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Active Learning and Bayesian Optimization: A Unified Perspective to Learn with a Goal Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-04-23 Francesco Di Fiore, Michela Nardelli, Laura Mainini
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Revolutionizing Dermatology: A Comprehensive Survey of AI-Enhanced Early Skin Cancer Diagnosis Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-04-23 Zinal M. Gohil, Madhavi B. Desai
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The Applications of 3D Input Data and Scalability Element by Transformer Based Methods: A Review Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-04-23 Abubakar Sulaiman Gezawa, Chibiao Liu, Naveed Ur Rehman Junejo, Haruna Chiroma
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A Review of Strategies to Detect Fatigue and Sleep Problems in Aviation: Insights from Artificial Intelligence Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-04-18 Yan Li, Jibo He
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Application of Artificial Intelligence in Aerospace Engineering and Its Future Directions: A Systematic Quantitative Literature Review Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-04-16 Kamal Hassan, Amit Kumar Thakur, Gurraj Singh, Jaspreet Singh, Lovi Raj Gupta, Rajesh Singh
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A Comparative Study and Systematic Analysis of XAI Models and their Applications in Healthcare Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-04-16 Jyoti Gupta, K. R. Seeja
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Advances in Discrete Element Modeling of Asphalt Mixture: A Literature Review Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-04-12 Xinman Ai, Junyan Yi, Zhongshi Pei, Wenyi Zhou, Decheng Feng
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A Computational Framework for Precise Aerial Agricultural Spray Delivery Processes Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-04-12 J. O. Betancourt, I. Li, E. Mengi, L. Corrales, T. I. Zohdi
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Machine Learning in Healthcare Analytics: A State-of-the-Art Review Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-04-04 Surajit Das, Samaleswari P. Nayak, Biswajit Sahoo, Sarat Chandra Nayak
The use of machine learning (ML) models have become a crucial factor in the growing field of healthcare, ushering in a new era of medical research and diagnosis. This study rigorously reviews research publications published in reputable journals during the last five years. The pace and dynamic nature of machine learning in the healthcare domains demonstrated by the arduous criteria, which are used
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Constructing Nitsche’s Method for Variational Problems Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-04-03 Joseph Benzaken, John A. Evans, Rasmus Tamstorf
Nitsche’s method is a well-established approach for weak enforcement of boundary conditions for partial differential equations (PDEs). It has many desirable properties, including the preservation of variational consistency and the fact that it yields symmetric, positive-definite discrete linear systems that are not overly ill-conditioned. In recent years, the method has gained in popularity in a number
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A Systematic Review on Game-Theoretic Models and Different Types of Security Requirements in Cloud Environment: Challenges and Opportunities Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-04-01 Komal Singh Gill, Anju Sharma, Sharad Saxena
The presented survey paper explores the application of game theoretic models for addressing security challenges in cloud computing environments. It highlights the significance of cloud computing as an integral part of modern technology due to its accessibility, scalability, and cost-effectiveness. However, the paper acknowledges that security issues pose a considerable concern in cloud computing, surpassing
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A Comprehensive Review: Applications of the Kozeny–Carman Model in Engineering with Permeability Dynamics Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-04-01 Maryam Rehman, Muhammad Bilal Hafeez, Marek Krawczuk
In this review article, we investigate the dynamic nature of the Kozeny–Carman Model concerning permeability and its application in engineering contexts. Providing insights into the changing dynamics of permeability within mining, petroleum, and geotechnical engineering, among other engineering applications. While some are complex and require additional modifications to be applicable, others are simple
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A Metaheuristic Perspective on Extracting Numeric Association Rules: Current Works, Applications, and Recommendations Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-29 Salma Yacoubi, Ghaith Manita, Amit Chhabra, Ouajdi Korbaa
In the vast field of data mining, the increasing significance of Numerical Association Rule Mining (NARM) lies in its capacity to unearth recurrent patterns and correlations across diverse attribute types, resonating across multifarious sectors such as healthcare, commercial databases, and beyond. This article explores in depth the intricacies of optimization algorithms and metaheuristic approaches
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Machine Learning Optimization Techniques: A Survey, Classification, Challenges, and Future Research Issues Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-29 Kewei Bian, Rahul Priyadarshi
