Abstract: Systems and methods to classify incident report documents are disclosed, comprising inputting, a first type data entry of a document into a deep neural network (DNN); encoding, via the DNN, the first type data entry to output a densely embedded contextual vector representing contents of the first type data entry; generating, a list containing ordered data from a second type data entry of the document; encoding, via a machine learning network, the ordered data into a sparse vector representation of the second type data entry; concatenating, the densely embedded contextual vector with the sparse vector representation to generate a representative vector of the document; and training a gradient-boosted classifier network by using as training inputs the representative vector and a label associated with the document to generate a classification of the document.

Abstract: An intelligent bicycle sharing system, or other vehicle sharing system, is able to provide helpful bicycle availability predictions based on historical data, including various utilization statistics. Historical data can be collected over time as users use the bicycle sharing system. For example, the historical data may include the number of available bicycles at various locations and times, as well as contextual data associated with the locations and times. Contextual data may include data regarding the weather, local events, season, day of the week or year, news events, among other environmental factors that may or may not influence bicycle utilization. In some embodiments, a model, such as a machine learning model (e.g., neural network) may be trained using the historical data as training data such that the model can predict bicycle availability for a certain future time and location.

Abstract: A method, system and apparatus are provided for optimized load shaping for optimizing production and consumption of energy. Information signals indicative of a first load shape signal are obtained corresponding to a total load, a renewable energy load of one or more renewable energy sources and a non-renewable energy load of one or more non-renewable energy sources. The first load shape signal corresponding to renewable energy load is removed from a non-renewable energy load to obtain a resulting load shape signal. The resulting load shape is flattened signal by apportioning the resulting load shape signal across time intervals to obtain a flattened load shape signal. At least a portion of the first component corresponding to the renewable energy load is added to the flattened load shape signal to create an optimized load shape signal. The optimized load shape signal is provided to modulate electric loads of energy-consuming devices.

Abstract: Methods and computer systems for managing access to resources in a computing environment. Detecting a projected overload condition from a projected demand for a resource. Identifying a server associated with a resource demand scheduled to be fulfilled prior to the projected overload condition. Generating a rescheduling request to reschedule the resource demand until after the projected overload condition. Sending the rescheduling request to the identified server. Providing access to the resource at a rescheduled time.

Abstract: A system includes a first dataset of vehicle trajectories including individual vehicle tracks forming a first track density, a desired vehicle track density profile, a spatio-temporal coverage metric, and a track model including Heaviside functions encoding track time origins and durations for the individual vehicle tracks and including locations for the plurality of individual vehicle tracks. Approximations of the Heaviside functions are minimized as a function of the spatio-temporal coverage metric. The first dataset of vehicle trajectories is manipulated to satisfy the desired vehicle track density profile through minimizing an approximation of the Heaviside functions. Each individual vehicle track in the first dataset of vehicle trajectories is shifted as a result of the optimization, thereby generating a second dataset of vehicle trajectories having a second track density.

Abstract: This specification generally discloses technology for optimizing the loading of pallets on trucks and other sorts of vehicles. A pallet loading technique includes receiving pallet information for a shipment, the pallet information describing pallets to be included in the shipment, receiving vehicle constraint information for a vehicle, the vehicle constraint information describing rules for loading pallets on the vehicle, and determining candidate solutions for loading the pallets on the vehicle, each candidate solution (i) satisfying the rules for loading pallets on the vehicle, and (ii) defining, for each pallet to be included in the shipment, a respective position and orientation of the pallet on the vehicle. At least some of the candidate solutions are evaluated, one of the candidate solutions is selected, and the vehicle is loaded according to the selected candidate solution.

Abstract: A system for modeling networks of electricity supply and demand includes a first user interface, a second user interface, a database, a controller, and a memory including instructions. The database includes a data set defining nodes and domains, each node being a geographic area with defined electricity supply and demand, each plan including instructions related to a node for managing energy infrastructure and supply and demand changes. The controller is configured to: receive a first request to create a first plan for a first node of a collection; receive plan instructions for the first plan; receive a second user request to create a second plan for a second node of the collection; receive a plan instruction to interconnect the first node with the second node in the first plan; generate a forecast including a projected value for an energy infrastructure variable; and display the forecast.

