公开(公告)号：US20150149191A1

公开(公告)日：2015-05-28

申请号：US14091689

申请日：2013-11-27

Applicant: Sung-Young LEE ,  Muhammad Bilal Amin

Inventor： Sung-Young LEE ,  Muhammad Bilal Amin

IPC: G06Q10/06 ,  G06Q50/22

CPC classification number: G06Q10/063 ,  G06F17/2785 ,  G06F19/00 ,  G06F19/10 ,  G06F19/28 ,  G06Q50/22 ,  G16H15/00 ,  G16H70/00

Abstract: An ontology matching apparatus for large-scale biomedical ontologies according to the present invention is provided, and the ontology matching apparatus includes a preprocessing unit configured to classify received candidate ontologies into one or more ontology subsets to generate ontology subsets, a distribution processing unit configured to divide the generated ontology subsets by virtue of a distribution algorithm, apply a matching algorithm to the divided ontology subsets to generate matching threads, and deliver the generated matching threads to individual cores of participating nodes, and an aggregating unit configured to collect and sum matching results generated by the individual cores performing matching operations based on the matching threads to generate an ontology mapping.

Abstract translation: 本发明提供了一种用于大规模生物医学本体的本体匹配装置，本体匹配装置包括：预处理单元，被配置为将接收到的候选本体分类成一个或多个本体子集以产生本体子集;分配处理单元， 通过分布算法对生成的本体子集进行划分，对分割的本体子集应用匹配算法以生成匹配线程，并将生成的匹配线程传递给参与节点的各个核心;以及聚合单元，用于收集和求和匹配结果 由各个核心基于匹配线程执行匹配操作生成本体映射。

公开(公告)号：US20130050922A1

公开(公告)日：2013-02-28

申请号：US13561166

申请日：2012-07-30

Applicant: Sung-Young LEE ,  Ki-Deuk KIM ,  Jung-Woong HYUN

Inventor： Sung-Young LEE ,  Ki-Deuk KIM ,  Jung-Woong HYUN

IPC: G06F1/16

CPC classification number: G06F1/1656 ,  G06F2200/1632 ,  H04M1/026

Abstract: An apparatus for mounting in a secure manner a stylus pen in an information device, in which there are a casing and the stylus pen. A guide unit having an inlet and an outlet is configured to have an opened top at the inlet and a closed bottom at the outlet, extended along a length direction of the casing, for accommodating the stylus pen.

Abstract translation: 一种用于将信号笔安全地安装在信息装置中的装置，其中存在壳体和触控笔。 具有入口和出口的引导单元被配置为在入口处具有敞开的顶部，并且在出口处具有沿壳体的长度方向延伸的封闭底部，用于容纳触针笔。

公开(公告)号：US20140111418A1

公开(公告)日：2014-04-24

申请号：US13905796

申请日：2013-05-30

Applicant: Sung-Young LEE ,  Man-Hyung HAN ,  Young-Tack PARK

Inventor： Sung-Young LEE ,  Man-Hyung HAN ,  Young-Tack PARK

IPC: G06F3/03

CPC classification number: G06F1/1694 ,  G06F3/0346 ,  G06F21/316 ,  G06F2203/0381 ,  G10H2220/351 ,  G10H2220/395 ,  G10H2230/015 ,  H04M1/72569 ,  H04M2250/10

Abstract: There is provided a method for recognizing a user context using multimodal sensors, and the method includes classifying accelerometer data by extracting candidates for movement feature from the accelerometer data collected from an accelerometer, selecting one or more movement features from the extracted candidates for movement feature based on relevance and redundancy thereof, and then inferring a user's movement type based on the selected movement features using a first time-series probability model; classifying audio data by extracting surrounding features from the audio data collected from an audio sensor and inferring the user's surrounding type based on the extracted surrounding features; and recognizing a user context by recognizing the user context based on either of the movement type or the surrounding type.

Abstract translation: 提供了一种用于使用多模式传感器识别用户上下文的方法，并且该方法包括通过从从加速度计收集的加速度计数据中提取运动特征的候选来对加速度计数据进行分类，从所提取的候选中选择一个或多个运动特征，用于运动特征 在其相关性和冗余度上，然后使用第一时间序列概率模型，基于所选择的运动特征来推断用户的运动类型; 通过从音频传感器收集的音频数据中提取周围特征并基于所提取的周围特征推断用户的周围类型来对音频数据进行分类; 以及基于所述运动类型或周围类型中的任一者来识别用户上下文来识别用户上下文。

公开(公告)号：US20130124438A1

公开(公告)日：2013-05-16

申请号：US13307219

申请日：2011-11-30

Applicant: Sung-Young LEE ,  Young-Koo Lee ,  La The Vinh

Inventor： Sung-Young LEE ,  Young-Koo Lee ,  La The Vinh

IPC: G06F15/18

CPC classification number: G06K9/00302 ,  G06K9/00718 ,  G06N20/00 ,  G10L15/14

Abstract: Provided is a method of recognizing patterns based on a hidden conditional random fields model to which full-Gaussian covariance has been applied. The method includes dividing a training input signal and outputting a frame sequence, extracting a feature vector from the frame sequence, calculating a parameter through a conditional random fields model to which Gaussian covariance has been applied using the feature vector, receiving, by the hidden conditional random fields model to which the parameter has been applied, a feature vector extracted from a test input signal measured for an actual pattern to infer a label indicating the actual pattern, and proposing a method of calculating gradient values for a conditional probability vector, a transition probability vector, a Gaussian mixture weight, a mean of Gaussian distributions, and covariance of the Gaussian distributions, as an analysis method.

