Search

In Morocco, the production of argan oil generates a natural organic residue available at a low cost, which is known as argan cake. It shows potential as a biodiesel resource due to its substantial oil residue content. A kinetic study of transesterification was conducted to evaluate the potential of argan cake oil (ACO) in producing biodiesel. The obtained activation energy is equal to Ea = 30.85 kJ/mol, and the reaction rate falls within the range of 0.0121 to 0.0241 min−1 at temperatures between 40 and 60 °C. Realizing that the catalyst type has a significant impact on the reaction kinetics, a comparison was made between homogeneous, heterogeneous, and enzymatic catalysts using the multi-criteria decision-making (MCDM) method. This method was employed to select the catalyst that maximizes biodiesel yield while minimizing cost and environmental impact. Five catalyst types were studied: homogeneous acid and basic catalysts, heterogeneous acid and basic catalysts, and enzymatic catalysts. In the classification process, eight criteria were considered: catalyst sensitivity to free fatty acid (FFA) and water in the raw material, biodiesel yield, reaction rate, glycerol recovery, catalyst recovery and recycling, energy cost, catalyst cost, and environmental impact. The results from the Fuzzy Technique for Order of Preference by Similarity to the Ideal Solution (FTOPSIS) showed that the basic heterogeneous catalyst outperforms the other four examined catalysts. [ABSTRACT FROM AUTHOR]

Copyright of Neutrosophic Computing & Machine Learning is the property of Multimedia Larga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Neutrosophic Computing & Machine Learning is the property of Multimedia Larga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Neutrosophic Computing & Machine Learning is the property of Multimedia Larga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Neutrosophic Computing & Machine Learning is the property of Multimedia Larga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Neutrosophic Computing & Machine Learning is the property of Multimedia Larga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Neutrosophic Computing & Machine Learning is the property of Multimedia Larga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Neutrosophic Computing & Machine Learning is the property of Multimedia Larga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Neutrosophic Computing & Machine Learning is the property of Multimedia Larga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Neutrosophic Computing & Machine Learning is the property of Multimedia Larga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Food safety is a global public health issue and also a crucial aspect of food security. For a food manufacturing company, food safety plays an important role in maintaining its reputation, so entrepreneurs adopt certification standard systems to safeguard consumers. However, choosing a certification standard can become a complex and conflicting process for companies' decision-makers. This study proposes a multi-attribute analysis based on the multicriteria fuzzy analytic hierarchy process (FAHP) for the selection of a certification standard for food safety. Firstly, a set of certification standards in the field of food safety was selected based on a literature review and interviews with scholars and company managers. Secondly, a quantitative-qualitative interview with decision makers of a food company was performed using the AHP method. By using the AHP method, decision makers were able to compare, in a structured way, each set of criteria and assign weights for each one, according to their perception of importance. Results indicated that the hierarchical ordering of the alternatives for the decision-makers presented similar opinions regarding the weight of each criterion. Moreover, decision makers considered the cost of certification to be the most important criteria for choosing a certification standard. This paper makes unique contributions by presenting a systematic approach for managers of an industry to successfully solve complex multiple-criteria problems, such as the choice of a certification standard for food safety, with less time-consuming efforts. [ABSTRACT FROM AUTHOR]

The sugar and alcohol sectors are dynamic as a result of climate alterations, the introduction of sugarcane varieties, and new technologies. Despite these factors, Brazil stands out as the main producer of sugarcane worldwide, being responsible for 45% of the production of fuel ethanol. Several varieties of sugarcane have been developed in the past few years to improve features of the plant. This, however, led to the challenge of which variety producers should choose to plant on their property. In order to support this process, this research aims to test the application of the analytic hierarchy process (AHP) method to support producers to select which sugarcane variety to plant on their property. To achieve this goal, the research relied on a single case study performed on a rural property located inland of São Paulo state, the main producer state in Brazil. The results demonstrate the feasibility of the approach used, specifically owing to the adaptability capacity of the AHP method.

