An Evaluation Model of Quantitative and Qualitative Fuzzy Multi-Criteria Decision-Making Approach for Location Selection of Transshipment Ports

The role of container logistics centre as home bases for merchandise transportation has become increasingly important. The container carriers need to select a suitable centre location of transshipment port to meet the requirements of container shipping logistics. In the light of this, the main purpose of this paper is to develop a fuzzy multi-criteria decision-making (MCDM) model to evaluate the best selection of transshipment ports for container carriers. At first, some concepts and methods used to develop the proposed model are briefly introduced. The performance values of quantitative and qualitative subcriteria are discussed to evaluate the fuzzy ratings. Then, the ideal and anti-ideal concepts and the modified distance measure method are used in the proposed model. Finally, a step-by-step example is illustrated to study the computational process of the quantitative and qualitative fuzzy MCDM model. The proposed approach has successfully accomplished our goal. In addition, the proposed fuzzy MCDM model can be empirically employed to select the best location of transshipment port for container carriers in the future study

Enhancing Stock Movement Prediction with Adversarial Training

This paper contributes a new machine learning solution for stock movement prediction, which aims to predict whether the price of a stock will be up or down in the near future. The key novelty is that we propose to employ adversarial training to improve the generalization of a neural network prediction model. The rationality of adversarial training here is that the input features to stock prediction are typically based on stock price, which is essentially a stochastic variable and continuously changed with time by nature. As such, normal training with static price-based features (e.g. the close price) can easily overfit the data, being insufficient to obtain reliable models. To address this problem, we propose to add perturbations to simulate the stochasticity of price variable, and train the model to work well under small yet intentional perturbations. Extensive experiments on two real-world stock data show that our method outperforms the state-of-the-art solution with 3.11% relative improvements on average w.r.t. accuracy, validating the usefulness of adversarial training for stock prediction task.Comment: IJCAI 201

Critical factors influencing customer value for global shipping carrier-based logistics service providers using Fuzzy AHP approach

The key purpose of this research is to apply Fuzzy analytic hierarchy process (AHP) approach to empirically study the critical factors influencing customer value for global shipping carrier-based logistics service providers based upon the customers' perspective. To facilitate the main issue for obtaining critical factors, the four key value metrics -service, quality, cost, and cycle time -are employed to derive those initially important factors firstly. These factors have been discussed and publicized in academic and management fields and can be summarized as four aspects and seventeen initially factors. Subsequently, the proposed Fuzzy AHP approach is used to measure relative weights for evaluating these factors. Finally, the systematic appraisal approach is to perform the empirical survey via AHP questionnaires. The results of this study show that: (1) quality is the highest aspect for customer value from the customers' perspective in Taiwan, and the time is the lowest one; and (2) the top four critical factors influencing customer value are reasonableness of price, related direct costs, safety, and customer satisfaction, respectively

A FUZZY EVALUATION MODEL OF CHOOSING A MIDDLE MANAGER FOR AN INTERNATIONAL SHIPPING SERVICE PROVIDER

Choosing a middle manager with management competency and capabilities will have a decisive influence on the organization\u27s development for international shipping service providers. There is ambiguity and uncertainty in the decision-making environment during the selection of a middle manager and many evaluation criteria must be considered. The main purpose of this article is to construct a fuzzy multiple criteria decision-making (MCDM) model for international shipping service providers to use when selecting a middle manager. First, some methods and concepts of the fuzzy theory are introduced in this article. Five steps of evaluation model of fuzzy MCDM algorithms are then proposed to choose a best middle manager. Finally, an international shipping case is presented and the proposed fuzzy MCDM model is illustrated step by step. It can be seen from the demonstration that this evaluation model can be used to effectively select the best middle manager

Distribution shift mitigation at test time with performance guarantees

Due to inappropriate sample selection and limited training data, a distribution shift often exists between the training and test sets. This shift can adversely affect the test performance of Graph Neural Networks (GNNs). Existing approaches mitigate this issue by either enhancing the robustness of GNNs to distribution shift or reducing the shift itself. However, both approaches necessitate retraining the model, which becomes unfeasible when the model structure and parameters are inaccessible. To address this challenge, we propose FR-GNN, a general framework for GNNs to conduct feature reconstruction. FRGNN constructs a mapping relationship between the output and input of a well-trained GNN to obtain class representative embeddings and then uses these embeddings to reconstruct the features of labeled nodes. These reconstructed features are then incorporated into the message passing mechanism of GNNs to influence the predictions of unlabeled nodes at test time. Notably, the reconstructed node features can be directly utilized for testing the well-trained model, effectively reducing the distribution shift and leading to improved test performance. This remarkable achievement is attained without any modifications to the model structure or parameters. We provide theoretical guarantees for the effectiveness of our framework. Furthermore, we conduct comprehensive experiments on various public datasets. The experimental results demonstrate the superior performance of FRGNN in comparison to mainstream methods

Use of the AHP Method to Evaluate Key Inventory Control Indicators: Case Study of a Taiwanese Manufacturer in China

