• Journal of the Korean Geosynthetics Society
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• v.12 no.2
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• pp.13-23
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• 2013

The Korean Peninsula is considered as a seasonal frozen area that is thawed in the spring and frozen in the winter. The influence of fines of the frost susceptibility of subgrade soils were established by laboratory freezing tests simulating closely the thermal conditions in the field. During the winter season, the climate is heavily influenced by the cold and dry continental high pressure. Because of siberian air mass, the temperature of January is $-6{\sim}-7^{\circ}C$ on average. This chilly weather generate the frost heaving by freezing the moisture of soil and damage potential of the geotechnical structure. In the freezing soil, the ice lenses increase the freeze portion of soil by absorbing the ground water with capillary action. However, the capillary characteristics differ from the sort of soil on the state of freezing condition. In this study, ten soil samples are prepared. The basic physical property tests were performed by following the Korean Industrial Standard and the soil specimens were classified by the Unified Soil Classification System (USCS). These classified soils are used to perform the laboratory opened systems freezing test in order to determine the frost heaving characteristics of soils such as unfrozen water content, heaving amount, and freezing depth.

• Journal of Korean Philosophical Society
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• v.123
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• pp.87-110
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• 2012

The kitsch was emerged from the people's cultural desire in the conditions of the various duplicating technology, the capital economy system, and the civil revolution in the western modern mass society. But it is underestimated constantly because of the conspicious consumption and the aesthetic inadequacy. Even though some kitsches are elevated to the 'kitsch arts' in the historical description of the modern arts, still the most of kitsches are remained as 'just kitsches' and excluded from the aesthetic research according to the double standard. In this essay, I research for whether anti-kitsch theory is convincing theoretically and practically. Anti-kitsch theory criticizes the kitsch on the basis of the modernist aesthetics, in which the 'fine art' provokes the aesthetic pleasure in the disinterested contemplation. But kitsch purposes for the sensual gratification and the sentimentality. So the anti-kitish theorists conclude that the kitsch is the bad taste. In critically analyzing the argumentation of Greenberg's. Kaplan's and $C{\tilde{a}}linescu^{\prime}s$, I refute the privileged prejudice of the ideal critic. They don't justify the criteria of the classification of 'art'/ 'kitsch'. They supplement the economical and the political grounds for the evaluative theory of the kitsch. But the argumentation of the kitsch is consumed conspicuously and results in the unlettered masses is not sufficient. People produce and enjoy the kitsches in the various ways. People envelope the genres, styles and media of the kitsches and they try to suggest the new horizon of the popular aesthetics. So anti-kitsch theories cannot be accepted because they adhere to the elitism and formalism. The exclusion of the kitsch is the derogation for people's taste. Also they didn't reflect the contemporary cultural practice and the aesthetic needs in the system of post-art. The alternative aesthetics of the kitsch is the topic of my next essay.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.845-856
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• 2020

This study proposes a bridge evaluation system for indivisible permit vehicles such as hydraulic cranes. The permit loads for the bridge evaluation are divided into three categories: routine permit loads, special permit 1 loads, and special permit 2 loads. Routine permit and special permit 1 vehicles are allowed to cross a bridge with normal traffic. For these two permits, the standard lane model in the Korean Highway Bridge Design Code was adopted to consider normal traffic in the same lane. Special permit 2 vehicles are assumed to cross a bridge without other traffic. Structural analyses of two prestressed-beam bridges and two steel box girder bridges were conducted for the proposed permit loads. The rating factors of the four bridges for all permit loads were calculated as sufficiently large values for the moment and shear force so that crossing the bridges can be permitted. A reliability assessment of the bridges was performed to identify the reliability levels for the permit vehicles. It was confirmed that the reliability level of the minimum required strength obtained by the load-resistance factors yields the target reliability index of the design code for the permit vehicles.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.225-236
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• 2023

Policy implications were derived by comparing/analyzing innovative SMEs and general SMEs that obtained innovation certification from 2015 to 2021 in terms of survival period. Work experience, scale (employment, capital and debt size, sales and operating profit) Korean standard industry classification (2 digit) was used to select general SMEs similar to innovative SMEs. Survival period was calculated by defining suspension, closure and overdue equivalent to default as events. As a result of the survival analysis, innovative SMEs showed a 9.8% reduction in the risk of delinquency compared to general SMEs, indicating that the survival period of innovative SMEs was significantly longer. In addition, it was found that the work experience and size (employment, capital) of SMEs had a positive effect on the survival period, but debt had a negative effect on the survival period. This means that the innovation certification system centered on innovation capabilities and future growth potential is a significant indicator in terms of survival period. As a result, it was concluded that the benefits and support policies provided by the innovation certification system need to be more systematic and sophisticated by reflecting the work experience and industry for the actual growth and survival of SMEs.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.2
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• pp.28-35
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• 2024

