• The Journal of the Korea Contents Association
• /
• v.8 no.2
• /
• pp.74-82
• /
• 2008

This paper investigates chrominance reconstruction methods that reconstruct subsampled chrominance information efficiently using the correlation between luminance and chrominance components in the decompression process of compressed images, and analyzes drawbacks involved in the adaptive-weighted 2-dimensional linear interpolation among the methods, which shows higher efficiency in the view of computational complexity than other methods. To improve the drawback that the spatial frequency distribution is not considered for the decompressed image and to support the application on a low-performance system in behalf of 2-dimensional linear interpolation, this paper proposes the multi-mode reconstruction method which uses three reconstruction methods having different computational complexity from each other according to the degree of edge response of luminance component. The performance evaluation on a development platform for embedded systems showed that the proposed reconstruction method supports the similar level of image quality for decompressed images while reducing the overall computation time for chrominance reconstruction in comparison with the 2-dimensional linear interpolation.

• Journal of KIISE:Computer Systems and Theory
• /
• v.36 no.4
• /
• pp.247-258
• /
• 2009

Distributed file systems running on a cluster of inexpensive commodity hardware are being recognized as an effective solution to support the explosive growth of storage demand in large-scale Internet service companies. This paper presents the design and implementation of BeanFS, a distributed file system for large-scale e-mail services. BeanFS is adapted to e-mail services as follows. First, the volume-based replication scheme alleviates the metadata management overhead of the central metadata server in dealing with a very large number of small files. Second, BeanFS employs a light-weighted consistency maintenance protocol tailored to simple access patterns of e-mail message. Third, transient and permanent failures are treated separately and recovering from transient failures is done quickly and has less overhead.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.10a
• /
• pp.53-58
• /
• 2006

MicroRNA (miRNA)는 약 22 nt의 작은 RNA 조각으로 이루어져 있으며 stem-loop 구조의 precursor 형태에서 최종적으로 만들어 진다. miRNA는 mRNA의 3‘UTR에 상보적으로 결합하여 유전자의 발현을 억제하거나 mRNA의 분해를 촉진한다. miRNA를 동정하기 위한 실험적인 방법은 조직 특이적인 발현, 적은 발현양 때문에 방법상 한계를 가지고 있다. 이러한 한계는 컴퓨터를 이용한 방법으로 어느 정도 해결될 수 있다. 하지만 miRNA의 서열상의 낮은 보존성은 homology를 기반으로 한 예측을 어렵게 한다. 또한 기계학습 방법인 support vector machine (SVM) 이나 naive bayes가 적용되었지만, 생물학적인 의미를 해석할 수 있는 generative model을 제시해 주지 못했다. 본 연구에서는 우수한 miRNA 예측을 보일 뿐만 아니라 학습된 모델로부터 생물학적인 지식을 얻을 수 있는 Bayesian network을 적용한다. 이를 위해서는 생물학적으로 의미 있는 특질들의 선택이 중요하다. 여기서는 position weighted matrix (PWM)과 Markov chain probability (MCP), Loop 크기, Bulge 수, spectrum, free energy profile 등을 특질로서 선택한 후 Information gain의 특질 선택법을 통해 예측에 기여도가 높은 특질 25개 와 27개를 최종적으로 선택하였다. 이로부터 Bayesian network을 학습한 후 miRNA의 예측 성능을 10 fold cross-validation으로 확인하였다. 그 결과 pre-/mature miRNA 각 각에 대한 예측 accuracy가 99.99% 100.00%를 보여, SVM이나 naive bayes 방법보다 높은 결과를 보였으며, 학습된 Bayesian network으로부터 이전 연구 결과와 일치하는 pre-miRNA 상의 의존관계를 분석할 수 있었다.

