Smart lifting table
    1.
    外观设计

    公开(公告)号:USD1011094S1

    公开(公告)日:2024-01-16

    申请号:US29880046

    申请日:2023-07-17

    申请人: Zheng Chen

    设计人: Zheng Chen

    摘要: FIG. 1 is a front top perspective view of a smart lifting table, showing my new design;
    FIG. 2 is a rear bottom perspective view thereof;
    FIG. 3 is a front bottom perspective view thereof in another angle thereof;
    FIG. 4 is a front elevational view thereof;
    FIG. 5 is a rear elevational view thereof;
    FIG. 6 is a left side view thereof;
    FIG. 7 is a right side view thereof;
    FIG. 8 is a top plan view thereof;
    FIG. 9 is a bottom plan view thereof;
    FIG. 10 is an enlarged view of detail 10 in FIG. 1;
    FIG. 11 is an enlarged view of detail 11 in FIG. 2;
    FIG. 12 is an enlarged view of detail 12 in FIG. 2;
    FIG. 13 is an enlarged view of detail 13 in FIG. 2;
    FIG. 14 is an enlarged view of detail 14 in FIG. 2;
    FIG. 15 is an enlarged view of detail 15 in FIG. 2;
    FIG. 16 is an enlarged view of detail 16 in FIG. 3;
    FIG. 17 is an enlarged view of detail 17 in FIG. 3;
    FIG. 18 is an enlarged view of detail 18 in FIG. 3;
    FIG. 19 is an enlarged view of detail 19 in FIG. 3;
    FIG. 20 is an enlarged view of detail 20 in FIG. 4;
    FIG. 21 is an enlarged view of detail 21 in FIG. 4;
    FIG. 22 is an enlarged view of detail 22 in FIG. 4;
    FIG. 23 is an enlarged view of detail 23 in FIG. 5;
    FIG. 24 is an enlarged view of detail 24 in FIG. 5;
    FIG. 25 is an enlarged view of detail 25 in FIG. 6;
    FIG. 26 is an enlarged view of detail 26 in FIG. 6;
    FIG. 27 is an enlarged view of detail 27 in FIG. 7;
    FIG. 28 is an enlarged view of detail 28 in FIG. 9;
    FIG. 29 is an enlarged view of detail 29 in FIG. 9;
    FIG. 30 is an enlarged view of detail 30 in FIG. 9;
    FIG. 31 is an enlarged view of detail 31 in FIG. 9;
    FIG. 32 is an enlarged view of detail 32 in FIG. 9; and,
    FIG. 33 is an enlarged view of detail 33 in FIG. 9.

    Energy-recovery generation system for handling and carrying electric vehicle
    3.
    发明授权
    Energy-recovery generation system for handling and carrying electric vehicle 有权
    用于处理和携带电动车辆的能量回收发电系统

    公开(公告)号:US09422949B2

    公开(公告)日:2016-08-23

    申请号:US13977100

    申请日:2011-11-30

    IPC分类号: F15B15/00 B66F9/22 F15B21/14

    摘要: An energy-recovery generation system for a handling and carrying electric vehicle, comprising a hoisting cylinder (9), wherein an output pipeline of the hoisting cylinder (9) is provided with a pressure sensor unit (1) and a directional valve (2); the directional valve (2) is under the control of the pressure sensor unit (1); a first outlet of the directional valve (2) is connected to a tank (5) through a way of a multi-way valve (4) with an operating handle; the pressure oil, flowing out from a second outlet of the directional valve (2), passes through a pump (7) having an oil suction port capable of bearing pressure or a motor, and then passes through the multi-way valve (4), to finally flow back to the tank (5); the pump (7) having an oil suction port capable of bearing pressure or the motor drives an electric motor (16) to output electric energy; an electric energy output end of the electric motor (16) is connected to an energy storage device (20) through a converter (21).

    摘要翻译: 一种用于处理和运载电动车辆的能量回收发电系统,包括一个起重气缸(9),其中提升气缸(9)的输出管道设置有压力传感器单元(1)和方向阀(2) ; 方向阀(2)处于压力传感器单元(1)的控制下; 方向阀(2)的第一出口通过具有操作手柄的多通阀(4)的方式连接到罐(5); 从方向阀(2)的第二出口流出的压力油通过具有能够承受压力的油吸入口的泵(7)或马达,然后通过多通阀(4) ,最终流回罐(5); 所述泵(7)具有能够承受压力的吸油口或所述电动机驱动电动机(16)输出电能; 电动机(16)的电能输出端通过转换器(21)与能量存储装置(20)连接。

    Transfer of learning for query classification
    5.
    发明授权
    Transfer of learning for query classification 有权
    转移学习查询分类

    公开(公告)号:US08719192B2

    公开(公告)日:2014-05-06

    申请号:US13081391

    申请日:2011-04-06

    IPC分类号: G06N5/02 G06F17/30

    CPC分类号: G06N99/005

    摘要: Transfer of learning trains a new domain for the classification of search queries according to different tasks, as well as the generation of a corresponding domain-specific query classifier that may be used to classify the search queries according to the different tasks in the new domain. The transfer of learning may include preparing a new domain to receive classification knowledge from one or more source domains by populating the new domain with preliminary query patterns extracted for a search engine log. The transfer of learning may further include preparing the classification knowledge in each source domain for transfer to the new domain. The classification knowledge in each source domain may then be transferred to the new domain.

