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Patent Agency Ranking
公开(公告)号：KR101503466B1
公开(公告)日：2015-03-19
申请号：KR1020130134941
申请日：2013-11-07
Applicant: 목포대학교산학협력단
IPC: H04B17/00 , H04B1/7073
CPC classification number: H04B1/7073 , H04B1/7097
Abstract: 본 발명은 직접 수열 확산 대역 시스템의 고속 부호 획득을 위한 순차 추정 기법들의 성능 분석 방법에 관한 것으로서, 구체적으로 RASE, SASE, RSSE 기법들에 대한 칩 추정 성능을 비교하여 고속 부호 획득을 위한 방법에 관한 것이다.
본 발명은 직접 수열 확산 대역 시스템의 고속 부호 획득을 위한 순차 추정 기법들의 성능 분석 방법으로 RASE, SASE, RSSE 기법들의 코드 길이를 같게 설정하여 모니터링 함으로써 상기 RASE, SASE, RSSE 기법들의 신호 획득 성능을 상대적으로 비교 분석한다.Abstract translation: 本发明涉及一种用于直接序列扩频系统的快速码获取的顺序估计方法的性能分析方法，更具体地说，涉及一种通过将芯片估计性能与RASE，SASE， 和RSSE方案。 根据本发明的用于直接序列扩频系统的快速码采集的顺序估计方案的性能分析方法通过监视RASE，SASE和RSSE方案的信号采集性能来比较和分析信号采集性能， 同样设置RASE，SASE和RSSE方案的代码长度。
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公开(公告)号：KR1020150019832A
公开(公告)日：2015-02-25
申请号：KR1020130097200
申请日：2013-08-16
Applicant: 목포대학교산학협력단
Abstract: 본 발명은 선박의 다수의 센서로부터 수신되는 센서 정보 및 휴대용 장치(Handheld Device)를 통해 사용자에 의해 입력되는 입력 정보를 수신하여 데이터베이스에 저장하는 단계, 및 저장된 상기 센서 및 입력 정보와 기설정된 선박검사 알고리즘을 이용하여 상기 선박의 상태를 검사하는 선박검사 동작을 수행하는 단계를 포함하는 선박검사 자동화 시스템의 동작 방법에 관한 것이다.
Abstract translation: 本发明涉及一种用于操作船舶检查自动化系统的方法，包括以下步骤：通过接收由用户通过手持设备输入的输入信息和从多个传感器接收的传感器信息来将输入信息存储在数据库中 的船 并使用预设的船舶检查算法和存储的传感器和输入信息执行船舶检查操作来检查船舶的状态。
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公开(公告)号：KR1020140046575A
公开(公告)日：2014-04-21
申请号：KR1020120110835
申请日：2012-10-05
Applicant: 목포대학교산학협력단
Abstract: The present invention relates to a method for clustering of a vessel USN with designation of a cluster head in a vessel USN system, wherein the method comprises the steps of receiving information on residual energy from multiple nodes and a cluster head after one cycle expires; and designating a cluster head among the nodes based on the information on residual energy. According to the present invention, energy consumption on communications among the nodes can be reduced since the designation of a cluster head based on residual energy is used. And, the cluster head is not replaced frequently, thereby providing economic feasibility and stable communications among the nodes. In addition, when a fault occurs in the cluster head of the vessel USN, the entire re-clustering can be avoided and rearrangement of overlapping cluster heads is not required. Moreover, it is possible to reduce inconvenience resulting from communications required for exchange of state information among cluster heads. [Reference numerals] (AA) Start; (BB) End; (S210) Receive residual energy; (S220) Designate a cluster head
Abstract translation: 本发明涉及一种用于在船只USN系统中指定簇头的船舶USN的聚类方法，其中所述方法包括以下步骤：在一个周期到期之后从多个节点和簇头接收关于剩余能量的信息; 并根据剩余能量信息指定节点之间的簇头。 根据本发明，由于使用基于剩余能量的簇头的指定，因此可以减少节点之间的通信的能量消耗。 而且，簇头不经常更换，从而提供节点之间的经济可行性和稳定的通信。 另外，当船只USN的簇头发生故障时，可以避免整个重新聚集，不需要重叠的簇头。 此外，可以减少在簇头之间交换状态信息所需的通信所产生的不便。 （附图标记）（AA）开始; （BB）结束; （S210）接收剩余能量; （S220）指定簇头
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公开(公告)号：KR1020130012811A
公开(公告)日：2013-02-05
申请号：KR1020110074214
申请日：2011-07-26
Applicant: 목포대학교산학협력단
