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Intelligent vehicle routing for stochastic service times: a grouping evolution strategy approach

International Journal of Transportation science and Technology 2025年

作者： Rezvanian, Sepinoud Husseinzadeh Kashan, Ali Rezvanian, Alireza Sabzevari, Alireza Faculty of Industrial and Systems Engineering Tarbiat Modares University Tehran Iraq Department of Computer Engineering University of Science and Culture Tehran Iraq Department of Biomedical Engineering Meybod University Meybod Iraq Department of Chemical Engineering Hamedan University of Technology Hamadan Iraq

After-sales service companies often need to transport and distribute their products, as well as provide services like installation and setup. In this paper, we study a vehicle routing problem (VRP) that considers the possibility of on-site servicing by installers, with stochastic service times. We formulate the distribution of products to customers as a VRP and extract the route plan for installers by solving a traveling salesman-type problem. To model the stochastic service times, we use a chance constraint while minimizing the total cost for both vehicles and installers. We develop a Grouping Evolution Strategy (GES) algorithm equipped with various heuristics to generate efficient solutions for large-scale problems. Numerical results are reported from a case study using existing data for the problem. The computational experiments demonstrate that GES can produce near-optimal solutions for operational use within a reasonable amount of time. In summary, our study shows the effectiveness of GES in solving the VRP with on-site stochastic service times, which is relevant to many after-sales service companies. © 2025 Tongji University and Tongji University Press

关键词： Traveling salesman problem

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Eliciting Requirements from Stakeholders’ Responses Using Natural Language Processing

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computer Modeling in engineering & sciences 2021年第4期127卷 99-116页

作者： Mohammed Lafi Bilal Hawashin Shadi AlZu’bi Department of Software Engineering Faculty of Science and Information TechnologyAl-Zaytoonah University of JordanAmman11733Jordan Department of Computer Information Systems Faculty of Science and Information TechnologyAl-Zaytoonah University of JordanAmman11733Jordan Department of Computer Science Faculty of Science and Information TechnologyAl-Zaytoonah University of JordanAmman11733Jordan

Most software systems have different stakeholders with a variety of *** process of collecting requirements from a large number of stakeholders is vital but *** propose an efficient,automatic approach to collecting requirements from different stakeholders’responses to a specific *** use natural language processing techniques to get the stakeholder response that represents most other stakeholders’*** study improves existing practices in three ways:Firstly,it reduces the human effort needed to collect the requirements;secondly,it reduces the time required to carry out this task with a large number of stakeholders;thirdly,it underlines the importance of using of data mining techniques in various software engineering *** approach uses tokenization,stop word removal,and word lemmatization to create a list of frequently accruing *** then creates a similarity matrix to calculate the score value for each response and selects the answer with the highest *** experiments show that using this approach significantly reduces the time and effort needed to collect requirements and does so with a sufficient degree of accuracy.

关键词： Software requirements requirements elicitation natural language processing

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Micro tool diameter monitoring by means of laser diffraction for on-machine measurement

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International Journal of Automation Technology 2017年第5期11卷 736-741页

作者： Khajornrungruang, Panart Kimura, Keiichi Suzuki, Keisuke Inoue, Tomoki Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Iizuka-shi Fukuoka820-8502 Japan School of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Iizuka Fukuoka820-8502 Japan

This study proposes a non-contact measurement method for evaluating a micro cutting tool diameter at a sub-micrometer precision in atmospheric environment. Practically, non-contact tool measurements are widely used in optical measurement methods. However, the generally used geometrical optical measurement methods do fundamentally not have submicrometer precision due to well-known light diffraction phenomenon, notably when measuring a micro tool. We have been proposing and developing a measurement method especially for the micro tool utilizing laser diffraction. In this study, we subtracted a transparent light component from a laser light distribution diffracted by the micro tool to be measured to enhance diffraction pattern characteristics. Consequently, micro rods having diameters of 15, 20, and 30 µm could be precisely measured. Furthermore, in order to verify themethod validity, a two-helical-fluted micro tool (20 micrometer in diameter) was also measured while rotating (4 min-1) with less than 400 nm difference compared to images from a scanning electron microscopy (SEM) image. Finally, a trial to measure a micro drill diameter was also carried out during high-speed tool rotation (136,800 min-1) with our developed apparatus that is enough compact to be installed to machine tools, in order to perform the measurement in real rotation without stopping the tool rotation. © 2017, Fuji Technology Press. All rights reserved.

