• Title/Summary/Keyword: adaptive background

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Effects of different day length and wind conditions to the seedling growth performance of Phragmites australis

  • Hong, Mun Gi;Nam, Bo Eun;Kim, Jae Geun
    • Journal of Ecology and Environment
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    • v.45 no.2
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    • pp.78-87
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    • 2021
  • Background: To understand shade and wind effects on seedling traits of common reed (Phragmites australis), we conducted a mesocosm experiment manipulating day length (10 h daytime a day as open canopy conditions or 6 h daytime a day as partially closed canopy conditions) and wind speed (0 m/s as windless conditions or 4 m/s as windy conditions). Results: Most values of functional traits of leaf blades, culms, and biomass production of P. australis were higher under long day length. In particular, we found sole positive effects of long day length in several functional traits such as internode and leaf blade lengths and the values of above-ground dry weight (DW), rhizome DW, and total DW. Wind-induced effects on functional traits were different depending on functional traits. Wind contributed to relatively low values of chlorophyll contents, angles between leaf blades, mean culm height, and maximum culm height. In contrast, wind contributed to relatively high values of culm density and below-ground DW. Conclusions: Although wind appeared to inhibit the vertical growth of P. australis through physiological and morphological changes in leaf blades, it seemed that P. australis might compensate the inhibited vertical growth with increased horizontal growth such as more numerous culms, indicating a highly adaptive characteristic of P. australis in terms of phenotypic plasticity under windy environments.

A Robust Staff Line Height and Staff Line Space Estimation for the Preprocessing of Music Score Recognition (악보인식 전처리를 위한 강건한 오선 두께와 간격 추정 방법)

  • Na, In-Seop;Kim, Soo-Hyung;Nquyen, Trung Quy
    • Journal of Internet Computing and Services
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    • v.16 no.1
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    • pp.29-37
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    • 2015
  • In this paper, we propose a robust pre-processing module for camera-based Optical Music Score Recognition (OMR) on mobile device. The captured images likely suffer for recognition from many distortions such as illumination, blur, low resolution, etc. Especially, the complex background music sheets recognition are difficult. Through any symbol recognition system, the staff line height and staff line space are used many times and have a big impact on recognition module. A robust and accurate staff line height and staff line space are essential. Some staff line height and staff line space are proposed for binary image. But in case of complex background music sheet image, the binarization results from common binarization algorithm are not satisfactory. It can cause incorrect staff line height and staff line space estimation. We propose a robust staff line height and staff line space estimation by using run-length encoding technique on edge image. Proposed method is composed of two steps, first step, we conducted the staff line height and staff line space estimation based on edge image using by Sobel operator on image blocks. Each column of edge image is encoded by run-length encoding algorithm Second step, we detect the staff line using by Stable Path algorithm and removal the staff line using by adaptive Line Track Height algorithm which is to track the staff lines positions. The result has shown that robust and accurate estimation is possible even in complex background cases.

The effect of Meister high school students' career maturity with respect to the impact on school maladjustment (마이스터고등학교 학생들의 진로성숙도가 학교 부적응에 미치는 영향)

  • Yoo, Jae-Man;Lee, Byung-Wook
    • 대한공업교육학회지
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    • v.41 no.2
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    • pp.1-23
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    • 2016
  • This study was conducted to analyze the effect Meister high school students' career maturity with respect to the impact on school maladjustment. Also, this study clarify the relationship. This study purpose is to permanently provide Meister as the basis for the vocational education sector career education needed to faithfully serve as a special purpose high schools. Tools used for the survey is maladaptive measurement tools developed by Leegyumi (2004) and Career maturity measurement tools developed at Korea Research Institute for Vocational Education and Training (2012). Using these tools, a reliability test was conducted. Meister students' career maturity was conducted correlation analysis and multiple regression analysis to analyze the impact of school maladjustment. Independent variables are consisted of career maturity and independence, attitude toward the job, planning, self-understanding, rational decision-making, information retrieval, knowledge of the desired job, career exploration and ready for action. Meister high school student's career maturity according to the students' background variables are little girls was higher than boys, but it was not statistically significant. T-test was conducted to ascertain the career maturity and school maladjustment differences of adaptation groups and maladaptive group in meister school students in background variables. A career maturity and school maladjustment between adaptive and maladaptive population groups showed a statistically significant difference in background variables.

