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公开(公告)号：KR101200494B1
公开(公告)日：2012-11-12
申请号：KR1020100109954
申请日：2010-11-05
Applicant: 목포대학교산학협력단
IPC: H04N19/40
Abstract: Ｈ.264에서 MPEP-2로의 트랜스코딩 방법이 개시된다. 이 Ｈ.264에서 ＭＰＥＰ-2로의 트랜스코딩 방법은 선박-육지 간 실시간 통신에서 다양한 콘텐츠를 제공하는 방송국 및 콘텐츠 제공자는 위성 통신을 통하여 H.264 표준으로 압축한 동영상을 실시간으로 MPEG-2표준 디바이스를 사용 중인 선박에 원활한 서비스를 제공할 수 있게 된다.
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公开(公告)号：KR1020120048367A
公开(公告)日：2012-05-15
申请号：KR1020100109966
申请日：2010-11-05
Applicant: 목포대학교산학협력단
Abstract: PURPOSE: A wireless indoor location measuring method based on KNN(k-nearest Neighbor) and PCM(Possibilistic C-Mean) is provided to form a wireless fingerprint type database by measuring a signal to noise ratio from several APs. CONSTITUTION: The first electric wave feature data is stored in a database with a wireless fingerprint type(S110). k reference points are selected by using KNN(S120). A group of the first electric wave feature data of the k reference points is formed(S130). A group of a location coordinate of the k reference points is formed(S140). A group including the reference points included in the first electric wave feature data based group and the reference point location coordinate based group is formed(S150). A group with the minimum distance square value of a group central vector and the first electric wave feature data is selected(S160). The average of the location coordinate of the reference points belonging to the selected group is produced. The location of a terminal is estimated(S170).
Abstract translation: 目的：提供一种基于KNN（k-最近邻）和PCM（可能性C均值）的无线室内位置测量方法，通过测量多个AP的信噪比来形成无线指纹类型数据库。 规定：第一电波特征数据存储在无线指纹类型的数据库中（S110）。 使用KNN（S120）选择k个参考点。 形成一组k个基准点的第一电波特征数据（S130）。 形成一组k个基准点的位置坐标（S140）。 形成包括在基于第一电波特征数据的组和基准点位置坐标组中的参考点的组（S150）。 选择具有组中心矢量的最小距离平方值和第一电波特征数据的组（S160）。 产生属于所选组的参考点的位置坐标的平均值。 估计终端的位置（S170）。
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公开(公告)号：KR1020120047645A
公开(公告)日：2012-05-14
申请号：KR1020100109329
申请日：2010-11-04
Applicant: 목포대학교산학협력단
IPC: A61B5/0476 , B63H25/04 , B63H25/08
Abstract: PURPOSE: A system for controlling a ship steering gear is provided to reduce the burden of an operator by estimating an operation behavior using brain waves of the operator and controlling a ship steering gear according to the estimated result. CONSTITUTION: A brain wave measuring unit(110) measures brain waves of an operator. A brain wave analyzer(120) grasps the movement of the operator by analyzing the measured brain waves. A database(130) includes SVM algorithm. A ship steering control unit(140) controls a ship according to the movement of the operator.
Abstract translation: 目的：提供一种用于控制船舶舵机的系统，以通过使用操作者的脑波估计操作行为并根据估计结果控制船舵机来减轻操作者的负担。 构成：脑波测量单元（110）测量操作者的脑波。 脑波分析仪（120）通过分析测得的脑电波来掌握操作者的运动。 数据库（130）包括SVM算法。 船舶转向控制单元根据操作员的移动来控制船舶。
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公开(公告)号：KR1020120048366A
公开(公告)日：2012-05-15
申请号：KR1020100109965
申请日：2010-11-05
Applicant: 목포대학교산학협력단
Abstract: PURPOSE: A PFCM(Possibilistic Fuzzy C-Means) and KNN(K-Nearest Neighbor) grouping based mixed wireless indoor positioning method is provided to measure a signal noise ratio received from a plurality of access points, thereby building a wireless fingerprint type database. CONSTITUTION: A database is built with first propagation characteristic value data in a wireless fingerprint mode(S110). A standard point is searched using a KNN(K-Nearest Neighbor)/PFCM(Possibilistic Fuzzy C-Means) mixed technique. k standard points are selected using a KNN technique(S120). A group of the first propagation characteristic value data of the k standard points is formed(S130). A group which has a minimum distance square sum with respect to the first propagation characteristic value data is selected(S140). An average of standard point position coordinates belonged to the selected group is calculated. The location of a terminal is estimated(S150).
