• Title/Summary/Keyword: Processing speed

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Comparative Study on the Methodology of Motor Vehicle Emission Calculation by Using Real-Time Traffic Volume in the Kangnam-Gu (자동차 대기오염물질 산정 방법론 설정에 관한 비교 연구 (강남구의 실시간 교통량 자료를 이용하여))

  • 박성규;김신도;이영인
    • Journal of Korean Society of Transportation
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    • v.19 no.4
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    • pp.35-47
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    • 2001
  • Traffic represents one of the largest sources of primary air pollutants in urban area. As a consequence. numerous abatement strategies are being pursued to decrease the ambient concentration of pollutants. A characteristic of most of the these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emission inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for vehicle types. The majority of inventories are compiled using passive data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. The study of current trends are towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this study, a methodology of motor vehicle emission calculation by using real-time traffic data was studied. A methodology for estimating emissions of CO at a test area in Seoul. Traffic data, which are required on a street-by-street basis, is obtained from induction loops of traffic control system. It was calculated speed-related mass of CO emission from traffic tail pipe of data from traffic system, and parameters are considered, volume, composition, average velocity, link length. And, the result was compared with that of a method of emission calculation by VKT(Vehicle Kilometer Travelled) of vehicles of category.

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Local Shape Analysis of the Hippocampus using Hierarchical Level-of-Detail Representations (계층적 Level-of-Detail 표현을 이용한 해마의 국부적인 형상 분석)

  • Kim Jeong-Sik;Choi Soo-Mi;Choi Yoo-Ju;Kim Myoung-Hee
    • The KIPS Transactions:PartA
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    • v.11A no.7 s.91
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    • pp.555-562
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    • 2004
  • Both global volume reduction and local shape changes of hippocampus within the brain indicate their abnormal neurological states. Hippocampal shape analysis consists of two main steps. First, construct a hippocampal shape representation model ; second, compute a shape similarity from this representation. This paper proposes a novel method for the analysis of hippocampal shape using integrated Octree-based representation, containing meshes, voxels, and skeletons. First of all, we create multi-level meshes by applying the Marching Cube algorithm to the hippocampal region segmented from MR images. This model is converted to intermediate binary voxel representation. And we extract the 3D skeleton from these voxels using the slice-based skeletonization method. Then, in order to acquire multiresolutional shape representation, we store hierarchically the meshes, voxels, skeletons comprised in nodes of the Octree, and we extract the sample meshes using the ray-tracing based mesh sampling technique. Finally, as a similarity measure between the shapes, we compute $L_2$ Norm and Hausdorff distance for each sam-pled mesh pair by shooting the rays fired from the extracted skeleton. As we use a mouse picking interface for analyzing a local shape inter-actively, we provide an interaction and multiresolution based analysis for the local shape changes. In this paper, our experiment shows that our approach is robust to the rotation and the scale, especially effective to discriminate the changes between local shapes of hippocampus and more-over to increase the speed of analysis without degrading accuracy by using a hierarchical level-of-detail approach.

Analysis of Prevalence and Survival pattern of Staphylococcus aureus from Dried Seasoned Fishes (조미건어포의 Staphylococcus aureus 오염도 및 생존패턴 분석)

  • Cho, Joon-Il;Lee, Soon-Ho;Choi, Jun-Hyuk;Choi, Eun-Jung;Hwang, In-Gyun
    • Journal of Food Hygiene and Safety
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    • v.26 no.4
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    • pp.366-369
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    • 2011
  • In this study, the contamination levels of total aerobic bacteria, E. coli, total coliform and S. aureus of seasoned dried fishes (SDF) in Korea were investigated. A total of 81 SDF samples were purchased randomly from 28 stores. Contamination range of total aerobic bacteria, total coliform and S. aureus were 150~1,700,000, 10~31,000 and 10~220 CFU/g, respectively. E. coli was detected in only one samples in the qualitative test. We have analyzed quantitatively Staphylococcal enterotoxins (SE-type A, C and D) produced by S. aureus contaminated in SDF using a TECRA kit and standard curve. The curve equation was Y = 0.1499 * X + 0.1183 and maximum amount of SEs in SDF was 0.71 ng/ml. Reduction speed of S. aureus in SDF stored at $37^{\circ}C$ was the highest among the samples stored for 8 days at different temperature of 7, 18 and $37^{\circ}C$. On the basis of the results, SDF in Korea can be contaminated by a variety of pathogenic bacteria. Therefore, precautionary measures are necessary for consumer protection, including the improvement of sanitary conditions in the processing plants in Korea.

