Longitudinal and temporal water temperature patterns in the Yangtze River and its influence on spawning of the Chinese sturgeon (Acipenser sinensis Gray 1835)

In this study, water temperature longitudinal and temporal patterns were investigated in four locations of the Yangtze River to identify their influence on spawning of the Chinese sturgeon (Acipenser sinensis Gray 1835). The results showed that, historically (1960–1980), the four locations, Pingshan (PS, 2,687 river kilometres [rkm]), Yichang (YC, 1,640 rkm), Chenglingji (CLJ, 1,265 rkm), and Hukou (HK, 805 rkm), all had similar average annual water temperatures (around 18.0 °C) but very different amplitudes: The upper two locations, PS (11.4–23.2 °C) and YC (9.1–25.9 °C), were relatively stable and had smaller amplitude than the lower two ones, CLJ (6.0–30.0 °C) and HK (5.9–30.8 °C). On the basis of the physiological effects for Chinese sturgeon, we defined three water temperature ranges: stressing (>23 °C), holding (23–20 °C), and spawning (20–16 °C). We found that the upper two locations with successful spawning of the Chinese sturgeon (PS and YC) had short or no stressing period but long holding and spawning periods. Currently (2013–2016), the impoundment of the Three Gorges Reservoir increases the time for water temperature decreasing to 20 °C at the current spawning ground (YC) in autumn, which increases the stressing and holding periods, and has significant negative impact on the spawning of Chinese sturgeon. Nonetheless, considering the very high stressing temperature and the short duration of the holding and spawning periods at CLJ and HK, we propose that YC is still the most suitable spawning location for the Chinese sturgeon.     

Estimating discharge in gravel‐bed river using non‐contact ground‐penetrating and surface‐velocity radars

Discharge measurement is a critical task for gravel‐bed channels. Under high‐flow conditions, the elevation of the riverbed changes significantly by intensive torrential flow. The stage–discharge relations commonly used for stream discharge estimation may no longer be adequate. The contact‐type velocity measuring is also subject to measurement errors and/or instrument failures by the high‐flow velocities, driftwood, stumps, and debris. This study developed a new real‐time method to estimate river discharge in gravel‐bed channels. A systematic measuring technology combining ground‐penetrating radar and surface‐velocity radar was employed. The rating curves representing the relations of water surface velocity to the channel cross‐sectional mean velocity and flow area were established. Stream discharge was then deduced from the resulting mean velocity and flow area. The proposed method was examined in a steep gravel‐bed reach of the Cho‐Shui River in central Taiwan. The estimated stream discharge during three flood events were compared to the prediction by using the stage–discharge relation and the index‐velocity method. The proposed method of this study is capable of computing reasonable values of discharge for an entire flood hydrograph, whereas the other two methods tend to produce large extrapolation errors. Moreover, when the computed discharge is used in 2D flood flow simulation, the proposed method demonstrates better performance than the commonly used stage–discharge and index‐velocity methods.     

A demerit-fuzzy rating system,monitoring scheme and classification for manufacturing processes

For monitoring online manufacturing processes, the proportion of weights imposed on each type of product’s defects (nonconformities or demerits) has a profoundly effective impact on control charts’ performance. Apparently, the demerit-chart approach is superior than the widely-used c-chart scheme, because it allows us to place relative precise weights (real numbers) on defects according to their distinctly inferior degrees affecting the product quality so that the abnormal variations of processes can be literally exposed. However, in many applications, the seriousness of defects is evaluated partially or entirely by the inspectors’ perceptive judgement or knowledge, so with the precise-weight assignment, the demerit rating mechanism is considered to be somewhat constrained and subjective which inevitably leads to the targeted manufacturing process with limited and possibly biased information for online surveillance. To cope with the drawback, a demerit-fuzzy rating system and monitoring scheme is proposed in this paper. We first incorporate fuzzy weights (fuzzy numbers) to properly reflect the severity measures of defects which are categorized linguistically. Then, based on properties of fuzzy set theory and proposed approaches for fuzzy-number ranking, we develop the demerit-fuzzy charting scheme which is capable of discriminating process conditions into multi-intermittent statuses between in-control and out-of-control. This approach improves the traditional process control techniques with the binary-classification restraint for the process conditions. Finally, the proposed demerit-fuzzy rating system, monitoring scheme, and classification is elucidated by an application in garment industry to monitor textile-stitching nonconformities conditions.     

Novel associative classifier based on dynamic adaptive PSO: Application to determining candidates for thoracic surgery

Association rule mining is a data mining technique for discovering useful and novel patterns or relationships from databases. These rules are simple to infer and intuitive and can be easily used for classification in any domain that requires explanation for and investigation into how the classification works. Examples of such areas are medicine, agriculture, education, etc. For such a system to find wide adoptability, it should give output that is correct and comprehensible. The amount of data has been growing very fast and so has the search space of these problems. So we need to change traditional methods. This paper discusses a rule mining classifier called DA-AC (dynamic adaptive-associative classifier) which is based on a Dynamic Particle Swarm Optimizer. Due to its seeding method, exemplar selection, adaptive parameters, dynamic reconstruction of regions and velocity update, it avoids premature convergence and provides a better value in every dimension. Quality evaluation is done both for individual rules as well as entire rulesets. Experiments were conducted over fifteen benchmark datasets to evaluate performance of proposed algorithm in comparison with six other state-of-the-art non associative classifiers and eight associative classifiers. Results demonstrate competitive performance of proposed DA-AC while considering predictive accuracy and number of mined patterns as parameters. The method was then applied to predict life expectancy of post operative thoracic surgery patients.     

