• Title/Summary/Keyword: Identification Number

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A Numerical Coding System (MCRCODE-N) for Identification of Glucose Nonfermenting Gram-Negative Bacilli (숫자표기에 의한 포도당 비발효균의 동정시안(MCRCODE-N))

  • Hong, Seok-Il;Kim, Chung-Suk
    • Journal of Yeungnam Medical Science
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    • v.2 no.1
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    • pp.183-190
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    • 1985
  • The glucose nonfermenting gram-negative bacilli encountered about 10% of all gram-negative bacilli isolated from clinical material. Therefore, a rapid and correct identification of glucose nonfermenting gram-negative bacilli is impostent for a better management of infectious disease. There are many conventional systems for the Identification of glucose nonfermenting gram-negative bacilli but most of them have problems and difficulties. Commercial Kit Systems exist and they are too expensive for dally use 10 Korea because of high cost. Based on 12 selected tests we propose a new code system, MCRCODE-N for rapid and 10-expensive identification of glucose nonfermenting gram-negative bacilli. The selective 12 tests are oxidase, glucose oxidation motility, urease, DNase arginine dehydrolase, nitrate reduction, gelatin Liquefaction, esculin hydrolysis, mannitol oxidation, maltose oxidation, Lactose oxidation. The 12 tests are divided 4 group and then each group has 3 tests. The result of each group is expressed by the number as below. The positive test is given by specific number (1st test = 1, 2nd test = 2, 3rd test = 4), while any negative result is 0. Each 3 numbers of one group are added and make number of 1 digit. Four digit number is refered to the code book of MCRCODE-N system or MCRCODE system using computer (Apple-II model) created by authors. This MCRCODE-N system is suitable ones for our use 10 Korea. We propose the MCRCODEN-N system for clinical use.

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Slab Region Localization for Text Extraction using SIFT Features (문자열 검출을 위한 슬라브 영역 추정)

  • Choi, Jong-Hyun;Choi, Sung-Hoo;Yun, Jong-Pil;Koo, Keun-Hwi;Kim, Sang-Woo
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.5
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    • pp.1025-1034
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    • 2009
  • In steel making production line, steel slabs are given a unique identification number. This identification number, Slab management number(SMN), gives information about the use of the slab. Identification of SMN has been done by humans for several years, but this is expensive and not accurate and it has been a heavy burden on the workers. Consequently, to improve efficiency, automatic recognition system is desirable. Generally, a recognition system consists of text localization, text extraction, character segmentation, and character recognition. For exact SMN identification, all the stage of the recognition system must be successful. In particular, the text localization is great important stage and difficult to process. However, because of many text-like patterns in a complex background and high fuzziness between the slab and background, directly extracting text region is difficult to process. If the slab region including SMN can be detected precisely, text localization algorithm will be able to be developed on the more simple method and the processing time of the overall recognition system will be reduced. This paper describes about the slab region localization using SIFT(Scale Invariant Feature Transform) features in the image. First, SIFT algorithm is applied the captured background and slab image, then features of two images are matched by Nearest Neighbor(NN) algorithm. However, correct matching rate can be low when two images are matched. Thus, to remove incorrect match between the features of two images, geometric locations of the matched two feature points are used. Finally, search rectangle method is performed in correct matching features, and then the top boundary and side boundaries of the slab region are determined. For this processes, we can reduce search region for extraction of SMN from the slab image. Most cases, to extract text region, search region is heuristically fixed [1][2]. However, the proposed algorithm is more analytic than other algorithms, because the search region is not fixed and the slab region is searched in the whole image. Experimental results show that the proposed algorithm has a good performance.