Optimization approaches in machine learning (ML) are essential for training models to obtain high performance across numerous domains. The article provides a comprehensive overview of ML optimization strategies, emphasizing their classification, obstacles, and potential areas for further study. We proceed with studying the historical progression of optimization methods, emphasizing significant developments
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Computational Modelling and Mechanical Characteristics of Polymeric Hybrid Composite Materials: An Extensive Review Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-28 Ankit Gangwar, Vikash Kumar, Murat Yaylaci, Subrata Kumar Panda
This study explores the reinforcement of foreign materials (fibers/particles) in polymeric composites, aiming to improve structural characteristics under variable loads. The article critically reviews experimental techniques for composite fabrication, computational modelling, and analysis. It also offers a detailed examination of mechanical properties, manufacturing defects, and applications associated
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The Role of Machine Learning in Earthquake Seismology: A Review Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-28 Anup Chitkeshwar
This comprehensive survey addresses the notable yet relatively uncharted territory of machine learning (ML) applications within the realm of earthquake engineering. While previous reviews have touched on ML’s involvement, this work strives to fill a gap by providing an extensive analysis of the extent to which ML has permeated earthquake engineering. It delves into how ML is facilitating and propelling
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Regression Method in Data Mining: A Systematic Literature Review Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-27 Mohammad Vahid Sebt, Yaser Sadati-Keneti, Misagh Rahbari, Zohreh Gholipour, Hamid Mehri
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A Comprehensive Survey of Multi-Level Thresholding Segmentation Methods for Image Processing Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-27 Mohammad Amiriebrahimabadi, Zhina Rouhi, Najme Mansouri
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AI-Based Approaches for the Diagnosis of Mpox: Challenges and Future Prospects Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-26 Sohaib Asif, Ming Zhao, Yangfan Li, Fengxiao Tang, Saif Ur Rehman Khan, Yusen Zhu
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Nature-Inspired Heuristic Frameworks Trends in Solving Multi-objective Engineering Optimization Problems Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-25 Clifford Choe Wei Chang, Tan Jian Ding, Chloe Choe Wei Ee, Wang Han, Johnny Koh Siaw Paw, Iftekhar Salam, Mohammad Arif Sobhan Bhuiyan, Goh Sim Kuan
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Big Data—Supply Chain Management Framework for Forecasting: Data Preprocessing and Machine Learning Techniques Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-24 Md Abrar Jahin, Md Sakib Hossain Shovon, Jungpil Shin, Istiyaque Ahmed Ridoy, M. F. Mridha
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Explainable Neural Networks: Achieving Interpretability in Neural Models Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-21 Manomita Chakraborty
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A Comprehensive Comparative Review of Various Advanced Finite Elements to Alleviate Shear, Membrane and Volumetric Locking Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-20 Dhiraj S. Bombarde, Lakshmi Narayan Silla, Sachin S. Gautam, Arup Nandy
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A Bird’s Eye View Approach on the Usage of Deep Learning Methods in Lung Cancer Detection and Future Directions Using X-Ray and CT Images Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-20 P. K. Kalkeseetharaman, S. Thomas George
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Theoretical Assessment for Weather Nowcasting Using Deep Learning Methods Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-19 Abhay B. Upadhyay, Saurin R. Shah, Rajesh A. Thakkar
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Decision-Making Model Construction of Emergency Material Allocation for Critical Incidents Based on BP Neural Network Algorithm: An Overview Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-14
Abstract Effective emergency material allocation is critical for mitigating the impact of critical incidents. This paper proposes a decision-making model for emergency material allocation based on the Backpropagation (BP) Neural Network algorithm. The model is designed to learn from historical emergency incidents and optimize resource allocation in real-time. The study includes a comprehensive case
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Design and Performance Measures of AVS/R Systems: A Bibliometric Literature Review Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-09 Elif Burcu Kızılırmak, Sinan Öztaş, Nadide Çağlayan, Mahmut Tutam
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Smart City Public Transportation Route Planning Based on Multi-objective Optimization: A Review Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-08 Ming Xiao, Lihua Chen, Haoxiong Feng, Zhigao Peng, Qiong Long
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Fractional Spectral and Fractional Finite Element Methods: A Comprehensive Review and Future Prospects Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-05 Muhammad Bilal Hafeez, Marek Krawczuk
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Deep Learning Challenges and Prospects in Wireless Sensor Network Deployment Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-04 Yaner Qiu, Liyun Ma, Rahul Priyadarshi
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Impact of Climate Change on the Dynamic Processes of Marine Environment and Feedback Mechanisms: An Overview Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-02
