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Article ; Online: Optimal Waste-to-Energy Strategy Assisted by Fuzzy MCDM Model for Sustainable Solid Waste Management

Nguyen Van Thanh

Sustainability, Vol 14, Iss 6565, p

2022 Volume 6565

Abstract: In Vietnam, rapid population and economic growth are responsible for the recent increase in solid waste. Energy production from waste is now becoming an effective solution around the world, especially in Vietnam, to solve environmental challenges while ... ...

Abstract	In Vietnam, rapid population and economic growth are responsible for the recent increase in solid waste. Energy production from waste is now becoming an effective solution around the world, especially in Vietnam, to solve environmental challenges while contributing to the country’s sustainable energy production. Waste-to-energy production has become a solution to the municipal solid waste problem, which is projected to increase by 10–16%. In this study, the author proposed a fuzzy MCDM model to assess and select a solid-waste-to-energy plant location in Vietnam. In the first stage, the fuzzy analytic hierarchy process (FAHP) technique is utilized to analyze the relative weight of the primary and secondary evaluation elements, and a combined compromise solution (CoCoSo) model is used to rank the candidates in the final stage. This is the first solid-waste-to-energy plant location evaluation and selection model used in a renewable energy project in Vietnam based on expert interviews and a literature review. This study’s contribution can be a significant guide in analyzing and selecting appropriate locations for solid-waste-to-energy projects, as well as for decision makers and investors in other renewable energy projects in Vietnam and throughout the world.
Keywords	fuzzy theory ; MCDM model ; decision making ; solid waste to energy ; sustainable development ; operation research ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	690
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Blockchain Development Services Provider Assessment Model for a Logistics Organizations

Nguyen Van Thanh

Processes, Vol 10, Iss 1209, p

2022 Volume 1209

Abstract: As the global market develops along with technological advances, especially the opening of markets in developing and underdeveloped countries, the logistics industry is considered by managers to be a useful tool to link different functions of corporate ... ...

Abstract	As the global market develops along with technological advances, especially the opening of markets in developing and underdeveloped countries, the logistics industry is considered by managers to be a useful tool to link different functions of corporate strategy. Logistics is the process of planning, implementing and controlling the movement of goods or information that are related to raw materials (inputs) and final products (outputs) from the point of origin to the point of consumption in order to meet customer requirements. The logistics industry brings about many positive effects, not only for the national economy but also for creating equal business opportunities for businesses of all economic sectors. However, large companies in the logistics industry still depend on EDI or APIS to exchange secure authentication data, which increase the security of operations within the industry, but this is the cause of a lot of confusion with serious consequences on the supply chain when it is too dependent on these systems. To minimize the risks and optimize the problems mentioned above, blockchain technology could help the logistics industry to operate optimally. In an era when everything is digitized, from personal information to financial transactions, choosing a system with high reliability and security becomes extremely important. Currently, there are many blockchain development services providers and it is essential to choose the investment in this technology that suits the characteristics and purposes of the logistics organization in question. This study aimed to propose a two-stage fuzzy multicriteria decision-making model for the assessment of blockchain development services providers for logistics organizations. The hybrid MCDM model was evaluated through a real-world case study at a logistics organization. The contribution of this work is the provision of useful guidelines for the evaluation and selection of blockchain technology services providers for logistics companies.
Keywords	blockchain technology ; MCDM model ; fuzzy theory ; logistics ; Chemical technology ; TP1-1185 ; Chemistry ; QD1-999
Subject code	650
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A New Hybrid Triple Bottom Line Metrics and Fuzzy MCDM Model

Nguyen Van Thanh / Nguyen Thi Kim Lan

Axioms, Vol 11, Iss 57, p

Sustainable Supplier Selection in the Food-Processing Industry

2022 Volume 57

Abstract: Vietnam’s food processing and production industries in the past have managed to receive many achievements, contributing heavily to the growth of the country’s economic growth, especially the production index. Even with an increase of 7% per year over the ...

