• Research in Community and Public Health Nursing
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• v.10 no.1
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• pp.70-79
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• 1999

This study attempts to encourage the development of a rehabilitation delivery system as a substitute service for hospitalization such as a community based intermediate facility or home health care. We need substitute services for hospitalization to curtail the length of stay for inpatients due to car accidents. It focused on developing an estimation for early discharge based on a detailed statement of treatment from medical records of 109 inpatients who were hospitalized at General Hospital in 1997. This study has three specific purposes: First, to find the mean length of stay and mean medical expenditure. Second, to estimate the mean of early discharge from the mean length of stay. Third, to analyize the income effect per bed from early discharge. In order to analyze the length of stay and medical expenditure of inpatients the author conducted a micro and macro-analysis with medical expenditure records. To estimate the early discharge we examined with a group of 4 experts decreases in the amount of treatment after surgery, in treatments, in tests, in drug methods. We also looked their vital signs, the start of ROM exercise, the time removel, a patient's visitations, and possible stable conditions. In addition to identifing the income effect due to an early discharge, the data was analyzed by an SPSS-PC for windows and Excell program with a regression analysis model. The research findings are as follows: First, the mean length of stay was 47.56 days, but the mean length of stay due to early discharge was 32.26 days. The estimation of early discharge days was shown to depend on the length of stay. The longer the length of stay, the longer the length before discharge. For example, if the patient stayed under 14 days the mean length of stay was 7.09 while an early discharge was 6.39, whereas if the mean length of stay was 155.73, the early discharge time was 107.43. The mean medical expenditure per day of car accident patients was found to be 169,085 Won, whereas the mean medical expenditure per day was shown to be in a negative linear form according to the length of stay. That is the mean expenditure for under 14 days of stay was 303,015 Won and the period of the hospitalization of 15 days to 29 days was 170,338 Won and those of 30 days to 59 days was 113,333 Won. The estimation of the income effect due to being discharged 16 days was around 2,350,000 Won with a regression analysis model. However, this does not show the real benefits from an early discharge, but only the income increasing amount without considering prime medical cost at a general hospital. Therefore, we need further analysis on cost containments and benefits incending turn over rates and medical prime costs. From these research findings, the following suggestions have been drawn, we need to develop strategies on a rehabilitation delivery system focused on consumers for the 21st century. Varions intermediate facilities and home health care should be developed in the community as a substitute for shortening the length of stay in hospitals. In home health care cases, patients who want rehabilitation services as a substitute for hospitalization in cooperation with private health insurance companies might be available immediately.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.30 no.3
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• pp.408-412
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• 1997

The cytogenetic analysis of river puffer, Takifugu obscurus belongs to Family Tetraodontidae, was performed. The chromosome number of T. obscurus was 44 and the fundamental number was 64. Heteromorphic sex chromosomes were not found. The mean cellular size and nuclear size were $11.01\times7.95{\mu}m$ and $4.05\times3.15{\mu}m$, respectively. The mean surface area and volume in cell and nucleus were $68.76{\mu}m^2\;and\;366.00{\mu}m^3,\;10.06{\mu}m^2\;and\;21.36{\mu}m^3$, respectively. The number of erythrocyte of both female and male was $12\~13\times10^5/m\ell$. Gill tissues from diploid individuals had cells with one or two nucleoli. These cytogenetic studies should be used for cytotaxonomy and as a valuable estimation of polyploidy to come in T. obscurus.

• Journal of the Earthquake Engineering Society of Korea
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• v.28 no.3
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• pp.121-128
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• 2024

There are growing concerns that the recently implemented Earthquake Early Warning service is overestimating the rapidly provided earthquake magnitudes (M). As a result, the predicted damages unnecessarily activate earthquake protection systems for critical facilities and lifeline infrastructures that are far away. This study is conducted to improve the estimation accuracy of M by incorporating the observed S-wave seismograms in the near source region after removing the site effects of the seismograms in real time by filtering in the time domain. The ensemble of horizontal S-wave spectra from at least five seismograms without site effects is calculated and normalized to a hypocentric target distance (21.54 km) by using the distance attenuation model of Q(f)=348f^0.52 and a cross-over distance of 50 km. The natural logarithmic mean of the S-wave ensemble spectra is then fitted to Brune's source spectrum to obtain the best estimates for M and stress drop (SD) with the fitting weight of 1/standard deviation. The proposed methodology was tested on the 18 recent inland earthquakes in South Korea, and the condition of at least five records for the near-source region is sufficiently fulfilled at an epicentral distance of 30 km. The natural logarithmic standard deviation of the observed S-wave spectra of the ensemble was calculated to be 0.53 using records near the source for 1~10 Hz, compared to 0.42 using whole records. The result shows that the root-mean-square error of M and ln(SD) is approximately 0.17 and 0.6, respectively. This accuracy can provide a confidence interval of 0.4~2.3 of Peak Ground Acceleration values in the distant range.

