Comprehensive Methodological Review Research Articles

Correction to: How to Harness the Power of GPT for Scientific Research: A Comprehensive Review of Methodologies, Applications, and Ethical Considerations

Correction to: How to Harness the Power of GPT for Scientific Research: A Comprehensive Review of Methodologies, Applications, and Ethical Considerations

A comprehensive review of methodology and advancement in the development of superhydrophobic membranes for efficient oil–water separation

A comprehensive review of methodology and advancement in the development of superhydrophobic membranes for efficient oil–water separation

Predictive Power- Leveraging Data Analytics and Mining for Future Trends Forecasting

In an era of vast data availability, the ability to predict future trends accurately has become a critical advantage for businesses, policymakers, and researchers alike. This paper examines the predictive power inherent in data analytics and mining techniques and their applications in forecasting future trends across various domains. Through a comprehensive review of methodologies, case studies, and real-world applications, we explore how data analytics and mining enable the extraction of valuable insights from large datasets to anticipate trends in finance, healthcare, marketing, and beyond. We delve into the tools, and best practices employed in predictive modeling, emphasizing their role in enhancing decision-making processes and strategic planning.

Exploring Fracture Patterns: Assessing Representation Methods for Bone Fracture Simulation.

Fracture pattern acquisition and representation in human bones play a crucial role in medical simulation, diagnostics, and treatment planning. This article presents a comprehensive review of methodologies employed in acquiring and representing bone fracture patterns. Several techniques, including segmentation algorithms, curvature analysis, and deep learning-based approaches, are reviewed to determine their effectiveness in accurately identifying fracture zones. Additionally, diverse methods for representing fracture patterns are evaluated. The challenges inherent in detecting accurate fracture zones from medical images, the complexities arising from multifragmentary fractures, and the need to automate fracture reduction processes are elucidated. A detailed analysis of the suitability of each representation method for specific medical applications, such as simulation systems, surgical interventions, and educational purposes, is provided. The study explores insights from a broad spectrum of research articles, encompassing diverse methodologies and perspectives. This review elucidates potential directions for future research and contributes to advancements in comprehending the acquisition and representation of fracture patterns in human bone.

A comprehensive review of methodologies and implications for evaluating flood susceptibility

Floods, ever since the dawn of human civilization, have been seen as causes of massive disasters. Since its onset, the influence of human activity has increased, making this calamity more severe. Vulnerability to flooding is complex and multifaceted and it is a matter of critical importance. Since the scale of damage changes with location and with time, determining how susceptible a community is to flooding is of paramount importance. The research is an effort to summarize the methods developed to evaluate flood risk. By examining the authors and terms most commonly cited in the works of others, actionable tactics were uncovered. High-resolution data and a multidimensional approach to vulnerability assessment can enhance current procedures and strategies for estimating flood risk. This research recommends merging hydrodynamic models, geospatial methodologies for flood assessment to present a more complete view of flood vulnerability. It is potentially helpful in identifying methodological inadequacies for measuring flood risk at various geographical scales. The study analyzes several vulnerability components. This research has the potential to fill critical knowledge gaps in our understanding of how to measure exposure to flood risk across a variety of geographical scales.

UX Audit: A Comprehensive Review of Methodologies and Best Practices for Evaluating User Experiences

User experience (UX) is crucial to modern-day digital products and services. A UX audit evaluates the UX of an application, website, or digital product by analyzing user data, conducting heuristic evaluations, and identifying areas for improvement. This review paper aims to outline UX audits, including their benefits, key components, and steps involved in the process. The research also discusses the importance of using empirical data in UX audits and how to measure the success of a UX audit. Additionally, the paper highlights UX auditors' challenges and provides recommendations for overcoming them.