Abstract	Vietnam’s food processing and production industries in the past have managed to receive many achievements, contributing heavily to the growth of the country’s economic growth, especially the production index. Even with an increase of 7% per year over the past five years, the industry currently also faces problems and struggles that require business managers to rewrite legal documents and redevelop the business environment as well as the production conditions in order to compete better and use the available resources. Xanthan gum (a food additive and a thickener) is one of the most used ingredients in the food-processing industry. Xanthan gum is utilized in a number of variety of products such as canned products, ice cream, meats, breads, candies, drinks, milk products, and many others. Therefore, in order to improve competitiveness, the stage of selecting raw-material suppliers is a complicated task. The purpose of this study was to develop a new composite model using Triple Bottom Line Metrics, the Fuzzy Analytical Hierarchy Process (FAHP) method, and the Combined Compromise Solution (CoCoSo) algorithm for the selection of suppliers. The application process was accomplished for the Xanthan-gum (β-glucopyranose (C 35 H 49 O 29 )n) supplier selection in a food processing industry. In this study, the model building, solution, and application processes of the proposed integrated model for the supplier selection in the food-processing industry are presented.
Keywords	fuzzy theory ; FAHP ; CoCoSo ; MCDM ; chemistry ; supplier selection model ; Mathematics ; QA1-939
Subject code	650
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Optimization of Cold Chain Logistics with Fuzzy MCDM Model

Do Ngoc Hien / Nguyen Van Thanh

Processes, Vol 10, Iss 947, p

2022 Volume 947

Abstract: Vaccines are biological products containing a weakened, inactivated part of bacteria or viruses that are not harmful to the human body. Vaccine manufacturers and distributors should always store vaccines at the right temperature. To do this task, ... ...

Abstract	Vaccines are biological products containing a weakened, inactivated part of bacteria or viruses that are not harmful to the human body. Vaccine manufacturers and distributors should always store vaccines at the right temperature. To do this task, manufacturers and distributors need to manage cold supply chains to the required standards. Cold chain management helps manufacturers control and keep vaccines at the right temperature while ensuring quality and extending their expiration date. That will help businesses in the medical industry reduce economic losses, avoid waste, and bring more significant benefits to patients. The selection and evaluation process for logistics suppliers, especially those who deal with low-temperature storage, considers many factors to reduce the potential waste of products from poor storage strategies. The author introduces an integrated approach to solve such a fuzzy multiple criteria decision-making (MCDM) problem based on the Fuzzy Analytical Hierarchy Process (FAHP) model and an Interactive and Multi-criteria Decision-Making in Portuguese Model (TODIM) model methods under the fuzzy linguistic environment. In this work, the SF-AHP method derives criteria weights in the first stage, and then a TODIM method is presented to identify the ranking of logistics providers. Finally, the authors present a case study on the evaluation and selection of cold chain logistics suppliers to demonstrate the applicability of the proposed fuzzy MCDM model.
Keywords	vaccine supply chain ; logistics providers ; fuzzy MCDM model ; cold supply chain ; Chemical technology ; TP1-1185 ; Chemistry ; QD1-999
Subject code	650
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Logistics Service Provider Evaluation and Selection

Le Anh Luyen / Nguyen Van Thanh

Processes, Vol 10, Iss 1024, p

Hybrid SERVQUAL–FAHP–TOPSIS Model

2022 Volume 1024

Abstract: Production and business enterprises are aiming to improve their logistics activities in order to increase competitiveness. Therefore, the criteria and decision support models for selecting logistics service providers are significant to businesses. Fuzzy ... ...

Abstract	Production and business enterprises are aiming to improve their logistics activities in order to increase competitiveness. Therefore, the criteria and decision support models for selecting logistics service providers are significant to businesses. Fuzzy theory has been applied to almost all industrial engineering fields, such as decision making, operations research, quality control, project scheduling and many more. In this research, the authors combined fuzzy theory and a Multicriteria Decision Making (MCDM) model for the evaluation and selection of potential third-party logistics (3PL) providers. The goal is to take the advantages of these approaches and allow for more accurate and balanced (symmetric) decision making through their integration. The main contribution of this study is that it develops a complete approach to assessing the quality of the logistics service industry. The combined method of the SERVQUAL and FAHP–TOPSIS models not only provides reasonable results, but it also allows decision makers to visualize the impact of different criteria on the final outcome. Furthermore, this integrated model can provide valuable insights and methods for other areas to define service quality.
Keywords	fuzzy theory ; MCDM ; logistics services provider ; optimization ; Chemical technology ; TP1-1185 ; Chemistry ; QD1-999
Subject code	650
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: MXene nanosheet-derived N, S-codoped graphene quantum dots for ultrasensitive and selective detection of 3-nitro-l-tyrosine in human serum.

