• Title/Summary/Keyword: Number Matching

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Identification Performance of Low-Molecular Compounds by Searching Tandem Mass Spectral Libraries with Simple Peak Matching

  • Milman, Boris L.;Zhurkovich, Inna K.
    • Mass Spectrometry Letters
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    • v.9 no.3
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    • pp.73-76
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    • 2018
  • The number of matched peaks (NMP) is estimated as the spectral similarity measure in tandem mass spectral library searches of small molecules. In the high resolution mode, NMP provides the same reliable identification as in the case of a common dot-product function. Corresponding true positive rates are ($94{\pm}3$) % and ($96{\pm}3$) %, respectively.

Studies on image recognition of human sperms using a neural network

  • Kitamura, S.;Tanaka, K.;Kurematsu, Y.;Takeshima, M.;Iwahara, H.;Teraguchi, T.
    • 제어로봇시스템학회:학술대회논문집
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    • 1989.10a
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    • pp.1135-1139
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    • 1989
  • Three layered neural network was applied for the pattern recognition problem of human spermatozoa in clinical test. The goodness of recognition rate was studied in relation to the number of hidden layer cells and of output layer cells. The proposed method provided better results than conventional template matching technique. Parallel processing of the back propagation learning algorithm was also studied using transputers and its performance was evaluated.

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A Novel Query-by-Singing/Humming Method by Estimating Matching Positions Based on Multi-layered Perceptron

  • Pham, Tuyen Danh;Nam, Gi Pyo;Shin, Kwang Yong;Park, Kang Ryoung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.7
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    • pp.1657-1670
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    • 2013
  • The increase in the number of music files in smart phone and MP3 player makes it difficult to find the music files which people want. So, Query-by-Singing/Humming (QbSH) systems have been developed to retrieve music from a user's humming or singing without having to know detailed information about the title or singer of song. Most previous researches on QbSH have been conducted using musical instrument digital interface (MIDI) files as reference songs. However, the production of MIDI files is a time-consuming process. In addition, more and more music files are newly published with the development of music market. Consequently, the method of using the more common MPEG-1 audio layer 3 (MP3) files for reference songs is considered as an alternative. However, there is little previous research on QbSH with MP3 files because an MP3 file has a different waveform due to background music and multiple (polyphonic) melodies compared to the humming/singing query. To overcome these problems, we propose a new QbSH method using MP3 files on mobile device. This research is novel in four ways. First, this is the first research on QbSH using MP3 files as reference songs. Second, the start and end positions on the MP3 file to be matched are estimated by using multi-layered perceptron (MLP) prior to performing the matching with humming/singing query file. Third, for more accurate results, four MLPs are used, which produce the start and end positions for dynamic time warping (DTW) matching algorithm, and those for chroma-based DTW algorithm, respectively. Fourth, two matching scores by the DTW and chroma-based DTW algorithms are combined by using PRODUCT rule, through which a higher matching accuracy is obtained. Experimental results with AFA MP3 database show that the accuracy (Top 1 accuracy of 98%, with an MRR of 0.989) of the proposed method is much higher than that of other methods. We also showed the effectiveness of the proposed system on consumer mobile device.

Fingerprint Recognition Algorithm using Clique (클릭 구조를 이용한 지문 인식 알고리즘)

  • Ahn, Do-Sung;Kim, Hak-Il
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.2
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    • pp.69-80
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    • 1999
  • Recently, social requirements of personal identification techniques are rapidly expanding in a number of new application ares. Especially fingerprint recognition is the most important technology. Fingerprint recognition technologies are well established, proven, cost and legally accepted. Therefore, it has more spot lighted among the any other biometrics technologies. In this paper we propose a new on-line fingerprint recognition algorithm for non-inked type live scanner to fit their increasing of security level under the computing environment. Fingerprint recognition system consists of two distinct structural blocks: feature extraction and feature matching. The main topic in this paper focuses on the feature matching using the fingerprint minutiae (ridge ending and bifurcation). Minutiae matching is composed in the alignment stage and matching stage. Success of optimizing the alignment stage is the key of real-time (on-line) fingerprint recognition. Proposed alignment algorithm using clique shows the strength in the search space optimization and partially incomplete image. We make our own database to get the generality. Using the traditional statistical discriminant analysis, 0.05% false acceptance rate (FAR) at 8.83% false rejection rate (FRR) in 1.55 second average matching speed on a Pentium system have been achieved. This makes it possible to construct high performance fingerprint recognition system.

