Journal of the Korea Society of Computer and Information
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v.14
no.8
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pp.117-125
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2009
In this paper, an integrated management system of seismic observatory information based on XML is proposed. The number of organizations which have their own seismic stations eg. KMA, KIGAM etc is increasing since 1998. Related informations such as location, installed instruments. and operational profile are essential for efficient utilization of seismic data. It's not easy to provide the uniform type of information and has limitation to announce the updated information of station rapidly through individual information management system of each organization. In this paper, we propose an integrated management system of seismic observatory information which can support to manage information of their own seismic observatory by a person in charge via Web, to integrate that in nation-wide and to provide that for users. We investigated minimum information of observatory were needed to use seismic data and the analysis result was structured by using XML. The integrated management system consists of the observatory management module. information search module, and the latest information supply module etc. By using proposed system, seismic observatory information of each organization can be managed and be supplied efficiently in nation-wide.
Purpose: This study aimed to construct a structural equation model to explain and predict factors affecting the health-related quality of life (QoL) in female rheumatoid arthritis (RA) patients based on the health-related QoL model by Ferrans et al. (2005) and a literature review. Methods: Patients (N=243) who were either registered members of an internet cafe composed of patients with RA or rheumatology outpatients at two tertiary general hospitals in Busan, Korea, were recruited via convenience sampling. Data were collected from July 2 to September 9, 2021, and the survey was conducted using a web-based questionnaire. The data were analyzed by SPSS and AMOS 26.0. Results: The goodness-of-fit statistics of the final model exhibited good results (χ2/degree of freedom=2.68, Turker-Lewis index=.94, comparative fit index=.96, standardized root mean-squared residual=.04, root mean- square error of approximation=.08), and 11 out of 14 paths of the model were supported. The squared multiple correlation, which reflected the explanatory power of the environmental characteristics, symptoms, functional status, and perceived health status on health-related QoL, was 80%. In the hypothesis model, 10 paths had significant direct effects, 6 paths had significant indirect effects, and 12 paths had significant total (direct and indirect) effects. Conclusion: Considering that factors directly affecting the health-related QoL of female patients with RA were social support, symptoms (fatigue and depression), resilience, and perceived health status, and that resilience was the most influential factor, clinicians can encourage resilience. Hence, to improve the health-related QoL of female patients with RA, continuing management is necessary, using various intervention methods that focus on enhancing resilience from the early stage to the end of treatment for RA.
As the Internet and web technology develop around mobile devices, image data contains various types of sensitive information such as people, text, and space. In addition to these characteristics, as the use of SNS increases, the amount of damage caused by exposure and abuse of personal information online is increasing. However, research on de-identification technology based on multi-type object detection for personal information protection is insufficient. Therefore, this paper proposes an artificial intelligence model that detects and de-identifies multiple types of objects using existing single-type object detection models in parallel. Through cutmix, an image in which person and text objects exist together are created and composed of training data, and detection and de-identification of objects with different characteristics of person and text was performed. The proposed model achieves a precision of 0.724 and mAP@.5 of 0.745 when two objects are present at the same time. In addition, after de-identification, mAP@.5 was 0.224 for all objects, showing a decrease of 0.4 or more.
Nurul Ashykin ABD AZIZ;Mohamad Rohieszan RAMDAN;Khairunnisa ABDUL AZIZ;Hasif Rafidee HASBOLLAH;Noreen Noor ABD AZIZ;Nik Syuhailah NIK HUSSIN;Md Zaki MUHAMAD HASAN
Journal of Distribution Science
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v.21
no.10
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pp.39-49
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2023
Purpose: The purpose of this study is to explore areas that have been studied extensively in previous studies related to franchising as a platform for global distribution. Furthermore, franchising is a strategic distribution method that gives entrepreneurs the opportunity to replicate an established business model. In addition, franchisees benefit from the use of established branding and receive support from the franchisor. Research design, data, and methodology: This study used the Preferred Reporting Items Systematics Review and Meta-Analyses (PRISMA) method to analyse data from 2003 to 2023 in the Web of Science and Scopus databases. Results: A total of 79 articles were identified and analysed to see trends and related themes such as product distribution, business distribution, business strategy, emerging market, and franchising relationship. Also, publication trends by year related to franchises are also presented. Conclusions: Overall, the research trend related to franchising as a global distribution is well seen, and every year, many researchers begin to explore the topic of franchising as a method of distribution that can be explored from various aspects either quantitatively or qualitatively. Lastly, limitations and recommendations are made to provide guidance for future studies related to the topic broadly and deeply in enriching the findings.