Abstract: Systems and methods directed to managing computer resource allocation by monitoring signals indicating demand for services utilizing computer resources are described. A method includes maintaining, for each first event of first events, historical registration data and respective parameter values of the first event and identifying, for a second event having an open registration status, respective parameter values of the second event, and registration data for the second event. The method includes computing a similarity score between the second event and each first event of the plurality of first events, based on the respective parameter values of the first event and the second event and the registration data of the second event and the historical registration data of the first event, generating, for the second event, a projected number of entities based on determined information and determining a ranking of the second event.

Abstract: Embodiments of vehicle data systems for use in distributed computer network are disclosed. Particular embodiments may determine and enhance vehicle data from various data sources distributed across the computer network, and utilize the enhanced vehicle data in the determination of normalization metrics that account for geography and population density or spatial behavioral patterns. Embodiments may utilize these normalization metrics to determine or predict one or more metrics about participants in a network.

Abstract: An initial transaction is generated representing a forecasted demand for material needed to manufacture equipment via a supply chain. The initial transaction is added to a blockchain for access by entities in the supply chain comprising at least a subset of one or more supply entities, one or more material distribution entities, and one or more manufacturing entities. In one or more examples, the steps may be performed by an OEM blockchain node that accesses any transactions added by the various entities on the blockchain node and limits access to transactions on the blockchain by the various entities. Further, the initial transaction may be a main transaction and a transaction representing a commitment by one of the supply entities may be a sub-transaction of the main transaction, and the sub-transaction is closed in the blockchain upon the request for payment for the committed material or payment of the request.

Abstract: Systems, apparatuses, and methods for providing roadside assistance services are described herein. The system may include network computing devices and computing devices associated with user vehicles and service vehicles. The system may predict incoming requests for roadside services, and may allocate service providers among various geographical regions and/or time slots to handle the incoming requests. The system may receive a request for a roadside service from a user. The system may select an appropriate service provider to assist the user, and may assign the service request to the selected service provider.

Abstract: A transportation system controls a fleet of autonomous vehicles to implement passenger transportation and coordinate delivery of baggage or other associated items using separate vehicles. The transportation system receives passenger data and associated item data via a user interface, and determines the number and type of autonomous vehicles to transport the passengers and items from selected pick-up locations to a destination. In various implementations, the transportation system may support different pick-up locations, pick-up times and/or delivery times for the passengers and associated items. The transportation system also may determine delayed item delivery options for different delivery times and modes of transportation.

Abstract: A server for scheduling electric charging for vehicles is provided. The server receives vehicle charging information associated with a plurality of electric vehicles. The vehicle charging information includes at least one of: first information related to a location of charging, second information related to a time period of charging, or third information related to state-of-charge (SOC). The server determines, based on the received vehicle charging information, a set of electric vehicles from the plurality of electric vehicles. The server further determines a charging schedule for each of the determined set of electric vehicles based on one or more charging criterions. The server further transmits one or more charging control instructions to each of the determined set of electric vehicles, based on the determined charging schedule.

Abstract: A device, system, and method whereby a speech-driven system can distinguish speech obtained from users of the system from other speech spoken by background persons, as well as from background speech from public address systems. In one aspect, the present system and method prepares, in advance of field-use, a voice-data file which is created in a training environment. The training environment exhibits both desired user speech and unwanted background speech, including unwanted speech from persons other than a user and also speech from a PA system. The speech recognition system is trained or otherwise programmed to identify wanted user speech which may be spoken concurrently with the background sounds. In an embodiment, during the pre-field-use phase the training or programming may be accomplished by having persons who are training listeners audit the pre-recorded sounds to identify the desired user speech. A processor-based learning system is trained to duplicate the assessments made by the human listeners.

