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Xie Y, Wang Y, He J, Yang X, Duan X, Zhao B. Human emissions of size-resolved fluorescent bioaerosols in control situations. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 926:171661. [PMID: 38490427 DOI: 10.1016/j.scitotenv.2024.171661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Revised: 03/09/2024] [Accepted: 03/09/2024] [Indexed: 03/17/2024]
Abstract
Human bioaerosols contribute significantly to indoor air quality. This study used a Wideband Integrated Bioaerosol Sensor (WIBS-4A) instrument for real-time measurement of particle size distribution and count to differentiate fluorescent bioaerosols from non-fluorescent aerosols. Through an experiment involving 12 subjects (six men and six women) wearing standard cotton clothing in a 2 m × 2 m × 2 m environmental chamber, we established a quantitative method to obtain the bioaerosol emission rate of a single subject, aiming to explore the effects of masks and sex on bioaerosol emissions from different individuals. The mean emission rates of fluorescent bioaerosols in the particle size ranges of 0.5-2.5 μm and 2.5-10 μm were 3.192±2.11×104 counts/(person·h) and 13.98±9.34×104 counts/(person·h), respectively. A comparison between those wearing and not wearing masks revealed no significant differences in the emissions of fluorescent bioaerosols. This suggests respiratory sources may not significantly impact the emissions of fluorescent bioaerosols from individuals under seated breathing conditions. Significant disparities in the fluorescent bioaerosol emission rates of different biological sexes were observed through independent sample analysis. Males exhibited 41 % and 15 % higher emission rates than females for particle size ranges of 0.5-2.5 μm and 2.5-10 μm, respectively, possibly because of different metabolic rates. A significant correlation between metabolic rates and fluorescent bioaerosols (sig = 0.044 < 0.05) was observed in all the subjects. These findings underscore the individual variations that affect bioaerosol emission rates. The data provided by this study will facilitate further analysis of the on-site measured data and source analysis.
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Affiliation(s)
- Yangyang Xie
- Department of Building Science, School of Architecture, Tsinghua University, Beijing, China; Department of Building Environment and Energy Engineering, School of Civil and Resources Engineering, University of Science and Technology Beijing, Beijing, China
| | - Yuxing Wang
- Department of Building Environment and Energy Engineering, School of Civil and Resources Engineering, University of Science and Technology Beijing, Beijing, China
| | - Junzhou He
- Department of Power Engineering, North China Electric Power University, Baoding, Hebei, China.
| | - Xudong Yang
- Department of Building Science, School of Architecture, Tsinghua University, Beijing, China; Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, China
| | - Xiaoli Duan
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, China
| | - Bin Zhao
- Department of Building Science, School of Architecture, Tsinghua University, Beijing, China; Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, China.
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Jana C, Hezam IM. Multi-attribute group decision making method for sponge iron factory location selection problem using multi-polar fuzzy EDAS approach. Heliyon 2024; 10:e27712. [PMID: 38509959 PMCID: PMC10950874 DOI: 10.1016/j.heliyon.2024.e27712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 02/29/2024] [Accepted: 03/05/2024] [Indexed: 03/22/2024] Open
Abstract
This paper presents new averaging operators, such as mpF Einstein weighted averaging (mpFEWA), mpF Einstein ordered weighted averaging (mpFEOWA), mpF Einstein hybrid weighted averaging (mpFEHWA), mpF Einstein weighted geometric (mpFEWG), and mpF Einstein hybrid weighted geometric (mpFEHWG), as well as new Einstein operations (mpFNs) for handling multi-polar fuzzy numbers. We evaluate these operators for idempotency, boundedness, monotonicity, and commutativity, and we design them to deal with multi-polar fuzzy numbers (mpFNs). Furthermore, the study investigates the use of these operators in MAGDM settings, namely mpFEWA and mpFEWG operators, to expand on this. Additionally, it proposes a procedure for determining the best site for a sponge iron production plant by use of the created MAGDM method. The EDAS method, which stands for "Evaluation based on Distance from Average Solution," verifies that the solutions are effective. Finally, the suggested model highlights the benefits and possible improvements provided by these creative strategies by comparing the new approach to conventional methods and evaluating its efficiency and practicality.
