• The Korean Nurse
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• v.36 no.1
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• pp.108-117
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• 1997

This study was carried out to examine the standards for evaluation of laboratory facilities and equipment. These constitute the most important yet vulnerable area of our system of higher education among the six school evaluation categories provided by the Korean Council for University Education. To obtain data on the present situation of holdings and management of laboratory facilities and equipment at nursing schools in Korea, questionnaires were prepared by members of a special committee of the Korea Nursing Education Society on the basis of the Standards for University Laboratory Facilities and Equipment issued by the Ministry of Education. The questionnaires were sent to nursing schools across the nation by mail on October 4, 1995. 39 institutions completed and returned the questionnaires by mail by December 31 of the same year. The results of the analysis of the survey were as follows: 1. The Physical Environment of Laboratories According to the results of investigation of 14 nursing departments at four-year colleges, laboratories vary in size ranging from 24 to 274.91 pyeong ($1{\;}pyeong{\;}={\;}3.3m^2).$. The average number of students in a laboratory class was 46.93 at four-year colleges, while the number ranged from 40 to 240 in junior colleges. The average floor space of laboratories at junior colleges, however, was almost the same as those, of laboratories at four-year colleges. 2. The Actual State of Laboratory Facilities and Equipment Laboratory equipment possessed by nursing schools at colleges and universities showed a very wide distribution by type, but most of it does not meet government standards according to applicable regulations while some types of equipment are in excess supply. The same is true of junior colleges. where laboratory equipment should meet a different set of government standards specifically established for junior colleges. Closer investigation is called for with regard to those types of equipment which are in short supply in more than 80 percent of colleges and universities. As for the types of equipment in excess supply, investigation should be carried out to determine whether they are really needed in large quantities or should be installed. In many cases, it would appear that unnecessary equipment is procured, even if it is already obsolete, merely for the sake of holding a seemingly impressive armamentarium. 3. Basic Science Laboratory Equipment Among the 39 institutions, five four-year colleges were found to possess equipment for basic science. Only one type of essential equipment, tele-thermometers, and only two types of recommended equipment, rotators and dip chambers, were installed in sufficient numbers to meet the standards. All junior colleges failed to meet the standards in all of equipment categories. Overall, nursing schools at all of the various institutions were found to be below per in terms of laboratory equipment. 4. Required Equipment In response to the question concerning which type of equipment was most needed and not currently in possession, cardiopulmonary resuscitation (CPR) machines and electrocardiogram (ECG) monitors topped the list with four respondents each, followed by measuring equipment. 5. Management of Laboratory Equipment According to the survey, the professors in charge of clinical training and teaching assistants are responsible for management of the laboratory at nursing schools at all colleges and universities, whereas the chief of the general affairs section or chairman of the nursing department manages the laboratory at junior colleges. This suggests that the administrative systems are more or less different. According to the above results, laboratory training could be defined as a process by which nursing students pick up many of the nursing skills necessary to become fully qualified nurses. Laboratory training should therefore be carefully planned to provide students with high levels of hands-on experience so that they can effectively handle problems and emergencies in actual situations. All nursing students should therefore be thoroughly drilled and given as much on-the-job experience as possible. In this regard, there is clearly a need to update the equipment criteria as demanded by society's present situation rather than just filling laboratory equipment quotas according to the current criteria.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.37-50
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• 2020

