• Journal of agricultural medicine and community health
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• v.43 no.4
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• pp.224-233
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• 2018

Objectives: This study was conducted to identify the relations between multiple chronic diseases and peridontal diseases in Korean adults. Methods: A total of 4,142 cases was set for analysis, who aged 35 and over and finished with the third year health survey and oral health check-up of the fifth Korea National Health and Nutrition Examination Survey(2012). Peridontal disease was defined if community periodontal index(CPI) was 3(formation of paradental cyst of more than 4mm) or 4(formation of paradental cyst of more than 6mm). Results: The subjects consisted of 48.5% male and 51.5% female. The prevalence rate of peridontal disease was found to be 30.1% in total. In peridontal disease the more the age increased, and the lower the education level and income level as well as the more where the residential area was rural, the higher the prevalence rate was(p<0.01). According to the number of multiple chronic conditions the prevalence rate of periodontal disease accounted for 27.8%, 31.9%, 33.1%, and 35.2% when there were 0, 1, 2, and 3 or more chronic diseases respectively. As a result of logistic regression analysis, gender, age, education level, residential area, current smoking, and use of oral hygienic products were found to be significant factors on peridontal disease. Conclusions: This research revealed the prevalence rate of peridontal disease was 30.1% in Korean adults and health behaviors affecting on periodontal disease were more significant.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.73-80
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• 2005

Recently there have been many efforts to support searching and browsing based on the visual content of image and multimedia data. Most existing approaches to content-based image retrieval rely on query by example or user based low-level features such as color, shape, texture. But these methods of query are not easy to use and restrict. In this paper we propose a method for automatic color object extraction and labelling to support multiple queries of content-based image retrieval system. These approaches simplify the regions within images using single colorizing algorithm and extract color object using proposed Color and Spatial based Binary tree map(CSB tree map). And by searching over a large of number of processed regions, a index for the database is created by using proposed labelling method. This allows very fast indexing of the image by color contents of the images and spatial attributes. Futhermore, information about the labelled regions, such as the color set, size, and location, enables variable multiple queries that combine both color content and spatial relationships of regions. We proved our proposed system to be high performance through experiment comparable with another algorithm using 'Washington' image database.

• Korean Journal of Radiology
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• v.20 no.5
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• pp.812-822
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• 2019

Objective: To assess the diagnostic value of combining diffusion-weighted imaging (DWI) with conventional magnetic resonance imaging (MRI) for differentiating between pathologic and traumatic fractures at extremities from metastasis. Materials and Methods: Institutional Review Board approved this retrospective study and informed consent was waived. This study included 49 patients each with pathologic and traumatic fractures at extremities. The patients underwent conventional MRI combined with DWI. For qualitative analysis, two radiologists (R1 and R2) independently reviewed three imaging sets with a crossover design using a 5-point scale and a 3-scale confidence level: DWI plus non-enhanced MRI (NEMR; DW set), NEMR plus contrast-enhanced fat-saturated T1-weighted imaging (CEFST1; CE set), and DWI plus NEMR plus CEFST1 (combined set). McNemar's test was used to compare the diagnostic performances among three sets and perform subgroup analyses (single vs. multiple bone abnormality, absence/presence of extra-osseous mass, and bone enhancement at fracture margin). Results: Compared to the CE set, the combined set showed improved diagnostic accuracy (R1, 84.7 vs. 95.9%; R2, 91.8 vs. 95.9%, p < 0.05) and specificity (R1, 71.4% vs. 93.9%, p < 0.005; R2, 85.7% vs. 98%, p = 0.07), with no difference in sensitivities (p > 0.05). In cases of absent extra-osseous soft tissue mass and present fracture site enhancement, the combined set showed improved accuracy (R1, 82.9-84.4% vs. 95.6-96.3%, p < 0.05; R2, 90.2-91.1% vs. 95.1-95.6%, p < 0.05) and specificity (R1, 68.3-72.9% vs. 92.7-95.8%, p < 0.005; R2, 83.0-85.4% vs. 97.6-98.0%, p = 0.07). Conclusion: Combining DWI with conventional MRI improved the diagnostic accuracy and specificity while retaining sensitivity for differentiating between pathologic and traumatic fractures from metastasis at extremities.