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Affiliation(s)
- Chiranjibe Jana
- Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Chennai 602105, Tamil Nadu, India
| | - Ibrahim M. Hezam
- Department of Statistics & Operations Research, College of Sciences, King Saud University, Riyadh, Saudi Arabia
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Chen TY. Multiple criteria decision analytic methods in management with T-spherical fuzzy information. Artif Intell Rev 2023:1-71. [PMID: 37362889 PMCID: PMC10148592 DOI: 10.1007/s10462-023-10461-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/28/2023]
Abstract
With a focus on T-spherical fuzzy (T-SF) sets, the aim of this paper is to create a split-new appraisal mechanism and an innovative decision analytic method for use with multiple-criteria assessment and selection in uncertain situations. The T-SF frame is the latest recent advancement in fuzzy settings and uses four facets (consisting of membership grades of positivity, neutrality, negativity, and refusal) to elucidate complex uncertainties, thereby evidently reducing information loss, in anticipation of fully manifesting indistinct and equivocal information. This paper adds to the body of knowledge regarding multiple criteria choice modeling by raising T-SF correlation-oriented measurements connected to the fixed and displaced ideal/anti-ideal benchmarks and by creating an approachable appraisal mechanism for advancing a T-SF decision analytic methodology. Consider, in particular, the performance ratings of available options in terms of judging criteria under the T-SF type of uncertainties. This research gives correlation-oriented measurements focusing on two varieties of maximum and square root functions in T-SF situations, which serve as a solid foundation for an efficacious appraisal mechanism from two views of anchored judgments corresponding to the fixed and displaced benchmarks. The T-SF Minkowski distance index is generated to integrate the outranking and outranked identifiers relying on correlation-oriented measurements for figuring out the local outranking and outranked indices. The T-SF decision analytic procedures are constructed using a new appraisal significance index that is founded on certain valuable insights of correlation-oriented maximizing and minimizing indices as well as global outranking and outranked indices. Additionally, a concrete location selection dilemma is dealt with in this research to showcase the applicability and efficiency of the suggested T-SF decision analytic methodology. Sensitivity analyses and comparative studies are carried out to investigate substantial modifications in pertinent parameters and to confirm the robustness of the predominance relationships among the available options. The suggested approaches are adaptable, flexible, and reliable, according to the application outcomes and comparison findings. This research provides four scientific contributions: (1) the utilization of T-SF correlation coefficients as the basis for prioritization analysis involving multiple criteria assessments, (2) the evolution of the T-SF Minkowski distance index to model outranking decision-making processes, (3) the creation of a reliable appraisal mechanism based on T-SF correlation-oriented measurements for intelligent decision support, and (4) the advancement of computational tools and procedures (e.g., correlation-oriented maximizing and minimizing indices, global outranking and outranked indices, and appraisal significance indices) to perform the decision analytic procedure in T-SF settings. In terms of managerial implications, the solution findings support the employment of the fixed ideal/anti-ideal benchmarking mechanism, as its measurements and indices are easy to operate and suitably sensitive. Next, in practical implementations of the T-SF decision analytic procedure, it is advised to utilize the T-SF Manhattan distance index for calculating convenience. Finally, the T-SF decision analytic techniques offer fundamental ideas and measurements appropriate for manipulating T-SF information in complex decision situations, thereby increasing the application potential in the area of decision-making with information uncertainty.