The Validity and Reliability of 'Computerized Neurocognitive Function Test' in the Elementary School Child (학령기 정상아동에서 '전산화 신경인지기능검사'의 타당도 및 신뢰도 분석)

  • Lee, Jong-Bum;Kim, Jin-Sung;Seo, Wan-Seok;Shin, Hyoun-Jin;Bai, Dai-Seg;Lee, Hye-Lin
    • Korean Journal of Psychosomatic Medicine
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    • v.11 no.2
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    • pp.97-117
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    • 2003
  • Objective: This study is to examine the validity and reliability of Computerized Neurocognitive Function Test among normal children in elementary school. Methods: K-ABC, K-PIC, and Computerized Neurocognitive Function Test were performed to the 120 body of normal children(10 of each male and female) from June, 2002 to January, 2003. Those children had over the average of intelligence and passed the rule out criteria. To verify test-retest reliability for those 30 children who were randomly selected, Computerized Neurocognitive Function Test was carried out again 4 weeks later. Results: As a results of correlation analysis for validity test, four of continues performance tests matched with those on adults. In the memory tests, results presented the same as previous research with a difference between forward test and backward test in short-term memory. In higher cognitive function tests, tests were consist of those with different purpose respectively. After performing factor analysis on 43 variables out of 12 tests, 10 factors were raised and the total percent of variance was 75.5%. The reasons were such as: 'sustained attention, information processing speed, vigilance, verbal learning, allocation of attention and concept formation, flexibility, concept formation, visual learning, short-term memory, and selective attention' in order. In correlation with K-ABC to prepare explanatory criteria, selectively significant correlation(p<.0.5-001) was found in subscale of K-ABC. In the test-retest reliability test, the results reflecting practice effect were found and prominent especially in higher cognitive function tests. However, split-half reliability(r=0.548-0.7726, p<.05) and internal consistency(0.628-0.878, p<.05) of each examined group were significantly high. Conclusion: The performance of Computerized Neurocognitive Function Test in normal children represented differ developmental character than that in adult. And basal information for preparing the explanatory criteria could be acquired by searching for the relation with standardized intelligence test which contains neuropsycological background.

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Formation of Enzyme Resistant Starch by Extrusion Cooking of High Amylose Corn Starch (고아밀로즈 옥수수전분의 압출성형에 의한 난소화성화)

  • Kim, Ji-Yong;Lee, Cherl-Ho
    • Korean Journal of Food Science and Technology
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    • v.30 no.5
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    • pp.1128-1133
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    • 1998
  • Extrusion cooking treatment was compared with autoclaving/cooling treatment for formation of enzyme resistant starch of high amylose corn starch (HACS). Effects of barrel temperature $(100^{\circ}C,\;120^{\circ}C,\;140^{\circ}C)$ and feed moisture content (25%, 35%, 45%) on extrusion processing in a co-rotating twin-screw extruder under fixed screw speed (100 rpm) were investigated by measuring enzyme resistant starch (RS) yield. RS yield were estimated by in-vitro pancreatin digestion method and enzymatic-gravimetric method using termamyl. Barrel temperature and yield of RS were negatively correlated and feed moisture content and yield of RS was positively correlated as determined by in-vitro pancreatin method. The highest yield (38.4%) of RS was obtained from HACS extrudate processed at the barrel temperature of $100^{\circ}C$ and the feed moisture content of 45%, while the yield of RS by 5 times of autoclaving/cooling was 25%. The yield of RS by in vitro pancreatin digestion method was 20.7% with high amylose corn starch and 8.2% with ordinary corn starch (CS), respectively, under the same extrusion condition (barrel temperature $120^{\circ}C$, feed moisture content 35%). At the same condition, the yields of RS by enzyme-gravimetric method were 14.6% with HACS and 6.8% with CS, respectively. The yield of RS increased during the storage at $4^{\circ}C$ for 4 weeks and the highest yield (60%) was obtained by the storage of HACS extrudates extruded at $100^{\circ}C$ and 45% feed moisture content.

