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1. 发明申请

US20110246573A1 DISTRIBUTED NON-NEGATIVE MATRIX FACTORIZATION 有权
标题翻译：分布式非负矩阵法
公开(公告)号：US20110246573A1
公开(公告)日：2011-10-06
申请号：US12750772
申请日：2010-03-31
申请人： Chao Liu , Hung-Chih Yang , Jinliang Fan , Li-Wei He , Yi-Min Wang
发明人： Chao Liu , Hung-Chih Yang , Jinliang Fan , Li-Wei He , Yi-Min Wang
IPC分类号： G06F15/16
CPC分类号： G06F17/16
摘要： Architecture that scales up the non-negative matrix factorization (NMF) technique to a distributed NMF (denoted DNMF) to handle large matrices, for example, on a web scale that can include millions and billions of data points. To analyze web-scale data, DNMF is applied through parallelism on distributed computer clusters, for example, with thousands of machines. In order to maximize the parallelism and data locality, matrices are partitioned in the short dimension. The probabilistic DNMF can employ not only Gaussian and Poisson NMF techniques, but also exponential NMF for modeling web dyadic data (e.g., dwell time of a user on browsed web pages).
摘要翻译：将非负矩阵分解（NMF）技术扩展到分布式NMF（表示为DNMF）以处理大型矩阵的架构，例如，可以包括数百万和数十亿个数据点的网络规模。为了分析网络规模数据，DNMF通过并行性应用于分布式计算机集群，例如数千台机器。为了最大化并行度和数据局部性，矩阵在短维中被划分。概率DNMF不仅可以采用高斯和泊松NMF技术，还可以采用指数NMF来建模网络二进制数据（例如，用户在浏览的网页上的停留时间）。

2. 发明授权

US08362501B2 Light-emitting device 有权
标题翻译：发光装置
公开(公告)号：US08362501B2
公开(公告)日：2013-01-29
申请号：US12769744
申请日：2010-04-29
申请人： Hung-Chih Yang , Yu-Jiun Shen , Hsin-Mao Liu
发明人： Hung-Chih Yang , Yu-Jiun Shen , Hsin-Mao Liu
IPC分类号： H01L33/22
CPC分类号： H01L33/40 , H01L2933/0091
摘要： The application illustrates a light-emitting device including a contact layer and a current spreading layer on the contact layer. A part of the contact layer is a rough structure and a part of the contact layer is a flat structure. A part of the current spreading layer is a rough structure and a part of the current spreading layer is a flat structure. The rough region of the contact layer and the rough region of the current spreading layer are substantially overlapped.
摘要翻译：该应用示出了在接触层上包括接触层和电流扩散层的发光器件。接触层的一部分是粗糙结构，并且接触层的一部分是平坦结构。电流扩散层的一部分是粗糙结构，并且电流扩展层的一部分是平坦结构。接触层的粗糙区域和电流扩散层的粗糙区域基本上重叠。

3. 发明申请

US20080133474A1 BIOINFORMATICS COMPUTATION USING A MAPRREDUCE-CONFIGURED COMPUTING SYSTEM 审中-公开
标题翻译：使用映射配置计算系统进行生物计算
公开(公告)号：US20080133474A1
公开(公告)日：2008-06-05
申请号：US11564983
申请日：2006-11-30
申请人： Ruey-Lung Hsiao , Ali Dasdan , Hung-Chih Yang
发明人： Ruey-Lung Hsiao , Ali Dasdan , Hung-Chih Yang
IPC分类号： G06F17/30
CPC分类号： G16B30/00 , G16B50/00
摘要： A MapReduce architecture may be utilized for sequence alignment algorithm processing (such as BLAST or BLAST-like algorithms). In addition, a MapReduce architecture may be extended such that memory of the computing devices of a MapReduce-configured system may be shared between different jobs of sequence alignment and/or other bioinformatics algorithm processing, thereby reducing overhead associated with executing such jobs using the MapReduce-configured system.
摘要翻译： MapReduce架构可用于序列比对算法处理（如BLAST或BLAST类算法）。此外，MapReduce架构可以被扩展，使得MapReduce配置的系统的计算设备的存储器可以在序列对准和/或其他生物信息学算法处理的不同作业之间共享，从而减少与使用MapReduce执行这样的作业相关联的开销配置系统。

