Xiaoxuan
Xiaoxuan Leaym, Manhattan, KS US
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20120157824 | MRI AND OPTICAL ASSAYS FOR PROTEASES - The present invention provides multifunctional nanoplatforms for assessing the activity of a protease in vivo or in vitro, along with methods of imaging and detecting the presence of cancerous or precancerous tissues, and the therapeutic treatment thereof, including monitoring of treatment. The diagnostic nanoplatforms comprise nanoparticles and are linked to each other or other particles via an oligopeptide linkage that comprises a consensus sequence specific for the target protease. Cleavage of the sequence by the target protease can be detected using various sensors, and the diagnostic results can be correlated with cancer prognosis. Individual unlinked nanoplatforms are also adaptable for therapeutic hyperthermia treatment of the cancerous tissue. | 06-21-2012 |
Xiaoxuan Zhang, Stony Brook, NY US
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20120078687 | SYSTEM AND METHOD FOR LOWEST COST AGGREGATE ENERGY DEMAND REDUCTION - A method, apparatus and computer program product for determining lowest cost aggregate energy demand reduction at multiple network levels such as distribution and feeder networks. An algorithm for an optimal incentive mechanism offered to energy customers (e.g. of a utility power entity) that accounts for heterogeneous customer flexibility in load reduction, with the demand response realized via the utility's rebate signal and, accounts for temporal aspects of demand shift in response for rebates. A mathematical formulation of a cost minimization problem is solved to provide incentives for customers to reduce their demand. A gradient descent algorithm is used to solve for the optimal incentives customized for individual end users. | 03-29-2012 |
20120185106 | INTEGRATION OF DEMAND RESPONSE AND RENEWABLE RESOURCES FOR POWER GENERATION MANAGEMENT - System and method of solving, in a single-period, an optimal dispatching problem for a network of energy generators connected via multiple transmission lines, where it is sought to find the lowest operational cost of dispatching of various energy sources to satisfy demand. The model includes traditional thermal resources and renewable energy resources available generation capabilities within the grid. The method considers demand reduction as a virtual generation source that can be dispatched quickly to hedge against the risk of unforeseen shortfall in supply. Demand reduction is dispatched in response to incentive signals sent to consumers. The control options of the optimization model consist of the dispatching order and dispatching amount energy units at generators together with the rebate signals sent to end-users at each node of the network under a demand response policy. Numerical experiments based on an analysis of representative data illustrate the effectiveness of demand response as a hedging option. | 07-19-2012 |
Xiaoxuan Zhang, Park Ridge, NJ US
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20140324532 | SYSTEM AND METHOD FOR MODELING AND FORECASTING CYCLICAL DEMAND SYSTEMS WITH DYNAMIC CONTROLS AND DYNAMIC INCENTIVES - Systems and methods for modeling and forecasting cyclical demand systems in the presence of dynamic control or dynamic incentives. A method for modeling a cyclical demand system comprises obtaining historical data on one or more demand measurements over a plurality of demand cycles, obtaining historical data on incentive signals over the plurality of demand cycles, constructing a model using the obtained historical data on the one or more demand measurements and the incentive signals, wherein constructing the model comprises specifying a state-space model, specifying variance parameters in the model, and estimating unknown variance parameters. | 10-30-2014 |
20140365022 | Managing Time-Substitutable Electricity Usage using Dynamic Controls - A predictive-control approach allows an electricity provider to monitor and proactively manage peak and off-peak residential intra-day electricity usage in an emerging smart energy grid using time-dependent dynamic pricing incentives. The daily load is modeled as time-shifted, but cost-differentiated and substitutable, copies of the continuously-consumed electricity resource, and a consumer-choice prediction model is constructed to forecast the corresponding intra-day shares of total daily load according to this model. This is embedded within an optimization framework for managing the daily electricity usage. A series of transformations are employed, including the reformulation-linearization technique (RLT) to obtain a Mixed-Integer Programming (MIP) model representation of the resulting nonlinear optimization problem. In addition, various regulatory and pricing constraints are incorporated in conjunction with the specified profit and capacity utilization objectives. | 12-11-2014 |
