Effects of imperfect automation on decision making in a simulated command and control task

OBJECTIVE: Effects of four types of automation support and two levels of automation reliability were examined. The objective was to examine the differential impact of information and decision automation and to investigate the costs of automation unreliability. BACKGROUND: Research has shown that imperfect automation can lead to differential effects of stages and levels of automation on human performance. Method: Eighteen participants performed a "sensor to shooter" targeting simulation of command and control. Dependent variables included accuracy and response time of target engagement decisions, secondary task performance, and subjective ratings of mental work-load, trust, and self-confidence. RESULTS: Compared with manual performance, reliable automation significantly reduced decision times. Unreliable automation led to greater cost in decision-making accuracy under the higher automation reliability condition for three different forms of decision automation relative to information automation. At low automation reliability, however, there was a cost in performance for both information and decision automation. CONCLUSION: The results are consistent with a model of human-automation interaction that requires evaluation of the different stages of information processing to which automation support can be applied. APPLICATION: If fully reliable decision automation cannot be guaranteed, designers should provide users with information automation support or other tools that allow for inspection and analysis of raw data.     

基于数据点松紧度的局部线性嵌入算法

局部线性嵌入算法（LLE）是流形学习中非线性数据降维的重要方法之一。考虑数据点分布大多呈现不均匀性,LLE对近邻点的选取方式将会导致大量的信息丢失。根据其不足,提出一种基于数据点松紧度的局部线性嵌入改进算法——tLLE算法,针对数据点分布不均匀的数据集,tLLE算法能有效地进行维数约简,且具有比LLE更好的降维效果。在人造数据和现实数据上的嵌入以及分类识别结果表明了tLLE算法的有效性。     

Effect of nitrogen addition on the microstructure and mechanical behavior of 317L and 904L austenitic stainless steel welds

A systematic study of the effect of nitrogen addition on the microstructure and mechanical behavior of two different austenitic stainless steel welds, namely, 317L and 904L was carried out. For this, nitrogen content of the welds was altered by introducing different proportions of nitrogen gas into the argon shielding gas during welding. Nitrogen addition to 317L weld changed solidification mode from primary ferrite to primary austenite. As 904L weld solidify by primary austenitic mode, no change in the solidification mode was found with N addition. The results showed that, with rise in nitrogen content of the welds, various mechanical properties like ultimate tensile strength and ductility had improved significantly and that the welds prepared with 1 vol% N₂ in the shielding gas indeed failed in the base alloy making the weld stronger than the parent metal. It was noticed that the effect of N towards improving the mechanical properties 904L weld was higher than that found in the case of 317L weld.     

Impact of applying pre-processing techniques for improving classification accuracy

Image denoising is a procedure aimed at removing noise from images while retaining as many important signal features as possible. Many images suffer from poor contrast due to inadequate illumination or finite sensitivity of the imaging device, electronic sensor noise or atmospheric disturbances. This paper proposes a hybrid directional lifting technique for image denoising to retain the original information present in the images. The primary objective of this paper is to show the impact of applying preprocessing techniques for improving classification accuracy. In order to classify the image accurately, effective preservation of edges and contour details of an image is essential. The discrete wavelet transform-based interpolation technique is developed for resolution enhancement. The image is then classified using support vector machine classifier, which is well suitable for image classification. The efficiency of the classifier is analyzed based on receiver operating characteristic (ROC) curves. The quantitative performance measures peak signal to noise ratio and ROC analysis show the significance of the proposed techniques.     

Alternative search techniques for face detection using location estimation and binary features

The sliding window approach is the most widely used technique to detect an object from an image. In the past few years, classifiers have been improved in many ways to increase the scanning speed. Apart from the classifier design (such as the cascade), the scanning speed also depends on a number of different factors (such as the grid spacing, and the scale at which the image is searched). When the scanning grid spacing is larger than the tolerance of the trained classifier it suffers from low detections. In this paper, we present a technique to reduce the number of missed detections when fewer subwindows are processed in the sliding window approach for face detection. This is achieved by using a small patch to predict the location of the face within a local search area. We use simple binary features and a decision tree for location estimation as it proved to be efficient for our application. We also show that by using a simple interest point detector based on quantized gradient orientation, as the front-end to the proposed location estimation technique, we can further improve the performance. Experimental evaluation on several face databases show better detection rate and speed with our proposed approach when fewer number of subwindows are processed compared to the standard scanning technique.     

A review of the effects of catalyst and additive on biodiesel production, performance, combustion and emission characteristics

This article is a literature review of the effect of different catalysts and additives on biodiesel production, performance, combustion and emission characteristics. This study is based on the reports of about 60 scientists who published their findings between 1998 and 2010. It was reported that base catalyst produced more biodiesel compared to acid type catalysts. There was not much variation in engine performance with the use of catalyst. Combustion characteristics were improved with the use of additives. It was found that ignition delay was reduced and premixed combustion duration was increased with the addition of catalyst. HC emission and PM emission were reduced with the use of catalysts.     

Ion Electrodiffusion Governs Silk Electrogelation

Silk electrogelation involves the transition of an aqueous silk fibroin solution to a gel state (E-gel) in the presence of an electric current. The process is based on local pH changes as a result of water electrolysis - generating H(+) and OH(-) ions at the (+) and (-) electrodes, respectively. Silk fibroin has a pI=4.2 and when local pH相似文献   

A review and new approach to minimize the cost of solar assisted absorption cooling system

Solar energy is an alternative energy source for cooling systems where electricity is demand or expensive. Many solar assisted cooling systems have been installed in different countries for domestic purpose. Many researches are going on to achieve economical and efficient thermal systems when compared with conventional systems. This paper reviews the past efforts of solar assisted-single effect vapour absorption cooling system using LiBr–H₂O mixture for residential buildings. Solar assisted single-effect absorption cooling systems were capable of working in the driving temperature range of 70–100 °C. In this system LiBr–H₂O are the major working pairs and has a higher COP than any other working fluids. Besides the review of the past theoretical and experimental investigations of solar single effect absorption cooling systems, some new ideas were introduced to minimize the capital and operational cost, to reduce heat loss from generator and thus to increase COP to get effective cooling.     

Additive manufacturing of barium titanate based ceramic heaters with positive temperature coefficient of resistance (PTCR)

Lanthanum/manganese doped barium titanate (BT) based PTCR functional heater elements/structures were fabricated with desirable electrical properties for the first time using Additive Manufacturing (AM). 3D printed components of varying size and shape and prototype honeycomb lattices with high density were achieved through AM. Aqueous, less organic containing (2.5 wt% additives versus 10–30 wt% added typically), eco-friendly ink formulations were developed with suitable rheological properties for 3D printing. For BT prints, the sintered densities of the 3D ceramic parts were found to be >99% TD, highest reported value so far. The microstructure, electrical properties and heating characteristics of the printed PTCR components were studied in detail and their thermal stability evaluated using infrared imaging and benchmarked against commercial PTCR heating element. The heating behaviour of the solid and porous 3D printed components was demonstrated to be similar, paving the way for light weight (?47% reduction in weight) heaters suitable for automotive/aerospace applications and less materials wastage during device fabrication.