Mapping Compound Flooding Risks for Urban Resilience in Coastal Zones: A Comprehensive Methodological Review

Coastal regions, increasingly threatened by floods due to climate-change-driven extreme weather, lack a comprehensive study that integrates coastal and riverine flood dynamics. In response to this research gap, we conducted a comprehensive bibliometric analysis and thorough visualization and mapping of studies of compound flooding risk in coastal cities over the period 2014–2022, using VOSviewer and CiteSpace to analyze 407 publications in the Web of Science Core Collection database. The analytical results reveal two persistent research topics: the way to explore the return periods or joint probabilities of flood drivers using statistical modeling, and the quantification of flood risk with different return periods through numerical simulation. This article examines critical causes of compound coastal flooding, outlines the principal methodologies, details each method’s features, and compares their strengths, limitations, and uncertainties. This paper advocates for an integrated approach encompassing climate change, ocean–land systems, topography, human activity, land use, and hazard chains to enhance our understanding of flood risk mechanisms. This includes adopting an Earth system modeling framework with holistic coupling of Earth system components, merging process-based and data-driven models, enhancing model grid resolution, refining dynamical frameworks, comparing complex physical models with more straightforward methods, and exploring advanced data assimilation, machine learning, and quasi-real-time forecasting for researchers and emergency responders.

Analysis Of In-service Traffic Sign Visual Condition: An Overview

This paper offers a comprehensive review of methodologies to assess the visual condition of traffic signs. It explores image processing, machine learning, and computer vision techniques to evaluate degradation, readability, and overall visibility. The objective is to enhance maintenance and effectiveness of traffic sign systems for safer roads. Regular assessment of traffic signs is vital for their efficacy and safety, considering factors like damage, fading, obstruction, and placement. Addressing these issues can significantly enhance road safety by enabling precise and safe navigation for drivers. The study delves into various aspects including shape, background color, symbol color, temperature, land use, visibility distance, and prevailing visibility conditions of traffic signs.

Advancements in Security Testing: A Comprehensive Review of Methodologies and Emerging Trends in Software Quality Engineering

Advancements in Security Testing: A Comprehensive Review of Methodologies and Emerging Trends in Software Quality Engineering

A REVIEW OF METHODOLOGIES FOR PATH PLANNING AND OPTIMIZATION OF MOBILE ROBOTS

Abstract: This research paper provides a comprehensive review of methodologies for path planning and optimization of mobile robots. With the rapid development of robotics technology, path planning and optimization have become fundamental areas of research for achieving efficient and safe autonomous robot navigation. In this paper, we review the classic and state-of-the-art techniques of path planning and optimization, including artificial potential fields, A* algorithm, Dijkstra's algorithm, genetic algorithm, swarm intelligence, and machine learning-based methods. We analyze the strengths and weaknesses of each approach and discuss their application scenarios. Moreover, we identify the challenges and open problems in this field, such as dealing with dynamic environments and real-time constraints. This paper serves as a comprehensive reference for researchers and practitioners in the robotics community, providing insights into the latest trends and developments in path planning and optimization for mobile robots.

A Comprehensive Overview of Unit-Level Modeling of Survey Data for Small Area Estimation Under Informative Sampling

Abstract Model-based small area estimation is frequently used in conjunction with survey data to establish estimates for under-sampled or unsampled geographies. These models can be specified at either the area-level, or the unit-level, but unit-level models often offer potential advantages such as more precise estimates and easy spatial aggregation. Nevertheless, relative to area-level models, literature on unit-level models is less prevalent. In modeling small areas at the unit level, challenges often arise as a consequence of the informative sampling mechanism used to collect the survey data. This article provides a comprehensive methodological review for unit-level models under informative sampling, with an emphasis on Bayesian approaches.

A REVIEW OF METHODOLOGIES FOR PATH PLANNING AND OPTIMIZATION OF MOBILE ROBOTS

This research paper provides a comprehensive review of methodologies for path planning and optimization of mobile robots. With the rapid development of robotics technology, path planning and optimization have become fundamental areas of research for achieving efficient and safe autonomous robot navigation. In this paper, we review the classic and state-of-the-art techniques of path planning and optimization, including artificial potential fields, A* algorithm, Dijkstra's algorithm, genetic algorithm, swarm intelligence, and machine learning-based methods. We analyze the strengths and weaknesses of each approach and discuss their application scenarios. Moreover, we identify the challenges and open problems in this field, such as dealing with dynamic environments and real-time constraints. This paper serves as a comprehensive reference for researchers and practitioners in the robotics community, providing insights into the latest trends and developments in path planning and optimization for mobile robots.

Best practice for wildlife gut microbiome research: A comprehensive review of methodology for 16S rRNA gene investigations.