关键词： Cutting tools

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Novel Framework of Segmentation 3D MRI of Brain Tumors

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computers, Materials & Continua 2023年第2期74卷 3489-3502页

作者： Ibrahim Mahmoud El-Henawy Mostafa Elbaz Zainab H.Ali Noha Sakr Department of Computer Science Faculty of Computers and InformaticsZagazig UniversityZagazigEgypt Department of Computer Science Faculty of Computers and InformaticsKafrelsheikh UniversityKafrelsheikhEgypt Department of Embedded Network Sys.and Tec. Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikhEgypt Computers Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansouraEgypt

Medical image segmentation is a crucial process for computer-aided diagnosis and *** image segmentation refers to portioning the images into small,disjointed parts for simplifying the processes of analysis and *** and speckle noise are different types of noise in magnetic resonance imaging(MRI)that affect the accuracy of the segmentation process ***,image enhancement has a significant role in MRI *** paper proposes a novel framework that uses 3D MRI images from Kaggle and applies different diverse models to remove Rician and speckle noise using the best possible noise-free *** proposed techniques consider the values of Peak Signal to Noise Ratio(PSNR)and the level of noise as inputs to the attention-U-Net model for segmentation of the *** framework has been divided into three stages:removing speckle and Rician noise,the segmentation stage,and the feature extraction *** framework presents solutions for each problem at a different stage of the *** the first stage,the framework uses Vibrational Mode Decomposition(VMD)along with Block-matching and 3D filtering(Bm3D)algorithms to remove the ***,the most significant Rician noise-free images are passed to the three different methods:Deep Residual Network(DeRNet),Dilated Convolution Auto-encoder Denoising Network(Di-Conv-AE-Net),andDenoising Generative Adversarial Network(DGAN-Net)for removing the speckle *** Bm3D have achieved PSNR values for levels of noise(0,0.25,0.5,0.75)for reducing the Rician noise by(35.243,32.135,28.214,24.124)and(36.11,31.212,26.215,24.123)*** framework also achieved PSNR values for removing the speckle noise process for each level as follows:(34.146,30.313,28.125,24.001),(33.112,29.103,27.110,24.194),and(32.113,28.017,26.193,23.121)forDeRNet,Di-Conv-AE-Net,and DGAN-Net,*** experiments that have been conducted have proved the efficiency of the proposed framework a

关键词： MRI Rician noise speckle noise segmentation deep learning

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A low-cost device-based data approach to Eight Hop Test

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Procedia computer science 2025年 256卷 1135-1142页

作者： Luís Pimenta Paulo Jorge Coelho Norberto Jorge Gonçalves José Paulo Lousado Carlos Albuquerque Nuno M. Garcia Eftim Zdravevski Petre Lameski Ivan Miguel Pires Escola de Ciências e Tecnologia University of Trás-os-Montes e Alto Douro Vila Real Portugal Polytechnic University of Leiria Leiria Portugal Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra) Coimbra Portugal Research Centre in Digital Services (CISeD) Polytechnic Institute of Viseu Portugal Health Sciences Research Unit: Nursing (UICISA: E) Nursing School of Coimbra (ESEnfC) Coimbra Portugal Higher School of Health Polytechnic Institute of Viseu Viseu Portugal Child Studies Research Center (CIEC) University of Minho Braga Portugal Institute of Biophysics and Biomedical Engineering (IBEB) Faculty of Sciences University of Lisbon Lisbon Portugal Faculty of Computer Science and Engineering University Ss Cyril and Methodius Skopje Macedonia Instituto de Telecomunicações Escola Superior de Tecnologia e Gestão de Águeda Universidade de Aveiro Águeda Portugal

The Eight Hop Test is a physical rehabilitation exercise involving jumping with one leg in a circuit similar to the number eight. This study aims to analyze data related to the performance of the test, relating it to gender and pathologies in the population. A mobile application was implemented to acquire accelerometer data, which was then analyzed using various artificial intelligence methods. The study found reliable accuracy in identifying participants’ gender (60%) and specific pathologies (50%), suggesting that mobile sensors can effectively support medical evaluations. Neural Network showed the highest accuracy for multivariate data, while the k-Nearest Neighbor was most effective for binary classifications. The mobile device-based method helps healthcare professionals measure physical strength evolution in lower limb injuries and predicts pathologies with near-100% accuracy using machine learning methods. Future research will explore more individuals and data to improve healthcare treatments and explore new techniques and analyses.