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Design and Implementation of Content-based Video Database using an Integrated Video Indexing Method (통합된 비디오 인덱싱 방법을 이용한 내용기반 비디오 데이타베이스의 설계 및 구현)

  • Lee, Tae-Dong;Kim, Min-Koo
    • Journal of KIISE:Computing Practices and Letters
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    • v.7 no.6
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    • pp.661-683
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    • 2001
  • There is a rapid increase in the use of digital video information in recent years, it becomes more important to manage video databases efficiently. The development of high speed data network and digital techniques has emerged new multimedia applications such as internet broadcasting, Video On Demand(VOD) combined with video data processing and computer. Video database should be construct for searching fast, efficient video be extract the accurate feature information of video with more massive and more complex characteristics. Video database are essential differences between video databases and traditional databases. These differences lead to interesting new issues in searching of video, data modeling. So, cause us to consider new generation method of database, efficient retrieval method of video. In this paper, We propose the construction and generation method of the video database based on contents which is able to accumulate the meaningful structure of video and the prior production information. And by the proposed the construction and generation method of the video database implemented the video database which can produce the new contents for the internet broadcasting centralized on the video database. For this production, We proposed the video indexing method which integrates the annotation-based retrieval and the content-based retrieval in order to extract and retrieval the feature information of the video data using the relationship between the meaningful structure and the prior production information on the process of the video parsing and extracting the representative key frame. We can improve the performance of the video contents retrieval, because the integrated video indexing method is using the content-based metadata type represented in the low level of video and the annotation-based metadata type impressed in the high level which is difficult to extract the feature information of the video at he same time.

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A Road Luminance Measurement Application based on Android (안드로이드 기반의 도로 밝기 측정 어플리케이션 구현)

  • Choi, Young-Hwan;Kim, Hongrae;Hong, Min
    • Journal of Internet Computing and Services
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    • v.16 no.2
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    • pp.49-55
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    • 2015
  • According to the statistics of traffic accidents over recent 5 years, traffic accidents during the night times happened more than the day times. There are various causes to occur traffic accidents and the one of the major causes is inappropriate or missing street lights that make driver's sight confused and causes the traffic accidents. In this paper, with smartphones, we designed and implemented a lane luminance measurement application which stores the information of driver's location, driving, and lane luminance into database in real time to figure out the inappropriate street light facilities and the area that does not have any street lights. This application is implemented under Native C/C++ environment using android NDK and it improves the operation speed than code written in Java or other languages. To measure the luminance of road, the input image with RGB color space is converted to image with YCbCr color space and Y value returns the luminance of road. The application detects the road lane and calculates the road lane luminance into the database sever. Also this application receives the road video image using smart phone's camera and improves the computational cost by allocating the ROI(Region of interest) of input images. The ROI of image is converted to Grayscale image and then applied the canny edge detector to extract the outline of lanes. After that, we applied hough line transform method to achieve the candidated lane group. The both sides of lane is selected by lane detection algorithm that utilizes the gradient of candidated lanes. When the both lanes of road are detected, we set up a triangle area with a height 20 pixels down from intersection of lanes and the luminance of road is estimated from this triangle area. Y value is calculated from the extracted each R, G, B value of pixels in the triangle. The average Y value of pixels is ranged between from 0 to 100 value to inform a luminance of road and each pixel values are represented with color between black and green. We store car location using smartphone's GPS sensor into the database server after analyzing the road lane video image with luminance of road about 60 meters ahead by wireless communication every 10 minutes. We expect that those collected road luminance information can warn drivers about safe driving or effectively improve the renovation plans of road luminance management.

An Implementation Method of the Character Recognizer for the Sorting Rate Improvement of an Automatic Postal Envelope Sorting Machine (우편물 자동구분기의 구분율 향상을 위한 문자인식기의 구현 방법)

  • Lim, Kil-Taek;Jeong, Seon-Hwa;Jang, Seung-Ick;Kim, Ho-Yon
    • Journal of Korea Society of Industrial Information Systems
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    • v.12 no.4
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    • pp.15-24
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    • 2007
  • The recognition of postal address images is indispensable for the automatic sorting of postal envelopes. The process of the address image recognition is composed of three steps-address image preprocessing, character recognition, address interpretation. The extracted character images from the preprocessing step are forwarded to the character recognition step, in which multiple candidate characters with reliability scores are obtained for each character image extracted. aracters with reliability scores are obtained for each character image extracted. Utilizing those character candidates with scores, we obtain the final valid address for the input envelope image through the address interpretation step. The envelope sorting rate depends on the performance of all three steps, among which character recognition step could be said to be very important. The good character recognizer would be the one which could produce valid candidates with very reliable scores to help the address interpretation step go easy. In this paper, we propose the method of generating character candidates with reliable recognition scores. We utilize the existing MLP(multilayered perceptrons) neural network of the address recognition system in the current automatic postal envelope sorters, as the classifier for the each image from the preprocessing step. The MLP is well known to be one of the best classifiers in terms of processing speed and recognition rate. The false alarm problem, however, might be occurred in recognition results, which made the address interpretation hard. To make address interpretation easy and improve the envelope sorting rate, we propose promising methods to reestimate the recognition score (confidence) of the existing MLP classifier: the generation method of the statistical recognition properties of the classifier and the method of the combination of the MLP and the subspace classifier which roles as a reestimator of the confidence. To confirm the superiority of the proposed method, we have used the character images of the real postal envelopes from the sorters in the post office. The experimental results show that the proposed method produces high reliability in terms of error and rejection for individual characters and non-characters.