Abstract: Systems and techniques for a computational unified graph hierarchy model are disclosed herein. A set of source data may be received that may include entity data and relationship data. An entity may be identified in the entity data. A hierarchy may be determined for the entity. An entity graph network may be generated. A non-hierarchical link between the entity and a related entity may be determined. The entity graph network may be updated to include the non-hierarchical link. A set of measures may be generated for a relational link of the entity. A dependency may be configured between the set of measures for the relational link and a second set of measures of a second relational link. A change may be identified to a value of a measure and a dependent entity node measure value may be updated based on a computational effect of the change to the value.

Abstract: A mobile sensory platform includes a propulsion system configured to move the mobile sensory platform along a surface of a growing area. The mobile sensory platform also includes multiple sensors configured to capture measurement data associated with multiple plants in the growing area. The mobile sensory platform further includes a communication interface configured to support two-way communication over a wireless network. In addition, the mobile sensory platform also includes a power supply and a control system configured to control movement of the mobile sensory platform and operation of the sensors. The multiple sensors include one or more microclimate sensors configured to generate microclimate sensor data based on changes in a microclimate around individual ones of the multiple plants.

Abstract: An electric power system includes a plurality of power adjustment resources electrically connectable to a power grid, and a management device configured to manage the power adjustment resources. The management device is configured to acquire a first request signal for requesting demand-and-supply adjustment in the power grid, and a second request signal for requesting the power adjustment resources to adjust electric energy in a predetermined period, transmit a power command signal indicating a command power value for each predetermined interval in the predetermined period to a predetermined power adjustment resource included in the power adjustment resources, and generate the power command signal to respond to both requests of the first request signal and the second request signal.

Abstract: Methods and systems for determining a time-variant supplier variable related to a contract. The method includes receiving, by a processor having a supplier variable module, a user historical data set, a global historical data set and an external data set. The method includes generating, by the supplier variable module, a set of outcomes; outputting, by the supplier variable module, the set of outcomes. The set of outcomes comprises at least one time-variant supplier variable. In an example, the supplier variable module includes a supplier variable model, which includes a machine learning model.

Abstract: A calculation unit (15a) calculates a degree of association between words included in compound word candidates that are each constituted by consecutive words in a document. The calculation unit (15a) calculates the degree of association by using a conditional probability that is a probability of a word that precedes a last word being present in the document under the condition that the last word follows. A selection unit (15b) selects, as a compound word, a compound word candidate whose degree of association thus calculated is higher than a predetermined threshold value. A learning unit (15c) learns a positional relationship between words that include the selected compound word in the document and predetermined tags added to the document. An addition unit (15d) adds the predetermined tags to the document based on the positional relationship between words that include the learned compound word in the document and the predetermined tags added to the document.

Abstract: A merchant system structures communications among merchants, partners, and customers. The merchant system may include a messaging component that organizes messages so that a manager can quickly navigate and understand the content of incoming messages. The messaging system also may categorize a user's profile so that a user may share profile information established at a first merchant with a second merchant.

Abstract: A vehicle allocation system includes: an automatic driving vehicle; a mobile terminal configured to transmit a vehicle allocation request signal containing at least information on a vehicle allocation place of the automatic driving vehicle; and a server configured to allocate the automatic driving vehicle at the vehicle allocation place in response to reception of the vehicle allocation request signal, give a notification to the mobile terminal in response to arrival of the automatic driving vehicle from the vehicle allocation place within a predetermined distance range, and permit usage of the automatic driving vehicle when a user of the mobile terminal is authenticated based on authentication information transmitted from the mobile terminal in response to the notification.

