• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.6
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• pp.546-552
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• 2016

We present a quantitative evaluation of an algorithm for model-based face recognition. The algorithm actively learns how individual faces vary through video sequences, providing on-line suppression of confounding factors such as expression, lighting and pose. By actively decoupling sources of image variation, the algorithm provides a framework in which identity evidence can be integrated over a sequence. We demonstrate that face recognition can be considerably improved by the analysis of video sequences. The method presented is widely applicable in many multi-class interpretation problems.

• Science of Emotion and Sensibility
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• v.25 no.1
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• pp.21-28
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• 2022

People differ greatly in their capacity to persist in the face of challenges. Despite significant research, relatively little is known about cognitive factors that might be involved in perseverance. Building upon human threat-management mechanism, we predicted that perseverant people would be characterized by reduced sensitivity (i.e., longer detection latency) to threat cues. Our data from 5,898 job applicants showed that highly perseverant individuals required more time to correctly identify anger in faces, regardless of stimulus type (dynamic or static computer-morphed faces). Such individual differences were not observed in response to other facial expressions (happiness, sadness), and the effect was independent of gender, dispositional anxiety, or conscientiousness. Discussions were centered on the potential role of threat sensitivity in effortful pursuit of goals.

• Communications for Statistical Applications and Methods
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• v.23 no.2
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• pp.179-187
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• 2016

The fixed effects panel probit model faces "incidental parameters problem" because it has a property that the number of parameters to be estimated will increase with sample size. The maximum likelihood estimation fails to give a consistent estimator of slope parameter. Unlike the panel regression model, it is not feasible to find an orthogonal reparameterization of fixed effects to get a consistent estimator. In this note, a hierarchical Bayesian model is proposed. The model is essentially equivalent to the frequentist's random effects model, but the individual specific effects are estimable with the help of Gibbs sampling. The Bayesian estimator is shown to reduce reduced the small sample bias. The maximum likelihood estimator in the random effects model is also efficient, which contradicts Green (2004)'s conclusion.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.493-494
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• 2022

The development of livestock faces intensive farming results in a rising need for recognition of individual animals such as cows and pigs is related to high traceability. In this paper, we present a non-invasive biometrics systematic approach based on the deep-learning classification model to pig face identification. Firstly, in our systematic method, we build a ROS data collection system block to collect 10 pig face data images. Secondly, we proposed a preprocessing block in that we utilize the SSIM method to filter some images of collected images that have high similarity. Thirdly, we employ the improved image classification model of CNN (ViT), which uses the finetuning and pretraining technique to recognize the individual pig face. Finally, our proposed method achieves the accuracy about 98.66%.

• Knowledge Management Research
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• v.18 no.3
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• pp.163-178
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• 2017

Recent advances in technology are evolving to enable individuals to perform various activities necessary for their lives, without being constrained by physical, temporal, and spatial constraints. The online services and experiences that originated from solving the discomfort in the actual offline space have created the newness that can only be experienced in the digital world and furthermore uniquely new experiences in actual space as well. While many previous studies have suggested several interpretations of unique individual behaviors in virtual environments, a recent research approaches virtuality as an interesting perspective of the change of thinking style. Virtuality is defined as how far apart we are from everyday reality, and if the individual faces a situation far from reality, the psychological distance of the individual becomes distant and ultimately leads to the thinking style of high construal level. Otherwise, it is said to have a relatively low construal level of thinking style. In this study, I try to confirm the virtual distance as the role of psychological distance in new virtual contexts. Simultaneously considering temporal distance, which are most used in psychological distance, and virtual distance based on virtuality, this study tries to find whether the effect of virtual distance on product attitude is the same as that of temporal distance and check the relationship between virtual distance and temporal distance in the context of consumers' product evaluations depending on product information type.

• Journal of Biosystems Engineering
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• v.29 no.4
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• pp.341-346
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• 2004

Recent livestock people concern not only increase of production, but also superior quality of animal-breeding environment. So far, the optimization of the breeding and air environment has been focused on the production increase. In the very near future, the optimization will be emphasized on the environment for the animal welfare and health. Especially, cattle farming demands the precision livestock farming and special attention has to be given to the management of feeding, animal health and fertility. The management of individual animal is the first step for precision livestock farming and animal welfare, and recognizing each individual is important for that. Though electronic identification of a cattle such as RFID(Radio Frequency Identification) has many advantages, RFID implementations practically involve several problems such as the reading speed and distance. In that sense, computer vision might be more effective than RFID for the identification of an individual animal. The researches on the identification of cattle via image processing were mostly performed with the cows having black-white patterns of the Holstein. But, the native Korean and Japanese cattle do not have any definite pattern on the body. The purpose of this research is to identify the Japanese black cattle that does not have a body pattern using computer vision technology and neural network algorithm. Twelve heads of Japanese black cattle have been tested to verify the proposed scheme. The values of input parameters were specified and then computed using the face images of cattle. The images of cattle faces were trained using associate neural network algorithm, and the algorithm was verified by the face images that were transformed using brightness, distortion, and noise factors. As a result, there was difference due to transform ratio of the brightness, distortion, and noise. And, the proposed algorithm could identify 100% in the range from -3 to +3 degrees of the brightness, from -2 to +4 degrees of the distortion, and from 0% to 60% of the noise transformed images. It is concluded that our system can not be applied in real time recognition of the moving cows, but can be used for the cattle being at a standstill.

