• Journal of Animal Science and Technology
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• v.54 no.5
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• pp.375-379
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• 2012

This study was carried out to define the "Wolla" coat color using 376 Jeju registered horses (white patched 142, solid coat color 234). Three major factors related to the white patches i.e ECA3-inversion for Tobiano, EDNRB 2 bp nucleotide substitution for frame Overo, and the KIT intron 16 single nucleotide polymorphism (SNP) for Sabino types of coat color were analyzed. It was found that out of 142 Jeju horses with white patches that have the genotype for ECA3-inversion (To) 140 horses were +/To heterozygous and 2 horses were To/To homozygous all Jeju horses with white patches had ECA3-inversion allele. However, there was no frame Overo or Sabino allele type in EDNRB and KIT intron 16 SNP in Jeju horses with white patches. As for 234 Jeju horses with a solid coat color, there was no ECA3-inversion allele related to the white patches. Thus, it could be considered that Wolla coat color with white patches in Jeju horses might have come from the Tobiano line in the genetic classification by coat color.

• Smart Media Journal
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• v.9 no.4
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• pp.102-108
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• 2020

In this paper, we propose a real-time method of detecting hand motions and extracting the signal frame induced by EF(Electric Field) sensors. The signal induced by hand motion includes not only noises caused by various environmental sources as well as sensor's physical placement, but also different initial off-set conditions. Thus, it has been considered as a challenging problem to detect the motion signal and extract the motion frame automatically in real-time. In this study, we remove the PLN(Power Line Noise) using LPF with 10Hz cut-off and successively apply MA(Moving Average) filter to obtain clean and smooth input motion signals. To sense a hand motion, we use two thresholds(positive and negative thresholds) with offset value to detect a starting as well as an ending moment of the motion. Using this approach, we can achieve the correct motion detection rate over 98%. Once the final motion frame is determined, the motion signals are normalized to be used in next process of classification or recognition stage such as LSTN deep neural networks. Our experiment and analysis show that our proposed methods produce better than 98% performance in correct motion detection rate as well as in frame-matching rate.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.6
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• pp.547-552
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• 2015

In this paper, an ARS-EKF based motion counting algorithm for repetitive exercises such as calisthenics is proposed using a smartwatch. Raw sensor signals from accelerometers and gyroscopes are widely used for conventional smartwatch counting algorithms based on pattern recognition. However, generated features from raw data are not intuitive to reflect the movement of motions. The proposed motion counter algorithm is composed of navigation based feature generation and counting with error correction. The candidate features for each activity are velocity and attitude calculated through an ARS-EKF algorithm. In order to select those features which reveal the characteristics of each motion, an exercise frame from the initial sensor frame is introduced. Counting processes are basically based on the zero crossing method, and misdetected counts are eliminated via simple classification algorithms considering the frequency of the counted motions. Experimental results show that the proposed algorithm efficiently and accurately counts the number of exercises.

• Journal of Korean Academy of Nursing Administration
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• v.7 no.3
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• pp.571-588
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• 2001

Purpose : This study was to develop the nursing database for gastric cancer patients for clinical application. Method : Nursing data that development of this data base is comprehensive connected with gastric cancer patient nursing process frame to foundation as classification. Result : Each stage was processed based on the System Development Life Cycle. At the Strategy Planning stage, gastric cancer patient nursing process were analyzed. At the system Analysis Stage, database flowchart was drawn up based on frame of nursing process was drawn up. At the system Design Stage, a system was developed based on the flowchart and named the Nursing Database. The Nursing Database consisted of the patient's Basic Information, Patient's Nursing History, Discharge summary, Nursing Assessment, Nursing Diagnosis, Nursing Intervention/activity, Nursing Evaluation, Statics, Code Registration. Each element in flowchart was coded and made into a database. Nursing Assessment classified according to Gorden's Health Pattern Typology, and nursing diagnosis draws the standard 27 name of Hanguls and connected with nursing assessment. Nursing intervention and nursing activity draw 192 of thing that present in NIC, connected this with nursing assessment. Nursing evaluation is linked with nursing assessment, diagnosis and intervention by achievement availability of nursing goals. Conclusion : The biggest advantage of this database nursing process that can manage nursing information exactly and rapidly to foundation be.

• Fashion & Textile Research Journal
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• v.7 no.6
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• pp.585-593
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• 2005

Diverse and complicated trends of fashion design which were initiated at the latter part of the 20th century have been evolving in the cultural framework of Postmodernism. At this point of time, Poststructuralism, with its aims to interpret and understand modern fashion design, is a new system of thinking that reveals the contradictory aspects of rationalistic Western philosophy and accepts uncertainty and disorder as they exist. The main purpose of this study is to examine the various theoretic systems and characteristic concepts of Poststructuralism, and supply a new cognizance frame to understand the processes of fashion design with free and varied notions of deconstruction and generation, in place of the former systematic and consistent interpretation of meaning. Concerning fashion design, analysis of theories and analysis of contents. By probing and examining deconstruction theory, 'I'-other theory, textual theory, and nomadic thinking, the concepts of cognizance are classified into Nonboundariness, Otherness, and Textualism. The theoretic foundation for this analysis and classification is supplied by Derrida's deconstructional philosophy, Lacan's mental analysis, Bartes's textual theory, Deleuze's change and generation theory, together with other theories of Poststructuralism. In analysis of theories, a cognizance frame is proposed that can categorize the concepts, derived from various theories of Poststructuralism, as traits expressed in fashion design.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.889-894
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• 2009