Extensive research in well-studied animal models underscores the importance of commensal gastrointestinal (gut) microbes to animal physiology. Gut microbes have been shown to impact dietary digestion, mediate infection, and even modify behavior and cognition. Given the large physiological and pathophysiological contribution microbes provide their host, it is reasonable to assume that the vertebrate gut microbiome may also impact the fitness, health and ecology of wildlife. In accordance with this expectation, an increasing number of investigations have considered the role of the gut microbiome in wildlife ecology, health, and conservation. To help promote the development of this nascent field, we need to dissolve the technical barriers prohibitive to performing wildlife microbiome research. The present review discusses the 16S rRNA gene microbiome research landscape, clarifying best practices in microbiome data generation and analysis, with particular emphasis on unique situations that arise during wildlife investigations. Special consideration is given to topics relevant for microbiome wildlife research from sample collection to molecular techniques for data generation, to data analysis strategies. Our hope is that this article not only calls for greater integration of microbiome analyses into wildlife ecology and health studies but provides researchers with the technical framework needed to successfully conduct such investigations.

Field experiments in marketing research: a systematic methodological review

PurposeThe purpose of this study is to present a systematic methodological review of the application of field experiments in the domain of marketing research. By performing this study, the authors seek to offer necessary advice and suggestions to marketing scholars interested in the application of field experiments and to promote the adoption of field experiments as a preferred methodological choice among scholars in this domain.Design/methodology/approachA total of 315 field experiments published in the ten leading marketing journals in the past five decades were analyzed in this systematic methodological review. This study examines various aspects of field experiments, including the research profile of existing research, different trends and topics related to field experiments, choice of research questions, methods of observations, unobtrusive data collection, types of interventions and outcome variables.FindingsThis study identified various trends and topics, categories of manipulations, types of limitations and important considerations in designing field experiments and offered necessary advice on the future of field experiments in marketing research.Research limitations/implicationsThis study provides a complete roadmap for future marketing scholars to adopt field studies in their research plans. The systematic summary of limitations and the checklist will be helpful for the researchers to design and execute field studies more effectively and efficiently.Practical implicationsThis review study offers a complete roadmap for marketing scholars who are interested in adopting field experiments in their research projects. The discussion of trends and topics, manipulations, limitations, design considerations and checklist items for field experiments offers relevant insights to marketing scholars and may help them design and execute field experiments more effectively and efficiently.Originality/valueTo the best of the authors’ knowledge, this study is the first of its kind to provide a comprehensive methodological review of field experiments published in leading marketing journals throughout the past five decades. This study makes novel and unique contributions to both theory and literature on field experiments in the marketing discipline.

Exploring lean six sigma: A comprehensive review of methodology and its role in business improvement

In a highly competitive industrial landscape, organizations are increasingly adopting strategies to enhance product quality, with Lean Six Sigma emerging as a notable approach. This paper presents a comprehensive review of Lean Six Sigma, a synergistic approach combining the waste-reduction principles of Lean with the process optimization strategies of Six Sigma. The study underscores the importance of the Lean Six Sigma approach as a valuable tool for businesses, seeking process improvement and increased competitiveness and acknowledging that its applicability depends on an organization’s specific circumstances and needs. Furthermore, the paper critically assesses the benefits and potential criticisms of Lean Six Sigma, providing balanced insights into challenges to its implementation. By offering a comprehensive understanding of Lean Six Sigma, this review paper serves as a valuable resource for organizations aiming to enhance their operational efficiency, reduce cost, and improve customer satisfaction.

A review of methodologies for path planning and optimization of mobile robots

This research paper provides a comprehensive review of methodologies for path planning and optimization of mobile robots. With the rapid development of robotics technology, path planning and optimization have become fundamental areas of research for achieving efficient and safe autonomous robot navigation. In this paper, we review the classic and state-of-the-art techniques of path planning and optimization, including artificial potential fields, A* algorithm, Dijkstra's algorithm, genetic algorithm, swarm intelligence, and machine learning-based methods. We analyze the strengths and weaknesses of each approach and discuss their application scenarios. Moreover, we identify the challenges and open problems in this field, such as dealing with dynamic environments and real-time constraints. This paper serves as a comprehensive reference for researchers and practitioners in the robotics community, providing insights into the latest trends and developments in path planning and optimization for mobile robots.

