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    • 4. 发明申请
    • DISEASE MARKER DETECTION KIT AND DISEASE MARKER DETECTION METHOD
    • 疾病标记检测试剂盒和疾病标记检测方法
    • WO2011162563A3
    • 2012-05-31
    • PCT/KR2011004610
    • 2011-06-24
    • KOREA RES INST OF STANDARDSLEE TAE GEOLCHO YOUNG-LAISON MI YOUNG
    • LEE TAE GEOLCHO YOUNG-LAISON MI YOUNG
    • G01N33/68G01N23/225G01N33/573G01N33/574
    • G01N33/57488G01N33/553G01N33/6848
    • A detection kit according to the present invention is a disease detection kit which is used together with secondary ion mass spectrometry to detect the disease marker contained in a biological sample. The detection kit comprises: a base on which a noble metal film is formed; a reactant which contains a peptide that specifically reacts with the disease marker; first storage means in which the reactant is stored; a sample which contains the biological sample of a possible disease carrier; second storage means in which the sample is stored; mixing means for mixing the reactant and the sample to produce a detection substance which contains the peptide which specifically reacts with the disease marker contained in the biological sample; and contact means for enabling the detection substance produced by the mixing means to contact the base, so as to bind the specifically reacted material to the noble metal film of the base.
    • 根据本发明的检测试剂盒是与二次离子质谱法一起使用以检测生物样品中所含的疾病标志物的疾病检测试剂盒。 检测试剂盒包括:形成有贵金属膜的基材; 含有特异性与疾病标记反应的肽的反应物; 存储反应物的第一储存装置; 包含可能的疾病携带者的生物样品的样品; 存储样品的第二存储装置; 混合装置,用于混合反应物和样品以产生检测物质,其含有与生物样品中所含的疾病标志物特异性反应的肽; 以及用于使得由混合装置产生的检测物质能够接触基底的接触装置,以便将特异反应的材料与基底的贵金属膜结合。
    • 9. 发明申请
    • SYSTEM AND METHOD FOR ESTIMATING LONG TERM CHARACTERISTICS OF BATTERY
    • 用于估计电池长期特性的系统和方法
    • WO2009035288A3
    • 2009-05-07
    • PCT/KR2008005403
    • 2008-09-12
    • LG CHEMICAL LTDSONG HYUN-KONCHO JEONG-JUCHOO YEON-UKSON MI-YOUNGLEE HO-CHUN
    • SONG HYUN-KONCHO JEONG-JUCHOO YEON-UKSON MI-YOUNGLEE HO-CHUN
    • H01M10/48
    • H01M10/482G01R31/3651G01R31/3679H01M10/48
    • A system includes a learning data input unit for receiving initial and long term characteristic learning data of a battery to be a learning object; a measurement data input unit for receiving initial characteristic measurement data of a battery to be an object for long term characteristic estimation; an artificial neural network operation unit for converting the learning data into first and second data structures, allowing an artificial neural network to learn the learning data based on each data structure, converting the measurement data into first and second data structures, and individually applying the learned artificial neural network corresponding to each data structure to calculate and output long term characteristic estimation data based on each data structure; and a long term characteristic evaluation unit for calculating an error of the estimation data of each data structure and determining reliability of the estimation data depending on error.
    • 一种系统,包括:学习数据输入单元,用于接收作为学习对象的电池的初始和长期特性学习数据; 测量数据输入单元,用于接收作为用于长期特性估计的对象的电池的初始特性测量数据; 人工神经网络操作单元,用于将学习数据转换为第一和第二数据结构,允许人造神经网络基于每个数据结构学习学习数据,将测量数据转换为第一和第二数据结构,并且单独应用学习 根据每个数据结构计算并输出长期特征估计数据的人工神经网络; 以及长期特性评估单元,用于计算每个数据结构的估计数据的误差并且根据误差确定估计数据的可靠性。
    • 10. 发明申请
    • SYSTEM AND METHOD FOR ESTIMATING LONG TERM CHARACTERISTICS OF BATTERY
    • 用于估计电池长期特性的系统和方法
    • WO2009025512A3
    • 2009-04-23
    • PCT/KR2008004883
    • 2008-08-21
    • LG CHEMICAL LTDSONG HYUN-KONCHO JEONG-JUCHOO YEON-UKSON MI-YOUNGLEE HO-CHUN
    • SONG HYUN-KONCHO JEONG-JUCHOO YEON-UKSON MI-YOUNGLEE HO-CHUN
    • G01R31/36
    • G01R31/3651G06N7/00
    • A system for estimating long term characteristics of a battery includes a learning data input unit for receiving initial characteristic learning data and long term characteristic learning data of a battery to be a learning object; a measurement data input unit for receiving initial characteristic measurement data of a battery to be an object for estimation of long term characteristics; and an artificial neural network operation unit for receiving the initial characteristic learning data and the long term characteristic learning data from the learning data input unit to allow learning of an artificial neural network, receiving the initial characteristic measurement data from the measurement data input unit and applying the learned artificial neural network thereto, and thus calculating long term characteristic estimation data from the initial characteristic measurement data of the battery and outputting the long term characteristic estimation data.
    • 一种用于估计电池的长期特性的系统包括:学习数据输入单元,用于接收作为学习对象的电池的初始特性学习数据和长期特性学习数据; 测量数据输入单元,用于接收作为估计长期特性的对象的电池的初始特性测量数据; 以及人工神经网络运算单元,用于从学习数据输入单元接收初始特征学习数据和长期特征学习数据,以允许学习人工神经网络,从测量数据输入单元接收初始特征测量数据并应用 向其学习人造神经网络,并且由此从电池的初始特性测量数据计算长期特性估计数据并输出长期特性估计数据。