New approaches to determine the interface height of fire smoke based on a three-layer zone model and its verification in large confined space

Large confined space has high incidence of fires, which seriously threatens the safety of people working there. Understanding the distribution of smoke in such large space is critical to fire development prediction and smoke control. Three improved methods for the stratification interface prediction of fire smoke are developed, including of improved intra-variance, integral ratio and N-percentage methods. In these methods, the interface height is determined by the vertical temperature distribution based on a three-layer smoke zone model, which is an improvement of a two-layer zone model. Thereafter, the three improved methods are applied to several typical fire cases simulated CFD to predict the smoke interface, and their applicability and reliability are verified by comparison of the smoke stratification results with the filed simulation results. Results show that the three improved methods can effectively determine the location of the three-layer zone model's interface, and they have the ability to predict smoke interface for fires with different fire source types and ventilation conditions.     

A comparison of pivot selection techniques for permutation-based indexing

Recently, permutation based indexes have attracted interest in the area of similarity search. The basic idea of permutation based indexes is that data objects are represented as appropriately generated permutations of a set of pivots (or reference objects). Similarity queries are executed by searching for data objects whose permutation representation is similar to that of the query, following the assumption that similar objects are represented by similar permutations of the pivots. In the context of permutation-based indexing, most authors propose to select pivots randomly from the data set, given that traditional pivot selection techniques do not reveal better performance. However, to the best of our knowledge, no rigorous comparison has been performed yet. In this paper we compare five pivot selection techniques on three permutation-based similarity access methods. Among those, we propose a novel technique specifically designed for permutations. Two significant observations emerge from our tests. First, random selection is always outperformed by at least one of the tested techniques. Second, there is no technique that is universally the best for all permutation-based access methods; rather different techniques are optimal for different methods. This indicates that the pivot selection technique should be considered as an integrating and relevant part of any permutation-based access method.     

基于三维胞元空间的MA双向并行路由算法

针对传统移动代理(MA)在监测无线传感器网络(WSNs)的感兴趣信息时产生的延迟较大和能耗较多问题,提出了基于三维胞元空间的MA双向并行(3D-BPMA)路由算法.3D-BPMA将MA与传统的客户/服务器(c/S)模式相结合,在胞元内利用C/S模式搜集信息,在单层胞元系统和路由器与路由器之间采用MA双向并行的策略进行传输.仿真结果表明:3D-BPMA与LCF,DSG-MIP算法相比减少了平均响应时间和网络平均能耗,提高了MA发送率.     

Continuous space maximal coverage: Insights,advances and challenges

Siting facilities in continuous space to maximize coverage of regional demand is an important planning problem. It is challenging to solve because demand is continuously distributed in a region and facilities may be sited anywhere in the region, suggesting that an infinite number of locations must be considered both as demand for service as well as a potential facility. An ingenious approach for solving continuous space coverage problems is abstracting continuously distributed demand as discrete spatial objects (points, lines or polygons), generating a finite dominating set from continuous space as candidate facility sites, and applying a discrete location coverage model. However, abstracting continuous demand and potential facility sites often introduces errors and uncertainties in coverage of regional demand, rendering findings (service and optimal facility locations) less than definitive. In this paper we examine the continuous space maximal coverage problem. Studies focused on locating antennas in Paradise Valley, Arizona and emergency warning sirens in Dublin, Ohio, are used to highlight issues and challenges in continuous space modeling. Potential paths forward are suggested based on empirical insights.     

城市空间与其使用价值——汕头中山公园的城市空间意义

文章通过论述汕头中山公园在策划背景、分析论证、用地选址和大规模建设各方面，是如何作为城市空间来体现其社会使用价值，来探讨城市空间产生过程中错综复杂的政治、经济、社会和文化多方面力量的博弈，以及城市社会和空间使用的相互关系。     

关于信息化测绘时代工程测量发展的思考

如今我国信息化技术全面发展，尤其对于工程测量工作领域来讲，不管是在工程建设和管理方面都产生不小的支撑引导效用。由此，笔者具体结合如今工程建设信息化测绘核心任何以及设备布置细节，进行结构整体安全管理周期和周边地理空间信息技术发展能效整理解析，试图将工程测量最新发展机遇和技术挑战问题处理完全。希望能够借此为日后一定时期范围内相关工程测量规划主体提供合理指导性建议内容，最终为我国各类工程事业可持续发展前景绽放奠定深刻适应基础。     

一种计算空间异面高压线间最短距离的方法

在电力工程建设、运行、管理中,需要遵循许多行业规范,尤其是高压线间的间距,关系到电网运行的安全与否。对于一些容易判断两线间最短距离的高压线,如平行的高压线等,可以方便的求出其最短距离,但是,在遇到一些不易判断出两线间最短距离位置的高压线时,需要通过一定的方法求出两高压线间的最短距离,以判断是否符合规范要求,确保电网的安全运行。本文提出一种利用Mathematica软件计算空间异面高压线间最短距离的方法。     

Supply chain data analytics for predicting supplier disruptions: a case study in complex asset manufacturing

Although predictive machine learning for supply chain data analytics has recently been reported as a significant area of investigation due to the rising popularity of the AI paradigm in industry, there is a distinct lack of case studies that showcase its application from a practical point of view. In this paper, we discuss the application of data analytics in predicting first tier supply chain disruptions using historical data available to an Original Equipment Manufacturer (OEM). Our methodology includes three phases: First, an exploratory phase is conducted to select and engineer potential features that can act as useful predictors of disruptions. This is followed by the development of a performance metric in alignment with the specific goals of the case study to rate successful methods. Third, an experimental design is created to systematically analyse the success rate of different algorithms, algorithmic parameters, on the selected feature space. Our results indicate that adding engineered features in the data, namely agility, outperforms other experiments leading to the final algorithm that can predict late orders with 80% accuracy. An additional contribution is the novel application of machine learning in predicting supply disruptions. Through the discussion and the development of the case study we hope to shed light on the development and application of data analytics techniques in the analysis of supply chain data. We conclude by highlighting the importance of domain knowledge for successfully engineering features.