Article
Biodiversity Conservation
Arjun B. Doke, Rajendra B. Zolekar, Hemlata Patel, Sumit Das
Summary: Groundwater, an essential natural resource for various activities, was geospatially mapped using GIS, MCDM, AHP, and remote sensing techniques in this study. The methodology and results were accurate in determining different groundwater potential zones and can be useful in similar drought-prone regions globally.
ECOLOGICAL INDICATORS
(2021)
Article
Chemistry, Multidisciplinary
Hanif Ur Rahman, Mushtaq Raza, Palwasha Afsar, Abdullah Alharbi, Sultan Ahmad, Hashym Alyami
Summary: Global Software Development (GSD) has drawn the interest of businesses worldwide, offering advantages such as access to a vast labor pool, cost savings, and round-the-clock growth. However, GSD also presents technological and organizational diversity, along with obstacles like geographical distance, cultural differences, communication, and language barriers.
APPLIED SCIENCES-BASEL
(2021)
Article
Economics
Ilgin Gokasar, Muhammet Deveci, Onur Kalan
Summary: This paper investigates the impact of bridge maintenance on the environment and ranks the priority of different bridge maintenance projects using a multi-criteria decision-making model, which includes considering the additional CO2 emissions caused by truck detours.
RESEARCH IN TRANSPORTATION ECONOMICS
(2022)
Article
Agronomy
Parvin Zolfaghary, Mahdi Zakerinia, Hossein Kazemi
Summary: The study investigated the suitability of using urban treated wastewater for irrigation, considering both technical-economic and environmental factors. Results showed that the Bandar Gaz plant performed better in criteria such as aquifer vulnerability and nitrate contamination, highlighting the importance of these factors in decision-making.
AGRICULTURAL WATER MANAGEMENT
(2021)
Article
Environmental Sciences
Ismail Elkhrachy, Ali Alhamami, Saleh H. Alyami
Summary: Dealing with solid waste management involves practical issues and consideration of environmental effects. In this study, multi-criteria decision analysis (MCDA) was used to evaluate and suggest the best locations for landfill sites in Najran, KSA. Remote sensing data and ArcGIS software were utilized to prepare thematic layers, and the weightings of these layers were evaluated using a questionnaire and analytical hierarchy process (AHP) and fuzzy set technique. The results provided a landfill suitability index (LSI) map and demonstrated the percentage of suitable areas. The findings can guide decision-makers in selecting an optimal landfill site and enhance landfill site suitability in Najran city.
Article
Thermodynamics
Mohsen Rezaei
Summary: A novel concept called possibilistic stochastic multi-attribute decision-making (PSMADM) is proposed in this study to address uncertainties in the field of energy policy. The approach is used to rank Iran's biodiesel development policies, with the results indicating that supporting the private sector for more participation in biodiesel development is the best alternative. The study also introduces a new scenario planning method for designing biodiesel scenarios, and utilizes fuzzy SWARA and fuzzy EDAS methods to solve different MCDM models.
Article
Green & Sustainable Science & Technology
Seyyed Shahabaddin Hosseini Dehshiri, Bahar Firoozabadi
Summary: The purpose of this study is to evaluate and compare solar tracking systems connected to the grid. The technical, economic and environmental assessment of different solar systems was conducted using HOMER software. Multi-criteria decision-making approaches were used to prioritize the tracking systems based on their economic and technical superiority. The results showed that the Two-Axis (TA) tracking system generated the most electricity and had the highest reduction in CO2 emissions.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2023)
Article
Chemistry, Physical
Ruojue Lin, Shengfang Lu, Ao Yang, Weifeng Shen, Jingzheng Ren
Summary: Hydrogen is gaining more attention for its low environmental impact and high energy density, but the sustainability priorities of different production pathways have not been determined. This study aims to develop a framework to assist in the sustainability-oriented selection of hydrogen production pathways, addressing the difficulty of hybrid information from different sources with a new method.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2021)
Article
Computer Science, Artificial Intelligence
Juan Miguel Sanchez-Lozano, Adela Ramos-Escudero, Isabel C. Gil-Garcia, Ma Socorro Garcia-Cascales, Angel Molina-Garcia
Summary: The research compares various fuzzy MCDM methodologies for selecting optimal locations of offshore wind power plants, showing the robustness of fuzzy TOPSIS method and the minimal impact of different fuzzy membership functions on the fuzzy VIKOR method.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Mathematics
Chin-Yi Chen, Jih-Jeng Huang
Summary: This paper presents an innovative method that integrates dynamic Bayesian networks (DBNs) with the analytic hierarchy process (AHP) to model dynamic interdependencies between criteria in multi-criteria decision-making (MCDM) problems. The proposed method extends the AHP to accommodate time-dependent issues and reduces to the conventional AHP when ignoring specific information, making it a more general AHP model.
