Abstract: Techniques are described for providing a ML data analytics application including guided ML workflows that facilitate the end-to-end training and use of various types of ML models, where such guided workflows may also be referred to as ML “experiments.” For example, the ML data analytics application may enable users to create experiments related to prediction of numeric fields (for example, using linear regression techniques), predicting categorical fields (for example, using logistic regression), detecting numerical outliers (for example, using various distribution statistics), detecting categorical outliers (for example, using probabilistic statistics), forecasting time series data, and clustering numeric events (for example, using k-means, density-based spatial clustering of applications with noise (DBSCAN), spectral clustering, or other techniques), among other possible uses of various types of ML models to analyze data.

Abstract: Techniques for heterogeneous compute instance auto-scaling with reinforcement learning (RL) are described. A user specifies a reward function that generates rewards for use with an application simulation for determining what different instance types should be added to or removed from the application as part of training a RL model. The RL model can be automatically deployed and used to monitor an application to automatically scale the application fleet using heterogenous compute instances.

Abstract: A method, apparatus and a product for generating a dataset for a reinforcement model. The method comprises obtaining a plurality of different subsets of the set of features; for each subset of features, determining a policy using a Markov Decision Process; obtaining a state comprises a valuation of each feature of the set of features; applying the plurality of policies on the state, whereby obtaining a plurality of suggested actions for the state, based on different projections of the state onto different subsets of features; determining, for the state, one or more actions and corresponding scores thereof based on the plurality of suggested actions; and training a reinforcement learning model using the state and the one or more actions and corresponding scores thereof.

Abstract: A system configured to perform decision tasks carried out by a machine learning engine operates with a machine learning model, and includes a training component for improving the machine learning model, a device for carrying out decisions based on a set of input data, and an interaction interface for switching the machine learning model between training component and a device that includes a model attestation checker. The device performs acquiring input data, and ascertaining at least one machine learning model over the interaction interface. The model attestation checker performs checking if said machine learning model is trusted by a model attestation, and considering, for decision making, only those machine learning models that are trusted. The machine learning engine performs carrying out the decision task for input data by using a trusted machine learning model, and providing a result attestation for the decision output.

Abstract: Techniques for adapting previously-annotated training examples into updated training examples for training a machine learning model are disclosed. One example includes a computer program that recognizes a find expression, a replacement expression, and a filtering constraint in which the filtering constraint distinguishes a subset of previously-annotated training examples from others of the previously-annotated training examples. An instance of the find expression is identified by the computer program within the subset of the previously-annotated training examples that were identified among the previously-annotated training examples based on the filtering constraint. The instance of the find expression identified within the subset of the previously-annotated training examples is replaced by the computer program with an instance of the replacement expression to obtain an updated subset of training examples.

Abstract: A vehicle recommendation device and a method for machine learning based recommendation of vehicle is provided. The vehicle recommendation device receives vehicle log data from a plurality of sensors associated with each of a first set of vehicles. The first set of vehicles are classified based on a set of vehicle types. The vehicle recommendation device generates vehicle trip data, associated with a plurality of trips of each of the first set of vehicles, based on the received vehicle log data. The vehicle recommendation device further determines a set of features, associated with the plurality of trips or with information about the first set of vehicles, based on the generated vehicle trip data. The vehicle recommendation device further generates a machine learning model which is trained based on the determined set of features to output a first type of vehicle from the set of vehicle types.

Abstract: Systems and methods are described herein for curating content that follows a narrative structure. A narrative structure comprises narrative portions that have a defined order. Signature analysis of known content that follows the narrative structure is used to train machine learning models for the narrative structure and the narrative portions that make up the narrative structure. Signature analysis of candidate content segments, along with machine learning models for the narrative portions, are used to identify candidate content segments that match the respective narrative portions. A candidate playlist is generated of the identified candidate content segments in the defined order. In one embodiment, the machine learning model for the narrative structure is used to validate the generated playlist.

Abstract: Techniques for refinement of data pipelines are provided. An original file of serialized objects is received, and an original pipeline comprising a plurality of transformations is identified based on the original file. A first computing cost is determined for a first transformation of the plurality of transformations. The first transformation is modified using a predefined optimization, and a second cost of the modified first transformation is determined. Upon determining that the second cost is lower than the first cost, the first transformation is replaced, in the original pipeline, with the optimized first transformation.

Abstract: Classification of erroneous cell data includes performing unsupervised pre-training of a machine learning model to learn a bidirectional encoder representation of data cells, obtaining an initial training set, with labeled training examples that correlate observed cell data to correct cell data, for training the machine learning model to classify cell data, automatically augmenting the initial training set to produce an augmented training set, where the augmenting includes identifying patterns in the labeled training examples, generating transformation functions, and using the transformation functions, learning an augmentation strategy and automatically generating additional training examples correlating erroneous data values to correct data values, and training the machine learning model using the augmented training set.

Abstract: An agricultural data collection framework is provided in a system and method for tracking and managing livestock, and for analyzing animal conditions such as health, growth, nutrition, and behavior. The framework uses ultra-high frequency interrogation of RFID tags to collect individual animal data across multiple geographical locations, and incorporates artificial intelligence techniques to develop machine learning base models for statistical process controls around each animal for evaluating the animal condition. The framework provides a determination of normality at an individual animal basis or for a specific location, and generates alerts, predictions, and a targeted processing or application schedule for prioritizing and delivering resources when intervention is needed.