Fast Detection of Finger-vein Region for Finger-vein Recognition (지정맥 인식을 위한 고속 지정맥 영역 추출 방법)

  • Kim, Sung-Min;Park, Kang-Roung;Park, Dong-Kwon;Won, Chee-Sun
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.1
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    • pp.23-31
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    • 2009
  • Recently, biometric techniques such as face recognition, finger-print recognition and iris recognition have been widely applied for various applications including door access control, finance security and electric passport. This paper presents the method of using finger-vein pattern for the personal identification. In general, when the finger-vein image is acquired from the camera, various conditions such as the penetrating amount of the infrared light and the camera noise make the segmentation of the vein from the background difficult. This in turn affects the system performance of personal identification. To solve this problem, we propose the novel and fast method for extracting the finger-vein region. The proposed method has two advantages compared to the previous methods. One is that we adopt a locally adaptive thresholding method for the binarization of acquired finger-vein image. Another advantage is that the simple morphological opening and closing are used to remove the segmentation noise to finally obtain the finger-vein region from the skeletonization. Experimental results showed that our proposed method could quickly and exactly extract the finger-vein region without using various kinds of time-consuming filters for preprocessing.

Contour Extraction Method using p-Snake with Prototype Energy (원형에너지가 추가된 p-Snake를 이용한 윤곽선 추출 기법)

  • Oh, Seung-Taek;Jun, Byung-Hwan
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.4
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    • pp.101-109
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    • 2014
  • It is an essential element for the establishment of image processing related systems to find the exact contour from the image of an arbitrary object. In particular, if a vision system is established to inspect the products in the automated production process, it is very important to detect the contours for standardized shapes such lines and curves. In this paper, we propose a prototype adaptive dynamic contour model, p-Snake with improved contour extraction algorithms by adding the prototype energy. The proposed method is to find the initial contour by applying the existing Snake algorithm after Sobel operation is performed for prototype analysis. Next, the final contour of the object is detected by analyzing prototypes such as lines and circles, defining prototype energy and using it as an additional energy item in the existing Snake function on the basis of information on initial contour. We performed experiments on 340 images obtained by using an environment that duplicated the background of an industrial site. It was found that even if objects are not clearly distinguished from the background due to noise and lighting or the edges being insufficiently visible in the images, the contour can be extracted. In addition, in the case of similarity which is the measure representing how much it matches the prototype, the prototype similarity of contour extracted from the proposed p-ACM is superior to that of ACM by 9.85%.

Validation of Deep-Learning Image Reconstruction for Low-Dose Chest Computed Tomography Scan: Emphasis on Image Quality and Noise

  • Joo Hee Kim;Hyun Jung Yoon;Eunju Lee;Injoong Kim;Yoon Ki Cha;So Hyeon Bak
    • Korean Journal of Radiology
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    • v.22 no.1
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    • pp.131-138
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    • 2021
  • Objective: Iterative reconstruction degrades image quality. Thus, further advances in image reconstruction are necessary to overcome some limitations of this technique in low-dose computed tomography (LDCT) scan of the chest. Deep-learning image reconstruction (DLIR) is a new method used to reduce dose while maintaining image quality. The purposes of this study was to evaluate image quality and noise of LDCT scan images reconstructed with DLIR and compare with those of images reconstructed with the adaptive statistical iterative reconstruction-Veo at a level of 30% (ASiR-V 30%). Materials and Methods: This retrospective study included 58 patients who underwent LDCT scan for lung cancer screening. Datasets were reconstructed with ASiR-V 30% and DLIR at medium and high levels (DLIR-M and DLIR-H, respectively). The objective image signal and noise, which represented mean attenuation value and standard deviation in Hounsfield units for the lungs, mediastinum, liver, and background air, and subjective image contrast, image noise, and conspicuity of structures were evaluated. The differences between CT scan images subjected to ASiR-V 30%, DLIR-M, and DLIR-H were evaluated. Results: Based on the objective analysis, the image signals did not significantly differ among ASiR-V 30%, DLIR-M, and DLIR-H (p = 0.949, 0.737, 0.366, and 0.358 in the lungs, mediastinum, liver, and background air, respectively). However, the noise was significantly lower in DLIR-M and DLIR-H than in ASiR-V 30% (all p < 0.001). DLIR had higher signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) than ASiR-V 30% (p = 0.027, < 0.001, and < 0.001 in the SNR of the lungs, mediastinum, and liver, respectively; all p < 0.001 in the CNR). According to the subjective analysis, DLIR had higher image contrast and lower image noise than ASiR-V 30% (all p < 0.001). DLIR was superior to ASiR-V 30% in identifying the pulmonary arteries and veins, trachea and bronchi, lymph nodes, and pleura and pericardium (all p < 0.001). Conclusion: DLIR significantly reduced the image noise in chest LDCT scan images compared with ASiR-V 30% while maintaining superior image quality.

