基于推理注意力机制的二阶段网络图像修复

现有的图像修复方法在处理大面积缺失或高度纹理化的图像时，通常会产生扭曲的结构或与周围区域不一致的模糊纹理，无法重建合理的图像结构。为此，提出了一种基于推理注意力机制的二阶段网络图像修复方法。首先通过边缘生成网络生成合理的幻觉边缘信息，然后在图像补全网络完成图像的重建工作。为了进一步生成视觉效果更逼真的图像，提高图像修复的精确度，在图像补全网络采用推理注意力机制，有效控制了生成特征的不一致性，从而生成更有效的信息。所提方法在多个数据集上进行了实验验证，结果表明该图像修复方法的结构相似性指数达到了88.9%，峰值信噪比达到了25.56 dB，与现有的图像修复方法相比，该方法具有更高的图像修复精确度，生成的图像更逼真。     

Extending social responsibility to small and medium-sized suppliers in supply chains: A fuzzy-set qualitative comparative analysis

Buying firms’ sales and reputation will be greatly damaged by any non-responsible behaviors on the part of suppliers, especially when those suppliers, like small and medium-sized enterprises (SMEs), have restricted resources and capabilities. To eradicate these risks, a growing number of buying firms have introduced socially responsible supplier development (SRSD). SRSD, including monitoring and evaluating suppliers, can provide them with incentives and assistance. Based on configuration theory and contingency theory, fuzzy-set qualitative comparative analysis (fsQCA) is adopted in this study to examine how SRSD practices adopted by buying firms, supply chain partnership, and market turbulence affect the corporate social responsibility (CSR) performance of their SME suppliers. We find that, as core factors, supplier monitoring, supplier assistance, and supply chain partnership can work together with peripheral conditions to achieve superior CSR performance. In addition, even at different levels of market turbulence, superior CSR performance can be realized through different causal configurations.     

An e-government framework for assessing readiness for public sector e-procurement in a lower-middle income country

ABSTRACT

Governments globally are leveraging information and communication technology (ICT) growth towards improving the quality of public procurement services for socio-economic development. However, the extent of its application differs across nations. Notwithstanding the extant theoretical and empirical literature on IT for development, knowledge on how to assess readiness for adopting a full e-procurement system in the public sector of lower and lower-middle income countries (LMICs) begs for understanding. With the narrative of Ghana, we address this gap by drawing on the institutional and economic theory and the United Nations E-Government Development Index towards a holistic framework beyond the dyad of linear website functionalities and internet focus of prior e-government adoption models. Elite interviews gathered from multiple cases from Ghana’s public sector reveals the key readiness determinants for a full public sector e-procurement system. This study has significant implications for shaping the process-oriented management of government e-procurement projects towards socio-economic development in LMICs amid their complex institutional and socio-technical environments.     

借鉴逻辑学方法提高临床思维能力

目的：正确的临床决策必须遵循逻辑规律。本文旨在剖析用逻辑学方法提高临床思维训练的可行性。方法：进行临床医学和逻辑学的跨学科整合研究，重点探讨三类常用逻辑方法：演绎法、归纳法和溯因推理法在临床实践中的应用。 结果：发现演绎、溯因和归纳推理分别对应于：①评估临床资料；②提出诊断假设和③完善初步诊断这三种临床思维活动。发现并概括临床思维和医疗实践中包含的逻辑规律，有助于提高思维的准确性、有效性和清晰性。结论：掌握临床思维的逻辑规律，并在中针对性地加以应用，有助于培养医生的思维和决策能力。     

基于改进的Random Subspace的客户投诉分类方法

电信业的客户投诉不断增多而又亟待高效处理。针对电信客户投诉数据的特点，提出了一种面向高维数据的改进的集成学习分类方法。该方法综合考虑客户投诉中的文本信息及客户通讯状态信息，基于Random Subspace方法，以支持向量机（Support Vector Machine，SVM）为基分类器，采用证据推理（Evidential Reasoning，ER）规则为一种新的集成策略，构造分类模型对电信客户投诉进行分类。所提模型和方法在某电信公司客户投诉数据上进行了验证，实验结果显示该方法能够显著提高客户投诉分类的准确率和投诉处理效率。     

Veterinarian perceptions on the care of surplus dairy calves

Both male and female calves that are not required in the dairy herd sometimes receive inadequate care on dairy farms. Veterinarians work with farmers to improve animal care, and farmers often view veterinarians as trusted advisors; however, little is known about the attitudes of veterinarians on surplus calves. This study investigated the perspectives of Canadian cattle veterinarians on the care and management of surplus calves, as well as how they view their role in improving care. We conducted 10 focus groups with a total of 45 veterinarians from 8 provinces across Canada. Recorded audio files were transcribed, anonymized, and coded using thematic analysis. We found that veterinarians approached surplus calf management issues from a wide lens, with 2 major themes emerging: (1) problematic aspects of surplus calf management, including colostrum management, transportation, and euthanasia, and suggested management and structural solutions, including ways to improve the economic value of these calves, and (2) the veterinarian's role in advising dairy farmers on the care of surplus calves, including on technical issues, and more broadly working with farmers to better address public concerns. We conclude that veterinarians are concerned about the care of surplus calves on dairy farms and believe that they have an important role in developing solutions together with their farmer clientele.     

Short term stock selection with case-based reasoning technique

Stock selection is an important decision making problem. Trading strategies and rules based on fundamental and technical analysis can be used for decision making process. In this paper, we propose an intelligent stock selection method, which is called case-based reasoning (CBR). This technique uses the fundamental and technical indicators to identify the winning stocks around the earning announcements. CBR method is compared with other artificial intelligence techniques such as multi layer perceptron (MLP), decision trees (QUEST, Classification and Regression Trees, C5), generalized rule induction (GRI) and logistic regression. We show that the performance of CBR is better than the performance of other techniques in terms of classification accuracy, average return, Sharpe ratio and ideal profit.