Mathematical model of delay in the secondary literature publishing process

In this paper, the internal law of delay in the secondary literature publishing process is presented. The process is demonstrated to abide by the partial differential equation of periodical literature publishing process. A definite solution of the publishing delay process is derived. Accordingly, the expression of average publication delay indicator based on the particular solution is deduced. Then the problem is studied that some information of primary literatures is missed in information retrieval, and the relationship is established between the average delay indicator and the miss ratio of primary literatures in the index periodicals or databases. Also it is proposed that the primary literature should be used as a supplemental tool in information retrieval to guarantee the recall ratio. This revised version was published online in June 2006 with corrections to the Cover Date.     

Centrifugal atomization of stainless-steel rotating rods melted by a high-power LASER beam

316L grade stainless steel powders were produced by centrifugal atomization during the melting of a rotating rod heated by a high-power LASER beam. The feasibility has been demonstrated by atomizing a range of stainless steel rods. The atomization process has been observed via high-speed imaging and fragmentation regimes have been identified according to a literature review on the rotating electrode process (REP). Results were compared with literature data and an existing prediction model for such a process. High-speed observation can monitor the present process and it is shown that a solidified layer of metal is formed at the edge of the rod during the process inducing metal flake ejection due to the centrifugal stresses. Effects of incident LASER beam power density, ejection speed and oxygen content of the surrounding atmosphere on the particle size distribution and the sample surface have been studied and compared with literature data on classical REP atomizers. The study focuses on the production of irregular particles during the atomization process and highlights the influence of the oxygen content in the surrounding atmosphere on the fragmentation regime and the resulting particle size distribution.     

Drivers and consequences of green product and process innovation: A systematic review,conceptual framework,and future outlook

Drawing clear conclusions from the literature on green innovation is challenging, due to its sheer breadth and the inconsistent insights it offers. This study systematically addresses this issue by conducting a systematic literature review of articles on innovation in green products and processes, with the aim of enhancing conceptual clarity and consistency, thus, advancing theory and research. This study reviewed 195 articles relating to both green product and process innovation published during 1991–2016. The articles were analyzed in terms of key attributes of green product and process innovation using content analysis. Based on the analysis, this study identifies the key drivers and consequences, mediators and moderators and develops a conceptual framework of green product and process innovation. It also discusses the limitations and main theories of green innovation literature, and articulates potential paths for future research.     

服务设计的一般性策略流程研究

目的在中国,服务设计尚处于萌芽阶段,服务设计的概念和一般流程还没有被人们广泛了解,因此,这是对服务设计的一般流程进行了梳理和分析,建构出服务设计的一般性策略流程。方法以桌面研究为基础,对相关文献和信息进行检索,通过案例分析进一步揭示服务设计策略流程的细节。结论对现有的服务设计的一般性策略流程进行分析,总结其相似性和差异性,指出其探索的方向,最后为服务设计的未来指明发展方向。     

Joint optimization in process target and tolerance limit for L -type quality characteristics

Most models reported in the current process target literature assume a nominal-the-best type quality characteristic in determining the optimal process mean value. In real-world industrial settings, however, a number of quality characteristics of interest are of a larger-the-better type (L-type), and the problem of jointly determining the optimum process mean and tolerance limit for the L-type quality characteristic may be of significant practical importance, yet this has largely been overlooked in the literature. In this paper, cost-effective optimization models are developed, and the methods of finding optimum solutions are presented. Numerical examples and sensitivity analysis are given.     

