Article
Green & Sustainable Science & Technology
Jiaqi Hu, Rui Huang, Fangting Xu
Summary: This study proposes a new framework that combines data mining technology and evidence-based safety theory to explore and obtain latent safety evidence in coal-mine data, and improve the reliability and sustainability of coal-mine safety management.
Article
Agronomy
Jiyoung Ha, Seunghyun Lee, Sangtae Kim
Summary: This study analyzed the influence relationship between news articles on onions and the consumer selling price of onions in Korea. The findings showed that hypermarket onion sales, onion supply and demand stabilization measures, and inflation had a significant impact on the selling price of onions.
Article
Construction & Building Technology
Yipeng Liu, Junwu Wang, Shanrong Tang, Jiaji Zhang, Jinyingjun Wan
Summary: Construction accident investigation reports are difficult to analyze due to the voluminous Chinese text. To overcome this problem, a novel approach combining text mining techniques and LDA models is proposed to identify the key factors leading to safety accidents in the Chinese construction industry.
Article
Multidisciplinary Sciences
Leacky Muchene, Wende Safari
Summary: The study utilized a two-stage topic modeling approach, using Latent Dirichlet Allocation for per-document topic probability derivation in the first stage, and hierarchical clustering with Hellinger distance for final topic cluster discovery in the second stage. The analysis revealed dominant research themes at the University of Nairobi, including HIV and malaria research, agricultural and veterinary services research, as well as cross-cutting themes in humanities and social sciences, demonstrating the effectiveness of hierarchical clustering in organizing discovered latent topics into homogeneous clusters.
Article
Computer Science, Artificial Intelligence
Mimu Kawai, Hiroyuki Sato, Takayuki Shiohama
Summary: This study proposes hybrid recommender models that use content-based filtering and latent Dirichlet allocation (LDA)-based models to address the cold-start problem in recommender systems. Experimental results demonstrate that these models achieve similar prediction performances compared to baseline models, while providing better interpretability of user and item topics.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Business
Junhan Kim, Youngjung Geum
Summary: This study proposes a systematic and concrete framework to develop data-driven technology roadmaps, consisting of three phases: layer mapping, contents mapping, and opportunity finding. This contributes to the field by providing a systematic method for data-driven roadmapping and offering data-driven evidence for more reasonable decision-making by experts.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2021)
Article
Computer Science, Artificial Intelligence
Radwa M. K. Saeed, Sherine Rady, Tarek F. Gharib
Summary: A supervised learning approach for Arabic sentiment classification is proposed, utilizing optimized compact features and feature reduction techniques to ensure high accuracy and time/space savings. Experimental results demonstrate significant improvement in accuracy, feature space savings, and classification execution time.
COGNITIVE COMPUTATION
(2021)
Review
Immunology
Chenyang Yu, Yingzhao Huang, Wei Yan, Xian Jiang
Summary: This study conducted a bibliometric analysis to evaluate the trends and hotspots in psoriatic research. The results showed that research on psoriasis is flourishing, with molecular pathogenesis, skin inflammation, and clinical trials being the current hotspots. Nail psoriasis, epidemiological study, and comorbidities of psoriasis have also gained increased attention.
FRONTIERS IN IMMUNOLOGY
(2023)
Review
Health Care Sciences & Services
Lauryn J. Hagg, Stephanie S. Merkouris, Gypsy A. O'Dea, Lauren M. Francis, Christopher J. Greenwood, Matthew Fuller-Tyszkiewicz, Elizabeth M. Westrupp, Jacqui A. Macdonald, George J. Youssef
Summary: This scoping review examines the methodological approaches used in psychology research using latent Dirichlet allocation (LDA). The findings highlight the growing use of LDA in psychological science and the need for improved analytical reporting standards and evidence-based best practice recommendations.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2022)
Review
Computer Science, Information Systems
Chetan Sharma, Isha Batra, Shamneesh Sharma, Arun Malik, A. S. M. Sanwar Hosen, In-Ho Ra
Summary: This study investigates the research trends and patterns in the field of smart cities, providing a comprehensive overview of smart cities research, including prominent countries, institutions, sources, and authors, as well as noteworthy research directions. The study also discusses scientific collaboration across countries, organizations, and authors, and presents a roadmap of smart cities research trends through experimental research.
