• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.37 no.2
• /
• pp.227-232
• /
• 2013

This study proposes a method for predicting the reliability of the barrel in small arms by analyzing the dispersion. The periodicity with which the barrel needs to be changed can be determined by detecting the inner surface directly or by inspecting scratches inside the barrel using an optical sensor. However, soldiers and directors in the logistics command need a more easy way to check the periodicity of barrel. Therefore, this study focuses on the relation between the firing round and the dispersion. A simple equation can be experimentally derived from pre-tests and analyses. This equation is confirmed through firing tests. In this sense, it can be easily applied to determine the periodicity with which the barrel of small arms needs to be changed in the field army.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.19
• /
• pp.8447-8450
• /
• 2014

Background: To evaluate factors for predicting the granulosa cell tumor of the ovary (GCTO) pre-operatively. Materials and Methods: This retrospective designed study was conducted on 34 women with GCTO as the study group and 76 women with benign ovarian cysts as the control group. Data were recorded from the hospital database and included age, body mass index (BMI), parity, serum estradiol ($E_2$) levels, diameter of the mass, ultrasonographic features, serum CA125 level, risk of malignancy index (RMI), duration of menopause, postoperative histopathology result, and the neutrophil/lymphocyte ratio (NLR). Results: The demographic parameters showed no statistically significant difference between the groups. Preoperative diameter of the mass, CA125, duration of menopause, and neutrophil/lymphocyte ratio were significantly different between the groups. ROC curve analysis demonstrated that diameter of the mass, serum estradiol and Ca125 levels, RMI and NLR may be discriminative factors in predicting GCTO preoperatively. Conclusions: In conclusion, we think that a careful preoperative workshop including diameter of the mass, serum estradiol ($E_2$) and Ca125 levels, RMI and NLR may predict GCTO and may prevent incomplete approaches.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.10 no.1
• /
• pp.47-54
• /
• 2015

Recently, rapid urbanization and industrialization had increased the air pollution in major cities by increasing the fuel consumption. Air pollution models have been widely used for air quality management in many countries. Also, a lot of related studies have been conducted using air dispersion models. In this study, The meteorological preprocessing program was developed to convert the korea meteorological data to the U.S. meteorological data and to expand the usability of air dispersion models of U.S. EPA. In addition, the usability evaluation was carried out through a case study. In the results of the evaluation of the program, this program was accurately convert the Korea meteorological data to the U.S. meteorological data, and the prediction was carried out without a error in air quality modeling. Therefore, the program showed a high utilization as meteorological data pre-processing tool.

• Journal of the Korean Geotechnical Society
• /
• v.32 no.1
• /
• pp.45-53
• /
• 2016

Generally, conventional transport infrastructures consist of compacted granular materials. Their stiffness and response greatly depend on the particle sizes and distributions, and application of loading on the surface over a foundation may induce deformation in both the surface and the underlying foundations. Therefore, a better understanding of the deformation characteristics on granular materials and the prediction are needed. For this reason, an attempt to evaluate and predict deformation of coarse materials based on the discrete element method is presented in this paper. An algorithm for particle distribution curve analysis was formulated and incorporated into the discrete element program. The results show that the discrete element model with particle distribution curve is suitable for estimating stress deformation in a pre-peak response. Unlike conventional uniform or random particle distribution, the response can be obtained by the use of the proper model and approach.

• Journal of The Korean Association For Science Education
• /
• v.17 no.2
• /
• pp.179-189
• /
• 1997

In this study, a conceptual change model for effective laboratories was developed and its instructional effect on students' achievement, the acquisition of scientific conceptions, and the attitudes toward science was investigated. Considering several conceptual change models in literature and Korean educational situations, the conceptual change model was developed. The model consists of 5 stages; preliminary, prediction, exploration, consolidation and reconstruction, and application. The treatment and control groups (2 classes) were selected from a middle school in Seoul, and taught about the changes of states, density, and dissolution for three weeks. Prior to instruction, the Group Assessment of Logical Thinking and the Learning Approach Questionnaire were administered, and their scores were used as covariate and / or blocking variable. To examine students' alternative conceptions before the instructions, a pre-conceptions test was also administered. After the instructions, students' achievement, the acquisition of scientific conceptions, and the attitudes toward science were measured with a researcher-made achievement test, a post-conceptions test, and the subtests of the Test of Science-Related Attitudes, respectively. The results indicated that the score of the treatment group was significantly higher than that of the control group in the post-conceptions test. The students in the treatment group had also less alternative conceptions than those in the control group. However, there were no significant differences for the achievement and the attitudes toward science. Educational implications are discussed.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• 2008.11a
• /
• pp.597-600
• /
• 2008

Recently, Several Mega project are been performing as a multi-dimensional development project in Korea, but some problem has been revealed about deficiency of the history, experience, and skill. A multi-dimensional development project require the technology which can manage mega project to its specific at the level of program management. predicting schedule and schedule management are the most important for mega project, been performing over several years. This research shows the method of predicting and planning schedule in the early stage as a pre-study on developing a technology of schedule management. First of all, it presents the development of database considering the specific of mega project that can accumulate the history of schedule and search the schedule according to the type of single and multi building. Also it suggests the method of prediction schedule by creating scenarios according to owner requirements and cash flow, affecting schedule management in the early stage, and the shortening possibility of schedule duration using CCPM theory.

