• Korean small business review
• /
• v.39 no.3
• /
• pp.57-76
• /
• 2017

While the unemployment rate is rising rapidly due to recent economic recession at home and abroad, university students' reluctance to apply for jobs in Small and Medium Enterprises (SME's) causes instability in manpower supply and demand and social unrest. To provide insights for solving the problem, this study explores how beliefs and attitudes of university students influence their intention to apply for jobs in SME's using Theory of Planned Behavior proposed by Icek Ajzen. This study followed the 2-stage survey methodology suggested by Ajzen. In the first stage of pilot study, a small sample of university students was used to illicit readily accessible behavioral outcomes, normative referents, and control factors. In the second stage of main study, the standard questionnaire was designed and administered and data were collected and analysed using the PLS Structural Equation Modeling (SEM) technique. PLS-SEM was used instead of Covariance Based (CB)- SEM considering the exploratory nature of this study. In overall, the results showed that TPB is very effective in explaining and predicting the university student's intention to apply for jobs in SEM's. Gender turned out to be a significant moderator variable in the relations between intention and its influence factors. Student's scholastic performance showed a negative correlation with intention. More research efforts need to be exerted to better understand university student's job seeking behavior.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.18 no.4
• /
• pp.77-88
• /
• 2023

The purpose of this study is to confirm whether the current technology appraisal model for investment, which is designed to identify high-growth SMEs in sales, which is one of the characteristics of gazelle companies, has the possibility of expanding employment effects. For SMEs classified as technology investment adequate firms(TI1-TI6) through technology appraisal for investment between 2016 and 2018 were targeted. At this time, the employment effect was analyzed by dividing the absolute employment effect and the relative employment effect. As a result of the analysis, it was confirmed that the technology appraisal items for investment defined as innovation characteristics did not have significant explanatory power for the absolute employment effect. However, for the relative employment effect, among innovation characteristics, technicality(TC) was found to have significant explanatory power, and this is because the item appraised based on future growth potential. In particular, the relative employment effect is meaningful in terms of the actual employment effect, and the conclusion is drawn that the current technology appraisal model for investment is an appraisal model with the possibility of expansion in terms of employment effect.

• The Journal of the Acoustical Society of Korea
• /
• v.27 no.5
• /
• pp.221-228
• /
• 2008

To estimate array shape with reference sources in SONAR systems, nearfield signal modeling is required for the reference sources near a towed array. Array shape estimation method based on the nearfield signal modeling generally exploits the spatial covariance matrix of the received reference sources. Among those method, nearfield eigenvector method uses the eigenvector corresponding to the maximum eigenvalue as a steering vector of the reference source. In this paper, we propose a simplified subspace fitting method based on the nearfield signal modeling with spherical wave modeling. Furthermore, we analyze performance of the array shape estimation methods based on the nearfield signal modeling for various environments. The results of the numerical experiments indicate that the simplified subspace fitting method and the nearfield eigenvector method with single reference source shows almost similar performance. Furthermore, the simplified subspace fitting method with 2 reference sources consistently estimates the shape of the array regardless of the incident angle of the reference sources, whereas the nearfield eigenvector method cannot apply for the case of 2 reference sources.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.19 no.1
• /
• pp.31-38
• /
• 2024

The digital phase-locked loop(DPLL) is one of the circuits composed of a digital detector, digital loop filter, voltage-controlled oscillator, and divider as a fundamental circuit, widely used in many fields such as electrical and circuit fields. A state estimator using various mathematical algorithms is used to improve the performance of a digital phase-locked loop. Traditional state estimators have utilized Kalman filters of infinite impulse response state estimators, and digital phase-locked loops based on infinite impulse response state estimators can cause rapid performance degradation in unexpected situations such as inaccuracies in initial values, model errors, and various disturbances. In this paper, we propose a two-layer Frobenius norm-based finite impulse state estimator to design a new digital phase-locked loop. The proposed state estimator uses the estimated state of the first layer to estimate the state of the first layer with the accumulated measurement value. To verify the robust performance of the new finite impulse response state estimator-based digital phase locked-loop, simulations were performed by comparing it with the infinite impulse response state estimator in situations where noise covariance information was inaccurate.

• Nuclear Engineering and Technology
• /
• v.55 no.12
• /
• pp.4447-4464
• /
• 2023

