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Ronca V, Uflaz E, Turan O, Bantan H, MacKinnon SN, Lommi A, Pozzi S, Kurt RE, Arslan O, Kurt YB, Erdem P, Akyuz E, Vozzi A, Di Flumeri G, Aricò P, Giorgi A, Capotorto R, Babiloni F, Borghini G. Neurophysiological Assessment of An Innovative Maritime Safety System in Terms of Ship Operators' Mental Workload, Stress, and Attention in the Full Mission Bridge Simulator. Brain Sci 2023; 13:1319. [PMID: 37759921 PMCID: PMC10526160 DOI: 10.3390/brainsci13091319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 09/01/2023] [Accepted: 09/08/2023] [Indexed: 09/29/2023] Open
Abstract
The current industrial environment relies heavily on maritime transportation. Despite the continuous technological advances for the development of innovative safety software and hardware systems, there is a consistent gap in the scientific literature regarding the objective evaluation of the performance of maritime operators. The human factor is profoundly affected by changes in human performance or psychological state. The difficulty lies in the fact that the technology, tools, and protocols for investigating human performance are not fully mature or suitable for experimental investigation. The present research aims to integrate these two concepts by (i) objectively characterizing the psychological state of mariners, i.e., mental workload, stress, and attention, through their electroencephalographic (EEG) signal analysis, and (ii) validating an innovative safety framework countermeasure, defined as Human Risk-Informed Design (HURID), through the aforementioned neurophysiological approach. The proposed study involved 26 mariners within a high-fidelity bridge simulator while encountering collision risk in congested waters with and without the HURID. Subjective, behavioral, and neurophysiological data, i.e., EEG, were collected throughout the experimental activities. The results showed that the participants experienced a statistically significant higher mental workload and stress while performing the maritime activities without the HURID, while their attention level was statistically lower compared to the condition in which they performed the experiments with the HURID (all p < 0.05). Therefore, the presented study confirmed the effectiveness of the HURID during maritime operations in critical scenarios and led the way to extend the neurophysiological evaluation of the HFs of maritime operators during the performance of critical and/or standard shipboard tasks.
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Affiliation(s)
- Vincenzo Ronca
- Department of Computer, Control, and Management Engineering, Sapienza University of Rome, 00185 Roma, Italy; (V.R.); (P.A.); (R.C.)
- BrainSigns Srl, Industrial Neurosciences Lab, 00198 Rome, Italy; (A.V.); (G.D.F.); (A.G.); (F.B.)
| | - Esma Uflaz
- Department of Maritime Transportation and Management Engineering, Istanbul Technical University, Tuzla, Istanbul 34485, Turkey; (E.U.); (O.A.); (E.A.)
| | - Osman Turan
- Maritime Human Factors Centre, Histological, Forensic and Orthopaedic Sciences, University of Strathclyde Glasgow, Glasgow G1 1XQ, UK; (O.T.); (H.B.); (R.E.K.); (Y.B.K.); (P.E.)
| | - Hadi Bantan
- Maritime Human Factors Centre, Histological, Forensic and Orthopaedic Sciences, University of Strathclyde Glasgow, Glasgow G1 1XQ, UK; (O.T.); (H.B.); (R.E.K.); (Y.B.K.); (P.E.)
| | - Scott N. MacKinnon
- Department of Mechanics and Maritime Sciences, Chalmers University of Technology, 41296 Gothenburg, Sweden;
| | | | | | - Rafet Emek Kurt
- Maritime Human Factors Centre, Histological, Forensic and Orthopaedic Sciences, University of Strathclyde Glasgow, Glasgow G1 1XQ, UK; (O.T.); (H.B.); (R.E.K.); (Y.B.K.); (P.E.)
| | - Ozcan Arslan
- Department of Maritime Transportation and Management Engineering, Istanbul Technical University, Tuzla, Istanbul 34485, Turkey; (E.U.); (O.A.); (E.A.)