Article
Green & Sustainable Science & Technology
Young-joo Ahn, Katie Bokyun Kim, Jin-young Kim
Summary: This study aims to extract topics from news articles on DMZ tourism published between 1990 and 2020 by using LDA. The results found that news articles on DMZ tourism can provide considerable information on political, social, and environmental issues. The study identifies the trends and characteristics of topics over the past 30 years and highlights important issues related to DMZ tourism that can promote tourism products and content.
Article
Computer Science, Artificial Intelligence
Huda A. Almuzaini, Aqil M. Azmi
Summary: This paper proposes an unsupervised model using multi-label topic modeling and genetic algorithm to automatically annotate textual data. The model was tested on Arabic and English datasets, and compared against human annotations. The results show promising performance in automatic annotation.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Automation & Control Systems
Xinsheng Zhang, Yulong Ma
Summary: This paper proposes a hybrid model based on the ALBERT model, combining text convolutional neural network, hierarchical attention mechanism, and latent Dirichlet allocation for sentiment analysis of sudden-onset disasters. Experimental results demonstrate that compared to XLNet, DistilBERT, and RoBERTa models, this approach achieves better performance by incorporating external topic knowledge into the language representation model.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Environmental Sciences
D. Tomojiri, K. Takaya, T. Ise
Summary: The study used the LDA model to infer the research topics about anthropogenic marine debris (AMD) and provide an overview of the research area. The results showed that the AMD research topics were mostly applied topics in interdisciplinary or transdisciplinary research areas. Furthermore, topics related to plastic pollution exhibited an upward trend, while those dealing with spatiotemporal dynamics and distribution patterns of marine debris showed a downward trend.
MARINE POLLUTION BULLETIN
(2022)
Article
Business
Munan Li, Wenshu Wang, Keyu Zhou
Summary: With the spillover of knowledge in the field of AI, exploring the technology emergence (TE) and technology opportunities (TO) related to AI has become increasingly important. The proposed coupling analysis and computing framework provide new insights for exploring specific topics in AI, enriching methodologies for technical opportunity analysis.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2021)
Article
Engineering, Industrial
Hao Sun, Haiqing Wang, Ming Yang, Genserik Reniers
Summary: To maintain continuous production, chemical plant operators may choose to ignore or handle faults online rather than shutting down process systems. However, the interaction and interdependence between components in a digitalized process system are significant, and faults can propagate to downstream nodes, potentially leading to risk accumulation and major accidents. This study proposes a dynamic risk assessment method that integrates the system-theoretic accident model and process approach (STAMP) with the cascading failure propagation model (CFPM) to model the risk accumulation process. The proposed method is applied to a Chevron refinery crude unit and demonstrates its effectiveness in quantifying the process of risk accumulation and providing real-time dynamic risk profiles for decision-making.
Article
Engineering, Industrial
M. Rempel
Summary: This article examines a major maritime disaster scenario and explores the evacuation process in such a situation. The study finds that there are various factors that affect the number of lives saved, including the uncertainty of individuals' medical condition, the arrival time of maritime and air assets, and the decision policies used. The authors formulate the multi-domain operation as a sequential decision problem using a modeling framework and provide decision support through a hypothetical case study.
Review
Engineering, Industrial
D. Scorgie, Z. Feng, D. Paes, F. Parisi, T. W. Yiu, R. Lovreglio
Summary: This study investigates the application and effectiveness of VR safety training solutions in various industries such as construction, fire, aviation, and mining. The findings suggest a need for more studies that adopt theories and measure long-term retention. Two meta-analyses demonstrate that VR safety training outperforms traditional training in terms of knowledge acquisition and retention.
Article
Engineering, Industrial
Shital Thekdi, Terje Aven
Summary: This paper examines biases in risk studies and investigates how to identify and address them to ensure high-quality risk analysis. By considering biases related to systematic error, event inclusion, models, and cognitive factors, the paper explores their influence on risk characterization. The insights gained from this exploration can be valuable to risk analysts, policymakers, and other stakeholders involved in risk study applications.
Article
Engineering, Industrial
Maryam Lari
Summary: Occupational health and safety (OHS) are crucial for employee well-being and productivity. This study examines the impact of OHS practices on employee productivity in a UAE Fire and Security company, finding that OHS interventions can enhance workplace ambiance and significantly boost employee productivity.
Review
Engineering, Industrial
Elleke Ketelaars, Cyrille Gaudin, Simon Flandin, Germain Poizat
Summary: This systematic literature review examines the literature on resilience training (RT), specifically focusing on the effectiveness of RT interventions in preparing professionals to effectively respond to critical situations. The review identifies five types of RT and suggests the need for conceptual advancements, vocational education and training perspectives, and a cross-disciplinary approach in future research to enhance resilience in safety-related domains.
