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    • 5. 发明授权
    • Activity monitoring system and method for transmitting information for activity monitoring
    • 活动监测系统和传输信息的方法进行活动监测
    • US08620993B2
    • 2013-12-31
    • US12505566
    • 2009-07-20
    • Min Ho KimJae Won JangHo Youl JungSa Kwang SongSoo Jun ParkSeon Hee Park
    • Min Ho KimJae Won JangHo Youl JungSa Kwang SongSoo Jun ParkSeon Hee Park
    • G06F15/16
    • H04L67/125A61B5/0002G05B15/02G06F19/00G06F19/3418H04L67/22
    • An activity monitoring system and method are disclosed to reduce the size of an activity sensor device to reduce its power consumption and smoothly transmit activity and occupancy information from the activity sensor device and an occupancy sensor device to an activity monitoring server to monitor an individual's activity and occupancy information. The activity monitoring system includes: an activity sensor device configured to detect a physical activity of a user, classify the detected physical activity, and transmit activity classification information as a result along with user identification information; one or more occupancy sensor devices configured to receive the activity classification information and the individual's identification information from the activity sensor device, and transmit the received information along with occupancy information; and an activity monitoring server configured to manage the activity classification information, the occupancy information, and the individual's identification information received from the occupancy sensor devices.
    • 公开了一种活动监测系统和方法,以减少活动传感器装置的尺寸以减少其功率消耗,并将活动和占用信息从活动传感器装置和占用传感器装置平滑地传送到活动监测服务器以监测个体的活动, 占用信息。 活动监视系统包括:活动传感器装置,被配置为检测用户的身体活动,对检测到的身体活动进行分类,并且随着用户识别信息一起发送活动分类信息; 一个或多个占用传感器装置,被配置为从活动传感器装置接收活动分类信息和个体的识别信息,并将所接收的信息与占有信息一起发送; 以及活动监视服务器,被配置为管理从占用传感器装置接收的活动分类信息,占用信息和个人的识别信息。
    • 7. 发明授权
    • Method and system for sensing abnormal signs in daily activities
    • 日常活动中异常体征的检测方法和系统
    • US07847682B2
    • 2010-12-07
    • US12105386
    • 2008-04-18
    • Ho Youl JungSoo Jun ParkSeon Hee Park
    • Ho Youl JungSoo Jun ParkSeon Hee Park
    • G08B19/00
    • G06Q10/00
    • There are provided a method and system for sensing abnormal signs in daily activities, the method comprising, at the system, sensing the daily activities, reading previously stored daily activity information, generating a daily activity sequence based thereon, sensing the abnormal signs from the daily activity sequence by using a preset sequence alignment algorithm, and providing the sensed abnormal signs to a user. As described above, the abnormal signs, which should be checked to provide care services, are sensed via changes in a daily activity pattern and added to a care service system that will be installed in welfare facilities for the aged or a home of a solitary old person, thereby effectively sensing the abnormal signs in daily activities of the aged.
    • 提供了一种用于感测日常活动中的异常体征的方法和系统,所述方法包括在系统中感测日常活动,读取先前存储的日常活动信息,基于此产生日常活动序列,从日常活动中感测异常体征 通过使用预设的序列比对算法,向用户提供感测到的异常标志。 如上所述,通过日常活动模式的变化来检测应当检查以提供护理服务的异常体征,并将其添加到将被安装在老年人的福利设施或孤独老人的家中的护理服务系统 从而有效地感知老年人日常活动中的异常体征。
    • 9. 发明授权
    • Method and system for predicting gene pathway using gene expression pattern data and protein interaction data
    • 使用基因表达模式数据和蛋白质相互作用数据预测基因途径的方法和系统
    • US07848890B2
    • 2010-12-07
    • US11297008
    • 2005-12-07
    • Ho Youl JungMi Young ShinSun Hee Park
    • Ho Youl JungMi Young ShinSun Hee Park
    • G01N33/48
    • G06F19/26G06F19/12G06F19/20
    • Provided are a method and system for predicting pathways of genes that serve the same biological purpose using gene expression pattern data and protein interaction data. The method of predicting a gene pathway includes: a first step of generating partial pathways from gene expression pattern data by using a pathway extraction algorithm, and matching the partial pathways to express them as a graph; a second step of generating partial pathways from protein interaction data by using a pathway extraction algorithm, and matching the partial pathways to express them as a graph; and a third step of combining a graph made in the first step and a graph made in the second step by using a graph matching algorithm to make a combined graph.
    • 提供了使用基因表达模式数据和蛋白质相互作用数据来预测服务于相同生物学目的的基因途径的方法和系统。 预测基因途径的方法包括:通过使用途径提取算法从基因表达模式数据产生部分途径的第一步骤,并且匹配部分途径以将其表示为图; 通过使用途径提取算法从蛋白质相互作用数据产生部分路径的第二步骤,并且将部分路径匹配以将其表示为图; 以及第三步骤,通过使用图匹配算法来组合在第一步骤中制作的图形和第二步骤中制作的图形以组合图形。