Comprehensive Review of Methodology to Detect Reactive Oxygen Species (ROS) in Mammalian Species and Establish Its Relationship with Antioxidants and Cancer.

Evidence suggests that reactive oxygen species (ROS) mediate tissue homeostasis, cellular signaling, differentiation, and survival. ROS and antioxidants exert both beneficial and harmful effects on cancer. ROS at different concentrations exhibit different functions. This creates necessity to understand the relation between ROS, antioxidants, and cancer, and methods for detection of ROS. This review highlights various sources and types of ROS, their tumorigenic and tumor prevention effects; types of antioxidants, their tumorigenic and tumor prevention effects; and abnormal ROS detoxification in cancer; and methods to measure ROS. We conclude that improving genetic screening methods and bringing higher clarity in determination of enzymatic pathways and scale-up in cancer models profiling, using omics technology, would support in-depth understanding of antioxidant pathways and ROS complexities. Although numerous methods for ROS detection are developing very rapidly, yet further modifications are required to minimize the limitations associated with currently available methods.

Disaggregation of conventional soil maps: a review

The disaggregation of conventional soil maps is an active research line inside the Digital Soil Mapping framework that aims to generate new cartographies by disclosing the non-explicit soil distribution pattern within the polytaxic or multi-component cartographic units. This article shows a comprehensive review of methodologies found after a bibliographic search in the Web of Science and Scopus databases. They are analysed regarding common factors such as the conventional soil map, environmental data sources and covariates, classification methods, and evaluation; likewise, those specific to the leveraging of conventional maps as the main source of soil information such as sampling scheme and assignment of soil categories for the classification. The applications were frequently carried out in small and medium areas with intensive and extensive conventional soil maps and featuring supervised classification methods. The definition of the training sets is a critical task that has a strong influence on their performance. The comparative analysis noted the potential of the reviewed disaggregation methodologies that adopted two-stage strategies: first, areas potentially associated with soil categories are delimited; and second, supervised models are built on them. Ultimately, the development of new disaggregation methodologies is possible by combining those strategies within each factor that yielded the best results in terms of accuracy.

Factors Affecting Marital Satisfaction and Marital Communication Among Marital Women: Literature of Review

This paper provides a comprehensive methodological review of the literature assessing the factors affecting marital satisfaction and marital communication among marital women. This systematic review surveys published articles from 1981 to 2017. First, scientific databases such as Pubmed/Medline, Scopus, Elsevier, and Cochran library, Springer, Scientific Information Database (SID), IranMedex, Magiran and Medlib were searched using relevant key words and phrases. All published peer reviewed articles studied exploring associations between marital satisfaction and effective factors were considered for inclusion. The findings indicated that the income and eco-nomic status can exert a positive effect on the couple’s satisfaction which can be one of the important factors affecting marital satisfaction. According to the results of these articles, the influential effect of some factors such as occupation, length of marriage, age, Number of children, economic factor and income had been emphasized. In mate selection, it is necessary to note various criteria, including religious matters, moral, mental health, communication skills and sexual factor and action through education, counseling and treatment if there is problem.

Tunnels in squeezing clay-rich rocks

Squeezing ground conditions, which can lead to severe loads in tunnels, have historically been associated with the presence of clay minerals in the ground. Over the years, many methodologies have been proposed to predict squeezing in tunnels based on tunnel depth, in situ stress, ground mineralogy, and ground strength and deformation behavior. This paper presents a comprehensive review of methodologies to predict tunnel squeezing in clay-rich rocks. A new methodology is proposed where ground conditions and squeezing potential are assessed based on the Stress History and Normalized Soil Engineering Properties (SHANSEP) approach adapted to clay-rich rocks, Peck’s stability number and Hoek & Brown’s (1997) Geological Strength Index (GSI). A squeezing number S is suggested to classify ground conditions based on the level of squeezing that the ground may experience in response to tunneling. Finally, it is demonstrated that by combining the proposed classification system and an existing classification system for ground squeezing condition, an accurate estimate of tunnel strain can also be obtained. The proposed method is applied to four case studies of tunnels in squeezing ground in shale and mudstone.