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1.
Nowadays assuring that search and recommendation systems are fair and do not apply discrimination among any kind of population has become of paramount importance. This is also highlighted by some of the sustainable development goals proposed by the United Nations. Those systems typically rely on machine learning algorithms that solve the classification task. Although the problem of fairness has been widely addressed in binary classification, unfortunately, the fairness of multi-class classification problem needs to be further investigated lacking well-established solutions. For the aforementioned reasons, in this paper, we present the Debiaser for Multiple Variables (DEMV), an approach able to mitigate unbalanced groups bias (i.e., bias caused by an unequal distribution of instances in the population) in both binary and multi-class classification problems with multiple sensitive variables. The proposed method is compared, under several conditions, with a set of well-established baselines using different categories of classifiers. At first we conduct a specific study to understand which is the best generation strategies and their impact on DEMV’s ability to improve fairness. Then, we evaluate our method on a heterogeneous set of datasets and we show how it overcomes the established algorithms of the literature in the multi-class classification setting and in the binary classification setting when more than two sensitive variables are involved. Finally, based on the conducted experiments, we discuss strengths and weaknesses of our method and of the other baselines.  相似文献   
2.
The massive number of Internet of Things (IoT) devices connected to the Internet is continuously increasing. The operations of these devices rely on consuming huge amounts of energy. Power limitation is a major issue hindering the operation of IoT applications and services. To improve operational visibility, Low-power devices which constitute IoT networks, drive the need for sustainable sources of energy to carry out their tasks for a prolonged period of time. Moreover, the means to ensure energy sustainability and QoS must consider the stochastic nature of the energy supplies and dynamic IoT environments. Artificial Intelligence (AI) enhanced protocols and algorithms are capable of predicting and forecasting demand as well as providing leverage at different stages of energy use to supply. AI will improve the efficiency of energy infrastructure and decrease waste in distributed energy systems, ensuring their long-term viability. In this paper, we conduct a survey to explore enhanced AI-based solutions to achieve energy sustainability in IoT applications. AI is relevant through the integration of various Machine Learning (ML) and Swarm Intelligence (SI) techniques in the design of existing protocols. ML mechanisms used in the literature include variously supervised and unsupervised learning methods as well as reinforcement learning (RL) solutions. The survey constitutes a complete guideline for readers who wish to get acquainted with recent development and research advances in AI-based energy sustainability in IoT Networks. The survey also explores the different open issues and challenges.  相似文献   
3.
共享经济行业可持续性评价的社会感知和客观绩效不一致将造成认知错位、投资误判和政策失效等结果。本文在线挖掘2017—2019年我国主要社交媒体上29 771条文本信息,并收集行业统计数据,综合测度共享经济行业的可持续性并比较其差异。研究发现:社会公众并不认为共享经济行业具有显著的总体可持续性,而且行业实际绩效展现的可持续性与社会大众认知截然不同。进一步发现:受限于主观认知能力,社会公众认为共享经济可持续性主要来自可观察到的行业外部经济和外部生态等维度,但客观绩效表明共享经济行业内部的经济和外部的技术优势才是其可持续性的重要支撑。此外,二者评价的差异在住宿与医疗等产能共享内部过程不易被大众观察的行业中最为突出。  相似文献   
4.
The focus of this paper is on a group of pupils with reading and writing difficulties who have been participating in an intervention study using assistive technology. That intervention study contained supervised training sessions with reading and writing tasks using an iPad with special supportive applications. The current study is a qualitative investigation of whether there has been any transfer from the intervention, to the pupils’ everyday school activities. Interviews with pupils and their teachers and observations during classroom lectures have been used to collect data. The results show that the pupils were positive to the assistive technology (the applications on the iPads), they found the apps easy to learn how to use and they appreciated the benefits they could give. Even so, only a few of the pupils had found use for and continued to use the tools after the intervention period finished. Possible reasons are that when the novelty wore off, students reverted to their usual study habits and that older students with many teachers and different classrooms were less able to adapt to using the apps. To improve transfer, it is suggested to introduce assistive technology earlier to students, in the younger grades, before study habits have been formed and to inform teachers about the use of AT in the classroom, including what is available and how it can benefit students.  相似文献   
5.
[目的/意义] 比较分析数据管理与数据治理差异与联系,为制定科学数据开放共享政策提供参考。[方法/过程] 运用比较分析法,解析数据管理与数据治理在定义与内涵、功能、目标、原则、焦点领域5个方面的异同,由此解析其对制定我国科学数据开放共享政策的启示。[结果/结论] 数据管理与数据治理在定义与内涵、功能、目标、原则、焦点领域上都有显著差异,但两者也有内在联系。数据治理是成功实施数据管理的关键。认清两者的关系有助于明晰目前我国科学数据管理政策的不足之处,为今后完善科学数据管理办法提供参考,从而规划与制定实用的科学数据开放共享细则。  相似文献   
6.
《左传》是我国首部以编年为次序、以鲁国十二公为传主,系统记述春秋战国时期历史,对中国文化产生了巨大影响的文史作品。文章在概述《左传》文化价值的基础上,梳理了两千多年来关于《左传》文本与作者的主要学术争论,甄别《左传》流变过程中的22个关键文本。  相似文献   
7.
全民都获取全面的健康是能否成为强国的重要标准之一,是"以人为本"的基本体现。在健康中国行动的背景下,国家越来越重视以体育健身来促进人民的健康发展,也相继出台了一系列关于全民健康相关的文件和纲要。本文通过对国内国外研究现状进行了分析,通过对体育健康的梳理,了解体育健康目前发展现状,分析不足之处,为体育健康在以后的界定打下基础。  相似文献   
8.
与其他的体育运动项目相比,田径运动的历史要悠久许多。在田径运动项目中,成绩高低与田径训练中使用的训练方式有着很大的关联,同时田径训练方式的使用得当与否对于运动员的心理素质、训练效率、运动负荷等方面的提升有着十分显著的影响。本文就从当前的田径训练方式的特征分析出发,并以此为基础展望了未来田径训练方式的发展新趋势,以期对今后的田径训练方式发展提供相应的帮助。  相似文献   
9.
CBA2016-2017赛季常规赛已经结束,通过数据分析法、逻辑分析法等对20支队伍在常规赛38轮的比赛数据(如攻防效率、主场优势、与季后赛队伍和非季后赛队伍比赛的差异、每节净胜分、逆转能力)进行统计分析。针对中国男篮在攻防效率,球队队员的心理承受能力及外援的引进等方面提出发展对策,旨在为CBA及中国男篮的发展提供理论参考。  相似文献   
10.
社会快速发展、生活日趋便捷背景下,医学生面临着生理和心理上的问题,且医学生由于专业特殊性,认知能力中记忆力的重要性被凸显出来。本文运用查阅文献资料、专家访谈、问卷调查、逻辑分析等研究方法,探究从运动处方角度出发的实验--"高强度间歇运动对医学生不同时长记忆力的影响"具有多方面重要性。同时建议医学院校应当跟据研究结果和实际情况,制定科学、合理的运动训练计划,为医学生生理和心理健康提供保障。  相似文献   
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