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1.
Many prominent intelligence tests (e.g., Wechsler Intelligence Scale for Children, Fifth Edition [WISC-V] and Reynolds Intellectual Abilities Scale, Second Edition [RIAS-2]) offer methods for computing subtest- and composite-level difference scores. This study uses data provided in the technical manual of the WISC-V and RIAS-2 to calculate reliability coefficients for difference scores. Subtest-level difference score reliabilities range from 0.59 to 0.99 for the RIAS-2 and from 0.53 to 0.87 for the WISC-V. Composite-level difference score reliabilities generally range from 0.23 to 0.95 for the RIAS-2 and from 0.36 to 0.87 for the WISC-V. Emphasis is placed on comparisons recommended by test publishers and a discussion of minimum requirements for interpretation of differences scores is provided.  相似文献   
2.
ABSTRACT

This article explores the current state of Occupational Social Work/Employee Assistance (OSW/EA) education. It examines the relationship between social work curricula, field placement experiences, and entry-level employment opportunities in the OSW/EA field. It is based on an educational initiative called the Partnership for Employee Assistance Education. Drawing on the OSW/EA literature, surveys, and focus group materials, the article concludes that the nature of OSW/EA is being reshaped by information technology, shifting demographics, globalization, and evolving terms and conditions of employment. The authors discuss how the graduate-level OSW/EA curriculum and field placements are being transformed to reflect these trends. Concepts such as Organizational Social Work and organizational intelligence are discussed. Innovative educational strategies are recommended. Finally, the authors argue that the contemporary workplace offers potential opportunity for innovative social work practice and education.  相似文献   
3.
人工智能相关技术的迅猛发展和逐步普及,使得情报学难以避免人工智能的融合趋势,无论这种融合是主动为之或是被动选择。然而学界对人工智能时代情报学学科的发展走向并未予以充分探讨,大部分研究均将焦点置于大数据与下一代互联网环境中进行论述。本研究将人工智能时代情报学学科走向解构为"本体论""感知论""方法论""服务论"四个论题,对每个论题借由理论面向与实践面向的二分法展开阐释,并从整体视角上提出应在人工智能洪流中找准情报学定位,不能忽视"人"在情报学中的价值以及重视跨学科融合、跨领域应用的发展趋势。  相似文献   
4.
The quality of decision and assessment of risk are key determinants of successful sport performance. Athletes differ fundamentally in their decision-making ability according to their athletic expertise level. Moreover, given the influence of emotions on decision-making, it is likely that a trait reflecting emotional functioning, trait emotional intelligence, may also influence decision-making. Therefore, the aim of this research was to investigate the respective contribution of athletic expertise and trait emotional intelligence to non-athletic decision-making. In total, 269 participants aged between 18 and 26 years with a range of athletic experience i.e. none (n?=?71), novice (n?=?54), amateur (n?=?55), elite (n?=?45) and super-elite (n?=?44), completed the Emotional Intelligence Scale and the Cambridge Gambling Task. Regression modelling indicated a significant positive relationship of athletic expertise and trait emotional intelligence with the quality of decision-making, and a negative relationship with deliberation time and risk-taking. Cognitive skills transfer may explain the higher decision-making scores associated with higher athletic expertise, while individuals with higher trait emotional intelligence may anticipate better the emotional consequences linked with a gambling task, which may help individuals make better decisions and take less risks.  相似文献   
5.
[目的/意义]将情报工程思维融入云平台驱动的应急决策,旨在使应急决策更具效率性、科学性。[方法/过程]分析应急决策需求特性,在工程价值模型和情报系统基础上引入情报工程思维,即"事实数据"+"方法工具"+"专家智慧"3个要素,进而构建云平台驱动的应急决策情报工程架构。[结果/结论]云平台驱动的应急决策情报工程架构根据函数效应,从需求层(聚合需求,甄选信息)、工作层(挖掘情报,提升价值)、运行层(整合知识,集成智慧)以及服务层(快速响应,精准服务)4方面构建,使应急决策情报工程化及平行化,为应急决策在实际应用中提供一定思路。  相似文献   
6.
[目的/意义]安全问题是当前国家、政府、企业、社会、大众及学界广泛关注的一个重要现实问题,而安全情报是保障安全的必用之宝,故安全情报研究具有十分重要的理论与现实意义。[方法/过程]运用文献分析法和思辨法,从安全科学学理角度出发,论证基于安全科学视角解读与界定安全情报概念的必要性、重要性与紧迫性,探讨安全情报概念的由来与演进趋势,并分析安全情报的涵义。[结果/结论]从安全科学学理角度看,从安全信息到安全情报的安全管理新认识是提出安全情报概念的根本动力,安全情报概念的总体演进趋势是从分散到统一。同时,从系统安全学角度看,安全情报是指所有影响系统安全行为的安全信息。  相似文献   
7.
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   
8.
Among existing knowledge graph based question answering (KGQA) methods, relation supervision methods require labeled intermediate relations for stepwise reasoning. To avoid this enormous cost of labeling on large-scale knowledge graphs, weak supervision methods, which use only the answer entity to evaluate rewards as supervision, have been introduced. However, lacking intermediate supervision raises the issue of sparse rewards, which may result in two types of incorrect reasoning path: (1) incorrectly reasoned relations, even when the final answer entity may be correct; (2) correctly reasoned relations in a wrong order, which leads to an incorrect answer entity. To address these issues, this paper considers the multi-hop KGQA task as a Markov decision process, and proposes a model based on Reward Integration and Policy Evaluation (RIPE). In this model, an integrated reward function is designed to evaluate the reasoning process by leveraging both terminal and instant rewards. The intermediate supervision for each single reasoning hop is constructed with regard to both the fitness of the taken action and the evaluation of the unreasoned information remained in the updated question embeddings. In addition, to lead the agent to the answer entity along the correct reasoning path, an evaluation network is designed to evaluate the taken action in each hop. Extensive ablation studies and comparative experiments are conducted on four KGQA benchmark datasets. The results demonstrate that the proposed model outperforms the state-of-the-art approaches in terms of answering accuracy.  相似文献   
9.
优秀的服装作品是设计师灵性的创造;灵性是服装设计师"自我"的呈现;灵性设计要兼顾艺术与实用的关系。  相似文献   
10.
章鱼在人工养殖环境中生活习性的探讨   总被引:4,自引:0,他引:4  
章鱼人工养殖前人做得很少,通过探讨人工养殖环境中章鱼的生活习性等,为科学养殖章鱼提供参考.  相似文献   
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