An Advanced Analysis of Cloud Computing Concepts Based on the Computer Science Ontology

Our primary research hypothesis stands on a simple idea: The evolution of top-rated publications on a particular theme depends heavily on the progress and maturity of related topics. And this even when there are no clear relations or some concepts appear to cease to exist and leave place for newer ones starting many years ago. We implemented our model based on Computer Science Ontology (CSO) and analyzed 44 years of publications. Then we derived the most important concepts related to Cloud Computing (CC) from the scientific collection offered by Clarivate Analytics. Our methodology includes data extraction using advanced web crawling techniques, data preparation, statistical data analysis, and graphical representations. We obtained related concepts after aggregating the scores using the Jaccard coefficient and CSO Ontology. Our article reveals the contribution of Cloud Computing topics in research papers in leading scientific journals and the relationships between the field of Cloud Computing and the interdependent subdivisions identified in the broader framework of Computer Science.     

CME Forum: a response to “Construction flow index: a metric of production flow quality in construction”

The study of types of flow in construction is a relatively new field. This paper reviews the work of Sacks et al. and reveals that they have applied a production-line metaphor with recognition of two production flows. Process flow: locations are equated with products moving down a production line. Operations flow: work crews are equated to work stations. Their work proposes an index of the quality of production flow in construction, but the research design has three significant flaws: the skilled interpretation of flow-line charts is not in turn applied to the interpretation of their example charts; the conceptual framework does recognize that the underlying metaphor requires levels of detail in both location and task that is not supported in their analysis. The meaning of “quality of flow” in this context is not defined. This debate raises important epistemological questions for those working in lean construction and location-based management. While the concept of “production flow quality” is important, the Sacks et al. methodology does not address the detailed planning of individual crews. It is only possible to apply the production-line metaphor if micro-management is adopted as detailed planning.     

BIM-to-IGA: A fully automatic design-through-analysis workflow for segmented tunnel linings

Both planning and design phase of large infrastructural project require analysis, modelling, visualization, and numerical analysis. To perform these tasks, different tools such as Building Information Modelling (BIM) and numerical analysis software are commonly employed. However, in current tunnel engineering practice, there are no systematic solutions for the exchange between design and analysis models, and these tasks usually involve manual and error-prone model generation, setup and update. In this paper, focussing on tunnelling engineering, we demonstrate a systematic and versatile approach to efficiently generate a tunnel design and analyse the lining in different practical scenarios. To this end, a BIM-based approach is developed, which connects a user-friendly industry-standard BIM software with effective simulation tools for high-performance computing. A fully automatized design-through-analysis workflow solution for segmented tunnel lining is developed based on a fully parametric design model and an isogeometric analysis software, connected through an interface implemented with a Revit plugin. The IGA-Revit interface implements a reconstruction algorithm based on sweeping teachnique to construct trivariate NURBS lining segment geometry, which avoids the burden to deal with trimmed geometries.     

Identification of potential technologies for 1,4-Butanediol production using prospecting methodology

1,4-Butanediol (1,4-BDO) is a four-carbon diol used for industrial applications such as organic solvents, and the production of adhesives, fibers and polyurethanes. 1,4-BDO currently is produced through several petrochemical routes: hydrogenation of maleic anhydride, isomerization of propylene oxide, acetoxylation of butadiene, and the reaction between formaldehyde and acetylene. The current trends in 1,4-BDO production involve the utilization of renewable sources such as biomass. In this context, the present study aimed to identify promising technologies of 1,4-BDO production through prospecting methodology based on the analyses of patents and scientific article, describing the most relevant aspects of those emerging technologies. An increasing amount of 1,4-BDO production focused on biotechnological routes has been reported, with the US heavily involved in the development of new technologies. This study tracked three promising technologies which have potential for application in a biorefinery context because those processes involve (i) production of 1,4-BDO from sugars, classified herein as the biotechnological route; (ii) production of intermediates from sugar fermentation followed by catalytic conversion into 1,4-BDO, classified herein as the hybrid route, and (iii) furan/furfural conversion into 1,4-BDO. © 2020 Society of Chemical Industry     

Bayesian network construction from event log for lateness analysis in port logistics

The handling of containers in port logistics consists of several activities, such as discharging, loading, gate-in and gate-out, among others. These activities are carried out using various equipment including quay cranes, yard cranes, trucks, and other related machinery. The high inter-dependency among activities and equipment on various factors often puts successive activities off schedule in real-time, leading to undesirable activity down time and the delay of activities. A late container process, in other words, can negatively affect the scheduling of the following ones. The purpose of the study is to analyze the lateness probability using a Bayesian network by considering various factors in container handling. We propose a method to generate a Bayesian network from a process model which can be discovered from event logs in port information systems. In the network, we can infer the activities’ lateness probabilities and, sequentially, provide to port managers recommendations for improving existing activities.     