• International Journal of Computer Science & Network Security
• /
• v.22 no.10
• /
• pp.340-346
• /
• 2022

Construction industry is considered as one of the oldest industries in the world since human came into being and the need of their own space is realized. All this led to make the world a space of many beautiful constructive ventures. As per the requirements of today's world, every industry is recognizing the need for use and adoption of modern as well as innovative technologies due to their benefits and timely production. Now construction industry has also started adopting the use of modern and innovative technologies during their projects but still the rate of adoption is so slow. From design to completion, construction projects take a lot to manage for which technology based solutions have continuously been proposed. These include Computer Aided Design (CAD), building information modeling (BIM) and cloud computing have been proved to be much successful until now. The construction projects are high budgeted, and direly require timely and successful completion with quality, resource and other constraints. So, the researchers observe the need of more clear and technology based communication between the construction projects and its constructors and other stakeholders is required before and during the construction to take timely precautions for expected issues. This study has analyzed the use of Augmented Reality (AR) technology adopting GammaAR, and ARki applications in construction industry. It has been found that both applications are light-weighted, upgradable, provide offline availability and collaborative environment as well as fulfil most of the requirements of the construction industry except the cost. These applications also support different screen size for better visualization and deep understanding. Both applications are analyzed, based on construction's application requirements, usability of AR and ratings of applications user collected from application's platform. The purpose of this research is to provide a detail insight of construction applications which are using AR to facilitate both the future developers and consumers.

• Clinical Endoscopy
• /
• v.57 no.1
• /
• pp.36-47
• /
• 2024

Background/Aims: Scissor-type endoscopic submucosal dissection (ST-ESD) knives can reduce the adverse events associated with ESDs. This study aimed to compare ST-ESD and non-scissor-type (NST)-ESD knives. Methods: We identified ten studies that compared the performance characteristics and safety profiles of ST-ESD and NST-ESD knives. Fixed- and random-effects models were used to calculate the pooled proportions. Heterogeneity was assessed using the I² test. Results: On comparing ST-ESD knives to NST-ESD knives, the weighted odds of en bloc resection was 1.61 (95% confidence interval [CI], 0.90-2.90; p=0.14), R0 resection was 1.10 (95% CI, 0.71-1.71; p=0.73), delayed bleeding was 0.40 (95% CI, 0.17-0.90; p=0.03), perforation was 0.35 (95% CI, 0.18-0.70; p<0.01) and ESD self-completion by non-experts was 1.89 (95% CI, 1.20-2.95; p<0.01). There was no heterogeneity, with an I² score of 0% (95% CI, 0%-54.40%). Conclusions: The findings of reduced odds of perforation, a trend toward reduced delayed bleeding, and an improvement in the rates of en bloc and R0 resection with ST-ESD knives compared to NST-ESD knives support the use of ST-ESD knives when non-experts perform ESDs or as an adjunct tool for challenging ESD procedures.

• Asia pacific journal of information systems
• /
• v.20 no.3
• /
• pp.191-204
• /
• 2010

Recently, the CO2 emission and energy consumption have become critical global issues to decide the future of nations. Especially, the spread of IT products and the increased use of internet and web applications result in the energy consumption and CO2 emission of IT industry though information technologies drive global economic growth. EU, the United States, Japan and other developed countries are using IT related environmental regulations such as WEEE(Waste Electrical and Electronic Equipment), RoHS(Restriction of the use of Certain Hazardous Substance), REACH(Registration, Evaluation, Authorization and Restriction of CHemicals) and EuP(Energy using Product), and have established systematic green business/IT strategies to enhance the competitiveness of IT industry. For example, the Japan government proposed the "Green IT initiative" for being compatible with economic growth and environmental protection. Not only energy saving technologies but energy saving systems have been developed for accomplishing sustainable development. Korea's CO2 emission and energy consumption continuously have grown at comparatively high rates. They are related to its industrial structure depending on high energy-consuming industries such as iron and steel Industry, automotive industry, shipbuilding industry, semiconductor industry, and so on. In particular, export proportion of IT manufacturing is quite high in Korea. For example, the global market share of the semiconductor such as DRAM was about 80% in 2008. Accordingly, Korea needs to establish a systematic strategy to respond to the global environmental regulations and to maintain competitiveness in the IT industry. However, green competitiveness of Korea ranked 11th among 15 major countries and R&D budget for green technology is not large enough to develop energy-saving technologies for infrastructure and value chain of low-carbon society though that grows at high rates. Moreover, there are no concrete action plans in Korea. This research aims to deduce the priorities of the Korean green business/IT strategies to use multi attribute weighted average method. We selected a panel of 19 experts who work at the green business related firms such as HP, IBM, Fujitsu and so on, and selected six assessment indices such as the urgency of the technology development, the technology gap between Korea and the developed countries, the effect of import substitution, the spillover effect of technology, the market growth, and the export potential of the package or stand-alone products by existing literature review. We submitted questionnaires at approximately weekly intervals to them for priorities of the green business/IT strategies. The strategies broadly classify as follows. The first strategy which consists of the green business/IT policy and standardization, process and performance management and IT industry and legislative alignment relates to government's role in the green economy. The second strategy relates to IT to support environment sustainability such as the travel and ways of working management, printer output and recycling, intelligent building, printer rationalization and collaboration and connectivity. The last strategy relates to green IT systems, services and usage such as the data center consolidation and energy management, hardware recycle decommission, server and storage virtualization, device power management, and service supplier management. All the questionnaires were assessed via a five-point Likert scale ranging from "very little" to "very large." Our findings show that the IT to support environment sustainability is prior to the other strategies. In detail, the green business /IT policy and standardization is the most important in the government's role. The strategies of intelligent building and the travel and ways of working management are prior to the others for supporting environment sustainability. Finally, the strategies for the data center consolidation and energy management and server and storage virtualization have the huge influence for green IT systems, services and usage This research results the following implications. The amount of energy consumption and CO2 emissions of IT equipment including electrical business equipment will need to be clearly indicated in order to manage the effect of green business/IT strategy. And it is necessary to develop tools that measure the performance of green business/IT by each step. Additionally, intelligent building could grow up in energy-saving, growth of low carbon and related industries together. It is necessary to expand the affect of virtualization though adjusting and controlling the relationship between the management teams.