• Journal of Oral Medicine and Pain
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• v.46 no.4
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• pp.125-130
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• 2021

Purpose: The dental age estimation of children is performed using dental maturity. Postmortem missing of the anterior teeth or the distortion of image of the anterior teeth in panoramic radiographs can make it difficult to analyze the development of the anterior teeth. This pilot study was conducted to derive a new age estimation method based only on the developmental stage of mandibular posterior teeth. Methods: This study was conducted using panoramic radiographs of 650 subjects aged 3 to 15 years old. The dental developmental stages of the lower left first premolar, second premolar, first molar and second molar were evaluated according to the Demirjian's criteria. The intra-/inter-observer reliability was evaluated, and multiple linear regression analyses were performed including the developmental stage of each tooth as an independent variable. Results: The intra-/inter-observer reliability was 0.9626 and 0.8877, respectively, and showed very high reproducibility. Multiple linear regression analyses were performed for males and females, and the age calculation table was derived by obtaining the intercept and the coefficient according to the development stage of each tooth. The coefficient of determination (r²) of the age calculation method was 0.9634 for male and 0.9570 for female subjects, and the mean difference between chronological age and estimated dental age was -0.42 and -0.21, respectively. Conclusions: This pilot study evaluated the developmental stages of four lower posterior teeth in the Korean group according to Demirjian's criteria, and derived age estimation method. The accuracy was lower than when more teeth were used, but it will be useful to estimate age of children when the anterior teeth are difficult to accurately analyze.

• Journal of Periodontal and Implant Science
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• v.43 no.5
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• pp.215-220
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• 2013

Purpose: Cigarette smoking is a major risk factor in periodontal diseases. The pathogenesis of periodontal diseases may be affected by alterations of the inflammatory response by smoke. Nitric oxide (NO) is a gaseous, colorless, highly reactive, short-lived free radical with a pivotal role in the regulation of various physiological and pathological mechanisms in the body. It is important in host defense and homeostasis, on the one hand, whereas, on the other hand, it modulates the inflammatory response in periodontitis, leading to harmful effects. The aim of this study was to assess the levels of NO in both the serum and saliva of smokers and nonsmokers having chronic periodontitis and to compare them with periodontally healthy controls. Methods: Sixty subjects participated in the study and were divided into three groups: group I, healthy nonsmoking subjects; group II, nonsmoking patients with chronic periodontitis; group III, smoking patients with chronic periodontitis. Each group consisted of twenty subjects. The biochemical estimation of NO in the collected serum and in the saliva was performed using the Griess colorimetric reaction. Results: The results showed that the mean value of the salivary and serum NO was greater in group II than in group I, and also greater in group III than in group II. Conclusions: NO appears to play an important and rather complex role in the immuno-inflammatory process and in the remodeling and maintenance of osseous structures. It is therefore logical that modulation of this mediator has potential for the treatment of a number of inflammatory conditions including periodontal disease.

• Archives of Plastic Surgery
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• v.40 no.3
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• pp.203-208
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• 2013

Background Preoperative volume assessment is useful in breast reconstruction. Magnetic resonance imaging (MRI) and mammography are commonly available to reconstructive surgeons in the care of a patient with breast cancer. This study aimed to verify the accuracy of breast volume measured by MRI, and to identify any factor affecting the relationship between measured breast volume and actual breast weight to derive a new model for accurate breast volume estimation. Methods From January 2012 to January 2013, a retrospective review was performed on a total of 101 breasts from 99 patients who had undergone total mastectomy. The mastectomy specimen weight was obtained for each breast. Mammographic and MRI data were used to estimate the volume and density. A standard statistical analysis was performed. Results The mean mastectomy specimen weight was 340.8 g (range, 95 to 795 g). The mean MRI-estimated volume was $322.2mL^3$. When divided into three groups by the "difference percentage value", the underestimated group showed a significantly higher fibroglandular volume, higher percent density, and included significantly more Breast Imaging, Reporting and Data System mammographic density grade 4 breasts than the other groups. We derived a new model considering both fibroglandular tissue volume and fat tissue volume for accurate breast volume estimation. Conclusions MRI-based breast volume assessment showed a significant correlation with actual breast weight; however, in the case of dense breasts, the reconstructive surgeon should note that the mastectomy specimen weight tends to overestimate the volume. We suggested a new model for accurate breast volume assessment considering fibroglandular and fat tissue volume.

