Lee, Kichun;Choi, So Yun;Kim, Jae Kyeong;Ahn, Hyunchul
Journal of Intelligence and Information Systems
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v.20
no.1
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pp.1-14
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2014
Both researchers and practitioners are showing an increased interested in interactive exhibition services. Interactive exhibition services are designed to directly respond to visitor responses in real time, so as to fully engage visitors' interest and enhance their satisfaction. In order to install an effective interactive exhibition service, it is essential to adopt intelligent technologies that enable accurate estimation of a visitor's emotional state from responses to exhibited stimulus. Studies undertaken so far have attempted to estimate the human emotional state, most of them doing so by gauging either facial expressions or audio responses. However, the most recent research suggests that, a multimodal approach that uses people's multiple responses simultaneously may lead to better estimation. Given this context, we propose a new multimodal emotional state estimation model that uses various responses including facial expressions, gestures, and movements measured by the Microsoft Kinect Sensor. In order to effectively handle a large amount of sensory data, we propose to use stratified sampling-based MRA (multiple regression analysis) as our estimation method. To validate the usefulness of the proposed model, we collected 602,599 responses and emotional state data with 274 variables from 15 people. When we applied our model to the data set, we found that our model estimated the levels of valence and arousal in the 10~15% error range. Since our proposed model is simple and stable, we expect that it will be applied not only in intelligent exhibition services, but also in other areas such as e-learning and personalized advertising.
Journal of the Korea Academia-Industrial cooperation Society
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v.21
no.1
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pp.577-583
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2020
This study analyzed the effect of career preparation behavior of female college graduates on their job satisfaction. The results of this study are as follows: First, the relationship between job satisfaction and career preparation behavior and a regression analysis of job satisfaction were all examined. This study used the original data from the Korea Employment Information Service for '2012 College Graduates' Occupation Route Survey'. The subjects of this study were 1,569 women in the science and engineering fields (649 engineering graduates, and 920 science graduates). The data was analyzed by frequency analysis, independent sample t tests, correlation analysis, and hierarchical multiple regression analysis using SPSS WIN 19.0. As a result, women with 4 years of college have higher job stability and job satisfaction than college students, but the reasons for major selection, university type, college location, and department. The results of this study are as follows. First, the effect of the variables on career satisfaction and job satisfaction was not statistically significant. This suggests that the type of college does not have a significant effect on job satisfaction if the university systematically prepares people for a career and the university suits a person's aptitude.
In this study, natural surfactants were extracted from Medicago sativa L. The O/W emulsification processes with the extracted natural surfactants were optimized using central composite design model-response surface methodology (CCD-RSM) and a 95% confidence interval was used to confirm the reasonableness of the optimization. Herein, independent parameters were the ratio of saponins to total surfactant (P), amount of surfactant (W), and emulsification speed (R), whereas the reaction parameters were the emulsion stability index (ESI), mean droplet size (MDS), and viscosity (V). Using the multiple reaction, the optimal conditions for the ratio of saponins to total surfactant, amount of surfactant, and emulsification speed for O/W emulsification were 49.5%, 9.1 wt%, and 6559.5 rpm, respectively. Under these optimal conditions, the expected values of ESI, MDS, and V as the reaction parameters were 89.9%, 1058.4 nm, and 1522.5 cP, respectively. The values of ESI, MDS, and V from these expected values were 88.7%, 1026.4 nm, and 1486.5 cP, respectively, and the average experimental error for validating the accuracy was about 2.3 (± 0.4)%. Therefore, it was possible to design an optimization process for evaluating the O/W emulsion process with Medicago sativa L. using CCD-RSM.
This study was conducted to provide basic data for crop monitoring by comparing and analyzing changes in reflectance and vegetation index by sensor of multi-spectral sensors mounted on unmanned aerial vehicles. For four types of unmanned aerial vehicle-mounted multispectral sensors, such as RedEdge-MX, S110 NIR, Sequioa, and P4M, on September 14 and September 15, 2020, aerial images were taken, once in the morning and in the afternoon, a total of 4 times, and reflectance and vegetation index were calculated and compared. In the case of reflectance, the time-series coefficient of variation of all sensors showed an average value of about 10% or more, indicating that there is a limit to its use. The coefficient of variation of the vegetation index by sensor for the crop test group showed an average value of 1.2 to 3.6% in the crop experimental sites with high vitality due to thick vegetation, showing variability within 5%. However, this was a higher value than the coefficient of variation on a clear day, and it is estimated that the weather conditions such as clouds were different in the morning and afternoon during the experiment period. It is thought that it is necessary to establish and implement a UAV flight plan. As a result of comparing the NDVI between the multi-spectral sensors of the unmanned aerial vehicle, in this experiment, it is thought that the RedEdeg-MX sensor can be used together without special correction of the NDVI value even if several sensors of the same type are used in a stable light environment. RedEdge-MX, P4M, and Sequioa sensors showed a linear relationship with each other, but supplementary experiments are needed to evaluate joint utilization through off-set correction between vegetation indices.
Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.