| | - Yasin Burak Kurt
- Maritime Human Factors Centre, Histological, Forensic and Orthopaedic Sciences, University of Strathclyde Glasgow, Glasgow G1 1XQ, UK; (O.T.); (H.B.); (R.E.K.); (Y.B.K.); (P.E.)
| | - Pelin Erdem
- Maritime Human Factors Centre, Histological, Forensic and Orthopaedic Sciences, University of Strathclyde Glasgow, Glasgow G1 1XQ, UK; (O.T.); (H.B.); (R.E.K.); (Y.B.K.); (P.E.)
| | - Emre Akyuz
- Department of Maritime Transportation and Management Engineering, Istanbul Technical University, Tuzla, Istanbul 34485, Turkey; (E.U.); (O.A.); (E.A.)
| | - Alessia Vozzi
- BrainSigns Srl, Industrial Neurosciences Lab, 00198 Rome, Italy; (A.V.); (G.D.F.); (A.G.); (F.B.)
- Department of Anatomical, Histological, Forensic and Orthopaedic Sciences, Sapienza University of Rome, 00185 Roma, Italy
| | - Gianluca Di Flumeri
- BrainSigns Srl, Industrial Neurosciences Lab, 00198 Rome, Italy; (A.V.); (G.D.F.); (A.G.); (F.B.)
- Department of Molecular Medicine, Sapienza University of Rome, 00185 Roma, Italy
| | - Pietro Aricò
- Department of Computer, Control, and Management Engineering, Sapienza University of Rome, 00185 Roma, Italy; (V.R.); (P.A.); (R.C.)
- BrainSigns Srl, Industrial Neurosciences Lab, 00198 Rome, Italy; (A.V.); (G.D.F.); (A.G.); (F.B.)
| | - Andrea Giorgi
- BrainSigns Srl, Industrial Neurosciences Lab, 00198 Rome, Italy; (A.V.); (G.D.F.); (A.G.); (F.B.)
- Department of Anatomical, Histological, Forensic and Orthopaedic Sciences, Sapienza University of Rome, 00185 Roma, Italy
| | - Rossella Capotorto
- Department of Computer, Control, and Management Engineering, Sapienza University of Rome, 00185 Roma, Italy; (V.R.); (P.A.); (R.C.)
- BrainSigns Srl, Industrial Neurosciences Lab, 00198 Rome, Italy; (A.V.); (G.D.F.); (A.G.); (F.B.)
| | - Fabio Babiloni
- BrainSigns Srl, Industrial Neurosciences Lab, 00198 Rome, Italy; (A.V.); (G.D.F.); (A.G.); (F.B.)
- Department of Molecular Medicine, Sapienza University of Rome, 00185 Roma, Italy
- College of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310005, China
| | - Gianluca Borghini
- BrainSigns Srl, Industrial Neurosciences Lab, 00198 Rome, Italy; (A.V.); (G.D.F.); (A.G.); (F.B.)