关键词： Eight Hop Test machine learning accelerometer diseases gender

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Distance Matrix and Markov Chain Based Sensor Localization in WSN

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computers, Materials & Continua 2022年第5期71卷 4051-4068页

作者： Omaima Bamasaq Daniyal Alghazzawi Surbhi Bhatia Pankaj Dadheech Farrukh Arslan Sudhakar Sengan Syed Hamid Hassan Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Information Systems College of Computer Science and Information TechnologyKing Faisal UniversitySaudi Arabia Department of Computer Science and Engineering Swami Keshvanand Institute of TechnologyManagement&GramothanJaipurRajasthanIndia University of Engineering and Technology LahorePakistan Department of Computer Science and Engineering PSN College of Engineering and TechnologyTirunelveliTamilnaduIndia

Applications based on Wireless Sensor Networks(WSN)have shown to be quite useful in monitoring a particular geographic area of *** geometries of the surrounding environment are essential to establish a successful WSN *** it is literally hard because constructing a localization algorithm that tracks the exact location of Sensor Nodes(SN)in a WSN is always a challenging *** this research paper,Distance Matrix and Markov Chain(DM-MC)model is presented as node localization technique in which Distance Matrix and Estimation Matrix are used to identify the position of the *** method further employs a Markov Chain Model(MCM)for energy optimization and interference *** are performed against two well-known models,and the results demonstrate that the proposed algorithm improves performance by using less network resources when compared to the existing *** probability is used in the Markova chain to sustain higher energy ***,the proposed Distance Matrix and Markov Chain model decrease energy use by 31%and 25%,respectively,compared to the existing DV-Hop and CSA *** experimental results were performed against two proven models,Distance VectorHop Algorithm(DV-HopA)and Crow Search Algorithm(CSA),showing that the proposed DM-MC model outperforms both the existing models regarding localization accuracy and Energy Consumption(EC).These results add to the credibility of the proposed DC-MC model as a better model for employing node localization while establishing a WSN framework.

关键词： Wireless sensor network resource optimization routing distance matrix Markov chain

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Historical Arabic Images Classification and Retrieval Using Siamese Deep Learning Model

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computers, Materials & Continua 2022年第7期72卷 2109-2125页

作者： Manal M.Khayyat Lamiaa A.Elrefaei Mashael M.Khayyat Computer Science Department Umm Al-Qura UniversityMakkahSaudi Arabia Computer Science Department King Abdulaziz UniversityJeddahSaudi Arabia Electrical Engineering Department Faculty of Engineering at ShoubraBenha UniversityCairoEgypt Department of Information Systems and Technology College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia

Classifying the visual features in images to retrieve a specific image is a significant problem within the computer vision field especially when dealing with historical faded colored ***,there were lots of efforts trying to automate the classification operation and retrieve similar images *** reach this goal,we developed a VGG19 deep convolutional neural network to extract the visual features from the images ***,the distances among the extracted features vectors are measured and a similarity score is generated using a Siamese deep neural *** Siamese model built and trained at first from scratch but,it didn’t generated high evaluation ***,we re-built it from VGG19 pre-trained deep learning model to generate higher evaluation ***,three different distance metrics combined with the Sigmoid activation function are experimented looking for the most accurate method formeasuring the similarities among the retrieved *** that the highest evaluation parameters generated using the Cosine distance ***,the Graphics Processing Unit(GPU)utilized to run the code instead of running it on the Central Processing Unit(CPU).This step optimized the execution further since it expedited both the training and the retrieval time *** extensive experimentation,we reached satisfactory solution recording 0.98 and 0.99 F-score for the classification and for the retrieval,respectively.

关键词： Visual features vectors deep learning models distance methods similar image retrieval

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Metaheuristic Optimization for Mobile Robot Navigation Based on Path Planning

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computers, Materials & Continua 2022年第11期73卷 2241-2255页

作者： El-Sayed M.El-kenawy Zeeshan Shafi Khan Abdelhameed Ibrahim Bandar Abdullah Aloyaydi Hesham Arafat Ali Ali E.Takieldeen Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Computer Science Department College of Engineering and Computer ScienceMustaqbal UniversityBuraidahSaudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Mechanical Engineering Qassim UniversityBuraidah51452Saudi Arabia

Recently,the path planning problem may be considered one of the most interesting researched topics in autonomous *** is why finding a safe path in a cluttered environment for a mobile robot is a significant requisite.A promising route planning for mobile robots on one side saves time and,on the other side,reduces the wear and tear on the robot,saving the capital *** route planning methods for the mobile robot have been developed and *** to our best knowledge,no method offers an optimum solution among the existing *** Swarm Optimization(PSO),a numerical optimization method based on the mobility of virtual particles in a multidimensional space,is considered one of the best algorithms for route planning under constantly changing environmental *** the researchers,reactive methods are increasingly common and extensively used for the training of neural networks in order to have efficient route planning for mobile *** paper proposes a PSO Weighted Grey Wolf Optimization(PSOWGWO)*** is a hybrid algorithm based on enhanced Grey Wolf Optimization(GWO)with *** order to measure the statistical efficiency of the proposed algorithm,Wilcoxon rank-sum and ANOVA statistical tests are *** experimental results demonstrate a 25%to 45%enhancement in terms of Area Under Curve(AUC).Moreover,superior performance in terms of data size,path planning time,and accuracy is demonstrated over other state-of-the-art techniques.