Article
Engineering, Civil
Homayoun Motiee, Reza Khalili, Behrooz Gholami, Soroush Motiee
Summary: This paper explores the use of AHP and GIS to identify the optimal route for a pressurized water transmission line. Economic, environmental, social, and technical criteria are considered in the decision-making process. AHP is used to weight these criteria, and GIS is employed to overlay and analyze the weighted layers, ultimately determining the most cost-effective path among available options.
WATER RESOURCES MANAGEMENT
(2023)
Article
Environmental Sciences
Farahnaz Rashidi, Shadi Sharifian
Summary: Natural resource management relies on considering ecological constraints, assessing land suitability, and meeting socio-economic demands. However, in many developing countries, natural resources are often over-utilized due to the lack of consideration for conservation and natural constraints during planning, influenced by political or economic views. To address this issue, this study examines the application of three multi-criteria decision-making methods in assessing land suitability for afforestation. The results show that the fuzzy AHP method combined with TOPSIS generates more reliable outcomes than the AHP method, providing useful insights for decision-making in afforestation.
ENVIRONMENTAL MONITORING AND ASSESSMENT
(2022)
Article
Green & Sustainable Science & Technology
H. Diaz, C. Guedes Soares
Summary: This paper presents a method for planning offshore wind farm locations using multi criteria decision analysis and geographic information systems. Various criteria are considered, including technological, environmental, social, and economic factors, to evaluate and rank potential locations. The robustness of the results is assessed through sensitivity and consensus analyses, demonstrating the potential of the tool to support planners in designating regions for floating wind farm development.
Article
Computer Science, Artificial Intelligence
S. Haseena, S. Saroja, T. Revathi
Summary: Due to busy lifestyles, people easily adapt to unhealthy diets, leading to various health problems. This study proposes a system that ranks diet plans based on personal information to meet individual nutritional needs.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Biology
Orhan Mete Kilic, Kemal Ersayin, Hikmet Gunal, Ahlam Khalofah, Moodi Saham Alsubeie
Summary: Land suitability classification using GIS and AHP-fuzzy algorithm was conducted to analyze the suitability of bread wheat cultivation in the Tozanli sub-basin of Yesilirmak Basin, Turkey. The study integrated topographic characteristics and soil properties to generate a land suitability map, which identified different suitability levels for wheat production.
SAUDI JOURNAL OF BIOLOGICAL SCIENCES
(2022)
Article
Construction & Building Technology
Jia Liang, Qipeng Zhang, Xingyu Gu
Summary: A lightweight PCSNet-based segmentation model is developed to address the issues of insufficient performance in feature extraction and boundary loss information. The introduction of generalized Dice loss improves prediction performance, and the visualization of class activation mapping enhances model interpretability.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Gilsu Jeong, Minhyuk Jung, Seongeun Park, Moonseo Park, Changbum Ryan Ahn
Summary: This study introduces a contextual audio-visual approach to recognize multi-equipment activities in tunnel construction sites, improving monitoring effectiveness. Tested against real-world operation data, the model achieved remarkable results, emphasizing the potential of contextual multimodal models in enhancing operational efficiency in complex construction sites.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Jin Wang, Zhigao Zeng, Pradip Kumar Sharma, Osama Alfarraj, Amr Tolba, Jianming Zhang, Lei Wang
Summary: This study presents a dual-path network for pavement crack segmentation, combining Convolutional Neural Network (CNN) and transformer. A lightweight CNN encoder is used for local feature extraction, while a novel transformer encoder integrates high-low frequency attention mechanism and efficient feedforward network for global feature extraction. Additionally, a complementary fusion module is introduced to aggregate intermediate features extracted from both encoders. Evaluation on three datasets confirms the superior performance of the proposed network.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Pierre Gilibert, Romain Mesnil, Olivier Baverel
Summary: This paper introduces a flexible method for crafting 2D assemblies adaptable to various geometric assumptions in the realm of sustainable construction. By utilizing digital fabrication technologies and optimization approaches, precise control over demountable buildings can be achieved, improving mechanical performance and sustainability.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Jorge Loy-Benitez, Myung Kyu Song, Yo-Hyun Choi, Je-Kyum Lee, Sean Seungwon Lee