Abstract translation: 目的：提供一种基于混合无线室内定位方法的PFCM（可能模糊C均值）和KNN（K-最近邻）分组，以测量从多个接入点接收的信号噪声比，从而构建无线指纹类型数据库。 构成：以无线指纹模式中的第一传播特征值数据构建数据库（S110）。 使用KNN（K最近邻）/ PFCM（可能模糊C均值）混合技术搜索标准点。 使用KNN技术选择k个标准点（S120）。 形成k个标准点的第一传播特性值数据的一组（S130）。 选择相对于第一传播特性值数据具有最小距离平方和的组（S140）。 计算属于所选组的标准点位置坐标的平均值。 估计终端的位置（S150）。
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公开(公告)号：KR1020120048357A
公开(公告)日：2012-05-15
申请号：KR1020100109954
申请日：2010-11-05
Applicant: 목포대학교산학협력단
IPC: H04N19/40
CPC classification number: H04N19/40 , H04N19/139 , H04N19/513
Abstract: PURPOSE: A transcoding method from H.264 to MPEG2 is provided to offer a plurality of video content and video data transmitted in real time from a broadcasting station to a ship by satellite communication. CONSTITUTION: A decoder(100) decodes an input bit stream encoded by a specific standard format. The specific standard format includes H264/AVC(Advanced Video Coding). An encoder(200) encodes the output of a loop filter(140) of the decoder. The encoder generates an output bit stream of a specific standard format such as MPEG2 standard format. A motion vector is detected by using a motion vector of a variable block.
Abstract translation: 目的：提供从H.264到MPEG2的代码转换方法，以便通过卫星通信提供从广播站到船舶实时传输的多个视频内容和视频数据。 构成：解码器（100）对由特定标准格式编码的输入比特流进行解码。 具体的标准格式包括H264 / AVC（高级视频编码）。 编码器（200）对解码器的环路滤波器（140）的输出进行编码。 编码器生成特定标准格式的输出比特流，例如MPEG2标准格式。 通过使用可变块的运动矢量来检测运动矢量。
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Patent Agency Ranking
公开(公告)号：KR1020110116565A
公开(公告)日：2011-10-26
申请号：KR1020100036049
申请日：2010-04-19
Applicant: 목포대학교산학협력단
CPC classification number: G06F17/16
Abstract: 본 발명은 베이지안 알고리즘을 이용한 실내 측위 방법에 관한 것으로서, 본 발명에 따른 복수의 엑세스 포인트(AP : Access Point)가 설치된 무선환경에서 베이지안 알고리즘을 이용한 실내 측위 방법은 위치 설정된 레퍼런스 포인트(RP : Reference Point)로부터 수집된 신호 강도(RSS) 데이터를 핑거프린트(FingerPrint) 방식으로 데이터베이스화하는 단계, 그리고 베이지안 학습의 사후 확률 분포를 이용한 NBC(Naive Bayesian Classifier)와 퍼지 군집화의 유사도 행렬을 사용하여 무선랜 실내 위치를 추정하고 결정하는 단계를 포함한다.
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公开(公告)号：KR1020120048376A
公开(公告)日：2012-05-15
申请号：KR1020100109976
申请日：2010-11-05
Applicant: 목포대학교산학협력단
Abstract: PURPOSE: A wireless indoor location measuring method based on a PFCM group using KNN and GG method is provided to estimate a location of a terminal by using an existing AP(Access Point). CONSTITUTION: The first electric wave feature data is stored in a database with a wireless fingerprint method(S110). K reference points are selected by using a KNN method(S120). The k reference points have a first electric wave feature value near a second electric wave feature value. A group of the first electric wave feature data of the k reference points is formed by using a GG method(S130). A group of a minimum distance between a group central vector and the first electric wave feature data is selected(S140). An average of a location coordinate of the reference points belong to the group is produced. A location of a terminal is estimated(S150).
