• Title/Summary/Keyword: biological information objects

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The Atom of Evolution

  • Bhak, Jonghwa;Bolser, Dan;Park, Daeui;Cho, Yoobok;Yoo, Kiesuk;Lee, Semin;Gong, SungSam;Jang, Insoo;Park, Changbum;Huston, Maryana;Choi, Hwanho
    • Genomics & Informatics
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    • v.2 no.4
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    • pp.167-173
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    • 2004
  • The main mechanism of evolution is that biological entities change, are selected, and reproduce. We propose a different concept in terms of the main agent or atom of evolution: in the biological world, not an individual object, but its interactive network is the fundamental unit of evolution. The interaction network is composed of interaction pairs of information objects that have order information. This indicates a paradigm shift from 3D biological objects to an abstract network of information entities as the primary agent of evolution. It forces us to change our views about how organisms evolve and therefore the methods we use to analyze evolution.

PROTOTYPE AUTOMATIC SYSTEM FOR CONSTRUCTING 3D INTERIOR AND EXTERIOR IMAGE OF BIOLOGICAL OBJECTS

  • Park, T. H.;H. Hwang;Kim, C. S.
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 2000.11b
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    • pp.318-324
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    • 2000
  • Ultrasonic and magnetic resonance imaging systems are used to visualize the interior states of biological objects. These nondestructive methods have many advantages but too much expensive. And they do not give exact color information and may miss some details. If it is allowed to destruct some biological objects to get the interior and exterior information, constructing 3D image from the series of the sliced sectional images gives more useful information with relatively low cost. In this paper, PC based automatic 3D model generator was developed. The system was composed of three modules. One is the object handling and image acquisition module, which feeds and slices objects sequentially and maintains the paraffin cool to be in solid state and captures the sectional image consecutively. The second is the system control and interface module, which controls actuators for feeding, slicing, and image capturing. And the last is the image processing and visualization module, which processes a series of acquired sectional images and generates 3D graphic model. The handling module was composed of the gripper, which grasps and feeds the object and the cutting device, which cuts the object by moving cutting edge forward and backward. Sliced sectional images were acquired and saved in the form of bitmap file. The 3D model was generated to obtain the volumetric information using these 2D sectional image files after being segmented from the background paraffin. Once 3-D model was constructed on the computer, user could manipulate it with various transformation methods such as translation, rotation, scaling including arbitrary sectional view.

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A Study of Detecting The Fish Robot Position Using The Object Boundary Algorithm (물체 형상인식 알고리즘을 이용한 물고기 로봇 위치 검출에 관한 연구)

  • Amarnath, Varma Angani;Kang, Min Jeong;Shin, Kyoo Jae
    • Proceedings of the Korea Information Processing Society Conference
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    • 2015.10a
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    • pp.1350-1353
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    • 2015
  • In this paper, we have researched about how to detect the fish robot objects in aquarium. We had used designed fish robots DOMI ver1.0, which had researched and developed for aquarium underwater robot. The model of the robot fish is analysis to maximize the momentum of the robot fish and the body of the robot is designed through the analysis of the biological fish swimming. We are planned to non-external equipment to find the position and manipulated the position using creating boundary to fish robot to detect the fish robot objects. Also, we focused the detecting fish robot in aquarium by using boundary algorithm. In order to the find the object boundary, it is filtering the video frame to picture frames and changing the RGB to gray. Then, applied the boundary algorithm stand of equations which operates the boundary for objects. We called these procedures is kind of image processing that can distinguish the objects and background in the captured video frames. It was confirmed that excellent performance in the field test such as filtering image, object detecting and boundary algorithm.

Development of Biological Cell Manipulation System using Visual Tracking Method

  • Lee, Geunho;Kang, Hyun-Jae;Kwon, Sang-Joo;Park, Gwi-Tae;Kim, Byungkyu
    • Proceedings of the IEEK Conference
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    • 2003.07c
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    • pp.2911-2914
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    • 2003
  • Conventionally, biological manipulations have been performed manually with long training and pretty low success rates. To overcome this problem, a novel biological manipulation system has been developed to manipulate biological cells without any interference of a human operator, In this paper, we demonstrate a development of tole-autonomous Cell Manipulation System (CMS) using an image processing at a remote site. The CMS consists of two manipulators, a plane stage, and an optical microscope. We developed deformable template-model-matching algorithm for micro objects and pattern matching algorithm of end effect for these manipulators in order to control manipulators and the stage. Through manipulation of biological cells using these algorithms, the performance of the CMS is verified experimentally.

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Automatic Estimation of Artemia Hatching Rate Using an Object Discrimination Method

  • Kim, Sung;Cho, Hong-Yeon
    • Ocean and Polar Research
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    • v.35 no.3
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    • pp.239-247
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    • 2013
  • Digital image processing is a process to analyze a large volume of information on digital images. In this study, Artemia hatching rate was measured by automatically classifying and counting cysts and larvae based on color imaging data from cyst hatching experiments using an image processing technique. The Artemia hatching rate estimation consists of a series of processes; a step to convert the scanned image data to a binary image data, a process to detect objects and to extract their shape information in the converted image data, an analysis step to choose an optimal discriminant function, and a step to recognize and classify the objects using the function. The function to classify Artemia cysts and larvae is optimally estimated based on the classification performance using the areas and the plan-form factors of the detected objects. The hatching rate using the image data obtained under the different experimental conditions was estimated in the range of 34-48%. It was shown that the maximum difference is about 19.7% and the average root-mean squared difference is about 10.9% as the difference between the results using an automatic counting (this study) and a manual counting were compared. This technique can be applied to biological specimen analysis using similar imaging information.