Support vector machines for recognizing shifts in correlated and other manufacturing processes

Traditional statistical process control (SPC) techniques of control charting are not applicable in many process industries where the data from the facilities are often autocorrelated. This is often true in piece-part manufacturing industries that are highly automated and integrated. Several attempts have been made in the literature to extend traditional SPC techniques to deal with autocorrelated parameters. However, these extensions pose several serious limitations. The literature discusses several machine-learning methods based on radial basis function (RBF) networks and multi-layer perceptron (MLP) networks to address the limitations, with some success. This paper demonstrates that support vector machines (SVMs) can be extremely effective in minimizing both Type-I errors (probability that the method would wrongly declare the process to be out of control or generate a false alarm) and Type-II errors (probability that the method will be unable to detect a true shift or trend present in the process) in these autocorrelated processes. Even while employing the simplest type of polynomial kernels, the SVMs were extremely good at detecting shifts in papermaking and viscosity datasets (available in the literature) and performed as well or better than traditional as well as machine learning methods. It was also observed that SVMs are good at minimizing both Type-I and Type-II errors even in monitoring non-correlated processes. When tested on datasets available in the literature, they once again performed as well or better than the classical Shewhart control charts and other machine learning methods.     

Wavelet-based multiscale statistical process monitoring: A literature review

Data that represent complex and multivariate processes are well known to be multiscale due to the variety of changes that could occur in a process with different localizations in time and frequency. Examples of changes may include mean shift, spikes, drifts and variance shifts all of which could occur in a process at different times and at different frequencies. Acoustic emission signals arising from machining, images representing MRI scans and musical audio signals are some examples that contain these changes and are not suited for single scale analysis. The recent literature contains several wavelet-decomposition-based multiscale process monitoring approaches including many real life process monitoring applications. These approaches are shown to be effective in handling different data types and, in concept, are likely to perform better than existing single scale approaches. There also exists a vast literature on the theory of wavelet decomposition and other statistical elements of multiscale monitoring methods, such as principal components analysis, denoising and charting. To our knowledge, no comprehensive review of the work relevant to multiscale monitoring of both univariate and multivariate processes has been presented to the literature. In this paper, over 150 both published and unpublished papers are cited for this important subject, and some extensions of the current research are also discussed.     

Process development: a theoretical framework

There have already been a number of review articles that focus on product development, but none on process development. Process development is technically difficult, time-critical and competitively important, thus worth being explored as a distinct unit of analysis. This paper develops a theoretical framework to fill this gap in knowledge based on a comprehensive literature review. Five objectives for process development are summarised to align with the goal of product realisation, and 12 enablers (including intra-functional enablers, inter-functional enablers, and learning enablers) are identified and discussed. The authors first locate process development in the product realisation process (including product design, process design, process execution and process improvement) and draw necessary parallel factors between product design and process design as a foundation. Then the attributes of all relevant literature are organised and general principles for successful performance of development projects are used to infer the enablers. The developed framework offers opportunities to further verify the new enablers and theoretical links in future studies. One implication is that process development should be viewed as a strategic function for competitive edge and as such specific measures should be set to create an environment that is conducive to successful performance.     

Identification of referencing and citation processes of scientific journals based on the citation distribution model

In this article, we firstly analyze the referencing process and the citation process of a scientific journal in theory, and find that the observed referencing or citation process includes the diffusing process and the aging process of cited literature and the publishing process of citing literature, thereby it is illuminated why the identified average publication delay ( [`(T)] = T_s + t ) \left( {\bar{T} = T_{s} + \tau } \right) was longer than the observed value. Secondly, we compare the transfer function model of the observed citing process with other classical citation distribution models and find that the model is superior to others. Finally, using the model, we identify parameters of actual referencing and citation processes from data of age distributions of references and citations of 38 journals of neurology and applied mathematics in JCR, respectively; and then compare differences of identified parameters and obtain some interesting conclusions.     

Stability and performance of a double MEWMA controller for drifted MIMO systems

Many semiconductor manufacturing processes have, by nature, Multiple-Input and Multiple-Output (MIMO) variables. For a drifted MIMO process, the double Multivariate Exponentially Weighted Moving Average (dMEWMA) controller is a popular run-to-run controller for adjusting the process mean to a desired target. The stability conditions of a dMEWMA controller have received considerable attention in the literature. There are two limitations in the existed literature. First, these approaches only demonstrate that the asymptotic mean will meet a desired target; however, they do not show that mean square error matrix for a process is bounded. Second, they do not have an explicit expression of the process output of the dMEWMA controller for any production run t. Hence, by using a conventional state space formulation, it is impossible to address the process performance (such as process fallout rate of the dMEWMA controller) analytically. Using a different approach, this paper derives an analytical expression for the process output of a dMEWMA controller. The problems of the stability conditions and the performance of the dMEWMA controller can then be addressed successfully.     