• Journal of Advanced Marine Engineering and Technology
• /
• v.31 no.3
• /
• pp.263-271
• /
• 2007

The heat transfer coefficient and pressure drop during 9as cooling process of $CO_2$ (R744) in a helically coiled copper tube with the inner diameter of 4.55 mm and outer diameter of 6.35 mm were investigated experimentally. The main components of the refrigerant loop are a receiver, a variable-speed pump. a mass flow meter a pre-heater and a helically coiled type gas cooler (test section). The refrigerant mass fluxes are varied from 200 to $800kg/m^2s$ and the inlet pressures of gas cooler are 7.5 to 10.0 MPa. The heat transfer coefficients of $CO_2$ in a helically coiled tube are higher than those in a horizontal tube. The Pressure drop of $CO_2$ in the gas cooler shows a relatively good agreement with those predicted by Ito's correlation developed for single-phase in a helically coiled tube. The local heat transfer coefficient of $CO_2$ agrees well with the correlation by Pitla et al. However. at the region near pseudo-critical temperature. the experiments indicate higher values than the Pitla et al correlation. Therefore, various experiments in helically coiled tubes have to be conducted and it is necessary to develop the reliable and accurate prediction determining the heat transfer and pressure drop of $CO_2$ in a helically coiled tube.

• Korean Journal of Acupuncture
• /
• v.33 no.3
• /
• pp.102-113
• /
• 2016

Objectives : This study is aimed at developing and discussing the prediction model of blood stasis pattern of traditional Korean medicine(TKM) using machine learning algorithms: multiple logistic regression and decision tree model. Methods : First, we reviewed the blood stasis(BS) questionnaires of Korean, Chinese, and Japanese version to make a integrated BS questionnaire of patient-reported outcomes. Through a human subject research, patients-reported BS symptoms data were acquired. Next, experts decisions of 5 Korean medicine doctor were also acquired, and supervised learning models were developed using multiple logistic regression and decision tree. Results : Integrated BS questionnaire with 24 items was developed. Multiple logistic regression models with accuracy of 0.92(male) and 0.95(female) validated by 10-folds cross-validation were constructed. By decision tree modeling methods, male model with 8 decision node and female model with 6 decision node were made. In the both models, symptoms of 'recent physical trauma', 'chest pain', 'numbness', and 'menstrual disorder(female only)' were considered as important factors. Conclusions : Because machine learning, especially supervised learning, can reveal and suggest important or essential factors among the very various symptoms making up a pattern identification, it can be a very useful tool in researching diagnostics of TKM. With a proper patient-reported outcomes or well-structured database, it can also be applied to a pre-screening solutions of healthcare system in Mibyoung stage.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.19 no.3
• /
• pp.253-261
• /
• 2001

Nowadays, various water quality prediction models have been studied, then these models can support the method which evaluate the effect of various alternative water quality management by simulation without experimentation. But, It is necessary to create complex input data file for applying these water quality model and even though the appropriate result is extracted, it is impossible to use as decision making data effectively because of the limitation of expression of model itself. As this study is about the stream water quality modeling, for overcoming the model's above limitation, by developing an interface which can calculate the pollutant load of watershed, I could create a input data file and visualize the simulation result so that I was going to integrate water quality model and GSIS using Flexible coupling applied to GSIS in the pre-process and post-process on model. The QUAL2E model, used in this study, is verified by stream water quality model in previous various results of study and has many examples through previous study, because that is appropriate to water quality model, especially in Korea, and comparatively accurate and their usage is quite simple.

• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2005.09a
• /
• pp.361-365
• /
• 2005

Over the past few years, the complex and subtle roles of microRNA (miRNA) in gene regulation have been increasingly appreciated. Computational approaches have played one of important roles in identifying miRNAs from plant and animals, as well as in predicting their putative gene target. We present a new approach of comprehensive analysis of the evolutionarily conserved element scores and applied data compression technique to detect putative miRNA genes. We used the evolutionarily conserved elements [19] (see more detail on method and material) to calculate for base-by-base along the candidate pre-miRNA gene region by detecting common conserved pattern from target sequence. We applied the data compression technique [20] to detect unknown miRNA genes. This zipping method devises, without loss of generality with respect to the nature of the character strings, a method to measure the similarity between the strings under consideration [20]. Our experience to using our new computational method for detecting miRNA gene identification (or miRNA gene prediction) has been stratified and we were able to find 28 putative miRNA genes.