Abstract This study explores the intricate relationship between climate change, marine dynamic processes, and feedback mechanisms, emphasizing the marine environment’s crucial role in global climate regulation and biodiversity support. Ocean currents, such as the Gulf Stream, play a pivotal role in heat dispersion and climate stability. Diverse ecosystems, including coral reefs and mangroves, contribute
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An Extensive Review of Machine Learning and Deep Learning Techniques on Heart Disease Classification and Prediction Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-02 Pooja Rani, Rajneesh Kumar, Anurag Jain, Rohit Lamba, Ravi Kumar Sachdeva, Karan Kumar, Manoj Kumar
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Comprehensive Analysis of Computational Methods for Predicting Anti-inflammatory Peptides Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-01 Ali Raza, Jamal Uddin, Shahid Akbar, Fawaz Khaled Alarfaj, Quan Zou, Ashfaq Ahmad
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A Systematic Literature Review on Swarm Intelligence Based Intrusion Detection System: Past, Present and Future Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-01
Abstract Swarm Intelligence (SI) has proven to be useful in solving issues that are difficult to solve using traditional mathematical methodologies by using a collective behavior of a decentralized or self-organized system. SI-based optimization algorithms use a collaborative trial-and-error process to identify a solution. The development of various efficient swarm optimization methods is largely due
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A Comprehensive Review on Sparse Representation and Compressed Perception in Optical Image Reconstruction Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-01 Jia Yi, Huilin Jiang, Xiaoyong Wang, Yong Tan
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An Overview of Stress Analysis of Composites Through Computational Modelling and Simulation with the Aid of Patent Landscape Analysis Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-01 V. Bhuvaneswari, B. Arulmurugan, Devarajan Balaji, M. Aravindh, L. Rajeshkumar
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Application of Machine Learning and Deep Learning in Finite Element Analysis: A Comprehensive Review Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-03-01 Dipjyoti Nath, Ankit, Debanga Raj Neog, Sachin Singh Gautam
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A Systematic and Comprehensive Review on 2-D and 3-D Numerical Modelling of Stirling Engine Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-02-20 Vaibhav Singh, Anil Kumar
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An Analytical Review and Performance Measures of State-of-Art Scheduling Algorithms in Heterogenous Computing Enviornment Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-02-19 Wakar Ahmad, Gaurav Gautam, Bashir Alam, Bhoopesh Singh Bhati
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Advancements in Automatic Kidney Segmentation Using Deep Learning Frameworks and Volumetric Segmentation Techniques for CT Imaging: A Review Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-02-19 Vishal Kumar Kanaujia, Awadhesh Kumar, Satya Prakash Yadav
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Chest X-ray Images for Lung Disease Detection Using Deep Learning Techniques: A Comprehensive Survey Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-02-19
Abstract In medical imaging, the last decade has witnessed a remarkable increase in the availability and diversity of chest X-ray (CXR) datasets. Concurrently, there has been a significant advancement in deep learning techniques, noted for their escalating accuracy. These developments have catalyzed a surge in the application of deep learning in various medical studies, particularly in detecting and
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A Comprehensive Survey on Artificial Electric Field Algorithm: Theories and Applications Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-02-15 Dikshit Chauhan, Anupam Yadav
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Machine Learning and Computer Vision Based Methods for Cancer Classification: A Systematic Review Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-02-12 Sufiyan Bashir Mukadam, Hemprasad Yashwant Patil
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Breast Mammograms Diagnosis Using Deep Learning: State of Art Tutorial Review Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-02-09 Osama Bin Naeem, Yasir Saleem, M. Usman Ghani Khan, Amjad Rehman Khan, Tanzila Saba, Saeed Ali Bahaj, Noor Ayesha
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A Comprehensive Survey on Diabetes Type-2 (T2D) Forecast Using Machine Learning Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-02-07
Abstract Diabetes type 2 remains a pressing worldwide health subject, highlighting the need for advanced early detection methods. In this study, we performed a comprehensive analysis of current literature presented at conferences and journals, focusing on the effectiveness of machine learning techniques for the early detection of diabetes type 2. Our review included thorough examination of various
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Computational Modelling and Analysis of Effect of Viscoelastic Materials on Damping and Vibrational Behaviors of Composite Structures—An Extensive Review Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-02-06 Yasser Hamed Elmoghazy, Babak Safaei, Mohammed Asmael, Saeid Sahmani, Qasim Zeeshan, Zhaoye Qin
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A Systematic Review on Role of Deep Learning in CT scan for Detection of Gall Bladder Cancer Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-02-05
