Sport and the obligation of solidarity

The paper departs from an analysis of the case of Michelle Dumaresq, a transgender female downhill mountain biker who experienced marginalization within her sport. The analysis is based on Axel Honneth’s theory of recognition. The Dumaresq case is particularly relevant to Honneth’s ideas of solidarity, which provide insight into the dynamics of social integration. Honneth’s theory of recognition also provides a conceptual framework and a methodology that gives new perspectives on the ethical significance of sport. In the paper, an analysis is presented of the lack of solidarity experienced by Dumaresq. The argument is made that sport has a particular potential for realizing solidarity among its practitioners. Realizing solidarity however depends to a large degree upon that the rules of sport are perceived as fair and just. In the Dumaresq case, challenges to solidarity came from what her competitors considered to be unfair classification rules. Summing up, it is argued that, as long as the rules of a sport is perceived as fair and just, voluntary engagement gives rise not only to obligations on fair play but to a moral obligation on solidarity as well.     

易学的推类逻辑

易学中的逻辑问题,是一个在易学和逻辑学研究中被忽视的问题,但又是一个关系到对中国文化史、思想史和逻辑史的再认识的重要问题。易学中的逻辑是推类逻辑,本文给出了理由,同时以现代逻辑的方法给出了易学推类逻辑的形式系统,并作了讨论。指出易学逻辑是在中国文化背景下的以汉字表述的特有逻辑形式,建立了中国古代的普遍语言,形成了自我满足的语义系统,其在为人们提供正确的认识方法和为古代科学提供认识工具方面与西方逻辑是一致的。     

Age and Education Differences in Marriages and their Effects on Life Satisfaction

Within marriages husbands typically tend to be older and higher educated than their wife. This paper tries to explain this by analyzing whether age and education differences between spouses have an effect on happiness. Two alternative hypotheses are tested on the relation between age and education gaps between partners and life satisfaction. It is found that a positive age gap between husband and wife increases both male and female life satisfaction, while female life satisfaction increases if the education gap is smaller.     

背景知识对4~8岁儿童和大学生分类活动的影响

以4-8岁儿童和大学生为被试,用虚拟生物图片为材料,采用2(不提供背景知识和提供背景知识)×6(年龄)的实验设计,考察背景知识对被试分类活动的影响及其年龄特点。结果发现:(1)两种实验条件下均有显著的年龄差异。(2)提供背景知识与否对不同年龄被试分类活动的影响不同,对4-5岁儿童分类活动的影响不显著,对6-8岁儿童及大学生分类活动的影响显著。     

Human factors of transitions in automated driving: A general framework and literature survey

The topic of transitions in automated driving is becoming important now that cars are automated to ever greater extents. This paper proposes a theoretical framework to support and align human factors research on transitions in automated driving. Driving states are defined based on the allocation of primary driving tasks (i.e., lateral control, longitudinal control, and monitoring) between the driver and the automation. A transition in automated driving is defined as the process during which the human-automation system changes from one driving state to another, with transitions of monitoring activity and transitions of control being among the possibilities. Based on ‘Is the transition required?’, ‘Who initiates the transition?’, and ‘Who is in control after the transition?’, we define six types of control transitions between the driver and automation: (1) Optional Driver-Initiated Driver-in-Control, (2) Mandatory Driver-Initiated Driver-in-Control, (3) Optional Driver-Initiated Automation-in-Control, (4) Mandatory Driver-Initiated Automation-in-Control, (5) Automation-Initiated Driver-in-Control, and (6) Automation-Initiated Automation-in-Control. Use cases per transition type are introduced. Finally, we interpret previous experimental studies on transitions using our framework and identify areas for future research. We conclude that our framework of driving states and transitions is an important complement to the levels of automation proposed by transportation agencies, because it describes what the driver and automation are doing, rather than should be doing, at a moment of time.     

