• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.1
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• pp.49-56
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• 2024

An automated dynamic structural analysis module stands as a crucial element within a structural integrated mitigation system. This module must deliver prompt real-time responses to enable timely actions, such as evacuation or warnings, in response to the severity posed by the structural system. The finite element method, a widely adopted approximate structural analysis approach globally, owes its popularity in part to its user-friendly nature. However, the computational efficiency and accuracy of results depend on the user-provided finite element mesh, with the number of elements and their quality playing pivotal roles. This paper introduces a computationally efficient adaptive mesh generation scheme that optimally combines the h-method of node movement and the r-method of element division for mesh refinement. Adaptive mesh generation schemes automatically create finite element meshes, and in this case, representative strain values for a given mesh are employed for error estimates. When applied to dynamic problems analyzed in the time domain, meshes need to be modified at each time step, considering a few hundred or thousand steps. The algorithm's specifics are demonstrated through a standard cantilever beam example subjected to a concentrated load at the free end. Additionally, a portal frame example showcases the generation of various robust meshes. These examples illustrate the adaptive algorithm's capability to produce robust meshes, ensuring reasonable accuracy and efficient computing time. Moreover, the study highlights the potential for the scheme's effective application in complex structural dynamic problems, such as those subjected to seismic or erratic wind loads. It also emphasizes its suitability for general nonlinear analysis problems, establishing the versatility and reliability of the proposed adaptive mesh generation scheme.

• Journal of Nutrition and Health
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• v.48 no.4
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• pp.344-351
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• 2015

Purpose: During the recent decades, the age at menarche continued to decline in Korea and worldwide. Prior studies have suggested that early menarche may increase the risk of various social, psychological, and physical health problems in young adolescent girls, but little is known about the determinants associated with early menarche. The purpose of this study is to evaluate independent determinants of early menarche among 5th~6th female graders in South Korea. Methods: Our analysis was conducted in 95 menarcheal girls and 95 age-matched pre-menarcheal girls residing in Daegu, South Korea. Demographic and lifestyle characteristics were collected using survey questionnaires for children and parents. Dietary information was assessed by 2 day~24 hour food records and survey questionnaires, which were completed by both children and their parents. Anthropometric data were obtained from the student health check-ups at the school. Results: A multiple logistic regression analysis using a conditional likelihood method was performed for simultaneous evaluation of several risk factors. There were significant differences in that higher proportion of obesity (OR, odds ratio = 5.60, 95% CI, confidence interval = 1.34~23.42), shorter sleep duration (OR = 0.45, 95% CI = 0.23~0.87), and younger mother's age at menarche (OR = 0.64, 95% CI = 0.44~0.93) were observed in the menarcheal group compared to the pre-menarcheal group. Conclusion: These findings indicate a possible association of sleep duration, mother's menarcheal age, and obesity with age at menarche. A well-planned, prospective cohort study is warranted to examine causal relationship.

• The Korean Journal of Financial Management
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• v.21 no.1
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• pp.205-229
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• 2004

The deviation from put-call parity condition may affect market prices since it provides an opportunity of arbitrage to many participants. This study uses the KOSPI200 index data and examines the interdependence among spot, futures, and options contracts by examining whether the deviations from the parity have significant roles in price formation. Whenever the parity condition is violated, the deviation tends to affect the prices significantly in most markets. The results show that positive values of deviation are associated with the fall of the prices in the spot and put option contracts and the rise of the call option premiums, thus decreasing the deviations. Also, the decreasing impact of deviations lasts for at Beast an hour in most markets. Futures prices, however, do not show clear relations with the deviations, which suggests the possibility that futures markets lead other markets.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.1
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• pp.11-17
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• 2004