Abstract: Systems and methods are provided herein for producing and vending ice in an energy-efficient manner. A system for producing and vending ice comprises: an ice-making device configured to manufacture ice; a reservoir coupled to the ice-making device and configured to store the manufactured ice manufactured; and a control circuit communicatively coupled to the ice-making device, the control circuit configured to: determine a beginning ice inventory at a first time; determine a predicted ice demand for a first period, wherein the predicted ice demand is a function of at least a historical factor, a weather factor, a customer social event factor, and a public social event factor; determine an ice manufacturing quantity based on the beginning ice inventory, the predicted ice demand, and a manufacturing capacity of the ice-making device; and cause the ice-making device to produce an amount of ice consistent with the determined ice manufacturing quantity.

Abstract: A power management system includes a plurality of power adjustment resources electrically connected to a microgrid. The plurality of power adjustment resources include a plurality of EVSEs, each of EVSEs including a parking space. When any one of a plurality of power feeding vehicles is parked in the parking space, an EVSE enables power feeding from a vehicle parked in the parking space to the microgrid. A CEMS server manages the parking space. When a balance of power supply and demand in the microgrid is in an overdemand state, the CEMS server allocates the parking space to a power feeding vehicle that responds to a request for power feeding to the microgrid, of the plurality of power feeding vehicles.

Abstract: A method (200) for determining future resource requirements in a given location, the method comprising the steps of obtaining (110) transaction data, the transaction data indicative of past resource use at a given location. At least one model may be trained (120) based on a set of parameters by determining (121) a distribution associated with the transaction data; and generating (122) a kernel based on the distribution and the set parameters, the kernel being arranged to output an estimated distribution. The kernel is refined (123) and validated (124) based on a comparison between the distribution and the estimated distribution. A density map is then generated (125) based on the at least one trained model. The density map is then sent (130) to a control system for determining future resource requirements in the given location.

Abstract: An example method of dynamically distributing messaging resources in a software as a service (SaaS) platform includes: receiving, by a processing device, from a first tenant associated with a first tenant set of a plurality of tenant sets, a request to forward a first message to a recipient within a specified destination; identifying, among a plurality of queues associated with the plurality of tenant sets, a subset of queues associated with the first tenant; queuing the first message into a first queue of the subset of queues associated with the first tenant; assigning, to each queue of the plurality of queues, a score reflecting a respective tenant portion of a messaging resource quota associated with the specified destination; retrieving a second message from a queue associated with a highest score; and forwarding the second message to a messaging gateway associated with the specified destination.

Abstract: A method, computer program, and computer system are provided for load forecasting. Datasets corresponding to source machine learning models and a target domain base model are identified. A set of forecasting models corresponding to the identified datasets are learned. An ensemble model is determined from the learned set of forecasting models based on gradient boosting. An available resource is allocated based on the ensemble model.

Abstract: Provided is a system, including: a demand information acquisition unit configured to acquire information indicating power demand in a power network; and a setting unit configured to, based on the power demand, set a usage fee for a parking lot having a power transmission and reception facility for a vehicle having a power supply for driving to transmit and receive power to/from the power network.

Abstract: A system includes a first facility element having a sensor and configured to generate recent performance data associated with a system of a facility, and a monitoring and control element in communication with the first facility element, where the monitoring and control element is configured to identify one or more analogous facility elements analogous to the first facility element, receive the recent performance data for the first facility element, generate projected performance data for the facility element according to historical performance data associated with the facility element and the one or more analogous facility elements, compare the projected performance data to a performance threshold, and override a setting or operating parameter of the first facility element according to a relationship of the projected performance data to the performance threshold and by sending one or more operational adjustment commands to at least one second facility element.

Abstract: Predicting end-of-life support deprecation is described. A system receives an identification of a product, and then identifies support request records associated with the product. The system identifies support information associated with the support request records. A predictive model uses the support information to predict a deprecation for the product. The system outputs the prediction of the deprecation for the product.

