• Bulletin of the Korean Chemical Society
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• v.35 no.8
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• pp.2419-2422
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• 2014

The syntheses and crystal structures of a three-dimensional (3D) coordination network $[Zn_4(2-mBIM)_5-(C_2H_6NCOO)(HCOO)({\mu}-OH)]{\cdot}DMF$ ($1{\cdot}$DMF; 2-mBIM = 2-methylbenzimidazolate) and a two-dimensional (2D) layer $[Zn_2(2-mBIM)_3(HCOO)(H_2O)]{\cdot}DMF$ ($2{\cdot}DMF$) are reported. Different structures were produced depending on the ratio of reactants. Structurally, 1 illustrates the formation of a unique framework based on a 2-mBIM bridge with the side group on an imidazole ring, while 2 possesses a honeycomb layer built up purely from imidazolates. For gas sorption, $CO_2$ is adsorbed on the activated phase of 1 but $N_2$ is not taken up.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.97.5-97
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• 2002

A sensor modeling via artificial neural network is presented in this paper. The optical sensor has been designed to treasure absolute 3-dimensional positions and orientations of objects in 6-DOF. The method utilizes a triangular pyramidal mirror having an equilateral cross-sectional shape referred as 3-facet mirror. The mirror has three lateral reflective surfaces inclined 45 degrees to its bottom surface. The 3-facet mirror is mounted on the object whose 6-DOF motion is to be measured. As optical components, a He-Ne laser source and three position-sensitive detectors(PSD) are used. The laser beam is emitted from the He-Ne laser source located at the upright position and vertically incident o...

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.3
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• pp.138-144
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• 2000

The detent force caused by the interaction of magnets with the teeth of a armature core deteriorates the driving performance of a permanent magnet linear synchronous motor. In this paper, we analyze the fields and forces of a linear synchronous motor with segmented or skewed magnet arrangement according to lateral overhang length of permanent magnets. For the analysis, the 3-dimensional equivalent magnetic circuit network method is used. The detent force and the static thrust are analyzed according to the segmented or skewed angle and the overhang length of permanent magnets, and the optimal angles that the detent force is minimized are found out in each case. The analysis results are compared with the experimental ones and shown a reasonable agreement.

• The Journal of Information Systems
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• v.22 no.3
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• pp.1-24
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• 2013

SNS(Social Network Services) is being recognized as an important part in our society, individual lives and corporate business aspects, and the influence of SNS is growing explosively as expansion and supply of infrastructures that support mobile environments increase. Previous studies related to SNS were focused on user acceptance of new technology, based on Technology Acceptance Model(TAM). However, they had a limitation to focus on technology acceptance, without the consideration of personal and behavioral factors in SNS use. However, above all, successful SNS requires the understanding of users who are active on the network. Therefore, from the user's perspective, this study attempted a multi-dimensional approach by reflecting characteristics that come from SNS usage. This study considered user innovation, virtual skill, self-efficacy, social pressure and network effect as independent variables, and perceived ease-of-use, perceived usefulness and perceived value as mediating variables, and intention-to-use as dependent variable. The result showed that user innovation, self-efficacy, social pressure and network effect had a significant effect on the mediating variables. The practical contribution of this study is to suggest useful decision alternatives concerned to marketing strategy for acquiring and retaining lone-term customers related to SNS business.

• Journal of Microbiology and Biotechnology
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• v.16 no.6
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• pp.911-920
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• 2006

[ $CD8^+$ ] T Iymphocytes with the cytotoxic activity and capability to release various cytokines are the major players in immune responses against viral infection and cancer. To identify the proteins specific to resting or activated human CD8$^+$ T cells, human CD8$^+$ T cells were activated with anti-CD3+anti-CD28 mAb in the presence of IL-2. The solubilized proteins from resting and activated human CD8$^+$ T cells were separated by high-resolution two-dimensional polyacrylamide gel electrophoresis, and their proteomes were analyzed. Proteomic analysis of resting and activated T cells resulted in identification of 35 proteins with the altered expression. Mass spectrometry coupled with Profound and SWISS-PROT database analysis revealed that these identified proteins are to be functionally associated with cell proliferation, metabolic pathways, antigen presentation, and intracellular signal transduction pathways. We also identified six unknown proteins predicted from genomic DNA sequences specific to resting or activated CD8$^+$ T cells. Protein network studies and functional characterization of these novel proteins may provide new insight into the signaling transduction pathway of CD8$^+$ T cell activation.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.84-90
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• 2022

