형상인식 기반 지능형 성별인식 디지털 사이니지에 대한 연구

Journal of Oriental Neuropsychiatry, 2015

Objectives: The purpose of this study was to review previous clinical studies on underlying mechanisms of sleep-related type-specific pathophysiological symptoms among the Sasang types. Methods and Procedure: We reviewed seven research databases from December 2003 to August 2015 with the keywords Sasang typology, constitution and sleep. The Sasang type-specific sleep-related symptoms were analyzed based on seven categories, including subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medications and daytime dysfunction. Results: Total of twelve studies were included in the analysis. The Tae-Yang type showed low subjective sleep quality, long sleep latency and frequent awakening, and the So-Yang type showed long sleep latency. The Tae-Eum type presented high subjective sleep quality, short sleep duration, frequent snore, toss and turn during the sleep, and insomnia and low frequency of dream. The So-Eum type showed long sleep latency in male and high frequency of dream. The Eum type combining Tae-Eum and So-Eum types had higher subjective sleep quality, longer sleep duration and higher frequency of dream than the Yang type combining Tae-Yang and So-Yang types. Conclusions: This study reviewed type-specific sleep-related characteristics and discussed possible pathophysiological mechanisms involved. Differences in sleep characteristics among the Sasang types might stem from type-specific temperaments and require further study.

Journal of Korean Society for Geospatial Information System, 2012

The method regarding obtaining various kinds of attribute data of spatial information, including that of digital map, is normally restricted to Geographic survey that deals with in-field surveys. Geographic surveying for drawing digital map, however, require much effort due to the fact that a surveyor has to characterize geographic features individually in the field. Not only does the Geographic survey cover large area, but also its need for manual drawing and surveying using Draft map makes it more expensive and time-consuming. Though some recent Geographic surveys take advantage of MMS(Mobile Mapping System) to collect computerized information, there are inevitable limits in creating digital map with such data. This research will analyze the problems in current Geographic surveys and suggest adequate methods and standards for Geographic surveys by researching the methods of domestic/international service organizations that deal with establishing spatial information. This study therefore will aim to enhance the efficiency of creating digital map and Geographic survey, which would ultimately maximize the applicability of pan-national digital map by improving reliability of digital map and upgrading the utilizability of Geographic survey data.

The Journal of Society for e-Business Studies, 2011

2013

Objective: The aim of this study is to propose the design process suitable for developing the cognitive interface considering system engineering process (SEP) models. Background: Due to the cognitive workload in an operation of HMS, some cognitive interfaces have been developed. It is somehow difficult to use the developed cognitive interface in real working environment since they often showed a conflict to stereotyped interface. So it is necessary to develop the design process suitable for the more operator-specific interface. Method: Various SEP models were reviewed for selecting the suitable design process which might resolve the problem from design-specific interface. Results: The suitable process for designing cognitive interface was proposed considering currently usable SEP models. Conclusion: The findings from the study may be helpful for systematic approach to designing cognitive interface in digitalized environment, Application: The proposed design process would be applied ...

Journal of The Korean Association For Science Education, 2015

In this study, we investigated the effects of individualized learning adapted to students' conceptions using smart devices in science instruction upon students' conceptual understanding, the retention of conception, achievement, learning motivation, enjoyment of science lessons, and perception about individualized learning using smart devices. Four seventh-grade classes at a coed middle school in Seoul were assigned to a control group and a treatment group. Students were taught about molecular motions for seven class periods. Two-way ANCOVA results revealed that the scores of a conception test, the retention of the conception test, a learning motivation test, and an enjoyment of science lessons test for the treatment group were significantly higher than those for the control group. Although the score of the treatment group was higher than that of the control group in the achievement test, the difference was not statistically significant. Students' perceptions about individualized learning using smart devices were also found to be positive.

Journal of the Institute of Electronics Engineers of Korea, 2013

We propose adaptive detection algorithm to reduce a false alarm by considering the characteristics of the random noise on the detection system based on a seismic sensor. The proposed algorithm consists of the first step detection using kernel function and the second step detection using detection classes. Kernel function of the first step detection is obtained from the threshold of the Neyman-Pearon decision criterion using the probability density functions varied along the noise from the measured signal. The second step detector consists of 4 step detection class by calculating the occupancy time of the footstep using the frist detected samples. In order to verify performance of the proposed algorithm, the detection of the footsteps using measured signal of targets (walking and running) are performed experimentally. The detection results are compared with a fixed threshold detector. The frist step detection result has the high detection performance of 95% up to 10m area. Also, the false alarm probability is decreased from 40% to 20% when it is compared with the fixed threshold detector. By applying the detection class(second step detector), it is greatly reduced to less than 4%.

Journal of Korea Multimedia Society, 2015

In recent years, ear has emerged as a new biometric trait, because it has advantage of higher user acceptance than fingerprint and can be captured at remote distance in an indoor or outdoor environment. This paper proposes an individual identification method using ear region based on SIFT(shift invariant feature transform). Unlike most of the previous studies using rectangle shape for extracting a region of interest(ROI), this study sets an ROI as a flexible expanded region including ear. It also presents an effective extraction and matching method for SIFT keypoints. Experiments for evaluating the performance of the proposed method were performed on IITD public database. It showed correct identification rate of 98.89%, and it showed 98.44% with a deformed dataset of 20% occlusion. These results show that the proposed method is effective in ear recognition and robust to occlusion.

Journal of Korea Multimedia Society, 2013

Journal of Ocean Engineering and Technology, 2012

In this paper, a Bayesian classifier based on PCA (principle component analysis) is proposed to classify underwater transient signals using 16 th order LPC (linear predictive coding) coefficients as feature vector. The proposed classifier is composed of two steps. The mechanical signals were separated from biological signals in the first step, and then each type of the mechanical signal was recognized in the second step. Three biological transient signals and two mechanical signals were used to conduct experiments. The classification ratios for the feature vectors of biological signals and mechanical signals were 94.75% and 97.23%, respectively, when all 16 order LPC vector were used. In order to determine the effect of underwater noise on the classification performance, underwater ambient noise was added to the test signals and the classification ratio according to SNR (signal-to-noise ratio) was compared by changing dimension of feature vector using PCA. The classification ratios of the biological and mechanical signals under ocean ambient noise at 10dB SNR, were 0.51% and 100% respectively. However, the ratios were changed to 53.07% and 83.14% when the dimension of feature vector was converted to three by applying PCA. For correct, classification, it is required SNR over 10 dB for three dimension feature vector and over 30dB SNR for seven dimension feature vector under ocean ambient noise environment.

Journal of Life Science, 2007