Abstract: A “SOUND ID SYSTEM” comprise a Device with a microphone that continuously monitors the surrounding environment. Pre-recorded personalized or unique sound patterns, signatures, and/or key words, and/or their derivatives, are stored in the Device. When such a pre-determined pre-recorded sound pattern, signature, or key words, or their derivatives, are recognized by the Device, a corresponding pre-determined action or action sequence will be sent to the Cloud, or other devices, to execute. Such other devices can attach, co-habitat, and wired/wirelessly connect to the Device, or share some components with the Device. If the Device does not recognize any particular pre-recorded sound pattern, signature or key words, or their derivatives, then the Device will not transmit to disclose to any outside device or other entity, any monitored sound information.

Abstract: A plant treatment platform uses a plant detection model to detect plants as the plant treatment platform travels through a field. The plant treatment platform receives image data from a camera that captures images of plants (e.g., crops or weeds) growing in the field. The plant treatment platform applies pre-processing functions to the image data to prepare the image data for processing by the plant detection model. For example, the plant treatment platform may reformat the image data, adjust the resolution or aspect ratio, or crop the image data. The plant treatment platform applies the plant detection model to the pre-processed image data to generate bounding boxes for the plants. The plant treatment platform then can apply treatment to the plants based on the output of the machine-learned model.

Abstract: A method may include applying, to a content associated with a first supplier, a machine learning model to determine one or more objectives of an enterprise affected by an incident associated with the content. A change in a first risk associated with the first supplier may be detected based on the objectives affected by the incident. In response to detecting the change in the first risk of the first supplier, a cost associated with replacing the first supplier with the second supplier may be determined by applying the machine learning model to analyze a first electronic document associated with the first supplier. If the cost of replacing the first supplier with the second supplier and/or a second risk of the second supplier satisfy one or more thresholds, a second electronic document associated with the second supplier may be generated to address the second risk of the second supplier.

Abstract: Systems and methods directed to managing computer resource allocation by monitoring signals indicating demand for services utilizing computer resources are described. A method includes maintaining, for each first event of first events, historical registration data and respective parameter values of the first event and identifying, for a second event having an open registration status, respective parameter values of the second event, and registration data for the second event. The method includes computing a similarity score between the second event and each first event of the plurality of first events, based on the respective parameter values of the first event and the second event and the registration data of the second event and the historical registration data of the first event, generating, for the second event, a projected number of entities based on determined information and determining a ranking of the second event.

Abstract: An integrated system and method measures building characteristics and user behavior to provide real-time and forecasted utility usages and costs. The system gathers current and historical heating and cooling load data, compares the data with current and historical weather data and a building system set point, and calculates the heating or cooling load needed for the building based on the user's call for heat or cooling and the ambient environmental conditions. The system additionally analyzes individual device usage using usage signatures and user inputted tracking to create a comprehensive real-time and forecast of utility usages with the estimated costs. Through history of selections with usage changes corresponding to user input of individual devices, the system will be able to learn various devices' usage. The system then creates a comprehensive, real-time forecast of utility costs including the foregoing characteristics.

Abstract: A system may include a rental property listing portal and a rental price prediction unit. The rental price prediction unit may additional include an amenity price prediction unit. The rental price prediction unit and the amenity price prediction unit may use one or more mathematical models, such as constrained optimization model and/or a machine learning approach such as a random forest model, to generate a suggested rental price at a given level of portfolio occupancy. The system may also provide risk thresholds to simulate leasing strategies based on market situations, predicting revenue potential and possible vacancy for each strategy. The system may also generate a delist time (time to rent) for a property at a given price. The system and method may be implemented in a multi-family apartment rental system, a storage space rental system, a student accommodation, and single family apartment rental systems.

Abstract: A non-transitory computer-readable medium stores computer-readable instructions executable by a processor of an information processing device communicable with a printer configured to perform printing until a print permission amount reaches a particular threshold. The instructions are configured to, when executed by the processor, cause the information processing device to obtain a first number of sheets that indicates a remaining number of sheets printable according to consumable information, in response to receiving, via a user interface, an instruction to add an additional print permission amount, obtain a second number of sheets that indicates an additional number of sheets printable by the printer according to the additional print permission amount, determine whether the second number of sheets is more than the first number of sheets, and when determining that the second number of sheets is more than the first number of sheets, cause the user interface to provide a notification.

