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Application of a four-dimensional framework to evaluate the quality of the HIV/AIDS data collection process in China

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INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS 2021年 145卷 104306-104306页

作者： Chen, Hong Yu, Ping Hailey, David Cui, Tingru Univ Wollongong UOW Fac Engn & Informat Sci EIS Ctr Digital Transformat CDT Sch Comp & Informat Technol SCIT Wollongong NSW Australia Jiangxi Prov Ctr Dis Control & Prevent Nanchang Jiangxi Peoples R China Illawarra Hlth & Med Res Inst Wollongong NSW Australia Univ Melbourne Sch Comp & Informat Syst Melbourne Sch Engn Melbourne Vic Australia

Objective: To qualitatively evaluate the quality of the data collection process used by the Chinese national HIV/ AIDS data repository (CRIMS), using a four-dimensional (4D) framework. The process is vital for the acquisition of high-quality data for ending the HIV/AIDS epidemic in China. Methods: The study was carried out in China from September 2014 to April 2015. Stratified convenient sampling was conducted to recruit 28 study participants including health administrators, public health professionals and clinicians. data were collected through semi-structured interviews with the participants and from field observations in six hospitals. Content analysis was conducted following the 4D Framework. Results: 61 percent of the facilitators and 74 percent of the barriers of the 4D Framework were confirmed in the CRIMS data collection process. The CRIMS achieved better-quality data collection management. The perceived gaps primarily included: impractical data collection protocol and invalid quality assessment mechanism for data collection management;weak leadership and unsupportive organizational policy for data collection environment;poor communication and job fatigue for data collection personnel;and inflexibility and inaccessibility of data collection system. Areas for improvement included: engaging frontline staff in the design of data collection protocol, standardizing quality assurance procedures, strengthening leadership, recognizing data collector's contributions, and meeting end-users' needs for the CRIMS. Conclusion: The findings generated knowledge about the quality of the CRIMS data collection process. The 4D Framework has potential as an evaluation tool for decision-makers on the improvement of the public health data collection process.

关键词： data quality data collection process HIV/AIDS information management systems China 4D framework

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Optimizing the reliability, maintainability and safety data collection process through lifecycle

Optimizing the reliability, maintainability and safety data ...

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Annual Reliability and Maintainability Symposium (RAMS)

作者： Adjallah, Kondo H. Wang, Zhouhang Univ Lorraine LCOMS EA7306 Ecole Nati Ingenieurs Metz 1 Route Ars Laquenexy F-57070 Metz Lorraine France

ISBN: (纸本)9781509052844

This paper focuses on an approach to develop a robust, reliable, maintainable and proactive process of data collection through relevant indicators. Mainly, it aims to model and optimize the effectiveness of the RAMS data collection process (DCP), under cost constraints, while taking into account the its operating conditions and human factors. It also deals with the data collection system maintenance, data collection process and database maintenance over time. The authors have proposed an approach to model and optimize the RAMS DCP based on data relevance assessment, indicators of complexity, the usefulness and the quantity of information collected using the DCP and database.

关键词： data collection process Modeling Optimization Reliability Maintainability Safety Lifecycle

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Enhancing transport mode classification benchmark by integrating spatial independence with multimodal dataset

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TRAVEL BEHAVIOUR AND SOCIETY 2025年 38卷

作者： Erdelic, Martina Caric, Tonci Erdelic, Tomislav Semanjski, Ivana Univ Zagreb Fac Transport & Traff Sci Dept Intelligent Transportat Syst Vukeliceva 4 Zagreb Croatia Fac Engn & Architecture Dept Ind Syst Engn & Prod Design Technol Pk Zwijnaarde 46 B-9052 Ghent Belgium

The transport network is a complex system that benefits from detailed data on user mobility. Analyzing user trajectories through clustering or classification methods can provide valuable insights into mobility patterns. Extracting transport modes from these trajectories using classification methods enhances the understanding of user mobility. The complexity of classification methods varies, with some classifying a few transport modes, such as walking, running, bicycling, and driving. In contrast, others classify up to seven modes or use private, unpublished datasets. A key challenge in transport mode classification is ensuring the comparability of different methods across various contexts. Additionally, comparing results is further complicated by the insufficient use of existing standardized benchmark, which in the case of transport mode classification, must contain a structured testing framework and a dataset on which the testing will be conducted. This research introduces a process for collecting data to develop a new transport mode classification dataset. The goal is to enhance the benchmark by evaluating classification methods across diverse traffic patterns and geographic areas, thereby assessing their spatial independence. Spatial independence is crucial because it ensures that classification methods remain accurate regardless of geographic variations. This improves comparability by enabling consistent evaluation of methods across regions, as the improved benchmark addresses spatial independence and ensures robustness for real-world deployment. The current benchmark in literature examines three types of independence: user, position, and time independence. Our tests employ a multilevel method based on Transition State Matrices (TSMs) and the Random Forest (RF) algorithm for transport mode classification. The results demonstrate that the multilevel method maintains spatial independence and achieves higher accuracy compared to the original benchmark problem.

