• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.68 no.4
• /
• pp.343-370
• /
• 2023

Developing improved wheat varieties is vital for global food security to meet the rising demand for food. Therefore, assessing the genetic diversity across wheat genotypes is crucial. This study examined the diversity of 168 durum wheat and 47 common wheat collections from 54 different countries using twelve agro-morphological parameters. Geumgang, a prominent Korean common wheat variety, was used as a control. Both qualitative and quantitative agronomical characteristics showed wide variations. Most durum wheats were shown to possess dense spikes (90%), while common wheats showed dense (40%) or loose (38%) spikes, with yellowish-white being the dominant spike color. The majority of the accessions were awned regardless of wheat type, yellowish-white being the main awn color. White or red kernels were produced, with white kernels dominating in both common (74%) and durum (79%) wheats. Days to heading (DH) and days to maturity (DM) were in the ranges of 166-215 and 208-250 days, respectively, while the culm length (CL), spike length (SL), and awn length (AL) were in the ranges of 53.67-163, 5.33-18.67, and 0.50-19.00 cm, respectively. Durum wheats possessed the shortest average DH, DM, and SL, while common wheat had the longest CL and AL (p < 0.05). Common wheats also exhibited the highest average one-thousand-kernel weight. Hierarchical cluster analysis, aided by principal component analysis, grouped the population into seven clusters with significant differences in their quantitative variables (p < 0.05). In conclusion, this research revealed diversity among common and durum wheat genotypes. Notably, 26 durum wheat and 17 common wheat accessions outperformed the control, offering the potential for developing early-maturing, high-yielding, and lodging-resistant wheat varieties.

• Journal of Radiation Protection and Research
• /
• v.39 no.3
• /
• pp.127-133
• /
• 2014

North Korea's uranium enrichment facility is a matter of international concern. It is of particular alarming to South Korea with regard to the security and safety of the country. This situation requires continuous monitoring of the DPRK and emergency preparedness on the part of the ROK. To assess the detectability of an undeclared uranium enrichment plant in North Korea, uranium concentrations in the air at both a short and a long distance from the enrichment facility were estimated. $UF_6$ source terms were determined by using existing information on North Korean facility and data from the operation experience of enrichment plants from other countries. Using the calculated source terms, two atmospheric dispersion models (Gaussian Plume Model and HYSPLIT models) and meteorological data were used to estimate the uranium particle concentrations from the Yongbyon enrichment facility. A maximum uranium concentration and its location are dependent upon the meteorological conditions and the height of the UF6 release point. This study showed that the maximum uranium concentration around the enrichment facility was about $1.0{\times}10^{-7}g{\cdot}m^{-3}$. The location of the maximum concentration was within about 0.4 km of the facility. It has been assumed that the uranium sample of about a few micrograms (${\mu}g$) could be obtained; and that few micrograms of uranium can be easily measured with current measurement instruments. On the contrary, a uranium concentration at a distance of more than 100 kilometers from the enrichment facility was estimated to be about $1.0{\times}10^{-13}{\sim}1.0{\times}10^{-15}g{\cdot}m^{-3}$, which is less than back-ground level. Therefore, based on the results of our paper, an air sample taken within the vicinity of the Yongbyon enrichment facility could be used to determine as to whether or not North Korea is carrying out an undeclared nuclear program. However, the air samples taken at a longer distance of a few hundred kilometers would prove difficult in detecting a clandestine nuclear activities.

• Journal of Intelligence and Information Systems
• /
• v.26 no.2
• /
• pp.131-145
• /
• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• The KIPS Transactions:PartD
• /
• v.9D no.2
• /
• pp.235-242
• /
• 2002

We propose an advanced transaction scheduling protocol for concurrency control of multilevel secure databases in wireless mobile network environment. Wireless communication is characterized by frequent spurious disconnections. So short-lived transaction must quickly access database without any delay by long-lived one. We adapted two-phase locking protocol, namely traditional syntax-oriented serializability notions, to multilevel secure databases in wireless mobile network environment. Altruistic locking, as an advanced protocol, has attempted to reduce delay effect associated with lock release moment by use of the idea of donation. An improved form of a1truism has also been deployed for extended a1truistic locking. This is in a way that scope of data to he early released is enlarged to include even data initially not intended to be donated. Our protocol is based on extended altruistic locking, but a new method, namely bi-directional donation locking for multilevel secure databases (MLBiDL), is additionally used in order to satisfy security requirements and concurrency. We showed the Simulation experiments that MLBiDL outperforms the other locking protocols in terms of the degree of throughput and average waiting time.

