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    • 2. 发明申请
    • CONNECTOR
    • 连接器
    • US20140227909A1
    • 2014-08-14
    • US14124425
    • 2012-05-29
    • Hiroshi KojimaTsutomu Sawada
    • Hiroshi KojimaTsutomu Sawada
    • H01R13/516
    • H01R13/516B60L53/16H01R13/4361H01R2201/26Y02T10/7005Y02T10/7072Y02T90/14
    • The connector to be mated with a mating connector has a connector housing receiving a terminal and fixing members for fixing the terminal, a case receiving the connector housing, and an abutment member vertically arranged in the case so that the abutment member is positioned at the end portion of the connector housing away from the mating connector, and abutting on the fixing member received in the end portion of the connector housing so as to prevent the terminal from moving in a longitudinal direction of the terminal. Thus, the connector can reduce the number of parts and simplify structure thereof. Furthermore, the connector can be assembled and disassembled at short time.
    • 与匹配连接器配合的连接器具有接收端子的连接器壳体和用于固定端子的固定构件,容纳连接器壳体的壳体和垂直布置在壳体中的抵接构件,使得抵接构件位于端部 连接器壳体的远离配合连接器的部分,并且抵靠在容纳在连接器壳体的端部中的固定构件上,以防止端子在端子的纵向方向上移动。 因此,连接器可以减少部件的数量并简化其结构。 此外,连接器可以在短时间内组装和拆卸。
    • 4. 发明授权
    • Robot apparatus and method of controlling the behavior thereof
    • 机器人装置及其行为控制方法
    • US08315454B2
    • 2012-11-20
    • US11224154
    • 2005-09-12
    • Fumihide TanakaHiroaki OgawaHirotaka SuzukiOsamu HanagataTsutomu SawadaMasato Ito
    • Fumihide TanakaHiroaki OgawaHirotaka SuzukiOsamu HanagataTsutomu SawadaMasato Ito
    • G06F19/00G05B19/04
    • G06N3/008
    • The present invention provides a robot apparatus that can perform appropriate actions in accordance with the ambient conditions, and a method of controlling the behavior of the robot apparatus. The robot apparatus includes a data-acquiring unit that acquires data, externally and/or internally, a subject-identifying unit that identifies a subject performing an action, by using the data externally acquired, a condition-recognizing unit that recognizes external conditions and/or internal conditions, by using the data externally acquired and/or the data internally acquired, an action-pattern acquiring unit that acquires an action pattern of the subject, by using the data externally acquired, a storage unit that stores action data representing the action of the subject, in association with condition data and subject identification data, the condition data representing conditions external and/or internal of the robot apparatus, and the subject identification data identifying the subject, and an action-performing unit that performs actions, wherein the action-performing unit performs an action represented by the action data stored in the storage unit, in accordance with the identification data and the external and/or internal condition data, when the subject-identifying unit identifies the subject.
    • 本发明提供一种能够根据环境条件执行适当动作的机器人装置,以及控制机器人装置的动作的方法。 机器人装置包括数据获取单元,其通过使用外部获取的数据来获取识别执行动作的对象的对象识别单元的外部和/或内部的数据,识别外部条件的条件识别单元和/ 或内部条件,通过使用外部获取的数据和/或内部获取的数据,动作模式获取单元,通过使用外部获取的数据来获取对象的动作模式;存储单元,存储表示动作的动作数据 与条件数据和对象识别数据相关联的条件数据表示机器人装置的外部和/或内部的条件以及标识对象的对象识别数据,以及执行动作的动作执行单元,其中, 动作执行单元根据识别符执行由存储在存储单元中的动作数据表示的动作 阳性数据和外部和/或内部条件数据,当主体识别单元识别对象时。
    • 7. 发明授权
    • Colloidal crystals and method and device for manufacturing colloidal crystal gel
    • 胶体晶体及胶体晶体凝胶制造方法及装置
    • US07772289B2
    • 2010-08-10
    • US10565323
    • 2004-07-21
    • Tsutomu SawadaToshimitsu KanaiAkiko Toyotama
    • Tsutomu SawadaToshimitsu KanaiAkiko Toyotama
    • B01J13/00
    • G02B5/20C30B5/00C30B7/10C30B29/58
    • Prior colloidal crystal preparation means requires much workmanship to obtain colloidal crystals, relying much on the expertise of an operator. To utilize colloidal crystals in various fields and develop them from now on, it is in demand to establish preparation means capable of preparing colloidal crystals with good reproducibility. The object of the invention is to meet such demand.A gas compressed in a compressor (1) is controlled by a gas pulse controller (3) to generate compressed air pulses, and the pulses are then guided to a colloidal crystal preparation vessel (6) having a flat plate type capillary portion to produce a pressure fluctuation, which is in turn used as driving power, thereby giving a flow and hard-stopping motion to a colloidal solution in the flat plate type capillary for formation of colloidal crystals of good single crystallinity.