HMM-Based Transient Identification in Dynamic Process

  • Kwon, Kee-Choon
    • Transactions on Control, Automation and Systems Engineering
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    • v.2 no.1
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    • pp.40-46
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    • 2000
  • In this paper, a transient identification based on a Hidden Markov Model (HMM) has been suggested and evaluated experimentally for the classification of transients in the dynamic process. The transient can be identified by its unique time dependent patterns related to the principal variables. The HMM, a double stochastic process, can be applied to transient identification which is a spatial and temporal classification problem under a statistical pattern recognition framework. The HMM is created for each transient from a set of training data by the maximum-likelihood estimation method. The transient identification is determined by calculating which model has the highest probability for the given test data. Several experimental tests have been performed with normalization methods, clustering algorithms, and a number of states in HMM. Several experimental tests have been performed including superimposing random noise, adding systematic error, and untrained transients. The proposed real-time transient identification system has many advantages, however, there are still a lot of problems that should be solved to apply to a real dynamic process. Further efforts are being made to improve the system performance and robustness to demonstrate reliability and accuracy to the required level.

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A Damage Identification for Railway Bridges using Static Response (철도교량의 손상도 평가기법 개발에 관한 연구)

  • 최일윤;이준석;이종순;조효남
    • Proceedings of the KSR Conference
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    • 2002.10b
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    • pp.1065-1073
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    • 2002
  • A new damage identification technique using static displacement data is developed to assess the structural integrity of bridge structures. In the conventional damage assessment techniques using dynamic response, it is usually difficult to obtain a significant natural frequencies variation from the measured data because the natural frequencies variation is intrinsically not sensitive to the damage of a bridge. In this proposed identification method, the stiffness reduction of the bridges can be estimated using the static displacement data measured periodically and a specific loading test is not required. The static displacement data due to the dead load of the bridge structure can be measured by devices such as a laser displacement sensor. In this study, structural damage is represented by the reduction in the elastic modulus of the element. The damage factor of the element is introduced to estimate the stiffness reduction of the bridge under consideration. Finally, the proposed algorithm is verified using various numerical simulation and compared with other damage identification method. Also, the effect of noise and number of damaged elements on the identification are investigated. The results show that the proposed algorithm is efficient for damage identification of the bridges.

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Optical security system for protection of personal identification information (개인신원정보 보호를 위한 광 보호 시스템)

  • 윤종수;도양회
    • Korean Journal of Optics and Photonics
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    • v.14 no.4
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    • pp.383-391
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    • 2003
  • A new optical security system for the protection of personal identification information is proposed. Personal identification information consisting of a pure face image and an identification number is used for verification and authentication. Image encryption is performed by a fully phase image encryption technique with two random phase masks located in the input and the Fourier plane of 4-f correlator. The personal information, however, can be leaked out in the decryption process. To cope with this possibility, the encrypted image itself is used in the identification process. An encrypted personal identification number is discriminated and recognized by using the proposed MMACE_p (multiplexed MACE_p) filter, and then authenticity of the personal information is verified by correlation of the face image using the optical wavelet matched filter (OWMF). MMACE_p filter is a synthetic filter with four MACE_p (minimum average correlation energy_phase encrypted) filters multiplexed in one filter plane to recognize 10 different encrypted-numbers at a time. OWMF can improve discrimination capability and SNR (signal to noise ratio). Computer simulations confirmed that the proposed security technique can be applied to the protection of personal identification information.

A Mechanism for Dynamic Allocation of Frame Size in RFID System

  • Lim, In-Taek
    • Journal of information and communication convergence engineering
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    • v.6 no.4
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    • pp.364-369
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    • 2008
  • The FSA algorithm for identifying multiple tags in RFID systems is based on the slotted ALOHA scheme with a fixed frame size. The performance of FSA algorithm is dependent on the frame size and the number of tags in the reader's identification range. Therefore, this paper proposes a new ODFSA. The proposed ODFSA algorithm dynamically allocates the optimal frame size at every frame based on the number of tags in the reader's identification range. According to the simulation results, the system efficiency of the proposed algorithm should be maintained optimally. Also, the proposed algorithm always obtained the minimum tag identification delay.