• Nutrition Research and Practice
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• v.15 no.5
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• pp.613-627
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• 2021

BACKGROUND/OBJECTIVES: Despite the widespread use of dietary assessment tools, the validity of food records has not been evaluated in Koreans. We assessed the accuracy of estimated food records and the effect of a short education session in young Korean women. SUBJECTS/METHODS: Thirty women (aged 18-23 yrs) each completed 3 food records during a controlled-feeding study. One educational session was provided on day 2 of the study. Food records were analyzed for the accuracy of food items and portion size estimation according to food group (grains; meat, fish, eggs, and beans; vegetables; fruit; dairy; and oils and sugars) and type of dish (rice, kimchi, soup, side dishes, spreads, beverages, and snacks). Reported food items were categorized as exact, close, or far matches, exclusions, or intrusions. Portion sizes were evaluated as accurate, similar, or inaccurate estimates, or missing. The means of days 2 and 3 were used to assess post-education results. Paired t-tests were performed to assess the effects of the education session. RESULTS: The mean percentages of exact matches, close matches, far matches, and exclusions on day 1 were 80.9%, 10.9%, 2.0%, and 6.2%, respectively, and mean intrusions observed were 0.1. The education session slightly increased the accuracy of recorded food items. The percentages of accurate, similar, and inaccurate estimates, and missing portion sizes were 11.7%, 19.8%, 12.2%, and 56.3%, respectively, at baseline. The percentage of missing portion size estimates decreased to 14.0% after the education session, resulting in an increase in the percentages of all other estimates. An increase was observed in the accuracy of reported portion sizes of vegetables, rice, and kimchi. CONCLUSIONS: In young Korean women, estimated food records are highly accurate for food items but not for portion size estimates without prior education. A short education session can improve the accuracy of portion size estimation.

• Journal of Korean Neurosurgical Society
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• v.49 no.1
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• pp.1-7
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• 2011

Objective: Glutamate is a key excitatory neurotransmitter in the brain, and its excessive release plays a key role in the development of neuronal injury. In order to define the effect of nimodipine on glutamate release, we monitored extracellular glutamate release in real-time in a global ischemia rat model with eleven vessel occlusion. Methods: Twelve rats were randomly divided into two groups: the ischemia group and the nimodipine treatment group. The changes of extracellular glutamate level were measured using microdialysis amperometric biosensor, in coincident with cerebral blood flow (CBF) and electroencephalogram. Nimodipine (0.025 ${\mu}g$/100 gm/min) was infused into lateral to the CBF probe, during the ischemic period. Also, we performed Nissl staining method to assess the neuroprotective effect of nimodipine. Results: During the ischemic period, the mean maximum change in glutamate concentration was $133.22{\pm}2.57\;{\mu}M$ in the ischemia group and $75.42{\pm}4.22\;{\mu}M$ (p<0.001) in the group treated with nimodipine. The total amount of glutamate released was significantly different (P<0.001) between groups during the ischemic period. The %cell viability in hippocampus was $47.50{\pm}5.64$ (p<0.005) in ischemia group, compared with sham group. But, the %cell viability in nimodipine treatment group was $95.46{\pm}6.60$ in hippocampus (p<0.005). Conclusion: From the real-time monitoring and Nissl staining results, we suggest that the nimodipine treatment is responsible for the protection of the neuronal cell death through the suppression of extracellular glutamate release in the 11-VO global ischemia model of rat.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.187-206
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• 2007