• Journal of Korean Clinical Health Science
• /
• v.5 no.1
• /
• pp.790-802
• /
• 2017

Purpose. This study was designed to analyze recent trends in Children Art Therapy Program Intervention research in Korea and suggest future research directions in this area. Methods. Studies(29) selected from http://www.riss4u.net for last 15 year were used. They were analyzed by publication type, field and design of the study, study participants and outcome variables used in intervention studies. Results. 1. As for academic field, there are 15 art therapy academic journals(51.72%), which made up the largest proportion. 2. As for subjects of the study, there are 17 articles of Elementary (58.6%) education, which made up the largest proportion. As for the subjects of sex, 8 articles (27.59%) are for male students, 7 (24.14%) articles are for female students and 14 articles (48.28.%) are for both male and female students. 3. As for 7 articles of Art therapy(24.14%), 7 articles of Group Art therapy (24.14%) made up the largest proporton 4. As for the intervention study method according to the subjects of suicide intervention program, there are 15 articles of monoclonal Pre and post design (51.72%),which made up the largest proportion. 5. As for the sample size, there were 16.79 persons in the treatment group on average, 13.28 persons in the control group have average and the total persons were 10 on average. The treatment period was 12 weeks on average and the average number of treatment times was 18. The places of treatment were 3 schools (10.38%), which made up the largest proportion. 19. The results of the experimental study support the research hypothesis of all 29 programs. Conclusions. As the above, the studies on the art therapy intervention program for children are increasing but the subjects are overly weighted toward elementary school students. Although the content of the art therapy intervention program was varied, it was found that the development of the program using various art media which can induce the motivation of the child was lacking. In addition, the place of experimental mediation was concentrated on psychology center as 12(41.38%), indicating that there are not enough places to connect with community organizations such as schools and hospitals. The variables of experimental study were focused on psychological variables and it was found that there were insufficient application of various variables including coping method, social support, and physiological variables.