Purpose: This study aimed to identify factors related to the workload of intensive care unit nurses through a systematic literature review and meta-analysis to provide basic data to explore the direction of development of nursing staffing standards. Methods: This study involved quantitative studies about nurses working in intensive care units related to nursing workload published in English or Korean since 2000. Search terms included 'intensive care unit', 'nursing workload', and their variations. Databases such as RISS, DBpia, MEDLINE(PubMed), CINAHL, PsycINFO, and Web of Science were utilized. Quality assessment was conducted using the Joanna Briggs Institute's Critical Appraisal Checklist for Analytical Cross-Sectional Studies. JAMOVI software facilitated the analysis of effect sizes, employing a meta-analysis approach for 7 studies with correlational or regression data. Results: From 16 studies on the workload of intensive care unit nurses, a total of 20 patient and nurse-related factors were identified. Patient-related factors included severity of illness, length of stay, and age. Meta-analysis was conducted for three patient-related factors: age, severity of illness measured by SAPS 3, and length of stay. Only severity of illness measured by SAPS 3 was significantly associated with nurse workload (Zr=0.16, p<.001, 95% CI=0.09-0.24). Conclusion: In previous studies, the characteristics of intensive care units and patients varied across studies, and a variety of scales for measuring workload and severity of illness were also used. Sustained research reflecting domestic intensive care unit work environments and assessing the workload of intensive care unit nurses should be imperative.
It takes a lot of time and manpower to search for the missing. As part of the solution, a missing person search AI system was implemented using a YOLO-based model. In order to train object detection models, the model was learned by collecting recognition images (road fixation) of drone mobile objects from AI-Hub. Additional mountainous terrain datasets were also collected to evaluate performance in training datasets and other environments. In order to optimize the missing person search AI system, performance evaluation based on model size and hyperparameters and additional performance evaluation for concerns about overfitting were conducted. As a result of performance evaluation, it was confirmed that the YOLOv5-L model showed excellent performance, and the performance of the model was further improved by applying data augmentation techniques. Since then, the web service has been applied with the YOLOv5-L model that applies data augmentation techniques to increase the efficiency of searching for missing people.
Miguel Angel Gaxiola-Garcia;Joseph M. Escandon;Oscar J. Manrique;Kristin A. Skinner;Beatriz Hatsue Kushida-Contreras
Archives of Plastic Surgery
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v.51
no.2
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pp.212-233
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2024
This is a retrospective review of surgical management for primary lymphedema. Data were extracted from 55 articles from PubMed MEDLINE, Web of Science, SCOPUS, and Cochrane Central Register of Controlled Trials between the database inception and December 2022 to evaluate the outcomes of lymphaticovenous anastomosis (LVA) and vascularized lymph node transfer (VLNT), and outcomes of soft tissue extirpative procedures such as suction-assisted lipectomy (SAL) and extensive soft tissue excision. Data from 485 patients were compiled; these were treated with LVA (n = 177), VLNT (n = 82), SAL (n = 102), and excisional procedures (n = 124). Improvement of the lower extremity lymphedema index, the quality of life (QoL), and lymphedema symptoms were reported in most studies. LVA and VLNT led to symptomatic relief and improved QoL, reaching up to 90 and 61% average circumference reduction, respectively. Cellulitis reduction was reported in 25 and 40% of LVA and VLNT papers, respectively. The extirpative procedures, used mainly in patients with advanced disease, also led to clinical improvement from the volume reduction, as well as reduced incidence of cellulitis, although with poor cosmetic results; 87.5% of these reports recommended postoperative compression garments. The overall complication rates were 1% for LVA, 13% for VLNT, 11% for SAL, and 46% for extirpative procedures. Altogether, only one paper lacked some kind of improvement. Primary lymphedema is amenable to surgical treatment; the currently performed procedures have effectively improved symptoms and QoL in this population. Complication rates are related to the invasiveness of the chosen procedure.
International conference on construction engineering and project management
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2024.07a
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pp.1308-1308
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2024
Computer vision techniques have been widely employed in automated construction management to enhance safety and prevent accidents at construction sites. However, previous research in the field of vision-based approaches has often overlooked small-sized construction tools. These tools present unique challenges in data collection due to their diverse shapes and sizes, as well as in improving model performance to accurately detect and classify them. To address these challenges, this study aimed to enhance the performance of vision-based classifiers for small-sized construction tools, including bucket, cord reel, hammer, and tacker, by leveraging synthetic images generated from a 3D virtual environment. Three classifiers were developed using the YOLOv8 algorithm, each differing in the composition of the training dataset: (i) 'Real-4000', trained on 4,000 authentic images collected through web crawling methods (1,000 images per object); (ii) 'Hybrid-4000', consisting of 2,000 authentic images and 2,000 synthetic images; and (iii) 'Hybrid-8000', incorporating 4,000 authentic images and 4,000 synthetic images. To validate the performance of the classifiers, 144 directly-captured images for each object were collected from real construction sites as the test dataset. The mean Average Precision at an IoU threshold of 0.5 (mAP_0.5) for the classifiers was 79.6%, 90.8%, and 94.8%, respectively, with the 'Hybrid-8000' model demonstrating the highest performance. Notably, for objects with significant shape variations, the use of synthetic images led to the enhanced performance of the vision-based classifiers. Moreover, the practical applicability of the proposed classifiers was validated through confidence scores, particularly between the 'Hybrid-4000' and 'Hybrid-8000' models. Statistical analysis using t-tests indicated that the performance of the 'Hybrid-4000' model would either matched or exceeded that of the 'Hybrid-8000'model based on confidence scores. Thus, employing the 'Hybrid-4000' model may be preferable in terms of data collection efficiency and processing time, contributing to enhanced safety and real-time automation and robotics in construction practices.