Abstract translation: 目的：提供基于使用KNN和GG方法的PFCM组的无线室内位置测量方法，以通过使用现有AP（接入点）来估计终端的位置。 规定：第一电波特征数据以无线指纹法存储在数据库中（S110）。 通过使用KNN方法选择K个参考点（S120）。 k个参考点具有靠近第二电波特征值的第一电波特征值。 通过使用GG方法形成k个参考点的一组第一电波特征数据（S130）。 选择组中心向量与第一电波特征数据之间的最小距离的组（S140）。 产生属于该组的参考点的位置坐标的平均值。 估计终端的位置（S150）。
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8.发明公开
公开(公告)号：KR1020120048373A
公开(公告)日：2012-05-15
申请号：KR1020100109972
申请日：2010-11-05
Applicant: 목포대학교산학협력단
Abstract: PURPOSE: A wireless indoor location measuring method based on a FCM(Fuzzy C-Mean) group using KNN(k-Nearest Neighbor) and a GK(Gustafson-Kessel) method is provided to improve database searching efficiency. CONSTITUTION: The first electric wave feature data is stored in a database with a wireless fingerprint method(S110). K reference points are selected by using a KNN method(S120). A group of the first electric wave feature data of the k reference points is formed by using an FCM method(S130). A group with the minimum GK distance the first electric wave feature data and the group central vector is selected(S140). The average of the location coordinate of the reference points belonging to the group is produced. The location of the terminal is estimated(S150).
Abstract translation: 目的：提供基于使用KNN（k-最近邻）和GK（Gustafson-Kessel）方法的FCM（Fuzzy C-Mean）组的无线室内位置测量方法，以提高数据库搜索效率。 规定：第一电波特征数据以无线指纹法存储在数据库中（S110）。 通过使用KNN方法选择K个参考点（S120）。 通过使用FCM方法形成k个参考点的一组第一电波特征数据（S130）。 选择具有最小GK距离的组，第一电波特征数据和组中心矢量被选择（S140）。 产生属于该组的参考点的位置坐标的平均值。 估计终端的位置（S150）。
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9.发明公开
公开(公告)号：KR1020120048356A
公开(公告)日：2012-05-15
申请号：KR1020100109953
申请日：2010-11-05
Applicant: 목포대학교산학협력단 , 주식회사 대문정보
Abstract: PURPOSE: A PFCM(Possibilistic Fuzzy C-Means) grouping based mixed wireless indoor positioning method which uses KNN(K-Nearest Neighbor) and GK(Gustafson-Kessel) methods is provided to measure a signal noise ratio received from a plurality of access points in a training step, thereby building a wireless fingerprint type database. CONSTITUTION: A database is built with first propagation characteristic value data in a wireless fingerprint mode(S110). A standard point is searched using a PFCM(Possibilistic Fuzzy C-Means) mixed technique. k standard points are selected using a KNN(K-Nearest Neighbor) technique(S120). A group of the first propagation characteristic value data of the k standard points is formed(S130). A group which has a minimum GK(Gustafson-Kessel) distance with respect to the first propagation characteristic value data and a group center vector are selected(S140). The average of standard point position coordinates belonged to the selected group is calculated. The position of a terminal is estimated(S150).
Abstract translation: 目的：提供一种使用KNN（K-最近邻）和GK（Gustafson-Kessel）方法的PFCM（可能模糊C均值）分组混合无线室内定位方法，用于测量从多个接入点接收的信号噪声比 在培训步骤中，从而构建无线指纹类型数据库。 构成：以无线指纹模式中的第一传播特征值数据构建数据库（S110）。 使用PFCM（可能性模糊C均值）混合技术搜索标准点。 使用KNN（K最近邻）技术选择k个标准点（S120）。 形成k个标准点的第一传播特性值数据的一组（S130）。 选择相对于第一传播特性值数据和组中心向量具有最小GK（Gustafson-Kessel）距离的组（S140）。 计算属于所选组的标准点位置坐标的平均值。 估计终端的位置（S150）。
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公开(公告)号：KR1020110116840A
公开(公告)日：2011-10-26
申请号：KR1020100036489
申请日：2010-04-20
Applicant: 목포대학교산학협력단
Abstract: 본 발명은 사례기반추론을 이용한 상황인식기반 적조 예측 시스템에 대하여 개시한다. 본 발명의 일면에 따른 적조 예측 시스템은, 과거에 발생한 적조의 과거 사례들의 데이터를 저장하는 데이터베이스; 감지지역에 대해 감지된 현 사례의 데이터를 입력받는 입력부; 상기 과거 사례들의 데이터와 상기 현 사례의 데이터와의 유사도를 측정하여 유사도가 상대적으로 높은 사례를 선별하는 추론부; 상기 유사도가 상대적으로 높은 과거 사례의 데이터와 상기 현 사례의 데이터를 연관시켜 표시하거나, 상기 감지지역에 대한 적조의 발생 여부를 표시하는 표시부를 포함하는 것을 특징으로 한다.
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