Social equity and equity in higher education: A comparison of the liberal Anglo-American and Chinese political cultures     

《International Journal of Educational Development》2021

This study compares the ideas of social equity in the liberal Anglo-American and Chinese political cultures and seeks potential hybridisations. Through a conceptual examination of scholarly works, this study identifies differences and similarities of social equity between the two political cultures. A common conceptual bridge, deriving from the comparison and hybridisation, is further developed for the discussion of social equity and equity in higher education across the two cultures. The common bridge consists of four constitutes of social equity: political and civil equality, social and economic equality, equality of opportunity and equality of potential and freedom to achieve, the last of which is new hybridity of the two political cultures. This study argues that the hybridity – equality of potential and freedom to achieve – is enlightening to the discussion of equity in higher education as well as social equity across contexts.  相似文献   

“健康中国2030”背景下全民健身与全民健康深度融合发展的基本态势及发展策略     

白杨  王家宏 《武汉体育学院学报》2021,54(11):41-49

运用文献资料法对"健康中国2030"背景下全民健身与全民健康深度融合发展的基本态势进行梳理，剖析深度融合的薄弱环节及解决路径。全民健身与全民健康进行深度融合的发展趋势及态势集中体现在习近平总书记关于全民健身以及全民健康的一系列重要讲话、国家政策支撑、发展成果、成果转化与应用四个方面。深度融合存在协同体制机制障碍、法律法规缺失或不完善、供需矛盾协调障碍、交叉领域专业人才不足等薄弱环节。研究建议：需从部门融合和联合设置工作小组、部门和地方政策法规融合及保持延续性、资源融合与供需两端改革、专业融合和人才融合等四条路径进行改革，全方位推进全民健身与全民健康的深度融合发展。  相似文献   

文化功能视角下江口“金钱杆”的发展逻辑研究     

陈伟 《中华武术(研究)》2021,(1):119-121

文化功能也就是"出之于人,归之于人",江口土家族"金钱杆"起于秦末时期的西楚霸王,形于族人生产生活实践中。经过研究发现,"金钱杆"是具有彰显土家族文化的独特符号、"常"与"非常"之间转换的独特节点、教化孩童的重要载体以及增强体质的独特途径的少数民族传统体育活动。本研究主要探求"金钱杆"发展逻辑,旨在为"金钱杆"的传承和发展提供有益的指导。  相似文献   

High fidelity LPV systems under constraints     

《Journal of The Franklin Institute》2022,359(6):2755-2757

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A multimodal time-series method for gifting prediction in live streaming platforms     

《Information processing & management》2023,60(3):103254

Viewer gifting is an important business mode in live streaming industry, which closely relates to the income of the platforms and streamers. Previous studies on gifting prediction are often limited to cross-section data and consider the problem from the macro perspective of the whole live streaming. However, the multimodal information and the time accumulation effect of live streaming content on viewer gifting behavior are ignored. In this paper, we put forward a multimodal time-series method (MTM) for predicting real-time gifting. The core module of the method is the multimodal time-series analysis (MTA), which targets at effectively fusing multimodal information. Specifically, the proposed orthogonal projection (OP) model can promote cross-modal information interaction without introducing additional parameters. To achieve the interaction of multi-modal information at the same level, we also design a stackable joint representation layer, which makes each target modality's representation (visual, acoustic and textual modality) can benefit from all the other modalities. The residual connections are introduced as well to ensure the integration of low-level and high-level information. On our dataset, our model shows improved performance compared to other advanced models by at least 8% on F1. Meanwhile, the MTA is able to meet the real-time requirements of the live streaming setting, and has demonstrated its robustness and transferability in other tasks. Our research may offer some insights about how to efficiently fuse multimodal information, and contribute to the research on viewer gifting behavior prediction in the live streaming context.  相似文献   

Information analysis for dynamic sale planning by AI decision support process     

《Information processing & management》2023,60(3):103319

Marketing is all about finding out what your customers want and need. The information is used to create the model and improve the quality of products and services to satisfy customers. There are two major parts to a sale's planning: containing sales tactics and sales strategy. To aid in business decision-making, a data warehouse (DW) for sales collects and organizes relevant and historical data. DW is also a method for combining data from various heterogeneous databases (DB) and other sources of information for analysis. In this paper, Information analysis for dynamic Sale planning by AI Decision support process was done. Particle Swarm Optimization (PSO) and Quantum Particle Swarm Optimization (QPSO) algorithms have been used to find optimal MVs for sale planning since several authors prove that these algorithms are better than other existing algorithms. MVs selection is based on three factors: time running of MVs, area of MVs, and access frequency of MVs by manipulating the selection result using a weighted combination of each factor as needed by the designer. For PSO, the most cost of frequency was 1.924 for View (V) 11, while for QPSO, it was 1.722 for V11. For PSO, the most cost of time was 1.931 for V2, while for QPSO, it was 1.221 for V22. For PSO, the most cost of the area was 1.800 for V17, while for QPSO, it was 1.071 for V17. The results revealed that Quantum Particle Swarm Optimization is much more accurate than Particle Swarm Optimization.  相似文献   