Multi-stage approach for structural damage identification using particle swarm optimization

  • Tang, H.;Zhang, W.;Xie, L.;Xue, S.
    • Smart Structures and Systems
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    • v.11 no.1
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    • pp.69-86
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    • 2013
  • An efficient methodology using static test data and changes in natural frequencies is proposed to identify the damages in structural systems. The methodology consists of two main stages. In the first stage, the Damage Signal Match (DSM) technique is employed to quickly identify the most potentially damaged elements so as to reduce the number of the solution space (solution parameters). In the second stage, a particle swarm optimization (PSO) approach is presented to accurately determine the actual damage extents using the first stage results. One numerical case study by using a planar truss and one experimental case study by using a full-scale steel truss structure are used to verify the proposed hybrid method. The identification results show that the proposed methodology can identify the location and severity of damage with a reasonable level of accuracy, even when practical considerations limit the number of measurements to only a few for a complex structure.

A Case Report of Chronic cough treated by Soshiho-tang based on Shanghanlun Provisions (『상한론(傷寒論)』 변병진단체계(辨病診斷體系)에 근거하여 소시호탕(小柴胡湯)투여 후 호전된 만성기침 1례)

  • Ryu, Hee-Chang;Lee, Soong-In
    • 대한상한금궤의학회지
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    • v.8 no.1
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    • pp.99-108
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    • 2016
  • Objective : The purpose of this paper is to report the improvement of patient with chronic cough treated by herb medication based on Shanghanlun disease pattern identification diagnostic system. Methods : According to 'Disease Pattern Identification Diagnostic System based on Shanghanlun Provisions', the patient diagnosed with Taeyang-byung, number 96 provision, and took Soshiho-tang herb medication 50days. The changing symptom of chronic cough was estimated by LCQ(Leicester Cough Questionnaire) and VAS(Visual Analogue Scale). Results : The LCQ score changed 57 to 111 and VAS changed 10 to 0. Conclusions : On the number 96 provision of Shanghanlun, '或欬' means 'H or K' sound cough. This is the first case report treating the chronic cough with herb medication of shanghanlun in Korea.

$\bar{X}$ Control Chart Pattern Identification Through Efficient Neural Network Training (효율적인 신경회로망 학습을 이용한 $\bar{X}$ 관리도의 이상패턴 인식에 관한 연구)

  • 김기영;유정현;윤덕균
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.21 no.45
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    • pp.365-374
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    • 1998
  • Control Chart is a powerful tool to detect that process is in control or out of control. CIM can have real effect when CIM involve automated quality control. A neural network approach is used for unnatural pattern detecting of control chart. The previous moving window method uses all unnatural pattern that is detected as moving time window. Therefore, It trains a large number of unnatural pattern and takes training time long. In this paper, the proposed method tests a small number of training unnatural pattern which modifies test data without repeating time. We shows that the proposed method has differences In training time and identification rate on the previous moving windows method. As results, we reduced training time and obtain the same identification rate.

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Service Identification of Internet-Connected Devices Based on Common Platform Enumeration

  • Na, Sarang;Kim, Taeeun;Kim, Hwankuk
    • Journal of Information Processing Systems
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    • v.14 no.3
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    • pp.740-750
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    • 2018
  • There are a great number of Internet-connected devices and their information can be acquired through an Internet-wide scanning tool. By associating device information with publicly known security vulnerabilities, security experts are able to determine whether a particular device is vulnerable. Currently, the identification of the device information and its related vulnerabilities is manually carried out. It is necessary to automate the process to identify a huge number of Internet-connected devices in order to analyze more than one hundred thousand security vulnerabilities. In this paper, we propose a method of automatically generating device information in the Common Platform Enumeration (CPE) format from banner text to discover potentially weak devices having the Common Vulnerabilities Exposures (CVE) vulnerability. We demonstrated that our proposed method can distinguish as much adequate CPE information as possible in the service banner.