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Enhanced Block Matching Scheme for Denoising Images Based on Bit-Plane Decomposition of Images (영상의 이진화평면 분해에 기반한 확장된 블록매칭 잡음제거)

  • Pok, Gouchol
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.12 no.3
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    • pp.321-326
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    • 2019
  • Image denoising methods based on block matching are founded on the experimental observations that neighboring patches or blocks in images retain similar features with each other, and have been proved to show superior performance in denoising different kinds of noise. The methods, however, take into account only neighboring blocks in searching for similar blocks, and ignore the characteristic features of the reference block itself. Consequently, denoising performance is negatively affected when outliers of the Gaussian distribution are included in the reference block which is to be denoised. In this paper, we propose an expanded block matching method in which noisy images are first decomposed into a number of bit-planes, then the range of true signals are estimated based on the distribution of pixels on the bit-planes, and finally outliers are replaced by the neighboring pixels belonging to the estimated range. In this way, the advantages of the conventional Gaussian filter can be added to the blocking matching method. We tested the proposed method through extensive experiments with well known test-bed images, and observed that performance gain can be achieved by the proposed method.

The effect of policy on Korean personal assistance service for persons with disabilities of labor market participation (장애인활동지원서비스제도의 노동시장 참여에 대한 정책효과)

  • Kim, Song Sook;Kim, Yoo-Min;Na, Ga-Yeon;Baek, Seung-Hee;Lee, Kun-Chul
    • Journal of the Korea Convergence Society
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    • v.12 no.4
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    • pp.267-274
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    • 2021
  • This study used data from the 6rd and 12th year of the Korean Welfare Panel to evaluate the effects of the Personal Assistance Service(PAS) system on the labor market of PAS users' participation. For the purpose of this study, 64 program groups using the Korean PAS and 344 control groups not using the Korean PAS were selected using Caliper matching among the propensity score matching. A chi-square test was used for the difference in characteristics between groups, and a simple difference-in-differences (DID) model and a double-difference multiple regression analysis of DID were performed to estimate the effect of thepolicy before and after the Korean PAS. As a result of the study, it was found that statistically, PAS had no significant effect on the labor market. This is due to the low number of system users, resulting in low post-hoc power, incomplete matching and limited availability of PAS Assistants for Disabled People. Therefore, In order to demonstrate the effectiveness of the Personal Assistance Service(PAS) system, specialized services and systems that meet the needs of the disabled and household members should be implemented.

Job Preference Analysis and Job Matching System Development for the Middle Aged Class (중장년층 일자리 요구사항 분석 및 인력 고용 매칭 시스템 개발)