4. 发明申请

US20130320296A1 LIGHT EMITTING DEVICE WITH QCSE-REVERSED AND QCSE-FREE MULTI QUANTUM WELL STRUCTURE 审中-公开
标题翻译：具有QCSE反射和无QCSE的多量子结构的发光器件
公开(公告)号：US20130320296A1
公开(公告)日：2013-12-05
申请号：US13488764
申请日：2012-06-05
申请人： Chun-Ta Yu , Chien-Yuan Tseng , Yu-Yao Lin , Shih-Pang Chang , Hung-Chih Yang
发明人： Chun-Ta Yu , Chien-Yuan Tseng , Yu-Yao Lin , Shih-Pang Chang , Hung-Chih Yang
IPC分类号： H01L33/04
CPC分类号： H01L33/06 , H01L33/32
摘要： A light-emitting device comprises a semiconductor stacked structure, the semiconductor stacked structure comprising a p-type semiconductor layer, a n-type semiconductor layer and an multiple quantum well structure between the p-type semiconductor layer and the n-type semiconductor layer, wherein the multiple quantum well structure comprises a first multiple quantum well structure near the n-type semiconductor layer and a second multiple quantum well structure near the p-type semiconductor layer, wherein the first multiple quantum well structure has positive interface bound charge and the second multiple quantum well structure has zero interface bound charge.
摘要翻译：发光器件包括半导体堆叠结构，在p型半导体层和n型半导体层之间的半导体层叠结构包括p型半导体层，n型半导体层和多量子阱结构，其中所述多量子阱结构包括靠近所述n型半导体层的第一多量子阱结构和在所述p型半导体层附近的第二多量子阱结构，其中所述第一多量子阱结构具有正界面结合的电荷，多量子阱结构具有零界面界限电荷。

5. 发明授权

US08190610B2 MapReduce for distributed database processing 有权
标题翻译： MapReduce用于分布式数据库处理
公开(公告)号：US08190610B2
公开(公告)日：2012-05-29
申请号：US11539090
申请日：2006-10-05
申请人： Ali Dasdan , Hung-Chih Yang , Ruey-Lung Hsiao
发明人： Ali Dasdan , Hung-Chih Yang , Ruey-Lung Hsiao
IPC分类号： G06F17/30
CPC分类号： G06F17/30584 , Y10S707/968
摘要： An input data set is treated as a plurality of grouped sets of key/value pairs, which enhances the utility of the MapReduce programming methodology. By utilizing such a grouping, map processing can be carried out independently on two or more related but possibly heterogeneous datasets (e.g., related by being characterized by a common primary key). The intermediate results of the map processing (key/value pairs) for a particular key can be processed together in a single reduce function by applying a different iterator to intermediate values for each group. Different iterators can be arranged inside reduce functions in ways however desired.
摘要翻译：输入数据集被视为多个分组的键/值对集合，这增强了MapReduce编程方法的实用性。通过利用这样的分组，可以在两个或更多个相关但可能异质的数据集上独立地执行地图处理（例如，通过由公共主键表征）相关联。通过将不同的迭代器应用于每个组的中间值，可以在单个减少函数中一起处理特定密钥的映射处理（密钥/值对）的中间结果。减少功能内的不同迭代器可以以所需的方式排列。

6. 发明授权

US07837350B2 Light emitting diode illuminating device 有权
标题翻译：发光二极管照明装置
公开(公告)号：US07837350B2
公开(公告)日：2010-11-23
申请号：US12057720
申请日：2008-03-28
申请人： Chih-Chung Tsao , Mei-Jiun Lin , Hung-Chih Yang , Jui-Wen Fang , Shu-Hui Hsieh , Chih-Ming Lai
发明人： Chih-Chung Tsao , Mei-Jiun Lin , Hung-Chih Yang , Jui-Wen Fang , Shu-Hui Hsieh , Chih-Ming Lai
IPC分类号： F21V5/00
CPC分类号： F21V5/02 , F21V5/04 , F21V7/0091 , F21V13/04 , F21Y2115/10 , G02B5/0215 , G02B5/0242 , G02B5/0247 , G02B5/0268 , G02B5/0278 , G02B6/0028 , G02B6/0051 , G02B19/0028 , G02B19/0061 , G02B19/0066 , G02B19/0071
摘要： A light emitting diode (LED) illumination device (10) includes an LED (11), a frustum-shaped light guide member (12) and a light diffusing plate (13). The frustum-shaped light guide member (12) has a light input surface (120) and a light output surface (122) opposite to the light input surface (120). The light guide member (12) tapers from the light output surface (122) to the light input surface (120). The light input surface (120) is optically coupled to the LED (11), and the light diffusing plate (13) is optically coupled to the light output surface (122) of the light guide member (12).
摘要翻译：发光二极管（LED）照明装置（10）包括LED（11），截头锥形导光构件（12）和光漫射板（13）。截头锥形导光构件（12）具有与光输入表面（120）相对的光输入表面（120）和光输出表面（122）。导光构件（12）从光输出表面（122）向光输入表面（120）逐渐变细。光输入表面（120）光耦合到LED（11），并且光漫射板（13）光学耦合到导光构件（12）的光输出表面（122）。

