Abstract: A vehicle coordination system is provided for coordinating the trajectories of vehicles on a road network. The vehicle coordination system comprises a plurality of vehicles each having respective vehicle position tracking assemblies that are in communication with respective vehicle communication systems for transmitting vehicle state messages including positions of the vehicles. A task assignment allocator is provided that is arranged to generate task assignments for each of the plurality of vehicles, including destinations in the road network for the vehicles. A vehicle coordination assembly is in communication with the vehicle communication systems via a data network for receiving the vehicle state messages.

Abstract: In one aspect, a method for filtering out erroneous sequence reads from a genomic sequence dataset, is disclosed. The genomic sequence dataset is received by one or more processors. The dataset is comprised of a plurality of fragment sequence reads, each with an associated barcode sequence and a unique identifier sequence. A threshold value for filtering out select fragment sequence reads from the genomic sequence dataset is determined by the one or more processors. The threshold value is a number of fragment sequence reads in the genomic sequence dataset with the same unique identifier sequence. Fragment sequence reads with the same unique identifier sequence occurring at less than the threshold value in the genomic sequence dataset is filtered out by the one or more processors. A filtered genomic sequence dataset is generated by the one or more processors.

Abstract: Method for identifying a subset of cells from a dataset for targeted gene expression analysis, comprising: defining an expected total recovered cell count for a barcode dataset; determining a region of interest for the total recovered cell count by calculating a lower bound for the region; and (b) calculating an upper bound for the region of interest by including an additional subset of barcodes having molecule counts below the lower bound; fitting the barcode dataset to a model; wherein the model groups barcodes as a function of molecule count; identifying a cut-off value on the model, wherein all barcodes having a molecule count above the cut-off value are called as cells; and identifying a targeted subset of cells from the called cells for conducting targeted gene expression, wherein a cell qualifies as part of the targeted subset if the cell has a molecule count above a target threshold.

Abstract: A system and method for isolating electronic data and generating enhanced data. A data subscription unit receives data having plural data formats from data source devices. The data may be received pre-filtered or filtered by the data subscription unit. A modeling unit may receive the filtered data from the storage databases, may determine eligibility of the stored data based on eligibility criteria, sort the eligible data based on at least one sorting parameter, adjust and/or normalize the eligible data based on at least one adjustment parameter and/or an aggregate value for a data attribute, generate data metrics over a defined set of time periods based on the eligible data, generate further data metrics based on the data metrics, and derive specified values from these metrics. A data distribution device may transmit or make available the data metrics, further data metrics and values to remote devices.

Abstract: A system and method for isolating electronic data and generating enhanced data. A data subscription unit receives data having plural data formats from data source devices. The data may be received pre-filtered or filtered by the data subscription unit. A modeling unit may receive the filtered data from the storage databases, may determine eligibility of the stored data based on eligibility criteria, sort the eligible data based on at least one sorting parameter, adjust and/or normalize the eligible data based on at least one adjustment parameter and/or an aggregate value for a data attribute, generate data metrics over a defined set of time periods based on the eligible data, generate further data metrics based on the data metrics, and derive specified values from these metrics. A data distribution device may transmit or make available the data metrics, further data metrics and values to remote devices.

Abstract: A method is provided for operating a railway network having a number of trains, the method comprises operating a scheduling machine that is in communication with the railway network over a data communication system, to receive time separated state data defining states of the railway network at respective times. The scheduling machine accesses a model of the railway network that is stored in an electronic data source. The model defines locations in the railway network that allows for passing of trains and paths for journeys of each of the trains. The method includes operating the scheduling machine to apply the state data to the model to determine, at each of the respective times, controls associated with each trains' path for each of the trains.

Abstract: A system and method for isolating electronic data and generating enhanced data. A data subscription unit receives data having plural data formats from data source devices. The data may be received pre-filtered or filtered by the data subscription unit. A modeling unit may receive the filtered data from the storage databases, may determine eligibility of the stored data based on eligibility criteria, sort the eligible data based on at least one sorting parameter, adjust and/or normalize the eligible data based on at least one adjustment parameter and/or an aggregate value for a data attribute, generate data metrics over a defined set of time periods based on the eligible data, generate further data metrics based on the data metrics, and derive specified values from these metrics. A data distribution device may transmit or make available the data metrics, further data metrics and values to remote devices.

Abstract: A system and method for isolating electronic data and generating enhanced data. A data subscription unit receives data having plural data formats from data source devices. The data may be received pre-filtered or filtered by the data subscription unit. A modeling unit may receive the filtered data from the storage databases, may determine eligibility of the stored data based on eligibility criteria, sort the eligible data based on at least one sorting parameter, adjust and/or normalize the eligible data based on at least one adjustment parameter and/or an aggregate value for a data attribute, generate data metrics over a defined set of time periods based on the eligible data, generate further data metrics based on the data metrics, and derive specified values from these metrics. A data distribution device may transmit or make available the data metrics, further data metrics and values to remote devices.