Speckle Reduction in the Wavelet Domain for Image with Optical Coherence Tomography

  • Chang, Ju-Wan;Lee, Chang-Su;Na, Ji-Hoon;Paes, Stephane;Lee, Byeong-Ha
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.2459-2463
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    • 2005
  • Optical coherence tomography (OCT) is high resolution medical imaging system which is obtaining image inside biological objects with non-destructive method. OCT system is based on Michelson interferometer with a reciprocating mirror in the reference arm and a biological object in the sample arm. The obtained OCT image suffers from a granular or mottled image, called speckle. Speckle is caused by random interferences between reflected coherence waves. In this paper, we propose effective speckle reduction method that uses wavelet transform. With wavelet domain image, sub-windowing and thresholding are performed. Finally, speckle reduction experiments for Misgurnus mizolepis skin and rat eye images are shown.

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A Computer-aided Design Tool with Semiautomatic Image-Processing Features for Visualizing Biological Pathways

  • Ham, Sung-Il;Yang, San-Duk;Thong, Chin-Ting;Park, Hyun-Seok
    • Genomics & Informatics
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    • v.7 no.3
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    • pp.168-170
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    • 2009
  • The explosion in biological data resulting from high-throughput experiments requires new software tools to manipulate and display pathways in a way that can integrate disparate sources of information. A visual Java-based CAD tool for drawing and annotating biological pathways with semiautomatic image-processing features is described in this paper. The result of the image-editing process is an XML file for the appropriate links. This tool integrates the pathway images and XML file sources. The system has facilities for linking graphical objects to external databases and is capable of reproducing existing visual representations of pathway maps.

Hybrid Retrieval Machine for Recognizing 3-D Protein Molecules (3차원 단백질 분자 인식을 위한 복합 추출기)

  • Lee, Hang-Chan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.59 no.5
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    • pp.990-995
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    • 2010
  • Harris corner detector is commonly used to detect feature points for recognizing 2-D or 3-D objects. However, the feature points calculated from both of query and target objects need to be same positions to guarantee accurate recognitions. In order to check the positions of calculated feature points, we generate a Huffman tree which is based on adjacent feature values as inputs. However, the structures of two Huffman trees will be same as long as both of a query and targets have same feature values no matter how different their positions are. In this paper, we sort feature values and calculate the Euclidean distances of coordinates between two adjacent feature values. The Huffman Tree is generated with these Euclidean distances. As a result, the information of point locations can be included in the generated Huffman tree. This is the main strategy for accurate recognitions. We call this system as the HRM(Hybrid Retrieval Machine). This system works very well even when artificial random noises are added to original data. HRM can be used to recognize biological data such as proteins, and it will curtail the costs which are required to biological experiments.

3D Markov chain based multi-priority path selection in the heterogeneous Internet of Things

  • Wu, Huan;Wen, Xiangming;Lu, Zhaoming;Nie, Yao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.11
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    • pp.5276-5298
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    • 2019
  • Internet of Things (IoT) based sensor networks have gained unprecedented popularity in recent years. With the exponential explosion of the objects (sensors and mobiles), the bandwidth and the speed of data transmission are dwarfed by the anticipated emergence of IoT. In this paper, we propose a novel heterogeneous IoT model integrated the power line communication (PLC) and WiFi network to increase the network capacity and cope with the rapid growth of the objects. We firstly propose the mean transmission delay calculation algorithm based the 3D Markov chain according to the multi-priority of the objects. Then, the attractor selection algorithm, which is based on the adaptive behavior of the biological system, is exploited. The combined the 3D Markov chain and the attractor selection model, named MASM, can select the optimal path adaptively in the heterogeneous IoT according to the environment. Furthermore, we verify that the MASM improves the transmission efficiency and reduce the transmission delay effectively. The simulation results show that the MASM is stable to changes in the environment and more applicable for the heterogeneous IoT, compared with the other algorithms.

A Detection Algorithm of the Position of Marks for the Development of Motion Analyzer (동작 분석기 개발을 위한 Mark의 위치 검출 알고리즘 개발)

  • Kim, Sung-Ho;Lee, Sung-Hee;Kim, Min-Gi
    • Proceedings of the KOSOMBE Conference
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    • v.1994 no.05
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    • pp.32-34
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    • 1994
  • An automatic multiframe procedure for tracking signalized points on multiple, differently moving discontinuous surface is described. The position of markers which attached on human body give us some important information such as velocity, acceleration, angular velocity and angular acceleration, etc, of the rigid objects. Generally, the detected objects occufying some area in images rather than a point because of the generic size of the marks or the smeared effects of the camera. To solve the problem we used a modified clustering algorithm.

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