Anh, Nguyen Thi Ngoc / Huynh, Trung Viet / Nguyen, Van Thanh / Nguyen, Thi Kim Anh / Doong, Ruey-An

Analytica chimica acta

2024 Volume 1292, Page(s) 342237

Abstract: 3-Nitro-l-tyrosine (3NT) is an oxidative stress metabolite associated with neurodegenerative diseases such as Parkinson's disease and rheumatoid arthritis. In this study, the N, S-co-doped graphene quantum dots (NSGQDs) derived from nitrogen-doped ... ...

Abstract	3-Nitro-l-tyrosine (3NT) is an oxidative stress metabolite associated with neurodegenerative diseases such as Parkinson's disease and rheumatoid arthritis. In this study, the N, S-co-doped graphene quantum dots (NSGQDs) derived from nitrogen-doped Ti
MeSH term(s)	Humans ; Graphite ; Quantum Dots ; Nitrogen ; Neurodegenerative Diseases ; Nitrites ; Tyrosine/analogs & derivatives ; Transition Elements
Chemical Substances	Graphite (7782-42-5) ; 3-nitrotyrosine (3604-79-3) ; MXene ; Nitrogen (N762921K75) ; Nitrites ; Tyrosine (42HK56048U) ; Transition Elements
Language	English
Publishing date	2024-01-12
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	1483436-4
ISSN	1873-4324 ; 0003-2670
ISSN (online)	1873-4324
ISSN	0003-2670
DOI	10.1016/j.aca.2024.342237
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: 3D hierarchical cobalt vanadate nanosheet arrays on Ni foam coupled with redox additive for enhanced supercapacitor performance.

Nguyen, Van Thanh / Sari, Fitri Nur Indah / Ting, Jyh-Ming

RSC advances

2022 Volume 12, Issue 45, Page(s) 29170–29176

Abstract: Room-temperature synthesized 3D hierarchical cobalt vanadate ( ... ...

Abstract	Room-temperature synthesized 3D hierarchical cobalt vanadate (Co
Language	English
Publishing date	2022-10-12
Publishing country	England
Document type	Journal Article
ISSN	2046-2069
ISSN (online)	2046-2069
DOI	10.1039/d2ra05679h
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Article: A statistical approach to multisite downscaling of daily extreme temperature series: A case study using data in Bangladesh

Rahman, Mahzabeen / Nguyen, Van Thanh Van

International Association for Hydro-environment Engineering and Research, Asia Pacific Division Journal of hydro-environment research. 2022 Sept., v. 44

2022

Abstract: Downscaling techniques are required to describe the linkages between Global Climate Model outputs at coarse-grid resolutions to surface hydrologic variables at relevant finer scales for climate change impact and adaptation studies. In particular, several ...

Abstract	Downscaling techniques are required to describe the linkages between Global Climate Model outputs at coarse-grid resolutions to surface hydrologic variables at relevant finer scales for climate change impact and adaptation studies. In particular, several statistical methods have been proposed in many previous studies for downscaling of extreme temperature series for a single local site without taking into account the observed spatial dependence of these series between different locations. The present study proposes therefore an improved statistical approach to downscaling of daily maximum (Tmax) and minimum (Tmin) temperature series located at many different sites concurrently. This new multisite multivariate statistical downscaling (MMSD) method was based on a combination of the modeling of the linkages between local daily temperature extremes and global climate predictors by a multiple linear regression model; and the modeling of its stochastic components by the combined singular value decomposition and multivariate autoregressive (SVD-MAR) model to represent more effectively and more accurately the space-time variabilities of these extreme daily temperature series. Results of an illustrative application using daily extreme temperature data from a network of four weather stations in Bangladesh and two different NCEP/NCAR reanalysis datasets have indicated the effectiveness and accuracy of the proposed approach. In particular, this new approach was found to be able to reproduce accurately the basic statistical properties of the Tmax and Tmin at a single site as well as the spatial variability of temperature extremes between different locations. In addition, it has been demonstrated that the proposed method can produce better results than those given by the widely-used single-site downscaling SDSM procedure, especially in preserving the observed inter-site correlations.
Keywords	case studies ; climate ; climate change ; climate models ; data collection ; regression analysis ; research ; space and time ; temperature ; weather ; Bangladesh
Language	English
Dates of publication	2022-09
Size	p. 77-87.
Publishing place	Elsevier B.V.
Document type	Article
ISSN	1570-6443
DOI	10.1016/j.jher.2022.07.006
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Multicriteria Decision Making and Its Application in Geothermal Power Project

Thai Hoang Tuyet Nhi / Chia-Nan Wang / Nguyen Van Thanh

Sustainability, Vol 14, Iss 16016, p

2022 Volume 16016

Abstract: The International Energy Agency (IEA) assesses Vietnam as the second largest electricity user in Southeast Asia. The energy consumption growth rate in the region is one of the fastest in the world, with demand growing at a steady 6% per year for the past ...