Information security has become an important issue in the world. Various information and communication technologies, such as the Internet of Things, big data, cloud, and artificial intelligence, are developing, and the need for information security is increasing. Although the necessity of information security is expanding according to the development of information and communication technology, interest in information security investment is insufficient. In general, measuring the effect of information security investment is difficult, so appropriate investment is not being practice, and organizations are decreasing their information security investment. In addition, since the types and specification of information security measures are diverse, it is difficult to compare and evaluate the information security countermeasures objectively, and there is a lack of decision-making methods about information security investment. To develop the organization, policies and decisions related to information security are essential, and measuring the effect of information security investment is necessary. Therefore, this study proposes a method of constructing an investment portfolio for information security measures using game theory and derives an optimal defence probability. Using the two-person game model, the information security manager and the attacker are assumed to be the game players, and the information security countermeasures and information security threats are assumed as the strategy of the players, respectively. A zero-sum game that the sum of the players' payoffs is zero is assumed, and we derive a solution of a mixed strategy game in which a strategy is selected according to probability distribution among strategies. In the real world, there are various types of information security threats exist, so multiple information security measures should be considered to maintain the appropriate information security level of information systems. We assume that the defence ratio of the information security countermeasures is known, and we derive the optimal solution of the mixed strategy game using linear programming. The contributions of this study are as follows. First, we conduct analysis using real performance data of information security measures. Information security managers of organizations can use the methodology suggested in this study to make practical decisions when establishing investment portfolio for information security countermeasures. Second, the investment weight of information security countermeasures is derived. Since we derive the weight of each information security measure, not just whether or not information security measures have been invested, it is easy to construct an information security investment portfolio in a situation where investment decisions need to be made in consideration of a number of information security countermeasures. Finally, it is possible to find the optimal defence probability after constructing an investment portfolio of information security countermeasures. The information security managers of organizations can measure the specific investment effect by drawing out information security countermeasures that fit the organization's information security investment budget. Also, numerical examples are presented and computational results are analyzed. Based on the performance of various information security countermeasures: Firewall, IPS, and Antivirus, data related to information security measures are collected to construct a portfolio of information security countermeasures. The defence ratio of the information security countermeasures is created using a uniform distribution, and a coverage of performance is derived based on the report of each information security countermeasure. According to numerical examples that considered Firewall, IPS, and Antivirus as information security countermeasures, the investment weights of Firewall, IPS, and Antivirus are optimized to 60.74%, 39.26%, and 0%, respectively. The result shows that the defence probability of the organization is maximized to 83.87%. When the methodology and examples of this study are used in practice, information security managers can consider various types of information security measures, and the appropriate investment level of each measure can be reflected in the organization's budget.

• Journal of Biomedical Engineering Research
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• v.21 no.3 s.61
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• pp.321-331
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• 2000

Multiple 15-hue tests were designed and implemented on a PC in the study so as to quickly and quantitatively evaluate color vision acuity. Difficulty of the test was control)ed by the value of CDBACC (color difference between adjacent color chips) calculated using a CIELAB formula. The multiple 15-hue tests consist of eight of the hue tests (test 3-10) and three of the basic color (red, green, blue) tests (test 11-13). The 15 colors used for the hue tests were specified by the 15 color coordinates that were located at a constant distance (d = 2. 3. 5. 7, 10, 20, 30. 40) from white reference in the CIE chromaticity coordinate system and were separated by a constant color difference (CDBACC = 0.75, 1.1, 1.8. 2.5. 3.5. 7.5. 11, 14) from the adjacent chips. The color coordinates for the 15 chips for the basic color tests were the same as those of the 15 points spaced equally by a constant color difference (6.87 for the green color test. 7.27 for the red color test, 7.86 for the blue color test) from the white reference along the axis of red, green and blue. Thirty normal subjects who were not color blind were taken to undergo the multiple 15-hue tests. It was observed that most of the subjects correctly arranged color chips for the tests with CDBACC greater than 5, whereas no one correctly answered for those with CDBACC less than 2. Rapid changes in the number of the subjects correctly arranged took place when CDBACC of the tests was between 2 and 4.5. In the basic color tests, unlike the hue tests having similar values of CDBACC, it was seen that the subjects arranged color chips even less correctly. It was found that JNCD (just noticeable color difference) - a measure of color vision acuity was about 3 in average for the subjects. The JNCD was chosen as the value of the CDBACC of the test for which about $50\%$ of the subjects failed to successfully arrange color chips. ERCCA (error rate of color chips arrangement) for the test with CDBACC the same as the JNCD was shown to be about $20\%$. It is expected that the multi 15-hue tests implemented on a PC in the study will be an economical tool to quickly and quantitatively evaluate color vision acuity and, accordingly, the tests can be used for early diagnosis to massive potential patients suffering from diseases (ex. diabetes, glaucoma) which may induce changes in color vision acuity.

• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.360-373
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• 2017

The BTO-a projects is the types, which has a demand risk among the type of PPP projects in Korea. When demand risk is realized, private investor encounters financial difficulties due to lower revenue than its expectation and the government may also have a problem in stable infrastructure operation. In this regards, the government has applied various risk sharing policies in response to demand risk. However, the amount of government's risk sharing is the government's contingent liabilities as a result of demand uncertainty, and it fails to be quantified by the conventional NPV method of expressing in the text of the concession agreement. The purpose of this study is to estimate the value of investment risk sharing by the government considering the demand risk in the profit sharing system (BTO-a) introduced in 2015 as one of the demand risk sharing policy. The investment risk sharing will take the form of options in finance. Private investors have the right to claim subsidies from the government when their revenue declines, while the government has the obligation to pay subsidies under certain conditions. In this study, we have established a methodology for estimating the value of investment risk sharing by using the Black - Scholes option pricing model and examined the appropriateness of the results through case studies. As a result of the analysis, the value of investment risk sharing is estimated to be 12 billion won, which is about 4% of the investment cost of the private investment. In other words, it can be seen that the government will invest 12 billion won in financial support by sharing the investment risk. The option value when assuming the traffic volume risk as a random variable from the case studies is derived as an average of 12.2 billion won and a standard deviation of 3.67 billion won. As a result of the cumulative distribution, the option value of the 90% probability interval will be determined within the range of 6.9 to 18.8 billion won. The method proposed in this study is expected to help government and private investors understand the better risk analysis and economic value of better for investment risk sharing under the uncertainty of future demand.