This study was conducted to determine the relationship of stomatal responses, photosynthesis, and intercellular $CO_2$ concentration( $C_{i}$) of Betula Species to ozone exposure. Five Betula Species(B. costata, B. davurica, B. schmidtii, B. platyphylla var, iaponica and B, ermani) were grown in the greenhouse. One-year-old potted seedlings of the five Betula Species were exposed to ozone(100 pub) for 8 hours da $y^{-1}$ for 5 weeks in a fumigation chamber. Net photosynthesis was significantly different among species and treatments from early in the period of the fumigation. Stomatal conductance and transpiration rate differences among species and treatments became significant after three weeks of fumigation. $C_{i}$ was significantly different only among treatments; $C_{i}$ of four species, except for B. davurica, was higher than that of control plants. Carboxylation efficiency and photo-respiration rate were significantly different among species or treatments; carboxylation efficiency and photo-respiration rate of the five Betula Species were decreased by ozone treatment. It was concluded that stomatal closure of Betula Species may be the result of the reduction of photosynthesis and rubisco activity and the resulting increase of $C_{i}$. The higher $C_{i}$ likely resulted from reduced photosynthesis because of physiological processes.ocesses.

• Journal of Internet Computing and Services
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• v.19 no.4
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• pp.53-63
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• 2018

The traditional mass media function of conveying information and forming public opinion has rapidly changed into an environment in which information and opinions are shared through social media with the development of ICT technology, and such social media further strengthens its influence. In other words, it has been confirmed that the influence of the public opinion through the production and sharing of public opinion on political, social and economic changes is increasing, and this change is already in use on the political campaign. In addition, efforts to grasp and reflect the opinions of the public by utilizing social media are being actively carried out not only in the political area but also in the public area. The purpose of this study is to explore the possibility of using social media based public opinion in educational policy. We collected media data, analyzed the main topic and probability of occurrence of each topic, and topic trends. As a result, we were able to catch the main interest of the public(the 'Domestic Computer Education Time' accounted for 43.99%, and 'Prime Project Selection' topics was 36.81% and 'Artificial Intelligence Program' topics was 7.94%). In addition, we could get a suggestion that flexible policies should be established according to the timing of the curriculum and the subject of the policy even if the category of the policy is same.

• The Journal of Engineering Geology
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• v.16 no.2 s.48
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• pp.201-214
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• 2006

To study the relationship between rainfall conditions and landslides according to a geological condition in land-slides areas such asJangheung Kyounggi, Sangju and Pohang Kyoungbuk, the data of rainfall and landslides are investigated and analyzed. Many landslides occurred at these areas because of the heavy rainfall in two or four days of the summer 1998. The data of rainfall are collected in observatories within a 50km radius from landslides occurrence areas, and the data of landslides are investigated directly in landslides areas. The data of rainfall are the accumulative rainfall and the rainfall intensity, and the data of landslides are the occurrence frequency considering the geological condition. These data are analyzed statistically to know the relationship the rainfall and landslides. The landslides are concentrated in the heavy rainfall area from the analysis of these data. It knows that the land-slides are triggered by the heavy rainfall. Meanwhile, the rainfall factors such as the accumulative rainfall, the rain-fall intensity and the dropping time are different in each landslides area, and the shape and frequency of landslides are different respectively. The landslides have occurred in the area of high accumulative rainfall, while the land-slides have not occurred around that area. Therefore, the rainfall is very important factor induced by the landslides, and the accumulative rainfall is really related to the frequency of landslides.

• The Korean Journal of Blood Transfusion
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• v.23 no.2
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• pp.162-168
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• 2012