This paper focuses on the development of a new computational model of the CNESTEN's TRIGA Mark II research reactor using the 3D continuous energy Monte-Carlo code TRIPOLI-4 (T4). This new model was developed to assess neutronic simulations and determine quantities of interest such as kinetic parameters of the reactor, control rods worth, power peaking factors and neutron flux distributions. This model is also a key tool used to accurately design new experiments in the TRIGA reactor, to analyze these experiments and to carry out sensitivity and uncertainty studies. The geometry and materials data, as part of the MCNP reference model, were used to build the T4 model. In this regard, the differences between the two models are mainly due to mathematical approaches of both codes. Indeed, the study presented in this article is divided into two parts: the first part deals with the development and the validation of the T4 model. The results obtained with the T4 model were compared to the existing MCNP reference model and to the experimental results from the Final Safety Analysis Report (FSAR). Different core configurations were investigated via simulations to test the computational model reliability in predicting the physical parameters of the reactor. As a fairly good agreement among the results was deduced, it seems reasonable to assume that the T4 model can accurately reproduce the MCNP calculated values. The second part of this study is devoted to the sensitivity and uncertainty (S/U) studies that were carried out to quantify the nuclear data uncertainty in the multiplication factor k_eff. For that purpose, the T4 model was used to calculate the sensitivity profiles of the k_eff to the nuclear data. The integrated-sensitivities were compared to the results obtained from the previous works that were carried out with MCNP and SCALE-6.2 simulation tools and differences of less than 5% were obtained for most of these quantities except for the C-graphite sensitivities. Moreover, the nuclear data uncertainties in the k_eff were derived using the COMAC-V2.1 covariance matrices library and the calculated sensitivities. The results have shown that the total nuclear data uncertainty in the k_eff is around 585 pcm using the COMAC-V2.1. This study also demonstrates that the contribution of zirconium isotopes to the nuclear data uncertainty in the k_eff is not negligible and should be taken into account when performing S/U analysis.

• Journal of Radiation Industry
• /
• v.17 no.1
• /
• pp.19-32
• /
• 2023

The amount of radioactive waste is expected to dramatically increase with decommissioning of nuclear power plants such as Kori-1, the first nuclear power plant in South Korea. Accurate nuclide analysis is necessary to manage the radioactive wastes safely, but research on verification of radionuclide analysis has yet to be well established. This study aimed to develop the technology that can verify the results of radionuclide analysis based on artificial intelligence. In this study, we propose an anomaly detection algorithm for inspecting the analysis error of radionuclide. We used the data from 'Updated Scaling Factors in Low-Level Radwaste' (NP-5077) published by EPRI (Electric Power Research Institute), and resampling was performed using SMOTE (Synthetic Minority Oversampling Technique) algorithm to augment data. 149,676 augmented data with SMOTE algorithm was used to train the artificial neural networks (classification and anomaly detection networks). 324 NP-5077 report data verified the performance of networks. The anomaly detection algorithm of radionuclide analysis was divided into two modules that detect a case where radioactive waste was incorrectly classified or discriminate an abnormal data such as loss of data or incorrectly written data. The classification network was constructed using the fully connected layer, and the anomaly detection network was composed of the encoder and decoder. The latter was operated by loading the latent vector from the end layer of the classification network. This study conducted exploratory data analysis (i.e., statistics, histogram, correlation, covariance, PCA, k-mean clustering, DBSCAN). As a result of analyzing the data, it is complicated to distinguish the type of radioactive waste because data distribution overlapped each other. In spite of these complexities, our algorithm based on deep learning can distinguish abnormal data from normal data. Radionuclide analysis was verified using our anomaly detection algorithm, and meaningful results were obtained.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.4
• /
• pp.357-365
• /
• 2024

The purpose of this study is to investigate the effects of children's robot-based play on sequential thinking through appreciation of picture books. For this purpose, 15 children aged 5 years old in each kindergarten located in Seoul were selected and J kindergarten (experimental group) supported <Picture book appreciation robot play> and C kindergarten (comparison group) supported <Picture book appreciation free play>. In order to examine the difference in play experience between the two groups, the score data before and after play support was collected using the sequential thinking test tool, and the collected data were analyzed using SPSS 28.0 program to perform ANCOVA (Covariance Analysis). As a result, the experimental group that experienced robot-based play through picture book appreciation showed significant improvement in the total score of sequential thinking and the sub-areas of dynamics, behavior, and intention compared to the control group.The results of this study are valuable as a play study to discover the value of robots as a creative play medium led by young children and to promote sequential thinking ability, which is emphasized as the capacity of future society.

• Journal of The Korean Association For Science Education
• /
• v.36 no.1
• /
• pp.177-190
• /
• 2016

The purpose of this study is to validate learning progressions for Earth's motion and solar system from two different perspectives of validity. One is construct validity, that is whether a hypothetical pathway derived from our study of LPs is supported by empirical evidence of children's substantive development. The other is consequential validity, which refers to the impact of LP-based adaptive instruction on children's improved learning outcomes. For this purpose, 373 fifth-grade students and 17 teachers from six elementary schools in Seoul, Kangwon province, and Gwangju participated. We designed LP-based adaptive instruction modules delving into the unit of 'Solar system and stars.' We also employed 13 ordered multiple-choice items and analyzed the transitions of children's achievement levels based on the results of pre-test and post-test. For testing construct validity, 64 % of children in the experimental group showed improvement according to the hypothetical pathways. Rasch analysis also supports this results. For testing consequential validity, the analysis of covariance between experimental and control groups revealed that the improvement of experimental group is significantly higher than the control group (F=30.819, p=0.000), and positive transitions of children's achievement level in the experimental group are more dominant than in the control group. In addition, the findings of applying Rasch model reveal that the improvement of students' ability in the experimental group is significantly higher than that of the control group (F=11.632, p=0.001).