Abstract translation: 提供了一种基于已应用全高斯协方差的隐藏条件随机场模型识别模式的方法。 该方法包括分割训练输入信号并输出​​帧序列，从帧序列中提取特征向量，通过使用特征向量应用高斯协方差的条件随机场模型计算参数，通过隐藏条件 从应用了参数的随机场模型，从针对实际模式测量的测试输入信号提取的特征向量，推断出表示实际模式的标签，以及提出计算条件概率向量的梯度值的方法 概率向量，高斯混合权重，高斯分布的平均值和高斯分布的协方差作为分析方法。

公开(公告)号：US20110108795A1

公开(公告)日：2011-05-12

申请号：US12929118

申请日：2011-01-03

Applicant: Dong-Won KIM ,  Dong-Gun PARK ,  Sung-Young LEE ,  Yang-Kyu CHOI ,  Lee-Eun YU

Inventor： Dong-Won KIM ,  Dong-Gun PARK ,  Sung-Young LEE ,  Yang-Kyu CHOI ,  Lee-Eun YU

IPC: H01L29/66

CPC classification number: H01L51/0595 ,  B82Y10/00 ,  G11C13/0014 ,  H01L51/102 ,  Y10T428/24

Abstract: Molecular devices and methods of manufacturing the molecular device are provided. The molecular device may include a lower electrode on a substrate and a self-assembled monolayer on the lower electrode. After an upper electrode is formed on the self-assembled monolayer, the self-assembled monolayer may be removed to form a gap between the lower electrode and the upper electrode. A functional molecule having a functional group may be injected into the gap.

公开(公告)号：US20130132312A1

公开(公告)日：2013-05-23

申请号：US13315427

申请日：2011-12-09

Applicant: Sung-Young LEE ,  Asad Masood Khattak

Inventor： Sung-Young LEE ,  Asad Masood Khattak

IPC: G06N3/12 ,  G06N5/04

CPC classification number: G16H50/20 ,  G06F19/00

Abstract: Provided is a data processing method for clinical decision support system. The data processing method provides an algorithm capable of performing parsing based on an Ontology technique and automatically updating rule database in order to reduce time and labor overloads accompanied by update of the rule database. According to an aspect, the data processing method includes inferring input data having a natural language format based on an Ontology technique to recognize at least one input rule included in the input data; inferring storage data having a natural language format and stored in rule database based on the Ontology technique to recognize at least one storage rule associated with the input rule from the storage data; comparing the input rule to the storage rule using a Self Evolutionary Rule-base algorithm; and updating the storage data stored in the rule database to the input data according to the result of the comparison.

Abstract translation: 提供了一种用于临床决策支持系统的数据处理方法。 数据处理方法提供了一种能够基于本体技术执行解析并自动更新规则数据库的算法，以便减少伴随规则数据库更新的时间和劳动力过载。 根据一方面，数据处理方法包括基于本体技术推断具有自然语言格式的输入数据，以识别包括在输入数据中的至少一个输入规则; 推断具有自然语言格式的存储数据并基于本体技术存储在规则数据库中，以从存储数据识别与输入规则相关联的至少一个存储规则; 使用自我进化规则库算法将输入规则与存储规则进行比较; 以及根据比较结果将存储在规则数据库中的存储数据更新为输入数据。

公开(公告)号：US20110077919A1

公开(公告)日：2011-03-31

申请号：US12886800

申请日：2010-09-21

Applicant: Sung-Young LEE ,  Young-Koo LEE ,  La The VINH ,  Le Xuan HUNG ,  Ngo Quoc HUNG ,  Hyoung-Il KIM ,  Man-Hyung HAN

Inventor： Sung-Young LEE ,  Young-Koo LEE ,  La The VINH ,  Le Xuan HUNG ,  Ngo Quoc HUNG ,  Hyoung-Il KIM ,  Man-Hyung HAN

IPC: G06F7/60 ,  G06F17/11

CPC classification number: G06K9/6297 ,  G06K9/00771

Abstract: A method of recognizing an activity on the basis of a semi-Markov conditional random field (CRF) model is provided. The method includes segmenting an input signal measured by an accelerometer to output frame sequences, extracting training feature vectors from the frame sequences, building a codebook containing kernel vectors from the training feature vectors; quantizing vector sequences into discrete symbol sequences, using linear chain semi-Markov CRF model to compute the likelihood of a label given its corresponding symbol sequence.

Abstract translation: 提供了一种基于半马尔科夫条件随机场（CRF）模型识别活动的方法。 该方法包括对由加速度计测量的输入信号进行分割以输出帧序列，从帧序列中提取训练特征向量，从训练特征向量建立包含核向量的码本; 将矢量序列量化为离散符号序列，使用线性链半马尔科夫CRF模型来计算给定其对应符号序列的标签的可能性。