易爆品运输车辆中的路径选择模型仿真

易爆品运输车辆必须选择最优路线模型,以保证运输安全.易爆品运输过程中,不但需要考虑运输成本和运输的线路,还需要考虑运输风险的因素.传统的路线选择模型仅仅以成本分析为基础,没有加入易爆品运输的风险因素,路线选择存在较大缺失.提出采用粒子群离散变换算法的易爆品运输车辆路径选择方法.根据最小二乘法相关原理,计算运输路径危险环境函数,获取危险程度拟合曲线,根据该函数得到运输路径中的危险程度.根据最小危害路径选择的目标函数,对所有的待优化变量进行二进制编码,并针对编码结果进行离散化变换,实现易爆品运输车辆路径的选择.实验结果表明,利用改进算法进行易爆品运输车辆路径选择,降低了路径协同误差和路径选择误差.     

Evaluating the Wisdom of Strangers: The Perceived Credibility of Online Consumer Reviews on Yelp

This study examined the effects of review valence, the reviewer profile, and the receiver's familiarity with the platform (user/nonuser) on the perceived credibility of a review on Yelp.com and on the receiver's attitude toward the reviewed object. The results demonstrated a difference in cue‐taking between users and nonusers. For users, there was an interaction effect of 2 profile cues (number of friends and number of reviews) on competence. Users interpreted the cues in combination, whereas non‐users were not influenced by them. The friends × reviews × platform familiarity interaction indirectly affected attitude through competence. Further, review valence was positively associated with perceived credibility and attitude. The findings support and extend the social information processing theory and cue combination literature.     

Signage Versus Environmental Affordances: Is the Explicit Information Strong Enough to Guide Human Behavior During a Wayfinding Task?

This study aims to explore how people behave when they have to find a location within a complex building and are confronted with situations where directional signage (i.e., explicit information) is in opposition to environmental affordances that naturally direct users towards a specific path, creating a situation with conflicting information (e.g., a brighter corridor vs. a darker corridor but with a directional sign indicating to follow the darker one). A virtual reality–based methodology was used and a between‐subject design was considered. Thus, participants were given the tasks of finding three publicly accessible central points in a virtual hotel and confronted with a two forced‐choice task of local scenes in which environmental variables (i.e., corridor width and brightness) and signage varied systematically, in two experimental conditions (i.e., neutral and signage). For the signage condition, signs were inserted to explicitly point in the opposite direction than that implicitly suggested by the environmental affordances, creating situations with conflicting information. Results indicate that environmental variables were able to direct people indoors acting as environmental affordances. Users preferred to follow the wider and brighter paths. However, when directional signage pointed in the opposite direction of the paths preferred by the participants, most of them complied with signage.     

A novel approach to generate MCQs from domain ontology: Considering DL semantics and open-world assumption

Ontologies are structures, used for knowledge representation, which model domain knowledge in the form of concepts, roles, instances and their relationships. This knowledge can be exploited by an assessment system in the form of multiple choice questions (MCQs). The existing approaches, which use ontologies expressed in the Web Ontology Language (OWL) for MCQ generation, are limited to simple concept related questions — “What is C?” or “Which of the following is an example of C?” (where $C$ is a concept symbol) — or analogy type questions involving roles. There are no efforts in the literature which make use of the terminological axioms in the ontology such as existential, universal and cardinality restrictions on concepts and roles for MCQ generation. Also, there are no systematic methods for generating incorrect answers (distractors) from ontologies. Distractor generation process has to be given much importance, since the generated distractors determine the quality and hardness of an MCQ. We propose two new MCQ generation approaches, which generate MCQs that are very useful and realistic in conducting assessment tests, and the corresponding distractor generating techniques. Our distractor generation techniques, unlike other methods, consider the open-world assumption, so that the generated MCQs will always be valid (falsity of distractors is ensured). Furthermore, we present a measure to determine the difficulty level (a value between 0 and 1) of the generated MCQs. The proposed system is implemented, and experiments on specific ontologies have shown the effectiveness of the approaches. We also did an empirical study by generating question items from a real-world ontology and validated our results with the help of domain experts.     