- Department of Molecular Medicine, Sapienza University of Rome, 00185 Roma, Italy
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Molęda M, Małysiak-Mrozek B, Ding W, Sunderam V, Mrozek D. From Corrective to Predictive Maintenance-A Review of Maintenance Approaches for the Power Industry. SENSORS (BASEL, SWITZERLAND) 2023; 23:5970. [PMID: 37447820 DOI: 10.3390/s23135970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 06/23/2023] [Accepted: 06/24/2023] [Indexed: 07/15/2023]
Abstract
Appropriate maintenance of industrial equipment keeps production systems in good health and ensures the stability of production processes. In specific production sectors, such as the electrical power industry, equipment failures are rare but may lead to high costs and substantial economic losses not only for the power plant but for consumers and the larger society. Therefore, the power production industry relies on a variety of approaches to maintenance tasks, ranging from traditional solutions and engineering know-how to smart, AI-based analytics to avoid potential downtimes. This review shows the evolution of maintenance approaches to support maintenance planning, equipment monitoring and supervision. We present older techniques traditionally used in maintenance tasks and those that rely on IT analytics to automate tasks and perform the inference process for failure detection. We analyze prognostics and health-management techniques in detail, including their requirements, advantages and limitations. The review focuses on the power-generation sector. However, some of the issues addressed are common to other industries. The article also presents concepts and solutions that utilize emerging technologies related to Industry 4.0, touching on prescriptive analysis, Big Data and the Internet of Things. The primary motivation and purpose of the article are to present the existing practices and classic methods used by engineers, as well as modern approaches drawing from Artificial Intelligence and the concept of Industry 4.0. The summary of existing practices and the state of the art in the area of predictive maintenance provides two benefits. On the one hand, it leads to improving processes by matching existing tools and methods. On the other hand, it shows researchers potential directions for further analysis and new developments.
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Affiliation(s)
- Marek Molęda
- TAURON Wytwarzanie S.A., Promienna 51, 43-603 Jaworzno, Poland
| | - Bożena Małysiak-Mrozek
- Department of Distributed Systems and Informatic Devices, Silesian University of Technology, 44-100 Gliwice, Poland
| | - Weiping Ding
- School of Information Science and Technology, Nantong University, No. 9 Seyuan Road, Nantong 226019, China
| | - Vaidy Sunderam
- Department of Computer Science, Emory University, Atlanta, GA 30322, USA
| | - Dariusz Mrozek
- Department of Applied Informatics, Silesian University of Technology, 44-100 Gliwice, Poland
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3
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A reliable probabilistic risk-based decision-making method: Bayesian Technique for Order of Preference by Similarity to Ideal Solution (B-TOPSIS). Soft comput 2022. [DOI: 10.1007/s00500-022-07462-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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Gupta S, Khanna R, Kohli P, Agnihotri S, Soni U, Asjad M. Risk evaluation of electric vehicle charging infrastructure using Fuzzy AHP – a case study in India. OPERATIONS MANAGEMENT RESEARCH 2022. [DOI: 10.1007/s12063-022-00290-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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5
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Causal Analysis and Prevention Measures for Extreme Heavy Rainstorms in Zhengzhou to Protect Human Health. Behav Sci (Basel) 2022; 12:bs12060176. [PMID: 35735386 PMCID: PMC9219977 DOI: 10.3390/bs12060176] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 05/25/2022] [Accepted: 05/31/2022] [Indexed: 12/10/2022] Open
Abstract
This study focused on the extreme heavy rainstorm that occurred in Zhengzhou in July 2021; approximately 380 people were killed or missing as a result of this storm. To investigate the evolution behaviors of this rainstorm and take corresponding prevention measures, several methods and models were adopted, including cloud modeling, preliminary hazard analysis (PHA), fault tree analysis (FTA), bow-tie modeling, and chaos theory. The main reasons for this rainstorm can be divided into the following three aspects: force majeure, such as terrain and extreme weather conditions, issues with city construction, and insufficient emergency rescue. The secondary disasters caused by this rainstorm mainly include urban water logging, river flooding, and mountain torrents and landslides. The main causes of the subway line-5 accident that occurred can be described as follows: the location of the stabling yard was low, the relevant rules and regulations of the subway were not ideal, insufficient attention was given to the early warning information, and the emergency response mechanism was not ideal. Rainstorms result from the cross-coupling of faults in humans, objects, the environment, and management subsystems, and the evolution process shows an obvious butterfly effect. To prevent disasters caused by rainstorms, the following suggestions should be adopted: vigorously improve the risk awareness and emergency response capabilities of leading cadres, improve the overall level of urban disaster prevention and mitigation, reinforce the existing reservoirs in the city, strengthen the construction of sponge cities, and improve the capacity of urban disaster emergency rescue.