案例推理属性权重的分配模型比较研究

案例推理系统中各属性权重的赋值决定了案例之间的相似度 大小,进而对推理结果的正确与否产生显著影响.以属性加权K-最近邻 相似案例检索为基础,讨论了使用注水原理分配属性权重的机理,并通过建 立权重分配的合理性指标,构造拉格朗日函数对权重进行优 化求解,得到了收敛的注水分配算法.通过五折交叉的模式分类实验 ,分别对属性权重的平均分配法、注水分配算法和遗传算法分配法进行了比较研究,案例推理分类结果证明,在引入注水分配算法后,其分类性能得到有效改善.     

Computational Problem Solving in Spatial Substrates -- A Cognitive Systems Engineering Approach

The ability to perform spatial tasks is crucial for everyday life and of great importance to cognitive agents such as humans, animals, and autonomous robots. A common artificial intelligence approach to accomplish spatial tasks is to represent spatial configurations and tasks in form of detailed knowledge about various aspects of space and time. Suitable algorithms then use the representations to compute solutions to spatial problems. In comparison, natural embodied and situated agents often solve spatial tasks without detailed knowledge about geometric, topological, or mechanical laws; they directly relate actions to effects that are due to spatio-temporal affordances in their bodies and environments. Accordingly, we propose a paradigm that makes the spatio-temporal substrate an integral part of the engine that drives spatial problem solving. We argue that spatial and temporal structures in body and environment can substantially support (and even replace) reasoning effort in computational processes: physical manipulation and perception in spatial environments substitute formal computation. While the approach is well known – for example, we employ diagrams as spatial substrate for geometric problem solving and maps for wayfinding – the underlying principle has not been systematically investigated or formally analyzed as a paradigm of cognitive processing. Topology, distance, and orientation constraints are all integrated and interdependent in truly 2- or 3-dimensional space. Exploiting this fact may not only help overcome the need for acquiring detailed knowledge about the interrelationships between different aspects of space; it also can point to a way of avoiding exploding computational complexity that occurs when we deal with these aspects of space in complex real-world scenarios. Our approach employs affordance-based object-level problem solving to complement knowledge-level formal approaches. We will assess strengths and weaknesses of the new cognitive systems paradigm.     

基于Bayes特征判别的选煤建模与识别

研究了煤块的Harr小波变换和幅度投影分析,在对原始图像进行特征判别分析的基础上,建立了煤块和煤矸石的统计模型,提出了用Bayes判别函数分选煤块和煤矸石的算法,实现了用计算机视觉系统对样本进行了识别检验.并运用神经网络BP算法进行训练识别,检验其正确性,最后通过实验验证了算法有效性.     

Insect sex pheromones

The half-lives (t _1/2) for evaporative loss ofn-alkyl andn-alkenyl acetates from rubber septa were determined at temperatures varying from 15 to 35 °C. The changes int _1/2 with temperature gave high correlations with the equation, Int _1/2 = H/RT+y _o where H is the heat of vaporization,R is the gas constant,T is the absolute temperature, andy _o is a constant. Half-lives changed dramatically with temperature and the degree of change with temperature increased with increasing molecular weight. For mixtures, component ratios changed with temperature, but the degree was modest. At 20 °C there was a 7.5-fold ratio oft _1/2 between members of the homologousn-alkyl orn-alkenyl acetates differing by two carbon atoms. The large change int _1/2 with temperature and with number of carbon atoms is a consequence of the thermodynamic relationships and the temperature range of pheromone usage. Therefore, a similar degree of change inf _1/2 with temperature and number of carbon atoms will apply to other formulations of the same type (those in which the rate of evaporation is first order). The values oft _1/2 at 20 °C mainly agreed very well with those reported previously at room temperature. However, our previously reported values for pentadecyl and hexadecyl acetate were revised. Half-lives were shown to depend on the vapor pressure of a compound in the formulation substrate, but not on the vapor pressure of the pure compound.Mention of a commercial or proprietary product does not constitute an endorsement by the USDA.     

一种基于深度卷积网络的鲁棒头部姿态估计方法

针对头部姿态估计方法受特征提取限制导致姿态估计效果不佳的问题,提出使用深度卷积网络自动学习有效特征并进行分类的头部姿态估计方法。首先,利用DCNN非线性映射和自动提取图像结构信息的能力,设计一个深度卷积网络实现对姿态鲁棒特征的提取;然后再将提取的特征用于分类器训练并最终实现头部姿态估计。在Pointing’04和FacePix数据库上的测试结果表明,本文设计的深度卷积网络能有效的进行特征学习,避免了人工设计特征的不足,与现有的基于人工设计特征方法相比,本文方法在两个数据库上达到的预测平均绝对误差分别为4.05〫和2.04〫,充分证实了本文算法的稳定性和可靠性。