• Child Health Nursing Research
• /
• v.6 no.2
• /
• pp.119-131
• /
• 2000

The purpose of this study was to identify the trends and contents of intervention towards children using meta analysis, to support the basis for using in the field and research method about nursing intervention. We used 27 materials which was reported from 1970 to August, 1999 : dissertation study and Korean Nurses' Academic society Journals, the Journal of Korean Academic society of Adult Nursing, The Korea Journal of Maternal and Child Health Nursing. The types of intervention we used came from 3 different researchers. Snyder showed cognitive, movement, social sensory intervention. McCloskey & Bulechek categorized as the following : self-care assistance, acute care management, life-style alteration, health promotion, life support intervention, Craft & Denehy classified psychosocial intervention and biophysiological intervention. Some findings are summarized as follow : Out of the 27 researches sensory intervention had the most in there thesis, recently cognitive intervention research has a tendency to increase. 18 researches has acute care management in there theses, and health promotion was found the least. Out of the 27 thesis 15 thesis was classified as biophysiological intervention and 12 had psychosocial. 27 thesis had 11 types of interventions which originally was categorized by Snyder, therefore sensory intervention thesis had the most. 11 types of intervention which originally was classified by McClosky & Bulechek, teaching and information had the most out of acute care management. Out of 27 thesis, 14 had dealt with newborns, especially newborns with sensory intervention. Therefore school age and above had cognitive intervention which was used for teaching and information. Infants, preschool, schoolage children received acute care management the most, health promotion intervention was used towards adolescences. Depending on the characteristics of dependent variables, it was analysed using meta however 17 thesis are possible except primary experimental research. Mean effect size comparison by Snyder classification, cognitive intervention was the largest mean(1.51), sensory intervention was larger(0.71) also, movement intervention was in the middle(0.56) as shown. Comparison done by McClosky & Bulechek, the intervention leading to life style alteration was the largest mean(1.97), teaching was used the most. Comparison by Craft & Denehy classification, psychosocial intervention was larger(1.15) than biophysiological intervention (0.67). The result of nursing intervention through age classification, the largest weighted mean effect size in the research was towards infants and neonates. The research which was focused on nursing intervention, has important meaning in nursing practice and knowledge development. When we know that children's nursing intervention is necessary and overcome our biased view, efficiency of children's nursing intervention are increased and professionalized. Therefore results will be important basic data to guide a development of child nursing intervention & classification.

• Korean Journal of Radiology
• /
• v.23 no.12
• /
• pp.1281-1289
• /
• 2022

Objective: Radiomic modeling using multiple regions of interest in MRI of the brain to diagnose juvenile myoclonic epilepsy (JME) has not yet been investigated. This study aimed to develop and validate radiomics prediction models to distinguish patients with JME from healthy controls (HCs), and to evaluate the feasibility of a radiomics approach using MRI for diagnosing JME. Materials and Methods: A total of 97 JME patients (25.6 ± 8.5 years; female, 45.5%) and 32 HCs (28.9 ± 11.4 years; female, 50.0%) were randomly split (7:3 ratio) into a training (n = 90) and a test set (n = 39) group. Radiomic features were extracted from 22 regions of interest in the brain using the T1-weighted MRI based on clinical evidence. Predictive models were trained using seven modeling methods, including a light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, with radiomics features in the training set. The performance of the models was validated and compared to the test set. The model with the highest area under the receiver operating curve (AUROC) was chosen, and important features in the model were identified. Results: The seven tested radiomics models, including light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, showed AUROC values of 0.817, 0.807, 0.783, 0.779, 0.767, 0.762, and 0.672, respectively. The light gradient boosting machine with the highest AUROC, albeit without statistically significant differences from the other models in pairwise comparisons, had accuracy, precision, recall, and F1 scores of 0.795, 0.818, 0.931, and 0.871, respectively. Radiomic features, including the putamen and ventral diencephalon, were ranked as the most important for suggesting JME. Conclusion: Radiomic models using MRI were able to differentiate JME from HCs.

• Journal of the Korean Society of Radiology
• /
• v.18 no.3
• /
• pp.187-201
• /
• 2024

Osteoporosis is a major health issue globally, often remaining undetected until a fracture occurs. To facilitate early detection, deep learning (DL) models were developed to classify osteoporosis using abdominal computed tomography (CT) scans. This study was conducted using retrospectively collected data from 3,012 contrast-enhanced abdominal CT scans. The DL models developed in this study were constructed for using image data, demographic/clinical information, and multi-modality data, respectively. Patients were categorized into the normal, osteopenia, and osteoporosis groups based on their T-scores, obtained from dual-energy X-ray absorptiometry, into normal, osteopenia, and osteoporosis groups. The models showed high accuracy and effectiveness, with the combined data model performing the best, achieving an area under the receiver operating characteristic curve of 0.94 and an accuracy of 0.80. The image-based model also performed well, while the demographic data model had lower accuracy and effectiveness. In addition, the DL model was interpreted by gradient-weighted class activation mapping (Grad-CAM) to highlight clinically relevant features in the images, revealing the femoral neck as a common site for fractures. The study shows that DL can accurately identify osteoporosis stages from clinical data, indicating the potential of abdominal CT scans in early osteoporosis detection and reducing fracture risks with prompt treatment.