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Affiliation(s)
- Ting-Yu Chen
- Department of Industrial and Business Management, Graduate Institute of Management, Chang Gung University, No. 259, Wenhua 1st Rd., Guishan District, Taoyuan City, 33302 Taiwan
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Peng Y, Song D, Qiu L, Wang H, He X, Liu Q. Combined Prediction Model of Gas Concentration Based on Indicators Dynamic Optimization and Bi-LSTMs. SENSORS (BASEL, SWITZERLAND) 2023; 23:2883. [PMID: 36991592 PMCID: PMC10059839 DOI: 10.3390/s23062883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 02/17/2023] [Accepted: 02/27/2023] [Indexed: 06/19/2023]
Abstract
In order to accurately predict the gas concentration, find out the gas abnormal emission in advance, and take effective measures to reduce the gas concentration in time, this paper analyzes multivariate monitoring data and proposes a new dynamic combined prediction method of gas concentration. Spearman's rank correlation coefficient is applied for the dynamic optimization of prediction indicators. The time series and spatial topology features of the optimized indicators are extracted and input into the combined prediction model of gas concentration based on indicators dynamic optimization and Bi-LSTMs (Bi-directional Long Short-term Memory), which can predict the gas concentration for the next 30 min. The results show that the other gas concentration, temperature, and humidity indicators are strongly correlated with the gas concentration to be predicted, and Spearman's rank correlation coefficient is up to 0.92 at most. The average R2 of predicted value and real value is 0.965, and the average prediction efficiency R for gas abnormal or normal emission is 79.9%. Compared with the other models, the proposed dynamic optimized indicators combined model is more accurate, and the missing alarm of gas abnormal emission is significantly alleviated, which greatly improves the early alarming accuracy. It can assist the safety monitoring personnel in decision making and has certain significance to improve the safety production efficiency of coal mines.
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Affiliation(s)
- Yujie Peng
- School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
- Key Laboratory of Ministry of Education for High-Efficient Mining and Safety of Metal, University of Science and Technology Beijing, Beijing 100083, China
| | - Dazhao Song
- School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
- Key Laboratory of Ministry of Education for High-Efficient Mining and Safety of Metal, University of Science and Technology Beijing, Beijing 100083, China
| | - Liming Qiu
- School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
- Key Laboratory of Ministry of Education for High-Efficient Mining and Safety of Metal, University of Science and Technology Beijing, Beijing 100083, China
- State Key Laboratory of Coking Coal Exploitation and Comprehensive Utilization, Pingdingshan 467000, China
| | - Honglei Wang
- College of Safety Engineering, North China Institute of Science and Technology, Langfang 065201, China
| | - Xueqiu He
- School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
- Key Laboratory of Ministry of Education for High-Efficient Mining and Safety of Metal, University of Science and Technology Beijing, Beijing 100083, China
| | - Qiang Liu
- School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
- Key Laboratory of Ministry of Education for High-Efficient Mining and Safety of Metal, University of Science and Technology Beijing, Beijing 100083, China
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Meng Z, Lin R, Wu B. A novel multicriteria decision‐making approach based on Pythagorean fuzzy sets and graph theory. INT J INTELL SYST 2022. [DOI: 10.1002/int.23092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Zhenhua Meng
- State Key Laboratory of Networking and Switching Technology School of Computer Science (National Pilot Software Engineering School), Beijing University of Posts and Telecommunications Beijing China
| | - Rongheng Lin
- State Key Laboratory of Networking and Switching Technology School of Computer Science (National Pilot Software Engineering School), Beijing University of Posts and Telecommunications Beijing China
| | - Budan Wu
- State Key Laboratory of Networking and Switching Technology School of Computer Science (National Pilot Software Engineering School), Beijing University of Posts and Telecommunications Beijing China
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Intuitionistic and Interval-Valued Fuzzy Set Representations for Data Mining. ALGORITHMS 2022. [DOI: 10.3390/a15070249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Data mining refers to a variety of techniques in the fields of databases, machine learning and pattern recognition. The intent is to obtain useful patterns and associations from a large collection of data. In this paper we describe extensions to the attribute generalization process to deal with interval and intuitionistic fuzzy information. Specifically, we consider extensions for using interval-valued fuzzy representations in both data and the generalization hierarchy. Moreover, preliminary representations using intuitionistic fuzzy information for attribute generalization are described. Finally, we consider how to use fuzzy hierarchies for the generalization of interval-valued fuzzy representations.
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