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Kumar M, Singh K. Fuzzy fault tree analysis of chlorine gas release hazard in Chlor-Alkali industry using α-cut interval-based similarity aggregation method. Appl Soft Comput 2022. [DOI: 10.1016/j.asoc.2022.109199] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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7
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Su L, Zhang F, Yang F, Zhang L, Shen Y, Wei C, Yang Z. Study on quantification scheme of weight coefficient for electrical fire risk assessment of high-rise building. INTERNATIONAL JOURNAL OF METROLOGY AND QUALITY ENGINEERING 2022. [DOI: 10.1051/ijmqe/2022010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Electrical fire is a very important fire type in high-rise building fire. Therefore, it has high research value for risk assessment of electric fire in high-rise buildings. However, it is difficult to accurately obtain the weight index coefficient of electrical fire risk assessment by single qualitative or quantitative risk assessment method, so the reliability and objectivity of electrical fire risk assessment cannot be guarantee. In order to solve this problem, a method of using numerical simulation to obtain different types of fire risk data is proposed. Then, taking fire risk influencing factors as the research object, a comprehensive fire risk evaluation system is established. Through the comprehensive evaluation system, the electrical fire risk data are evaluated to determine the electrical fire risk weight coefficient. The results show that the fire risk quantification scheme of weight coefficient proposed in this paper can eliminate the subjectivity of traditional expert ratings. The proposed evaluation standard is a comprehensive evaluation system based on the numerical simulation and analytic hierarchy process. Above mentioned method can improve the reliability and accuracy of the weight coefficient of electrical fire risk assessment, and provide a theoretical basis for the research and classification of fire risk.
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8
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An Integrated Fuzzy Fault Tree Model with Bayesian Network-Based Maintenance Optimization of Complex Equipment in Automotive Manufacturing. ENERGIES 2021. [DOI: 10.3390/en14227758] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Process integrity, insufficient data, and system complexity in the automotive manufacturing sector are the major uncertainty factors used to predict failure probability (FP), and which are very influential in achieving a reliable maintenance program. To deal with such uncertainties, this study proposes a fuzzy fault tree analysis (FFTA) approach as a proactive knowledge-based technique to estimate the FP towards a convenient maintenance plan in the automotive manufacturing industry. Furthermore, in order to enhance the accuracy of the FFTA model in predicting FP, the effective decision attributes, such as the experts’ trait impacts; scales variation; and assorted membership, and the defuzzification functions were investigated. Moreover, due to the undynamic relationship between the failures of complex systems in the current FFTA model, a Bayesian network (BN) theory was employed. The results of the FFTA model revealed that the changes in various decision attributes were not statistically significant for FP variation, while the BN model, that considered conditional rules to reflect the dynamic relationship between the failures, had a greater impact on predicting the FP. Additionally, the integrated FFTA–BN model was used in the optimization model to find the optimal maintenance intervals according to the estimated FP and total expected cost. As a case study, the proposed model was implemented in a fluid filling system in an automotive assembly line. The FPs of the entire system and its three critical subsystems, such as the filling headset, hydraulic–pneumatic circuit, and the electronic circuit, were estimated as 0.206, 0.057, 0.065, and 0.129, respectively. Moreover, the optimal maintenance interval for the whole filling system considering the total expected costs was determined as 7th with USD 3286 during 5000 h of the operation time.
