Enhanced user performance in an image gallery application with a mobile autostereoscopic touch display

In this study, we explored how stereoscopic depth affects performance and user experience in a mobile device with an autostereoscopic touch display. Participants conducted a visual search task with an image gallery application on three layouts with different depth ranges. The task completion times were recorded, and the participants were asked to rate their experiences. The results revealed that the image search times were facilitated by a mild depth effect and that too great a depth slowed search times and decreased user-experience ratings.     

Revisiting the two-stage choice model: an empirical study of consumer choice on brand website visits

In consumer choice behaviour literature, a two-stage choice model serves as a base theory where choice behaviour is decomposed into a consideration stage plus a choice stage. Yet, this default model has been increasingly challenged by the ‘limited consumer search’ school of thought because consumers do not necessarily review all products in a choice set before making decisions, but frequently draw on external information as mental short cuts. Methodologically, the choice behaviour in stage 1 has traditionally been latent because data that directly observe how consumers form their consideration sets by eliminating alternatives are lacking. This study continues the ‘limited consumer search’ line of reasoning and proposes an aided non-compensatory process in choice stage 1, where consumers reduce brand website alternatives by using online ratings to arrive at a consideration set. We use observed Web analytics data to unveil the stage 1 choice process and also the transition from stage 1 to stage 2, which is in need of further research based on extant literature. Lastly, we cross-validate our model with two types of websites (i.e. search vs. experience/credence) and find our model is contingent on the type of website content, where consumers’ inclination to use online ratings for decision-making varies.     

Prediction of DNA-binding regulatory proteins in bacteriophage T7

The high-resolution structure of several specific DNA-bindingproteins have been determined, and they display a common structuralmotif which mediates their binding to DNA. This motif consistsof two -helices connected by a sharp turn, and its amino acidsequence has several distinguishing features. A computer searchof the proteins coded by the genome of bacteriophage T7 hasbeen performed in an attempt to identify those proteins thatpotentially contain this motif. Eight proteins were found tohave regions similar to that of the motif. Of these, three arerelatively small, have no known function and are good candidatesfor being DNA-binding regulatory proteins. The methods describeduse commonly available computer programs and databases, andare therefore easy to implement.     

基于k-最近邻筛选的BMA集合预报模型研究

针对冗余训练样本会降低BMA参数求解效率与精度问题,本文提出在BMA运算之前采用k-最近邻(k-nearest neighbor)算法筛选有价值训练样本,并用于BMA参数求解的改进模型。模拟试验在淮河王家坝站进行,分别以k-最近邻筛选、不筛选两种方案为BMA提供训练样本,统计分析两种方案中王家坝站流量模拟结果,评价BMA改进法的性能。模拟结果显示,采用k-最近邻样本筛选方法后,BMA模型对洪水过程以及洪峰的预报精度提升明显;概率预报结果的离散程度降低的同时,可靠性程度获得提升。k-最近邻样本筛选方法的引入,能够有效去除BMA模型训练样本中的冗余数据,以少量的样本获得更可靠的模型参数,改善集合预报性能。     

基于Nutch与元搜索引擎技术的高校网络舆情监测系统研究

针对高校网络舆情监测工作的不足,结合高校舆情信息的传播特点,提出了在校园网范围内基于Nutch搜索引擎技术进行信息检索,在互联网上采用元搜索引擎技术获取相关信息的舆情监测系统构建方案。采用关键词特征库匹配方式自动进行网络舆情监测,及时准确地发现网络舆情信息;探讨了高校对于网络舆情的监测、分析、引导和反馈等环节的处理方法,从而形成完善的应对机制。     

一种基于稀疏表示的WLAN室内定位算法

随着科技进步和人民生活水平的提高,越来越多的用户对定位技术需求变得日益迫切。基于WLAN的室内定位技术研究在此背景下应运而生,但是该技术容易受非视距离以及多径影响。而位置指纹算法有效地克服了上述缺点,并得到了广泛应用。提出一种基于稀疏表示的WLAN室内定位算法,以解决位置指纹算法K近邻方法中参数选择问题、不能综合利用全局参考点信息问题,并对其进行了实验仿真。     

动态适应布谷鸟搜索算法

介绍一种新的生物启发算法—–布谷鸟搜索(CS)及其相关的L′evy飞行搜索机制.为了进一步提高算法的适应性,将反馈引入算法框架,建立了CS算法参数的闭环控制系统.将Rechenberg的1/5法则作为进化的评价指标,引入学习因子平衡种群的多样性和集中性,提出动态适应布谷鸟算法(DACS).最后,通过数值实验验证了所提出算法的有效性.     

轨迹空间中基于特征符号搜索算法的非刚体三维运动重建研究

现有研究一般是在正交约束条件下采用最小二乘法来求解三维运动轨迹基重建问题,然而这些算法的性能容易受噪声影响,产生不适定性。为此,通过利用离散线性的方法为三维运动搜索最优轨迹基系数和三维结构,建立了一种基于特征符号搜索算法的三维运动轨迹基重建方法。利用该方法,对一系列单目图像序列进行了重建实验研究,结果表明所提出的方法是可行的,并提高了重建算法的准确性。     

基于Voronoi图的连续反向最近邻查询

为解决动态环境中移动点的连续反向最近邻查询问题,将连续反向最近邻查询分为单色和双色2种情况进行研究。利用移动点Voronoi图,分别给出单色连续反向最近邻查询算法、双色连续反向最近邻查询算法以及相关定理,对算法正确性和可终止性进行证明,分析算法时间复杂性。按照移动点Voronoi图的拓扑结构是否改变分为2种情况,分析每种情况下候选所在区域的变化,在变化区域内进行Voronoi图的重构,得到对应的解决方法。在多数情况下,该算法只需生成局部移动点的Voronoi图即可找到结果,减小了连续反向最近邻查询的代价。     

A multiobjective hybrid ant colony optimization approach applied to the assignment and scheduling problem

The assignment and scheduling problem is inherently multiobjective. It generally involves multiple conflicting objectives and large and highly complex search spaces. The problem allows the determination of an efficient allocation of a set of limited and shared resources to perform tasks, and an efficient arrangement scheme of a set of tasks over time, while fulfilling spatiotemporal constraints. The main objective is to minimize the project makespan as well as the total cost. Finding a good approximation set is the result of trade‐offs between diversity of solutions and convergence toward the Pareto‐optimal front. It is difficult to achieve such a balance with NP‐hard problems. In this respect, and in order to efficiently explore the search space, a hybrid bidirectional ant‐based approach is proposed in this paper, which is an improvement of a bi‐colony ant‐based approach. Its main characteristic is that it combines a solution construction developed for a more complicated problem with a Pareto‐guided local search engine.