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Joint Optimal Scheduling for electric Vehicle Battery Swapping-charging Systems Based on Wind Farms

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CSEE Journal of Power and Energy Systems 2021年第3期7卷 555-566页

作者： Mingfei Ban Jilai Yu Yiyun Yao College of Mechanical and elec-trical engineering Northeast Forestry UniversityHarbin 150040China department of electrical engineering Harbin Institute of TechnologyHarbin 150001China National Renewable Energy Laboratory Golden 80401USA

Insufficiencies in charging facilities limit the broad application of electric vehicles(EVs).In addition,EV can hardly represent a green option if its electricity primarily depends on fossil *** these two problems,this paper studies a battery swapping-charging system based on wind farms(hereinafter referred to as W-BSCS).In a W-BSCS,the wind farms not only supply electricity to the power grid but also cooperate with a centralized charge station(CCS),which can centrally charge EV batteries and then distribute them to multiple battery swapping stations(BSSs).The operational framework of the W-BSCS is analyzed,and some preprocessing technologies are developed to reduce complexity in ***,a joint optimal scheduling model involving a wind power generation plan,battery swapping demand,battery charging and discharging,and a vehicle routing problem(VRP)is *** a heuristic method based on the exhaustive search and the Genetic Algorithm is employed to solve the formulated NP-hard *** results verify the effectiveness of the joint optimal scheduling model,and they also show that the W-BSCS has great potential to promote EVs and wind power.

关键词： Battery swapping station electric vehicle vehicle routing problem wind power

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

Advancements in Liver Tumor Detection:A Comprehensive Review of Various Deep Learning Models

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Computer Modeling in engineering & Sciences 2025年第1期142卷 91-122页

作者： Shanmugasundaram Hariharan D.Anandan Murugaperumal Krishnamoorthy Vinay Kukreja Nitin Goyal Shih-Yu Chen Deptartment of Artificial Intelligence and Data Science Vardhaman College of EngineeringHyderabad501218India Deptartment of CSE V.S.B College of EngineeringKarur639111India Deptartment of electrical and electronics engineering Vardhaman College of EngineeringHyderabad501218India Centre for Research Impact&Outcome Chitkara UniversityRajpura140401PunjabIndia department of Computer Science and engineering School of Engineering and TechnologyCentral University of HaryanaMahendergarh123031HaryanaIndia department of Computer Science and Information engineering National Yunlin University of Science and TechnologyYunlin64002Taiwan Intelligence Recognition Industry Service Research Center National Yunlin University of Science and TechnologyYunlin64002Taiwan

Liver cancer remains a leading cause of mortality worldwide,and precise diagnostic tools are essential for effective treatment *** Tumors(LTs)vary significantly in size,shape,and location,and can present with tissues of similar intensities,making automatically segmenting and classifying LTs from abdominal tomography images crucial and *** review examines recent advancements in Liver Segmentation(LS)and Tumor Segmentation(TS)algorithms,highlighting their strengths and limitations regarding precision,automation,and *** metrics are utilized to assess key detection algorithms and analytical methods,emphasizing their effectiveness and relevance in clinical *** review also addresses ongoing challenges in liver tumor segmentation and identification,such as managing high variability in patient data and ensuring robustness across different imaging *** suggests directions for future research,with insights into technological advancements that can enhance surgical planning and diagnostic accuracy by comparing popular *** paper contributes to a comprehensive understanding of current liver tumor detection techniques,provides a roadmap for future innovations,and improves diagnostic and therapeutic outcomes for liver cancer by integrating recent progress with remaining challenges.

关键词： Liver tumor detection liver tumor segmentation image processing liver tumor diagnosis feature extraction tumor classification deep learning machine learning

Impact of Pollutant Concentration and Particle Deposition on the Radiative Flow of Casson-Micropolar Fluid between Parallel Plates

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Computer Modeling in engineering & Sciences 2025年第1期142卷 665-690页

作者： Ghaliah Alhamzi Badr Saad T.Alkahtani Ravi Shanker Dubey Vinutha Kalleshachar Neelima Nizampatnam department of Mathematics and Statistics College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11564Saudi Arabia department of Mathematics College of ScienceKing Saud UniversityRiyadh11989Saudi Arabia department of Mathematics Amity School of Applied SciencesAmity University RajasthanJaipur302002RajasthanIndia department of Studies in Mathematics Davangere UniversityDavangere577002India department of electronics and Communication engineering Amrita School of EngineeringAmrita Vishwa VidyapeethamBengaluru560035India