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Li L, Xu K, Yao X, Chen S. Probabilistic analysis of aluminium production explosion accidents based on a fuzzy Bayesian network. J Loss Prev Process Ind 2021. [DOI: 10.1016/j.jlp.2021.104618] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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10
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Xu Q, Xu K. Importance-Based Key Basic Event Identification and Evolution Mechanism Investigation of Hydraulic Support Failure to Protect Employee Health. SENSORS 2021; 21:s21217240. [PMID: 34770546 PMCID: PMC8587061 DOI: 10.3390/s21217240] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 10/20/2021] [Accepted: 10/28/2021] [Indexed: 11/16/2022]
Abstract
Background: Although hydraulic support can help enterprises in their production activities, it can also cause fatal accidents. Methods: This study established a composite risk-assessment method for hydraulic support failure in the mining industry. The key basic event of hydraulic support failure was identified based on fault tree analysis and gray relational analysis, and the evolution mechanism of hydraulic support failure was investigated based on chaos theory, a synthetic theory model, and cause-and-effect-layer-of-protection analysis (LOPA). Results: After the basic events of hydraulic support failure are identified based on fault tree analysis, structure importance (SI), probability importance (PI), critical importance (CI), and Fussell–Vesely importance (FVI) can be calculated. In this study, we proposed the Fussell–Vesely–Xu importance (FVXI) to reflect the comprehensive impact of basic event occurrence and nonoccurrence on the occurrence probability of the top event. Gray relational analysis was introduced to determine the integrated importance (II) of basic events and identify the key basic events. According to chaos theory, hydraulic support failure is the result of cross-coupling and infinite amplification of faults in the employee, object, environment, and management subsystems, and the evolutionary process has an obvious butterfly effect and inherent randomness. With the help of the synthetic theory model, we investigated the social and organizational factors that may lead to hydraulic support failure. The key basic event, jack leakage, was analyzed in depth based on cause-and-effect-LOPA, and corresponding independent protection layers (IPLs) were identified to prevent jack leakage. Implications: The implications of these findings with respect to hydraulic support failure can be regarded as the foundation for accident prevention in practice.
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Affiliation(s)
- Qingwei Xu
- College of Information and Management Science, Henan Agricultural University, Zhengzhou 450046, China
- Correspondence:
| | - Kaili Xu
- School of Resources and Civil Engineering, Northeastern University, Shenyang 110819, China;
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11
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A fuzzy decision-making approach to analyze the design principles for green ergonomics. Neural Comput Appl 2021. [DOI: 10.1007/s00521-021-06494-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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12
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Rehman OU, Ali Y. Enhancing healthcare supply chain resilience: decision-making in a fuzzy environment. INTERNATIONAL JOURNAL OF LOGISTICS MANAGEMENT 2021. [DOI: 10.1108/ijlm-01-2021-0004] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
PurposeResilience is a fundamental component of healthcare supply chains, as the quality and endurance of human life are dependent on them. However, there are numerous resilience-building measures, and there is a need for prioritization of those strategies. This research study aims to prioritize resilience strategies for healthcare supply chains while considering the risks that most severe, probable to occur and have the lengthiest periods of recovery.Design/methodology/approachThis research study has used multi-criteria decision-making (MCDM) techniques for analysis. Initially, the criteria for prioritization of risks, i.e. severity, probability of occurrence and recovery time were assigned with importance weights through the fuzzy analytical hierarchy process (AHP). Then, these weights were used in the fuzzy technique for order preference by similarity to ideal solution (TOPIS) analysis for prioritization of risks. Subsequently, the identified risks were used for highlighting the appropriate resilience strategies through the fuzzy quality function deployment (QFD) technique.FindingsResults indicate that Industry 4.0, multiple sourcing, risk awareness, agility and global diversification of suppliers, markets and operations are the most significant resilience strategies.Research limitations/implicationsThis study's limitation is that it is conducted in a general perspective, rather than reducing the context to a developing or developed country. Different areas have variable market factors, due to which potential risks occur in a different form. Moreover, resilience strategies work differently in different environments. Therefore, for future endeavors, the studies should be carried out in a limited context.Originality/valueThis research study proposes a novel MCDM-based approach for ranking resilience strategies, in light of the most probable, severe and long-lasting risks. In addition, this approach has been employed for the enhancement of resilience in healthcare supply chains.
