• Title/Summary/Keyword: Regions of Interest

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CpG Islands Detector: a Window-based CpG Island Search Tool

  • Kim, Ki-Bong
    • Genomics & Informatics
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    • v.8 no.1
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    • pp.58-61
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    • 2010
  • CpG is the pair of nucleotides C and G, appearing successively, in this order, along one DNA strand. It is known that due to biochemical considerations CpG is relatively rare in most DNA sequences. However, in particular subsequences, which are a few hundred to a few thousand nucleotides long, the couple CpG is more frequent. These subsequences, called CpG islands, are known to appear in biologically more significant parts of the genome. The ability to identify CpG islands along a chromosome will therefore help us spot its more significant regions of interest, such as the promoters or 'start' regions of many genes. In this respect, I developed the CpG islands search tool, CpG Islands Detector, which was implemented in JAVA to be run on any platform. The window-based graphical user interface of CpG Islands Detector may facilitate the end user to employ this tool to pinpoint CpG islands in a genomic DNA sequence. In addition, this tool can be used to highlight potential genes in genomic sequences since CpG islands are very often found in the 5' regions of vertebrate genes.

Forest Fire Detection and Identification Using Image Processing and SVM

  • Mahmoud, Mubarak Adam Ishag;Ren, Honge
    • Journal of Information Processing Systems
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    • v.15 no.1
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    • pp.159-168
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    • 2019
  • Accurate forest fires detection algorithms remain a challenging issue, because, some of the objects have the same features with fire, which may result in high false alarms rate. This paper presents a new video-based, image processing forest fires detection method, which consists of four stages. First, a background-subtraction algorithm is applied to detect moving regions. Secondly, candidate fire regions are determined using CIE $L{\ast}a{\ast}b{\ast}$ color space. Thirdly, special wavelet analysis is used to differentiate between actual fire and fire-like objects, because candidate regions may contain moving fire-like objects. Finally, support vector machine is used to classify the region of interest to either real fire or non-fire. The final experimental results verify that the proposed method effectively identifies the forest fires.

Multi-Level Segmentation of Infrared Images with Region of Interest Extraction

  • Yeom, Seokwon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.4
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    • pp.246-253
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    • 2016
  • Infrared (IR) imaging has been researched for various applications such as surveillance. IR radiation has the capability to detect thermal characteristics of objects under low-light conditions. However, automatic segmentation for finding the object of interest would be challenging since the IR detector often provides the low spatial and contrast resolution image without color and texture information. Another hindrance is that the image can be degraded by noise and clutters. This paper proposes multi-level segmentation for extracting regions of interest (ROIs) and objects of interest (OOIs) in the IR scene. Each level of the multi-level segmentation is composed of a k-means clustering algorithm, an expectation-maximization (EM) algorithm, and a decision process. The k-means clustering initializes the parameters of the Gaussian mixture model (GMM), and the EM algorithm estimates those parameters iteratively. During the multi-level segmentation, the area extracted at one level becomes the input to the next level segmentation. Thus, the segmentation is consecutively performed narrowing the area to be processed. The foreground objects are individually extracted from the final ROI windows. In the experiments, the effectiveness of the proposed method is demonstrated using several IR images, in which human subjects are captured at a long distance. The average probability of error is shown to be lower than that obtained from other conventional methods such as Gonzalez, Otsu, k-means, and EM methods.

An Analysis on Regional Ripple Effects of the Sale and Chenosei Prices of the Apartments: A GVAR Approach (아파트 매매가격 및 전세가격의 지역별 파급효과: GVAR 모형 접근법)

  • Yoon, Jai-Hyung
    • Asia-Pacific Journal of Business
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    • v.13 no.3
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    • pp.343-359
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    • 2022
  • We analyze the regional ripple effects of both the sale prices and cheonsei prices using the global VAR(GVAR) model. The interest rate shock causes the regional sale prices to fall. Moreover, the greatest responses to the shock are those of Gangnam-gu, etc. because of there were many transactions for investment purpose. When interest rate rose, the cheonsei price in Gangnam-gu reacted greatly. Conversely, if interest rates fall, the cheonsei demand to live in Gangnam-gu increases. Furthermore, the response of sale price to the interest rate shock are greater than those of the cheonsei prices. Whereas, a positive shock on the sale price in Gangnam-gu increases the sale price there. It also raises the sale prices of the surrounding area in a similar pattern. The shock on the sale price in Gangnam-gu also increases the cheonsei price in Gangnam-gu. In addition, an increase in the sale price in Gangnam-gu leads to increases of cheonsei prices in other regions. Therefore, the recent rise of the base rate can negatively affect the sale prices, and thus a decrease in the sale price spreads to the surrounding areas. Accordingly, it is time for policy alternatives to make a soft landing in sale prices.

Detection of Microcalcifications ROI in Digital Mammograms using Linear Filters (디지털 마모그램에서 선형 필터를 이용한 미소석회질 ROI 검출)

  • 이승상;김기훈;박동선
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.229-232
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    • 2003
  • In this paper, we present an efficient algorithm to detect microcalcifications ROI (Regions of Interest) in digital mammograms using Linear filters. To efficiently detect microcalcifications ROI, we used three sequential processes; preprocessing for breast area detection, modified multilevel thresholding, ROI selection using mean filter and linear filters.