Abstract	The International Energy Agency (IEA) assesses Vietnam as the second largest electricity user in Southeast Asia. The energy consumption growth rate in the region is one of the fastest in the world, with demand growing at a steady 6% per year for the past 20 years. Within the context that domestic fossil fuel production cannot keep up with demand and climate change is occurring, to avoid depending on imported energy to operate the power system, the Government of Vietnam has turned to developing renewable energy. The potential for developing geothermal energy in Vietnam is promising with more than 200 sources of water around 40 to 100 °C, which is sufficient for the development of geothermal energy projects. Today, a method to conserve natural resources and invest in renewable energy is provided by the government by controlling the importation of gas and coal while investing in building geothermal power plants. One of the hardest problems, however, is determining a suitable place to construct a geothermal power plant (GPP). For this main reason, in the hope of solving this problem, the author has proposed a decision-making model that utilizes a fuzzy set under multi-criteria conditions. It uses two methods, Fuzzy Analytic Hierarchy Process (FAHP) followed by Weighted Aggregated Sum Product Assessment (WASPAS), for a GPP site selection decision. The FAHP model is first used to determine the weights of each criterion and sub-criterion. Then, the ranking of each alternative is calculated by the WASPAS model. A final alternative is determined to be the best solution based on calculations from the methods above for identifying suitable locations for a GPP. This research has contributed a method of using a fuzzy multi-criteria decision-making model for determining a suitable location selection. This contribution also shows a development of flexibility towards decision making for other renewable energy projects worldwide.
Keywords	geothermal power plant (GPP) ; sustainable development ; fuzzy theory ; decision making ; MCDM model ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	690
Language	English
Publishing date	2022-11-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Enhancing the Fatigue Strength of the Weld Line in Advanced Polymer Injection Molding: Gas-Assisted Mold Temperature Control for Thermoplastic Polyurethane (TPU) Composites.

Minh, Pham Son / Uyen, Tran Minh The / Do, Thanh Trung / Nguyen, Van-Thuc / Nguyen, Van Thanh Tien

Polymers

2023 Volume 15, Issue 11

Abstract: This study presents an innovative approach to enhancing weld line strength in advanced polymer injection molding through applying gas-assisted mold temperature control, significantly increasing mold temperature beyond typical values observed in ... ...

Abstract	This study presents an innovative approach to enhancing weld line strength in advanced polymer injection molding through applying gas-assisted mold temperature control, significantly increasing mold temperature beyond typical values observed in conventional processes. We investigate the effects of various heating times and frequencies on the fatigue strength of Polypropylene (PP) samples and the tensile strength of Acrylonitrile Butadiene Styrene (ABS) composite samples at different Thermoplastic Polyurethane (TPU) percentages and heating times. Using gas-assisted mold heating, mold temperatures exceeding 210 °C are achieved, which represents a significant advancement compared to the standard mold temperatures of less than 100 °C. As a result, the fatigue strength of the PP sample with mold heating at 15 s shows a remarkable increase of up to 5.4 times at 5 Hz compared to the sample without mold temperature control. Moreover, ABS/TPU blends with 15 wt.% TPU exhibit the highest ultimate tensile strength (UTS) value of 36.8 MPa, while blends with 30 wt.% TPU have the lowest UTS value of 21.3 MPa. This advancement demonstrates the potential for improved welding line bonding and fatigue strength in manufacturing. Our findings reveal that increasing the mold temperature before injection results in higher fatigue strength in the weld line, with the TPU percentage having a more significant influence on the mechanical properties of ABS/TPU blends than heating time. The results of this study contribute to a deeper understanding of advanced polymer injection molding and offer valuable insights for process optimization.
Language	English
Publishing date	2023-05-25
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527146-5
ISSN	2073-4360 ; 2073-4360
ISSN (online)	2073-4360
ISSN	2073-4360
DOI	10.3390/polym15112440
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