The authors have shown that errors in the values of indicator importance coefficients that characterize the system of interest can influence solutions obtained by multicriteria methods (alternative ranking and formation of their kernel). Assessing the stability of these solutions is an essential component of conclusions about the practical applicability of recommendations developed on their basis. The authors have proposed an approach to assessing the stability and used it in several examples of calculations. This approach increases the validity of the results of solving multicriteria problems by providing sufficiently objective basis for conclusions regarding their stability. [ABSTRACT FROM AUTHOR]

Copyright of GeSec: Revista de Gestao e Secretariado is the property of Sindicato das Secretarias e Secretarios do Estado de Sao Paulo (SINSESP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Everywhere in the world, in various scenarios and situations, it is necessary to deal with the need to make decisions. In the context of public management, this need is often seen. However, this process is not always finished with satisfactory and positive results. It was proposed to use the hybrid method to support decision-making AHP-TOPSIS-2N, which is the combination of the AHP (Analytic Hierarchy Process) method with the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method to assist the decision maker to improve the control of public spending. Several studies were presented that prove the veracity and effectiveness of the method being used in different contexts. The present study proved to be effective in presenting the method as a great tool that can assist public management in the bidding processes, and thus ensure results with greater transparency and effect, in addition to presenting to society favorable results with the use of this systematized and structured method. [ABSTRACT FROM AUTHOR]

The sugar and alcohol sectors are dynamic as a result of climate alterations, the introduction of sugarcane varieties, and new technologies. Despite these factors, Brazil stands out as the main producer of sugarcane worldwide, being responsible for 45% of the production of fuel ethanol. Several varieties of sugarcane have been developed in the past few years to improve features of the plant. This, however, led to the challenge of which variety producers should choose to plant on their property. In order to support this process, this research aims to test the application of the analytic hierarchy process (AHP) method to support producers to select which sugarcane variety to plant on their property. To achieve this goal, the research relied on a single case study performed on a rural property located inland of São Paulo state, the main producer state in Brazil. The results demonstrate the feasibility of the approach used, specifically owing to the adaptability capacity of the AHP method. [ABSTRACT FROM AUTHOR]

Copyright of Neutrosophic Computing & Machine Learning is the property of Multimedia Larga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Neutrosophic Computing & Machine Learning is the property of Multimedia Larga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In Tunisia, the evacuation of olive mill wastewater (OMWW) in storage tanks remains the most common way to manage this toxic effluent. Several environmental damages are registered due to the inappropriate locations of this OMWW tanks. Indeed, the storage tanks locations must be carefully selected where hydrogeological, environmental as well as socioeconomic criteria must be simultaneously considered. For this purpose, an integrated approach based on Geographic Information System (GIS), Global Positioning System (GPS) and multicriteria method (Analytic Hierarchy Process AHP) were developed to asses OMWW tanks sustainable management in Sousse region (Tunisia). The present paper consists to evaluate the current management of OMWW tanks in comparison with the existing standards. The results showed that most of the sites were not in the appropriate zone and did not meet the necessary standards and the minimum requirement to put in a storage tank, as expressed by the exclusion criteria. This strongly emphasizes the seriousness of the deteriorated environmental situation in the region. An awareness of these dangers that threaten public health and have some other associated risks is important. Hard work to resolve this situation is urgently required.

Copyright of Neutrosophic Computing & Machine Learning is the property of Multimedia Larga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Neutrosophic Computing & Machine Learning is the property of Multimedia Larga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

One of the operational reliability analyzes starts from analyzing three variables, the Equipment Variable, the Human Variable and the Technological Process Variable. The objective of the research was to propose a procedure using the AHP multicriteria method to quantify the relative importance of each of the variables present in the concept of operational reliability, equipment, human resources and technological process. A procedure supported by the method of the analytical hierarchy process and the use of Hierarchies software was proposed, expert analysis methods and surveys were also used. For the application of the procedure, a biopharmaceutical company was selected and within it two plants with different operational contexts, verifying that the results obtained were different and that the experts reached conclusions of different impact of these variables in the process. [ABSTRACT FROM AUTHOR]