树立科学的发展观,大力推进皮革工业环境建设

文章将对中国皮革工业的发展历程与现在基本的环境状况作出详尽的介绍与分析,提出必须以科学发展观为指导,加大力度深入探讨皮革工业的环境建设,并且积极的树立健康良好的皮革工业环境建设观念,以此来促进皮革工业健康可持续的发展。     

Applying Feature-Weighted Gradient Decent K-Nearest Neighbor to Select Promising Projects for Scientific Funding

Due to its outstanding ability in processing large quantity and high-dimensional data, machine learning models have been used in many cases, such as pattern recognition, classification, spam filtering, data mining and forecasting. As an outstanding machine learning algorithm, K-Nearest Neighbor (KNN) has been widely used in different situations, yet in selecting qualified applicants for winning a funding is almost new. The major problem lies in how to accurately determine the importance of attributes. In this paper, we propose a Feature-weighted Gradient Decent K-Nearest Neighbor (FGDKNN) method to classify funding applicants in to two types: approved ones or not approved ones. The FGDKNN is based on a gradient decent learning algorithm to update weight. It updatesthe weight of labels by minimizing error ratio iteratively, so that the importance of attributes can be described better. We investigate the performance of FGDKNN with Beijing Innofund. The results show that FGDKNN performs about 23%, 20%, 18%, 15% better than KNN, SVM, DT and ANN, respectively. Moreover, the FGDKNN has fast convergence time under different training scales, and has good performance under different settings.     

Formal Approach to Workflow Application Fragmentations Over Cloud Deployment Models

Workflow management technologies have been dramatically improving their deployment architectures and systems along with the evolution and proliferation of cloud distributed computing environments. Especially, such cloud computing environments ought to be providing a suitable distributed computing paradigm to deploy very large-scale workflow processes and applications with scalable on-demand services. In this paper, we focus on the distribution paradigm and its deployment formalism for such very large-scale workflow applications being deployed and enacted across the multiple and heterogeneous cloud computing environments. We propose a formal approach to vertically as well as horizontally fragment very large-scale workflow processes and their applications and to deploy the workflow process and application fragments over three types of cloud deployment models and architectures. To concretize the formal approach, we firstly devise a series of operational situations fragmenting into cloud workflow process and application components and deploying onto three different types of cloud deployment models and architectures. These concrete approaches are called the deployment-driven fragmentation mechanism to be applied to such very large-scale workflow process and applications as an implementing component for cloud workflow management systems. Finally, we strongly believe that our approach with the fragmentation formalisms becomes a theoretical basis of designing and implementing very large-scale and maximally distributed workflow processes and applications to be deployed on cloud deployment models and architectural computing environments as well.     

基于VSE的大南湖一矿通风系统现状仿真与评估

为了掌握大南湖一矿通风系统现状,科学评估其安全性、稳定可靠性及合理性,对全矿进行了通风参数精准普查,基于VSE软件对通风系统运行状况进行了仿真与评估。结果表明大南湖一矿通风系统存在部分巷道微风、回风大巷风速偏高、井下通风设施较多、部分角联分支易发生风流转向、矿井通风阻力分布不合理等问题,为系统的优化改造指明了方向。     

Exploration and design of knitted composites for architectural application: The MeiTing project

Knitted composites are textile composite materials that consist of knitted textile reinforcement and polymer matrix. Knitted composites exhibit great design flexibility by allowing the customization of shapes, textures, and material properties. These features facilitate the optimization of buildings’ material systems and the creation of buildings with light weight and high material efficiency.To achieve such a lightweight, material-efficient building structure with knitted composites, this research investigates the material properties of knitted composites and proposes a design process for building-scale knitted composite systems. In the material study, this research examines certain mechanical properties of the material and the effects of additional design elements. In the design exploration, this research explores the design workflow of the structural form, element arrangement, and knit distribution of the material system at the macro-, meso-, and microscales. The project of MeiTing serves as proof of the concept and the design workflow.