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    • 11. 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
    • WO2009025512A2
    • 2009-02-26
    • PCT/KR2008/004883
    • 2008-08-21
    • LG CHEM, LTD.SONG, 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用于接收作为学习对象的电池的初始特征学习数据和长期特征学习数据的学习数据输入单元; 测量数据输入单元,用于接收作为用于估计长期特性的对象的电池的初始特性测量数据; 以及人工神经网络操作单元,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,以允许学习人造神经网络,从测量数据输入单元接收初始特征测量数据并应用 从而从电池的初始特性测量数据计算长期特征估计数据并输出长期特征估计数据。
    • 12. 发明申请
    • PHARMACEUTICAL COMPOSITION COMPRISING A P25/CDK5 INHIBITOR FOR PREVENTING OR TREATING A NEURODEGENERATIVE DISEASE
    • 包含P25 / CDK5抑制剂的药物组合物,用于预防或治疗神经病变疾病
    • WO2006075808A1
    • 2006-07-20
    • PCT/KR2005/000098
    • 2005-01-12
    • INJE UNIVERSITYCHUNG, Sul-HeeHA, IlhoSON, Mi-YoungLEE, Hye-Won
    • CHUNG, Sul-HeeHA, IlhoSON, Mi-YoungLEE, Hye-Won
    • A61K31/381A61P25/28
    • A61K31/381
    • A pharmaceutical composition for preventing or treating a neurodegenerative disease comprises a compound inhibiting a P25/CDK (cycline-dependent kinase 5) complex as an active ingredient. Also disclosed is a method for screening a compound capable of preventing or treating a neurodegenerative disease, which comprises the steps of a) reacting a candidate compound with a P25/CDK5 complex and beta-site APP (amyloid precursor protein)-cleaving enzyme 1 (BACEl) or treating a mammalian cell expressing P25 with the candidate compound, and measuring BACE l phosphorylation; and b) comparing the measured BACEl phosphorylation with that of a control group employing no candidate compound, and identifying a compound reducing BACEl phosphorylation compared to the control group. The compound inhibiting the P25/CDK5 complex may be useful for preventing or treating a neurodegenerative disease including Alzheimer's disease because it inhibits BACEl phosphorylation and reduces the secretion of β-amyloid and the hyperphosphorylation of Tau.
    • 用于预防或治疗神经变性疾病的药物组合物包括抑制P25 / CDK(cycline-dependent kinase 5)复合物作为活性成分的化合物。 还公开了一种筛选能够预防或治疗神经变性疾病的化合物的方法,其包括以下步骤:a)使候选化合物与P25 / CDK5复合体和β-位点APP(淀粉样蛋白前体蛋白)切割酶1( BACE1)或用候选化合物处理表达P25的哺乳动物细胞,并测量BACE1磷酸化; 和b)比较测定的BACE1磷酸化与不使用候选化合物的对照组的BACE1磷酸化,并且与对照组相比,鉴定减少BACE1磷酸化的化合物。 抑制P25 / CDK5复合物的化合物可用于预防或治疗包括阿尔茨海默病在内的神经变性疾病,因为它抑制BACE1磷酸化并降低β-淀粉样蛋白的分泌和Tau的过度磷酸化。
    • 15. 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
    • WO2009035288A2
    • 2009-03-19
    • PCT/KR2008/005403
    • 2008-09-12
    • LG CHEM, LTD.SONG, 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,包括用于接收作为学习对象的电池的初始和长期特征学习数据的学习数据输入单元; 测量数据输入单元,用于接收作为长期特性估计对象的电池的初始特性测量数据; 一种用于将学习数据转换为第一和第二数据结构的人造神经网络操作单元,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,以及单独应用所学习的 对应于每个数据结构的人工神经网络,基于每个数据结构计算和输出长期特征估计数据; 以及长期特征评估单元,用于计算每个数据结构的估计数据的误差,并根据误差确定估计数据的可靠性。