A comprehensive analysis of the importance of investigating the impact of Construction 4.0 skills on project performance DOI Creative Commons

Praveena Munianday,

Miri Sarawak,

Rahimi A. Rahman

et al.

Journal of Information Technology in Construction, Journal Year: 2024, Volume and Issue: 29, P. 686 - 721

Published: Sept. 29, 2024

Construction projects often face challenges of poor performance, resulting in increased costs, delays, and defects. To address these issues, 4.0 (C4.0) employs innovative technologies to enhance project efficiency, safety, sustainability. However, construction lag adopting technologies, meeting significant obstacles, with the inadequately trained workforce being a major, underexplored difficulty leading subpar performance. This study aims investigate current status existing research on C4.0 skills achieve this aim, conducts systematic literature review using Preferred Reporting Items for Systematic Reviews Meta-Analyses (PRISMA) method 50 articles. The findings suggest that general are recognized, but specific impact during fourth industrial revolution stays unexplored. emphasize need targeted identify examine crucial projects.

Language: Английский

Multi-Objective Optimization in Topic Modeling Using Sentence Reduction Based on Length and Weight (SR-LW) Technique DOI
Rana F. Najeeb, Ban N. Dhannoon, Farah Q. Al-Khalidi

et al.

Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 3 - 16

Published: Jan. 1, 2025

Language: Английский

Citations

0
Condition Monitoring and Diagnostic of Hydropower Units based on Machine Learning Techniques DOI

Samy Jad,

Xavier Desforges, Kamal Medjaher

et al.

Renewable Energy, Journal Year: 2025, Volume and Issue: unknown, P. 123210 - 123210

Published: April 1, 2025

Language: Английский

Citations

0
HCIVAD: Explainable hybrid voting classifier for network intrusion detection systems DOI

Usman Ahmed,

Jiangbin Zheng, Sheharyar Khan

et al.

Cluster Computing, Journal Year: 2025, Volume and Issue: 28(5)

Published: April 29, 2025

Language: Английский

Citations

0
Machine Learning for Precision Agriculture and Crop Yield Optimization DOI

Prodipto Roy,

Mrutyunjay Padhiary,

Azmirul Hoque

et al.

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 189 - 234

Published: March 28, 2025

The swift advancement of machine learning (ML) has altered several industries, including agriculture, by providing innovative ways addressing complex challenges related to modern farming. This chapter discusses the use ML in precision emphasizing its capacity maximize crop output and improve agricultural practices. It studies supervised, unsupervised, reinforcement, deep methodologies evaluate extensive datasets derived from remote sensing technologies, soil sensors, climate data, equipment. Principal applications include predictive modeling for yield estimation, pest disease identification, health assessment, irrigation optimization, fertilization. also examines problems limits implementation data quality farmer acceptance.

Language: Английский

Citations

0
Data stream mining techniques for real-time monitoring and control of smart power grids in Kenya: challenges and opportunities DOI Creative Commons

Cornelius Mutuku Mulevu,

George Okeyo,

Joseph Muliaro Wafula

et al.

Discover Internet of Things, Journal Year: 2025, Volume and Issue: 5(1)

Published: May 2, 2025

Language: Английский

Citations

0
Homogeneity and heterogeneity of diurnal and nocturnal hotspots and the implications for synergetic mitigation in heat-resilient urban planning DOI
Huimin Liu, Miao Li, Qingming Zhan

et al.

Computers Environment and Urban Systems, Journal Year: 2024, Volume and Issue: 117, P. 102241 - 102241

Published: Dec. 14, 2024

Language: Английский

Citations

3
Consumer Segmentation and Market Analysis for Sustainable Marketing Strategy of Electric Vehicles in the Philippines DOI Creative Commons

John Robin R. Uy,

Ardvin Kester S. Ong,

Danica Mariz B. De Guzman

et al.