Abstract: A system and method for isolating electronic data and generating enhanced data. A data subscription unit receives data having plural data formats from data source devices. The data may be received pre-filtered or filtered by the data subscription unit. A modeling unit may receive the filtered data from the storage databases, may determine eligibility of the stored data based on eligibility criteria, sort the eligible data based on at least one sorting parameter, adjust and/or normalize the eligible data based on at least one adjustment parameter and/or an aggregate value for a data attribute, generate data metrics over a defined set of time periods based on the eligible data, generate further data metrics based on the data metrics, and derive specified values from these metrics. A data distribution device may transmit or make available the data metrics, further data metrics and values to remote devices.

Abstract: Systems and methods for projecting one or more trends in electronic data and generating enhanced data. A system includes a data forecasting system is in electronic communication with one or more electronic data sources via an electronic network. The data forecasting system is configured to: monitor the electronic data source(s) for data that meet one or more predetermined criteria; obtain at least a portion of the monitored data from electronic data source(s) based on the predetermined criteria; create a data set from the obtained data; derive one or more data values associated with the data set over a predetermined period according to a forward-looking term methodology; and utilize the data set and the derived value(s) over the predetermined period to derive at least one data forecast metric associated with the data set.

Abstract: A system and method for isolating electronic data and generating enhanced data. A data subscription unit receives data having plural data formats from data source devices. The data may be received pre-filtered or filtered by the data subscription unit. A modeling unit may receive the filtered data from the storage databases, may determine eligibility of the stored data based on eligibility criteria, sort the eligible data based on at least one sorting parameter, adjust and/or normalize the eligible data based on at least one adjustment parameter and/or an aggregate value for a data attribute, generate data metrics over a defined set of time periods based on the eligible data, generate further data metrics based on the data metrics, and derive specified values from these metrics. A data distribution device may transmit or make available the data metrics, further data metrics and values to remote devices.

Abstract: Systems and methods for projecting one or more trends in electronic data and generating enhanced data. A system includes a data forecasting system is in electronic communication with one or more electronic data sources via an electronic network. The data forecasting system is configured to: monitor the electronic data source(s) for data that meet one or more predetermined criteria; obtain at least a portion of the monitored data from electronic data source(s) based on the predetermined criteria; create a data set from the obtained data; derive one or more data values associated with the data set over a predetermined period according to a forward-looking term methodology; and utilize the data set and the derived value(s) over the predetermined period to derive at least one data forecast metric associated with the data set.

Abstract: Systems and methods for projecting one or more trends in electronic data and generating enhanced data. A system includes a data forecasting system is in electronic communication with one or more electronic data sources via an electronic network. The data forecasting system is configured to: monitor the electronic data source(s) for data that meet one or more predetermined criteria; obtain at least a portion of the monitored data from electronic data source(s) based on the predetermined criteria; create a data set from the obtained data; derive one or more data values associated with the data set over a predetermined period according to a forward-looking term methodology; and utilize the data set and the derived value(s) over the predetermined period to derive at least one data forecast metric associated with the data set.

Abstract: Systems and methods for projecting one or more trends in electronic data and generating enhanced data. A system includes a data forecasting system is in electronic communication with one or more electronic data sources via an electronic network. The data forecasting system is configured to: monitor the electronic data source(s) for data that meet one or more predetermined criteria; obtain at least a portion of the monitored data from electronic data source(s) based on the predetermined criteria; create a data set from the obtained data; derive one or more data values associated with the data set over a predetermined period according to a forward-looking term methodology; and utilize the data set and the derived value(s) over the predetermined period to derive at least one data forecast metric associated with the data set.

Abstract: A system and method for isolating electronic data and generating enhanced data. A data subscription unit receives data having plural data formats from data source devices. The data may be received pre-filtered or filtered by the data subscription unit. A modeling unit may receive the filtered data from the storage databases, may determine eligibility of the stored data based on eligibility criteria, sort the eligible data based on at least one sorting parameter, adjust and/or normalize the eligible data based on at least one adjustment parameter and/or an aggregate value for a data attribute, generate data metrics over a defined set of time periods based on the eligible data, generate further data metrics based on the data metrics, and derive specified values from these metrics. A data distribution device may transmit or make available the data metrics, further data metrics and values to remote devices.

Abstract: Systems and methods for projecting one or more trends in electronic data and generating enhanced data. A system includes a data forecasting system is in electronic communication with one or more electronic data sources via an electronic network. The data forecasting system is configured to: monitor the electronic data source(s) for data that meet one or more predetermined criteria; obtain at least a portion of the monitored data from electronic data source(s) based on the predetermined criteria; create a data set from the obtained data; derive one or more data values associated with the data set over a predetermined period according to a forward-looking term methodology; and utilize the data set and the derived value(s) over the predetermined period to derive at least one data forecast metric associated with the data set.