Summary: This paper discusses the advancement of tunnel boring machines (TBM) through the application of artificial intelligence. It highlights the significance of AI-based management subsystems for automatic TBM operations and presents recent contributions in this field. The paper evaluates modeling, monitoring, and control subsystems and suggests research paths for integrating existing management subsystems into TBM automation.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Alireza Shamshiri, Kyeong Rok Ryu, June Young Park
Summary: This paper reviews the application of text mining and natural language processing in the construction field, highlighting the need for automation and minimizing manual tasks. The study identifies potential research opportunities in strengthening overlooked construction aspects, coupling diverse data formats, and leveraging pre-trained language models and reinforcement learning.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Zhengyi Chen, Hao Wang, Keyu Chen, Changhao Song, Xiao Zhang, Boyu Wang, Jack C. P. Cheng
Summary: This study proposes an improved coverage path planning system that leverages building information modeling and robotic configurations to optimize coverage performance in indoor environments. Experimental validation shows the effectiveness and applicability of the system. Future research will focus on further enhancing coverage ratio and optimizing computation time.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Yonglin Fu, Junjie Chen, Weisheng Lu
Summary: This study presents a review of human-robot collaboration (HRC) in modular construction manufacturing (MCM), focusing on tasks, human roles, and interaction levels. The review found that HRC solutions are applicable to various MCM tasks, with a primary focus on timber component production. It also revealed the diverse collaborative roles humans can play and the varying levels of interaction with robots.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Qiong Liu, Shengbo Cheng, Chang Sun, Kailun Chen, Wengui Li, Vivian W. Y. Tam
Summary: This paper presents an approach to enhance the path-following capability of concrete printing by integrating steel cables into the printed mortar strips, and validates the feasibility and effectiveness of this approach through experiments.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Honghu Chu, Lu Deng, Huaqing Yuan, Lizhi Long, Jingjing Guo
Summary: The study proposes a method called Cascade CATransUNet for high-resolution crack image segmentation. This method combines the coordinate attention mechanism and self-cascaded design to accurately segment cracks. Through a customized feature extraction architecture and an optimized boundary loss function, the proposed method achieves impressive segmentation performance on HR images and demonstrates its practicality in UAV crack detection tasks.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Daniel Lamas, Andres Justo, Mario Soilan, Belen Riveiro
Summary: This paper introduces a new method for creating synthetic point clouds of truss bridges and demonstrates the effectiveness of a deep learning approach for semantic and instance segmentation of these point clouds. The proposed methodology has significant implications for the development of automated inspection and monitoring systems for truss bridges.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Kahyun Jeon, Ghang Lee, Seongmin Yang, Yonghan Kim, Seungah Suh
Summary: This study proposes two enhanced unsupervised text classification methods for domain-specific non-English text. The results of the tests show that these methods achieve excellent performance on Korean building defect complaints, outperforming state-of-the-art zero-shot and few-shot text classification methods, with minimal data preparation effort and computing resources.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Yoonhwa Jung, Julia Hockenmaier, Mani Golparvar-Fard
Summary: This study introduces a transformer-based natural language processing model, UNIfORMATBRIDGE, that automatically labels activities in a project schedule with Uniformat classification. Experimental results show that the model performs well in matching unstructured schedule data to Uniformat classifications. Additionally, the study highlights the importance of this method in developing new techniques.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
De-Graft Joe Opoku, Srinath Perera, Robert Osei-Kyei, Maria Rashidi, Keivan Bamdad, Tosin Famakinwa
Summary: This paper introduces a digital twin technology combining Building Information Modelling and the Internet of Things for the construction industry, aiming to optimize building conditions. The technology is implemented in a university library, successfully achieving real-time data capture and visual representation of internal conditions.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Zaolin Pan, Yantao Yu
Summary: The construction industry faces safety and workforce shortages globally, and worker-robot collaboration is seen as a solution. However, robots face challenges in recognizing worker intentions in construction. This study tackles these challenges by proposing a fusion method and investigating the best granularity for recognizing worker intentions. The results show that the proposed method can recognize multi-granular worker intentions effectively, contributing to seamless worker-robot collaboration in construction.
AUTOMATION IN CONSTRUCTION
(2024)