    • 以前的胶态晶体制备意味着需要大量的工艺来获得胶体晶体,这取决于操作者的专业知识。 为了利用各种领域的胶体晶体,从现在开始,需要建立能够制备具有良好重现性的胶体晶体的制备方法。 本发明的目的是满足这种需求。 在压缩机(1)中压缩的气体由气体脉冲控制器(3)控制以产生压缩空气脉冲,然后将脉冲引导至具有平板型毛细管部分的胶体晶体制备容器(6),以产生 压力波动,其又被用作驱动力,从而对平板型毛细管中的胶体溶液进行流动和硬停止运动,以形成具有良好单一结晶度的胶体晶体。
    • 8. 发明授权
    • Learning method and apparatus utilizing genetic algorithms
    • 利用遗传算法的学习方法和设备
    • US07720774B2
    • 2010-05-18
    • US11589638
    • 2006-10-30
    • Tsutomu Sawada
    • Tsutomu Sawada
    • G06N3/12
    • G06N7/005
    • A learning apparatus for building a network structure of a Bayesian network based on learning data. In the Bayesian network, a cause and effect relationship between plural nodes is represented by a directed graph. The learning apparatus includes a storage portion in which the learning data is stored and a learning portion for building the network structure based on the learning data. The learning portion prepares an initial population of individuals formed by individuals each having a genotype in which orders between the nodes and cause and effect relationship have been stipulated, repeatedly performs processing for crossovers and/or mutations on the initial population of individuals based on a genetic algorithm, calculates an evaluated value of each individual based on the learning data, searches for an optimum one of the individuals, and takes a phenotype of the optimum individual as the network structure.
    • 一种用于基于学习数据构建贝叶斯网络的网络结构的学习装置。 在贝叶斯网络中,多个节点之间的因果关系由有向图表示。 学习装置包括存储学习数据的存储部分和用于基于学习数据构建网络结构的学习部分。 学习部分准备由个体形成的个体的初始种群,每个个体具有其中节点之间的顺序和因果关系已经被规定的基因型,基于遗传重复地对个体的初始种群进行交叉和/或突变的处理 算法,基于学习数据计算每个个体的评估值,搜索最佳个体之一,并将最佳个体的表型作为网络结构。
    • 9. 发明申请
    • INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND COMPUTER PROGRAM
    • 信息处理设备,信息处理方法和计算机程序
    • US20090030865A1
    • 2009-01-29
    • US12176921
    • 2008-07-21
    • Tsutomu SAWADA
    • Tsutomu SAWADA
    • G06N5/02
    • G06K9/00362G06K9/6293
    • An information processing apparatus includes plural information input units that input information including image information or sound information in an actual space, an event detecting unit that generates event information including estimated position information and estimated identification information of users present in the actual space by analyzing the information inputted from the information input unit, and an information-integration processing unit that sets probability distribution data of hypotheses concerning position and identification information of the users and executes generation of analysis information including user position information and user identification information of the users present in the actual space by updating and selecting the hypotheses on the basis of the event information.
    • 一种信息处理设备,包括输入包括实际空间中的图像信息或声音信息的信息的多个信息输入单元,通过分析信息来生成包含实际空间中存在的用户的估计位置信息和估计识别信息的事件信息的事件检测单元 从信息输入单元输入的信息综合处理单元,设定与用户的位置和识别信息有关的假设的概率分布数据,并执行生成包含用户位置信息和实际使用者的用户识别信息的分析信息 通过基于事件信息更新和选择假设的空间。
    • 10. 发明申请
    • Learning apparatus and method
    • 学习设备和方法
    • US20070112708A1
    • 2007-05-17
    • US11589638
    • 2006-10-30
    • Tsutomu Sawada
    • Tsutomu Sawada
    • G06N3/08
    • G06N7/005
    • A learning apparatus for building a network structure of a Bayesian network based on learning data. In the Bayesian network, a cause and effect relationship between plural nodes is represented by a directed graph. The learning apparatus includes a storage portion in which the learning data is stored and a learning portion for building the network structure based on the learning data. The learning portion prepares an initial population of individuals formed by individuals each having a genotype in which orders between the nodes and cause and effect relationship have been stipulated, repeatedly performs processing for crossovers and/or mutations on the initial population of individuals based on a genetic algorithm, calculates an evaluated value of each individual based on the learning data, searches for an optimum one of the individuals, and takes a phenotype of the optimum individual as the network structure.
    • 一种用于基于学习数据构建贝叶斯网络的网络结构的学习装置。 在贝叶斯网络中,多个节点之间的因果关系由有向图表示。 学习装置包括存储学习数据的存储部分和用于基于学习数据构建网络结构的学习部分。 学习部分准备由个体形成的个体的初始种群,每个个体具有其中节点之间的顺序和因果关系已经被规定的基因型,基于遗传重复地对个体的初始种群进行交叉和/或突变的处理 算法,基于学习数据计算每个个体的评估值,搜索最佳个体之一,并将最佳个体的表型作为网络结构。