• Journal of the Korean Society of School Health
• /
• v.11 no.2
• /
• pp.171-187
• /
• 1998

In recent years, adolescent issues including smoking, drinking, drug abuse, juvenile delinquency, deviant sexual behavior, mental health problems, high suicide rate, juvenile delinquency and absence without due notice, etc are emerging as serious social problems and the debate on these controversial issues is heating up. The previous studies on adolescent health behavior and social juvenile delinquency such as run-away from home and absence without due notice have been conducted mostly by cause analysis utilizing social demographic factors or biological factors. In other words, the main factors analyzed were demographic and economic factors or parent's educational level, etc, which were the fixed environmental ones that were unable to cause the change in the health behavior. Accordingly, the purpose of this study is to analyze factors which are changeable and fixable among the factors influencing the adolescent's health behavior and misconducts and, eventually influencing factors which can be used as the basis to establish health policies and health promotion program to reduce the health risk behavior and misconducts of adolescents. The study subjects were selected by dividing senior high school student in Seoul by region and through random sampling. The 890 subjects were selected from 10 schools including the preparatory school, vocational schools and institutional schools. The duration of the study was for July 1-5, 1997 for the first survey and the second one, for August 25-September 10. Regarding the analysis method, the SAS program was used. The adoptablity of theoretical model was tested through covariance structural analysis utilizing PC-LISREL 8.12 Program. The major findings of the study are as follows: As a result of establishing the model of factors influencing health behavior and juvenile delinquency, in case of male students as the health behavior self-efficacy, education level of fathers, economic level, self-control and the health interest of parent were higher, students were more likely to practice the health promoting behavior. Juvenile delinquency and health risk behavior were prevalent among those with the less shyness, the lower health behavior self-efficacy, lower self-control, lower self-assertiveness, lower economic level. The self-control was the most powerful factor. In case of female students, those with higher health behavior self-efficacy were more likely to practice the health promoting behavior whereas those with lower health behavior self-efficacy, lower self-control, lower self- assertiveness, less shyness were more likely to practice health risk behavior and juvenile delinquency. In case of prep schools, those with higher health behavior self-efficacy and better perceived health status were more likely to practice the health promoting behavior while those with less shyness, lower health behavior self-efficacy and lower academic achievement were more likely to engage in health risk behavior and juvenile delinquency. In case of vocational schools, as health behavior self-efficacy and economic level were higher, the practice rate of health promoting behavior was higher. As the self-control, shyness, self-assertiveness, health behavior self-efficacy were lower, the rate of health risk behavior and juvenile delinquency were higher. In case of social institutional schools, as, the health behavior self-efficacy, social support and economic level, health interest of parents were higher, the rate of health promoting behavior were higher. As the self-control, shyness, self-assertiveness, health behavior self-efficacy and social support were lower, the rate of health risk behavior and juvenile delinquency were higher. So the health promoting behavior was positively related to the health behavior self-efficacy, health interest of parents, social support, education level of fathers, level of perceived health status, economic level. The health risk behavior and juvenile delinquency were higher with the lower health behavior self-efficacy, self-control and self-assertiveness, lower health locus control, less shyness and loneliness, lower economic level and academic achievement. In conclusion, the health risk behavior and juvenile delinquency can be reduced by enhancing self-control, self-assertiveness, health behavior self-efficacy and social support. According to the final model drawn by connecting health behavior and juvenile delinquency, the reduction of health risk behavior can greatly contribute to decreasing social juvenile delinquency as the process of juvenile delinquency was extended from common behaviors to problem behaviors and further into juvenile delinquency.

• Journal of dental hygiene science
• /
• v.12 no.1
• /
• pp.7-13
• /
• 2012

Critical thinking is a essential competency for dental hygiene education and practice. The purpose of this study was to examine critical thinking disposition between groups classified by GPA score in two dental hygiene educational program. A total 252 dental hygiene students responded. The study extracted six dimensions(intellectual eagerness/curiosity, prudence, healthy skepticism, intellectual integrity, objectivity, self-confidence) derived from 27 items with the exception of systematicity using factor analysis. The mean score for critical thinking disposition was 3.47 on a 5 point scale. The result showed a statistically significant correlation critical thinking disposition and age. Multivariate analysis of covariance(MANCOVA) was used to compare six subscales between the three groups. MANCOVA results revealed that intellectual eagerness/curiosity for three groups were significantly different(Wilks's lamda=0.914, F(6, 24)=1.869), p=0.01, partial eta square=0.044). Multiple comparison for intellectual eagerness/curiosity by Scheffe's method showed differences between high score group and mid score group(p=0.027), high score group and low score group(p=0.002). In this study, academic achievement and critical thinking tends to show significant correlations is known. Critical thinking skills by examining the actual grade compares the difference in propensity scores according to a case study in intellectual curiosity, passion, and could tell the difference to appear.