7. 发明申请

US20080120314A1 MAP-REDUCE WITH MERGE TO PROCESS MULTIPLE RELATIONAL DATASETS 有权
标题翻译： MAP-REDUCE与MERGE处理多个关系数据
公开(公告)号：US20080120314A1
公开(公告)日：2008-05-22
申请号：US11560523
申请日：2006-11-16
申请人： Hung-Chih Yang , Ali Dasdan , Ruey-Lung Hsiao
发明人： Hung-Chih Yang , Ali Dasdan , Ruey-Lung Hsiao
IPC分类号： G06F7/00
CPC分类号： G06F17/30498 , Y10S707/99942 , Y10S707/99943 , Y10S707/99945
摘要： A method of processing relationships of at least two datasets is provided. For each of the datasets, a map-reduce subsystem is provided such that the data of that dataset is mapped to corresponding intermediate data for that dataset. The intermediate data for that dataset is reduced to a set of reduced intermediate data for that dataset. Data corresponding to the sets of reduced intermediate data are merged, in accordance with a merge condition. In some examples, data being merged may include the output of one or more other mergers. That is, generally, merge functions may be flexibly placed among various map-reduce subsystems and, as such, the basic map-reduce architecture may be advantageously modified to process multiple relational datasets using, for example, clusters of computing devices.
摘要翻译：提供了一种处理至少两个数据集的关系的方法。对于每个数据集，提供了一个map-reduce子系统，以便将该数据集的数据映射到该数据集的相应中间数据。该数据集的中间数据被减少为该数据集的一组减少的中间数据。根据合并条件合并与缩减的中间数据集相对应的数据。在一些示例中，合并的数据可以包括一个或多个其他合并的输出。也就是说，通常，合并功能可以灵活地放置在各种map-reduce子系统之间，并且因此，可以有利地修改基本的map-reduce架构以使用例如计算设备的集群来处理多个关系数据集。

8. 发明申请

US20130253888A1 ONE-PASS STATISTICAL COMPUTATIONS 审中-公开
标题翻译：一次统计计算
公开(公告)号：US20130253888A1
公开(公告)日：2013-09-26
申请号：US13427626
申请日：2012-03-22
申请人： Hung-Chih Yang , Xiong Zhang , Danny B. Lange
发明人： Hung-Chih Yang , Xiong Zhang , Danny B. Lange
IPC分类号： G06F17/10
CPC分类号： G06F17/18
摘要： Some embodiments of the invention employ algorithms enabling the calculation of one or more statistical moments in a single pass of a dataset. For example, some embodiments may apply algorithms for calculating statistical moments to a dataset using a map-reduce framework, whereby an input dataset is partitioned into multiple shards, a separate map process is used to apply an algorithm enabling calculation of one or more statistical moments in a single scan to each shard, and one or more reduce processes consolidate the results generated by the map processes to calculate the one or more statistical moments across the entire dataset. In other embodiments of the invention, a map-reduce framework may be employed to apply algorithms enabling calculation of a covariance between data elements expressed in a dataset, instead of or in addition to one or more statistical moments.
摘要翻译：本发明的一些实施例使用能够计算数据集的单次通过中的一个或多个统计矩阵的算法。例如，一些实施例可以应用用于使用map-reduce框架来计算统计矩阵到数据集的算法，由此将输入数据集划分成多个分片，使用单独的映射过程来应用能够计算一个或多个统计时刻的算法对每个分片进行单次扫描，并且一个或多个减少过程合并由映射过程生成的结果，以计算整个数据集中的一个或多个统计矩。在本发明的其他实施例中，可以采用映射减少框架来应用能够计算在数据集中表示的数据元素之间的协方差的算法，而不是一个或多个统计矩阵，或者除了一个或多个统计矩。