Background: Potassium, the most common cation in the intracellular space, plays a critical role in our physiology. Potassium imbalance may cause life-threatening problems, ranging from general weakness to cardiac arrest due to ventricular fibrillation. For emergency physicians, detection of such derangement within a short period of time is of critical importance. In this study, we wanted to determine whether analysis of whole blood samples can be used as a screening tool for potassium imbalance by comparative analysis of whole blood and serum samples. Methods: Two samples were drawn from 227 patients. The whole blood sample was taken from the radial artery and contained in a commercially available arterial blood collection syringe with a lithium-heparin coating. The serum sample was contained in a commercially available vacuum bottle in a non-additive silicone coated tube and transported to the laboratory. The study population was divided into three groups, patients with normal whole blood potassium, patients with decreased whole blood potassium, and patients with elevated whole blood potassium. Potassium levels for each group were coupled with serum potassium levels and compared. Results: No significant difference in potassium values was observed between whole blood and serum samples (P<0.05). Strong associations were observed among the three groups (normal range, hypokalemia, and hyperkalemia group). Compared to the normal group (r=0.851), the hyperkalemia group showed a stronger association between variables (r=0.897), and the hypokalemia group showed a weaker association (r=0.760). Their correlation coefficients were highly significant (P<0.05). Conclusion: Our study illustrates that point-of-care testing using whole blood with whole blood can be a reliable screening tool when treating patients with suspicious potassium abnormality, especially in hyperkalemia patients.

• Journal of the Korea Society of Computer and Information
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• v.18 no.12
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• pp.1-9
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• 2013

Even though the multiple pages TLB are effective in improving the performance, a conventional method with OS support cannot utilize multiple page sizes in user application. Thus, we propose a new multiple-TLB structure supporting multiple page sizes for high performance and low power consumption without any operating system support. The proposed TLB is organised as two parts of a S-TLB(Small TLB) with a small page size and a L-TLB(Large TLB) with a large page size. Both are designed as fully associative bank structures. The S-TLB stores small pages are evicted from the L-TLB, and the L-TLB stores large pages including a small page generated by the CPU. Each one bank module of S-TLB and L-TLB can be selectively accessed base on particular one and two bits of the virtual address generated from CPU, respectively. Energy savings are achieved by reducing the number of entries accessed at a time. Also, this paper proposed the simple 1-bit LRU policy to improve the performance. The proposed LRU policy can present recently referenced block by using an additional one bit of each entry on TLBs. This method can simply select a least recently used page from the L-TLB. According to the simulation results, the proposed TLB can reduce Energy * Delay by about 76%, 57%, and 6% compared with a fully associative TLB, a ARM TLB, and a Dual TLB, respectively.

• Composites Research
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• v.32 no.5
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• pp.199-205
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• 2019

The composite material has the advantage that the fibers can be arranged in a desired direction and can be manufactured in one piece. However, micro voids can be formed due to micro air, moisture or improper curing temperature or pressure, which may cause the deterioration in mechanical strength. In this paper, the composite panels with different thicknesses were made by varying the curing pressure in an autoclave vacuum bag process and their microporosities were evaluated. Microporosity was measured by image analysis method, acid digestion method, and combustion method and their correlation with ultrasonic attenuation coefficient was analyzed. From the test results, it was found that the acid digestion method had the highest accuracy and the lower the curing pressure, the higher the microporosity and the ultrasonic attenuation coefficient. In addition, the microporosity and the ultrasonic attenuation coefficient were increased as the thickness of the composite panel was increased at the same curing pressure.

• The Journal of Society for e-Business Studies
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• v.24 no.1
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• pp.105-120
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• 2019

The World Health Organization (WHO) and other government agencies aroundthe world have warned against antibiotic-resistant bacteria due to abuse of antibiotics and are strengthening their care and monitoring to prevent infection. However, it is highly necessary to develop an expeditious and accurate prediction and estimating method for preemptive measures. Because it takes several days to cultivate the infecting bacteria to identify the infection, quarantine and contact are not effective to prevent spread of infection. In this study, the disease diagnosis and antibiotic prescriptions included in Electronic Health Records were embedded through neural embedding model and matrix factorization, and deep learning based classification predictive model was proposed. The f1-score of the deep learning model increased from 0.525 to 0.617when embedding information on disease and antibiotics, which are the main causes of antibiotic resistance, added to the patient's basic information and hospital use information. And deep learning model outperformed the traditional machine hospital use information. And deep learning model outperformed the traditional machine learning models.As a result of analyzing the characteristics of antibiotic resistant patients, resistant patients were more likely to use antibiotics in J01 than nonresistant patients who were diagnosed with the same diseases and were prescribed 6.3 times more than DDD.