Feasibility study of large-scale mass customization 3D printing framework system with a case study on Nanjing Happy Valley East Gate

At present, the development and implementation of digital transformation are the keys to promoting high-quality industry development. The new digital fabrication method of robotic 3D printing is a research area being studied by many to tackle the issue of the declining productivity of traditional construction methods. Although many studies have been done, most of the current 3D printing projects are facing limitations in terms of scale. In order to bridge the gap, this article proposed a mass customization 3D printing framework system for large-scale projects. This article discusses how mass customization is made possible through the joint operation of the FUROBOT software and 3D printing hardware. By taking the east gate of Nanjing Happy Valley Plaza as a case study, the article demonstrates and studies the feasibility of the large-scale mass customization 3D printing framework system.     

航空工业中的锻压技术及其发展

本文论述了锻压技术在航空工业中的重要作用及其发展；指出了目前应重点发展等温模锻技术、大型锻件的模锻技术、大型风扇叶片的成形及连接技术、锻压过程的物理模拟试验技术和钛合金叶片精锻技术的推广应用等。     

Evolving Least Squares Support Vector Machines for Stock Market Trend Mining

In this paper, an evolving least squares support vector machine (LSSVM) learning paradigm with a mixed kernel is proposed to explore stock market trends. In the proposed learning paradigm, a genetic algorithm (GA), one of the most popular evolutionary algorithms (EAs), is first used to select input features for LSSVM learning, i.e., evolution of input features. Then, another GA is used for parameters optimization of LSSVM, i.e., evolution of algorithmic parameters. Finally, the evolving LSSVM learning paradigm with best feature subset, optimal parameters, and a mixed kernel is used to predict stock market movement direction in terms of historical data series. For illustration and evaluation purposes, three important stock indices, S&P 500 Index, Dow Jones Industrial Average (DJIA) Index, and New York Stock Exchange (NYSE) Index, are used as testing targets. Experimental results obtained reveal that the proposed evolving LSSVM can produce some forecasting models that are easier to be interpreted by using a small number of predictive features and are more efficient than other parameter optimization methods. Furthermore, the produced forecasting model can significantly outperform other forecasting models listed in this paper in terms of the hit ratio. These findings imply that the proposed evolving LSSVM learning paradigm can be used as a promising approach to stock market tendency exploration.     

Credit scoring using support vector machines with direct search for parameters selection

Support vector machines (SVM) is an effective tool for building good credit scoring models. However, the performance of the model depends on its parameters’ setting. In this study, we use direct search method to optimize the SVM-based credit scoring model and compare it with other three parameters optimization methods, such as grid search, method based on design of experiment (DOE) and genetic algorithm (GA). Two real-world credit datasets are selected to demonstrate the effectiveness and feasibility of the method. The results show that the direct search method can find the effective model with high classification accuracy and good robustness and keep less dependency on the initial search space or point setting.     

The Role of Organizational Vision in Guiding Idea Generation within SME Contexts

New ideas are required if our organizations are going to survive and grow. Without the ability to think differently, firms can quickly stagnate and decline. A key contributor to the success (or otherwise) of the ideation process is the extent to which organizations provide effective control mechanisms, with existing literature drawing tentative links between this and the subject of organizational vision. The aim of this paper is to explore the control of idea generation in SME contexts, examining the interaction between organizational vision and the guidance of ideation in these settings. Through in‐depth qualitative research with a range of SMEs, this study shows that structure in the form of an outlining framework assists in opening a liminal space for ideation. More importantly, this paper provides empirical evidence, which demonstrates that organizational visions provide this framework by acting as a target, assisting the development of relevant ideas. Ideation, within the SME, is argued to be fundamentally subject to, and contingent upon, the direction of the organization.     

Modeling the customer satisfaction function: a two-country comparison

This paper provides a framework that integrates and reinterprets prior research on satisfaction modeling (function) and proposes the existence of non-linear and curvilinear/higher-order relationships to model online banking customers. It provides a framework that examines two closely related but distinct countries—Malaysia, a developing country, and Singapore, a developed country—and identifies whether modeling online banking customers through satisfaction is unique to each context or is generic. Using a systematic and step-by-step hierarchical moderated regression approach, this study tries to understand the relationship among repurchase intention, satisfaction, and trust, moderated by bank size. Malaysia portrays a linear relationship, while Singapore depicts non-linear and curvilinear/high-order relationships. The findings suggest that modeling online banking customers through satisfaction depends on a country’s economic development. By contrast, prior studies on modeling customers through satisfaction were conducted independently and did not employ proper and systematic steps to capture the satisfaction function.     

Application of genetic algorithm for fuzzy rules optimization on semi expert judgment automation using Pittsburg approach

Genetic algorithm is well-known of its best heuristic search method. Fuzzy logic unveils the advantage of interpretability. Genetic fuzzy system exploits potential of optimization with ease of understanding that facilitates rules optimization. This paper presents the optimization of fourteen fuzzy rules for semi expert judgment automation of early activity based duration estimation in software project management. The goal of the optimization is to reduce linguistic terms complexity and improve estimation accuracy of the fuzzy rule set while at the same time maintaining a similar degree of interpretability. The optimized numbers of linguistic terms in fuzzy rules by 27.76% using simplistic binary encoding mechanism managed to improve accuracy by 14.29% and reduce optimization execution time by 6.95% without compromising on interpretability in addition to promote improvement of knowledge base in fuzzy rule based systems.     

碳酸镉转化制备氢氧化镉及产物光催化降解性

用碳酸钠溶液直接混合硫酸镉溶液制备了沉淀碳酸镉,再以沉淀碳酸镉为基体,氢氧化钠溶液为转化剂,通过阴离子交换制备出氢氧化镉纳米材料。采用X射线衍射仪（XRD）和场发射扫描电子显微镜（FESEM）对沉淀碳酸镉和转化产物的结构和形貌进行了表征。结果表明,沉淀碳酸镉的结构遭到破坏,转化完全所得到的氢氧化镉的形貌完全不同于沉淀碳酸镉,为片状组装的不规则球体。紫外光照射下光催化降解罗丹明B染料测试表明,转化产物比沉淀碳酸镉具有更好的光催化降解性能,转化时间不同的产物表现出不同的降解效率。当20 mg的转化产物分散到50 mL 8 mg/L的罗丹明B染料中,在黑暗环境中磁力搅拌吸附120 min达吸附平衡,开启300 W紫外汞灯后,效率最高的转化产物可在180 min内将染料完全降解。     

Abiotic methylation of mercury in the aquatic environment

Methylation of inorganic mercury in the aquatic environment has been considered to be largely the result of biological processes, primarily involving sulfate-reducing bacteria. However, these processes cannot account for all of the methylmercury that is formed naturally. A growing body of evidence suggests that chemical reactions represent another possible pathway for mercury methylation in the aquatic environment. In order to assess the abiotic contribution to mercury methylation in the water column, and specifically the conditions under which this contribution may be significant, the current state of knowledge about environmentally significant methylation reactions is reviewed. Results of our laboratory-based investigations of aqueous mercury reactions with some potential methyl donors, including MeCo(dmg)(2)(H2O), a simple model for methylcobalamin, various methyltin compounds and methyl iodide, are presented. In each reaction, the yield of methylmercury and the rate of methylation depend strongly on environmental factors such as pH, temperature, and the presence of complexing agents, especially chloride.