• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3C
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• pp.125-132
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• 2005

This paper describes a computer vision system based on active IR illumination for real-time gaze discrimination system. Unlike most of the existing gaze discrimination techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze discrimination system can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using generalized regression neural networks (GRNNs). With GRNNs, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Futhermore, the mapping function can generalize to other individuals not used in the training. To further improve the gaze estimation accuracy, we employ a reclassification scheme that deals with the classes that tend to be misclassified. This leads to a 10% improvement in classification error. The angular gaze accuracy is about 5°horizontally and 8°vertically. The effectiveness of our gaze tracker is demonstrated by experiments that involve gaze-contingent interactive graphic display.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.1
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• pp.38-46
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• 2010

This paper describes a computer vision system based on active IR illumination for real-time gaze discrimination system. Unlike most of the existing gaze discrimination techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze discrimination system can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using generalized regression neural networks (GRNNs). With GRNNs, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Furthermore, the mapping function can generalize to other individuals not used in the training. To further improve the gaze estimation accuracy, we employ a reclassification scheme that deals with the classes that tend to be misclassified. This leads to a 10% improvement in classification error. The angular gaze accuracy is about $5^{\circ}$horizontally and $8^{\circ}$vertically. The effectiveness of our gaze tracker is demonstrated by experiments that involve gaze-contingent interactive graphic display.

• Journal of Korean Society of Disaster and Security
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• v.6 no.3
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• pp.35-42
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• 2013

The purpose of this research is to systematize safety management for practical application through analysis and review of several safety standards currently in force among the statutes and rules regarding various safety accidents. Accordingly, the safety standard systems of Japan, US, and Germany were examined and a KOSAM entity relationship diagram (ERD) was drawn based on the ontology system. The ERD consists of the safety standard scope, safety management statute, safety management standard, safety management subjects, causes of safety accidents, and safety management organization entities. Next, each entity was assigned a code and finally a KOSAM safety management condition search screen was designed based on the ERD. This research is expected to bring an overall improvement in safety standard management and operation through safety standard DB construction and the execution of safety management system development.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.322-329
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• 2005

This paper describes a computer vision system based on active IR illumination for real-time gaze discrimination system. Unlike most of the existing gaze discrimination techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze discrimination system can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using generalized regression neural networks (GRNNS). With GRNNS, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. furthermore, the mapping function can generalize to other individuals not used in the training. To further improve the gaze estimation accuracy, we employ a reclassification scheme that deals with the classes that tend to be misclassified. This leads to a 10$\%$ improvement in classification error. The angular gaze accuracy is about $5^{circ}$horizontally and $8^{circ}$vertically. The effectiveness of our gaze tracker is demonstrated by experiments that involve gaze-contingent interactive graphic display.

• Journal of Animal Science and Technology
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• v.51 no.5
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• pp.427-432
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• 2009

This study was undertaken to screen a high xylanase and mannanase producing microbes. In the first experiment, screening was undertaken against 50 samples of microorganisms having xylanase and mannanase activities from soil and fallen leaves. The screening process has focused on picking out fungi having high xylanase and mannanase activities under the solid-state fermentation. The xylanase and mannanase activities of 6 screened microbes were 0.9~1.6 unit/mL and 0.2~0.4 unit/mL, respectively, under the submerged fermentation condition. However, under the solid-state fermentation, xylanase and mannanase activities were 103.7~220.0 unit/g and 20.1~40.3 unit/g, respectively. Finally one microbe (E-3) was selected and its xylanase and mannanase activities were 197.3 unit/g and 39.9 unit/g, respectively. The morphological and molecular biological classification of E-3 showed 99% homology with the Aspergillus niger.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.7
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• pp.3-12
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• 2004

The need to predict the rate of soil erosion, both under existing conditions and those expected to occur following soil conservation practice, has been led to the development of various models. In this study Morgan model especially developed for field-sized areas on hill slopes was applied to assess the rate of soil erosion using RS/GIS environment in the Dukchun river basin, one of two tributaries flowing into Jinyang lake. In order to run the model, land cover mapping was made by the supervised classification method with Landsat TM satellite image data, the digital soil map was generated from scanning and screen digitizing from the hard copy of soil maps, digital elevation map (DEM) in order to generate the slope map was made by the digital map (DM) produced by National Geographic Information Institute (NGII). Almost all model parameters were generated to the multiple raster data layers, and the map calculation was made by the raster based GIS software, IL WIS which was developed by ITC, the Netherlands. Model results show that the annual soil loss rates are 5.2, 18.4, 30.3, 58.2 and 60.2 ton/ha/year in forest, paddy fields, built-up area, bare soil, and upland fields respectively. The estimated rates seemed to be high under the normal climatic conditions because of exaggerated land slopes due to DEM generation using 100 m contour interval. However, the results were worthwhile to estimate soil loss in hilly areas and the more precise result could be expected when the more accurate slope data is available.