关键词： Mobile robot swarm optimization robot route planning neural networks

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Fabrication, characterization and response surface method optimization for quantum efficiency of fluorescent nitrogen-doped carbon dots obtained from carboxymethylcellulose of oil palms empty fruit bunch

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Chinese Journal of Chemical engineering 2020年第2期28卷 584-592页

作者： Mohammed Abdullah Issa Zurina Zainal Abidin Shafreeza Sobri Suraya Abdul-Rashid Mohd Adzir Mahdi Nor Azowa Ibrahim Musa Y.Pudza Department of Chemical and Environmental Engineering Faculty of EngineeringUniversiti Putra Malaysia43400 UPM SerdangSelangorMalaysia Department of Computer&Communications Systems Engineering Faculty of EngineeringUniversiti Putra Malaysia43400 UPM SerdangSelangorMalaysia Department of Chemistry Faculty of ScienceUniversiti Putra Malaysia43400 SerdangSelangorMalaysia

Bio based nitrogen doped carbon dots(N-CDs)were obtained from empty fruit bunch carboxymethylcellulose and ethylenediamine(EDA)through one-pot hydrothermal carbonization *** optimum as-formed NCDs were thoroughly characterized via Transmission electron microscopy(TEM),high-resolution TEM(HRTEM),Fourier transform infrared(FTIR),X-ray photoelectron spectra(XPS),UV–vis spectra(UV–Vis)and Fluorescence spectra(PL).Response surface methodology was statistically used to assess three independent variables that have major influence on the fluorescence quantum yield(QY),including temperature(230–270℃),time(2–6 h)and EDA mass(10%–23.3%).Based on analysis of variance(ANOVA)results,synthesis temperature was found to be the most influential factor on the QY,followed by time and EDA *** temperature,long synthesis time and high amount of EDA were satisfactorily enough for efficient carbonization conversion rate and obtaining highest QY of *** obtained quadratic model(R^2=0.9991)shows a good correlation between the experimental data and predicted *** optimum synthetic parameters are of 270℃temperature,6 h reaction time and 23.3%of EDA *** optimized as-made N-CDs exhibited blue photoluminescence with both excitation dependent/independent phenomena and high nitrogen *** maximum emission intensity was 426 nm at a maximum excitation wavelength of 320 nm,with a QY of up to 22.9%.XPS and FTIR data confirmed the existence of polar containing groups,such as carbonyl,carboxyl,hydroxyl and amino groups over the surface of N-CDs whereas nitrogen species in the form of(pyridinic and graphitic-N)were introduced in the aromatic carbon domains,which imparts the hydrophilic and photostability of *** into account the low-cost and sustainable production of N-CDs,this method considered a feasible route for converting low quality waste into value-added nanomaterials and utilizing for different functionalization processes and analytical applications.

关键词： Carbon dots Fluorescence Response surface methodology Optimization Nitrogen doped

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Generation of High-Quality Relevant Judgments through Document Similarity and Document Pooling for the Evaluation of Information Retrieval systems 14

Generation of High-Quality Relevant Judgments through Docume...

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14th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2022

作者： Joseph, Minnu Helen Ravana, Sri Devi University of Malaya Faculty of Computer Science & Information Technology Department of Information Systems Malaysia Faculty of Computer Science Engineering & Technology Malaysia

ISBN: (纸本)9781665493345

The Information Retrieval System Evaluation have carried out through Cranfield-paradigm in which the test collections provide the foundation of the evaluation process. The test collections consist of document corpus, topics, and a set of relevance judgements. The relevant judgements are the documents which retrieved from the test collections based on the topics. The precision of the evaluation process is based on the number of relevant documents in the relevant judgement list called qrels. This paper presents a study on how methodologies like pooling and document similarity helps to generate more relevant documents into the relevance judgments set in order to increase the accuracy of the evaluation process. The initial results have shown that combination of pooling with document similarity performs better compared to base clustering or classification. © 2022 IEEE.

关键词： Information retrieval systems

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