For construction companies, the decision about whether to bid for a project is a strategic decision. This paper provides a model for assessing project attractiveness levels and deciding whether to submit a proposal. The model introduces a classification model that incorporates fuzzy preferential information to evaluate project attractiveness under multiple dimensions and enables the decision‐maker to make more effective decisions. Projects are assigned to ordinal categories of attractiveness based on an adapted fuzzy ELECTRE TRI‐C procedure. The main advantages of this model are that the attractiveness level can be used as an input for the bidding strategies, the attractiveness evaluation can support the contractor in prioritizing the projects to bid on, and the model captures the decision process's subjective assessments and situations of imprecision observed on early phases of the project life cycle. [ABSTRACT FROM AUTHOR]

It is known that selecting competent employees according to the company's profile is a recurring difficulty among all professionals and sectors of human resources, where decision making requires a high level of cognitive effort to make a correct and clear selection about the attributes competed. The most common ways of selecting a new employee is mostly based on several interviews, theorical and practical tests, forms and group dynamics, in the expectation that the data provided by the candidates will be the starting point for a great selection, but, in most cases, the selection is made in a way that do not use some logical think, just the empirical thinking, liable to make unjust selections or that do not meet expectations properly. Based on this fact, the objective of this work is to report the use of the multicriteria method to support decision making AHP-TOPSIS-2N through the web software Three Decision Methods to support the choice of intern for the IoT-Based startup "Riverdata". After interviews with the chosen one, it was noticed that the results were satisfactory and met the expectations of those responsible for the selection. [ABSTRACT FROM AUTHOR]

Copyright of PARC Pesquisa em Arquitetura e Construção is the property of Universidade Estadual de Campinas - Portal de Periodicos Eletronicos Cientificos and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Brazilian Business Law Journal / Administração de Empresas em Revista is the property of Administracao de Empresas em Revista and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Maintaining the supply chain of cattle introduces a challenge in the production destined for consumption, representing meat a food highly demanded by people. Measuring product quality is an essential element to ensure user satisfaction. Quality can be modeled from the behavior of a set of evaluative indicators through a multicriteria approach. The degree of compliance of an indicator is expressed through a direct relationship of performance or denial of this with a spectrum of neutrality representing a domain of neutrosophic values. The implementation of Soft Computing techniques has been used to represent uncertainty in decision-making processes of this nature. The present investigation describes a solution to the problem posed by developing a model that uses multicriteria method with Single-Valued Neutrosophic Number (SVNN) for the evaluation of the quality of the beef. [ABSTRACT FROM AUTHOR]

Large-scale photovoltaic (LSPV) may cause significant changes in the environment and lead to detrimental impacts on the natural and anthropic environments. First, this paper reviews the scholarly literature to collect data regarding the different environmental impacts occurring during LSPV installation and operation. Secondly, methods used in the Environmental Impact Assessment (EIA) for LSPV are evaluated through a sample of 20 EIAs. This shows that there are flaws in the methodology used in the EIAs that support environmental licensing of LSPV. In this context, this work proposes a multicriteria approach that aims to convey the main environmental and socio-economic aspects of LSPV and assess impact magnitude and importance. The method is built on the needs to improve EIA for the licensing of solar projects in Brazil. The model offers a structured approach that incorporates detailed criteria that reflect direct and indirect impacts of both terrestrial and floating PV and is designed to provide the assessment magnitude and estimate scenarios according to different stakeholder's views. [ABSTRACT FROM AUTHOR]