• Korean Journal of Community Nutrition
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• v.24 no.3
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• pp.232-244
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• 2019

Objectives: This study evaluated the nutritional status and prevalence of metabolic syndrome of the people who participated in the KNHANES according to the number of household members. They were assessed by using information from the 2013~2014 Korea National Health and Nutrition Examination Survey (KNHANES). Methods: A total of 6,088 persons aged 19 years and over participated in 2013~2014 KNHANES, and they were classified into three groups according to the number of household members (single-person, two-person, three-person & over). The dietary behavior, nutritional status, health-related factors and the prevalence of metabolic syndrome of the subjects were investigated with using information from the survey questionnaires of KNHANES. The nutrient intake data of the subjects were obtained by the 24-hour recall method and this was analyzed for evaluating the nutrition adequacy ratio and the index of nutritional quality. The prevalence of metabolic syndrome among the subjects, and according to the study groups, was estimated using the blood and physical measurement data of the subjects. Results: As for EQ-5D index available for all the health states generated by the EQ-5D descriptive system, the single-person household member was the lowest among all the household types. The index of nutrition quality for protein, crude fiber, calcium, phosphorus, potassium, riboflavin and vitamin C in the single-person household was lower than that of the two-person or the three-person and over households (p<0.001). The mean adequacy ratio of single-person households was significantly decreased compared with that of the other types of households (p<0.001). The prevalence of metabolic syndrome was higher in the single-person households than that in the multiple-person households (p<0.001). Conclusions: These results showed that dietary behaviors, nutrition status and health status might be influenced by the number of household members. The results from this study would be useful for improving Korean people's dietary life and health status by implementing evidence-based, specialized intervention for the members of diverse types of households.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.1
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• pp.139-149
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• 2019

The purpose of this study is to contribute to the minimization of the social cost due to the insolvency by improving the success rate of the startups by providing useful information to the founders and the start-up support institutions through analysis of non-financial information affecting the failure of the startups. This study is aimed at entrepreneurs. The entrepreneurs that are defined by the credit guarantee institutions generally refer to entrepreneurs within 5 years of establishment. The data used in the study are sampled from the companies that were supported by the start-up guarantee from January 2014 to December 2013 as the end of December 2017. The total number of sampled firms is 2,826, 2,267 companies (80.2%), and 559 non-performing companies (19.8%). The non-financial information of the entrepreneur was divided into the entrepreneur characteristics information, the entrepreneur characteristics information, the entrepreneur asset information and the entrepreneur 's credit information, and cross-tabulations and logistic regression analysis were conducted. As a result of cross-tabulations, univariate analysis showed that personal credit rating, presence in the industry, presence of residential housing, presence of employees, and presence of financial statements were selected as significant variables. As a result of the logistic regression analysis, three variables such as personal credit rating, occupation in the industry, and presence of residential house were found to be important factors affecting the failure of founding companies. This result shows the importance of entrepreneur 's personal credibility and experience and entrepreneur' s assets in business management. The start-up support institutions should reflect these results in the entrepreneur 's credit evaluation system, and the entrepreneurs need training on the importance of the personal credit and the management plan in the entrepreneurial education. The results of this analysis will contribute to the minimization of the incapacity of startups by providing useful non-financial information to founders and start-up support organizations.

