International Business Machines Corporation

Semiconductor Manufacturing International (shanghai) Corporation

Semiconductor Manufacturing International (beijing) Corporation

Semiconductor Manufacturing International Corp.

Heng Cao

Ju Wei Shi

Sheng Fen Chiu

Yu Wang

Bin Zhang

Chao Zhang

Wei Shan Dong

Chen Wang

Wen Jun Yin

Chun Ma

Tarun Kumar

Jin Dong

Yu Ying Wang

Jia Zou

Ming Xie

Chunhua Tian

Lan Jun Wang

Chen Jiang

Michael Adendorff

Shengfen Chiu

David L Jensen

Jacqueline Giang Huong Morris

Jianying Hu

Ta-Hsin Li

Bonnie Kathryn Ray

Richard D Lawrence

Grace Y Lin

Yingdong Lu

Yunhee Jang

Roger R Gung

Mark A Eaton

Meng-Chen Hsieh

A memory cell includes a substrate including a first diode region, a second diode region, a third diode region, and a fourth diode region, a first well region formed in the first diode region and the second diode region, a second well region formed in the third diode region and the fourth diode region, a doped conductive region formed on the first well region and the second well region, and a deep trench isolation structure formed in the substrate to electrically isolate different portions of each of the first well region, the second well region, and the doped conductive region formed over different diode regions. The second well region and the first well region have different doping types. The memory cell includes a resistance random access memory device formed over the substrate and electrically connected to the doped conductive region in the second diode region and the third diode region.

Memory cells and memory array structures including RRAM, and fabrication methods thereof

A memory cell includes a bit line and a reset line sharing a same line, a word line, a first diode including a first N-well region in a substrate, and a first P-type doped region adjacent to the first N-well region that is coupled to a set line, a second diode spaced apart from the first diode and including a second N-well region in the substrate, a first N-type doped region and a second P-type doped region spaced apart from each other and adjacent to the second N-well region, the second P-type doped region coupled to the bit line and the reset line, a bottom electrode coupled to the first P-type doped region and the first N-type doped region, a top electrode coupled to the word line, and a data storage material layer disposed between the bottom electrode and the top electrode.

Memory cell, memory cell array and operating method thereof

A method and an apparatus for determining a location of a mobile device. The location of a mobile device is determined accurately according to information which includes call data records of the mobile device. By employing a partial ellipse integral model, two physical world factors are taken into consideration in reducing the location uncertainty in call data records. The factors include: spatiotemporal constraints of the device's movement in the physical world and the telecommunication cell area's geometry information, which increase the accuracy of determining the location of a mobile device.

Determining a location of a mobile device

Semiconductor devices and fabrication methods thereof are provided to form a memory cell. The memory cell includes a first diode, a second diode separated from the first diode. The first diode includes a first well region in a substrate, a first N-type doped region adjacent to the first well region and connected to a bit line, and a first P-type doped region adjacent to the first well region and separated from the first N-type doped region. The second diode includes a second well region in the substrate, a second N-type doped region adjacent to the second well region, and a second P-type doped region. The memory cell further includes a bottom electrode connected to the first P-type doped region and the second N-type doped region, respectively, a top electrode connected to a word line, and a data storage material layer located between the bottom electrode and the top electrode.

Memory cell, memory cell array, memory device and operation method of memory cell array

A memory cell array structure includes memory cells arranged in m rows and n columns on a substrate, and n columns of first and second well regions with different conductivity types alternatively arranged along the column direction. Each of the memory cells includes first and second diodes. The first diode formed of a first doped region in the same column is disposed in the first well region. The second diode formed of a second doped region in the same column is disposed in the second well region. A third doped region having the conductivity type of the first well region is disposed in the first well region and is connected to the reset line of the same column. A fourth doped region having the conductivity type of the second well region is disposed in the second well region and is connected to the bit line of the same column.

Structure and method for memory cell array

A memory cell includes a first diode, a second diode, and a random access memory cell element. The first diode and the random access memory cell element are series connected between a bit line and a word line. The second diode and the random access memory cell element are series connected between the word line and a reset line. A set path is formed through the first diode and the random access memory cell element, and a reset path is formed through the random access memory cell element and the second diode. The first diode is configured to performed a read operation and a set operation. The second diode is configured to perform a reset operation. The memory cell has higher forward current, lower leakage current and smaller size comparing with conventional memory cells.

