Machine vision systems are among the novel tools proven to be useful in different applications, among which monitoring and controlling manufacturing processes is one of the most important ones. However, due to the complexity resulted from high-dimensional image data and their inherent correlations, the acquisition of traditional statistical process control tools seems inapplicable. To overcome the shortcomings of the traditional methods in this regard, a statistical model is proposed in this paper which utilizes the concepts of both the PCA-based T2 control chart and the classification methods to develop a tool capable of controlling an image-based process. By defining the warning zones, collected data taken from an image-based process are classified into more than the two classes related to in-control and out-of-control processes. This helps practitioners to define rules to make it easier to realize when the process is getting out of control. Through simulation, the accuracy performance and the speed of four different types of classifiers including linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), kth nearest neighbors (KNN), and support vector machine (SVM) are assessed in different scenarios, based on which the functionality of the proposed approach is evaluated in in-control and out-of-control conditions.

Multi-criteria decision making (MCDM) methods are systematical science projects to help decision-makers reach accurate decisions. Applying MCDM methods in the military is important because accurate decision making is the deciding factor for success and can reduce expenditure and increase defense capability. The full consistency method (FUCOM), one of the methods in the MCDM group, has many advantages, and its results are reliable. This paper aims to evaluate and select an appropriate fighter aircraft for Vietnam People’s Air Force. Using FUCOM as a decision-making process, we find the final weight values of criteria and apply the additive ratio assessment (ARAS) method to derive the final ranking of alternatives to comply with criteria. Sensitivity analysis is conducted and the result is compared with the weighted product method to substantiate the sturdiness of the proposed method. The results show the Su-35 as the best available solution.

The objective of this paper is to examine the determinants of the supplier selection process with green consideration. Thus, this analysis gathers a collection of factors from established literature of green supplier selection (GSS), including seven categories and 58 attributes. The objective of this research is to classify the key factors which are presented as qualitative information. Fuzzy logic rules are used to transform qualitative expert knowledge into numerical data. Then, we adopt the Delphi method (DM) to filter and rate unneeded factors according to their relevance. The results indicate 24 important factors for the GSS process. Five categories are included: Performance and technology ability, Environmental management, Pollution control, Quality and Service. The most significant factors are recognized as green research and development, eco-design, green image, green packaging and remanufacturing. Finally, the debate is held on the basis of the findings and future research are also recognized and stated.

The agricultural sector is directly affected by climate variables. The presence of climate variability causes a considerable risk to agricultural productivities. Thus, risk management is an alternative to reduce risks, including optimizing the allocation of farmland and choosing crop insurance for a specific planting date. The purpose of this study is to investigate the agricultural risk management through risk measure of climate variability using the Conditional Value-at-Risk (CVaR) in rice production. This paper investigated several possible considerations of agricultural insurance premiums based on losses climate index. We concluded that the climate index insurance policy is the best choice that farmers can choose for each planting date, the higher the significance value considered, the more the value of Value-at-Risk and Conditional Value-at-Risk.

The ranking of decision-making units (DMUs) is one of the main issues in data envelopment analysis (DEA). Hence, many different ranking models have been proposed. However, each of these ranking models may produce different ranking results for similar problems. Therefore, it is wise to try different ranking models and aggregate the results of each ranking model that provides more reliable results in solving the ranking problems. In this paper, a novel ranking method (Aggregating the results of aggressive and benevolent models) based on the CRITIC method is proposed. To prove the applicability of the proposed ranking method, it is examined in three numerical examples, six nursing homes, fourteen international passenger airlines and seven biomass materials for processing into fuel briquettes. First, benevolent and aggressive models were used to calculate the efficiency rating for each DMU. As a result, the decision matrix was generated. In the decision matrix, the results of benevolent and aggressive models were viewed as criteria and DMUs were viewed as alternatives. Then, the weights of each criterion were generated by the CRITIC method. Finally, each DMU was ranked. In a comparative analysis, the proposed method can lead to achieving a more reliable decision than the method which is based on a stand-alone method.