• Journal of Korean Academy of Dental Administration
• /
• v.7 no.1
• /
• pp.39-43
• /
• 2019

Smartphone usage has become so common that it has reached 2 billion people in the last year. As a result of this, hospitals have started making use of smartphones at various medical sites and research services for patients. This study aimed to establish support for developing a long distance program for patients with implants who have difficulty visiting clinics or with busy modern lives, by using smartphones for oral hygiene management instruction. The data were collected for 12 weeks, from July 24 to October 21, 2015, for patients who agreed to participate in the study. Although the subjects found the process of transferring photos via smartphone to be cumbersome (75%), the satisfaction level of the oral hygiene management program was excellent for all participating patients, and they all wanted to continue with further management using this process. The results from the phone satisfaction survey showed that oral hygiene self-management after oral hygiene control training by smartphones was mostly equal to previous habits (87.5%) or had partially increased but had not decreased. The need for data on more varied age groups and the issues of protecting the security of personal information on smartphones require further study. However, our study confirmed the efficacy of using electronic media (smartphones) for oral hygiene management in patients with a dental implant due to their improvement of oral hygiene performance as evidenced by less bleeding from probing on post-program visit.

• Korean Security Journal
• /
• no.50
• /
• pp.209-237
• /
• 2017

Theories on 'opportunity for crime' have utilized CCTV in crime prevention approach, and empirical studies showing crime prevention effects of CCTV have supported expansion of CCTV installation. Particularly, in Korea, the number of CCTV installation had tripled from 2011 to 2015, and governmental policies regarding CCTV have become one of the mainstream social control strategies. Although a couple of empirical studies showed decrease in crime rate due to CCTV installation, there is no study investigating B/C analysis(Benefit vs. cost analysis) of CCTV installation. B/C analysis results will be beneficial for official decision-making of criminal justice policy, and this study is purported to produce such fundamental evidence for policy making procedure. To fulfill this goal, this study collected data on financial information, crime data between 2011 and 2015 across the nation from 232 governmental district offices and the Korean National Police. This study then conducted two different B/C analyses(simple B/C analysis, regression-based B/C analysis). The simple B/C analysis results showed that 1) total costs for CCTV installation in 2014 was 68,626,000,000 won(approximately, US$57,188,333.00, money exchange rate 1200won=US$1), 2) benefits of crime reduction was 90,888,000,000 won(appx. US$75,740,000), and 3) B/C rate was 1.32. The regression-based B/C analysis results showed that 1) B/C rate was 1.52 when only reduced costs of criminal justice processes for crime employed, and 2) B/C rate was 3.62 when overall social costs including reduced costs of criminal justice processes and social benefits, e.g., reduction in costs for managing fear of crime, due to the crime reduction. Based on the results, this study provided policy implications.

• Journal of Intelligence and Information Systems
• /
• v.23 no.1
• /
• pp.143-159
• /
• 2017

Due to the rapid development of IT in recent years, not only personal information but also the key technologies and information leakage that companies have are becoming important issues. For the enterprise, the core technology that the company possesses is a very important part for the survival of the enterprise and for the continuous competitive advantage. Recently, there have been many cases of technical infringement. Technology leaks not only cause tremendous financial losses such as falling stock prices for companies, but they also have a negative impact on corporate reputation and delays in corporate development. In the case of SMEs, where core technology is an important part of the enterprise, compared to large corporations, the preparation for technological leakage can be seen as an indispensable factor in the existence of the enterprise. As the necessity and importance of Information Security Management (ISM) is emerging, it is necessary to check and prepare for the threat of technology infringement early in the enterprise. Nevertheless, previous studies have shown that the majority of policy alternatives are represented by about 90%. As a research method, literature analysis accounted for 76% and empirical and statistical analysis accounted for a relatively low rate of 16%. For this reason, it is necessary to study the management model and prediction model to prevent leakage of technology to meet the characteristics of SMEs. In this study, before analyzing the empirical analysis, we divided the technical characteristics from the technology value perspective and the organizational factor from the technology control point based on many previous researches related to the factors affecting the technology leakage. A total of 12 related variables were selected for the two factors, and the analysis was performed with these variables. In this study, we use three - year data of "Small and Medium Enterprise Technical Statistics Survey" conducted by the Small and Medium Business Administration. Analysis data includes 30 industries based on KSIC-based 2-digit classification, and the number of companies affected by technology leakage is 415 over 3 years. Through this data, we conducted a randomized sampling in the same industry based on the KSIC in the same year, and compared with the companies (n = 415) and the unaffected firms (n = 415) 1:1 Corresponding samples were prepared and analyzed. In this research, we will conduct an empirical analysis to search for factors influencing technology leakage, and propose an early warning system through data mining. Specifically, in this study, based on the questionnaire survey of SMEs conducted by the Small and Medium Business Administration (SME), we classified the factors that affect the technology leakage of SMEs into two factors(Technology Characteristics, Organization Characteristics). And we propose a model that informs the possibility of technical infringement by using Support Vector Machine(SVM) which is one of the various techniques of data mining based on the proven factors through statistical analysis. Unlike previous studies, this study focused on the cases of various industries in many years, and it can be pointed out that the artificial intelligence model was developed through this study. In addition, since the factors are derived empirically according to the actual leakage of SME technology leakage, it will be possible to suggest to policy makers which companies should be managed from the viewpoint of technology protection. Finally, it is expected that the early warning model on the possibility of technology leakage proposed in this study will provide an opportunity to prevent technology Leakage from the viewpoint of enterprise and government in advance.

