fsh—A functional unix command interpreter

Command interpreters under the UNIX operating system typically employ the syntax and semantics of imperative programming languages. Many of the advantages that functional programming languages hold over imperative languages can be incorporated in a functional command interpreter. Unfortunately, functional command interpreters to date have used the syntax of Backus's FP. The advantages of command expressiveness and composition have not been appreciated. A powerful functional command interpreter, fsh, that overcomes many of the deterrents of previous functional command interpreters is presented. Much of the unnecessary complexity of existing UNIX command interpreters is avoided by following the functional paradigm. fsh has been implemented under the UNIX 4.2BSD and System V operating systems.     

Synfuel development impacts— econometric modelling and policy analysis

The prospects for rapid near-term development of a synfuel industry in the USA have decreased, due to depressed world oil prices, synfuel project cost overruns, and the lukewarm support of the Reagan administration. Nonetheless, socioeconomic and environmental impact analysis studies can provide valuable information for determining the regional welfare effects of proposed projects. The author discusses the results of a regional econometric analysis of the synfuel projects planned for Western Kentucky, which focuses on environmental impacts, and reveals the inevitable trade-offs that would accompany synfuel development. Some policy issues are briefly reviewed, especially that of efficient energy pricing.     

尿素合成塔腐蚀情况及原因分析

针对尿素合成塔的腐蚀问题,详细介绍了从投产使用到现在该设备的腐蚀现状.并从不同角度进行详细分析,提出了解决问题的办法及日常运行中应注意的问题.     

Domestic and Industrial Wastewater Treatment with Ozonated Activated Sludge

Poor sludge settleability is a problem encountered in many activated sludge wastewater treatment plants. This study was aimed at combatting the unwanted biological growths at the root of this phenomenon with ozone. Ozone dosed directly into the aeration basins of small activated sludge pilot plants treating both domestic and synthetic fuel wastewaters led to a substantial reduction of the bulking problem even at dosages as low as 6 to 10 mg/L. Ozone did not interfere in the delicate nutrient removal processes and significantly enhanced effluent quality.     

Decision support in machine vision system for monitoring of TFT-LCD glass substrates manufacturing

This study addresses classification methodology for the automatic inspection of a range of defects on the surface of glass substrates in thin film transistor liquid crystal display glass substrate manufacturing. The proposed methodology consisted of four stages: (1) feature extraction by calculating the wavelet co-occurrence signature from the substrate images, (2) handling of imbalanced dataset using the Synthetic Minority Over-sampling TEchnique (SMOTE), (3) reduction of the feature's dimension by principal component analysis, and (4) finally choosing the best classifier between three different methods: Classification And Regression Tree (CART), Multi-Layer Perceptron (MLP) and Support Vector Machine (SVM). In training the SVM and MLP classifiers, the simulated annealing algorithm was used to obtain the optimal tuning parameters for the classifiers. From the industrial case study, the proposed feature extraction algorithm could remove the defect-irrelevant image features and SMOTE increased the accuracy of all three methods. Furthermore, the optimized SVM and MLP models were more accurate than the CART model whereas a higher accuracy of 89.5% was observed for the proposed SVM model.     

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.     

一种合成聚焦的便携式B型超声成像方法

传统合成聚焦超声成像方法在图像重建过程中处理数据量较大,致使其在便携式B型超声设备中应用受限。针对该问题,提出一种基于压缩感知理论和合成聚焦波束形成算法的便携式B型超声成像方法(SFCS)。该方法通过对接收到的射频回波信号进行随机采样得到欠采样的测量信号,将测量信号经过合成聚焦波束形成处理获得欠采样的射频信号线,基于压缩感知的信号重构算法,由欠采样的射频信号线高质量地恢复信号后供后续成像处理使用。仿真实验结果表明,SFCS可有效地解决合成聚焦超声成像过程中数据量大的问题,从而在保证较高成像质量的前提下满足便携式B型超声设备小型化、低成本的技术要求,具有工程应用价值。     

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.