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A Real-Time Head Tracking Algorithm Using Mean-Shift Color Convergence and Shape Based Refinement (Mean-Shift의 색 수렴성과 모양 기반의 재조정을 이용한 실시간 머리 추적 알고리즘)

  • Jeong Dong-Gil;Kang Dong-Goo;Yang Yu Kyung;Ra Jong Beom
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.6
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    • pp.1-8
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    • 2005
  • In this paper, we propose a two-stage head tracking algorithm adequate for real-time active camera system having pan-tilt-zoom functions. In the color convergence stage, we first assume that the shape of a head is an ellipse and its model color histogram is acquired in advance. Then, the min-shift method is applied to roughly estimate a target position by examining the histogram similarity of the model and a candidate ellipse. To reflect the temporal change of object color and enhance the reliability of mean-shift based tracking, the target histogram obtained in the previous frame is considered to update the model histogram. In the updating process, to alleviate error-accumulation due to outliers in the target ellipse of the previous frame, the target histogram in the previous frame is obtained within an ellipse adaptively shrunken on the basis of the model histogram. In addition, to enhance tracking reliability further, we set the initial position closer to the true position by compensating the global motion, which is rapidly estimated on the basis of two 1-D projection datasets. In the subsequent stage, we refine the position and size of the ellipse obtained in the first stage by using shape information. Here, we define a robust shape-similarity function based on the gradient direction. Extensive experimental results proved that the proposed algorithm performs head hacking well, even when a person moves fast, the head size changes drastically, or the background has many clusters and distracting colors. Also, the propose algorithm can perform tracking with the processing speed of about 30 fps on a standard PC.

Enhanced Production of Carboxymethylcellulase by a Newly Isolated Marine Microorganism Bacillus atrophaeus LBH-18 Using Rice Bran, a Byproduct from the Rice Processing Industry (미강을 이용한 해양미생물 Bacillus atrophaeus LBH-18 유래의 carboxymethylcellulase 생산의 최적화)

  • Kim, Yi-Joon;Cao, Wa;Lee, Yu-Jeong;Lee, Sang-Un;Jeong, Jeong-Han;Lee, Jin-Woo
    • Journal of Life Science
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    • v.22 no.10
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    • pp.1295-1306
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    • 2012
  • A microorganism producing carboxymethylcellulase (CMCase) was isolated from seawater and identified as Bacillus atrophaeus. This species was designated as B. atrophaeus LBH-18 based on its evolutionary distance and the phylogenetic tree resulting from 16S rDNA sequencing and the neighbor-joining method. The optimal conditions for rice bran (68.1 g/l), peptone (9.1 g/l), and initial pH (7.0) of the medium for cell growth was determined by Design Expert Software based on the response surface method; conditions for production of CMCase were 55.2 g/l, 6.6 g/l, and 7.1, respectively. The optimal temperature for cell growth and the production of CMCase by B. atrophaeus LBH-18 was $30^{\circ}C$. The optimal conditions of agitation speed and aeration rate for cell growth in a 7-l bioreactor were 324 rpm and 0.9 vvm, respectively, whereas those for production of CMCase were 343 rpm and 0.6 vvm, respectively. The optimal inner pressure for cell growth and production of CMCase in a 100-l bioreactor was 0.06 MPa. Maximal production of CMCase under optimal conditions in a 100-l bioreactor was 127.5 U/ml, which was 1.32 times higher than that without an inner pressure. In this study, rice bran was developed as a carbon source for industrial scale production of CMCase by B. atrophaeus LBH-18. Reduced time for the production of CMCase from 7 to 10 days to 3 days by using a bacterial strain with submerged fermentation also resulted in increased productivity of CMCase and a decrease in its production cost.