• Journal of the Korean earth science society
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• v.41 no.6
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• pp.617-629
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• 2020

Sea surface temperature (SST), which plays an important role in climate change and global environmental change, can be divided into skin sea surface temperature (SSST) observed by satellite infrared sensors and the bulk temperature of sea water (BSST) measured by instruments. As sea surface temperature products distributed by many overseas institutions represent temperatures at different depths, it is essential to understand the relationship between the SSST and the BSST. In this study, we constructed an observation system of infrared radiometer onboard a marine research vessel for the first time in Korea to measure the SSST. The calibration coefficients were prepared by performing the calibration procedure of the radiometer device in the laboratory prior to the shipborne observation. A series of processes were applied to calculate the temperature of the layer of radiance emitted from the sea surface as well as that from the sky. The differences in skin-bulk temperatures were investigated quantitatively and the characteristics of the vertical structure of temperatures in the upper ocean were understood through comparison with Himawari-8 geostationary satellite SSTs. Comparison of the skin-bulk temperature differences illustrated overall differences of about 0.76℃ at Jangmok port in the southern coast and the offshore region of the eastern coast of the Korean Peninsula from 21 April to May 6, 2020. In addition, the root-mean-square error of the skin-bulk temperature differences showed daily variation from 0.6℃ to 0.9℃, with the largest difference of 0.83-0.89℃ at 1-3 KST during the daytime and the smallest difference of 0.59℃ at 15 KST. The bias also revealed clear diurnal variation at a range of 0.47-0.75℃. The difference between the observed skin sea surface temperature and the satellite sea surface temperature showed a mean square error of approximately 0.74℃ and a bias of 0.37℃. The analysis of this study confirmed the difference in the skin-bulk temperatures according to the observation depth. This suggests that further ocean shipborne infrared radiometer observations should be carried out continuously in the offshore regions to understand diurnal variation as well as seasonal variations of the skin-bulk SSTs and their relations to potential causes.

• Economic and Environmental Geology
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• v.55 no.1
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• pp.63-76
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• 2022

Dacitic tuffs, 97 to 118 m thick, were recovered from the lower part of the subsurface Seongdongri Formation, Janggi Basin, which was drilled to assess the potential for underground storage of carbon dioxide. The tuffs are divided into four depositional units(Unit 1 to 4) based on internal structures and particle componentry. Unit 1 and Units 3/4 are ignimbrites that accumulated in subaerial and subaqueous settings, respectively, whereas Unit 2 is braided-stream deposits that accumulated during a volcanic quiescence, and no dacitic tuff is observed. A series of analysis shows that mordenite and clinoptilolite mainly fill the vesicles of glass shards, suggesting their formation by replacement and dissolution of volcanic glass and precipitation from interstitial water during burial and diagenesis. Glass-replaced clinoptilolite has higher Si/Al ratios and Na contents than the vesicle-filling clinoptilolite in Units 3. However, the composition of clinoptilolite becomes identical in Unit 4, irrespective of the occurrence and location. This suggests that the Si/Al ratio and pH in the interstitial water increased with time because of the replacement and leaching of volcanic glass, and that the composition of interstitial water was different between the eastern and western parts of the basin during the formation of the clinoptilolite in Units 1 and 3. It is also inferred that the formation of the two zeolite minerals was sequential according to the depositional units, i.e., the clinoptilolite formed after the growth of mordenite. To summarize, during a volcanic quiescence after the deposition of Unit 1, pH was higher in the western part of the basin because of eastward tilting of the basin floor, and the zeolite ceased to grow because of the closure of the pore space as a result of the growth of smectite. On the other hand, clinoptilolite could grow in the eastern part of the basin in an open system affected by groundwater, where braided stream was developed. Afterwards, Units 3 and 4 were submerged under water because of the basin subsidence, and the alkali content of the interstitial water increased gradually, eventually becoming identical in the eastern and western parts of the basin. This study thus shows that volcanic deposits of similar composition can have variable distribution of zeolite mineral depending on the drainage and depositional environment of basins.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.1-17
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• 2017