Opto-Digital Implementation of Convergence-Controlled Stereo Target Tracking System (주시각이 제어된 스테레오 물체추적 시스템의 광-디지털적 구현)

  • 고정환;이재수;김은수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.4B
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    • pp.353-364
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    • 2002
  • In this paper, a new onto-digital stereo object-tracking system using hierarchical digital algorithms and optical BPEJTC is proposed. This proposed system can adaptively track a moving target by controlling the convergence of stereo camera. firstly, the target is detected through the background matching of the sequential input images by using optical BPEJTC and then the target area is segmented by using the target projection mask which is composed by hierarchical digital processing of image subtraction, logical operation and morphological filtering. Secondly, the location's coordinate of the moving target object for each of the sequential input frames can be extracted through carrying out optical BPEJTC between the reference image of the target region mask and the stereo input image. Finally, the convergence and pan/tilt of stereo camera can be sequentially controlled by using these target coordinate values and the target can be kept in tracking. Also, a possibility of real-time implementation of the adaptive stereo object tracking system is suggested through optically implementing the proposed target extraction and convergence control algorithms.

Driving Performance Evaluation Using Bio-signals from the Prefrontal Lobe in the Driving Simulator

  • Kim, Young-Hyun;Kim, Yong-Chul
    • Journal of the Ergonomics Society of Korea
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    • v.31 no.2
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    • pp.319-325
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    • 2012
  • Objective: The aim of this study was to develop the assistive device for accelerator and brake pedals using bio-signals from the prefrontal lobe in the driving simulator and evaluate its performance. Background: There is lack of assistive devices for the driving in peoples with disabilities in Korea. However, if bio-signals and/or brain waves are used at driving a car, the people with serious physical limitations can improve their community mobility. Method: 15 subjects with driver's license participated in this study for experiment of driving performance evaluation in the simulator. Each subject drove the simulator the same course 10 times in three separated groups which use different interface controllers to accelerate and brake: (1) conventional pedal group, (2) joystick group and (3) bio-signal group(horizontal quick glance of the eyes and clench teeth). All experiments were recorded and the driving performances were evaluated by three inspectors. Results: Average score of bio-signal group for the driving in the simulator was increased 3% compared with the pedal group and was increased 9% compared with the joystick group(p<0.01). The subjects using bio-signals was decreased 44% in number of deduction compared with others because the device had the built-in modified cruise control. Conclusion: The assistive device for accelerator and brake pedals using bio-signals showed significantly better performance than using general pedal and a joystick interface(p<0.01). Application: This study can be used to design adaptive vehicle for driving in people with disabilities.

Object Detection and Tracking using Bayesian Classifier in Surveillance (서베일런스에서 베이지안 분류기를 이용한 객체 검출 및 추적)

  • Kang, Sung-Kwan;Choi, Kyong-Ho;Chung, Kyung-Yong;Lee, Jung-Hyun
    • Journal of Digital Convergence
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    • v.10 no.6
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    • pp.297-302
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    • 2012
  • In this paper, we present a object detection and tracking method based on image context analysis. It is robust from the image variations such as complicated background, dynamic movement of the object. Image context analysis is carried out using the hybrid network of k-means and RBF. The proposed object detection employs context-driven adaptive Bayesian framework to relive the effect due to uneven object images. The proposed method used feature vector generator using 2D Haar wavelet transform and the Bayesian discriminant method in order to enhance the speed of learning. The system took less time to learn, and learning in a wide variety of data showed consistent results. After we developed the proposed method was applied to real-world environment. As a result, in the case of the object to detect pass outside expected area or other changes in the uncertain reaction showed that stable. The experimental results show that the proposed approach can achieve superior performance using various data sets to previously methods.

Individual Instruction and CAI on Open Education (열린교육에서의 개별화수업과 CAI)

  • Lee, Jae-In;Sim, Jung-Young
    • Journal of The Korean Association of Information Education
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    • v.1 no.1
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    • pp.62-73
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    • 1997
  • Open education can be defined as education which apply rule of respect, rule of freedom, rule of individual instruction, and rule of environment. The purpose of this study was to look into the present condition of individual instruction, to find the problems of instruction, especially ill practical arts, and then to suggest the improvement plans on the problems. In order to solve the problems, after briefly reviewing theoretical background of open education, we suggested a CAI(Computer Assisted Instruction) program which was made by Chinju National University of Education and KEDI(Korean Educational Development Institute). And then we applied the program to the classes of the 4th grade of elementary school. In this thesis, we didn't analyze the result of the questionnaire or interview, however, it is believed that using CAI program is a adaptive lesson method of individual instruction.

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