• Title/Summary/Keyword: analysis of algorithms

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An Analysis of Test Results Using the New Fusion Weight Conversion Algorithm for High-speed Weigh-In-Motion System (주행시험을 통한 고속축중기의 융합형 중량환산 알고리즘 효과 분석)

  • Kim, Jong Woo;Jung, Young Woo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.4
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    • pp.67-80
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    • 2020
  • High-speed weigh in motion (HS-WIM) is a real-time unmanned system for measuring the weight of a freight-carrying vehicle while it is in motion without controlling vehicle traffic flow or deceleration. In Korea, HS-WIM systems are installed on the national highways and general national ways for pre-selection by law enforcement. In this study, to improve the measurement accuracy of HS-WIM, we devise improvements to the existing integral and peak weight conversion algorithms, and we provide a new fusion algorithm that can be applied to the mat-type HS-WIM. As a result of analyzing vehicle driving tests at a real site, we confirmed the highest level of weight-measuring accuracy.

Phoneme Segmentation in Consideration of Speech feature in Korean Speech Recognition (한국어 음성인식에서 음성의 특성을 고려한 음소 경계 검출)

  • 서영완;송점동;이정현
    • Journal of Internet Computing and Services
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    • v.2 no.1
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    • pp.31-38
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    • 2001
  • Speech database built of phonemes is significant in the studies of speech recognition, speech synthesis and analysis, Phoneme, consist of voiced sounds and unvoiced ones, Though there are many feature differences in voiced and unvoiced sounds, the traditional algorithms for detecting the boundary between phonemes do not reflect on them and determine the boundary between phonemes by comparing parameters of current frame with those of previous frame in time domain, In this paper, we propose the assort algorithm, which is based on a block and reflecting upon the feature differences between voiced and unvoiced sounds for phoneme segmentation, The assort algorithm uses the distance measure based upon MFCC(Mel-Frequency Cepstrum Coefficient) as a comparing spectrum measure, and uses the energy, zero crossing rate, spectral energy ratio, the formant frequency to separate voiced sounds from unvoiced sounds, N, the result of out experiment, the proposed system showed about 79 percents precision subject to the 3 or 4 syllables isolated words, and improved about 8 percents in the precision over the existing phonemes segmentation system.

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LAB color illumination revisions for the improvement of non-proper image (비정규 영상의 개선을 위한 LAB 컬러조명보정)

  • Na, Jong-Won
    • Journal of Advanced Navigation Technology
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    • v.14 no.2
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    • pp.191-197
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    • 2010
  • Many does an application and application but the image analysis of face detection considerably is difficult. In order for with effect of the illumination which is irregular in the present paper America the illumination to range evenly in the face which is detected, detects a face territory, Complemented the result which detects only the front face of existing. With LAB color illumination revisions compared in Adaboost face detection of existing and 32% was visible the face detection result which improves. Bought two images which are input and executed Glassfire label rings. Compared Area critical price and became the area of above critical value and revised from RGB smooth anger and LAB images with LCFD system algorithm. The operational conversion image which is extracted like this executed a face territory detection in the object. In order to extract the feature which is necessary to a face detection used AdaBoost algorithms. The face territory remote login with the face territory which tilts in the present paper, until Multi-view face territory detections was possible. Also relationship without high detection rate seems in direction of illumination, With only the public PC application is possible was given proof user authentication field etc.

Applying Image Processing Algorithm to Raw LiDAR Data for Extracting Ground Information (LiDAR 원시자료에서의 지면정보 추출을 위한 영상처리기법 적용 연구)

  • Choi, Yun-Woong;Sohn, Duk-Jae;Cho, Gi-Sung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.27 no.5
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    • pp.575-583
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    • 2009
  • Various algorithms and methods, related to preprocessing of LiDAR data, are being developed and proposed. These methods are two ways, one of them is to use the regular form such as DSM or the image converted from raw LiDAR data, and the other is to use raw LiDAR data directly. The image processing method is one of representative method for the regular grid form data. This method is easy to apply to a numerical analysis technique and has an advantage of modeling and noise elimination through smoothing, but it lose the information during the data conversion. This study apply the image processing method to the irregular raw LiDAR data directly for the extracting ground information with minimized information loss and evaluate the extracting accuracy of ground information.

A Novel Network Anomaly Detection Method based on Data Balancing and Recursive Feature Addition

  • Liu, Xinqian;Ren, Jiadong;He, Haitao;Wang, Qian;Sun, Shengting
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.7
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    • pp.3093-3115
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    • 2020
  • Network anomaly detection system plays an essential role in detecting network anomaly and ensuring network security. Anomaly detection system based machine learning has become an increasingly popular solution. However, due to the unbalance and high-dimension characteristics of network traffic, the existing methods unable to achieve the excellent performance of high accuracy and low false alarm rate. To address this problem, a new network anomaly detection method based on data balancing and recursive feature addition is proposed. Firstly, data balancing algorithm based on improved KNN outlier detection is designed to select part respective data on each category. Combination optimization about parameters of improved KNN outlier detection is implemented by genetic algorithm. Next, recursive feature addition algorithm based on correlation analysis is proposed to select effective features, in which a cross contingency test is utilized to analyze correlation and obtain a features subset with a strong correlation. Then, random forests model is as the classification model to detection anomaly. Finally, the proposed algorithm is evaluated on benchmark datasets KDD Cup 1999 and UNSW_NB15. The result illustrates the proposed strategies enhance accuracy and recall, and decrease the false alarm rate. Compared with other algorithms, this algorithm still achieves significant effects, especially recall in the small category.