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Li H, Guo JY, Yazdi M, Nedjati A, Adesina KA. Supportive emergency decision-making model towards sustainable development with fuzzy expert system. Neural Comput Appl 2021. [DOI: 10.1007/s00521-021-06183-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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15
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Das S, Garg A, Maiti J, Krishna O, Thakkar JJ, Gangwar R. A comprehensive methodology for quantification of Bow-tie under type II fuzzy data. Appl Soft Comput 2021. [DOI: 10.1016/j.asoc.2021.107148] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Oluwagbemi OO, Oluwagbemi FE, Jatto A, Hui C. MAVSCOT: A fuzzy logic-based HIV diagnostic system with indigenous multi-lingual interfaces for rural Africa. PLoS One 2020; 15:e0241864. [PMID: 33156877 PMCID: PMC7647102 DOI: 10.1371/journal.pone.0241864] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2020] [Accepted: 10/21/2020] [Indexed: 11/17/2022] Open
Abstract
HIV still constitutes a major public health problem in Africa, where the highest incidence and prevalence of the disease can be found in many rural areas, with multiple indigenous languages being used for communication by locals. In many rural areas of the KwaZulu-Natal (KZN) in South Africa, for instance, the most widely used languages include Zulu and Xhosa, with only limited comprehension in English and Afrikaans. Health care practitioners for HIV diagnosis and treatment, often, cannot communicate efficiently with their indigenous ethnic patients. An informatics tool is urgently needed to facilitate these health care professionals for better communication with their patients during HIV diagnosis. Here, we apply fuzzy logic and speech technology and develop a fuzzy logic HIV diagnostic system with indigenous multi-lingual interfaces, named Multi-linguAl HIV indigenouS fuzzy logiC-based diagnOstic sysTem (MAVSCOT). This HIV multilingual informatics software can facilitate the diagnosis in underprivileged rural African communities. We provide examples on how MAVSCOT can be applied towards HIV diagnosis by using existing data from the literature. Compared to other similar tools, MAVSCOT can perform better due to its implementation of the fuzzy logic. We hope MAVSCOT would help health care practitioners working in indigenous communities of many African countries, to efficiently diagnose HIV and ultimately control its transmission.
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Affiliation(s)
- Olugbenga Oluseun Oluwagbemi
- Department of Mathematical Sciences, Stellenbosch University, Matieland, Stellenbosch, South Africa
- Department of Computer Science and Information Technology, Sol Plaatje University, Kimberley, South Africa
- Nuffield Department of Medicine, Big Data Institute, University of Oxford, Oxford, United Kingdom
- DST/NRF Centre of Excellence in Epidemiological Modelling and Analysis, Stellenbosch University, Stellenbosch, South Africa
| | | | - Abdulwahab Jatto
- Department of Computer Science, Federal University Lokoja, Lokoja, Nigeria
| | - Cang Hui
- Department of Mathematical Sciences, Stellenbosch University, Matieland, Stellenbosch, South Africa
- African Institute for Mathematical Sciences, Cape Town, South Africa
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Azari A, Nabizadeh R, Mahvi AH, Nasseri S. Integrated Fuzzy AHP-TOPSIS for selecting the best color removal process using carbon-based adsorbent materials: multi-criteria decision making vs. systematic review approaches and modeling of textile wastewater treatment in real conditions. INTERNATIONAL JOURNAL OF ENVIRONMENTAL ANALYTICAL CHEMISTRY 2020. [DOI: 10.1080/03067319.2020.1828395] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Ali Azari
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Ramin Nabizadeh
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | - Amir Hossein Mahvi
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Simin Nasseri
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
- Center for Water Quality Research (CWQR), Institute for Environmental Research (IER), Tehran University of Medical Sciences (TUMS), Tehran, Iran
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Yin H, Liu C, Wu W, Song K, Liu D, Dan Y. Safety assessment of natural gas storage tank using similarity aggregation method based fuzzy fault tree analysis (SAM-FFTA) approach. J Loss Prev Process Ind 2020. [DOI: 10.1016/j.jlp.2020.104159] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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19