The purpose of this study was to investigate the influences of 5 intrinsic and 5 extrinsic factors on technology teachers' job satisfaction and commitment. The collected data from 108 technology teachers in Gwangju city and Jeolla Nam-do, were analyzed and tested at p<.05 or more by using Multiple Regression through SPSS program. The levels of the teachers' job satisfaction and commitment were respectively M=3.91 and M=3.69 at Likert scale. Among 5 intrinsic and 5 extrinsic factors, other factors except for two factors-work environment and salary were, even if a little, satisfied to the teachers. They were more satisfied with the intrinsic factors than the extrinsic. $R^2$=.515 was found between teachers' job satisfaction and the combination of 10 factors-achievement, work itself, responsibility, opportunity for growth, recognition, job safety, work environment, salary, supervision skill, human relation. $R^2$=.616 was between teachers' commitment with the combination of the factors. The combinations were respectively accountable for 51.5% of the job satisfaction change and for 61.6% of the commitment change. The relative importances of the factors were salary first, achievement second and others not for the job satisfaction, and achievement first, opportunity for growth second and others not for the commitment. The generalization of the above results is limited to improving technology teachers' job satisfaction and commitment at the secondary level in Gwangju city and Jeolla Nam-do.
Journal of the Korea Academia-Industrial cooperation Society
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v.20
no.11
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pp.96-105
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2019
This study analyzed the correlation of work values, career attitude maturity and employment preparation behavior by determining the sociodemographic characteristics, and the study confirmed the validity of the influence of work values and career attitude maturity on employment preparation behavior. The subjects of this study were 218 nursing students at a university located in Geonggi-do. The data was collected from June 4th to August 27th, 2019 by using structured questionnaires. As a result, female students scored significantly higher in work values and career attitude maturity than did the male students, and the students who had better grades showed higher employment preparation behavior. In addition, the result showed positive correlation between work values and employment preparation behavior, and the study showed correlation between career attitude maturity and employment preparation behavior. Greater independence, readiness, certainty, and decisiveness were higher and were sub-factors of career attitude maturity and employment preparation behavior. Moreover, the higher the students' patriotism and indoor activities, the higher was their employment preparation behavior. In conclusion, the employment preparation behavior was higher according to greater work values, while the influence of career attitude maturity on employment preparation behavior was not statistically significant.
Chung, Sang Hoon;Hwang, Kwang Mo;Sung, Joo Han;Kim, Ji Hong
Journal of Korean Society of Forest Science
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v.104
no.3
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pp.375-382
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2015
We classified the forest type and figured out the ecological characteristics for each of the types in order to provide the basic informations for being induced ecologically efficient forest practice plan by vegetation units in the natural forest of Songnisan. We established the 250 sample points and collected the vegetation data of vertical distribution for each sample. A variety of multivariate statistical methods were applied to classify the forest types. The species diversity index were analyzed to estimate the stability and maturity for forest vegetation in each the type. The types were divided from two to ten clusters by cluster analysis. The appropriate number of clusters was estimated five clusters by indicator species analysis. It was verified through the multiple discriminant analysis that the estimated number of clusters had been suitable. Based on the species composition for each the type, this study site was classified into five forest types: 1) Quercus serrata and 2) mixed mesophytic forest in the valley area, 3) Q. mongolica forest in the main ridge, 4) Pinus densiflora forest in the sub-ridge extending from the main, and 5) Q. variabilis-P. densiflora forest between the sub-ridge and valley. The species diversity index of the pine forest that had been a simple species composition was the lowest while that of the mixed mesophytic forest of which the composition had been diverse was the highest. As the forest vegetation was more varied, the index showed a tendency to increase.
Most of the existing multicast routing protocols for ad-hoc networks do not take into account the efficiency of the protocol for the cases when there are large number of sources in the multicast group, resulting in either large overhead or poor data delivery ratio when the number of sources is large. In this paper, we propose a multicast routing protocol for ad-hoc networks, which particularly considers the scalability of the protocol in terms of the number of sources in the multicast groups. The proposed protocol designates a set of sources as the core sources. Each core source is a root of each tree that reaches all the destinations of the multicast group. The union of these trees constitutes the data delivery mesh, and each of the non-core sources finds the nearest core source in order to delegate its data delivery. For the efficient operation of the proposed protocol, it is important to have an appropriate number of core sources. Having too many of the core sources incurs excessive control and data packet overhead, whereas having too little of them results in a vulnerable and overloaded data delivery mesh. The data delivery mesh is optimally reconfigured through the periodic control message flooding from the core sources, whereas the connectivity of the mesh is maintained by a persistent local mesh recovery mechanism. The simulation results show that the proposed protocol achieves an efficient multicast communication with high data delivery ratio and low communication overhead compared with the other existing multicast routing protocols when there are multiple sources in the multicast group.
Kim, Bo-Seong;Lee, Young-Chang;Lim, Dong-Hoon;Kim, Hyun-Woo;Min, Yoon-Ki
Science of Emotion and Sensibility
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v.13
no.3
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pp.475-484
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2010
This study examined the influence of the SOA(stimulus onset asynchrony) between visual and auditory stimuli on the integration phenomenon of audio-visual senses. Within the stimulus integration phenomenon, the redundant target effect (the faster and more accurate response to the target stimulus when the target stimulus is presented with more than two modalities) and the visual dominance effect (the faster and more accurate response to a visual stimulus compared to an auditory stimulus) were examined as we composed a visual and auditory unimodal target condition and a multimodal target condition and then observed the response time and accuracy. Consequently, despite the change between visual and auditory stimuli SOA, there was no redundant target effect present. The auditory dominance effect appeared when the SOA between the two stimuli was over 100ms. Theses results imply that the redundant target effect is continuously maintained even when the SOA between two modal stimuli is altered, and also suggests that the behavioral results of superior information processing can only be deducted when the time difference between the onset of the auditory stimuli and the visual stimuli is approximately over 100ms.
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