    摘要翻译: 学习的转移为根据不同任务对搜索查询进行分类的新领域提供了新的领域,以及生成可用于根据新域中的不同任务对搜索查询进行分类的相应的域特定查询分类器。 学习的转移可能包括准备一个新的域,以通过用搜索引擎日志提取的初步查询模式填充新域来从一个或多个源域接收分类知识。 学习的转移还可以包括准备每个源域中的分类知识以转移到新的域。 然后可以将每个源域中的分类知识转移到新域。

    Click modeling for URL placements in query response pages
    7.
    发明授权
    Click modeling for URL placements in query response pages 有权
    点击查询响应页面中的网址展示位置的建模

    公开(公告)号:US08589228B2

    公开(公告)日:2013-11-19

    申请号:US12795631

    申请日:2010-06-07

    CPC分类号: G06Q30/02 G06Q30/0255

    摘要: A “General Click Model” (GCM) is constructed using a Bayesian network that is inherently capable of modeling “tail queries” by building the model on multiple attribute values that are shared across queries. More specifically, the GCM learns and predicts user click behavior towards URLs displayed on a query results page returned by a search engine. Unlike conventional click modeling approaches that learn models based on individual queries, the GCM learns click models from multiple attributes, with the influence of different attribute values being measured by Bayesian inference. This provides an advantage in learning that enables the GCM to achieve improved generalization and results, especially for tail queries, than conventional click models. In addition, most conventional click models consider only position and the identity of URLs when learning the model. In contrast, the GCM considers more session-specific attributes in making a final prediction for anticipated or expected user click behaviors.

    摘要翻译: 使用贝叶斯网络构建“通用点击模型”(GCM),该贝叶斯网络本质上能够通过在查询之间共享的多个属性值上建立模型来建模“尾部查询”。 更具体地说,GCM学习并预测用户对搜索引擎返回的查询结果页面上显示的URL的点击行为。 不同于传统的点击建模方法,基于个别查询的模型,GCM从多个属性学习点击模型,不同属性值的影响是通过贝叶斯推理来衡量的。 这提供了学习的优势,使得GCM能够实现改进的泛化和结果,特别是尾部查询,而不是传统的点击模型。 此外,大多数传统的点击模型只在学习模型时考虑URL的位置和身份。 相比之下,GCM考虑更多的会话特定属性来对预期或预期的用户点击行为进行最终预测。

    ENERGY-RECOVERY GENERATION SYSTEM FOR HANDLING AND CARRYING ELECTRIC VEHICLE
    8.
    发明申请
    ENERGY-RECOVERY GENERATION SYSTEM FOR HANDLING AND CARRYING ELECTRIC VEHICLE 有权
    用于处理和携带电动汽车的能量恢复系统

    公开(公告)号:US20130283776A1

    公开(公告)日:2013-10-31

    申请号:US13977100

    申请日:2011-11-30

    IPC分类号: F15B15/00

    摘要: An energy-recovery generation system for a handling and carrying electric vehicle, comprising a hoisting cylinder (9), wherein an output pipeline of the hoisting cylinder (9) is provided with a pressure sensor unit (1) and a directional valve (2); the directional valve (2) is under the control of the pressure sensor unit (1); a first outlet of the directional valve (2) is connected to a tank (5) through a way of a multi-way valve (4) with an operating handle; the pressure oil, flowing out from a second outlet of the directional valve (2), passes through a pump (7) having an oil suction port capable of bearing pressure or a motor, and then passes through the multi-way valve (4), to finally flow back to the tank (5); the pump (7) having an oil suction port capable of bearing pressure or the motor drives an electric motor (16) to output electric energy; an electric energy output end of the electric motor (16) is connected to an energy storage device (20) through a converter (21).

    摘要翻译: 一种用于处理和运载电动车辆的能量回收发电系统,包括一个起重气缸(9),其中提升气缸(9)的输出管道设置有压力传感器单元(1)和方向阀(2) ; 方向阀(2)处于压力传感器单元(1)的控制下; 方向阀(2)的第一出口通过具有操作手柄的多通阀(4)的方式连接到罐(5); 从方向阀(2)的第二出口流出的压力油通过具有能够承受压力的油吸入口的泵(7)或马达,然后通过多通阀(4) ,最终流回罐(5); 所述泵(7)具有能够承受压力的吸油口或所述电动机驱动电动机(16)输出电能; 电动机(16)的电能输出端通过转换器(21)与能量存储装置(20)连接。

    Mining translations of web queries from web click-through data
    9.
    发明授权
    Mining translations of web queries from web click-through data 有权
    从网络点击数据挖掘网络查询的翻译

    公开(公告)号:US08543580B2

    公开(公告)日:2013-09-24

    申请号:US12342098

    申请日:2008-12-23

    IPC分类号: G06F7/00 G06F17/30

    CPC分类号: G06F17/30864 G06F2216/03

    摘要: Methods and technologies providing translations of web queries based on an analysis of user behavior in click-through data. These methods and technologies generates large-scale and timely query translation pairs guided by a small set of seed word pairs from a dictionary, without relying on additional knowledge or complex models.

    摘要翻译: 基于点击数据中的用户行为分析,提供Web查询翻译的方法和技术。 这些方法和技术不但依赖于额外的知识或复杂的模型,而是从词典中产生由小型种子字对引导的大规模和及时的查询翻译对。