• Korean Journal of Breeding Science
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• v.43 no.2
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• pp.133-138
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• 2011

The groundnut or cultivated peanut (Arachis hypogaea L.) in Korea consists of 36 domestic varieties which have been developed and registered as cultivars for the public during last 25 years. To screen and identify of Korean peanut varieties and genetic resources, we present a simple and reliable method. A methodology based on simple sequence repeat (SSR) markers developed and widely used for prominent gene identification and variety discrimination. For identification of those 36 Korean peanut varieties, 238 unique peanut SSR markers were selected from some previously reported results, synthesized and used for polymerase chain reaction (PCR). Data were taken through acryl amide gel electrophoresis and changed into proper formats for application of data mining analysis using Biomine (all-in-one functional genomics data mining program). Consequently, twelve SSR primers were investigated and revealed the differences between those 36 varieties. These primer pairs amplified 27 alleles with an average of 2.3 allele per primer pair. In addition, those results showed genetic relationship by classification method within 36 varieties. The approach described here could be applied to monitoring of our varieties and adapting to peanut breeding program.

• Journal of Veterinary Science
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• v.23 no.4
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• pp.56.1-56.17
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• 2022

Background: At the therapeutic doses, diclofenac sodium (DFS) has few toxic side effects on mammals. On the other hand, DFS exhibits potent toxicity against birds and the mechanisms remain ambiguous. Objectives: This paper was designed to probe the toxicity of DFS exposure on the hepatic proteome of broiler chickens. Methods: Twenty 30-day-old broiler chickens were randomized evenly into two groups (n = 10). DFS was administered orally at 10mg/kg body weight in group A, while the chickens in group B were perfused with saline as a control. Histopathological observations, serum biochemical examinations, and quantitative real-time polymerase chain reaction were performed to assess the liver injury induced by DFS. Proteomics analysis of the liver samples was conducted using isobaric tags for relative and absolute quantification (iTRAQ) technology. Results: Ultimately, 201 differentially expressed proteins (DEPs) were obtained, of which 47 were up regulated, and 154 were down regulated. The Gene Ontology classification and Kyoto Encyclopedia of Genes and Genomes pathway analysis were conducted to screen target DEPs associated with DFS hepatotoxicity. The regulatory relationships between DEPs and signaling pathways were embodied via a protein-protein interaction network. The results showed that the DEPs enriched in multiple pathways, which might be related to the hepatotoxicity of DFS, were "protein processing in endoplasmic reticulum," "retinol metabolism," and "glycine, serine, and threonine metabolism." Conclusions: The hepatotoxicity of DFS on broiler chickens might be achieved by inducing the apoptosis of hepatocytes and affecting the metabolism of retinol and purine. The present study could provide molecular insights into the hepatotoxicity of DFS on broiler chickens.

• Journal of Animal Science and Technology
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• v.63 no.6
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• pp.1453-1463
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• 2021

Feeding is the most important behavior that represents the health and welfare of weanling pigs. The early detection of feed refusal is crucial for the control of disease in the initial stages and the detection of empty feeders for adding feed in a timely manner. This paper proposes a real-time technique for the detection and recognition of small pigs using a deep-leaning-based method. The proposed model focuses on detecting pigs on a feeder in a feeding position. Conventional methods detect pigs and then classify them into different behavior gestures. In contrast, in the proposed method, these two tasks are combined into a single process to detect only feeding behavior to increase the speed of detection. Considering the significant differences between pig behaviors at different sizes, adaptive adjustments are introduced into a you-only-look-once (YOLO) model, including an angle optimization strategy between the head and body for detecting a head in a feeder. According to experimental results, this method can detect the feeding behavior of pigs and screen non-feeding positions with 95.66%, 94.22%, and 96.56% average precision (AP) at an intersection over union (IoU) threshold of 0.5 for YOLOv3, YOLOv4, and an additional layer and with the proposed activation function, respectively. Drinking behavior was detected with 86.86%, 89.16%, and 86.41% AP at a 0.5 IoU threshold for YOLOv3, YOLOv4, and the proposed activation function, respectively. In terms of detection and classification, the results of our study demonstrate that the proposed method yields higher precision and recall compared to conventional methods.

• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.441-446
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• 2009

This paper proposes an automatic indexing algorithm of golf video using audio information. In the proposed algorithm, the input audio stream is demultiplexed into the stream of video and audio. By means of Adaboost-cascade classifier, the continuous audio stream is classified into announcer's speech segment recorded in studio, music segment accompanied with players' names on TV screen, reaction segment of audience according to the play, reporter's speech segment with field background, filed noise segment like wind or waves. And golf swing sound including drive shot, iron shot, and putting shot is detected by the method of impulse onset detection and modulation spectrum verification. The detected swing and applause are used effectively to index action or highlight unit. Compared with video based semantic analysis, main advantage of the proposed system is its small computation requirement so that it facilitates to apply the technology to embedded consumer electronic devices for fast browsing.