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The Study for Construction of the Improved Optimization Algorithm by the Response Surface Method (반응표면법의 향상된 최적화 알고리즘 구성에 관한 연구)

  • Park, J.S.;Lee, D.J.;Im, J.B.
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.13 no.3
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    • pp.22-33
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    • 2005
  • Response Surface Method (RSM) constructs approximate response surfaces using sample data from experiments or simulations and finds optimum levels of process variables within the fitted response surfaces of the interest region. It will be necessary to get the most suitable response surface for the accuracy of the optimization. The application of RSM plan experimental designs. The RSM is used in the sequential optimization process. The first goal of this study is to improve the plan of central composite designs of experiments with various locations of axial points. The second is to increase the optimal efficiency applying a modified method to update interest regions.

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A Simulation Model of Object Movement for Evaluating the Communication Load in Networked Virtual Environments

  • Lim, Mingyu;Lee, Yunjin
    • Journal of Information Processing Systems
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    • v.9 no.3
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    • pp.489-498
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    • 2013
  • In this paper, we propose a common simulation model that can be reused for different performance evaluations of networked virtual environments. To this end, we analyzed the common features of NVEs, in which multiple regions compose a shared space, and where a user has his/her own interest area. Communication architecture can be client-server or peer-server models. In usual simulations, users move around the world while the number of users varies with the system. Our model provides various simulation parameters to customize the region configuration and user movement pattern. Furthermore, our model introduces a way to mimic a lot of users in a minimal experiment environment. The proposed model is integrated with our network framework, which supports various scalability approaches. We specifically applied our model to the interest management and load distribution schemes to evaluate communication overhead. With the proposed simulation model, a new simulation can be easily designed in a large-scale environment.

An efficient data dissemination scheme for sensor network with multiple target regions (다중 목적지 그룹을 가진 센서 네트워크에서 효율적인 데이터 전송 기법)

  • 오창석;이성희;고영배
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.10c
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    • pp.13-15
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    • 2004
  • 현재의 무선 센서네트워크는 다중 목적지 그룹에 동일한 interest를 전파함에 있어서 목적지 그룹별로 개별적인 interest 전송 경로를 사용한다. 이러한 데이터 전송기법은 동일한 정보를 여러 번에 걸쳐 전송함으로써 네트워크에 불필요한 트래픽을 증가시키고, 에너지 자원이 빈약한 센서네트워크의 네트워크 생명을 감소시키는 원인이 된다. 범용 센서네트워크에서 동일한 interest를 네트워크상의 다중 목적지에 전송하는 경우 공유경로의 사용을 통하여 네트워크 트래픽을 감소시킬 수 있다. 따라서 본 논문에서는 센서노드의 위치 정보를 기반으로 싱크노드로부터 복수개의 목적지 그룹까지 데이터를 전송함에 있어서 공유경로를 사용하여 데이터의 전송 경로를 최적화하는 기법을 제안한다. 제안 방우의 성능번상은 시걸친이해에 의해 불증하필으요, 에러 경로 최대 30%까지 감소하필다.

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3D Segmentation of a Diagnostic Object in Ultrasound Images Using LoG Operator (초음파 영상에서 LoG 연산자를 이용한 진단 객체의 3차원 분할)

  • 정말남;곽종인;김상현;김남철
    • Journal of Biomedical Engineering Research
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    • v.24 no.4
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    • pp.247-257
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    • 2003
  • This paper proposes a three-dimensional (3D) segmentation algorithm for extracting a diagnostic object from ultrasound images by using a LoG operator In the proposed algorithm, 2D cutting planes are first obtained by the equiangular revolution of a cross sectional Plane on a reference axis for a 3D volume data. In each 2D ultrasound image. a region of interest (ROI) box that is included tightly in a diagnostic object of interest is set. Inside the ROI box, a LoG operator, where the value of $\sigma$ is adaptively selected by the distance between reference points and the variance of the 2D image, extracts edges in the 2D image. In Post processing. regions of the edge image are found out by region filling, small regions in the region filled image are removed. and the contour image of the object is obtained by morphological opening finally. a 3D volume of the diagnostic object is rendered from the set of contour images obtained by post-processing. Experimental results for a tumor and gall bladder volume data show that the proposed method yields on average two times reduction in error rate over Krivanek's method when the results obtained manually are used as a reference data.

An Efficient Partial Matching System and Region-based Representation for 2D Images (2D 영상의 효과적인 부분 정합 시스템과 영역기반 영상 표현)

  • Kim, Seon-Jong
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.9
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    • pp.868-874
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    • 2007
  • This paper proposes an efficient partial matching system and representation by using a region-based method for 2D image, and we applied to an extraction of the ROI(Region of Interest) according to its matching score. The matching templates consist of the global pattern and the local one. The global pattern can make it by using region-based relation between center region and its rest regions in an object. And, the local pattern can be obtained appling to the same method as global, except relation between objects. As the templates can be normalized, we use this templates for extraction of ROI with invariant to size and position. And, our system operates only one try to match, due to normalizing of region size. To use our system for searching and examining if it's the ROI by evaluating the matching function, at first, we are searching to find candidate regions with the global template. Then, we try to find the ROI among the candidates, and it works this time by using the local template. We experimented to the binary and the color image respectively, they showed that the proposed system can be used efficiently for representing of the template and the useful applications, such as partially retrievals of 2D image.