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.     

Our current understanding of lake ecosystem response to climate change: What have we really learned from the north temperate deep lakes?

Climatic change is recognized as an important factor capable of influencing the structural properties of aquatic ecosystems. Lake ecosystems are particularly sensitive to climate change. Several long time-series studies have shown close coupling between climate, lake thermal properties and individual organism physiology, population abundance, community structure, and food-web structure. Understanding the complex interplay between climate, hydrological variability, and ecosystem structure and functioning is essential to inform water resources risk assessment and fisheries management. The purpose of this paper is to present the current understanding of climate-induced changes on lake ecosystem phenology. We first review the ability of climate to modulate the interactions among lake hydrodynamics, chemical factors, and food-web structure in several north temperate deep lakes (e.g., Lake Washington, Lake Tahoe, Lake Constance, Lake Geneva, Lake Baikal, and Lake Zurich). Our aim is to assess long-term trends in the physical (e.g., temperature, timing of stratification, and duration of ice cover), chemical (e.g., nutrient concentrations), and biological (e.g., timing of the spring bloom, phytoplankton composition, and zooplankton abundance) characteristics of the lakes and to examine the signature of local weather conditions (e.g., air temperature and rainfall) and large-scale climatic variability (e.g., ENSO and PDO) on the lake physics, chemistry and biology. We also conducted modeling experiments to quantify the relative effect of climate change and nutrient loading on lake phenology. These modeling experiments focused on the relative changes to the major causal associations underlying plankton dynamics during the spring bloom and the summer stratified period. To further understand the importance of climate change on lakes, we propose two complementary directions of future research. First, additional research is needed to elucidate the wide array of in-lake processes that are likely to be affected by the climate change. Second, it is essential to examine the heterogeneity in responses among different water bodies. The rationale of this approach and its significance for dealing with the uncertainty that the climate signals cascade through lake ecosystems and shape abiotic variability and/or biotic responses have been recently advocated by several other synthesis papers.     

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。     

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。     

Institutional competition protects consumers: Public power vs. private power

The historical competition between public power and private power shows that retail customers have chosen the former to reduce costs and improve customer service. Research also shows that publicly owned utilities employ cost-minimizing algorithms, and that federal and state regulators favor the interests of investors over those of customers, undermining their obligation to protect consumer welfare. Institutional options matter and should be strongly encouraged.     

Hard multidimensional multiple choice knapsack problems, an empirical study

Recent advances in algorithms for the multidimensional multiple choice knapsack problems have enabled us to solve rather large problem instances. However, these algorithms are evaluated with very limited benchmark instances. In this study, we propose new methods to systematically generate comprehensive benchmark instances. Some instances with special correlation properties between parameters are found to be several orders of magnitude harder than those currently used for benchmarking the algorithms. Experiments on an existing exact algorithm and two generic solvers show that instances whose weights are uncorrelated with the profits are easier compared with weakly or strongly correlated cases. Instances with classes containing similar set of profits for items and with weights strongly correlated to the profits are the hardest among all instance groups investigated. These hard instances deserve further study and understanding their properties may shed light to better algorithms.     

Gender differences in computer attitudes and the choice of technology-related occupations in a sample of secondary students in Spain

The dearth of women in technology and ICT-related fields continues to be a topic of interest for both the scientific community and decision-makers. Research on attitudes towards computers proves that women display more negative computer attitudes than men and also make less intense use of technology and computers than their male counterparts. For this reason, the main aims of this study are threefold. Firstly, to analyze the existence of gender differences in three dimensions of computer attitudes in a group of 550 secondary students in Spain (mean of age = 15 years old; SD = 1.73). Secondly, to study the moderating influence of a group of contextual variables on those gender differences in computer attitudes. And thirdly, to examine the predictive role of computer attitudes on the intention to pursue technology-related occupations. Some of the analyses of variance carried out show more positive computer attitudes in boys than in girls. These differences are more salient among students coming from rural areas and the upper social class, who are also enrolled in the domain of technology in secondary education, and whose mothers have no occupation outside the home. Finally, simple logistic regressions were carried out in order to prove that all dimensions of computer attitudes predict the enrollment intentions to pursue technology-related occupations. Nonetheless, gender only moderates the relationship between the cognitive dimension of computer attitudes and the enrollment intentions to pursue technology-related occupations.     

智能控制课双语教学改革

智能控制课采用双语教学有助于学生更好地掌握理论、了解国际先进的智能控制技术,但是教学内容的选择、教材和英语讲解始终是困扰双语教学的问题。教学内容要理论联系工程应用,教材使用中英文对照形式,着重基本概念和理论的原著解释、实例。英语讲授比例宜灵活掌握,淡化英语口语,着重专业词汇和专业原文阅读,并结合专业软件的应用。     

基于前景值的多类型出行者逐日路径选择模型

为研究非平衡态下的出行者逐日路径选择行为,以前景理论为基础,综合考虑出行者对路网随机性和逐日路径调整行为中的有限理性,基于出行经验数据逐日更新预留出行时间参考点,根据有限记忆规则和理解行程时间更新计算逐日路径前景值,并构建基于转移系数的逐日流量更新规则。最后结合算例分析了有限理性、完全理性、完全历史信息和非完全历史信息出行者所占比例及预留行程时间可靠度值对路网达到平衡态的演化时间及最终流量分布状态的影响。