Assessing the behaviour and concentration of waste pollutants deposited between two parallel plates is essential for effective environmental *** the effectiveness of treatment methods in reducing pollution scales is made easier by analysing waste discharge *** waste discharge concentration analysis is useful for assessing how effectively wastewater treatment techniques reduce pollution *** study aims to explore the Casson micropolar fluid flow through two parallel plates with the influence of pollutant concentration and thermophoretic particle *** explore the mass and heat transport features,thermophoretic particle deposition and thermal radiation are *** governing equations are transformed into ordinary differential equations with the help of suitable similarity *** Runge-Kutta-Fehlberg’s fourthfifth order technique and shooting procedure are used to solve the reduced set of equations and boundary *** integration of a neural network model based on the Levenberg-Marquardt algorithm serves to improve the accuracy of predictions and optimize the analysis of *** outcomes are displayed to analyze the characteristics of the relevant dimensionless parameters in the current *** reveal that concentration upsurges as the micropolar parameter *** concentration reduces with an upsurge in the thermophoretic *** upsurge in the external pollutant source variation and the local pollutant external source parameters enhances mass *** surface drag force declines for improved values of porosity and micropolar parameters.

关键词： Micropolar fluid thermal radiation porous medium thermophoretic particle deposition waste discharge concentration

Modeling and Comprehensive Review of Signaling Storms in 3GPP-Based Mobile Broadband Networks:Causes,Solutions,and Countermeasures

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Computer Modeling in engineering & Sciences 2025年第1期142卷 123-153页

作者： Muhammad Qasim Khan Fazal Malik Fahad Alturise Noor Rahman department of Computer Science Iqra National UniversityPeshawar25000Pakistan department of Cybersecurity College of ComputerQassim UniversityBuraydah52555Saudi Arabia department of Computer Science and engineering Al-Fayha CollegeAl Jubayl31961Saudi Arabia

Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband ***,they consume important and scarce network resources such as bandwidth and processing *** have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial *** paper draws its motivation from such real network disaster incidents attributed to signaling *** this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and *** provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding *** important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a *** paper presents an update and an extension of our earlier conference *** our knowledge,no similar survey study exists on the subject.

关键词： Signaling storm problems control signaling load analytical modeling 3GPP networks smart devices diameter signaling mobile broadband data access data traffic mobility management signaling network architecture 5G mobile communication

System Modeling and Optimal Dispatching of Multi-energy Microgrid with Energy Storage

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Journal of Modern Power Systems and Clean Energy 2020年第5期8卷 809-819页

作者： Liting Tian Lin Cheng Jianbo Guo Kuihua Wu department of elec trical engineering Tsinghua UniversityBeijingChina China electric Power Research Institute BeijingChina Economic&Technology Research Institute State Grid Shan dong Electric Power CompanyJinanShandongChina

The coordinated operation and comprehensive utilization of multi-energy sources require systematic research.A multi-energy microgrid(MEMG)is a coupling system with multiple inputs and *** this paper,a system model based on unified energy flows is proposed to describe the static relationship,and an analogue energy storage model is proposed to represent the time-dependency characteristics of energy transfer ***,the optimal dispatching model of an MEMG is established as a mixed-integer linear programming(MILP)problem using piecewise linear approximation and convex ***,the system model and optimal dispatching method are validated in an MEMG,including district electricity,natural gas and heat supply,and renewable *** proposed model and method provide an effective way for the energy flow analysis and optimization of MEMGs.

关键词： Energy flow energy storage multi-energy microgrid(MEMG) optimal dispatching

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Prediction of Shear Bond Strength of Asphalt Concrete Pavement Using Machine Learning Models and Grid Search Optimization Technique

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Computer Modeling in engineering & Sciences 2025年第1期142卷 691-712页

作者： Quynh-Anh Thi Bui Dam Duc Nguyen Hiep Van Le Indra Prakash Binh Thai Pham Civil engineering department University of Transport Technology54 Trieu KhucThanh XuanHanoi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India