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Xu Q, Xu K. Statistical Analysis and Prediction of Fatal Accidents in the Metallurgical Industry in China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17113790. [PMID: 32471060 PMCID: PMC7312879 DOI: 10.3390/ijerph17113790] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 05/22/2020] [Accepted: 05/25/2020] [Indexed: 12/14/2022]
Abstract
The metallurgical industry is a significant component of the national economy. The main purpose of this study was to establish a composite risk analysis method for fatal accidents in the metallurgical industry. We collected 152 fatal accidents in the Chinese metallurgical industry from 2001 to 2018, including 141 major accidents, 10 severe accidents, and 1 extraordinarily severe accident, together resulting in 731 deaths. Different from traffic or chemical industry accidents, most of the accidents in the metallurgical industry are poisoning and asphyxiation accidents, which account for 40% of the total number of fatal accidents. As the original statistical data of fatal accidents in the metallurgical industry have irregular fluctuations, the traditional prediction methods, such as linear or quadratic regression models, cannot be used to predict their future characteristics. To overcome this issue, the grey interval predicting method and the GM(1,1) model of grey system theory are introduced to predict the future characteristics of fatal accidents in the metallurgical industry. Different from a fault tree analysis or event tree analysis, the bow tie model integrates the basic causes, possible consequences, and corresponding safety measures of an accident in a transparent diagram. In this study, the bow tie model was used to identify the causes and consequences of fatal accidents in the metallurgical industry; then, corresponding safety measures were adopted to reduce the risk.
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Affiliation(s)
- Qingwei Xu
- College of Information and Management Science, Henan Agricultural University, Zhengzhou 450046, China
- Correspondence:
| | - Kaili Xu
- Key Laboratory of Ministry of Education on Safe Mining of Deep Metal Mines, School of Resources and Civil Engineering, Northeastern University, Shenyang 110819, China;
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Zarei E, Yazdi M, Abbassi R, Khan F. A hybrid model for human factor analysis in process accidents: FBN-HFACS. J Loss Prev Process Ind 2019. [DOI: 10.1016/j.jlp.2018.11.015] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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21
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Fuzzy dynamic risk-based maintenance investment optimization for offshore process facilities. J Loss Prev Process Ind 2019. [DOI: 10.1016/j.jlp.2018.11.014] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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22
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A hybrid approach based on the analytic hierarchy process and 2-tuple hybrid ordered weighted averaging for location selection of distribution centers. PLoS One 2018; 13:e0206966. [PMID: 30408083 PMCID: PMC6224092 DOI: 10.1371/journal.pone.0206966] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2017] [Accepted: 10/23/2018] [Indexed: 11/19/2022] Open
Abstract
Distribution centers (DCs) are an important part of the modern logistics system. The selection of a location for a DC is significant for saving costs and reducing externalities caused by distribution. In this paper, we propose a new hybrid method based on the analytic hierarchy process (AHP) and 2-tuple hybrid ordered weighted averaging (THOWA) to select the location of a DC in a megacity. First, we propose a new set of evaluation criteria integrating economic, political, social and ecological information based on the characteristics of Chinese megacities. Second, subjective criteria weights are calculated by AHP combining the evaluation of logistics experts. Third, experts from academia, enterprise and government assess the performance of alternatives. In addition, the overall evaluation values are aggregated by an improved THOWA operator to rank the alternatives. Finally, we conduct a sensitivity analysis to investigate the influence of criteria weights on the decision-making process. The proposed method is novel and addresses the uncertainty under limited quantitative information, which has the advantages of avoiding information loss and distortion problems in the integrating process and operating linguistic evaluation information effectively. The proposed method can be practically applied by municipal planning departments in deciding on the location of new DCs. A numerical application of the proposed method is provided.
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