• Journal of Preventive Medicine and Public Health
• /
• v.11 no.1
• /
• pp.123-127
• /
• 1978

The major objective of this research is to identify those hospital characteristics that best explain cost variation among hospitals and to formulate linear models that can predict hospital costs. Specific emphasis is placed on hospital output, that is, the identification of diagnosis related patient groups (DRGs) which are medically meaningful and demonstrate similar patterns of hospital resource consumption. A casemix index is developed based on the DRGs identified. Considering the common problems encountered in previous hospital cost research, the following study requirements are estab-lished for fulfilling the objectives of this research: 1. Selection of hospitals that exercise similar medical and fiscal practices. 2. Identification of an appropriate data collection mechanism in which demographic and medical characteristics of individual patients as well as accurate and comparable cost information can be derived. 3. Development of a patient classification system in which all the patients treated in hospitals are able to be split into mutually exclusive categories with consistent and stable patterns of resource consumption. 4. Development of a cost finding mechanism through which patient groups' costs can be made comparable across hospitals. A data set of Medicare patients prepared by the Social Security Administration was selected for the study analysis. The data set contained 27,229 record abstracts of Medicare patients discharged from all but one short-term general hospital in Connecticut during the period from January 1, 1971, to December 31, 1972. Each record abstract contained demographic and diagnostic information, as well as charges for specific medical services received. The 'AUT-OGRP System' was used to generate 198 DRGs in which the entire range of Medicare patients were split into mutually exclusive categories, each of which shows a consistent and stable pattern of resource consumption. The 'Departmental Method' was used to generate cost information for the groups of Medicare patients that would be comparable across hospitals. To fulfill the study objectives, an extensive analysis was conducted in the following areas: 1. Analysis of DRGs: in which the level of resource use of each DRG was determined, the length of stay or death rate of each DRG in relation to resource use was characterized, and underlying patterns of the relationships among DRG costs were explained. 2. Exploration of resource use profiles of hospitals; in which the magnitude of differences in the resource uses or death rates incurred in the treatment of Medicare patients among the study hospitals was explored. 3. Casemix analysis; in which four types of casemix-related indices were generated, and the significance of these indices in the explanation of hospital costs was examined. 4. Formulation of linear models to predict hospital costs of Medicare patients; in which nine independent variables (i. e., casemix index, hospital size, complexity of service, teaching activity, location, casemix-adjusted death. rate index, occupancy rate, and casemix-adjusted length of stay index) were used for determining factors in hospital costs. Results from the study analysis indicated that: 1. The system of 198 DRGs for Medicare patient classification was demonstrated not only as a strong tool for determining the pattern of hospital resource utilization of Medicare patients, but also for categorizing patients by their severity of illness. 2. The wei틴fed mean total case cost (TOTC) of the study hospitals for Medicare patients during the study years was $11,27.02 with a standard deviation of $117.20. The hospital with the highest average TOTC ($1538.15) was 2.08 times more expensive than the hospital with the lowest average TOTC ($743.45). The weighted mean per diem total cost (DTOC) of the study hospitals for Medicare patients during the sutdy years was $107.98 with a standard deviation of $15.18. The hospital with the highest average DTOC ($147.23) was 1.87 times more expensive than the hospital with the lowest average DTOC ($78.49). 3. The linear models for each of the six types of hospital costs were formulated using the casemix index and the eight other hospital variables as the determinants. These models explained variance to the extent of 68.7 percent of total case cost (TOTC), 63.5 percent of room and board cost (RMC), 66.2 percent of total ancillary service cost (TANC), 66.3 percent of per diem total cost (DTOC), 56.9 percent of per diem room and board cost (DRMC), and 65.5 percent of per diem ancillary service cost (DTANC). The casemix index alone explained approximately one half of interhospital cost variation: 59.1 percent for TOTC and 44.3 percent for DTOC. Thsee results demonstrate that the casemix index is the most importand determinant of interhospital cost variation Future research and policy implications in regard to the results of this study is envisioned in the following three areas: 1. Utilization of casemix related indices in the Medicare data systems. 2. Refinement of data for hospital cost evaluation. 3. Development of a system for reimbursement and cost control in hospitals.