Determination of Shear Bond strength(SBS)at interlayer of double-layer asphalt concrete is crucial in flexible pavement *** study used three Machine Learning(ML)models,including K-Nearest Neighbors(KNN),Extra Trees(ET),and Light Gradient Boosting Machine(LGBM),to predict SBS based on easily determinable input ***,the Grid Search technique was employed for hyper-parameter tuning of the ML models,and cross-validation and learning curve analysis were used for training the *** models were built on a database of 240 experimental results and three input variables:temperature,normal pressure,and tack coat *** validation was performed using three statistical criteria:the coefficient of determination(R2),the Root Mean Square Error(RMSE),and the mean absolute error(MAE).Additionally,SHAP analysis was also used to validate the importance of the input variables in the prediction of the *** show that these models accurately predict SBS,with LGBM providing outstanding ***(Shapley Additive explanation)analysis for LGBM indicates that temperature is the most influential factor on ***,the proposed ML models can quickly and accurately predict SBS between two layers of asphalt concrete,serving practical applications in flexible pavement structure design.

关键词： Shear bond asphalt pavement grid search optimization machine learning

Revealing and predicting the long-term biomechanical response of orthokeratology by developing a patient-specific computational model

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 156-168页

作者： Yifeng Li Zhuoran Yang Ziming Yan Huibin Shi Zhanli Liu Kaijie Wang department of engineering Mechanics School of Aerospace Engineering Tsinghua University Beijing Tongren Eye Center Beijing Tongren Hospital Capital Medical University Beijing Ophthalmology & Visual Sciences Key Lab

Orthokeratology(OK) is widely used for effective myopia correction and control. However, the incomplete understanding of its biomechanical mechanisms makes OK lens fitting rely heavily on clinician judgment, complicating accurate predictions of treatment outcomes. In this paper, we performed clinical experiments and numerical analysis to study corneal deformation modes and long-term changes in central corneal thickness. Clinical experiments were conducted on 194 Chinese myopic patients under OK treatment for 3 months. Based on the experimental data, a patient-specific computational biomechanical model for OK was established and validated. Specifically, the anisotropic mechanical properties of the cornea were incorporated into the model to describe the significant difference between its shear modulus(29.5 kPa) and tensile modulus(768.4 kPa). Additionally, a viscohyperelastic material model with a prolonged corneal relaxation time of 5.6 h was developed to capture the long-term deformation response. The results show that corneal thickness reduction in OK is primarily due to out-of-plane shear deformation,influenced by the cornea's low shear resistance. Modeling the extended corneal relaxation time is crucial for predicting long-term biomechanical responses. The computational model effectively captures long-term changes in central corneal thickness, potentially improving OK lens fitting accuracy.

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Aligned Ion Conduction Pathway of Polyrotaxane‑Based electrolyte with Dispersed Hydrophobic Chains for Solid‑State Lithium–Oxygen Batteries

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Nano-Micro Letters 2025年第2期17卷 169-186页

作者： Bitgaram Kim Myeong‑Chang Sung Gwang‑Hee Lee Byoungjoon Hwang Sojung Seo Ji‑Hun Seo Dong‑Wan Kim department of Materials Science and engineering Korea University145 Anam‑RoSeongbuk‑GuSeoul 02841Republic of Korea School of Civil Environmental and Architectural EngineeringKorea University145 Anam‑RoSeongbuk‑GuSeoul 02841Republic of Korea Materials Science and Chemical engineering Center Institute for Advanced Engineering(IAE)Yongin 17180Republic of Korea

A critical challenge hindering the practical application of lithium–oxygen batteries(LOBs)is the inevitable problems associated with liquid electrolytes,such as evaporation and safety *** study addresses these problems by proposing a modified polyrotaxane(mPR)-based solid polymer electrolyte(SPE)design that simultaneously mitigates solvent-related problems and improves ***-SPE exhibits high ion conductivity(2.8×10^(−3)S cm^(−1)at 25℃)through aligned ion conduction pathways and provides electrode protection ability through hydrophobic chain *** this mPR-SPE into solid-state LOBs resulted in stable potentials over 300 *** situ Raman spectroscopy reveals the presence of an LiO_(2)intermediate alongside Li_(2)O_(2)during oxygen *** situ X-ray diffraction confirm the ability of the SPE to hinder the permeation of oxygen and moisture,as demonstrated by the air permeability *** present study suggests that maintaining a low residual solvent while achieving high ionic conductivity is crucial for restricting the sub-reactions of solid-state LOBs.

关键词： Solid polymer electrolyte Lithium-oxygen batteries Polyrotaxane ion conductivity Hydrophobic chain

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