• Journal of Korean Neurosurgical Society
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• v.62 no.4
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• pp.442-449
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• 2019

Objective : Bone mineral density (BMD) is an important consideration during fusion surgery. Although dual X-ray absorptiometry is considered as the gold standard for assessing BMD, quantitative computed tomography (QCT) provides more accurate data in spine osteoporosis. However, QCT has the disadvantage of additional radiation hazard and cost. The present study was to demonstrate the utility of artificial intelligence and machine learning algorithm for assessing osteoporosis using Hounsfield units (HU) of preoperative lumbar CT coupling with data of QCT. Methods : We reviewed 70 patients undergoing both QCT and conventional lumbar CT for spine surgery. The T-scores of 198 lumbar vertebra was assessed in QCT and the HU of vertebral body at the same level were measured in conventional CT by the picture archiving and communication system (PACS) system. A multiple regression algorithm was applied to predict the T-score using three independent variables (age, sex, and HU of vertebral body on conventional CT) coupling with T-score of QCT. Next, a logistic regression algorithm was applied to predict osteoporotic or non-osteoporotic vertebra. The Tensor flow and Python were used as the machine learning tools. The Tensor flow user interface developed in our institute was used for easy code generation. Results : The predictive model with multiple regression algorithm estimated similar T-scores with data of QCT. HU demonstrates the similar results as QCT without the discordance in only one non-osteoporotic vertebra that indicated osteoporosis. From the training set, the predictive model classified the lumbar vertebra into two groups (osteoporotic vs. non-osteoporotic spine) with 88.0% accuracy. In a test set of 40 vertebrae, classification accuracy was 92.5% when the learning rate was 0.0001 (precision, 0.939; recall, 0.969; F1 score, 0.954; area under the curve, 0.900). Conclusion : This study is a simple machine learning model applicable in the spine research field. The machine learning model can predict the T-score and osteoporotic vertebrae solely by measuring the HU of conventional CT, and this would help spine surgeons not to under-estimate the osteoporotic spine preoperatively. If applied to a bigger data set, we believe the predictive accuracy of our model will further increase. We propose that machine learning is an important modality of the medical research field.

• The KIPS Transactions:PartD
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• v.14D no.3 s.113
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• pp.319-328
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• 2007

As the coverage of Web services become wider and the number of implementation cases is growing, the importance of applying the Web services quality model to real world is increased. For maintaining the level of Web services qualify, it should be required to study on assurance method of Web services qualify level. Assurance for Web services, which is newly proposed by OASIS TC, means the totality of activities for managing the quality level of them. For managing Web service quality, Web service associates could usually use SLA(Service Level Agreement) method in which a service consumer contracts for some service level with a service provider and gives for penalty or pays incentives according to the result of evaluation of services. But, there are some difficulties in applying SLA to Web services, because Web services have publicity, multiple users, and 3rd party for management. So, we need a new assurance method for Web service by considering the characteristics of Web services. This paper provides the new concept of committed assurance level for Web services. This concept can be defined as the set of maximum level of quality expected by each user, which provide the consistent view of Web service quality. This paper presents the method for duality associates to preserve some quality level of Web service by using this concept.

• Journal of the Korea Convergence Society
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• v.7 no.5
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• pp.247-254
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• 2016

The purpose of this study is to identify the degree of participation sport for how this affects the objectified body consciousness of the Physically Disabled. The subjects were enrolled in the members participating in the sport for the disabled, while 221 people living in the city A. Data processing was carried out frequency analysis, factor analysis using SPSS 21.0 program, the analysis of the specific factors independent t-test and the way analysis of variance and multiple regression analysis was carried out. All statistical significance level was set at .05. First, population, gender (male), age of the sociological characteristics of the handicapped (40, 50), the objectification of the body consciousness level of the disability rating (Level 4) showed that a positive effect. Second, there are life sports participation rate (exercise duration, exercise time, exercise intensity) has positive effects on the body shame of objectification of the body consciousness of the handicapped, the body monitoring Exercise Period, the body shame, the intensity of exercise, control beliefs this exercise showed that each time a positive impact.

• KEPCO Journal on Electric Power and Energy
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• v.8 no.2
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• pp.159-179
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• 2022

Often a network becomes complex, and multiple entities would get in charge of managing part of the whole network. An example is a utility grid. While the entire grid would go under a single utility company's responsibility, the network is often split into multiple subsections. Subsequently, each subsection would be given as the responsibility area to the corresponding sub-organization in the utility company. The issue of how to make subsystems of adequate size and minimum number of interconnections between subsystems becomes more critical, especially in real-time simulations. Because the computation capability limit of a single computation unit, regardless of whether it is a high-speed conventional CPU core or an FPGA computational engine, it comes with a maximum limit that can be completed within a given amount of execution time. The issue becomes worsened in real time simulation, in which the computation needs to be in precise synchronization with the real-world clock. When the subject of the computation allows for a longer execution time, i.e., a larger time step size, a larger portion of the network can be put on a computation unit. This translates into a larger margin of the difference between the worst and the best. In other words, even though the worst (or the largest) computational burden is orders of magnitude larger than the best (or the smallest) computational burden, all the necessary computation can still be completed within the given amount of time. However, the requirement of real-time makes the margin much smaller. In other words, the difference between the worst and the best should be as small as possible in order to ensure the even distribution of the computational load. Besides, data exchange/communication is essential in parallel computation, affecting the overall performance. However, the exchange of data takes time. Therefore, the corresponding consideration needs to be with the computational load distribution among multiple calculation units. If it turns out in a satisfactory way, such distribution will raise the possibility of completing the necessary computation in a given amount of time, which might come down in the level of microsecond order. This paper presents an effective way to split a given electrical network, according to multiple criteria, for the purpose of distributing the entire computational load into a set of even (or close to even) sized computational loads. Based on the proposed system splitting method, heavy computation burdens of large-scale electrical networks can be distributed to multiple calculation units, such as an RTDS real time simulator, achieving either more efficient usage of the calculation units, a reduction of the necessary size of the simulation time step, or both.

