基于数据局部性的推测式Hadoop任务调度算法研究

针对Hadoop平台现有任务调度算法优化程度不高的问题, 提出了一种基于数据局部性的推测式任务调度算法。该算法通过计算节点上Map和Reduce任务时长比例, 结合不同节点上数据的局部特性, 采用了比现有算法更精确的任务进度探测方式找出快慢节点, 在快节点上启动剩余时间最长的落后任务的备份任务, 用移动计算代替移动数据。在Hadoop环境中进行了实验, 结果表明该算法比现有算法缩短了任务平均运行时间, 加快了任务的执行效率。     

变化环境下河流健康评价研究进展

全球以温度升高为主要特征的气候变化耦合人类活动影响,造成了全球性变化环境背景下大范围的水资源危机、水环境污染和水生态退化问题,威胁河流健康,已成为当今世界各国急需解决的难题。针对变化环境背景,分别从河流健康的概念和内涵、河流健康评价的内容、方法及应用等方面,评述近年来国内外河流健康评价的研究进展。将河流健康定义为,特定时期一定的社会公众价值体系下,在保障河流自身基本生存需求的前提下,能够持续地为人类社会提供高效合理的生态服务功能,并实现服务功能综合价值最大化。在前人研究基础上,指出变化环境下河流健康评价研究存在的主要问题,如河流健康概念及内涵仍存在争议,河流健康变化的驱动机制尚不明确,河流健康评价的理论及方法有待完善,河流健康评价实践滞后及评价结果未能有效指导河流管理等。提出变化环境下河流健康评价的发展趋势:以流域为基本空间尺度结合多时间尺度开展河流健康评价与调控研究,因地制宜开展河流健康评价指标体系及评价标准研究,开展基于3S等技术的河流健康评价研究,建立长期且全面的河流健康监测网络,科学界定河流健康的"基准点",以及开展河流健康评价与水资源调控的集成研究等。     

I3WSN: Industrial Intelligent Wireless Sensor Networks for indoor environments

Sensor Web Enablement (SWE) technologies have been successfully applied to a great variety of outdoor scenarios but, in practical terms, little effort has been applied for indoor environments, and even less in the field of industrial applications. This article presents an intelligent SWE application for an indoor and industrial scenario, with the aim of improving and increasing the levels of human safety. The base low-level architecture is built on top of wireless sensor networks (WSN) connected to a Sensor Observation Service (SOS). Higher layers in the architecture include services that make real time decisions based on the collected data. Both simulation and experimental results are presented. The paper shows the viability of our approach in terms of performance, scalability, modularity and safety.     

Reputation mechanism for e-commerce in virtual reality environments

The interest in 3D technology and virtual reality (VR) is growing both from academia and industry, promoting the quick development of virtual marketplaces (VMs) (i.e. e-commerce systems in VR environments). VMs have inherited trust problems, e.g. sellers may advertise a perfect deal but doesn’t deliver the promised service or product at the end. In view of this, we propose a five-sense feedback oriented reputation mechanism (supported by 3D technology and VR) particularly for VMs. The user study confirms that users prefer VMs with our reputation mechanism over those with traditional ones. In our reputation mechanism, five-sense feedback is objective and buyers can use it directly in their reputation evaluation of target sellers. However, for the scenarios where buyers only provide subjective ratings, we apply the approach of subjectivity alignment for reputation computation (SARC), where ratings provided by one buyer can then be aligned (converted) for another buyer according to the two buyers’ subjectivity. Evaluation results indicate that SARC can more accurately model sellers’ reputation than the state-of-the-art approaches.     