Accompanied by the rapid development of Computer Vision, Visual surveillance has achieved great evolution with more and more complicated processing. However there are still many problems to be resolved for robust and reliable visual surveillance, and the cast shadow occurring in motion detection process is one of them. Shadow pixels are often misclassified as object pixels so that they cause errors in localization, segmentation, tracking and classification of objects. This paper proposes a novel cast shadow removal method. As opposed to previous conventional methods, which considers pixel properties like intensity properties, color distortion, HSV color system, and etc., the proposed method utilizes observations about edge patterns in the shadow region in the current frame and the corresponding region in the background scene, and applies Laplacian edge detector to the blob regions in the current frame and the background scene. Then, the product of the outcomes of application determines whether the blob pixels in the foreground mask comes from object blob regions or shadow regions. The proposed method is simple but turns out practically very effective for Gaussian Mixture Model, which is verified through experiments.

• Journal of the Korean Society of Costume
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• v.52 no.2
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• pp.115-124
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• 2002

The purposes of this study were to classify somatotype was obtained from the factor scores of the upper half of bodies and analyze the Somatometric characteristics. The sample group (hereinafter referred to as "1st age group") was drawn from bays at the ages 7 to 8 living in Pusan and Kyungsangnam-do. Data from each boy comprised 36 anthropometric measurements and 7 photographic measurements. The study reached following conclusions. 1. According to the analysis to draw Somatometric factors by the 1st age group, seven indicative factors were obtained from measurements of the upper half of bodies. The most significant factor "sectional size" and the second most significant factor "longitudinal size" characterized most aspects of body shape of boys at the ages 7 to 8. 2. According to the analysis of Somatometric characteristics by the upper half of bodies, the 1st age group was categorized into three types : Boys in type 1 had highest stature, biggest frame, broadest shoulders, most protruded chest and shoulder blades and flattest belly : boys in type 2 had shortest stature, smallest frame, sloping shoulders and most protruded belly boys in type 3 had quite high stature and his other measurements were close to the averages of this age group.he averages of this age group.

• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.420-432
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• 2014

In detection of moving objects from video sequences, an essential process for intelligent visual surveillance, the cast shadows accompanying moving objects are different from background so that they may be easily extracted as foreground object blobs, which causes errors in localization, segmentation, tracking and classification of objects. Most of the previous research results about moving cast shadow detection and removal usually utilize color information about objects and scenes. In this paper, we proposes a novel cast shadow removal method of moving objects in gray level video data for visual surveillance application. The proposed method utilizes observations about edge patterns in the shadow region in the current frame and the corresponding region in the background scene, and applies Laplacian edge detector to the blob regions in the current frame and the corresponding regions in the background scene. Then, the product of the outcomes of application determines moving object blob pixels from the blob pixels in the foreground mask. The minimal rectangle regions containing all blob pixles classified as moving object pixels are extracted. The proposed method is simple but turns out practically very effective for Adative Gaussian Mixture Model-based object detection of intelligent visual surveillance applications, which is verified through experiments.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.196-204
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• 2017

Behavior of intelligent video surveillance system is recognized by analyzing the pattern of the object of interest by using the frame information of video inputted from the camera and analyzes the behavior. Detection of object's certain behaviors in the crowd has become a critical problem because in the event of terror strikes. Recognition of object's certain behaviors is an important but difficult problem in the area of computer vision. As the realization of big data utilizing machine learning, data mining techniques, the amount of video through the CCTV, Smart-phone and Drone's video has increased dramatically. In this paper, we propose a multiple-sliding window method to recognize the cumulative change as one piece in order to improve the accuracy of the recognition. The experimental results demonstrated the method was robust and efficient learning units in the classification of certain behaviors.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.7
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• pp.70-82
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• 1993

In this paper, employing the 3-dimensional discrete cosine transform (DCT) for the utilization of the temporal correlation, an adaptive motion sequence coding technique is proposed. The energy distribution in a 3-D DCT block, due to the nonstationary nature of the image data, varies along the veritical, horizontal and temporal directions. Thus, aiming an adaptive system to local variations, adaptive procedures, such as the 3-D classification, the classified linear scanning technique and the VLC table selection scheme, have been implemented in our approach. Also, a hybrid structure which adaptively combines inter-frame coding is presented, and it is found that the adaptive hybrid frame coding technique shows a significant performance gain for a moving sequence which contains a relatively small moving area. Through an intensive computer simulation, it is demonstrated that, the performance of the proposed 3-D transform coding technique shows a close relation with the temporal variation of the sequence to be code. And the proposed technique has the advantages of skipping the computationally complex motion compensation procedure and improving the performance over the 2-D motion compensated transform coding technique for rates in the range of 0.5 ~ 1.0 bpp.