• Journal of Preventive Medicine and Public Health
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• v.21 no.1 s.23
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• pp.195-206
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• 1988

Two major issues of the blood bank management are quality assurance and inventory control. Recently, in Korea blood donation has gained popularity increasingly to allow considerable improvement of the quality assurance with respect to blood collection, transportation, storage, component preparation skills and hematological tests. Nevertheless the inventory control, the other issue of blood bank management, has been neglected so far. For the supply of blood by donation barely meets the demand, the blood bank policy on the inventory control has been 'the more the better.' The shortage itself by no means unnecessitate inventory control. In fact, in spite of shortage, no small amount of blood is outdated. The efficient blood inventory control makes it possible to economize the blood usage in the practice of state-of-the-art medical care. For the efficient blood inventory control in Korean hospitals, this tudy is to develop formulae forecasting the standard blood inventory level and suggest a set of policies improving the blood inventory control. For this study informations of $A^+$ whole bloods and packed cells inventory control were collected from a University Hospital and the Central Blood Bank of the Korean Red Cross. Using this informations, 1,461 daily blood inventory records were formulated.48 varieties of blood inventory control environment were identified on the basis of selected combinations of 4 inventory control variables-crossmatch, transfusion, inhospital donation and age of bloods from external supply. In order to decide the optimal blood inventory level for each environment, simulation models were designed to calculate the measures of performance of each environment. After the decision of 48 optimal blood inventory levels, stepwise multiple regression analysis was started where the independent variables were 4 inventory control variables and the dependent variable was optimal inventory level of each environment. Finally the standard blood inventory level decision rule was developed using the backward elimination procedure to select the best regression equation. And the effective alternatives of the issuing policy and crossmatch release period were suggested according to the measures of performance under the condition of the standard blood inventory level. The results of this study' were as follows ; 1. The formulae to calculate the standard blood inventory level($S^*$)was $S^*=2.8617X(d)^{0.9342}$ where d is the mean daily crossmatch(demand) for a blood type. 2. The measures of performace - outdate rate, average period of storage, mean age of transfused bloods, and mean daily available inventory level - were improved after maintenance of the standard inventory level in comparison with the present system. 3. Issuing policy of First In-First Out(FIFO) decreased the outdate rate, while Last In-First Out(LIFO) decreased the mean age of transfused bloods. The decrease of the crossmatch release period reduced the outdate rate and the mean age of transfused bloods.

• Journal of Broadcast Engineering
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• v.14 no.4
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• pp.450-462
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• 2009

So far, many methods for segmenting single images or video have been proposed, but few methods have dealt with multiple images with analogous content. These images, which we term consistent scene images, include concurrent images of a scene and gathered images of a similar foreground, and may be collectively utilized to describe a scene or as input images for multi-view stereo. In this paper, we present a method to segment these images with minimum user input, specifically, manual segmentation of one image, by iteratively propagating information via multi-level cues with adaptive confidence depending on the nature of the images. Propagated cues are used as the bases to compute multi-level potentials in an MRF framework, and segmentation is done by energy minimization. Both cues and potentials are classified as low-, mid-, and high- levels based on whether they pertain to pixels, patches, and shapes. A major aspect of our approach is utilizing mid-level cues to compute low- and mid- level potentials, and high-level cues to compute low-, mid-, and high- level potentials, thereby making use of inherent information. Through this process, the proposed method attempts to maximize the amount of both extracted and utilized information in order to maximize the consistency of the segmentation. We demonstrate the effectiveness of the proposed method on several sets of consistent scene images and provide a comparison with results based only on mid-level cues [1].

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1859-1864
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• 2004

An effective methodology is reported for the optimal design of multisite batch production/transportation and storage networks under uncertain demand forecasting. We assume that any given storage unit can store one material type which can be purchased from suppliers, internally produced, internally consumed, transported to or from other plant sites and/or sold to customers. We further assume that a storage unit is connected to all processing and transportation stages that consume/produce or move the material to which that storage unit is dedicated. Each processing stage transforms a set of feedstock materials or intermediates into a set of products with constant conversion factors. A batch transportation process can transfer one material or multiple materials at once between plant sites. The objective for optimization is to minimize the probability averaged total cost composed of raw material procurement, processing setup, transportation setup and inventory holding costs as well as the capital costs of processing stages and storage units. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the storage inventory. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two sub-problems. The first yields analytical solutions for determining lot sizes while the second is a separable concave minimization network flow subproblem whose solution yields the average material flow rates through the networks for the given demand forecast scenario. The result of this study will contribute to the optimal design and operation of large-scale supply chain system.