Results in Engineering最新文献

{"title":"Advancing sustainable cities and communities with internet of things: Global insights, trends, and research priorities for SDG 11","authors":"Shaher Zyoud ,&nbsp;Ahed H. Zyoud","doi":"10.1016/j.rineng.2025.104917","DOIUrl":"10.1016/j.rineng.2025.104917","url":null,"abstract":"<div><div>The quest for sustainable development is confronted with many challenges. Technological innovation, especially the Internet of Things (IoT), has come up as a key enabler in reaching sustainability. This research analyzes research landscapes on IoT supporting Sustainable Development Goal (SDG) 11. A targeted search combining SDG 11 with IoT-related terminology was conducted via the Scopus database, covering publications from 2010 to 2024. VOSviewer software was employed to map collaborative networks, co-citation patterns, and key themes. Furthermore, the SciMAT software was employed was employed to analyze themes' evolution and intellectual structures, hence showing emerging trends and assessing thematic consistency over time. A thorough analysis of 6,334 publications revealed the top contributors as China (1,356; 21.4 %), India (1,301; 20.5 %), the United States (736; 11.6 %), and Saudi Arabia (569; 9.0 %). Developing nations in Asia and the Middle East made significant contributions to IoT-SDG 11 research, driven by urbanization challenges. Key research themes include intelligent transportation systems (ITSs), cyber-physical systems, smart buildings, and urbanization. Specialized subjects explore the use of IoT-enabled drones for augmenting SDG 11 goals, particularly in disaster management. Findings emphasize the need to design green IoT models and close technology gaps. Harnessing the potential of IoT requires the incorporation of ethical, social, and environmental factors into its design for guaranteeing convergence with sustainability goals. Data security issues, market fragmentation, and lack of infrastructure, though, necessitate regulatory intervention and investment. Additionally, citizen engagement and the evolution of 5G, artificial intelligence (AI), and edge computing will further enhance IoT's role in sustainability.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104917"},"PeriodicalIF":6.0,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic review of multimodal fake news detection on social media using deep learning models","authors":"Maged Nasser ,&nbsp;Noreen Izza Arshad ,&nbsp;Abdulalem Ali ,&nbsp;Hitham Alhussian ,&nbsp;Faisal Saeed ,&nbsp;Aminu Da'u ,&nbsp;Ibtehal Nafea","doi":"10.1016/j.rineng.2025.104752","DOIUrl":"10.1016/j.rineng.2025.104752","url":null,"abstract":"<div><div>The volume of data circulating from online sources is growing rapidly and comprises both reliable and unreliable information published through many different sources. Researchers are making plausible efforts to develop reliable methods for detecting and eliminating fake web news. Deep learning (DL) methods play a vital role in addressing various fake news detection problems and are found to perform better compared to conventional approaches, making them state-of-the-art in this field. This paper provides a comprehensive review and analysis of existent DL-based models for multimodal fake news detection, focusing on diverse aspects, including user profiles, news content, images, videos, and audio data. This study considered the latest articles within the last seven years, starting from 2018 to 2025, and about 963 quality articles were obtained from the journals and conferences selected for this study. Subsequently, 121 studies were chosen for our SLR after careful screening of the abstract and the full-text eligibility analysis. The findings showed that the Transformer models and Recurrent Neural Networks (RNNs) are the most popular deep learning techniques for detecting multimodal fake news, followed by the Convolutional Neural Networks (CNNs) techniques. The Twitter and Weibo datasets are the two most frequently used standard datasets, and the most frequently used metrics to evaluate the performance of these models are the accuracy, precision, recall, and F-scores. In conclusion, the limitations of the current methods were summarized and some exciting possibilities for future research were highlighted, including designing robust multilingual fake news detection systems, hybridization of deep learning models to enhance detection accuracy, integration of explainable AI (XAI), and facilitating real-time fake news detection models.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104752"},"PeriodicalIF":6.0,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143799407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soiling estimation methods in solar photovoltaic systems: Review, challenges and future directions","authors":"J. Agbogla ,&nbsp;C.K.K. Sekyere ,&nbsp;F.K. Forson ,&nbsp;R. Opoku ,&nbsp;B. Baah","doi":"10.1016/j.rineng.2025.104810","DOIUrl":"10.1016/j.rineng.2025.104810","url":null,"abstract":"<div><div>Soiling, the accumulation of dust and particulate matter on solar photovoltaic (PV) panels, reduces their efficiency, energy yield, and increases operational costs, particularly in dust-prone regions. This review critically examines methods for estimating soiling losses, focusing on approaches to accurately quantify dust accumulation. It explores direct methods such as gravimetric, optical, and imaging techniques, which offer high accuracy but face challenges in scalability, cost, and environmental sensitivity<strong>.