• Proceedings of the Korean Society of Medical Physics Conference
• /
• 2004.11a
• /
• pp.49-52
• /
• 2004

A few studies have shown that the function of fusiform face area is selectively involved in the perception of faces including a race difference. We investigated the neural substrates of the face-selective region called fusiform face area In the ventral occipital-temporal cortex and same-race memory superiority In the fusiform face area by the event-related fMRI. In our fMRI study, twelve healthy subjects (Oriental-Korean) performed the implicit distinction of the race while they consciously made familiar-judgments, regardless of whether they considered a face as Oriental-Korean or European-American. In the race distinction as an implicit task, the fusiform face areas (FFA) and the right parahippocampal gyrus had a greater response to the presentation of Oriental-Korean than European-American faces, but in the consciously race distinction between Oriental-Korean and European-American faces, any significant difference in the FFA was not observed. These results suggest that different activation in the fusiform regions and right parahippocampal gyrus resulting from same-race memory superiority could be implicitly taken place by the physiological processes of face recognition.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.5
• /
• pp.990-992
• /
• 2007

The purpose of this study is to develop a practical gait-event detection system which is necessary for the FES (functional electrical stimulation) control of locomotion in paralyzed patients. The system is comprised of a sensor board and an event recognition algorithm. We focused on the practicality improvement of the system through 1) using accelerometer to get the angle of shank and dispensing with the foot-switches having limitation in indoor or barefoot usage and 2) using a rule-base instead of threshold to determine the heel-off/heel-strike events corresponding the stimulation on/off timing. The sensor signals are transmitted through RF communication and gait-events was detected using the peaks in shank angle. The system could detect two critical gait-events in all five paralyzed patients. The standard deviation of the gait events time from the peaks were smaller when 1.5Hz cutoff frequency was used in the derivation of the shank angle from the acceleration signals.

• Proceedings of the Korea Contents Association Conference
• /
• 2004.11a
• /
• pp.30-35
• /
• 2004

The objective of this research is to analyse the effect of family restaurant quality on the customer satisfaction level, by surveying college students who have used family restaurants. As these days well developed industrial society, not only service business but also most of business area needs to high quality service. For survey results, this study analyzed by statistical methods such as frequency analysis, factor analysis, and regression analysis.

• Journal of the Korean Society of Industry Convergence
• /
• v.26 no.2_1
• /
• pp.217-223
• /
• 2023

With the rapid advancement of technologies, need for different research fields where this technology can be used is also increasing. One of the most researched topic in computer vision is object detection, which has widely been implemented in various fields which include healthcare, video surveillance and education. The main goal of object detection is to identify and categorize all the objects in a target environment. Specifically, methods of object detection consist of a variety of significant techniq ues, such as image processing and patterns recognition. Anomaly detection is a part of object detection, anomalies can be found various scenarios for example crowded places such as subway stations. An abnormal event can be assumed as a variation from the conventional scene. Since the abnormal event does not occur frequently, the distribution of normal and abnormal events is thoroughly imbalanced. In terms of public safety, abnormal events should be avoided and therefore immediate action need to be taken. When abnormal events occur in certain places, real time detection is required to prevent and protect the safety of the people. To solve the above problems, we propose a modified YOLOv5 object detection algorithm by implementing dilated convolutional layers which achieved 97% mAP50 compared to other five different models of YOLOv5. In addition to this, we also created a simple mobile application to avail the abnormal event detection on mobile phones.

• Transactions of the Korean Society of Pressure Vessels and Piping
• /
• v.10 no.1
• /
• pp.25-30
• /
• 2014

Korea Hydro & Nuclear Power Co.,LTD(KHNP) was strongly interested in promotion of employee's Safety Culture because it is needed to change the recognition of Safety Culture after the Fukushima accident and Kori-1 blackout event. So, KHNP developed the KHNP Safety Culture Definition, Principles and Attributes and shared them with all employees. By using them, Safety Culture Assessment for a site plant employees was carried out. Through the pilot Safety Culture Assessment in 2012, In 2013, it was expanded to 6 plants and various improvements had been obtained from that. KHNP has been developing a variety of training materials, Safety Culture posters, videos which was designed to give lessons about safety culture with a variety of event cases. And keep trying to form Safety Culture Circumstances In this study, statistic methods are used to verify the effectiveness of KHNP Safety Culture Principles and Safety Culture Assessment.