An objective-guided ortho-synapse Hopfield network approach to machine grouping problems

This paper reports an ortho-synapse Hopfield network (OSHN) for solving machine grouping problems. An objective-guided search scheme is proposed to lead the search process. The OSHN structure and the objective-guided search scheme have been implemented in an algorithm. Unlike the back propagation or A RT1 neural networks, the proposed approach does not require training process and is not affected by the initial arrangement of the machine-part incidence matrix. As compared with the original Hopfield neural network, the computational efficiency and the solution quality can be considerably improved due to the reduced synapses in the OSHN and the objective-guided search process. The performance of the proposed algorithm has been tested using 28 notable problems from the literature and compared favourably with the solutions obtained in the literature.     

标准大数据实践(2)——内容深度挖掘

大数据时代,人们面对的问题不再是缺少数据,而是被数据淹没了,即所谓"人们淹没于数据,却饥饿于知识"[1].面对这样的状况,仅靠传统的检索工具已经远远不能满足人们的需要.本文研究了标准文献内容挖掘的关键技术:OCR、正则提取、反向索引,以及标准文献碎片挖掘与检索的系统实现的业务流程、技术框架以及实现效果.     

Examining the role of green IT/IS innovation in collaborative enterprise-implications in an emerging economy

Sustainability is a significant field in both research and practice as such Collaborative Enterprise (CE) are adopting sustainable initiatives to achieve efficient resource usage, CO2 emissions reduction, energy utilization reduction, moderate cost incurred, ethical waste management and natural resources conservation. Therefore, this research develops a model based on diffusion of innovation theory and sustainable life cycle process identified through literature review after which survey method was employed. The survey questionnaire was distributed targeting IT practitioners and IT managers of CE based in Malaysia. With 133 valid questionnaires in hand, the collected data were analysed using Statistical Package for Social Science (SPSS). Results reveal that the internal and external characteristics influences enterprise sustainability innovativeness. Furthermore, results confirm the identified sustainable life cycle process derived from the literature. Findings from this study support policy makers in CE understand and develop process towards sustainability attainment. By applying the developed model, CE can strategize their current process towards improving the sustainability of their enterprise.     

等温淬火球铁等温转变过程与奥贝球铁生产的若干问题

本文介绍了等温淬火球铁（ＡＤＩ）和它的一个品种──奥贝球铁。通过对文献资料的综述和分析，简述了ＡＤＩ等温转变的过程和由此引发而来的生产高质量奥贝球铁时应注意的若干问题。     

Wavelet-based SPC procedure for complicated functional data

Functional data characterize the quality or reliability performance of many manufacturing processes. As can be seen in the literature, such data are informative in process monitoring and control for nanomachining, for ultra-thin semiconductor fabrication, and for antenna, steel-stamping, or chemical manufacturing processes. Many functional data in manufacturing applications show complicated transient patterns such as peaks representing important process characteristics. Wavelet transforms are popular in the computing and engineering fields for handling these types of complicated functional data. This article develops a wavelet-based statistical process control (SPC) procedure for detecting ‘out-of-control’ events that signal process abnormalities. Simulation-based evaluations of average run length indicate that our new procedure performs better than extensions from well-known methods in the literature. More importantly, unlike recent SPC research on linear profile data for monitoring global changes of data patterns, our methods focus on local changes in data segments. In contrast to most of the SPC procedures developed for detecting a known type of process change, our idea of updating the selected parameters adaptively can handle many types of process changes whether known or unknown. Finally, due to the data-reduction efficiency of wavelet thresholding, our procedure can deal effectively with large data sets.     