20140365024 | Managing Time-Substitutable Electricity Usage using Dynamic Controls - A predictive-control approach allows an electricity provider to monitor and proactively manage peak and off-peak residential intra-day electricity usage in an emerging smart energy grid using time-dependent dynamic pricing incentives. The daily load is modeled as time-shifted, but cost-differentiated and substitutable, copies of the continuously-consumed electricity resource, and a consumer-choice prediction model is constructed to forecast the corresponding intra-day shares of total daily load according to this model. This is embedded within an optimization framework for managing the daily electricity usage. A series of transformations are employed, including the reformulation-linearization technique (RLT) to obtain a Mixed-Integer Programming (MIP) model representation of the resulting nonlinear optimization problem. In addition, various regulatory and pricing constraints are incorporated in conjunction with the specified profit and capacity utilization objectives. | 12-11-2014 |
20150019289 | System and Method for Forecasting Prices of Frequently-Promoted Retail Products - Systems and methods for forecasting prices of products are provided. A method for forecasting prices of products, comprises obtaining a time series history of a price of a product, imputing a state indicator value for each price data from the time series history, wherein a state is one of a promotional price state and a regular price state, extracting a first price time series for the price data in the promotional state and a second price time series for the price data in the regular state, extracting a promotion duration time series from the time series history, obtaining respective point forecasts for the extracted first price time series, the second price time series and the promotion duration time series, and combining the point forecasts for the extracted first and second price time series and the promotion duration time series to obtain a final price forecast. | 01-15-2015 |
20150019295 | SYSTEM AND METHOD FOR FORECASTING PRICES OF FREQUENTLY- PROMOTED RETAIL PRODUCTS - Systems and methods for forecasting prices of products are provided. A method for forecasting prices of products, comprises obtaining a time series history of a price of a product, imputing a state indicator value for each price data from the time series history, wherein a state is one of a promotional price state and a regular price state, extracting a first price time series for the price data in the promotional state and a second price time series for the price data in the regular state, extracting a promotion duration time series from the time series history, obtaining respective point forecasts for the extracted first price time series, the second price time series and the promotion duration time series, and combining the point forecasts for the extracted first and second price time series and the promotion duration time series to obtain a final price forecast. | 01-15-2015 |
Xiaoxuan Zhang, Jersey City, NJ US
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20150235239 | PREDICTING DEMAND OF A NEWLY INTRODUCED SHORT LIFECYCLE PRODUCT WITHIN AN ASSORTMENT - Predicting demand of a newly launched product may comprise obtaining customer sentiment data associated with the newly launched product, the customer sentiment data obtained at least from social media. A mean sentiment lag associated with the customer sentiment data may be determined. A weight given to a predicted PLC effect of the newly launched product relative to customer sentiment identified in the customer sentiment data may be determined. Numerical prediction parameters from parameter values associated with a like-item that is determined to be similar to the newly launched product may be obtained. A product utility valuation may be computed as a weighted combination of the predicted PLC effect and a lagged social media sentiment determined from the customer sentiment data accounted by the mean sentiment lag. The product utility valuation provides an indication of the future demand of the newly launched product. | 08-20-2015 |
Xiaoxuan Zhao, Shanghai CN
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20120210332 | ASYNCHRONOUS PROGRAMMING EXECUTION - One or more techniques and/or systems are disclosed for improving asynchronous programming execution at runtime. Asynchronous programming code can comprise more than one level of hierarchy, such as in an execution plan. Respective aggregation operations in a portion of the asynchronous programming code are unrolled, to create a single level iterative execution, by combining elements of the multi-level iterative execution of the asynchronous programming code. In this way, the aggregation operations are concatenated to local logic code for the aggregation operations. Thread context switching in the unrolled portion of asynchronous programming code is performed merely at an asynchronous operation, thereby mitigating unnecessary switches. Exceptions thrown during programming code can be propagated up to a top of a virtual callstack for the execution. | 08-16-2012 |