• Journal of the Korean Chemical Society
• /
• v.58 no.1
• /
• pp.126-129
• /
• 2014

Concerning the difficulty of learning science and reduced interest in science, the authors of this study searched for potential threshold concepts which are portals or gateways in the field of science (particularly chemistry). The nature of these concepts and how to overcome their troublesomeness were further questioned. For this study, 239 high school students completed chemistry II provided information about what difficult concepts and potential threshold concepts in high school chemistry are and how they affect learning chemistry. In particular, the mastery experience of the threshold concepts was explored in detail. Two, "mole and atomic structure" were selected as threshold concepts in chemistry. Not only as important but also as threshold, this study emphasized the importance of the two concepts in terms of features characterizing them as threshold concepts. In particular, the features objectify subjective experiences of students and provide information describing the scientific meaning and distinctive nature of threshold concepts in science. Along with the data from teachers, this study shows the integrative feature as key criteria for students to make meaningful understanding of the two threshold concepts.

• KIPS Transactions on Computer and Communication Systems
• /
• v.2 no.8
• /
• pp.349-356
• /
• 2013

As various features of the smartphone have been used, a lot of information have been stored in the smartphone, including the user's personal information. However, a frequent update of the operating system and applications may cause a loss of data and a risk of missing important personal data. Thus, the importance of data backup is significantly increasing. Many users employ the backup feature to store their data securely. However, in the point of forensic view these backup files are considered as important objects for investigation when issued hiding of smartphone or intentional deletion on data of smartphone. Therefore, in this paper we propose a scheme that analyze structure and restore data for Kies backup files of Samsung smartphone which has the highest share of the smartphone in the world. As the experimental results, the suggested scheme shows that the various types of files are analyzed and extracted from those backup files compared to other tools.

• The Journal of Bigdata
• /
• v.6 no.1
• /
• pp.133-144
• /
• 2021

This paper derives the fire risk of buildings in Seoul through the prediction of property damage and the occurrence of fires. This study differs from prior research in that it utilizes variables that include not only a building's characteristics but also its affiliated administrative area as well as the accessibility of nearby fire-fighting facilities. We use Ensemble Voting techniques to merge different machine learning algorithms to predict property damage and fire occurrence, and to extract feature importance to produce fire risk. Fire risk prediction was made on 300 buildings in Seoul utilizing the established model, and it has been derived that with buildings at Level 1 for fire risks, there were a high number of households occupying the building, and the buildings had many factors that could contribute to increasing the size of the fire, including the lack of nearby fire-fighting facilities as well as the far location of the 119 Safety Center. On the other hand, in the case of Level 5 buildings, the number of buildings and businesses is large, but the 119 Safety Center in charge are located closest to the building, which can properly respond to fire.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.1
• /
• pp.127-137
• /
• 2019

The growth in smartphone service has given rise to an increase in frequency and importance of authentication. Existing smartphone authentication mechanisms such as passwords, pattern lock and fingerprint recognition require a high level of awareness and authenticate users temporarily with a point-of-entry techniques. To overcome these disadvantages, there have been active researches in behavior-based authentication. However, previous studies focused on enhancing the accuracy of the authentication. Since authentication is directly used by people, it is necessary to reflect actual users' perception. This paper proposes user perception on behavior-based authentication with feature analysis. We conduct user survey to empirically understand user perception regarding behavioral authentication with selected authentication features. Then, we analyze acceptance of the behavioral authentication to provide continuous authentication with minimal awareness while using the device.

• The Journal of the Convergence on Culture Technology
• /
• v.5 no.1
• /
• pp.319-325
• /
• 2019

The importance of social responsibility is growing, and as a result of social awareness, many universities and institutions are carrying out community service activities. Although the volunteer portal site has excellent performance and good accessibility, the overall service performance of a specific organization cannot be managed because of personal information. Almost community service managers of a organization manually manage their community service activities without the support of a community service management program. In this study, have been feature analysis of existing portal site for volunteer coordination, then a prototype was designed and developed as a model of social contribution management system so that universities and organizations can systematically support and manage the social service activities of members based on the questionnaire about social contribution management system.