World Electric Vehicle Journal, Journal Year: 2024, Volume and Issue: 15(7), P. 301 - 301

Published: July 8, 2024

Despite the steady rise of electric vehicles (EVs) in other countries, Philippines has yet to capitalize on its proliferation due several mixed concerns. Status, socio-demographic characteristics, and availability have been main concerns with purchasing EVs country. Consumer segmentation analysis for EV acceptance utility were determined this study need understanding consumer preferences market towards Philippines. A total 311 valid responses coming from owners collected through purposive snowball sampling approaches. The data via face-to-face distribution online a questionnaire covering demographic characteristics segmentation. Demographic such as gender, age, residence type, car ownership, income used identify segments using K-means clustering approach. Jupyter Notebook v7.1.3 was overall analysis, number clusters optimized, ensuring precise results indicated strong correlation between ownership ability purchase EVs, where effectively identified groups. groupings also included “Not Capable at All” “Highly Capable” individuals based their likelihood EVs. Based results, core-value customers are male, older than 55 years old, live urban areas, own vehicle insurance, monthly more PHP 130,000. Following those high-value customers, considered target users expected use frequently. It could be posited that frequent purchasers products services. aged 36–45 car, 100,001–130,000. Both these should highly by industries, would driving constructed provided valuable insights industry, academic institutions, policymakers, offering foundation targeted marketing strategies promoting adoption Moreover, sustainable developed adopted extended among developing countries wanting adopt utility. Future works suggested limitations researchers consider extensions, holistic approach considers environmental, social, economic factors, well policies promotion development.

Language: Английский

Citations

1
A geospatial clustering algorithm and its integration into a techno-economic rural electrification planning model DOI Creative Commons
Mirelys Torres Pérez, Javier Domínguez, Luis Arribas

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 137, P. 109249 - 109249

Published: Sept. 8, 2024

Language: Английский

Citations

1
Applying Hybrid Clustering with Evaluation by AUC Classification Metrics DOI Creative Commons
Ali Fattah Dakhil,

Waffaa M. Ali,

Mustafa Asaad Hasan

et al.

International Journal of Computing and Digital Systems, Journal Year: 2024, Volume and Issue: 15(1), P. 1091 - 1102

Published: March 1, 2024

Traditional metrics may not adequately assess performance in certain situations, whereas the Area Under Curve (AUC) offers a comprehensive perspective by considering both sensitivity and specificity.This method enhances interpretability, addresses limitations, promotes development of robust clustering algorithms.In unsupervised learning, utilizing AUC is significant for improving precision accuracy machine learning models.Our work inspired several recent related works that implement approaches to manage challenges developing new can effectively evaluate algorithms.The research question relies on concept using an optimal metric model evaluation classification clustering.Therefore, paper investigates use validation purposes.The methodology we adopt hybrid because such technique combining strengths each model.The linkage approach directly impacts results, so give attention this feature our implementation.Among various methods, utilized single average linkages.The Manhattan Euclidean are distance measures used work.Thus, contribution explore benefit linkages measurement with help metric.In addition, entire proposed contributions evaluated applied NSL-KDD dataset.Based clustering, Detection Rate (DR), False Alarm (FAR), other criteria chosen examine model's results capabilities.

Language: Английский

Citations

0
Performance Optimization of Document Clustering for Harry Potter Series Comments using Cosine Similarity DOI Creative Commons

Firza Septian,

Arief Zikry,

Nina Dwi Putriani

et al.

Deleted Journal, Journal Year: 2024, Volume and Issue: 1(1), P. 31 - 41

Published: Feb. 12, 2024

This research delves into the distinctive realm of comment clustering, focusing on extensive discourse generated by Harry Potter series. Leveraging a dataset from Kaggle, study aims to optimize document clustering using cosine similarity within K-Means algorithm. The addresses nuanced dynamics sentiment and preferences fan community. A comprehensive methodology involves data collection, preprocessing, TF-IDF initialization, with varying distance metrics, result evaluation. 491 respondents unveils diverse gender, geographical, age distributions, adding complexity analysis. results highlight predominant positive sentiment, emphasizing enduring popularity study's originality lies in its focus cultural phenomenon, contributing analysis engagement discourse. implications extend researchers, practitioners, enthusiasts seeking deeper understanding online discussions surrounding iconic media franchises.

Language: Английский

Citations

0