Abstract: Implementations relate to crop yield prediction at the field- and pixel-level. In various implementations, a first temporal sequence of high-elevation digital images may be obtained that capture a first geographic area and are acquired over a first predetermined time interval while the first geographic area includes a particular crop. A first plurality of other data points may also be obtained that influence a ground truth crop yield of the first geographic area after the first predetermined time interval. The first plurality of other data points may be grouped into temporal chunks corresponding temporally with respective images of the first temporal sequence. The first temporal sequence and the temporal chunks of the first plurality of other data points may be applied, e.g., iteratively, as input across a machine learning model to estimate a crop yield of the first geographic area at the end of the first predetermined time interval.

Abstract: A building energy system includes equipment operable to consume, store, or generate one or more resources, a utility connection configured to obtain, from a utility provider, a first resource subject to a load-following-block rate structure and provide the first resource to the equipment, and a controller. The controller provides an objective function indicating a total value of purchasing the first resource from the utility provider over a plurality of time steps. The objective function includes a first term representing a load-following-block of the first resource from the utility provider as being sourced from a first supplier at a fixed rate and a second term representing a remainder of the first resource from the utility provider as being sourced from a second supplier at a variable rate. The controller controls the equipment based on a result of an optimization of the objective function.

Abstract: A system including: a processor; and a memory storing computer program code that controls the processor to: collect real-time business process metrics; collect real-time cluster metrics for a plurality of application clusters indicative of a required allotment of infrastructure resources for a given business process level; estimate a predicted future business process level; based on the estimated predicted future business process level and the real-time cluster metrics, predict a future infrastructure resource requirement of each of the plurality of application clusters; compare the predicted future infrastructure resource requirement of each of the plurality of application clusters to a current dedication of each of the plurality of application clusters; automatically adjust, in real-time and based on the comparison, respective allotments of infrastructure resources for each of the plurality of application clusters; receive an actual business process; and process the business process across the plurality of

Abstract: The disclosed embodiments provide a system for predicting hiring priorities. During operation, the system determines hiring features characterizing hiring activity by a company for a set of titles. Next, the system applies a first machine learning model to the hiring features to produce a first set of scores representing future hiring volumes and applies a second machine learning model to the hiring features to produce a second set of scores representing future hiring growth. The system then generates a first ranking of the titles by the first set of scores and a second ranking of the titles by the second set of scores. Finally, the system outputs at least a portion of the first ranking as a prediction of future hiring volumes by the company and at least a portion of the second ranking as a prediction of future hiring growth by the company.

Abstract: An infrastructure management subsystem receives a selection of a planned configuration of the computing infrastructure and a baseline demand that includes a current usage of computing resources of the computing infrastructure. The infrastructure management subsystem determines an anticipated turbulence. The anticipated turbulence includes a quantitative indication of anticipated fluctuations in future infrastructure demand as a function of time. The infrastructure management subsystem determines an effective turbulence for the planned infrastructure configuration. The effective turbulence includes a quantitative indication of anticipated fluctuations in future infrastructure availability. The infrastructure management subsystem determines a configuration score corresponding to an extent to which the anticipated fluctuations in the effective turbulence destructively interfere with the anticipated fluctuations in the anticipated turbulence.

Abstract: Described is a poll-based system that provides an on-line and mobile network of users and products, goods and services that are determined through polling each of the users. The system compares, in real-time, the current user's polling responses to identify which most similarly match the answered questions to that of the user. As the user progressively answers questions, the system updates the matching and presentation other users and of products, goods and services. Thus, as the user answers polling questions, the selected answers are compared against the selected descriptions of other products, goods and services, or general questions, to generate a likelihood of match between the users, and also each of the products, goods and services. The profiles of products, goods and services that have a likelihood of match within a predetermined threshold are then presented, including links within the profile for specific purchases.