Article
Engineering, Industrial
Meng Shi, Zhichao Zhang, Wenke Zhang, Yi Ma, Hanbo Li, Eric Wai Ming Lee
Summary: This study investigates pedestrian behaviours and evacuation processes in both fire and non-fire conditions using Minecraft. The results demonstrate the potential of Minecraft for realistically simulating evacuation processes, as the behaviours and flow patterns of pedestrians in virtual experiments fit well with real-life experiments. The study also shows that pedestrians exhibit fire avoidance behaviours and orderly queuing during a fire emergency, resulting in faster evacuation.
Article
Engineering, Industrial
Andrea Bikfalvi, Esperanza Villar Hoz, Gerusa Gimenez Leal, Monica Gonzalez-Carrasco, Nuria Mancebo
Summary: This paper proposes a solution for integrating occupational safety and health (OSH) into education, combining theoretical foundations and empirical evidence. The findings include analysis of teachers as stakeholders, barriers and facilitators of OSH integration, and the development of an ICT tool for interaction and sharing in this field. The main contribution lies in envisioning, orchestrating, and validating a solution to integrate OSH into schools and ultimately contribute to sustainable development goals.
Article
Engineering, Industrial
David Rehak, Alena Splichalova, Martin Hromada, Neil Walker, Heidi Janeckova, Josef Ristvej
Summary: This article discusses the adoption of a new directive on the resilience of critical entities and emphasizes the importance of assessing their level of resilience in relation to current security threats. The authors have developed a tool, known as the CERFI Tool, which uses a probabilistic algorithm to predict the failure point of critical entity resilience based on the relationship between threat intensity and protection. The tool is important for increasing the safety of technically oriented infrastructures, particularly in the energy and transport sectors.
Review
Engineering, Industrial
Leonardo Leoni, Ahmad Bahootoroody, Mohammad Mahdi Abaei, Alessandra Cantini, Farshad Bahootoroody, Filippo De Carlo
Summary: This paper presents a systematic bibliometric analysis (SBA) on the research of machine learning and deep learning in the field of safety. The main research areas, application fields, relevant authors and studies, and temporal evolution are investigated. It is found that rotating equipment, structural health monitoring, batteries, aeroengines, and turbines are popular fields, and there is an increase in popularity of deep learning and new approaches such as deep reinforcement learning.
Article
Engineering, Industrial
Tom Becker, Peter Ayton
Summary: By analyzing global civil aviation data, we found that there is a significant increase in the number of accidents and safety critical incidents, as well as the fatalities, when the Pilot-in-Command acts as the Pilot Flying instead of the Pilot Monitoring. Most of these events occurred in technically airworthy aircraft without any emergencies, and the flight crew assessed them as preventable. These findings align with the crew assignment effect, suggesting that role-dependent status hierarchy and cognitive overload contribute to ineffective flight crew teamwork. The measures implemented to enhance flight crew teamwork, such as Crew Resource Management training, have not been successful in preventing these issues.
Article
Engineering, Industrial
Ben Hutchinson, Sidney Dekker, Andrew Rae
Summary: This study found that health and safety audits often fail to identify critical deficiencies, with corrective actions mainly focusing on superficial fixes rather than addressing significant operational risks.
Review
Engineering, Industrial
Sina Rasouli, Yaghoub Alipouri, Shahin Chamanzad
Summary: Construction projects are risky environments, but the development of Personal Protective Equipment (PPE) and comprehensive safety management can effectively control the number of accidents.
Article
Engineering, Industrial
Laura Mills, Verity Truelove
Summary: This study investigated the use of police location communities (PLCs) for obtaining information about roadside drug testing (RDT) among drivers, and found that drivers who used PLCs were more concerned about being caught for drug driving, had a better understanding of the related penalties and procedures, and knew others who also used PLCs to avoid detection for drug driving. Furthermore, the study found that the use of PLCs was associated with choosing back roads for driving, which may reduce the risk of detection for drug driving.
Review
Engineering, Industrial
Chao Wu, Xi Huang, Bing Wang
Summary: After decades of development, the safety discipline in China has made remarkable progress. The project led by the Safety & Security Theory Innovation and Promotion Center of Central South University has filled the gaps in safety science education by creating textbooks and courses for postgraduate students. These achievements have played an important role in the development of safety science and can serve as a reference for basic research and talent training in safety science globally.