306,213 research outputs found

    CleanML: A Study for Evaluating the Impact of Data Cleaning on ML Classification Tasks

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    Data quality affects machine learning (ML) model performances, and data scientists spend considerable amount of time on data cleaning before model training. However, to date, there does not exist a rigorous study on how exactly cleaning affects ML -- ML community usually focuses on developing ML algorithms that are robust to some particular noise types of certain distributions, while database (DB) community has been mostly studying the problem of data cleaning alone without considering how data is consumed by downstream ML analytics. We propose a CleanML study that systematically investigates the impact of data cleaning on ML classification tasks. The open-source and extensible CleanML study currently includes 14 real-world datasets with real errors, five common error types, seven different ML models, and multiple cleaning algorithms for each error type (including both commonly used algorithms in practice as well as state-of-the-art solutions in academic literature). We control the randomness in ML experiments using statistical hypothesis testing, and we also control false discovery rate in our experiments using the Benjamini-Yekutieli (BY) procedure. We analyze the results in a systematic way to derive many interesting and nontrivial observations. We also put forward multiple research directions for researchers.Comment: published in ICDE 202

    Outsourcing and acquisition models comparison related to IT supplier selection decision analysis

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    This paper presents a comparison of acquisition models related to decision analysis of IT supplier selection. The main standards are: Capability Maturity Model Integration for Acquisition (CMMI-ACQ), ISO / IEC 12207 Information Technology / Software Life Cycle Processes, IEEE 1062 Recommended Practice for Software Acquisition, the IT Infrastructure Library (ITIL) and the Project Management Body of Knowledge (PMBOK) guide. The objective of this paper is to compare the previous models to find the advantages and disadvantages of them for the future development of a decision model for IT supplier selection

    Chapter 5: Evaluation

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    The OTiS (Online Teaching in Scotland) programme, run by the now defunct Scotcit programme, ran an International e-Workshop on Developing Online Tutoring Skills which was held between 8–12 May 2000. It was organised by Heriot–Watt University, Edinburgh and The Robert Gordon University, Aberdeen, UK. Out of this workshop came the seminal Online Tutoring E-Book, a generic primer on e-learning pedagogy and methodology, full of practical implementation guidelines. Although the Scotcit programme ended some years ago, the E-Book has been copied to the SONET site as a series of PDF files, which are now available via the ALT Open Access Repository. The editor, Carol Higgison, is currently working in e-learning at the University of Bradford (see her staff profile) and is the Chair of the Association for Learning Technology (ALT)

    Cognitive finance: Behavioural strategies of spending, saving, and investing.

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    Research in economics is increasingly open to empirical results. The advances in behavioural approaches are expanded here by applying cognitive methods to financial questions. The field of "cognitive finance" is approached by the exploration of decision strategies in the financial settings of spending, saving, and investing. Individual strategies in these different domains are searched for and elaborated to derive explanations for observed irregularities in financial decision making. Strong context-dependency and adaptive learning form the basis for this cognition-based approach to finance. Experiments, ratings, and real world data analysis are carried out in specific financial settings, combining different research methods to improve the understanding of natural financial behaviour. People use various strategies in the domains of spending, saving, and investing. Specific spending profiles can be elaborated for a better understanding of individual spending differences. It was found that people differ along four dimensions of spending, which can be labelled: General Leisure, Regular Maintenance, Risk Orientation, and Future Orientation. Saving behaviour is strongly dependent on how people mentally structure their finance and on their self-control attitude towards decision space restrictions, environmental cues, and contingency structures. Investment strategies depend on how companies, in which investments are placed, are evaluated on factors such as Honesty, Prestige, Innovation, and Power. Further on, different information integration strategies can be learned in decision situations with direct feedback. The mapping of cognitive processes in financial decision making is discussed and adaptive learning mechanisms are proposed for the observed behavioural differences. The construal of a "financial personality" is proposed in accordance with other dimensions of personality measures, to better acknowledge and predict variations in financial behaviour. This perspective enriches economic theories and provides a useful ground for improving individual financial services