Control of inventory is a crucial management task that can affect a company\u27s success and survival, and good inventory control offers many benefits. In this paper, the Analytic Hierarchy Process (AHP) method is used to investigate key inventory indicators at a manufacturer and obtained an initial set of factors influencing inventory control, including five major assessment dimensions and 15 assessment criteria. "Rolling customer demand forecast accuracy" was a key assessment dimension that can be used to evaluate the case company\u27s inventory. The five most important key inventory control indicators consisted of "forecasting accuracy," "purchases in China," "production, sale, and inventory (PSI) meeting," "skilled worker turnover rate," and "major changes in market demand." In addition, these key indicators are discussed and some practical recommendations are made

Ultrastructure and Topochemistry of Plant Cell Wall by Transmission Electron Microscopy

Plant cell walls are typically described as complex macromolecular composites consisting of an ordered array of cellulose microfibrils embedded in a matrix of non-cellulosic polysaccharides and lignin. Generally, the plant cell wall can be divided into three major layers: middle lamella, primary cell wall, and secondary cell wall. Investigation of plant cell walls is complicated by the heterogeneous and complex hierarchical structure, as well as variable chemical composition between different sub-layers. Thus, a complete understanding of the ultrastructure of plant cell walls is necessary. Transmission electron microscopy (TEM) has proven to be a powerful tool in elucidating fine details of plant cell walls at nanoscale. The present chapter describes the layering structure and topochemistry of plant cell wall revealed by TEM

Model studies of THz-range generation by down-conversion in GaSe and GaSeS crystals

Model study of not phase matched and phase matched optical rectification or down-conversion of Ti:Sapphire laser pulses at 950 nm into THz and far-IRrange in pure and S-doped GaSe single crystals is carried out. First, the ordinary and extraordinary wave dispersions of the GaSe refractive indices were measured by terahertz time-domain spectroscopy (THz-TDS). Measured data were approximated in the form of Sellmeier dispersion equations for 0.62 - 2000 [mu]m range with using available shorter wave data

基于Scopus的植物表型组学研究进展分析

Bibliometric analyses are capable of demonstrating the history and the tendency of scientific and technological development. This article aims to use big scientific data to explore the present status of plant phenomics, based on which sound recommendations could be provided for the development of this emerging research domain. [Methods] Based on academic outputs such as research publications, citations, collaborations, research areas, academic organizations, and authors retrieved from the Scopus database between 2013 and September 2018, statistical analysis tools such as SciVal and CiteSpace 5.0 were applied to quantitatively visualize the development and tendency of plant phenotyping, plant phenomics, and related research areas. [Results] This Scopus-based research has retrieved 20 953 articles that are related to plant phenotyping, plant phenomics, and related applications in plant research, with a total citation of 217 105 and 2.0% of them are TOP1% highly cited papers. According to total citations, the TOP10 countries are the United States, China, Germany, the United Kingdom, France, Japan, Australia, Spain, Canada, and the Netherlands. The TOP10 research organizations based on total citations are Chinese Academy of Sciences (CAS), Institut National de la Recherche Agronomique (INRA), the US Department of Agriculture, Centre National de la Recherche Scientifique (CNRS), Chinese Academy of Agricultural Sciences, Cornell University, Spanish National Research Council, University of California at Davis, Universite Paris-Sacly, and Wageningen University & Research. The scholar with the most academic outputs is Alisdair Robert Fernie at the Koch Planck Institute of Molecular Plant Physiology, Germany. He has published 58 papers using plant cellular phenotypes and was cited 1 246 times. At present, plant phenomics research has focused on a number of plant species, including Arabidopsis, rice, wheat, corn, tomato and soybean. [Conclusion] As an emerging research domain, plant phenomics requires interdisciplinary efforts to integrate agriculture, cultivation, breeding, and other plant biological research with computing sciences. In particular, high-throughput image analysis and related data analysis has become an important research theme at the present stage, with the topical saliency index reaches 98.8%, a very high relevance score

Using Fuzzy AHP Method to Evaluate Key Competency and Capabilities of Selecting Middle Managers for Global Shipping Logistics Service Providers

The main purpose of this article is to use the fuzzy analytic hierarchy process (AHP) method to empirically study the key competency and capabilities affecting the selection of middle managers for global shipping logistics service providers (GSLSPs). To facilitate this theme for obtaining key competency and capabilities, a list of five management competency with twenty-five capabilities are preliminary summarized. Subsequently, the proposed fuzzy AHP method is applied to measure relative weights for evaluating these competency and capabilities. The appraisal approach is then to perform empirical survey via AHP expert questionnaires. Finally, the empirical results show that: (1) ‘professional competency’ is the most important management competency affecting the selection of middle managers for GSLSPs. (2) In order of relative importance, the top six key management capabilities affecting the selection of middle managers for GSLSPs are the ‘capability to manage work pressure,’ ‘capability to manage crisis,’ ‘capability to lead team awareness,’ ‘capability to manage interpersonal networks perfectly,’ ‘capability to use logistics expertise to enhance work efficiency,’ and ‘capability to effectively build team spirit and work atmosphere,’ respectively. Furthermore, concluding remarks are provided in this article