基于文献计量学的感性工学研究进展可视化分析

目的 为系统概括感性工学相关研究全局特征,进一步掌握当前感性工学研究进展,对相关文献研究热点、前沿趋势与理论基础等进行可视化分析。方法 以Web of Science核心合集数据库收录的感性工学相关文献数据作为样本,综合运用VOSviewer及CiteSpace软件对文献产出分布、作者、国家、合作机构、     

LRV: A Tool for Academic Text Visualization to Support the Literature Review Process

Text visualization is concerned with the representation of text in a graphical form to facilitate comprehension of large textual data. Its aim is to improve the ability to understand and utilize the wealth of text-based information available. An essential task in any scientific research is the study and review of previous works in the specified domain, a process that is referred to as the literature survey process. This process involves the identification of prior work and evaluating its relevance to the research question. With the enormous number of published studies available online in digital form, this becomes a cumbersome task for the researcher. This paper presents the design and implementation of a tool that aims to facilitate this process by identifying relevant work and suggesting clusters of articles by conceptual modeling, thus providing different options that enable the researcher to visualize a large number of articles in a graphical easy-to-analyze form. The tool helps the researcher in analyzing and synthesizing the literature and building a conceptual understanding of the designated research area. The evaluation of the tool shows that researchers have found it useful and that it supported the process of relevant work analysis given a specific research question, and 70% of the evaluators of the tool found it very useful.     

Optimum arrangement of gate and vent locations for RTM process design using a mesh distance-based approach

Resin transfer molding (RTM) is considered a promising manufacturing process for high performance composite materials. In the RTM process, gate/vent location is one of the most important variables in process design. It has a great impact on mold filling time and resin flow pattern, thus affects the process efficiency and product quality. Many studies have been conducted on optimization of RTM mold filling process to determine the locations of gates and vents. Most of them approached the optimum process design problem via numerical method-based process simulations. Due to the extensive computations involved, such approaches are difficult to be implemented for large and complex parts. This paper introduces a new approach to optimum arrangement of gates and vents for two-dimensional or two and a half-dimensional parts based on the mesh distance concept. With the assumption that the resin first fills the nodes closest to gates, the vent locations that minimize the area of trapped air can be determined. With the objective of minimizing the maximum distance between gates and vents and avoiding dry spot formation, genetic algorithm was employed to carry out the gate location optimization. The new RTM process design approach was tested on numerous cases obtained from the literature. It was found that the new approach was very efficient and effective in finding the optimal locations for gates and vents. The resulting gate and vent locations lead to satisfactory process performance as indicated by the optimal process performance index. The computational time required by the new approach was only a fraction of that reported by those simulation-based methods in the literature.     

Stability assessment with the stability index

Assessment of process stability is an important way to ensure high quality. There have been various approaches in the literature to assess process stability. We describe these methods and provide a minor modification of a previous approach, which we call the stability index (SI). We provide justification for the SI as a best practice for practitioners who assess process stability. We provide examples of the computation of the SI for various scenarios and show how the SI can be used in conjunction with capability indices in a process performance graph.     

基于文献计量学的情感化设计研究进展、热点与趋势分析

目的 系统认识国际范围内情感化设计研究的全局特征,把握当前情感化设计的研究热点及理论基础,并根据当前研究热点探究未来发展新趋势。方法 以Web of Science收录的情感化设计相关文献作为数据源,以科学文献计量的方法综合运用VOSviewer和CiteSpace从文献的年份产出分布、国家、研究机构、作者、参考文献共被引情况和关键词聚类等方面绘制科学知识图谱,进行可视化分析以梳理研究脉络。结论 结果表明检索范围内文献数量整体呈上升趋势,中美等国处于研究的领先地位,研究热点主要集中在情感计算、感性工学、人机多通道交互、用户体验和设计评估等方面。研究现状较为成熟,形成了以三层次理论、感性工学和情感计算为主的理论体系。用户个性化、差异化情绪的识别与表达成为未来发展的新趋势。研究机构与作者合作不紧密,以及高产量作者不多是现阶段研究的主要局限。