锈蚀损伤混凝土管桩水平承载性状时变分析

为研究锈蚀损伤混凝土管桩的水平承载性状,依据Fick第二定律,建立了氯离子在混凝土管桩中的扩散方程,并结合初始和边界条件,得到扩散方程的解析解.依据厚壁圆筒模型,推导了钢筋混凝土管桩保护层锈胀开裂时的钢筋临界锈蚀深度.基于Faraday定律,对钢筋混凝土管桩保护层锈胀开裂时间进行了预测.并在此基础上,通过引入桩身抗弯刚度折减系数对海洋环境下锈蚀损伤钢筋混凝土管桩的桩身抗弯刚度的衰减规律进行了探讨,进而对海洋环境下锈蚀损伤钢筋混凝土管桩的水平承载性状的时变特性进行了分析.结果表明:海洋环境中氯离子侵蚀引起的钢筋锈蚀对钢筋混凝土管桩的水平承载性状有明显影响.随着暴露时间的延长,桩身抗弯刚度呈非线性衰减,桩身水平位移和桩身负剪力最大值逐渐增大,桩身弯矩逐渐减小.     

一种应用于噪声点分布密集环境下的噪声点识别算法

为了提高DBSCAN及其改进算法在噪声点分布密集环境下的噪声点识别率,通过结合PageRank算法思想及噪声数据分布密集的特点,构造簇间投票映射函数,提出了簇间投票噪声点识别算法-NoiseRank 。实验结果表明,在噪声点分布密集环境下,NoiseRank算法比DBSCAN算法具有更高的噪声点识别率。     

开发冲模CAD/CAM系统新模式的研究

基于ＣＡＳＥ（ＣｏｍｐｕｔｅｒＡｉｄｅｄＳｏｆｔｗａｒｅＥｎｇｉｎｅｅｒｉｎｇ）技术原理和冲摸设计与制造过程的特点以及ＣＡＤ／ＣＡＭ技术原理，在文献［２］的研究基础上，提出并研制了一种面向最终用户能多快好省地开发具体冲模ＣＡＤ／ＣＡＭ系统的新模式：冲模ＣＡＤ／ＣＡＭ系统的集成开发平台，论述了平台的总体设计思想，体系结构和工作流程，并给出实现平台的关键技术问题     

A flowchart‐based intelligent tutoring system for improving problem‐solving skills of novice programmers

Intelligent tutoring and personalization are considered as the two most important factors in the research of learning systems and environments. An effective tool that can be used to improve problem‐solving ability is an Intelligent Tutoring System which is capable of mimicking a human tutor's actions in implementing a one‐to‐one personalized and adaptive teaching. In this paper, a novel Flowchart‐based Intelligent Tutoring System (FITS) is proposed benefiting from Bayesian networks for the process of decision making so as to aid students in problem‐solving activities and learning computer programming. FITS not only takes full advantage of Bayesian networks, but also benefits from a multi‐agent system using an automatic text‐to‐flowchart conversion approach for engaging novice programmers in flowchart development with the aim of improving their problem‐solving skills. In the end, in order to investigate the efficacy of FITS in problem‐solving ability acquisition, a quasi‐experimental design was adopted by this research. According to the results, students in the FITS group experienced better improvement in their problem‐solving abilities than those in the control group. Moreover, with regard to the improvement of a user's problem‐solving ability, FITS has shown to be considerably effective for students with different levels of prior knowledge, especially for those with a lower level of prior knowledge.     

Development of a contextual decision-making game for improving students' learning performance in a health education course

Heath education is an important component of the curriculum for fostering children's correct health knowledge and good daily life habits. However, educators have indicated that most children might fail to realize the importance and meaning of health education content owing to the lack of authentic scenarios and daily life experience. With the advancement of computer technologies, researchers have tried to develop multimedia learning content in order to improve students' learning performance. Among various technology-enhanced learning alternatives, digital game-based learning has been recognized as a highly potential approach to motivating students. However, several previous studies have indicated that, without properly incorporating learning content into game scenarios, the effectiveness of digital game-based learning might not be as good as expected in comparison with conventional technology-enhanced learning. In this study, a contextual digital game was developed for improving students' learning performance in an elementary school health education course. A quasi experiment was conducted to evaluate the effectiveness of the proposed approach by situating the experimental group in the game-based learning scenario and the control group to learn with conventional e-books. The experimental results showed that the proposed approach not only improved the students' learning motivation, but also their learning achievement and problem-solving competences. Moreover, the significant two-way interaction suggested that the contextual game-based learning approach benefited the higher motivation students more than the lower motivation ones in terms of the advanced knowledge, showing the importance and potential of applying contextual games to health education activities.