Perception of Artificial Intelligence in Spain

This paper analyses the perception of Artificial Intelligence (AI) by individuals in Spain and the factors associated with it. It uses data from 6308 individuals from a 2018 Spanish survey. A binary logit regression model is formulated and estimated for the attitude towards robots and AI and its possible determinants. As main results are that a gender gap is detected, and that people have a negative attitude if they are not interested in scientific discoveries and technological developments and if AI and robots are not useful at work.     

“感知与人机交互”教学实践与PBL模式探索

机器人工程是在国家新工科发展战略背景下为了适应机器人专业人才需求而新近创建的专业。本文依托东南大学机器人工程专业教学体系，介绍了“感知与人机交互”课程的教学实践，探索了PBL教学模式在本门课程中的应用。具体介绍了课程教学内容设置、PBL教学方案例设计及存在问题分析等，可为自动化类机器人工程专业的相关课程教学实践提供参考。     

Effect of in-app components,medium, and screen size of electronic textbooks on reading performance,behavior, and perception

Although many app-based textbooks are available for students, reading have not been thoroughly outlined. This study aimed to understand how changes from paper to electronic textbooks have affected the academic reading task, investigate student users’ perceptions of in-app components and screen sizes, and identify issues affecting in-app components and task requirements. A mixed factorial design experiment was employed. Results showed that there were no significant changes in comprehension and time spent reading between print text and the iPad. Yet, student highlighting, notetaking, and reading behavior and perception significantly changed based on condition. In addition, students struggled to use in-app components and found them frustrating especially when accounting for sentence splitting. The findings presented can assist in understanding the changes in student reading behavior, which can be used to improve interface design of future e-textbooks.     

Prediction maintenance integrated decision-making approach supported by digital twin-driven cooperative awareness and interconnection framework

Predictive maintenance is one of the important technical means to guarantee and improve the normal industrial production. The existing bottlenecks for popularization and application are analyzed. In order to solve these problems, a cooperative awareness and interconnection framework across multiple organizations for total factors that affect prediction maintenance decision-making is discussed. Initially, the structure and operation mechanism of this framework are proposed. It is designed to support the sharing of data, knowledge and resources. As a key supporting technology, the digital twin is also integrated into it to improve the accuracy of fault diagnosis and prediction and support making a maintenance plan with higher accuracy and reliability. Then, under this framework, an integrated mathematical programming model is established with considering the parameter uncertainty and an NSGA-II hybrid algorithm is utilized to solve it. Moreover, an adjustment strategy for a maintenance plan is discussed in response to the dynamic characteristics of the actual maintenance environment. Finally, a case, prediction maintenance decision-making for bearings in grinding rolls of the large vertical mill, is studied. Analysis results verify the advantage of the integrated solving mechanism based on the proposed framework. The framework and integrated decision-making approach can guide the implementation of predictive maintenance with higher accuracy and reliability for industrial enterprises.     

Analyzing negative SNS behaviors of elementary and middle school students in Korea

With the growing speed of SNS accelerated recently, there are increasing concerns about the possibility of young students doing negative SNS behavior. This study tried to discover the relationship between various variables such as gender, grade, SNS usage time, motives to use SNS, degree of using advanced functions of SNS, SNS dependency, and perceptions about SNS with negative SNS behaviors among elementary and middle school students. The analyses revealed that regardless of gender and grade, the most frequently committed negative behavior is ‘stealing others’ private information’ and the least is ‘cyber bullying’, while ‘contacting strangers’ showing the most significant increase with the age. With the seriousness of negative SNS behaviors classified into four levels, it was found that the biggest significant difference across the levels appears on illegal use of photos and videos, followed by on verbal abuse and on cyber bullying. It was also found that a significant positive correlation exists between each of the factors considered and the negative SNS behavior. Based on these findings, a regression analysis was conducted to successfully extract several factors as significant predictors of the negative SNS behaviors. Furthermore, factors distinguishing the lowest level from the highest level of the negative SNS behaviors were identified to be gender, SNS dependency, utilization of advanced SNS functions, and grade, with its accuracy rate reaching as high as 85.6%.     

On the contribution of the senses to food emotional experience

Emotions are an important component of our daily lives and contribute to behavior as well as general well-being. Foods are prominent sources of emotions (e.g. enjoyment, disgust…). One question that may arise in food research is how the different senses interact to create a unified affective representation of food. Indeed, current research suggests that rather than a unimodal processing of each sensory aspect of a food, there is a very early and almost undistinguishable integration of the senses, especially for the construction of flavor. In the present paper, we argue that a multisensory approach is necessary to understand the way senses converge to enable an emotional experience when perceiving food. We further put an emphasis on the fact that such multisensory integration is influenced by higher-order cognitive processes and possibly by emotions as well. After presenting theories in the field as well as experimental data, we discuss some paradigms that could pave the way for future research on food-induced emotional processing.     

旅游驱动的少数民族建筑景观变迁研究——以九寨沟为例

旅游发展驱动的少数民族建筑景观的变迁,是旅游对区域文化影响的重要表现.文章通过对九寨沟树正寨的实地问卷与深入访谈调查,分析了居民和游客对藏寨建筑景观特色变迁的感知,认为居民对藏寨建筑景观的特色并没有清晰的认识,保护没有得到重视,而游客也缺乏对真实藏族传统文化的认识.研究认为,少数民族旅游地传统民族文化的保护,重在认清民族文化的差异和精华,增强当地居民的自我认同,促进社区居民参与旅游规划和管理,培养主人意识,形成对民族文化保护和传承的自觉性;同时还需要深化旅游地的管理,以引导为主,积极应对经济水平提高以后居民对生活环境改造的合理要求.     

利用MR大数据提升3G用户感知研究

运用大数据挖掘原理,对海量3G终端MR数据进行深入研究。从解决用户感知、用户体验方面入手,寻找网络质量规律,并在优化实例中予以应用。丰富了优化手段,取得良好效果,提高了优化效率,为深度优化提供了新思路。     

从“嗅”到“景”：嗅觉景观研究方法与设计理论综述

人、气味和建筑环境之间的相互 关系,成为过去十多年来嗅觉景观研究的焦 点。本文从气体测量与扩散模拟、嗅觉感知 评估、嗅觉的交叉模式研究、模拟和复制嗅 觉环境、人工智能与大数据研究等五个方面 系统性地回顾了嗅觉景观的研究方法。结合 案例,作者提出了从宏观（城市）、中观（街 道）、微观（人）尺度营造城市嗅觉景观的 设计方法,并指出嗅景设计中应当考虑包容 性。最后展望了未来嗅觉景观的研究方向。