• Journal of Korean Society of Disaster and Security
• /
• v.6 no.1
• /
• pp.65-72
• /
• 2013

In this study, the early suicide prevention program was applied to the elementary school students and compared the prior & post effect of the program, and verified the status of psychology change like emotional status, or temptation to take a suicide, and presented the possibility as a suicide prevention program. The period of adolescence is the very unstable period in the process of growth being cognitively immature, emotionally impulsive period. It is the period emotionally unstable and unpredictable possible to select the method of suicide as an extreme method to escape the reality, or impulsive problem solving against small conflict or dispute situation. Many stress of the student such as recent nuclear family, expectation of parents to their children, education problem, socio-environmental elements, individual psychological factor lead students to the extreme activity of suicide in recent days. In this study, the scope of stress experienced in the elementary school as well as idea and degree of temptation regarding suicide by the suicide prevention program were identified, and through prevention program such as meditation training, breath training and through experience of anger control, emotion-expression, self overcome and establish positive self-identity and make understanding Self-control, Self-esteem & preciousness of life based on which the effect to suicide prevention was analyzed. The study was made targeting 51 students of 2 classes of 6th grade of elementary school of Goyang-si and processed 30 minutes every morning focused on through experience & activity of the principle & method of brain science. The data was collected for 20 times before starting morning class by using Suicide Probability Scale(herein SPS-A) designed to predict effectively suicide Probability, suicide risk prediction scale, surveyed by 7 areas such as Positive outlook, Within the family closeness, Impulsivity, Interpersonal hostility, Hopelessness, Hopelessness syndrome, suicide accident. Analytical methods and validation was used the Wilcoxon's signed rank test using SPSS Program. Though the process of program in short period, but there was a effective and positive results in the 7 areas in the average comparison. But in the t-test result, there was a different outcome. It indicated changes in the 3 questionnaires (No.7, No.14, No.19) out of 31 SPS-A questionnaires, and there was a no change to the rest item. It also indicated more changes of the students in the class A than class B. And in case of the class A students, psychological changes were verified in the areas of Hopelessness syndrome, suicide accident among 7 areas after the program was processed. Through this study, it could be verified that different results could be derived depending on the Student tendency, program professional(teacher in charge, processing lecturer). The suicide prevention program presented in this article can be a help in learning and suicide prevention with consistent systematization, activation through emotion and impulse control based on emotional stress relief and positive self-identity recovery, stabilization of brain waves, and let the short period program not to be died out but to be continued connecting from childhood to adolescence capable to make surrounding environment for spiritual, physical healthy growth for which this could be an effective program for suicide prevention of the social problem.

• Journal of Digital Convergence
• /
• v.10 no.3
• /
• pp.233-240
• /
• 2012

This study aimed to clarify any factors that may have effect on the appropriateness of hospital admission and hospitalization with the intention of facilitating more efficient occupancy of hospital beds and better medical services in the aspect of their quality, minimizing unnecessary occupancy of beds, and ultimately helping patients requiring acute treatments to use immediately hospitals. This paper selected 154 Stroke patients who left neurology department of one general hospital from March, 1, 2006 to September, 31, 2010 as targets to meet the rate according to medical care security and to see the trend of recent 4 years. As study method, this paper analized medical treatment record with AEP to evaluate the appropriateness of hospital admission and stay and the collected data was computerized through SPSS 12.0. Based upon the results above, the conclusion was drawn that the higher appropriateness of hospital admission and the shorter length of hospital stay will lead to the higher appropriateness of hospitalization. In other words, it is required to provide hospitalized patients with all kinds of behaviors including medical treatments and nursing care service, management of pharmaceuticals, tests, rehabilitation and symptoms, as well as instructions and information for patients. Meanwhile, as it was found that the length of hospital stay may affect the appropriateness of hospitalization, the longer length of hospital stay may result in reduced bed turnover rate. In this light, it is necessary to organize a task force team responsible for evaluation and control of the appropriateness of hospitalization and hospital stay length to improve the quality of medical service in a medical center, so that patients can leave the center timely. Ultimately, governmental supports such as expansion of long-term care facilities will reduce the necessary length of hospital stay so that patients with stroke can receive rehabilitative treatments and long-term care service shortly after completion of acute treatments.