基于S7-300 PLC和现场总线的3150型盘绞成缆机控制系统设计

根据成缆生产线的工艺要求,提出了一种基于S7-300 PLC和现场总线的3150型盘绞成缆机控制系统的设计方案,给出了3150型盘绞成缆机的整体结构,详细介绍了系统硬件及软件设计,并给出了盘绞头与放线架的同步控制方法。实际应用表明,该系统结构简单、使用灵活方便、控制精度高、人机对话良好,达到了预期目标。     

On calibration error of randomized forecasting algorithms

It has been recently shown that calibration with an error less than Δ>0$\Delta >0$ is almost surely guaranteed with a randomized forecasting algorithm, where forecasts are obtained by random rounding the deterministic forecasts up to Δ$\Delta$. We show that this error cannot be improved for a vast majority of sequences: we prove that, using a probabilistic algorithm, we can effectively generate with probability close to one a sequence “resistant” to any randomized rounding forecasting with an error much smaller than Δ$\Delta$. We also reformulate this result by means of a probabilistic game.     

Least squares twin support vector machines for pattern classification

In this paper we formulate a least squares version of the recently proposed twin support vector machine (TSVM) for binary classification. This formulation leads to extremely simple and fast algorithm for generating binary classifiers based on two non-parallel hyperplanes. Here we attempt to solve two modified primal problems of TSVM, instead of two dual problems usually solved. We show that the solution of the two modified primal problems reduces to solving just two systems of linear equations as opposed to solving two quadratic programming problems along with two systems of linear equations in TSVM. Classification using nonlinear kernel also leads to systems of linear equations. Our experiments on publicly available datasets indicate that the proposed least squares TSVM has comparable classification accuracy to that of TSVM but with considerably lesser computational time. Since linear least squares TSVM can easily handle large datasets, we further went on to investigate its efficiency for text categorization applications. Computational results demonstrate the effectiveness of the proposed method over linear proximal SVM on all the text corpuses considered.     

Multi-category classifiers and sample width

In a recent paper, the authors introduced the notion of sample width for binary classifiers defined on the set of real numbers. It was shown that the performance of such classifiers could be quantified in terms of this sample width. This paper considers how to adapt the idea of sample width so that it can be applied in cases where the classifiers are multi-category and are defined on some arbitrary metric space.     

Applying eco-visualisations of different interface formats to evoke sustainable behaviours towards household water saving

The shortage of water resources is a global issue. This study attempts to utilise eco-visualisation interface design to affect users’ water-usage behaviour. Three interface proposals were designed in this study: numeric, water droplet (abstract symbol), and swimming fish (animated image). These three different interface formats range from abstract to figurative and from neutral to affective. A total of 93 subjects were divided into three groups and randomly performed designated dishwashing tasks twice. One of the tasks was completed without the assistance of any interface, whereas the other involved applying one of the three interface formats with eco-visualisations. In this study, the Self-Assessment Manikin scales, the System Usability Scale, and the Questionnaires for User Interaction Satisfaction were used to measure the emotional dimensions and perceived usability and to record the differences in water usage volume. The results indicated that the emotional valence evoked by the animated image interface was significantly higher than that by the numeric interface. The effect of the numeric interface formats on the subjects focused on emotional arousal, whereas other interfaces emphasised emotional valence. With the aid of the eco-visualisations of interface design, the evoked emotional response and enhanced usability could help improve sustainable behaviours towards water saving.     

Predictive capability of cognitive ability and cognitive style for spaceflight emergency operation performance

This study explores the effects of cognitive ability (information seeking, inference, spatial recognition, attention span, and attention allocation) and cognitive style (active-reflective, sensing-intuitive, visual-verbal, and sequential-global) on task performance of simulated spaceflight emergency operations that require judgment and operation on a Chinese spaceflight instrument board and the possible interaction effect with training experience. The performance criteria included task completion time and number of human errors. It was found that inference ability, spatial recognition ability, and attention span had significant effects on task completion time, while attention allocation ability had significant effect on the number of error. The participants with a sequential cognitive style made significantly fewer errors than those with a global cognitive style. Training experience significantly decreased task completion time. The participants with sequential cognitive style learnt faster than those with global cognitive style in the spaceflight instrument operations. With increasing training experience, the predictive capability of cognitive ability on performance decreased, whereas the predictive capability of the sequential-global cognitive style on performance increased.     

Indirect augmented reality

Developing augmented reality (AR) applications for mobile devices and outdoor environments has historically required a number of technical trade-offs related to tracking. One approach is to rely on computer vision which provides very accurate tracking, but can be brittle, and limits the generality of the application. Another approach is to rely on sensor-based tracking which enables widespread use, but at the cost of generally poor tracking performance. In this paper we present and evaluate a new approach, which we call Indirect AR, that enables perfect alignment of virtual content in a much greater number of application scenarios.To achieve this improved performance we replace the live camera view used in video see through AR with a previously captured panoramic image. By doing this we improve the perceived quality of the tracking while still maintaining a similar overall experience. There are some limitations of this technique, however, related to the use of panoramas. We evaluate these boundaries conditions on both a performance and experiential basis through two user studies. The result of these studies indicates that users preferred Indirect AR over traditional AR in most conditions, and when conditions do degrade to the point the experience changes, Indirect AR can still be a very useful tool in many outdoor application scenarios.     

Admission control for a responsive distributed middleware using decision trees to model run-time parameters

The software in modern systems has become too complex to make accurate predictions about their performance under different configurations. Real-time or even responsiveness requirements cannot be met because it is not possible to perform admission control for new or changing tasks if we cannot tell how their execution affects the other tasks already running. Previously, we proposed a resource-allocation middleware that manages the execution of tasks in a complex distributed system with real-time requirements. The middleware behavior can be modeled depending on the configuration of the tasks running, so that the performance of any given configuration can be calculated. This makes it possible to have admission control in such a system, but the model requires knowledge of run-time parameters. We propose the utilization of machine-learning algorithms to obtain the model parameters, and be able to predict the system performance under any configuration, so that we can provide a full admission control mechanism for complex software systems. In this paper, we present such an admission control mechanism, we measure its accuracy in estimating the parameters of the model, and we evaluate its performance to determine its suitability for a real-time or responsive system.     

Δ3-1,2,4—噻二唑类化合物的量子化学及构效关系研究

Δ3-1,2,4—噻二唑类化合物具有抑制黄瓜霜霉病毒的杀菌活性。本文用半经验PM3方法对25个该类化合物进行了量子化学计算,并依据原子的净电荷、前沿轨道能级、轨道主要成分及原子在前沿轨道中所占比重等计算结果和多重回归分析讨论了该类化合物的活性部位,为该类化合物结构与活性的研究奠定了理论基础。     

通用串行总线设备固件的设计

该文描述使用８ｘ９３０ａｘ微处理器开发通用串行总线设备固件的技术。