关键词： Real-time multimodal transport classification Multimodal transport data analysis Open transport dataset Benchmark problem extension data collection process

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Framework for a Knowledge-Based Course Recommender System Focused on IT Career Needs 16

Framework for a Knowledge-Based Course Recommender System Fo...

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16th International Conference on Knowledge Engineering and Ontology Development, KEOD 2024 as part of 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2024

作者： Xuan, Hien Pham Thi Nam, Le Nguyen Hoai Pham-Nguyen, Cuong Faculty of Information Technology University of Science Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9789897587160

This paper presents an approach for a knowledge-based recommender system that provides relevant courses based on learners’ profiles, requirements, and career needs. The framework integrates an automatic data collection process, ensuring that the knowledge base reflects the latest job market and course information. The recommendation method relies on a set of rules that combine various matching techniques, incorporating user requirements, skill and knowledge gaps, contextual information, and the course weight indicating its relevance to the career or market. An experiment was conducted to measure the satisfaction of the approach through a survey of users who used the system. The results reveal that the approach is deemed acceptable. This framework contributes to ongoing discussions surrounding the application of technology in building recommender systems for education. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Course Recommendation Method data collection process Knowledge Base

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A regression approach to the two-dataset problem

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STATISTICS 2022年第6期56卷 1225-1241页

作者： MacEachern, Steven N. Miyawaki, Koji Ohio State Univ Dept Stat Columbus OH 43210 USA Kwansei Gakuin Univ Sch Econ Nishinomiya Hyogo Japan

This paper considers the two-dataset problem, where data are collected from two potentially different populations sharing common aspects. This problem arises when data are collected by two different types of researchers or from two different sources. We may reach invalid conclusions without using knowledge about the data collection process. To address this problem, this paper develops statistical regression models focusing on the difference in measurement and proposes two prediction errors that help to evaluate the underlying data collection process. As a consequence, it is possible to discuss the heterogeneity/similarity of the set of predictors in terms of prediction. Two real datasets are selected to illustrate our method.

关键词： data collection process random coefficients model Bayesian model averaging

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Supervisory output prediction for bilinear systems by reinforcement learning

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IET CONTROL THEORY AND APPLICATIONS 2017年第10期11卷 1514-1521页

作者： Chasparis, Georgios C. Natschlaeger, Thomas Software Competence Ctr Hagenberg GmbH Softwarepk 21 A-4232 Hagenberg Austria

Online output prediction is an indispensable part of any model predictive control implementation. For several application scenarios, operating conditions may change quite often, while designing the data collection process may not be an option. To this end, this study introduces a supervisory output prediction scheme, tailored specifically for input-output stable bilinear systems, that intends on automating the process of selecting the most appropriate prediction model during runtime. The selection process is based upon a reinforcement-learning scheme, where prediction models are selected according to their prior prediction performance. An additional selection process is concerned with appropriately partitioning the control-inputs' domain also to allow for switched-system approximations of the original bilinear dynamics. The authors show analytically that the proposed scheme converges (in probability) to the best model and partition. They also demonstrate these properties through simulations of temperature prediction in residential buildings.

