• Title/Summary/Keyword: 벡터모델

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Electroencephalogram-Based Driver Drowsiness Detection System Using Errors-In-Variables(EIV) and Multilayer Perceptron(MLP) (EIV와 MLP를 이용한 뇌파 기반 운전자의 졸음 감지 시스템)

  • Han, Hyungseob;Song, Kyoung-Young
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39C no.10
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    • pp.887-895
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    • 2014
  • Drowsy driving is a large proportion of the total car accidents. For this reason, drowsiness detection and warning system for drivers has recently become a very important issue. Monitoring physiological signals provides the possibility of detecting features of drowsiness and fatigue of drivers. Many researches have been published that to measure electroencephalogram(EEG) signals is the effective way in order to be aware of fatigue and drowsiness of drivers. The aim of this study is to extract drowsiness-related features from a set of EEG signals and to classify the features into three states: alertness, transition, and drowsiness. This paper proposes a drowsiness detection system using errors-in-variables(EIV) for extraction of feature vectors and multilayer perceptron (MLP) for classification. The proposed method evaluates robustness for noise and compares to the previous one using linear predictive coding (LPC) combined with MLP. From evaluation results, we conclude that the proposed scheme outperforms the previous one in the low signal-to-noise ratio regime.

Job Level Determination of Organizational Member Using Fuzzy Theory (퍼지이론을 이용한 조직구성원의 업무수준결정)

  • Heo, Sik;Hwang, Seung-Gook
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.2
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    • pp.232-237
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    • 2007
  • In this paper, we suggest the model how to evaluate the job level of the member of Nong-Hyup branch, using fuzzy subordination relation by estimating the relationship of criteria and eigenvector method. The criteria for the evaluation of job levels are divided into two groups, that is, the job group to do in Nong-Hyup and the Job demanding details group that is needed to do this job. The study method used adding weight on the job group and the present level, the itemized weight about job demanding details and the present level, the relationship the job group and the job demanding details. This paper shows that there is room for improvement in the present evaluation method, which regards the job level of each branch as equal, evaluates each branch and ranks. Therefore we will expect to utilize it a lot when the Nong-Hyup and the branchs and places of like this company are estimated.

Three-Dimensional Magnetotelluric Modeling Using Integral Equations (적분방정식을 이용한 3차원 지자기 지전류 모델링)

  • Kim, Hee Joon;Lee, Dong Sung
    • Economic and Environmental Geology
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    • v.27 no.2
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    • pp.191-199
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    • 1994
  • We have developed an algorithm based on the method of integral equations to simulate the magnetotelluric (MT) responses of three-dimensional (3-D) bodies in a layered half-space. The inhomogeneities are divided into a number of cells and are replaced by an equivalent current distribution which is approximated by pulse basis functions. A matrix equation is constructed using the electric Green's tensor function appropriate to a layered earth, and is solved for the vector current in each cell. Subsequently, scattered fields are found by integrating electric and magnetic Green's tensor functions over the scattering current About a 3-D conductive body near the earth's surface, interpretation using 2-D transverse electric modeling schemes can imply highly erratic low resistivities at depth. This is why these routines do not account for the effect of boundary charges. However, centrally located profiles across elongate 3-D prisms may be modeled accurately with a 2-D transverse magnetic algorithm, which implicitly includes boundary charges in its formulation. Multifrequency calculations show that apparent resistivity and impedance phase are really two complementary parameters. Hence, they should be treated simultaneously in broadband MT interpretation.

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Non-Reference P Frame Coding for Low-Delay Encoding in Internet Video Coding (IVC의 저지연 부호화 모드를 위한 비참조 P 프레임의 부호화 기법)

  • Kim, Dong-Hyun;Kim, Jin-Soo;Kim, Jae-Gon
    • Journal of Broadcast Engineering
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    • v.19 no.2
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    • pp.250-256
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    • 2014
  • Non-reference P frame coding is used to enhance coding efficiency in low-delay encoding configuration of Internet Video Coding (IVC), which is being standardized as a royalty-free video codec in MPEG. The existing method of non-reference P frame coding which was adopted in the reference Test Model of IVC (ITM) 4.0 adaptively applies a non-reference P frame with a fixed coding structure based on the magnitude of motion vectors (MVs), however, which unexpectedly degrades the coding efficiency for some sequences. In this paper, the existing non-reference P frame coding is improved by changing non-reference P frame coding structure and applying a new adaptive method using the ratio of the amount of generated bits of non-reference frames to that of reference frames as well as MVs. Experimental results show that the proposed non-reference P frame coding gives 6.6% BD-rate bit saving in average over ITM 7.0.

Backward Path Following Under a Strong Headwind for UAV (강한 맞바람이 발생 했을 때 무인기의 후진경로추종에 관한 연구)

  • Byeon, Gwang-Yeol;Park, Sanghyuk
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.42 no.5
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    • pp.376-382
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    • 2014
  • This paper presents a method to enable a UAV in autonomous flight along a desired path to follow it backwards when a strong headwind prevents the vehicle from proceeding forward. The main purpose of the reverse path following in this study is to return to a mission quickly when the wind becomes weaker. When the nonlinear path following guidance law is used, there are two reference points available in the path following. One of the two points is selected considering a flight direction for calculating a straight-line distance(L) from the vehicle to the point for the path following. An initial heading angle with respect to the wind direction determines whether the reverse path following is feasible or not at the time of the wind is generated. The result of the proposed method based on kinematic model in this study is verified through simulations implemented in Matlab.