9. 发明申请

US20130246429A1 MULTI-CENTER CANOPY CLUSTERING 有权
标题翻译：多中心聚集
公开(公告)号：US20130246429A1
公开(公告)日：2013-09-19
申请号：US13423286
申请日：2012-03-19
申请人： Xiong Zhang , Danny Lange , Hung-Chih Yang
发明人： Xiong Zhang , Danny Lange , Hung-Chih Yang
IPC分类号： G06F17/30
CPC分类号： G06F17/30598 , G06F17/30011
摘要： A canopy clustering process merges at least one set of multiple single-center canopies together into a merged multi-center canopy. Multi-center canopies, as well as the single-center canopies, can then be used to partition data objects in a dataset. The multi-center canopies allow a canopy assignment condition constraint to be relaxed without risk of leaving any data objects in a dataset outside of all canopies. Approximate distance calculations can be used as similarity metrics to define and merge canopies and to assign data objects to canopies. In one implementation, a distance between a data object and a canopy is represented as the minimum of the distances between the data object and each center of a canopy (whether merged or unmerged), and the distance between two canopies is represented as the minimum of the distances for each pairing of the center(s) in one canopy and the center(s) in the other canopy.
摘要翻译：冠层聚类过程将至少一组多个单中心檐篷合并成合并的多中心冠层。多中心檐篷以及单中心檐篷可用于对数据集中的数据对象进行分区。多中心檐篷允许放宽冠层分配条件约束，而不会在所有檐篷之外的数据集中留下任何数据对象的风险。近似距离计算可以用作相似性度量来定义和合并檐篷，并将数据对象分配给檐篷。在一个实现中，数据对象和冠层之间的距离被表示为数据对象和冠层的每个中心之间的距离的最小值（无论是合并还是未合并），并且两个檐篷之间的距离被表示为一个冠层中心的每个配对的距离和另一个冠层中的一个或多个中心。

10. 发明授权

US09218630B2 Identifying influential users of a social networking service 有权
标题翻译：识别社交网络服务的有影响力的用户
公开(公告)号：US09218630B2
公开(公告)日：2015-12-22
申请号：US13427584
申请日：2012-03-22
申请人： Hung-Chih Yang , Danny B. Lange , Xiong Zhang
发明人： Hung-Chih Yang , Danny B. Lange , Xiong Zhang
IPC分类号： G06Q50/00 , G06Q10/10 , G06Q30/02 , G09B29/00
CPC分类号： G06Q30/0201 , G06Q10/101 , G06Q30/0251 , G06Q30/0269 , G06Q30/0271 , G06Q50/01 , G09B29/00 , H04L51/32 , H04L51/36 , H04L67/306
摘要： Techniques for identifying influential users of a social networking service are provided. Influential users may be identified via an algorithm in which an influence score is assigned to each user based at least in part on other members of the community users having taken an affirmative step with respect to the user's communications. Iterative processing may be performed, with each user's influence score being determined by contributions from other users, and each contribution being determined by the contributor's influence score as of a prior iteration. A map-reduce framework may be employed, with data representing the community being partitioned into a plurality of discrete shards, a map process corresponding to each shard calculating an influence score for users represented in the shard, and reduce processes ranking users according to influence score across all shards.
摘要翻译：提供了用于识别社交网络服务的有影响力用户的技术。可以通过至少部分地基于对用户的通信采取肯定步骤的社区用户的其他成员的算法来识别影响用户，其中影响分数被分配给每个用户。可以执行迭代处理，每个用户的影响分数由来自其他用户的贡献确定，并且每个贡献由先前迭代中的贡献者的影响分数确定。可以采用地图缩减框架，其中表示社区的数据被划分成多个离散碎片，对应于每个碎片的映射处理计算分片中表示的用户的影响分数，并且减少根据影响分数对用户进行排名的过程跨越所有碎片

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