    Implementation Science and Fidelity Measurement: A Test of the 3-5-7 Model™

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    Children and youths engaged with the child welfare system can experience grief and loss as a result of trauma, broken relationships, and inadequate attachments. Interventionists are often challenged to implement effective strategies that help youths to reestablish trusting relationships and to promote overall psychological well-being. A 5-year federal demonstration project funded by the U.S. Department of Health and Human Services, Children’s Bureau, guided by an implementation science model, sought to increase well-being in youths age 12–21 who were involved in the child welfare system. The 3-5-7 Model™, a strengths-based approach that empowers children, youths, and families to engage in grieving and integrating significant relationships, was studied. A fidelity system was created in order to test the model. Important lessons about implementation science guided the work of the demonstration project. Although definitive conclusions could not be reached, several indicators of psychological well-being were found to be associated with high levels of fidelity to the 3-5-7 ModelTM. Suggestions for future research are offered

    How supplier selection criteria affects business performance? A study of UK automotive sector

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    According to KPMG international (2015), global sales of automobiles are forecasted to reach 73.9 million vehicles and expected to hit 100 million units in the next two years. This shows that automotive sector has a tremendous growth potential and UK automotive sector is no different. However, in recent years the growing environmental awareness has become a major concern for automotive sector as they are faced with pressure of reducing carbon emissions as well as the costs. Suppliers play a significant role in achieving environmental goals set by organisations. Under these circumstances it is worth exploring the criteria that are used in assessing suppliers including the green aspects and how that affects the business performance. Design/methodology/approach: This research adopts a mixed method research approach. In order to collect the quantitative data a survey questionnaire was constructed and sent to automotive businesses listed in the FAME database. In order to triangulate the findings of this study, survey was complemented with in-depth interviews. Around 100 automotive manufacturers were invited for the survey however only 38 usable responses were received. In total seven semi-structured interviews were also conducted with people from different backgrounds and work experiences in the automotive sector. Findings: Literature identified delivery, cost, quality and technology as the supplier assessment criteria commonly used in assessing suppliers in automotive industries. Yet the issue of culture and green supply chain practices (GSP) were also widely concerned in several studies. The data analysis showed that delivery, quality, cost, technology, culture are correlated with exception of green supply chain practices. GSP was only found to be correlated with technology and cultural criteria. Semi-structured interviews suggest delivery and quality as the most important criteria when assessing supplier because of their greater impact toward business performance and reputation. Findings from all respondents also showed that most automotive manufacturers have already adopted environmental competency in their criteria. However, interviewees mentioned that this criterion does not take a major role in assessment compared with other criteria. The results also indicate that all factors studied do affect the business performance of automotive organisations. Value: This study contributes to the limited literature focused on assessing supplier selection criteria and business performance linkage in the UK automotive organisations. In addition, most studies on supplier selection and business performance ignore the green practices as important criteria which this study aims to address. Research limitations/implications: The study is based on the findings from a limited survey responses and semi-structured interviews. Having larger sample population would certainly improve the validity of the findings. The perspective of SMEs and large businesses with regard to each supplier selection criterion may be different hence the future research in this domain would also provide some valuable contributions. Practical implications: The survey responses indicate green supply practices as one of the important criteria in supplier selection. This suggests that automotive manufacturers should realize the importance of green practices while selecting their suppliers. This will help them to meet their own green goals while simultaneously meeting the government environmental.Ministry of Science and Technology, Taiwan â–Ş Economic Development Bureau, Kaohsiung, Taiwan â–Ş National Kaohsiung First University of Science & Tech, Taiwan â–Ş National Taiwan Ocean University, Taiwan â–Ş Taiwan International Ports Corp. Ltd. â–Ş Jade Yachts Shipbuilding Co., Ltd. â–Ş International Academy for Marine Economy and Technology, The University of Nottingham Ningbo Campus, China â–Ş The Institute for Advanced Manufacturing, The University of Nottingham, U

    Harnessing Real Estate Investment through Decision Process for Selecting Tenants in Nigeria

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    One of daunting challenges to harnessing real estate investment in Nigeria is selection of tenants. Many prospective tenants of completed development projects often appear good at the recruitment stage but later become belligerent with grave consequence and challenge to the Estate Surveyors. This paper examines the criteria set by practitioners in selecting tenants in Lagos Nigeria. A survey of Estate Surveyors and was carried out to obtain the criteria and relative importance index analysis carried to determine their rankings. The outcome showed the decision process to assist estate surveyors in recruiting reliable tenants such that investors in real estate will harness adequate and remunerative returns and have value for their investment
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