A novel DL-based algorithm integrating medical knowledge graph and doctor modeling for Q&A pair matching in OHP     

《Information processing & management》2023,60(3):103322

Using AI technology to automatically match Q&A pairs on online health platforms (OHP) can improve the efficiency of doctor-patient interaction. However, previous methods often neglected to fully exploit rich information contained in OHP, especially the medical expertise that could be leveraged through medical text modeling. Therefore, this paper proposes a model named MKGA-DM-NN, which first uses the named entities of the medical knowledge graph (KG) to identify the intention of the problem, and then uses graph embedding technology to learn the representation of entities and entity relationships in the KG. The proposed model also employs the relationship between entities in KG to optimize the hybrid attention mechanism. In addition, doctors' historical Q&A records on OHP are used to learn modeling doctors’ expertise to improve the accuracy of Q&A matching. This method is helpful to bridge the semantic gap of text and improve the accuracy and interpretability of medical Q&A matching. Through experiments on a real dataset from a Chinese well-known OHP, our model has been verified to be superior to the baseline models. The accuracy of our model is 4.4% higher than the best baseline model. The cost-sensitive error of our model is 13.53% lower than that of the best baseline model. The ablation experiment shows that the accuracy rate can be significantly improved by 8.72% by adding the doctor modeling module, and the cost-sensitive error can be significantly reduced by 17.27% by adding the medical KG module.  相似文献   

Auditing fairness under unawareness through counterfactual reasoning     

《Information processing & management》2023,60(2):103224

Artificial intelligence (AI) is rapidly becoming the pivotal solution to support critical judgments in many life-changing decisions. In fact, a biased AI tool can be particularly harmful since these systems can contribute to or demote people’s well-being. Consequently, government regulations are introducing specific rules to prohibit the use of sensitive features (e.g., gender, race, religion) in the algorithm’s decision-making process to avoid unfair outcomes. Unfortunately, such restrictions may not be sufficient to protect people from unfair decisions as algorithms can still behave in a discriminatory manner. Indeed, even when sensitive features are omitted (fairness through unawareness), they could be somehow related to other features, named proxy features. This study shows how to unveil whether a black-box model, complying with the regulations, is still biased or not. We propose an end-to-end bias detection approach exploiting a counterfactual reasoning module and an external classifier for sensitive features. In detail, the counterfactual analysis finds the minimum cost variations that grant a positive outcome, while the classifier detects non-linear patterns of non-sensitive features that proxy sensitive characteristics. The experimental evaluation reveals the proposed method’s efficacy in detecting classifiers that learn from proxy features. We also scrutinize the impact of state-of-the-art debiasing algorithms in alleviating the proxy feature problem.  相似文献   

Responsible and human centric AI-based insurance advisors     

《Information processing & management》2023,60(3):103273

The domain about what it means to give responsible and human centric recommendations in the context of Artificial Intelligence (AI)-based insurance has not yet been fully explored. In this article, we therefore, first provide an in-depth analysis and perform a systematic literature review on (i) the specifications and requirements for such systems from a regulation point of view, (ii) instructions on which data they can rely upon, (iii) which recommender techniques can be used for developing such an advisor, (iv) off-the-shelf components for the trustworthy, responsible, and ethical behavior of this AI-empowered tool. Then, we present a novel approach, based on AI, to suggest insurance coverage for users and families, as well as instructions on how to design such a system. The solution, as proposed in our paper, will be transparent, trustworthy, and responsible to the final users and thus, hopefully, better accepted by customers. After describing a possible system design and architecture, we critically discuss the challenges and opportunities for the deployment of such systems in insurance companies.  相似文献   

2022 Bower Award for Business Leadership presented to téphane Bancel; Albert Bourla,DVM, Ph.D.; and Alex Gorsky     

《Journal of The Franklin Institute》2022,359(18):10285-10287

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