• Journal of Korean Academy of Nursing
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• v.29 no.2
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• pp.418-428
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• 1999

The main purpose of this study was to identify the effects of group social support and individual social support on the reduction of burden and improvement in family functioning of families with asthmatic children. The design of this study was a randomized pre-posttest quasi-experimental design to compare the two experimental groups. The theoretical framework for this study was derived from the study of burden in family caregivers by Suh and Oh (1993) based on the main effect model of social support theories. The data were collected from February 12, 1998 to May 29, 1998 at the pediatric out patient department of a university hospital located in Suwon city. The sample consisted of 39 family members who were identified as families with asthmatic children, Eighteen subjects were randomly assigned to the group social support group and 21 were assigned to the individual social support group. Group and individual social support members were seen for 60 to 90 minutes, four times over one to three weeks. The instruments used in this study were the Burden Scale developed by Suh & Oh(1993), the Visual Analogue Scale, and the Family Adaptability Cohesion Evaluation Scale(FACES-III) developed by Olson, Portner, and Lavee(1985). The collected data were analyzed using Mann-Whitney test, x$^2$-test, Wilcoxon sign rank test, t-test, ANOVA (Scheff), Pearson correlation coefficient. multiple regression, and social support process and content analysis. The results are as follow : 1. There was no significant difference before the experimental treatment among the subjects in the group social support group and individual social support group for general characteristics, burden, or family functioning. 2. Hypothesis 1 : “There will be a greater reduction on the burden score of the group social support group compared to the individual social support group” was not statistically significant(U＝174.5, p＝.683). The burden scores showed a significant decrease after participation in social support as compared to before participation for both groups. However there was a tendency for more reduction in the burden scores for the group social support than for individual social support. 3. Hypothesis 2 : “There will be a greater improvement in the family functioning scores for the group social support group compared to the individual social support group” was not statistically significant(U＝153.0. p＝.309). There was a tendency toward improvement in the family functioning scores of the group social support as compared to that of the individual social support. 4. According to the length of the treatment period, families with asthmatic children displayed affirmative responses, and the families set up a self-help group of mothers with asthmatic children in order to share their experiences, to get information and to solve their problems. In conclusion, it was found that group social support was the more effective nursing intervention for reducing burden and for improving family functioning of families with asthmatic children.

• Journal of the Korean School Mathematics Society
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• v.2 no.1
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• pp.15-30
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• 1999

For the purpose of turning learners' locus of control into internal-controllable variables, counseling materials were developed, and attribution counseling was given. The counseling effects were practically confirmed by way of teaching and evaluation in the actual classes, and furthermore the efforts to provide learners with successful experiences in learning were repeatedly made. As a result, the conclusions are as follows: 1. The procedure of Individual counseling for learning attribution based on individual standard grades and data of the variable order of merit apparently shows learners that if learners are to try their best in learning, they will surely go far in terms of learning in the near future. 2. The procedure of Individual counseling for teaming attribution based on achievement distribution in individual behavior-oriented fields suggests to learners that how to learn is as important as how much effort they make. Surely enough, learners are required to make more effective and efficient efforts, considering their own learning abilities. 3. With the above 1, 2 procedures involved, learners have attributed locus of causality in achievement to their internal-controllable causes. 4. With preparatory assignments according to learner's abilities provided, even slower learners came to be assured that their constant efforts could give rise to success in learning achievement. 5. Above all, it was confirmed that the learners' struggling attitude might well have a significant correlation with achievement success. The learners who are willing to attribute locus of causality in achievement to their internal-controllable causes or strenuous efforts and intrinsic motivation tend to be convinced that they can address themselves to whatever faces them, so they can set up specific learning goals fit for their abilities. Accordingly, they will bit by bit acquire successful experiences (often called 'Aha' experiences) and in turn, feeling the senses of self-efficacy and self-esteem enough to push their efforts even further, they can grow to form a positive self-concept. With one successful experience after another fed back into learners, they are gradually motivated to bring the oncoming achievement expectation to a higher level. To conclude, it is necessary that instruction leading to internal-controllable attribution should be provided, inducing learners to recognize success and failure in learning achievement as a result of their strenuous efforts.

• International Journal of Advanced Culture Technology
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• v.8 no.2
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• pp.139-145
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• 2020

Individual personality traits are key factors that affect users' self-disclosure on SNS. We examined the relationship between an individual personality trait (i.e., narcissism) and three dimensions of self-disclosure behavior on Facebook (i.e., intention, level, and control of self-disclosure). A total of 261 Facebook users completed an online survey. The findings showed that more narcissistic individuals engage in deeper levels of self-disclosure and do so with greater intentionality than previous research indicated. More interestingly, narcissistic users simultaneously tend to control their expressions in public by concealing who they really are. Overall, these findings suggested that the self-disclosures on Facebook must not investigated by a single dimensions for better understanding of psychological dynamics of it users. In addition, the present research suggested that the narcissism should not be regarded as a predictor which simply gives either a positive or negative influence on self-disclosing behaviors in SNS.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.11
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• pp.943-956
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• 2003

A numerical program has been developed for the simulation of automotive engine cooling system. The program determines the mass flow rate of engine coolant circulating the engine cooling system and radiator cooling air when the engine speed is adopted by appropriate empirical correlation. The program used the method of thermal balance at individual element through the model for radiator component in radiator analysis. This study has developed the program that predicts the coolant mass flow rate, inlet and outlet temperatures of each component in the engine cooling system (engine, transmission, radiator and oil cooler) in its state of thermal equilibrium. This study also combined the individual programs and united into the total performance analysis program of the engine cooling system operating at a constant vehicle speed. An air conditioner system is also included in this engine cooling system so that the condenser of the air conditioner faces the radiator. The effect of air conditioner to the cooling performance, e.g., radiator inlet temperature, of the radiator and engine system was examined. This study could make standards of design of radiator capacity using heat rejection with respect to the mass flow rate of cooling air. This study is intended to predict the performance of each component at design step or to simulate the system when specification of the component is modified, and to analyze the performance of the total vehicle engine cooling system.