An Application and Design of Modern Culture's Contents Ontology using Topic Map (토픽맵을 이용한 현대문학 콘텐츠 온톨로지의 적용 및 설계)

  • Jeong, Hwa-Young;Ko, In-Hwan
    • Journal of Digital Convergence
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    • v.10 no.6
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    • pp.213-218
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    • 2012
  • Modern culture has describing the year's situation along the social environment. A literary work changed as if the year's situation change. Therefore we can understand the age through the literary work and get knowledge the social request of the year's. This literary works have made a chance to know approaching more closely to user as producing media resources. Recently, IT convergence and digital convergence become a new trend to combine each other academic area and get much synergy effect. In this paper, we propose an application and design of the ontology that needs to make digital content from modern literary work's information. For this works, we specify the structure of the year's literary work and the relation of each factor. The specification method used topic map. Each relation model was specified the connection by topic vector.

A Study on Intrusion Detection in Network Intrusion Detection System using SVM (SVM을 이용한 네트워크 기반 침입탐지 시스템에서 새로운 침입탐지에 관한 연구)

  • YANG, Eun-mok;Seo, Chang-Ho
    • Journal of Digital Convergence
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    • v.16 no.5
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    • pp.399-406
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    • 2018
  • Much research has been done using the KDDCup99 data set to study intrusion detection using artificial intelligence. Previous studies have shown that the performance of the SMO (SVM) algorithm is superior. However, intrusion detection studies of new intrusion types not used in training are insufficient. In this paper, a model was created using the instances of weka's SMO and KDDCup99 training data set, kddcup.data.gz. We tested existing instances(292,300) of the corrected.gz file and new intrusions(18,729). In general, intrusion labels not used in training are not tested, so new intrusion labels were changed to normal. Of the 18,729 new intrusions, 1,827 were classified as intrusions. 1,827 instances classified as new intrusions are buffer_overflow. Three, neptune. 392, portsweep. 164, ipsweep. 9, back. 511, imap. 1, satan. Dogs, 645, nmap. 102.

A Study on Electromyogram Signals Recognition Technique using Neural Network and Genetic Algorithms (신경회로망과 유전알고리즘을 이용한 근전신호 인식기법)

  • Shin, Chul-Kyu;Lee, Sang-Min;Lee, Eun-Sil;Kwon, Jang-Woo;Jang, Young-Gun;Hong, Seung-Hong
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.11
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    • pp.176-183
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    • 1998
  • A new recognition technique using neural network coupled with Genetic Algorithms (GAs) was proposed. This technique concentrate on efficient Electromyography signal recognition through out improving neural network's several demerits. GAs paly a role of selecting Multilayer Perceptron's optimized initial connection weights by its typical global search. Electro Myography signal was pre-processed with Hidden Markov Model (HMM) in order to refect its time-varying property into input pattern except other features such as Zero Crossing Number(ZCN) and Integral Absolute Value (IAV). Results for 6 primitive motions show that the suggested technique has better performance in learning time and recognition rates than already established ordinary methods. Moreover, it performed stable recognition without convergence into a local minimum.

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Classification of Music Data using Fuzzy c-Means with Divergence Kernel (분산커널 기반의 퍼지 c-평균을 이용한 음악 데이터의 장르 분류)

  • Park, Dong-Chul
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.46 no.3
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    • pp.1-7
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    • 2009
  • An approach for the classification of music genres using a Fuzzy c-Means(FcM) with divergence-based kernel is proposed and presented in this paper. The proposed model utilizes the mean and covariance information of feature vectors extracted from music data and modelled by Gaussian Probability Density Function (GPDF). Furthermore, since the classifier utilizes a kernel method that can convert a complicated nonlinear classification boundary to a simpler linear one, he classifier can improve its classification accuracy over conventional algorithms. Experiments and results on collected music data sets demonstrate hat the proposed classification scheme outperforms conventional algorithms including FcM and SOM 17.73%-21.84% on average in terms of classification accuracy.

Sun Sensor Aided Multiposition Alignment of Lunar Exploration Rover (달 탐사 로버의 태양 센서 보조 다중위치 정렬)

  • Cha, Jaehyuck;Heo, Sejong;Park, Chan-Gook
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.45 no.10
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    • pp.836-843
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    • 2017
  • In lunar exploration, the necessity of utilizing rover is verified by the examples of the Soviet Union and China and the similar Mars missions of the United States. In order to achieve the successful management of a lunar rover, a high precision navigation technique is required, and accordingly, high precision initial alignment is essential. Even though it is general to perform initial alignment in a steady state, a multiposition alignment technique is applied when high performance is needed. On the lunar surface, however, the performance of initial alignment decreases from that on Earth, and it cannot be improved by applying multiposition alignment method owing to certain constraints of lunar environment. In this paper, a sun sensor aided multiposition alignment technique is proposed. The measurement model for a sun vector is established, and its observability analysis is performed. The performance of the proposed algorithm is verified through computer simulations, and the results show the estimation performance is improved dramatically.