• Journal of Information Science Theory and Practice
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• v.7 no.3
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• pp.52-64
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• 2019

This research was aimed at studying the situation, problems, and requirements for digital collection lifecycle management of Thai theses and dissertations. The mixed research method used was composed of: (1) Study of the problem and situation in which the qualitative method was applied. The research site covered 10 higher education institutions where the Thailand Digital Collection (TDC) project is operated. The informants were key administrative officers of the TDC project of each institution. In-depth and structured interviews were conducted on an individual basis to obtain the most accurate answers. (2) Study of requirements based on the quantitative research method to survey the requirements for the digital collection management system for Thai theses and dissertations from 84 purposively-selected TDC project officers and 527 end users selected by accidental sampling, totaling 611 samples. Research findings are as follow: (1) The study of the situation and problems of digital collection lifecycle management shows that Thai higher institutions systematically manage their digital collection. The management lifecycle is consistent with the Guidance documents for lifecycle management of ETDs, which included seven steps: program planning, creation, submission, and ingestion, access and retrieval of digital objects, archiving and preservation, evaluation and assessment, interoperation (creation of institutional collaboration), and development of link data. (2) The study of requirements for digital collection management of Thai theses and dissertations shows five system requirements: acquisition and gathering, digitization, metadata standards, management of rights, and storage and retrieval, all of which are at M (mandatory) and D (desirable) levels.

• Journal of Distribution Science
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• v.21 no.2
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• pp.35-43
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• 2023

Purpose: As Thailand seeks to become a regional startup hub, Thai startups have been acquiring growth and scalability in the last ten years. Hence, this paper examines influential factors in Thailand's growth of logistics tech startups. The conceptual framework incorporates sensing user needs, sensing technological options, conceptualizing, scaling, and stretching, co-producing, and orchestrating, business strategy, strategic flexibility, and startup growth. Research design, data, and methodology: The quantitative method was applied to distribute the questionnaire to 500 managers and above in logistics tech startups in Thailand. The sampling techniques involve judgmental, convenience, and snowball samplings. Before the data collection, The Item Objective Congruence (IOC) Index and pilot test (n=45) were employed for content validity and reliability. The data were mainly analyzed by Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM). Results: The findings revealed that sensing technological options, scaling, and stretching, co-producing, and orchestrating, and business strategy significantly influence the growth of startups in Thailand. Nevertheless, sensing user needs, conceptualizing, and strategic flexibility have no significant relationship with startup growth. Conclusions: For Thailand to accelerate its digital economy driven by tech startups, firms must emphasize influential factors to accelerate growth by providing the right tech solutions for people's lives.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.27 no.3
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• pp.168-175
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• 2024

Purpose: The presence of alcoholic stool in biliary atresia (BA) patients is the basis of a stool color card (SCC), a screening tool that has led to more patients receiving Kasai portoenterostomy earlier. This study aimed to evaluate the color image processing of stool images captured using smartphones. We propose that measuring digital color parameters is a more objective method for identifying BA stools and may improve the sensitivity of BA screening. Methods: A prospective study was conducted in five hospitals in Thailand between October 1, 2020, and December 31, 2021. Stools from infants presenting with jaundice, acholic stool, or dark-colored urine were photographed. Digital image color analysis was performed, and software was developed based on the color on the original SCC. Sensitivity and specificity for predicting BA stools were compared between the SCC and the software. Results: Of 33 infants eligible for data collection, 19 were diagnosed with BA. Saturation and blue were two potential digital color parameters used to differentiate BA stools. The receiver operating characteristic curve was used to determine the optimum cutoff point of both values, and when saturation ≤56 or blue ≥61 was set as a threshold for detecting BA stool, high accuracy was achieved at 81.8% and 78.8%, respectively. Conclusion: Digital image processing is a promising technology. With appropriate cutoff values of saturation in hue, saturation, value and blue in red, green, blue color models, BA stools can be identified, and equivocal-colored stools of non-BA patients can be differentiated with acceptable accuracy in infants presenting with jaundice.