Machine tool state monitoring is a process that automatically detects the states of machine. In the manufacturing process, the efficiency of machining and the quality of the product are affected by the condition of the tool. Wear and broken tools can cause more serious problems in process performance and lower product quality. Therefore, it is necessary to develop a system to prevent tool wear and damage during the process so that the tool can be replaced in a timely manner. This paper proposes a method for diagnosing five tool states using a deep learning-based hierarchical convolutional neural network to change tools at the right time. The one-dimensional acoustic signal generated when the machine cuts the workpiece is converted into a frequency-based power spectral density two-dimensional image and use as an input for a convolutional neural network. The learning model diagnoses five tool states through three hierarchical steps. The proposed method showed high accuracy compared to the conventional method. In addition, it will be able to be utilized in a smart factory fault diagnosis system that can monitor various machine tools through real-time connecting.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.1
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• pp.77-88
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• 1993

In this paper, we propose a stereo vision system to solve correspondence problem with large disparity and sudden change in environment which result from small distance between camera and working objects. First of all, a specific feature is divided by predfined elementary feature. And then these are combined to obtain coded data for solving correspondence problem. We use Neural Network to extract elementary features from specific feature and to have adaptability to noise and some change of the shape. Fourier transformation and Log-polar mapping are used for obtaining appropriate Neural Network input data which has a shift, scale, and rotation invariability. Finally, we use associative memory to obtain coded data of the specific feature from the combination of elementary features. In spite of specific feature with some variation in shapes, we could obtain satisfactory 3-dimensional data from corresponded codes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.418-424
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• 2018

Detection and classification of underwater targets is an important issue for both military and non-military purposes. Recently, many performance improvements are being reported in the field of pattern recognition with the development of deep learning technology. Among the results, DBN showed good performance when used for pre-training of DNN. In this paper, DBN was used for the classification of underwater targets using active sonar, and the results are compared with that of the conventional BPNN. We synthesized active sonar target signals using 3-dimensional highlight model. Then, features were extracted based on FrFT. In the single aspect based experiment, the classification result using DBN was improved about 3.83% compared with the BPNN. In the case of multi-aspect based experiment, a performance of 95% or more is obtained when the number of observation sequence exceeds three.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.179-186
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• 2013

PACS is a medical system for digital medical images, and PACS expand to web-based service using public network, DICOM files should be protected from the man-in-the-middle attack because they have personal medical record. To solve the problem, we designed flexible secure transmission system using IPSec and adopted to a web-based three-dimensional medical image system. And next, we performed the performance evaluation changing integrity and encryption algorithm using DICOM volume dataset. At that time, combinations of the algorithm was 'DES-MD5', 'DES-SHA1', '3DES-MD5', and '3DES-SHA1, and the experiment was performed on our test-bed. In experimental result, the overall performance was affected by encryption algorithms than integrity algorithms, DES was approximately 50% of throughput degradation and 3DES was about to 65% of throughput degradation. Also when DICOM volume dataset was transmitted using secure transmission system, the network performance degradation had shown because of increased packet overhead. As a result, server and network performance degradation occurs for secure transmission system by ensuring the secure exchange of messages. Thus, if the secure transmission system adopted to the medical images that should be protected, it could solve server performance gradation and compose secure web PACS.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.117-127
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• 1995

In this paper, we suggest a motion analysis method using ART-I1 competitive learning neural network and fuzzy reasoning by matching the same objects through the consecutive image sequence. we use the size and mean intensity of the region obtained from image segmentation for the region matching by the region and use a ART-I1 competitive learning neural network wh~ch has a learning ability to reflect the topology of the input patterns in order to select characteristic points to describe the shape of a region. Motion vectors for each regions are obtained by matching selected characteristic points. However, the two dimensional image, the projection of the the three dimensional real world, produces fuzziness in motion analysis due to its incompleteness by nature and the error from image segmentation used for extracting information about objects. Therefore, the belief degrees for each regions are calculated using fuzzy reasoning to l-nanipulate uncertainty in motion estimation.