Shape Generation and Optimization Technique of Space Frame Structures with Ellipse and Vault Complex Type (타원형 및 볼트복합형 스페이스 프레임 구조물의 형상 생성 및 최적화 방안)

  • Kim, Ho-Soo;Park, Young-Sin
    • Journal of Korean Association for Spatial Structures
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    • v.10 no.4
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    • pp.113-122
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    • 2010
  • Space frame structures are included in the large spatial structures and can adopt various structure types. But, it is not easy to choose the optimal member size and shape because it depends on the structural engineer's experience and the repeated trial and error. Therefore, in this study, the final goal is to help the designer with the selection of the optimum shape. First, various space frame structures with ellipse dome and vault complex types are chosen and the shape generation method is considered to generate the nodes, coordinates and members. In optimal design process of space frame structure, each node coordinate changes according to height variation or the number of rings. Therefore, the auto generation technique of nodes and members is required in order to consider this phenomenon in optimal design process. Next, the shape generation module is created, base on the shape generation method. This module is connected with the analysis module and the optimization algorithm. Finally, the example model is presented for the evaluation of the efficiency of optimization algorithms.

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Identification of prognosis-specific network and prediction for estrogen receptor-negative breast cancer using microarray data and PPI data (마이크로어레이 데이터와 PPI 데이터를 이용한 에스트로겐 수용체 음성 유방암 환자의 예후 특이 네트워크 식별 및 예후 예측)

  • Hwang, Youhyeon;Oh, Min;Yoon, Youngmi
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.2
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    • pp.137-147
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    • 2015
  • This study proposes an algorithm for predicting breast cancer prognosis based on genetic network. We identify prognosis-specific network using gene expression data and PPI(protein-protein interaction) data. To acquire the network, we calculate Pearson's correlation coefficient(PCC) between genes in all PPI pairs using gene expression data. We develop a prediction model for breast cancer patients with estrogen-receptor-negative using the network as a classifier. We compare classification performance of our algorithm with existing algorithms on independent data and shows our algorithm is improved. In addition, we make an functionality analysis on the genes in the prognosis-specific network using GO(Gene Ontology) enrichment validation.

Implementation of Stereoscopic 3D Video Player System Having Less Visual Fatigue and Its Computational Complexity Analysis for Real-Time Processing (시청피로 저감형 S3D 영상 재생 시스템 구현 및 실시간 처리를 위한 알고리즘 연산량 분석)

  • Lee, Jaesung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.12
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    • pp.2865-2874
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    • 2013
  • Recently, most of movies top-ranked in the box office are screening in Stereoscopic 3D, and the world's leading electronics companies such as Samsung and LG are getting the hots for 3DTV sales. However, each person has different binocular disparity and different viewing distance, and thus he or she feels the severe visual fatigue and headaches if he or she is watching 3D content with the same binocular disparity, which is very different from things he or she feels in the real world. To solve this problem, this paper proposes and implement a 3D rendering system that correct the disparity of 3D content by reflecting binocular distance and viewing distance. Then, the computational complexity is analyzed. Optical-flow and Warping algorithms turn out to consume 732 seconds and 5.7 seconds per frame, respectively. Therefore, a dedicated chip-set for both blocks is strongly required for real-time HD 3D display.

Control Packet Transmission Decision Method for Wearable Sensor Systems (웨어러블 센서 시스템에서의 제어 패킷 전송 결정 기법)

  • Yu, Daeun;Kim, Namgi
    • Journal of Internet Computing and Services
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    • v.16 no.5
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    • pp.11-17
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    • 2015
  • In the general transmission power control model that is used for wearable sensor systems, if RSSI value gets out of the Target RSSI Margin, then the sink node finds new transmission power by using TPC(Transmission Power Control) Algorithm. At this time, the sink node sends the control packet to the sensor node for delivering the newly calculated transmission power. However, when the wireless network channel condition is poor, even it is consuming a lot of control packets, the sink node could not find an appropriate transmission power so it only waste of energy. Therefore, we proposed a new control packet transmission decision method that the sink node changes the transmission power when the wireless network channel condition is stabilized. It makes waste of energy decline. In this paper, we apply control packet transmission decision method to Binary TPC algorithms and analyze the results to evaluate the proposed method. We propose three methods that judge the state of wireless network channel. We experiment that methods and analysis the results.

An Automatic LOINC Mapping Framework for Standardization of Laboratory Codes in Medical Informatics (의료 정보 검사코드 표준화를 위한 LOINC 자동 매핑 프레임웍)

  • Ahn, Hoo-Young;Park, Young-Ho
    • Journal of Korea Multimedia Society
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    • v.12 no.8
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    • pp.1172-1181
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    • 2009
  • An electronic medical record (EMR) is the medical system that all the test are recorded as text data. However, domestic EMR systems have various forms of medical records. There are a lot of related works to standardize the laboratory codes as a LOINC (Logical Observation Identifiers Names and Code). However the existing researches resolve the problem manually. The manual process does not work when the size of data is enormous. The paper proposes a novel automatic LOINC mapping algorithm which uses indexing techniques and semantic similarity analysis of medical information. They use file system which is not proper to enormous medical data. We designed and implemented mapping algorithm for standardization laboratory codes in medical informatics compared with the existing researches that are only proposed algorithms. The automatic creation of searching words is being possible. Moreover, the paper implemented medical searching framework based on database system that is considered large size of medical data.

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