</strong> Indirect methods, including Performance Ratio (PR) analysis and meteorological models, provide scalable, cost-effective solutions but often lack precision due to confounding factors like shading and system degradation<strong>.</strong> Hybrid models that integrate both direct and indirect techniques improve accuracy but require substantial data and computational resources. A major challenge identified in the review is th<strong>e</strong> lack of standardized protocols for soiling measurement, making comparisons across studies and regions difficult. The review emphasizes the importance of real-time monitoring<strong>,</strong> machine learning integration for predictive maintenance<strong>,</strong> and the development of anti-soiling coatings and self-cleaning technologies. Long-term studies across diverse climates are needed to create universally applicable soiling estimation models. By addressing these challenges and advancing existing technologies, the solar industry can more effectively estimate soiling losses, enhance PV system efficiency, and contribute to achieving global sustainability goals, particularly SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action)<strong>.</strong></div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104810"},"PeriodicalIF":6.0,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143825410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-wire additive manufacturing: A comprehensive review on materials, microstructure, methodological advances, and applications","authors":"Rupendra S. Tanwar,&nbsp;Suyog Jhavar","doi":"10.1016/j.rineng.2025.104814","DOIUrl":"10.1016/j.rineng.2025.104814","url":null,"abstract":"<div><div>The industrial demand for high-performance multi-material components is rapidly growing due to their superior functionality in advanced applications. Traditional Wire Arc Additive Manufacturing (WAAM) is typically limited to the use of a single wire, which possesses a specific chemical composition and results in fixed properties for the fabricated component. Multi-Wire Arc Additive Manufacturing (MWAAM) has emerged as a promising alternative due to its ability to achieve property variations at specific locations, along with its cost-effectiveness and flexibility. This review examines the advancements in MWAAM for multi-material fabrication. It aims to evaluate the microstructural and mechanical properties of components produced, identify research gaps, and propose strategies for future advancements. The review synthesises findings from studies published between 2015 and 2024, specifically focusing on MWAAM applications in fabricating functionally graded materials (FGMs), bimetallic structures (BMS), high-entropy alloys (HEAs), shape memory alloys (SMAs), and intermetallic compounds (IMCs). Factors such as wire feeding mechanisms, deposition strategies, microstructural evolution, and mechanical performance have been analysed. MWAAM demonstrates significant potential in fabricating advanced multi-material components with enhanced strength, thermal stability, and corrosion resistance. Its capabilities include precise composition control and the creation of gradient structures using advanced wire feeding systems, such as dual-wire and twin-wire configurations. However, MWAAM is challenged by microstructural heterogeneity, phase segregation, and prevalence of porosity and cracking. Addressing these challenges through computational modelling and real-time monitoring systems can lead to broadening its industrial adoption and impact.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104814"},"PeriodicalIF":6.0,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancements in energy harvesting techniques for sustainable IoT devices","authors":"Ahsan Ali ,&nbsp;Hamna Shaukat ,&nbsp;Hassan Elahi ,&nbsp;Shaista Taimur ,&nbsp;Muhammad Qasim Manan ,&nbsp;Wael A. Altabey ,&nbsp;Sallam A. Kouritem ,&nbsp;Mohammad Noori","doi":"10.1016/j.rineng.2025.104820","DOIUrl":"10.1016/j.rineng.2025.104820","url":null,"abstract":"<div><div>This paper reviews the energy harvesting techniques for sustainable Internet of Things (IoT) devices. With the passage of time, more things and objects are connected to the internet, paving the way for the development of IoT. The term IoT describes the network of everyday devices that are interconnected together and exchange data via the Internet. Wireless sensors are included in IoT devices to collect data in an accurate and useful way for process monitoring and activity control. The batteries that run these wireless sensors have a limited lifespan, rapidly drain, and need replacement. The replacement and maintenance process is costly; thus, smart energy management is essential for IoT devices to be energy-efficient. Therefore, energy harvesting is a promising method to supply such low-powered IoT devices by utilizing various energy resources. This energy can be harvested from different environmental, mechanical, chemical, and bioenergy sources, eliminating battery dependence. First, this review explains the importance of energy harvesting techniques for powering IoT devices, followed by IoT energy harvesting. Then it explains different energy harvesting techniques, followed by a table showing the analysis of these techniques. After that, this review explains the cost of these harvesters. Finally, there are future recommendations and conclusion, which shows some challenges that IoT energy harvesting faces that need to be addressed to grow sustainable IoT devices.