The development of computer and information technology has been combined with the information superhighway internet infrastructure, so information widely spreads not only in special fields but also in the daily lives of people. Information ubiquity influences the traditional way of transaction, and leads a new E-commerce which distinguishes from the existing E-commerce. Not only goods as physical but also service as non-physical come into E-commerce. As the scale of E-Commerce is being enlarged as well. It keeps people from finding information they want. Recommender systems are now becoming the main tools for E-Commerce to mitigate the information overload. Recommender systems can be defined as systems for suggesting some Items(goods or service) considering customers' interests or tastes. They are being used by E-commerce web sites to suggest products to their customers who want to find something for them and to provide them with information to help them decide which to purchase. There are several approaches of recommending goods to customer in recommender system but in this study, the main subject is focused on collaborative filtering technique. This study presents a possibility of pre-evaluation for the prediction performance of customer's preference in collaborative filtering before the process of customer's preference prediction. Pre-evaluation for the prediction performance of each customer having low performance is classified by using the statistical features of ratings rated by each customer is conducted before the prediction process. In this study, MovieLens 100K dataset is used to analyze the accuracy of classification. The classification criteria are set by using the training sets divided 80% from the 100K dataset. In the process of classification, the customers are divided into two groups, classified group and non classified group. To compare the prediction performance of classified group and non classified group, the prediction process runs the 20% test set through the Neighborhood Based Collaborative Filtering Algorithm and Correspondence Mean Algorithm. The prediction errors from those prediction algorithm are allocated to each customer and compared with each user's error. Research hypothesis : Two research hypotheses are formulated in this study to test the accuracy of the classification criterion as follows. Hypothesis 1: The estimation accuracy of groups classified according to the standard deviation of each user's ratings has significant difference. To test the Hypothesis 1, the standard deviation is calculated for each user in training set which is divided 80% from MovieLens 100K dataset. Four groups are classified according to the quartile of the each user's standard deviations. It is compared to test the estimation errors of each group which results from test set are significantly different. Hypothesis 2: The estimation accuracy of groups that are classified according to the distribution of each user's ratings have significant differences. To test the Hypothesis 2, the distributions of each user's ratings are compared with the distribution of ratings of all customers in training set which is divided 80% from MovieLens 100K dataset. It assumes that the customers whose ratings' distribution are different from that of all customers would have low performance, so six types of different distributions are set to be compared. The test groups are classified into fit group or non-fit group according to the each type of different distribution assumed. The degrees in accordance with each type of distribution and each customer's distributions are tested by the test of ${\chi}^2$ goodness-of-fit and classified two groups for testing the difference of the mean of errors. Also, the degree of goodness-of-fit with the distribution of each user's ratings and the average distribution of the ratings in the training set are closely related to the prediction errors from those prediction algorithms. Through this study, the customers who have lower performance of prediction than the rest in the system are classified by those two criteria, which are set by statistical features of customers ratings in the training set, before the prediction process.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.1-22
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• 2017

Analysis of future business or investment opportunities, such as business feasibility analysis and company or technology valuation, necessitate objective estimation on the relevant market and expected sales. While there are various ways to classify the estimation methods of these new sales or market size, they can be broadly divided into top-down and bottom-up approaches by benchmark references. Both methods, however, require a lot of resources and time. Therefore, we propose a data-based intelligent demand forecasting system to support evaluation of new business. This study focuses on analogical forecasting, one of the traditional quantitative forecasting methods, to develop sales forecasting intelligence systems for new businesses. Instead of simply estimating sales for a few years, we hereby propose a method of estimating the sales of new businesses by using the initial sales and the sales growth rate of similar companies. To demonstrate the appropriateness of this method, it is examined whether the sales performance of recently established companies in the same industry category in Korea can be utilized as a reference variable for the analogical forecasting. In this study, we examined whether the phenomenon of "mean reversion" was observed in the sales of start-up companies in order to identify errors in estimating sales of new businesses based on industry sales growth rate and whether the differences in business environment resulting from the different timing of business launch affects growth rate. We also conducted analyses of variance (ANOVA) and latent growth model (LGM) to identify differences in sales growth rates by industry category. Based on the results, we proposed industry-specific range and linear forecasting models. This study analyzed the sales of only 150,000 start-up companies in Korea in the last 10 years, and identified that the average growth rate of start-ups in Korea is higher than the industry average in the first few years, but it shortly shows the phenomenon of mean-reversion. In addition, although the start-up founding juncture affects the sales growth rate, it is not high significantly and the sales growth rate can be different according to the industry classification. Utilizing both this phenomenon and the performance of start-up companies in relevant industries, we have proposed two models of new business sales based on the sales growth rate. The method proposed in this study makes it possible to objectively and quickly estimate the sales of new business by industry, and it is expected to provide reference information to judge whether sales estimated by other methods (top-down/bottom-up approach) pass the bounds from ordinary cases in relevant industry. In particular, the results of this study can be practically used as useful reference information for business feasibility analysis or technical valuation for entering new business. When using the existing top-down method, it can be used to set the range of market size or market share. As well, when using the bottom-up method, the estimation period may be set in accordance of the mean reverting period information for the growth rate. The two models proposed in this study will enable rapid and objective sales estimation of new businesses, and are expected to improve the efficiency of business feasibility analysis and technology valuation process by developing intelligent information system. In academic perspectives, it is a very important discovery that the phenomenon of 'mean reversion' is found among start-up companies out of general small-and-medium enterprises (SMEs) as well as stable companies such as listed companies. In particular, there exists the significance of this study in that over the large-scale data the mean reverting phenomenon of the start-up firms' sales growth rate is different from that of the listed companies, and that there is a difference in each industry. If a linear model, which is useful for estimating the sales of a specific company, is highly likely to be utilized in practical aspects, it can be explained that the range model, which can be used for the estimation method of the sales of the unspecified firms, is highly likely to be used in political aspects. It implies that when analyzing the business activities and performance of a specific industry group or enterprise group there is political usability in that the range model enables to provide references and compare them by data based start-up sales forecasting system.