  • Kim, Seongchan;Jang, Jincheul;Kim, Seong Jung;Chin, Hyojin;Yi, Mun Yong
    • Journal of Intelligence and Information Systems
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    • v.22 no.4
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    • pp.247-264
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    • 2016
  • With the rapid acceleration of low-birth rate and population aging, the employment of the neglected groups of people including the middle aged class is a crucial issue in South Korea. In particular, in the 2010s, the number of the middle aged who want to find a new job after retirement age is significantly increasing with the arrival of the retirement time of the baby boom generation (born 1955-1963). Despite the importance of matching jobs to this emerging middle aged class, private job portals as well as the Korean government do not provide any online job service tailored for them. A gigantic amount of job information is available online; however, the current recruiting systems do not meet the demand of the middle aged class as their primary targets are young workers. We are in dire need of a specially designed recruiting system for the middle aged. Meanwhile, when users are searching the desired occupations on the Worknet website, provided by the Korean Ministry of Employment and Labor, users are experiencing discomfort to search for similar jobs because Worknet is providing filtered search results on the basis of exact matches of a preferred job code. Besides, according to our Worknet data analysis, only about 24% of job seekers had landed on a job position consistent with their initial preferred job code while the rest had landed on a position different from their initial preference. To improve the situation, particularly for the middle aged class, we investigate a soft job matching technique by performing the following: 1) we review a user behavior logs of Worknet, which is a public job recruiting system set up by the Korean government and point out key system design implications for the middle aged. Specifically, we analyze the job postings that include preferential tags for the middle aged in order to disclose what types of jobs are in favor of the middle aged; 2) we develope a new occupation classification scheme for the middle aged, Korea Occupation Classification for the Middle-aged (KOCM), based on the similarity between jobs by reorganizing and modifying a general occupation classification scheme. When viewed from the perspective of job placement, an occupation classification scheme is a way to connect the enterprises and job seekers and a basic mechanism for job placement. The key features of KOCM include establishing the Simple Labor category, which is the most requested category by enterprises; and 3) we design MOMA (Middle-aged Occupation Matching Algorithm), which is a hybrid job matching algorithm comprising constraint-based reasoning and case-based reasoning. MOMA incorporates KOCM to expand query to search similar jobs in the database. MOMA utilizes cosine similarity between user requirement and job posting to rank a set of postings in terms of preferred job code, salary, distance, and job type. The developed system using MOMA demonstrates about 20 times of improvement over the hard matching performance. In implementing the algorithm for a web-based application of recruiting system for the middle aged, we also considered the usability issue of making the system easier to use, which is especially important for this particular class of users. That is, we wanted to improve the usability of the system during the job search process for the middle aged users by asking to enter only a few simple and core pieces of information such as preferred job (job code), salary, and (allowable) distance to the working place, enabling the middle aged to find a job suitable to their needs efficiently. The Web site implemented with MOMA should be able to contribute to improving job search of the middle aged class. We also expect the overall approach to be applicable to other groups of people for the improvement of job matching results.

Traversable Region Detection Algorithm using Lane Information and Texture Analysis (차로 수 정보와 텍스쳐 분석을 활용한 주행가능영역 검출 알고리즘)

  • Hwang, Sung Soo;Kim, Do Hyun
    • Journal of Korea Multimedia Society
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    • v.19 no.6
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    • pp.979-989
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    • 2016
  • Traversable region detection is an essential step for advanced driver assistance systems and self-driving car systems, and it has been conducted by detecting lanes from input images. The performance can be unreliable, however, when the light condition is poor or there exist no lanes on the roads. To solve this problem, this paper proposes an algorithm which utilizes the information about the number of lanes and texture analysis. The proposed algorithm first specifies road region candidates by utilizing the number of lanes information. Among road region candidates, the road region is determined as the region in which texture is homogeneous and texture discontinuities occur around its boundaries. Traversable region is finally detected by dividing the estimated road region with the number of lanes information. This paper combines the proposed algorithm with a lane detection-based method to construct a system, and simulation results show that the system detects traversable region even on the road with poor light conditions or no lanes.

New Randomness Testing Methods using Approximate Periods (근사 주기를 이용한 새로운 랜덤성 테스트 기법)

  • Lim, Ji-Hyuk;Lee, Sun-Ho;Kim, Dong-Kyue
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.6
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    • pp.742-746
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    • 2010
  • In this paper, we propose new randomness testing methods based on approximate periods in order to improve the previous randomness testing method using exact pattern matching. Finding approximate periods of random sequences enables us to search similarly repeated parts, but it has disadvantages since it takes long time. In this paper we propose randomness testing methods whose time complexity is O($n^2$) by reducing the time complexity of computing approximate periods from O($n^3$) to O($n^2$). Moreover, we perform some experiments to compare pseudo random number generated by AES cryptographic algorithms and true random number.

Face Recognition based on SURF Interest Point Extraction Algorithm (SURF 특징점 추출 알고리즘을 이용한 얼굴인식 연구)

  • Kang, Min-Ku;Choo, Won-Kook;Moon, Seung-Bin
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.48 no.3
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    • pp.46-53
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    • 2011
  • This paper proposes a SURF (Speeded Up Robust Features) based face recognition method which is one of typical interest point extraction algorithms. In general, SURF based object recognition is performed in interest point extraction and matching. In this paper, although, proposed method is employed not only in interest point extraction and matching, but also in face image rotation and interest point verification. image rotation is performed to increase the number of interest points and interest point verification is performed to find interest points which were matched correctly. Although proposed SURF based face recognition method requires more computation time than PCA based one, it shows better recognition rate than PCA algorithm. Through this experimental result, I confirmed that interest point extraction algorithm also can be adopted in face recognition.