Recently, as economic property it has become necessary to acquire and utilize the framework for water resource measurement and performance management as the property of water resources changes to hold "public property". To date, the evaluation of water technology has been carried out by feasibility study analysis or technology assessment based on net present value (NPV) or benefit-to-cost (B/C) effect, however it is not yet systemized in terms of valuation models to objectively assess an economic value of technology-based business to receive diffusion and feedback of research outcomes. Therefore, K-water (known as a government-supported public company in Korea) company feels the necessity to establish a technology valuation framework suitable for technical characteristics of water resources fields in charge and verify an exemplified case applied to the technology. The K-water evaluation technology applied to this study, as a public interest goods, can be used as a tool to measure the value and achievement contributed to society and to manage them. Therefore, by calculating the value in which the subject technology contributed to the entire society as a public resource, we make use of it as a basis information for the advertising medium of performance on the influence effect of the benefits or the necessity of cost input, and then secure the legitimacy for large-scale R&D cost input in terms of the characteristics of public technology. Hence, K-water company, one of the public corporation in Korea which deals with public goods of 'water resources', will be able to establish a commercialization strategy for business operation and prepare for a basis for the performance calculation of input R&D cost. In this study, K-water has developed a web-based technology valuation model for public interest type water resources based on the technology evaluation system that is suitable for the characteristics of a technology in water resources fields. In particular, by utilizing the evaluation methodology of the Institute of Advanced Industrial Science and Technology (AIST) in Japan to match the expense items to the expense accounts based on the related benefit items, we proposed the so-called 'K-water's proprietary model' which involves the 'cost-benefit' approach and the FCF (Free Cash Flow), and ultimately led to build a pipeline on the K-water research performance management system and then verify the practical case of a technology related to "desalination". We analyze the embedded design logic and evaluation process of web-based valuation system that reflects characteristics of water resources technology, reference information and database(D/B)-associated logic for each model to calculate public interest-based and profit-based technology values in technology integrated management system. We review the hybrid evaluation module that reflects the quantitative index of the qualitative evaluation indices reflecting the unique characteristics of water resources and the visualized user-interface (UI) of the actual web-based evaluation, which both are appended for calculating the business value based on financial data to the existing web-based technology valuation systems in other fields. K-water's technology valuation model is evaluated by distinguishing between public-interest type and profitable-type water technology. First, evaluation modules in profit-type technology valuation model are designed based on 'profitability of technology'. For example, the technology inventory K-water holds has a number of profit-oriented technologies such as water treatment membranes. On the other hand, the public interest-type technology valuation is designed to evaluate the public-interest oriented technology such as the dam, which reflects the characteristics of public benefits and costs. In order to examine the appropriateness of the cost-benefit based public utility valuation model (i.e. K-water specific technology valuation model) presented in this study, we applied to practical cases from calculation of benefit-to-cost analysis on water resource technology with 20 years of lifetime. In future we will additionally conduct verifying the K-water public utility-based valuation model by each business model which reflects various business environmental characteristics.
The objective of this study was to estimate rice yield in Korea using satellite and meteorological data such as sunshine hours or solar radiation, and rainfall. Terra and Aqua MODIS (The MOderate Resolution Imaging Spectroradiometer) products; MOD13 and MYD13 for NDVI and EVI, MOD15 and MYD15 for LAI, respectively from a NASA web site were used. Relations of NDVI, EVI, and LAI obtained in July and August from 2000 to 2011 with rice yield were investigated to find informative days for rice yield estimation. Weather data of rainfall and sunshine hours (climate data 1) or solar radiation (climate data 2) were selected to correlate rice yield. Aqua NDVI at DOY 233 was chosen to represent maximum vegetative growth of rice canopy. Sunshine hours and solar radiation during rice ripening stage were selected to represent climate condition. Multiple regression based on MODIS NDVI and sunshine hours or solar radiation were conducted to estimate rice yields in Korea. The results showed rice yield of $494.6kg\;10a^{-1}$ and $509.7kg\;10a^{-1}$ in 2011, respectively and the difference from statistics were $1.1kg\;10a^{-1}$ and $14.1kg\;10a^{-1}$, respectively. Rice yield distributions from 2002 to 2011 were presented to show spatial variability in the country.
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