Abstract Since the use of electric vehicles decreases the local pollution and noise emission electromobility gains a huge potential in sustainable transport. The currently insufficient charging network, namely the low number of stations and ill-chosen locations are a significant barrier of the widespread of electric vehicles in many countries. Accordingly, localization of new charging stations is of utmost importance. In this study, we develop a two-level charging station locating method. Weighted multicriteria methods were introduced to evaluate territory segments and allocate charging stations within a segment applying a hexagon-based approach and using a greedy algorithm. The novelty of the method in comparison with previous studies is that it assesses the potential of electric vehicle use on macro-level and the possible locations of charging stations on micro-level with a focus on the land-use. We apply the method to Hungary (macro evaluation) and to a district of the capital city, Budapest (micro evaluation). It is found that charging stations at P + R facilities, close to concentrated services and high-density areas are better suited to serve urban public charging demand than gas stations. [ABSTRACT FROM AUTHOR]

The paper provides an approach to the assessment of the validity of decisions made for complex systems using multicriteria methods. It is also proposed to evaluate the validity based on the relevant criterion, which involves not only assessment of the results obtained by the multicriteria methods but also preliminary stages related to preparation of the initial data. [ABSTRACT FROM AUTHOR]

Electricity generation via renewable sources is emerging as a possible solution to meet the growing demand for electricity worldwide. Additionally, the need to produce clean energy, with little or no pollutants or greenhouse gas emission is paramount. Due to these factors, wind farms are noticeably increasing in number, especially in Brazil. However, the vast size of the country and the poor quality of its infrastructure are among several factors that make it difficult for effective decision-making to accelerate the growth of this segment in Brazil. With the purpose of assisting government agencies, regulatory agencies and other institutions in this area, the use of a multi-criteria selection method called the analytic hierarchy process is proposed here to assist in decision-making and to select priority regions for implementing wind farms. This work focuses on a case study of the state of Bahia, in which 27 territories were selected for an installation priority evaluation. Computational tools were used to hierarchize these chosen territories, including Matlab, for the construction of the computational algorithm. The results indicate the priority pf the regions according to the established criteria, which allows installation locations to be mapped—these could serve as a basis for regional investment.

The authors provide an approach to multicriteria decision making in the analysis of complex systems. It is based on the results obtained from a number of methods (ranking as well as forming of the kernel), which increases the substantiation of the results due to increasing the completeness of alternatives comparison. [ABSTRACT FROM AUTHOR]

In the last decades, 3D models have known a significant expansion, as we can see them in many fields such as computer vision, biology, augmented reality, engineering, and even medicine. They become more and more popular and accessible than ever. Due to these facts, there is an increasing need for a retrieval system, which can return the most similar 3D objects existing in the database to the query. In the present paper, a new retrieval approach is proposed, based on a multi-criteria method to generate a compact descriptor, which represents a signature for each 3D model. The key idea behind this approach is to try to extract the best out of each criterion (i.e., measure) by extracting a combined score using the Data envelopment analysis method (DEA). The results of the proposed method are very satisfactory and outperform some commonly used retrieval methods which highlight the potential and the performance of our approach. [ABSTRACT FROM AUTHOR]

A suite of models is proposed for estimating the risk of pesticides against the grey partridge (Perdix perdix) and their clutches. Radio-tracked data of females, description and location of the clutches, and data on the pesticide treatments during the laying periods of the partridges were used as basic information. Quantitative structure–activity relationship (QSAR) and quantitative structure–property relationship (QSPR) modelling allowed us to characterize the pesticides by their 1-octanol/water partition coefficient (logP), vapour pressure, primary and ultimate biodegradation potential, acute toxicity (LD50) onP. perdix, and endocrine disruption potential. From these physicochemical and toxicological data, the system of integration of risk with interaction of scores (SIRIS) method was used to design scores of risk for pesticides, alone or in mixture. A program, written in R (version 3.1.1), called Simulation of Toxicity inPerdix perdix(SimToxPP), was designed for estimating the risk of substances, considered alone or in mixture, against the grey partridge during breeding. The software tool is flexible enough to simulate realistic in situ scenarios. Different examples of applications are shown. The advantages and limitations of the approach are briefly discussed. [ABSTRACT FROM PUBLISHER]