• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.79-94
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• 2013

Recently, the high value added business is steadily growing in the culture and art area. To generated high value from a performance, the satisfaction of audience is necessary. The flow in a critical factor for satisfaction, and it should be induced from audience and measures. To evaluate interest and emotion of audience on contents, producers or investors need a kind of index for the measurement of the flow. But it is neither easy to define the flow quantitatively, nor to collect audience's reaction immediately. The previous studies of the group flow were evaluated by the sum of the average value of each person's reaction. The flow or "good feeling" from each audience was extracted from his face, especially, the change of his (or her) expression and body movement. But it was not easy to handle the large amount of real-time data from each sensor signals. And also it was difficult to set experimental devices, in terms of economic and environmental problems. Because, all participants should have their own personal sensor to check their physical signal. Also each camera should be located in front of their head to catch their looks. Therefore we need more simple system to analyze group flow. This study provides the method for measurement of audiences flow with group synchronization at same time and place. To measure the synchronization, we made real-time processing system using the Differential Image and Group Emotion Analysis (GEA) system. Differential Image was obtained from camera and by the previous frame was subtracted from present frame. So the movement variation on audience's reaction was obtained. And then we developed a program, GEX(Group Emotion Analysis), for flow judgment model. After the measurement of the audience's reaction, the synchronization is divided as Dynamic State Synchronization and Static State Synchronization. The Dynamic State Synchronization accompanies audience's active reaction, while the Static State Synchronization means to movement of audience. The Dynamic State Synchronization can be caused by the audience's surprise action such as scary, creepy or reversal scene. And the Static State Synchronization was triggered by impressed or sad scene. Therefore we showed them several short movies containing various scenes mentioned previously. And these kind of scenes made them sad, clap, and creepy, etc. To check the movement of audience, we defined the critical point, ${\alpha}$and ${\beta}$. Dynamic State Synchronization was meaningful when the movement value was over critical point ${\beta}$, while Static State Synchronization was effective under critical point ${\alpha}$. ${\beta}$ is made by audience' clapping movement of 10 teams in stead of using average number of movement. After checking the reactive movement of audience, the percentage(%) ratio was calculated from the division of "people having reaction" by "total people". Total 37 teams were made in "2012 Seoul DMC Culture Open" and they involved the experiments. First, they followed induction to clap by staff. Second, basic scene for neutralize emotion of audience. Third, flow scene was displayed to audience. Forth, the reversal scene was introduced. And then 24 teams of them were provided with amuse and creepy scenes. And the other 10 teams were exposed with the sad scene. There were clapping and laughing action of audience on the amuse scene with shaking their head or hid with closing eyes. And also the sad or touching scene made them silent. If the results were over about 80%, the group could be judged as the synchronization and the flow were achieved. As a result, the audience showed similar reactions about similar stimulation at same time and place. Once we get an additional normalization and experiment, we can obtain find the flow factor through the synchronization on a much bigger group and this should be useful for planning contents.

• The Journal of the Acoustical Society of Korea
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• v.16 no.4
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• pp.57-63
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• 1997

In this paper, we study the efficient feature vector extraction method and front-end processing to improve the performance of the speech recognition system using KT(Korea Telecommunication) database collected through various telephone channels. First of all, we compare the recognition performances of the feature vectors known to be robust to noise and environmental variation and verify the performance enhancement of the recognition system using weighted cepstral distance measure methods. The experiment result shows that the recognition rate is increasedby using both PLP(Perceptual Linear Prediction) and MFCC(Mel Frequency Cepstral Coefficient) in comparison with LPC cepstrum used in KT recognition system. In cepstral distance measure, the weighted cepstral distance measure functions such as RPS(Root Power Sums) and BPL(Band-Pass Lifter) help the recognition enhancement. The application of the spectral subtraction method decrease the recognition rate because of the effect of distortion. However, RASTA(RelAtive SpecTrAl) processing, CMS(Cepstral Mean Subtraction) and SBR(Signal Bias Removal) enhance the recognition performance. Especially, the CMS method is simple but shows high recognition enhancement. Finally, the performances of the modified methods for the real-time implementation of CMS are compared and the improved method is suggested to prevent the performance degradation.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.2
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• pp.202-210
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• 2013