Abstract: Systems and methods for a product driven approach to technology provisioning, operations, and billing are provided. Some embodiments provide an Information Technology (IT) business architecture built around the product driven methodology. This architecture can be designed to optimize the demand side provisioning of technology products to meet business intent and the execution of supply side assembly and implementation lifecycle. A technology model can be used that recursively decomposes services and products into various components. As a result, the technology model allows for effective and efficient provisioning, pricing, and impact assessment of the organization's technology to thereby drive the efficiency of scale and the automation of the provisioning, the finance, and the operation businesses.

Abstract: A method, computer program product, and a system where a processor(s) determines generates a cognitive user profile representing patterns of usage of each of a plurality of users of the transportation resource sharing system, a cognitive resource profile for each resource of the plurality of resources, a cognitive route profile for each route traversed by at least one resource of the plurality of resources, and a cognitive station profile for each station of the plurality of stations. The processor(s) assigns one or more specific resources of the plurality of resources to one or more specific users of the plurality of users and the one or more specific resources of the plurality of resources to one or more specific stations of the plurality of stations.

Abstract: A merchant system structures communications among merchants, partners, and customers. The merchant system may include a messaging component that organizes messages so that a manager can quickly navigate and understand the content of incoming messages. The messaging system also may categorize a user's profile so that a user may share profile information established at a first merchant with a second merchant.

Abstract: In an example embodiment, a method determines a container containing one or more items associated with one or more item types, the container located at a current position in a storage facility; determines one or more order likelihoods of the one or more item types contained in the container; determines a container utilization likelihood of the container based on the one or more order likelihoods of the one or more item types contained in the container; determines an optimal position for the container in the storage facility based on the container utilization likelihood of the container, the optimal position being different from the current position of the container; and instructing an automated guided vehicle (AGV) to transport the container from the current position of the container to the optimal position of the container in the storage facility.

Abstract: Event-based replenishment simulation for an enterprise supply chain is described. On a per item, per node, per epoch basis, the simulation may generate a stream of action events based on forecasted demand, supply chain logic, and policy inputs that are applied to a current-run state of the supply chain in order to yield a stream of observation events. Requested metrics may be received, and the observation events may then be transformed to predict values for the metrics as output of the simulation. The simulation may be repeated for a given epoch using discrete demand values from a demand distribution, for a plurality of epochs, and/or across a plurality of items at a plurality of nodes. Resultantly, the simulation output can be used for predicting a future run-state of the supply chain across items and nodes.

Abstract: In some implementations, a device may receive data identifying products and encoded data identifying smart tags of the products. The device may map the data and the encoded data to generate encoded product data. The device may receive encoded data provided by smart tags of products received by a store. The device may receive images of the products. The device may compare the encoded data and the encoded product data to identify a set of the products received by the store. The device may correlate the images with the set of the products. The device may process the correlated data to identify locations of the set of the products in the store. The device may generate an instruction to relocate a product to a new location and may provide the instruction to a device, associated with the store, to cause the product to be relocated to the new location.

Abstract: A system and method for adaptive advertisement management for the serving of vehicle description pages and an automated customer engagement thereof. The system is a cloud-based network containing a campaign database, an analytics database, an adaptive advertisement management, a short message service server with automated response capabilities, and user mobile and compute devices that transmit a vehicle description page associated with an advertisement campaign embedded with a communication initiator for display on a customer computing device. Taken together or in part, said system optimizes advertising campaigns across multiple platforms, provides strong analytics for all advertising types while allowing users to engage with advertising quickly and in a real-time automated fashion.

Abstract: A computer implemented method for optimizing a delivery or settlement process for a plurality of portfolios of a plurality of participants. Data records indicative of obligations between the plurality of participants are identified. A weighted directed graph data structure is generated that comprises vertex data records representing the plurality of participants and edge data records representing the obligations between the participants. All paths of edge data records where a vertex data record is reachable from itself in the weighted directed graph data structure are identified. The data records indicative of obligations between the plurality of participants are altered based on the identified paths.