• Proceedings of the National Institute of Ecology of the Republic of Korea
• /
• v.2 no.1
• /
• pp.1-14
• /
• 2021

The study has been carried out with an objective to prepare Siberian roe deer habitat potential maps in South Korea based on three geographic information system-based models including frequency ratio (FR) as a bivariate statistical approach as well as convolutional neural network (CNN) and long short-term memory (LSTM) as machine learning algorithms. According to field observations, 741 locations were reported as roe deer's habitat preferences. The dataset were divided with a proportion of 70:30 for constructing models and validation purposes. Through FR model, a total of 10 influential factors were opted for the modelling process, namely altitude, valley depth, slope height, topographic position index (TPI), topographic wetness index (TWI), normalized difference water index, drainage density, road density, radar intensity, and morphological feature. The results of variable importance analysis determined that TPI, TWI, altitude and valley depth have higher impact on predicting. Furthermore, the area under the receiver operating characteristic (ROC) curve was applied to assess the prediction accuracies of three models. The results showed that all the models almost have similar performances, but LSTM model had relatively higher prediction ability in comparison to FR and CNN models with the accuracy of 76% and 73% during the training and validation process. The obtained map of LSTM model was categorized into five classes of potentiality including very low, low, moderate, high and very high with proportions of 19.70%, 19.81%, 19.31%, 19.86%, and 21.31%, respectively. The resultant potential maps may be valuable to monitor and preserve the Siberian roe deer habitats.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.44 no.4
• /
• pp.12-22
• /
• 2021

This article suggests the machine learning model, i.e., classifier, for predicting the production quality of free-machining 303-series stainless steel(STS303) small rolling wire rods according to the operating condition of the manufacturing process. For the development of the classifier, manufacturing data for 37 operating variables were collected from the manufacturing execution system(MES) of Company S, and the 12 types of derived variables were generated based on literature review and interviews with field experts. This research was performed with data preprocessing, exploratory data analysis, feature selection, machine learning modeling, and the evaluation of alternative models. In the preprocessing stage, missing values and outliers are removed, and oversampling using SMOTE(Synthetic oversampling technique) to resolve data imbalance. Features are selected by variable importance of LASSO(Least absolute shrinkage and selection operator) regression, extreme gradient boosting(XGBoost), and random forest models. Finally, logistic regression, support vector machine(SVM), random forest, and XGBoost are developed as a classifier to predict the adequate or defective products with new operating conditions. The optimal hyper-parameters for each model are investigated by the grid search and random search methods based on k-fold cross-validation. As a result of the experiment, XGBoost showed relatively high predictive performance compared to other models with an accuracy of 0.9929, specificity of 0.9372, F₁-score of 0.9963, and logarithmic loss of 0.0209. The classifier developed in this study is expected to improve productivity by enabling effective management of the manufacturing process for the STS303 small rolling wire rods.

• Journal of Korea Society of Industrial Information Systems
• /
• v.27 no.5
• /
• pp.73-82
• /
• 2022

Chronic diseases such as hypertension require a differentiated approach according to age and life cycle. Chronic diseases such as hypertension require differentiated management according to the life cycle. It is also known that the cause of hypertension is a combination of various factors. This study uses machine learning prediction techniques to analyze various factors affecting hypertension by life cycle. To this end, a total of 35 variables were used through preprocessing and variable selection processes for the National Health and Nutrition Survey data of the Korea Centers for Disease Control and Prevention. As a result of the study, among the tree-based machine learning models, XGBoost was found to have high predictive performance in both middle and old age. Looking at the risk factors for hypertension by life cycle, individual characteristic factors, genetic factors, and nutritional intake factors were found to be risk factors for hypertension in the middle age, and nutritional intake factors, dietary factors, and lifestyle factors were derived as risk factors for hypertension. The results of this study are expected to be used as basic data useful for hypertension management by life cycle.