The objective of this research was to examine the relationships of the five key foreign tourist markets in the Greater Mekong Sub-region (GMS), Cambodia, Laos, Myanmar, Thailand, and Vietnam. Quarterly data of tourist numbers from China, Japan, Korea, Malaysia, and the USA who traveled to the countries in GMS during the period 2001-2017 were used. Vector Autoregressive (VARs) was used to test Granger Causality to explain the relationships among tourist markets in the region. The findings revealed that tourist markets in Cambodia had forward relations with Laos and Vietnam. Those in Laos had forward relationship with Myanmar and Thailand. Tourist markets in Myanmar had forward relationship with Vietnam, Laos, and Thailand. Tourist markets in Thailand had forward relationship with Vietnam, Laos, and Myanmar whereas those of Vietnam had forward relationship with Laos, Myanmar, Thailand, and Cambodia. The overview shows that the key tourist markets in each country supported each other.

Evaluation of the software usability as concerns software alternatives represents a typical Multi-Criteria Decision-Analysis (MCDA) problem. Such a kind of problem can be successfully faced via structured models and approaches which validity have been widely shown in literature. In this work, a methodological framework based on a MCDA model integrating the DEMATEL method along with the ANP technique is proposed and explained with more detail to address the relevant issue of the software usability evaluation. The applicability of the considered DEMATEL-ANP (DANP) based model in the under analysis contest is demonstrated via a preliminary investigation, where the usability of the two major Mobile Operating Systems (MOSs) is compared and quantitatively prioritized. Results of both performed comparison method and sensitivity analysis confirm the validity of the proposed MCDA model as well robustness of its outcomes. Moreover, results obtained point out about the influenced, independent and core factors for the MOSs usability, as well as strengths, weaknesses and discrepancies in the usability as concerns the two investigated alternatives. Representing these outcomes crucial aspects for driving focused MOSs usability improvement processes and strategies, they give also evidence of the effectiveness of the proposed methodological framework.

Agri-food supply chains have received the attention of many researchers in recent years for various reasons, including food security and health-related issues. Wheat, as a staple food in many countries, is the most cultivated crop in the world. Due to the importance of wheat, this paper proposes a mixed-integer linear mathematical model for redesigning and planning of the wheat supply chain. The proposed model determines the location and capacity of new storage facilities while addressing supplier selection, ordering, storing, transportation, and distribution problems. This model considers the differences between long-term and short-term storage facilities and the quality of wheat. Moreover, the proposed model addresses the uncertainties associated with the quantity of domestic supply and demand through a stochastic scenario-based programming approach. Applicability of this model is investigated using real data from the wheat supply chain of Iran. Results show that seven new long-term storage facilities should be opened, which decreases total costs by 3.45 percent.

Community detection has gained much attention during the past few decades. So many algorithms have been developed to tackle this problem. In previous related works the weight of the edges and directionality were not considered at the same time in the models. Considering weights and directionality makes the models more realistic and prevents the loss of information in the network. In this article, we propose an overlapping community detection algorithm for networks with weighted and directed edges. We used the concept of information flows among the vertices i.e. the more flows exist in a community, the stronger the community. We implemented the concept of flow using weighted closed flows starting from a given node and ending to the same node. By using the mentioned assumption we developed a new modularity measure called weighted flow modularity (WFM) based on M function modularity. In addition, we developed an overlapping score criteria which considers overlap in vertices and edges at the same time and is much faster in the terms of run time. We compared the community detection results in terms of accuracy and running time with Order statistics local optimization method (OSLOM) on 74 LFR benchmark networks using normalized mutual information score. We also implemented the community detection process using LCFE on real world datasets and evaluated the community detection results using EQ measure. The experimental analysis results show that the LCFE is more accurate in most cases and is competitive in other cases with OSLOM.

This paper deals with retrial queues of the |MQ/M/c/∞|- type in which the rate of input flow depends on the number of sources of repeated calls and each call has only one retrial attempt. That is, if a call fails to enter the server facility at the retrial attempt, then it leaves the system without service. The existence conditions of stationary regime and the vector-matrix of the stationary probabilities of the service process are represented. This representation uses an approximation of the initial model by means of the truncated one and the directs passage to the limit. For these systems a threshold strategy for the rate of input flow is used. The multi-criterion optimization problem for finding optimal strategy of control is considered. The quality functionals of the optimization problem are represented through the stationary probabilities.