Corrosion inside electronic packages significantly impacts the system performance and reliability, necessitating non-destructive diagnostic techniques for system health management. This study aims to present a non-destructive method for assessing corrosion in copper interconnects using the Smith chart, a tool that integrates the magnitude and phase of complex impedance for visualization. For the experiment, specimens simulating copper transmission lines were subjected to temperature and humidity cycles according to the MIL-STD-810G standard to induce corrosion. The corrosion level of the specimen was quantitatively assessed and labeled based on color changes in the R channel. S-parameters and Smith charts with progressing corrosion stages showed unique patterns corresponding to five levels of corrosion, confirming the effectiveness of the Smith chart as a tool for corrosion assessment. Furthermore, by employing data augmentation, 4,444 Smith charts representing various corrosion levels were obtained, and artificial intelligence models were trained to output the corrosion stages of copper interconnects based on the input Smith charts. Among image classification-specialized CNN and Transformer models, the ConvNeXt model achieved the highest diagnostic performance with an accuracy of 89.4%. When diagnosing the corrosion using the Smith chart, it is possible to perform a non-destructive evaluation using electronic signals. Additionally, by integrating and visualizing signal magnitude and phase information, it is expected to perform an intuitive and noise-robust diagnosis.

• International Journal of Highway Engineering
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• v.11 no.4
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• pp.69-78
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• 2009

Korea has achieved significant economic growth with building the Gyeongbu Expressway. As the number of new road construction projects has decreased, it becomes more important to maintain optimal status of the current road networks. One of the best ways to accomplish it is weight enforcement as active control measure of traffic load. This study is to develop High-speed Weigh-in-motion System in order to enhance efficiency of weight enforcement, and to analyze patterns of overloaded trucks on highways through the system. Furthermore, it is to review possibilities of developing overweight control system with application of the HS-WIM system. The HS-WIM system developed by this study consists of two sets of an axle load sensor, a loop sensor and a wandering sensor on each lane. A wandering sensor detects whether a travelling vehicle is off the lane or not with the function of checking the location of tire imprint. The sensor of the WIM system has better function of classifying types of vehicles than other existing systems by detecting wheel distance and tire type such as single or dual tire. As a result, its measurement errors regarding 12 types of vehicle classification are very low, which is an advantage of the sensor. The verification tests of the system under all conditions showed that the mean measurement errors of axle weight and gross axle weight were within 15 percent and 7 percent respectively. According to the WIM rate standard of the COST-323, the WIM system of this study is ranked at B(10). It means the system is appropriate for the purpose of design, maintenance and valuation of road infrastructure. The WIM system in testing a 5-axle cargo truck, the most frequently overloaded vehicle among 12 types of vehicles, is ranked at A(5) which means the system is available to control overloaded vehicles. In this case, the measurement errors of axle load and gross axle load were within 8 percent and 5 percent respectively. Weight analysis of all types of vehicles on highways showed that the most frequently overloaded vehicles were type 5, 6, 7 and 12 among 12 vehicle types. As a result, it is necessary to use more effective overweight enforcement system for vehicles which are seriously overloaded due to their lift axles. Traffic volume data depending upon vehicle types is basic information for road design and construction, maintenance, analysis of traffic flow, road policies as well as research.

• Journal of agricultural medicine and community health
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• v.30 no.1
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• pp.1-14
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• 2005