宗教对信徒颜色认知的影响及作用机制:以中国台湾宗教信徒为例

采用自然分类法考察中国台湾佛教徒、道教徒、基督徒和非宗教信徒的基本颜色词分类,并做多维标度和聚类分析,以揭示宗教对信徒颜色认知的影响。结果发现,中国台湾三大宗教信徒对基本颜色词的分类既具有共性,又存在差异,宗教信徒与非宗教信徒的基本颜色词分类也存在着共性和差异,共性反映了汉语言和汉文化的影响,差异反映了宗教对颜色认知的影响。研究表明,颜色通过意象式传播方式影响信徒的颜色认知,支持颜色词与颜色认知的相互作用理论。     

The Politics of Biometric Standards: The Case of Israel Biometric Project

In 2017, after years of public debate, Israel ratified a national biometric project consisting of two initiatives: issuing of biometric ID cards and passports to all Israeli citizens and establishment of a centralized database for storing their bodily information. Design and implementation of a preceding four-year pilot study were accompanied by extensive standardization. Discourse and standard analyses of 33 official state documents – from legal records to performance reports – published by Israeli authorities during the pilot study, unravel the politics of biometric standards employed as part of this project. Biometric standards were used to establish hierarchies between individuals and groups by defining particular bodies as ‘biometrically ineligible.’ These individuals are mostly members of underprivileged and marginalized social groups. Biometric standards were also constructed discursively as scientific and objective to legitimize such discriminatory treatment. Israeli authorities used standards strategically, both as infrastructural elements and as a discursive means. As infrastructural elements, biometric standards were employed, inter alia, to achieve predetermined results and confirm the project’s success. As a discursive means, Israeli authorities actively adopted a ‘discourse of standardization’ to construct an objective and fair image to the project. Standardization of people – namely, quantification of lives, bodies and experiences – is inherently discriminatory because it necessarily results in the creation of categories and hierarchies between biometrically in/eligible bodies.     

Intelligent digital image firewall system for filtering privacy or sensitive images

As the commonest part of social networks, sharing images in social network not only provides more information, but also gives more intuitive view than text. However, images also can leak out information more easily than text, so the audit of image content is particularly essential. The disclosure of a tiny image, which involves sensitive information about individual, society even the state, may trigger a series of serious problems. In this paper, we design a kind of intelligent image firewall to detect and filter sensitive or privacy images. Two different approaches of the firewall are proposed. In the first approach, we propose an image firewall based on joint sparse representation, which can provide accurate and robust privacy prediction, and also can provide rich spatial relationship information. In the second approach, we propose a method based on the deep learning (Faster RCNN), which can predict the privacy relationships or actions (like kiss, hug and hand in hand) among the persons of an image. Experimental results show the effectiveness of the two kinds of approaches.     

Feature selection using Ant Colony Optimization (ACO) and Road Sign Detection and Recognition (RSDR) system

Road Sign Detection and Recognition (RSDR) is aimed to enable drivers maintain basic functionality with the aim of identifying and notifying driver through the existing restrictions so that the process is a success on the present widened road. Examples for RSDR include ‘traffic light ahead’ or ‘pedestrian crossing’ signs. An innovative RSDR system has been introduced which comprises of pre-processing, edge detection, feature extraction, features selection and Ensemble Fuzzy Support Vector Machine (EFSVM) classifier. Feature selection is carried out successfully by deployment of Ant Colony Optimization (ACO) algorithm to determine most prominent and definitive features. These features are then fed into the ensemble SVM to enable both road side traffic detection as well as recognition. Suggested system’s performance is analyzed and evaluated with respect to road signs having a capable recognition rate.     

Linking property crime using offender crime scene behaviour: A comparison of methods

This study compared the ability of seven statistical models to distinguish between linked and unlinked crimes. The seven models utilised geographical, temporal, and modus operandi information relating to residential burglaries (n = 180), commercial robberies, (n = 118), and car thefts (n = 376). Model performance was assessed using receiver operating characteristic analysis and by examining the success with which the seven models could successfully prioritise linked over unlinked crimes. The regression‐based and probabilistic models achieved comparable accuracy and were generally more accurate than the tree‐based models tested in this study. The Logistic algorithm achieved the highest area under the curve (AUC) for residential burglary (AUC = 0.903) and commercial robbery (AUC = 0.830) and the SimpleLogistic algorithm achieving the highest for car theft (AUC = 0.820). The findings also indicated that discrimination accuracy is maximised (in some situations) if behavioural domains are utilised rather than individual crime scene behaviours and that the AUC should not be used as the sole measure of accuracy in behavioural crime linkage research.