This study elucidated the effects of limited concentrate feeding on growth, plasma profile, and gene expression of gluconeogenic enzymes and visfatin in the liver of Hanwoo beef calves. The purpose of this study was to test that reducing the amount of concentrate would partially be compensated by increasing the intake of forage and by altering the metabolic status. The study utilized 20 Korean native beef calves (Hanwoo; 60 to 70 d of age) divided into two groups of 10 calves each for 158 d. Control group calves received the amount of concentrate as per the established Korean feeding standards for Hanwoo, whereas calves in the restricted group only received half the amount of concentrate as per standard requirements. Good quality forage (Timothy hay) was available for ad libitum consumption to both groups. Since calves were with their dam until 4 months of age in breeding pens before weaning, the intake of milk before weaning was not recorded, however, the concentrate and forage intakes were recorded daily. Body weights (BW) were recorded at start and on 10 d interval. Blood samples were collected at start and at 50 d interval. On the final day of the experiment, liver biopsies were collected from all animals in each group. The BW was not different between the groups at all times, but tended to be higher (p = 0.061) only at final BW in control than restricted group. Total BW gain in the control group was 116.2 kg as opposed to 84.1 kg in restricted group that led to average BW gain of 736 g/d and 532 g/d in respective groups, and the differences were significant (p<0.01). As planned, the calves in the control group had higher concentrate and lower forage intake than the restricted group. The plasma variables like total protein and urea were higher (p<0.05) in control than restricted group. The mRNA expressions for the gluconeogenic enzymes such as cytosolic phosphoenol pyruvate carboxykinase (EC 4.1.1.32) and pyruvate carboxylase (EC 6.4.1.1), and visfatin measured by quantitative real-time PCR in liver biopsies showed higher expression (p<0.05) in restricted group than control. Overall, restricting concentrate severely reduced the growth intensity and affected few plasma indices, and gene expression in liver was increased indicating that restricting concentrate in the feeding schemes during early growth for beef calves is not advocated.

• Journal of Advanced Navigation Technology
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• v.9 no.1
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• pp.48-55
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• 2005

In this paper, we propose an efficient moving object tracking technique for multi-camera surveillance system. Color CCD cameras used in this system are network cameras with their own IP addresses. Input image is transmitted to the media server through wireless connection among server, bridge, and Access Point (AP). The tracking system sends the received images through the network to the tracking module, and it tracks moving objects in real-time using color matching method. We compose two sets of cameras, and when the object is out of field of view (FOV), we accomplish hand-over to be able to continue tracking the object. When hand-over is performed, we use MHI(Motion History Information) based on color information and M-bin histogram for an exact tracking. By utilizing MHI, we can calculate direction and velocity of the object, and those information helps to predict next location of the object. Therefore, we obtain a better result in speed and stability than using template matching based on only M-bin histogram, and we verified this result by an experiment.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.8
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• pp.1131-1140
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• 2014

This research focused on the effects of different doses of Bacillus subtilis KN-42 on the growth performance, diarrhea incidence, faecal bacterial flora, and the relative number of Lactobacillus and Escherichia coli in faeces of weaned piglets to determine whether the strain can serve as a candidate antimicrobial growth promoter. A total of 360 piglets (initial body weight $7.14{\pm}0.63$ kg) weaned at $26{\pm}2$ days of age were randomly allotted to 5 treatment groups (4 pens per treatment with 18 pigs per pen) for a 28-day trial. Dietary treatments were basal diet without any antimicrobial (negative control; NC), basal diet supplemented with 120 mg/kg feed of neomycin sulfate (positive control; PC) and basal diet supplemented with $2{\times}10^9$ (L), $4{\times}10^9$ (M) and $20{\times}10^9$ (H) CFU/kg feed of B. subtilis KN-42. During the overall period, average daily gain and feed efficiency of piglets were higher in groups PC, M, and H than those in group NC (p<0.05), and all probiotics and antibiotics groups had a lower diarrhea index than group NC (p<0.05). The 16S rDNA gene-based methods were used to analyze faecal bacterial flora on day 28 of experiment. The result of denaturing gradient gel electrophoresis analysis showed that supplementation of B. subtilis KN-42 to the diet changed the bacterial communities, with a higher bacterial diversity and band number in group M than in the other four groups. Real-time polymerase chain reaction analysis showed that the relative number of Lactobacillus were higher in groups PC and H than in group NC (p<0.05), and the supplemented B. subtilis KN-42 to the diet also reduced the relative number of E. coli (p<0.05). These results suggest that dietary addition of B. subtilis KN-42 can improve the growth performance and gastrointestinal health of piglets.