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104820"},"PeriodicalIF":6.0,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143825409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recent developments in profiled steel sheeting dry board (PSSDB) systems: A systematic literature review","authors":"Abdulrahman Mubarak Salem Sawahli ,&nbsp;Sakhiah Abdul Kudus ,&nbsp;Adiza Jamadin ,&nbsp;Mohamad Farid Misnan ,&nbsp;Kunitomo Sugiura","doi":"10.1016/j.rineng.2025.104788","DOIUrl":"10.1016/j.rineng.2025.104788","url":null,"abstract":"<div><div>The Profiled Steel Sheeting Dry Board Composite construction system consists of profiled steel sheeting with dry board, offering power-efficient, lightweight, and flexible, making it suitable for a wide range of structural applications. While there are well-founded promises from its development, there is a lack of systematic and holistic studies on its application and structure performance. This systematic literature review aims to fill this gap and report on the relevant papers to PSSDB. Using the PRISMA methodology, a systematic screening process led to the identification of 552 publications, which were then filtered down to 33 articles that all constituted relevant research papers for analysis, ensuring scientific rigour and transparency. This paper evaluates the structural performance and applications of the PSSDB system and analyses critical issues and research perspectives. Key results indicate that local buckling remains a formidable design challenge for PSS over a continuum of design cases, with few investigations proposing feasible mitigation strategies. Moreover, the dynamic behaviour of PSSDB is largely unexplored due to the limited experimental modal analysis and related investigations, where vibration performance is critical for structural integrity. It summarises existing evidence to assess current boundaries and highlights areas for future research and implications for practice. It provides a foundation to create new, effective solutions for enhancing the structural performance and the versatility of PSSDB systems. Thereby, an improved understanding of the PSSDB supports to optimise it further and widely deploying it in current construction, thus making work a novel step that fills the research gap.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104788"},"PeriodicalIF":6.0,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143823345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A state-of-the-art review of geotechnical challenges and opportunities in recycling and reusing sewage sludge as landfill cover material: A review","authors":"Mohammad Jamalimoghadam ,&nbsp;Amir Hossein Vakili ,&nbsp;Hossein Bahmyari ,&nbsp;Abdollah Tabaroei","doi":"10.1016/j.rineng.2025.104764","DOIUrl":"10.1016/j.rineng.2025.104764","url":null,"abstract":"<div><div>This paper emphasizes the critical significance of sustainable Sewage Sludge (SS) management and its pivotal role in environmental protection. It also strives to identify shortcomings in established practices that warrant additional investigation and examination. The excessive generation of SS, replete with microorganisms and potentially hazardous inorganic and organic substances, is a formidable challenge closely linked to wastewater and biological treatment plants. Moreover, this paper furnishes an extensive survey of advancements in landfill cover systems incorporating SS, elucidating the underlying principles governing their effectiveness. SS could be a cost-effective alternative to traditional landfill covers with proper engineering and management, addressing waste disposal challenges and promoting environmental benefits. However, a comprehensive assessment of geotechnical properties and site conditions is essential to ensure the long-term effectiveness and safety of the landfill cover system. The literature reveals that specific parameters, such as hydraulic conductivity, UCS, and toxic substance leaching, are paramount in designing the cover layer. Nevertheless, some factors, including freezing-thawing, wetting-drying, and long-term behavior, have not received adequate research, suggesting potential future research avenues. In addition, potential environmental risks, such as the leaching of hazardous constituents into groundwater and resultant soil contamination, can be mitigated by integrating engineered barriers, continuous monitoring systems, and adaptive management practices to safeguard ecological integrity.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104764"},"PeriodicalIF":6.