *** this paper,we chose e-healthcare systems for efficient decision-making and data classification,especially in data security,data handling,diagnostics,laboratories,and *** Machine Learning(FML)is a new and advanced technology that helps to maintain privacy for Personal Health Records(PHR)and handle a large amount of medical data *** this context,XAI,along with FML,increases efficiency and improves the security of e-healthcare *** experiments show efficient system performance by implementing a federated averaging algorithm on an open-source Federated Learning(FL)*** experimental evaluation demonstrates the accuracy rate by taking epochs size 5,batch size 16,and the number of clients 5,which shows a higher accuracy rate(19,104).We conclude the paper by discussing the existing gaps and future work in an e-healthcare system.

关键词： Artificial intelligence data privacy federated machine learning healthcare system security

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Evaluating the Efficacy of Latent Variables in Mitigating Data Poisoning Attacks in the Context of Bayesian Networks:An Empirical Study

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1635-1654页

作者： Shahad Alzahrani Hatim Alsuwat Emad Alsuwat Independent Researcher Specializing in Data Security and Privacy Taif26571Saudi Arabia Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah24382Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif26571Saudi Arabia

Bayesian networks are a powerful class of graphical decision models used to represent causal relationships among ***,the reliability and integrity of learned Bayesian network models are highly dependent on the quality of incoming data *** of the primary challenges with Bayesian networks is their vulnerability to adversarial data poisoning attacks,wherein malicious data is injected into the training dataset to negatively influence the Bayesian network models and impair their *** this research paper,we propose an efficient framework for detecting data poisoning attacks against Bayesian network structure learning *** framework utilizes latent variables to quantify the amount of belief between every two nodes in each causal model over *** use our innovative methodology to tackle an important issue with data poisoning assaults in the context of Bayesian *** regard to four different forms of data poisoning attacks,we specifically aim to strengthen the security and dependability of Bayesian network structure learning techniques,such as the PC *** doing this,we explore the complexity of this area and offer workablemethods for identifying and reducing these sneaky ***,our research investigates one particular use case,the“Visit to Asia Network.”The practical consequences of using uncertainty as a way to spot cases of data poisoning are explored in this inquiry,which is of utmost *** results demonstrate the promising efficacy of latent variables in detecting and mitigating the threat of data poisoning ***,our proposed latent-based framework proves to be sensitive in detecting malicious data poisoning attacks in the context of stream data.

关键词： Bayesian networks data poisoning attacks latent variables structure learning algorithms adversarial attacks

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Quantitative and Qualitative Responses of Hydroponic Tomato Production to Different Levels of Salinity

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Phyton-International Journal of Experimental Botany 2024年第6期93卷 1311-1323页

作者： Khalid A.Al-Gaadi Ahmed M.Zeyada ElKamil Tola Abdullah M.Alhamdan Khalid A.M.Ahmed Rangaswamy Madugundu Mohamed K.Edrris Department of Agricultural Engineering College of Food and Agriculture SciencesKing Saud UniversityRiyadh11451Saudi Arabia Precision Agriculture Research Chair Deanship of Scientific ResearchKing Saud UniversityRiyadh11451Saudi Arabia Chair of Dates Industry&Technology Deanship of Scientific ResearchKing Saud UniversityRiyadh11451Saudi Arabia Agricultural Research Centre Agricultural Engineering Research Institute(AEnRI)Giza12619Egypt

From economic and nutritional points of view,tomato is,historically,considered one of the most important *** signiﬁcant yield reduction,most commercial cultivars of tomato crops are sensitive to moderate levels of ***,high levels of salt stress can negatively affect the yield and quality of tomato ***,this study was conducted to evaluate the yield and fruit quality of three tomato cultivars(Forester,Ghandowra-F1,and Feisty-Red)cultivated hydroponically,under three different levels of nutrient solution *** of tomato fruits was performed based on quantity(number and weight of fruits,and total fruit yield),physical quality(color andﬁrmness),and chemical quality(refractometric index“Brix”,pH,EC,K^(+),Na^(+),and NO_(3)-).Experiments were conducted using three salinity levels of the nutrient solution with electrical conductivity values(dSm^(-1))of 2.5(control),6.0,and *** showed that the studied tomato cultivars were signiﬁcantly inﬂuenced by high salinity(9.5 dSm^(-1))in comparison to the low(2.5 dSm^(-1))and medium(6.0 dSm^(-1))levels of *** average,the highest fruit weight per plant of 1944.84 g and total fruit yield of 4.42 kgm^(-2) were observed at the low salinity level;however,no signiﬁcant differences were obtained in the two yield factors(single fruit weight and total fruit yield)for the low and medium salinity *** the other hand,a signiﬁcant reduction in tomato yield(31%)was associated with the high salinity level compared to the yield at low and medium salinity *** of physical quality parameters showed highly signiﬁcant differences among all salinity *** average,the maximum value of color change(1.72)was associated with the medium salinity level,and the maximum value ofﬁrmness(9.61 Ncm^(-1))was recorded at the high salinity *** levels and tomato cultivars introduced signiﬁcant differences in chemical quality parameters;however,no signiﬁcant differences in these

关键词： Quality cultivars yield color ﬁrmness brix

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