Categorizing health-related cues to action: using Yelp reviews of restaurants in Hawaii

Yelp, a social media site, undeniably has an influence on consumers' food choice in spite of its ability to reflect consumers' real voice being criticized. Since unhealthy food choices contribute to health problems, such as obesity and malnourishment, we attempted to examine these problems by better understanding consumers through health-related cues to action—a construct from the Health Belief Model (HBM)— on Yelp Honolulu's restaurant reviews. Our research revealed 13 main categories: Ingredient, Type of food, Taste, Lifestyle, Cooking, Option, Price, Portion, Well-being, Nutrition, Hygiene, Emotional attachment and indulgence, and Feeling. We argue that these categories may ultimately lead consumers to make healthier food choices. In search of the most appealing way to communicate with the target group, underlying concepts that derived from these categories can be tested. Marketers in food industry (or public health policy-makers) can craft their strategies for healthy food brands/products (or healthy eating scheme) based on the concept test research. Moreover, Yelp can apply these insights in the development of their algorithm and filter system in order to help consumers find healthy food if they wish to do so. Restaurants can also improve their strategy, menu, and communication execution to meet the growing demands of health conscious consumers.     

Types of structural assurance and their relationships with trusting intentions in business-to-consumer e-commerce

This study examines the effects of different types of structural assurance mechanisms on trusting intention in business-to-consumer electronic commerce. Inconsistent results from prior research on structural assurance motivated the current study to further explore the nature of structural assurance. Based on the Institution-based Trust Theory, this paper proposes that different types of structural assurance mechanisms, specifically: seals of approval, vendor-specific guarantees, protections from credit card companies and transaction protections, may have their unique effects on trusting intentions. The results indicate that customer perceptions about seals of approval and vendor-specific guarantees can significantly influence trusting intentions while perceptions about protections from credit card companies, legal systems and technology infrastructures do not.     

信息系统体系结构模式的比较与选择

简要地介绍了主要的信息系统体系结构模式,针对软硬件要求、开发投入、维护与功能扩展、安全与稳定等几个方面,分析了各种体系结构模式的性能以及不同体系结构对信息系统开发的影响,并以应用实例方式,介绍了信息系统体系结构选择的过程。     

一种发现非确定选择平行关系的过程挖掘算法

任务间非确定选择平行关系是业务流程中一种普遍存在的流程逻辑关系,利用传统的工作流网建模这种逻辑关系会导致模型中出现重复任务,为过程挖掘带来困难。基于事件日志定义了非确定选择平行关系,结合同步管理器给出了判定非确定选择平行关系的定理以及γ算法。γ算法克服了目前挖掘算法的限制,挖掘流程结构的同时挖掘管理操作行为,加强了过程挖掘的可适用性。实例分析表明了算法的有效性。     

群体间竞争与协作的遗传算法解决旅行商问题

旅行商问题是经典的NP难组合优化问题之一,快速有效地解决旅行商问题具有重要的理论和实际意义。受自然界物种群体间相互联系的启发,提出了群体间竞争与协作的遗传算法来解决旅行商问题。该算法在迭代的过程中,每次只选择竞争力大的种群进行进化,同时为了维持各个种群间发展的平衡,对它们进行周期性的交流,能促使进化过程中中好的基因模式迅速地在各个种群中传播,提高了整体的进化速度。此算法不但能有效地维持群体的多样性,而且能提高收敛的速度。通过对旅行商问题的仿真实验,证明了该算法的可行性与有效性。     

支持向量回归机在物价预测上的应用

把时间序列SVM预测模型应用于物价指数的预测,采用逐步递归的方法进行,同时注意尽量减少训练样本的浪费和充分挖掘SVM模型适合短期预测的潜力.分析结果表明,无论是拟合情况,还是预测值的检验和物价指数的实际规律来看,都有很高的精度,可以作为物价指数预测的一种行之有效的方法.