Objectives: This study attempts to analyze the length of hospital stay and expenses of frequent disease admitted in a Vaterans Hospital. Methods: Data was collected from January 1, 2001 to December 31, 2003 from the Claim records of 9,640 patients in a Vaterans Hospital. Results: The results were as follows: 1. In age & sex distribution, there was male 70.9%, female 29.1%, and 35.8% of them is 70 age group. Frequency by insurance program was Health insurance 78.1%, Medical aid 14.2%, no insurance 4.1%, others 3.6%. Distribution of each department was internal medicine 28.3%, orthopedic surgery 21.3%, surgery 16.6%, neurosurgey 7.1%, pediatrics 5.9%. Also, in the veterans group, male to female patient ratio was 99.3% male to 0.7% female, them over 70 years old was 51.6%, and them which live in daejeon was 43.5%. 2. In frequency of disease, there was gastroenteritis 4.8%, pneumonia 3.8%, cartaract 3.7%, cerebral infarct 3.2%, hyperplasia of prostate 3.0%. In frequency of korean standard classification of diseases, there was injury and poisoning and certain other consequences of external causes 17.1%, diseases of digestive system 16.1%, diseases of musculoskeletal system and connective tissue 13.9%, diseases of respiratory system 9.4%, diseases of genitourinary system 8.6%. Also, in veterans group, frequency of them was diseases of musculoskeletal system and connective tissue 19.4%, diseases of digestive system 16.8%, injury and poisoning and certain other consequences of external causes 15.7%, diseases of genitourinary system 9.7%, diseases of circuatory system 8.2%. 3. Average length of hospital stay was 29.0 days for total patients, 51.8 days for the veterans group, 15.7 days for the non-veterans one. Average total expenses was 3,669,579 won, the veterans group 7,263,877 won, the non-veterans one 1,560,333 won. The ratio of insurer to insuree was 55.2 : 44.8, the ratio of amount paid by patient in the veterans group 61.7%, in the non-veterans one 33.0%. 4. In items of medical expenses, fee for hospital accommodation was 34.7%, fee for medication 13.2%(injection 7.8%, drug 5.4%), fee for service 48.6%(physical therapy 26.3%, operation 9.7%, laboratory examination 5.2%, radiological examination 3.1%, etc), others 3.4%. In them for the veterans group, fee for physical therapy was 35.3%, fee for hospital accommodation 35.2%, fee for injection 6.2%, fee for operation 5.9%, for the non-veterans one, fee for hospital accommodation 35.7%, fee for operation 16.4%, fee for injection 11.4%, fee for laboratory examination 8.3%. 5. In the comparison of the frequency by Korean standard classification of diseases and distance between the hospital and home, the region under 21.5Km was more frequent in symptoms, signs an abnormal clinical and laboratory findings 56.0%, injury and poisoning and certain other consequences of external causes 55.6%, diseases of the eye and adnexa 52.9%, the one over 21.5Km was more frequent in neoplasms 57.4%, diseases of musculoskeletal system and connective tissue 55.9%, diseases of genitourinary system 53.5%.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• KDI Journal of Economic Policy
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• v.12 no.4
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• pp.21-46
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• 1990

This paper, a sequel to Yoo and Lee (1990), attempts to investigate the interindustry determinants of technical efficiency in Korea's manufacturing industries, and also to conduct an exploratory analysis on the stability of technical efficiency over time. The hypotheses set forth in this paper are most found in the existing literature on technical efficiency. They are, however, revised and shed a new light upon, whenever possible, to accommodate any Korea-specific conditions. The set of regressors used in the cross-sectional analysis are chosen and the hypotheses are posed in such a way that our result can be made comparable to those of similar studies conducted for the U.S. and Japan by Caves and Barton (1990) and Uekusa and Torii (1987), respectively. It is interesting to observe a certain degree of similarity as well as differentiation between the cross-section evidence on Korea's manufacturing industries and that on the U.S. and Japanese industries. As for the similarities, we can find positive and significant effects on technical efficiency of relative size of production and the extent of specialization in production, and negative and significant effect of the variations in capital-labor ratio within industries. The curvature influence of concentration ratio on technical efficiency is also confirmed in the Korean case. There are differences, too. We cannot find any significant effects of capital vintage, R&D and foreign competition on technical efficiency, all of which were shown to be robust determinants of technical efficiency in the U.S. case. We note, however, that the variables measuring capital vintage effect, R&D and the degree of foreign competition in Korean markets are suspected to suffer from serious measurement errors incurred in data collection and/or conversion of industrial classification system into the KSIC (Korea Standard Industrial Classification) system. Thus, we are reluctant to accept the findings on the effects of these variables as definitive conclusions on Korea's industrial organization. Another finding that interests us is that the cross-industry evidence becomes consistently strong when we use the efficiency estimates based on gross output instead of value added, which provides us with an ex post empirical criterion to choose an output measure between the two in estimating the production frontier. We also conduct exploratory analyses on the stability of the estimates of technical efficiency in Korea's manufacturing industries. Though the method of testing stability employed in this paper is never a complete one, we cannot find strong evidence that our efficiency estimates are stable over time. The outcome is both surprising and disappointing. We can also show that the instability of technical efficiency over time is partly explained by the way we constructed our measures of technical efficiency. To the extent that our efficiency estimates depend on the shape of the empirical distribution of plants in the input-output space, any movements of the production frontier over time are not reflected in the estimates, and possibilities exist of associating a higher level of technical efficiency with a downward movement of the production frontier over time, and so on. Thus, we find that efficiency measures that take into account not only the distributional changes, but also the shifts of the production frontier over time, increase the extent of stability, and are more appropriate for use in a dynamic context. The remaining portion of the instability of technical efficiency over time is not explained satisfactorily in this paper, and future research should address this question.