关键词： bilinear systems learning (artificial intelligence) predictive control switching systems (control) buildings (structures) temperature control digital simulation supervisory output prediction reinforcement learning online output prediction model predictive control implementation data collection process input-output stable bilinear systems prior prediction performance control-input domain switched-system approximations original bilinear dynamics temperature prediction simulation residential buildings

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Health behavior tracking via mobile games: A case study among school-aged children

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COGENT EDUCATION 2017年第1期4卷 Article: 1311500页

作者： Sormunen, Marjorita Miettinen, Hanna Univ Eastern Finland Dept Nursing Sci POB 1627 Kuopio 70211 Finland

Mobile devices are increasingly being used, in various ways, to collect data and are also increasingly related to individuals' health behaviors. Because of the paucity of available data about the process of mobile data collection in tracking daily health behaviors among children, we designed this pilot study to determine the possibilities and the enhancing and inhibiting factors of a continuous data collection process using a mobile game. Twenty 10-12-year-old school children from two schools participated in the study. We asked the participants to play a game that recorded their health-related behaviors for seven consecutive days, answering 14-16 questions daily. The questions related to children's eating habits, hygiene habits, hobbies and activities, networks, media use and devices, and sleep. In this article, we describe and discuss the process of data collection with its advances and challenges, including the planning and preparation of the survey according to its content and technicalities, training the pupils and their teacher to use the device and the health game, implementing the survey, and concluding the process. Additionally, we present viewpoints on educating children using collective health data.

关键词： mobile game mobile data collection health behavior tracking data collection process school-aged children health education

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The system of collecting administrative data and how it responses to the guidelines of the code of practice and the peer review

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Statistical Journal of the IAOS 2017年第3期33卷 741-747页

作者： Laurila, Sinikka Eskelinen, Janne Sisto, Johanna Statistics Finland Helsinki Finland

Recently, Statistics Finland developed a centralised system for collecting and receiving administrative data. That work was well in line with Statistics Finland's strategic plans to harmonise processes, develop generic solutions and centralise data collection activities and know-how. The work was organised as a project to take place in the period from 2013 to 2015. Statistics Finland now has a new system that utilises process metadata to control and inspect the received administrative data. Project results also included the implementation of a generic tool for technical validation and distribution of administrative data. The European Statistics Code of Practice gives guidelines for statistical offices about using administrative data and registers in statistical production. This presentation evaluates how these guidelines are met in the new information system that receives and validates administrative data at Statistics Finland. A brief review is also presented on how it corresponds to the Peer Review (2013 to 2015) recommendations today. © IOS Press and the authors. All rights reserved.

关键词： Administrative data data collection process information system receiving administrative data

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Developmental discourses as a regime of truth in research with primary school students

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INTERNATIONAL JOURNAL OF QUALITATIVE STUDIES IN EDUCATION 2016年第7期29卷 911-924页

作者： Bartholomaeus, Clare Univ Adelaide Sch Social Sci Adelaide SA Australia Flinders Univ S Australia Sch Social & Policy Studies Adelaide SA Australia

While developmental discourses have been heavily critiqued in relation to education systems, less attention has been paid to how these impact the data collection process in classroom research. This article utilises Foucault's concept of regime of truth to highlight the pervasiveness of developmental discourses when conducting research in primary schools. Such a theoretical framing makes explicit how developmental discourses work and are constructed as 'truth', which limit the possibilities for alternative perspectives. This article shows how this regime of truth works in practice by reflecting on qualitative research conducted with two age groups in two primary schools in Australia, focusing on the researcher's navigations of these discourses. In particular, this article examines the impact of developmental discourses on conducting research with multiple age groups, initiating research, choosing methods for data collection, and negotiating power relations and ethical practices.

关键词： Developmental discourses regime of truth data collection process age primary school

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data Flows in Urban Freight Transport Management System 15th

Data Flows in Urban Freight Transport Management System

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15th International Conference on Transport Systems Telematics (TST)

作者： Iwan, Stanislaw Malecki, Krzysztof Maritime Univ Szczecin Poboznego 11 PL-70507 Szczecin Poland West Pomeranian Univ Technol PL-71210 Szczecin Poland

ISBN: (纸本)9783319245775;9783319245768

The fast growth of cities and the rising number of their users leads to an increase in demand for freight transport, thus contributing to an increase in logistic flow streams within a limited area. Currently, freight transport is usually done in an uncoordinated and chaotic manner. Specifying the information needs in the field of urban freight transport (UFT) will make it possible to take control over the increasing disorder in this area and enable its development in accordance with the principles of sustainable growth. This paper is focused on the analysis realized under the project "Analysis of information needs of heterogeneous environment in sustainable urban freight transport system". The aim of the project is to determine the structures of data relevant for the management of sustainable UFT, establish the sources of data acquisition, the scope and degree of integration, and also indicate the methods of knowledge extraction from the acquired data and information, necessary for improving freight transport efficiency in cities.

关键词： Urban freight transport data collection process Freight transport management Sustainable development Efficiency of city logistics Efficiency of transport systems

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