CPC classification number: H04N5/144 , H04N1/40012
Abstract: PURPOSE: An intelligent image monitoring method for ship is provided to supply the convenience and expandability of a hardware configuration in the implementation of a monitoring system by detecting movement by an image monitoring system by using an image. CONSTITUTION: An obtained image frame is converted into a gray scale. After the binarization of the converted image frame, a GMM(Gaussian Mixture Model) is applied. A value having the change of pixel among result values caused by the application of the GMM is determined as a white pixel value. The white pixel value is counted. The completed frame of the next page is inputted. The white pixel value of the image frame is counted. The movement is detected in comparison with a count value and a threshold value. [Reference numerals] (AA) Setting image compression; (BB) Inputting image data; (CC) Completing one sheet of an image frame; (DD) Registering a call-back function; (EE) Grayscale; (FF) Binarization; (GG) Applying a GMM filter; (HH) Correcting a threshold value; (II) Calculating the average of Avg[19]; (JJ) Storing the current pixel value in Avg[19]; (KK) Event processing; (LL) Counted pixel value > Threshold value; (MM) Counting a white pixel value
Abstract translation: 目的：提供一种用于船舶的智能图像监控方法，通过使用图像检测图像监控系统的运动，提供硬件配置在监控系统实现中的便利性和可扩展性。 构成：将获得的图像帧转换为灰度级。 在转换的图像帧二进制化之后，应用GMM（高斯混合模型）。 具有由应用GMM引起的结果值之间的像素变化的值被确定为白色像素值。 计数白色像素值。 输入下一页的完成帧。 对图像帧的白色像素值进行计数。 与计数值和阈值相比较，检测出移动。 （附图标记）（AA）设定图像压缩; （BB）输入图像数据; （CC）完成一张图像帧; （DD）注册回叫功能; （EE）灰度; （FF）二元化; （GG）应用GMM滤波器; （HH）校正阈值; （二）计算平均值[19]; （JJ）将当前像素值存储在Avg [19]中; （KK）事件处理; （LL）计数像素值>阈值; （MM）计数一个白色像素值
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公开(公告)号：KR1020120136564A
公开(公告)日：2012-12-20
申请号：KR1020110055569
申请日：2011-06-09
Applicant: 목포대학교산학협력단
Abstract: PURPOSE: A red tidal current recognition method using PCA(principal component analysis) and roundness is provided to recognize images without having a reference point of a red tidal image by using entropy and the roundness. CONSTITUTION: A vector set of a learning image is constructed by learning a red tide image through PCA(100). A candidate recognition image group is constructed by calculating the roundness of the learning image and inputted image and selecting an image which is close to the roundness(200). Entropy of an image in the candidate recognition image group is calculated(300). The entropy selects a recognition image by calculating the entropy of images in the candidate recognition image group. [Reference numerals] (100) Principal component analysis; (200) Calculating roundness; (300) Calculating entropy; (AA) Learning image; (BB) Input image
Abstract translation: 目的：提供使用PCA（主成分分析）和圆度的红潮流识别方法，通过使用熵和圆度来识别图像而不具有红色潮汐图像的参考点。 构成：通过PCA（100）学习红潮图像构建学习图像的向量集。 通过计算学习图像和输入图像的圆度并选择接近圆度（200）的图像来构造候选识别图像组。 计算候选识别图像组中的图像的熵（300）。 熵通过计算候选识别图像组中的图像的熵来选择识别图像。 （附图标记）（100）主成分分析; （200）计算圆度; （300）计算熵; （AA）学习形象; （BB）输入图像
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