• Proceedings of the IEEK Conference
• /
• 2000.06e
• /
• pp.127-130
• /
• 2000

Classification of Electroencephalogram(EEG) makes one of key roles in the field of clinical diagnosis, such as detection for epilepsy. Spectrum analysis using the fourier transform(FT) uses the same window to signals, so classification rate decreases for nonstationary signals such as EEG's. In this paper, wavelet power spectrum method using wavelet transform which is excellent in detection of transient components of time-varying signals is applied to the classification of three types of Event Related Potential(EP) and compared with the result by fourier transform. In the experiments, two types of photic stimulation, which are caused by eye opening/closing and artificial light, are used to collect the data to be classified. After choosing a specific range of scales, scale-averaged wavelet spectrums extracted from the wavelet power spectrum is used to find features by Back-Propagation(13P) algorithm. As a result, wavelet analysis shows superiority to fourier transform for nonstationary EEG signal classification.

• Korean journal of communication and information
• /
• v.25
• /
• pp.65-102
• /
• 2004

The purpose of this study was to examine the news attributes of the nuclear waste storage facility in Wido by conducting content analysis of two newspapers (Chosun Ilbo and Hangyoreh) and Ohmynews. Furthermore, this study measured the effects of news attributes on readers' attitude, opinion, and recognition of the event. The results of the content analysis indicated that all three newspapers focused on event-oriented coverage than issue-oriented one. Also, they only dealt with two issues-decision making process of the residents and rewards for residents-among a total of nine issues. That is, according to the hypothesis of the second-level agenda-setting theory, the media emphasize on a particular attribute while ignoring other attributes, which, in turn, make the particular attributes more salient. Based on the results of content analysis, this study conducted an experiment to measure the effects of media attributes on public recognition toward the attributes in terms of cognitive and of affective aspects. The results showed a significant relationship between media attributes and public attributes, which confirmed the effects of the second-level agenda setting. However, the transfer of attributes did not take place in affecting public opinion and public recognition of the event itself.

• Journal of Broadcast Engineering
• /
• v.23 no.6
• /
• pp.855-865
• /
• 2018

Sound event detection is one of the research areas to model human auditory cognitive characteristics by recognizing events in an environment with multiple acoustic events and determining the onset and offset time for each event. DCASE, a research group on acoustic scene classification and sound event detection, is proceeding challenges to encourage participation of researchers and to activate sound event detection research. However, the size of the dataset provided by the DCASE Challenge is relatively small compared to ImageNet, which is a representative dataset for visual object recognition, and there are not many open sources for the acoustic dataset. In this study, the sound events that can occur in indoor and outdoor are collected on a larger scale and annotated for dataset construction. Furthermore, to improve the performance of the sound event detection task, we developed a dual CNN structured sound event detection system by adding a supplementary neural network to a convolutional neural network to determine the presence of sound events. Finally, we conducted a comparative experiment with both baseline systems of the DCASE 2016 and 2017.

• Journal of Korean Society of Transportation
• /
• v.25 no.5
• /
• pp.149-160
• /
• 2007

Automobile black boxes store and provide accident and driving information. The accident and driving information can be utilized to build scientific traffic-event database and can be applied in various industries. The objective of this study is to develop a recognition system of dangerous driving through analyzing the driving characteristic patterns. In this paper, possible dangerous driving models are classified into four models on the basis of vehicle behaviors(acceleration, deceleration, rotation) and accident types from existing statistical data. Dangerous driving data have been acquired through vehicle tests using automobile black boxes. Characteristics of driving patterns have been analyzed in order to classify dangerous driving models. For the recognition of dangerous driving, this study selected critical value of each dangerous driving model and developed the recognition algorithm of dangerous driving. The study has been verified by the application of recognition algorithm of dangerous driving and vehicle tests using automobile black boxes. The presented recognition methods of dangerous driving can be used for on-line/off-line management of drivers and vehicles.

• Journal of Korea Multimedia Society
• /
• v.20 no.6
• /
• pp.950-959
• /
• 2017

Even though there are many studies on emotion recognition using EEG, there is a few research on specific emotion recognition in detail. In this paper, we construct test videos and conduct congruent-incongruent test for analysis on fear of crime. We compared the differences of event-related potential of subjects before and after watching the video using the congruent-incongruent test and analyzed the fear that subject perceived. Our results demonstrate that subjects showed lower amplitudes for unexpected stimuli in the PZ, POZ, and OZ electrodes of the occipital lobe, which process visual stimuli. These results indicate that the perception of subject is slower for unexpected objects.