The deep learning framework is software designed to help develop deep learning models. Some of its important functions include "automatic differentiation" and "utilization of GPU". The list of popular deep learning framework includes Caffe (BVLC) and Theano (University of Montreal). And recently, Microsoft's deep learning framework, Microsoft Cognitive Toolkit, was released as open-source license, following Google's Tensorflow a year earlier. The early deep learning frameworks have been developed mainly for research at universities. Beginning with the inception of Tensorflow, however, it seems that companies such as Microsoft and Facebook have started to join the competition of framework development. Given the trend, Google and other companies are expected to continue investing in the deep learning framework to bring forward the initiative in the artificial intelligence business. From this point of view, we think it is a good time to compare some of deep learning frameworks. So we compare three deep learning frameworks which can be used as a Python library. Those are Google's Tensorflow, Microsoft's CNTK, and Theano which is sort of a predecessor of the preceding two. The most common and important function of deep learning frameworks is the ability to perform automatic differentiation. Basically all the mathematical expressions of deep learning models can be represented as computational graphs, which consist of nodes and edges. Partial derivatives on each edge of a computational graph can then be obtained. With the partial derivatives, we can let software compute differentiation of any node with respect to any variable by utilizing chain rule of Calculus. First of all, the convenience of coding is in the order of CNTK, Tensorflow, and Theano. The criterion is simply based on the lengths of the codes and the learning curve and the ease of coding are not the main concern. According to the criteria, Theano was the most difficult to implement with, and CNTK and Tensorflow were somewhat easier. With Tensorflow, we need to define weight variables and biases explicitly. The reason that CNTK and Tensorflow are easier to implement with is that those frameworks provide us with more abstraction than Theano. We, however, need to mention that low-level coding is not always bad. It gives us flexibility of coding. With the low-level coding such as in Theano, we can implement and test any new deep learning models or any new search methods that we can think of. The assessment of the execution speed of each framework is that there is not meaningful difference. According to the experiment, execution speeds of Theano and Tensorflow are very similar, although the experiment was limited to a CNN model. In the case of CNTK, the experimental environment was not maintained as the same. The code written in CNTK has to be run in PC environment without GPU where codes execute as much as 50 times slower than with GPU. But we concluded that the difference of execution speed was within the range of variation caused by the different hardware setup. In this study, we compared three types of deep learning framework: Theano, Tensorflow, and CNTK. According to Wikipedia, there are 12 available deep learning frameworks. And 15 different attributes differentiate each framework. Some of the important attributes would include interface language (Python, C ++, Java, etc.) and the availability of libraries on various deep learning models such as CNN, RNN, DBN, and etc. And if a user implements a large scale deep learning model, it will also be important to support multiple GPU or multiple servers. Also, if you are learning the deep learning model, it would also be important if there are enough examples and references.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.3 no.2
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• pp.141-151
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• 1993

Blood samples obtained from 200 adults who had visited the "S" general hospital were analyzed to compare the zinc protoporphyrin (ZPP) levels quantified by high performance liquid chromatograph (HPLC) and by hematofluorometer (HF) to investigate the methodological difference if any and the relationship between the levels of blood lead and ZPP among no-lead exposed adults. Also investigated were the distribution of ZPP and protoporphyrin IX (PPIX) concentrations, the establishment of normal levels of blood ZPP and blood lead, and the contribution of age and sex factors to these values. These subjects had no previous occupational exposure to lead. The results obtained were as follows : 1. The mean values of blood lead for male and female subjects were $9.46{\pm}2.44{\mu}g/dl$ and $8.09{\pm}2.17{\mu}g/dl$, respectively. The difference observed in the mean concentrations between male and female subjects was statistically very significant. 2. The mean values of blood ZPP by HPLC for male and female subjects were $15.94{\pm}4.55{\mu}g/dl$ and $22.26{\pm}6.61{\mu}g/dl$, respectively. The difference observed in the mean concentrations between male and female subjects was statistically not significant. The mean values of blood PPIX by HPLC for male and female subjects were $2.51{\pm}1.78{\mu}g/dl$ and $2.81{\pm}1.56{\mu}g/dl$, respectively. The difference observed in the mean concentrations between male and female subjects was statistically not significant. 3. The mean values of blood ZPP by HF for male and female subjects were $28.44{\pm}7.11{\mu}g/dl$ and $37.77{\pm}8.04{\mu}g/dl$, respectively. The difference observed in the mean concentrations between male and female subjects was statistically very significant. 4. No statistically significant correlation was found between the levels of blood ZPP and blood lead. 5. The ratio of ZPP and protoporphyrin IX (PPIX) concentration to erythrocyte protoporphyrin (EP, EP=ZPP+PPIX) concentration was 87.4% and 12.6%, respectively. 6. A statistically very significant correlation was found between the ZPP concentrations determined by HPLC and the values by HF (r=0.7565). The ZPP concentraitons quantified by HF were 1.75 times as high as the values obtained by HPLC. 7. The blood ZPP concentrations quantified by HPLC, HF, and spectrofluorometer (SF) from the blood samples obtained from 14 lead-exposed workers and from 16 no-lead exposed adults showed wide variations. The ZPP concentrations by HF were the highest followed by the levels obtained by SF and by HPLC. In the exposed group, no statistically significant difference was found among three methods of quantifying blood ZPP levels. In the no-lead exposed group, however, statistically significant difference was observed among these methods. The ZPP concentrations by HF were about twice as high as those of by HPLC or by SF. Among three methods of quantifying blood ZPP (HPLC, SF and HF), the results revealed significant difference. Therefore it is suggested that objective methods of quantifying blood ZPP and a system of correcting different ZPP levels be developed by the ministry of Labor.