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143799408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soil structure interaction and the radiation damping: A state-of-the-art review","authors":"Yaseen Shayah","doi":"10.1016/j.rineng.2025.104755","DOIUrl":"10.1016/j.rineng.2025.104755","url":null,"abstract":"<div><div>This paper introduces the soil-structure interaction (SSI) concept and explores relevant research methodologies and modeling techniques to address SSI challenges. A comprehensive analysis of each model's advantages, disadvantages, and practical applications is conducted. Furthermore, the document summarizes the circumstances under which global standards necessitate the consideration of SSI. Nonlinear finite element modeling is demonstrated, and a thorough discussion of the available models, including comparisons and resolution of differences, is presented. The study also explores damping types in soil, including internal damping (comprising viscous and hysteretic damping) and radiation damping, which involves energy dissipation due to wave propagation towards infinity. Radiation damping techniques are explained in detail, along with their limitations. Finally, recommendations and suggestions for future research are outlined.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104755"},"PeriodicalIF":6.0,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143799409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning-based methods for detecting respiratory abnormalities using audio and visual analysis: A review","authors":"Sufyan O. Zaben ,&nbsp;Wan Mohd Nazmee Wan Zainon ,&nbsp;Ahmad H. Sabry","doi":"10.1016/j.rineng.2025.104744","DOIUrl":"10.1016/j.rineng.2025.104744","url":null,"abstract":"<div><div>Respiratory abnormalities pose a significant health burden, often demanding timely and accurate diagnosis. Traditional methods have limitations, prompting exploration of novel approaches. This review explores the potential of machine learning, leveraging both audio and visual analysis, for detecting respiratory abnormalities. We explore various methods employed, analyzing audio features like MFCCs and spectral energy, and exploring diverse visual features like chest wall motion and depth maps. Different machine learning techniques, including CNNs and RNNs, are discussed, highlighting their applications in detecting specific conditions like asthma and COPD. We systematically evaluate their performance, analyzing strengths and limitations of both audio-based and visual-based approaches. Further, we explore the potential of multimodal analysis, combining audio and visual information for enhanced performance. Reviewing existing studies, we assess the advantages gained over unimodal methods. Finally, we explore the clinical implications and future directions, discussing potential applications like remote monitoring and early diagnosis, while acknowledging remaining challenges and ethical considerations. By comprehensively examining the landscape of machine learning for audio and visual analysis in respiratory abnormality detection, this review offers valuable insights for researchers and clinicians, ultimately accelerating the translation of these promising methods into real-world practice.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104744"},"PeriodicalIF":6.0,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143769111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental and modeling study of 6FDA-Durene polyimide/ionic liquid-modified ZIF-8 mixed matrix membranes for CO2 separation","authors":"Mohammad Mehdi Moftakhari Sharifzadeh ,&nbsp;Farshid Pajoum Shariati ,&nbsp;Abtin Ebadi Amooghin ,&nbsp;Hamidreza Sanaeepur ,&nbsp;Mehdi Ardjmand","doi":"10.1016/j.rineng.2025.104686","DOIUrl":"10.1016/j.rineng.2025.104686","url":null,"abstract":"<div><div>Recent membrane research has garnered significant interest in the pursuit of physicochemically stable membranes with outstanding separation capabilities. Introducing inorganic/organic fillers into polymer matrices to create mixed matrix membranes (MMMs) is an effective approach to enhance membrane performance and address the permeability/selectivity trade-off. This study involved the fabrication of a series of MMMs by incorporating [OMIM][PF₆] ionic liquid-modified ZIF-8 as filler into the 6FDA-Durene polyimide (PI) matrix to enhance its physicochemical and separation properties. The pure gas permeation studies were performed on these MMMs with different filler loadings (0–10 wt.%) at 25 °C and 2–10 bar. Extensive characterization methods, such as FESEM, EDX, FTIR, DLS, DSC, TGA, XRD, and Zeta-potential, were utilized to evaluate the synthesized fillers and membranes. Moreover, molecular dynamics (MD) simulation, in conjunction with gas permeation models, and substantiated the exceptional compatibility of ZIF-8/IL with the PI chains. The Sobol method is used to analyze the impact of variable parameters on the efficacy of MMMs. The results indicated that the 6FDA-Durene/5 wt.% ZIF-8/IL membrane shown superior performance in CO₂/CH₄ and CO₂/N₂ separations. The CO₂ permeability rose from 640 Barrer for the pure 6FDA-Durene membrane to 1166 Barrer in the 6FDA-Durene/5 wt.% ZIF-8/IL MMM, representing an increase of approximately 82 %. The CO₂/CH₄ and CO₂/N₂ selectivities of 6FDA-Durene/5 wt. % ZIF-8/IL attained values of 21.45 and 20.48, respectively. The sensitivity analysis reveals that feed pressure significantly influences gas permeability, while filler loading represents the second highest first-order index among the other parameters. In comparison to the pure 6FDA-Durene membrane, the 6FDA-Durene/5 wt. % ZIF-8/IL MMM presents promising potential for further exploration in the advancement of high-performance membranes for gas separation applications.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104686"},"PeriodicalIF":6.0,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}