• Journal of the Korea Society of Computer and Information
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• v.25 no.9
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• pp.37-44
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• 2020

AI technology has developed in the form of decision support technology in law, patent, finance and national defense and is applied to disease diagnosis and legal judgment. To search real-time information with Deep Learning, Big data Analysis and Deep Learning Algorithm are required. In this paper, we try to predict the entrance rate to high-ranking universities using a Deep Learning model, RNN(Recurrent Neural Network). First, we analyzed the current status of private academies in administrative districts and the number of students by age in administrative districts, and established a socially accepted hypothesis that students residing in areas with a high educational fever have a high rate of enrollment in high-ranking universities. This is to verify based on the data analyzed using the predicted hypothesis and the government's public data. The predictive model uses data from 2015 to 2017 to learn to predict the top enrollment rate, and the trained model predicts the top enrollment rate in 2018. A prediction experiment was performed using RNN, a Deep Learning model, for the high-ranking enrollment rate in the special education zone. In this paper, we define the correlation between the high-ranking enrollment rate by analyzing the household income and the participation rate of private education about the current status of private institutes in regions with high education fever and the effect on the number of students by age.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.9
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• pp.18-23
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• 2017

The shipyard quay process struggles to control workers and maintain a secure working environment because of the presence of at least 1,000 people. Therefore, safety accidents such as an explosion or a fire are likely to occur. With the recent increase in safety accidents at shipyards, the requirements for safety and process monitoring have been strengthened. Major shipyards are conducting researchto monitor the process in real time and to detect the work environment for safety. In this paper, we propose a safe and accurate evacuation route based on the information of the dangerous area and the user's location based on a mobile application to reduce the casualty accidents in the presence of many personnel in a concentrated area. To do this, we analyze the trend of the fire escape system on the ground building, compare various algorithms for escape route calculation, select appropriate algorithms for this study, and perform programming. A basic experiment was conducted to confirm the results. The proposed method is expected to be used in large ship construction sites, passenger ships and large public facilities to reduce accidents in the case of a safety accident.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.55-69
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• 2017

Recently, the IoT (Internet of Things) environment is being developed rapidly through network which is linked to intellectual objects. Through the IoT, it is possible for human to intercommunicate with objects and objects to objects. Also, the IoT provides artificial intelligent service mixed with knowledge of situational awareness. One of the industries based on the IoT is a car industry. Nowadays, a self-driving vehicle which is not only fuel-efficient, smooth for traffic, but also puts top priority on eventual safety for humans became the most important conversation topic. Since several years ago, a research on the recognition of the surrounding environment for self-driving vehicles using sensors, lidar, camera, and radar techniques has been progressed actively. Currently, based on the WAVE (Wireless Access in Vehicular Environment), the research is being boosted by forming networking between vehicles, vehicle and infrastructures. In this paper, a research on the recognition of a traffic signs on highway was processed as a part of the awareness of the surrounding environment for self-driving vehicles. Through the traffic signs which have features of fixed standard and installation location, we provided a learning theory and a corresponding results of experiment about the way that a vehicle is aware of traffic signs and additional informations on it.

• Journal of the Korea Institute of Building Construction
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• v.11 no.3
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• pp.283-291
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• 2011

As the construction industry has recently been transformed by the emergence of ubiquitous and intelligent technology, there have been major changes in the management methods employed. Specifically, next-generation construction management systems have been developed that collect and analyze many pieces of information in real time by using various wireless sensors and networks. The purpose of this study is to understand the current status of Ubiquitous Sensor Networks (USN) in the construction sector, and to gain fundamental data for a system of measuring concrete curing temperature in a construction site that employs a USN. By investigating the application status of USN, it was confirmed that USN has mainly been applied to the maintenance of facilities, safety management, and quality control. In addition, a field experiment in which the curing temperature of concrete was measured using a USN was carried out to evaluate two systems with wireless sensor networks, and the applicability of these systems on site was confirmed. However, it is estimated that the embedded wireless sensor type is affected by metal equipment on site, internal battery of sensor and concrete depth, and studies to provide more stable system by USN are thus required.

• Journal of Internet Computing and Services
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• v.18 no.3
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• pp.29-36
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• 2017

In these days, 3D dynamic simulation is closely related to many industries. In the past, physically-based 3D simulation was used mainly in the car crash or construction related fields, but it also plays an important role in movies or games today. Many mathematical computations are needed to represent the 3D object realistically, but it is difficult to process a large amount of calculations for simulation of application based on CPU in real-time. Recently, with the advanced graphic hardware and improved architecture, GPU can be utilized for the general purposes of computation function as well as graphic computation. Many approaches using GPU have been applied for various research fields. In this paper, we analyze the performance variation of two cloth simulation algorithms based on GPU according to the change of execution properties of GPU shaders in oder to optimize the performance of GPU-based cloth simulation. Cloth simulation is implemented by the spring centric algorithm and node centric algorithm with GPU parallel computing using compute shader of GLSL 4.3. We compare the performance of between these algorithms according to the change of the size and dimension of work group. The experiment is repeated to 10 times during 5,000 frames for each test and experimental results are provided by averaging of FPS. The experimental result shows that the node centric algorithm is executed in higher speed than the spring centric algorithm.