Abstract Gall bladder cancer (GBC) is a challenging and often fatal disease, with early detection playing a critical role in improving patient outcomes. This systematic review explores the role of Deep Learning AI (Artificial Intelligence) in the diagnosis of gall bladder cancer using Computed Tomography (CT) scans. A wide-ranging search was done across various electronic databanks to find appropriate
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Machine Learning Applications for Smart Building Energy Utilization: A Survey Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-02-05 Matti Huotari, Avleen Malhi, Kary Främling
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A Critical Review of Moth-Flame Optimization Algorithm and Its Variants: Structural Reviewing, Performance Evaluation, and Statistical Analysis Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-02-02 Hoda Zamani, Mohammad H. Nadimi-Shahraki, Seyedali Mirjalili, Farhad Soleimanian Gharehchopogh, Diego Oliva
A growing trend of introducing new metaheuristic algorithms and their improvements is observed with almost the same inherited weaknesses. The main reason is that a few studies have been performed to analyze the algorithms and their variants before improving them. This paper aims to review and analyze the moth-flame optimization (MFO) algorithm and its variants to show the structural reviewing, performance
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Design and Analysis of Three-Dimensional Foams: A Review Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-01-31 Manas K. Sahoo, Animesh Mandal
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Artificial Intelligence and Machine Learning in Electronic Fetal Monitoring Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-01-31 Katerina Barnova, Radek Martinek, Radana Vilimkova Kahankova, Rene Jaros, Vaclav Snasel, Seyedali Mirjalili
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Comprehensive Review of Metaheuristic Algorithms (MAs) for Optimal Control (OCl) Improvement Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-01-31 Usman Mohammed, Tologon Karataev, Omotayo Oshiga, Oghorada Oghenewvogaga
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Comprehensive Review of Subloading Surface Model: Governing Law of Irreversible Mechanical Phenomena of Solids Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-01-29
Abstract The constitutive equations for the irreversible mechanical phenomena, e.g. the plastic deformation and the sliding between solids with the friction have been studied over the several centuries. Especially, they have been studied for the description of the cyclic loading behaviors in the last half century in order to respond to the high developments of the mechanical, the civil and the structural
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A Comprehensive Review of Explicit Topology Optimization Based on Moving Morphable Components (MMC) Method Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-01-29 Zhao Li, Hongyu Xu, Shuai Zhang
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Comparative Analysis of Different Deep Convolutional Neural Network Architectures for Classification of Brain Tumor on Magnetic Resonance Images Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-01-26
Abstract In the current study, the capability of pre-trained Deep Convolutional Neural Network (DCNN) by ImageNet features is proposed for categorization of brain tumors by utilizing MR images. The pre-trained models like ResNet50, InceptionV3, Xception, DenseNet121, MobileNetV3Large, EffcientNetB0, EfficientNetV2L, EfficientNetV2B0 have been exploited for classification purpose. The selection criteria
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Safety Assessment and Risk Management of Urban Arterial Traffic Flow Based on Artificial Driving and Intelligent Network Connection: An Overview Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-01-23 Yulong Pei, Lin Hou
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A Critical Review of How EXtended Reality (XR) has Addressed Key Factors Influencing Safety on Construction Projects (fSCPs) Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-01-23 F. Muñoz-La Rivera, J. Mora-Serrano, E. Oñate
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Molecular Dynamics Investigation of Shock-Induced Deformation Behavior and Failure Mechanism in Metallic Materials Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-01-15 Yiqi Zhu, Qihua Gong, Min Yi
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Topology Optimization to Fracture Resistance: A Review and Recent Developments Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-01-10
Abstract Topology optimization (TO) methods for fracture resistance offer new possibilities for designing stronger structures or materials with lower masses than conventional designs. This article presents an overview of TO techniques for fracture resistance, from pioneering works to the most recent developments at the time of writing. We first review stress-based methods, which were the forerunners
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Developments and Design of Differential Evolution Algorithm for Non-linear/Non-convex Engineering Optimization Arch. Computat. Methods Eng. (IF 9.7) Pub Date : 2024-01-10
Abstract Nowadays, the differential evolution (DE) achieved noticeable progress and solved a wide range of non-linear/non-convex engineering optimization issues. As a strong optimizer, DE has many advantages like simple structure, strong exploitation ability and considerable convergence speed. However, DE also suffers from low diversification, poor exploration ability and stagnation. After significant