• The Korean Nurse
• /
• v.37 no.2
• /
• pp.44-52
• /
• 1998

The purpose of this study is to inquire the people's views on nursing for nurses, correct the image of nurse and take it as basis to be applied on nursing education examining the image of nursing on Television drama playing important role of mass media. 22 nurses of the characters in drama is applied to the analysis object of this study by selecting 6 dramas of Television ones the nurse play on the prime time from June 1 to August 31 in 1997. Contents analysis method was used in Data Analysis, 4 items was used after Coders previously modify and compensate it based on research documents of 1m Milim(1996) 2 Coders made the Coding the article on each person by them seeing the recorded film making the Coding Paper each items is written by the character. The average of reliability degree was 90% which measured the reliability degree by the mathod of Holsti. The statisic method of frequency, percentage was used SPSS Program in data processing The results were as follows. 1. Relative importance of 86.2% nurses in drama was depicted as extra characters 2. The affair attitude of nurses shown on drama was revealed as mechanical(84.7%), passive(45.5%), dependent(54.4%) unkind(68.2%). 3. The activity of nurses was classified with professional! simple affair. The professional affairs such as I.V., Blood Pressure Check, Rounding, Nursing Recording, Patient Education, Assist of Operation, Assistant meal of Patient, etc is mainly depicted and the screen of simple affair such as Receiving telephone, Carrying Tray or Dragging, Stretcher Car, Dressing Car and or Wheel Chair than professional affair. 4. The appearance feature of nurses was shown on thin physique(68.2%), common stature(68.2), dirty costume(45.4%), common appearance(81.9%), unnoble action(63.6%). The image of nurses is illuminated as the exterial scene of technical affair such as assisting the doctors and affair focused on accident and educational activity of nureses or extended role is nor depicted on Television drama. Therefore, the people regard the nurse as sexual object with good appearance than professional worker working professional nursing We want the following, epigraph based on above conclusion. 1. The continuous research is required on the image of nurse shown on various mass media. 2. The later research is required on appliction strategy of mass media for advancing the image of nurse. 3. The research to strengthen the objectivity by comparing analyzed data on drama & analyzing it is required 4. Through the deep study, the standard to show a concrete and professional work of nurses to scenario writers of TV drama is suggested by the association. 5. The monitoring about the mass media must be activated, not by some nurses, on a national scale and much study on the basis of this is needed.

• Nuclear Engineering and Technology
• /
• v.55 no.12
• /
• pp.4357-4366
• /
• 2023

MARS-KS, a domestic regulatory confirmatory code of Republic of Korea, had been developed by integrating RELAP5/MOD2 and COBRA-TF. The integration of COBRA-TF allowed to extend the capability of MARS-KS, limited to one-dimensional analysis, to multi-dimensional analysis. The use of COBRA-TF was mainly focused on subchannel analyses for simulating multi-dimensional behavior within the reactor core. However, this feature has been remained as a legacy without ongoing maintenance. Meanwhile, MARS-KS also includes its own multidimensional component, namely MULTID, which is also feasible to simulate three-dimensional convection and diffusion. The MULTID is capable of modeling the turbulent diffusion using simple mixing length model. The implementation of the turbulent mixing is of importance for analyzing the reactor core where a disturbing cross-sectional structure of rod bundle makes the flow perturbation and corresponding mixing stronger. In addition, the presence of this turbulent behavior allows the secondary transports with net mass exchange between subchannels. However, a series of assessments performed in previous studies revealed that the turbulence model of the MULTID could not simulate the aforementioned effective mixing occurred in the subchannel-scale problems. This is obvious consequence since the physical models of the MULTID neglect the effect of mass transport and thereby, it cannot model the void drift effect and resulting phasic distribution within a bundle. Thus, in this study, the turbulence mixing model of the MULTID has been improved by means of the inter-channel mixing model, widely utilized in subchannel analysis, in order to extend the application of the MULTID to small-scale problems. A series of assessments has been performed against rod bundle experiments, namely GE 3X3 and PSBT, to evaluate the performance of the introduced mixing model. The assessment results revealed that the application of the inter-channel mixing model allowed to enhance the prediction of the MULTID in subchannel scale problems. In addition, it was indicated that the code could not predict appropriate phasic distribution in the rod bundle without the model. Considering that the proper prediction of the phasic distribution is important when considering pin-based and/or assembly-based expressions of the reactor core, the results of this study clearly indicate that the inter-channel mixing model is required for analyzing the rod bundle, appropriately.