Memory cell structures

A method of determining location of a user of a mobile device based on Call Detail Records (CDRs) includes determining data in CDRs related to the user; determining base stations associated with communication locations of the user and corresponding statistical data about communication frequency according to the determined data in the CDRs; and determining location of the user based on at least three determined base stations and the corresponding statistical data about communication frequency as well as physical coordinates of the three base stations.

Determining location of a user of a mobile device

A computer implemented method for clustering customers includes receiving a source set of customer records, wherein each customer record represents one customer, and each customer record includes at least one data attribute, and each data attribute has an attribute value; pre-processing the source set of customer records to generate a pre-processed set of customer records; executing a clustering algorithm on the pre-processed set of customer records to group the pre-processed set of customer records into clusters of a pre-defined number. The pre-processing comprises: determining the type of a customer in the source set of customer records; using a type attribute value to indicate the type of the customer in its customer record; normalizing data attribute values and type attribute values; weighting to the data attribute values and the type attribute values respectively to obtain weighted attribute values of the data attribute and weighted attribute values of the type attribute.

Clustering customers

A computer implemented method for clustering customers includes receiving a source set of customer records, wherein each customer record represents one customer, and each customer record includes at least one data attribute, and each data attribute has an attribute value; pre-processing the source set of customer records to generate a pre-processed set of customer records; executing a clustering algorithm on the pre-processed set of customer records to group the pre-processed set of customer records into clusters of a pre-defined number. The pre-processing comprises: determining the type of a customer in the source set of customer records; using a type attribute value to indicate the type of the customer in its customer record; normalizing data attribute values and type attribute values; weighting to the data attribute values and the type attribute values respectively to obtain weighted attribute values of the data attribute and weighted attribute values of the tune attribute.

There is provided a system, method and computer program product for integrating at least one analytical or modeling driver into an existing business analytic environment. The system comprises a BAMS (Business Analytics and Mathematical Sciences) driver, implemented on the memory device and run by the processor, loads a real database driver and redirects a request from a client application to the real database driver. An extension driver, invoked by the BAMS driver, provides an interface to a data modeling or processing software and converts the interface from a software environment compiled by a programming language to another software environment targeted to another programming language. The extension driver extends or overrides functionalities of the BAMS driver. Implementing the BAMS driver and the extension driver in the existing business analytic environment do not require any change made on the existing business analytic environment.

Enabling computational process as a dynamic data source for BI reporting systems

A system, method and computer program product for integrating at least one analytical or modeling driver into an existing business analytic environment. The system comprises a BAMS (Business Analytics and Mathematical Sciences) driver, implemented on the memory device and run by the processor, loads a real database driver and redirects a request from a client application to the real database driver. An extension driver, invoked by the BAMS driver, provides an interface to a data modeling or processing software and converts the interface from a software environment compiled by a programming language to another software environment targeted to another programming language. The extension driver extends or overrides functionalities of the BAMS driver. Implementing the BAMS driver and the extension driver in the existing business analytic environment do not require any change made on the existing business analytic environment.

Enabling computational process as a dynamic data source for bi reporting systems

A method of forecasting workforce demand, includes forecasting an ongoing engagements demand, forecasting an opportunities demand, forecasting a wedge engagements demand, representing a result of the forecasting the ongoing engagements demand as a first workforce demand statement, a result of the forecasting the opportunities demand as a second workforce demand statement, and a result of the forecasting the wedge engagements demand as third workforce demand statement, and integrating the first workforce demand statement, the second workforce demand statement and the third workforce demand statement to generate an overall workforce demand forecast.

Method and apparatus for workforce demand forecasting

A method (and structure) for developing a distribution function for the probability of winning a bid by a seller for a product or service, using the seller's own historical data for winning bids and lost bids, includes normalizing the data for winning bids and the data for lost bids and merging the normalized data into a single set of data.

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Shanghai, China

Heng Cao