Difference score reliabilities within the RIAS-2 and WISC-V     

Ryan L. Farmer  Samuel Y. Kim 《Psychology in the schools》2020,57(8):1273-1288

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   

RGAN-EL: A GAN and ensemble learning-based hybrid approach for imbalanced data classification     

《Information processing & management》2023,60(2):103235

Imbalanced sample distribution is usually the main reason for the performance degradation of machine learning algorithms. Based on this, this study proposes a hybrid framework (RGAN-EL) combining generative adversarial networks and ensemble learning method to improve the classification performance of imbalanced data. Firstly, we propose a training sample selection strategy based on roulette wheel selection method to make GAN pay more attention to the class overlapping area when fitting the sample distribution. Secondly, we design two kinds of generator training loss, and propose a noise sample filtering method to improve the quality of generated samples. Then, minority class samples are oversampled using the improved RGAN to obtain a balanced training sample set. Finally, combined with the ensemble learning strategy, the final training and prediction are carried out. We conducted experiments on 41 real imbalanced data sets using two evaluation indexes: F1-score and AUC. Specifically, we compare RGAN-EL with six typical ensemble learning; RGAN is compared with three typical GAN models. The experimental results show that RGAN-EL is significantly better than the other six ensemble learning methods, and RGAN is greatly improved compared with three classical GAN models.  相似文献   

Creating value from Social Big Data: Implications for Smart Tourism Destinations     

Pasquale Del Vecchio  Gioconda Mele  Valentina Ndou  Giustina Secundo 《Information processing & management》2018,54(5):847-860

This paper aims to demonstrate how the huge amount of Social Big Data available from tourists can nurture the value creation process for a Smart Tourism Destination. Applying a multiple-case study analysis, the paper explores a set of regional tourist experiences related to a Southern European region and destination, to derive patterns and opportunities of value creation generated by Big Data in tourism. Findings present and discuss evidence in terms of improving decision-making, creating marketing strategies with more personalized offerings, transparency and trust in dialogue with customers and stakeholders, and emergence of new business models. Finally, implications are presented for researchers and practitioners interested in the managerial exploitation of Big Data in the context of information-intensive industries and mainly in Tourism.  相似文献   

Occupational Social Work Education for Employee Assistance Practice     

Daniel Hughes  Carly Newhouse 《Journal of Teaching in Social Work》2018,38(4):379-397

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   

Remaining in Control with an Illusion of Interactivity: The Paternalistic Side of Data Journalism*     

Ester Appelgren 《Journalism Practice》2019,13(8):956-960

  相似文献   

人工智能时代情报学发展走向之辨——对本体论、感知论、方法论、服务论的再思考     

曹文振  赖纪瑶  王延飞 《情报学报》2020,39(5):557-564

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   

MARC to BIBFRAME: Converting the PCC to Linked Data     

Jacquie Samples  Ian Bigelow 《Cataloging & classification quarterly》2020,58(3-4):403-417

Abstract

The Program for Cooperative Cataloging (PCC) has formal relationships with the Library of Congress (LC), Share-VDE, and Linked Data for Production Phase 2 (LD4P2) for work on Bibliographic Framework (BIBFRAME), and PCC institutions have been very active in the exploration of MARC to BIBFRAME conversion processes. This article will review the involvement of PCC in the development of BIBFRAME and examine the work of LC, Share-VDE, and LD4P2 on MARC to BIBFRAME conversion. It will conclude with a discussion of areas for further exploration by the PCC leading up to the creation of PCC conversion specifications and PCC BIBFRAME data.  相似文献   

Using an interactive platform to recognize the intersection of social and spatial inequalities     

Lisa Poling  Travis Weiland 《Teaching Statistics》2020,42(3):108-116

With the creation of interactive tasks that allow students to explore spatial ways of knowing in conjunction with their other ways of knowing the world, we create a space where students can make sense of information as they organize these new ideas into their already existing schema. Through the use of a Common Online Data Analysis Platform (CODAP) and data from Public Use Microdata Areas (PUMA), students can explore the communities in which they live and work, critically examining opportunities and challenges within a defined space.  相似文献   

The effect of athletic expertise and trait emotional intelligence on decision-making     

Robert Vaughan  Sylvain Laborde  Christopher McConville 《European Journal of Sport Science》2019,19(2):225-233

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   

Cross-company customer churn prediction in telecommunication: A comparison of data transformation methods     

《International Journal of Information Management》2019

Cross-Company Churn Prediction (CCCP) is a domain of research where one company (target) is lacking enough data and can use data from another company (source) to predict customer churn successfully. To support CCCP, the cross-company data is usually transformed to a set of similar normal distribution of target company data prior to building a CCCP model. However, it is still unclear which data transformation method is most effective in CCCP. Also, the impact of data transformation methods on CCCP model performance using different classifiers have not been comprehensively explored in the telecommunication sector. In this study, we devised a model for CCCP using data transformation methods (i.e., log, z-score, rank and box-cox) and presented not only an extensive comparison to validate the impact of these transformation methods in CCCP, but also evaluated the performance of underlying baseline classifiers (i.e., Naive Bayes (NB), K-Nearest Neighbour (KNN), Gradient Boosted Tree (GBT), Single Rule Induction (SRI) and Deep learner Neural net (DP)) for customer churn prediction in telecommunication sector using the above mentioned data transformation methods. We performed experiments on publicly available datasets related to the telecommunication sector. The results demonstrated that most of the data transformation methods (e.g., log, rank, and box-cox) improve the performance of CCCP significantly. However, the Z-Score data transformation method could not achieve better results as compared to the rest of the data transformation methods in this study. Moreover, it is also investigated that the CCCP model based on NB outperform on transformed data and DP, KNN and GBT performed on the average, while SRI classifier did not show significant results in term of the commonly used evaluation measures (i.e., probability of detection, probability of false alarm, area under the curve and g-mean).  相似文献