Abstract: A method includes obtaining at least one program slice embedding vector and at least one register vector that are generated based on results from a static analysis tool, the at least one register vector corresponding to the at least one program slice embedding vector. The method also includes using a machine learning model to generate, from the at least one program slice embedding vector and the at least one register vector, at least one probability rating associated with a vulnerability. The method also includes reporting the at least one probability rating for use by the static analysis tool.

Abstract: A computer implemented method trains distributed sets of machine learning models by training each of the distributed machine learning models on different subsets of a set of training data, performing a first layer model synchronization operation in a first layer for each set of machine learning models, wherein each model synchronization operation in the first layer generates first updates for each of the machine learning models in each respective set, updating the machine learning models based on the first updates, performing a second layer model synchronization operation in a second layer for first supersets of the machine learning models wherein each model synchronization in the second layer generates second updates for updating each of the machine learning models in the first supersets based on the second updates such that each machine learning model in a respective first superset is the same.

Abstract: Techniques for adaptive asynchronous federated learning are described herein. An aspect includes providing a first version of a global parameter to a first client and a second client. Another aspect includes receiving, from the first client, a first gradient, wherein the first gradient was computed by the first client based on the first version of the global parameter and a respective first local dataset of the first client. Another aspect includes determining whether the first version of the global parameter matches a most recent version of the global parameter. Another aspect includes, based on determining that the first version of the global parameter does not match the most recent version of the global parameter, selecting a version of the global parameter. Another aspect includes aggregating the first gradient with the selected version of the global parameter to determine an updated version of the global parameter.

Abstract: An intelligent furnishing system. The furnishing system includes an electronic device, a server, and a workstation. The workstation includes a short-range communication circuit, a user interface including a light source, and an electronic processor. The electronic processor is configured to receive a reservation including a reservation start time, increase a communication range of the short-range communication circuit when the reservation start time is a predetermined period of time from a current time, and receive a proximity signal from the electronic device. The electronic processor is also configured to illuminate the light source in a first color, receive a check-in signal when the proximity signal is received, change the light source from the first color to a second color, receive a check-out signal when the check-in signal is received, and change the light source from the second color to a third color when the check-out signal is received.

Abstract: A golf communications system utilizes an interactive voice response system to facilitate user-selected omnichannel communications options among a community of golfers. The communications options include booking tee times, allocation of payments among a group of golfers, virtual pro shop communications, and e-commerce subscriptions. The various channels may include email, text, VoIP communications, Internet chatrooms, and/or Internet messaging services. The system fully automates reception of input from one or more golfers for purposes of booking tee times, distributing communications among a plurality of golfers, and making transactions.

Abstract: A system and a method are disclosed for replacing an accommodation of a canceled booking for a guest user. In an embodiment, an accommodation management system receives, from a homestay application, an indication that a booking for the accommodation in a region by the guest user over a time period has been canceled. The system retrieves a homestay listing associated with the booking and retrieves attributes of the homestay listing. The system maps each attribute to a set of similar attributes in an equivalence table. The system retrieves a set of available hotel listings in the region for the same time period and determines attributes of each available hotel listing. The system determines a set of comparable hotel listings that each include similar attributes to the homestay listing and sends a command to book a comparable hotel listing the guest user during the time period.

Abstract: A method, system and computer-readable medium for analyzing contact studies for a call service center is presented. The method includes the steps of: acquiring data instances of a Collector tool from all persons monitoring contacts at a call service center during a given study period; retrieving a study design from a Planner tool to verify that acquired data instances conform to the study design; selecting data parameters for the acquired data instances, wherein the data parameters describe multiple features of the acquired data; automatically selecting an appropriate chart format that is appropriate for measurement units used by the data parameters; and creating a chart using the appropriate chart format and the data parameters. The steps in the method may all be automatically performed by an Analyzer logic.

Abstract: A parking lot free parking space predicting method, apparatus, electronic device and storage medium are provided. The method comprises: building a parking lot association graph for parking lots in a region to be processed; as for any parking lot i, performing the following processing respectively: determining local space correlation information of the parking lot i at a current time according to environment context features of the parking lot i and neighboring parking lots which are in the parking lot association graph and connected to the parking lot i through edges; determining time correlation information of the parking lot i at the current time according to the local space correlation information, and predicting free parking space information of the parking lot i at at least one future time step according to the time correlation information of the parking lot i at the current time.

Abstract: An information processing apparatus includes a processor configured to: acquire a document; determine a route on which the document is to be processed in a workflow; determine a first process that is a final process for processing the document on the route among processes in which information is allowed to be input for a first item included in the document; and display the first item in a manner in accordance with the first process.

Abstract: A system and method for automatically communicating an identification signal from a vehicle controller of a vehicle that may include receiving trip data from a dispatch controller based on the identification signal that is communicated. Software of the vehicle controller may be updated at a determined time based on the trip data that is received, and movement of the vehicle may be controlled based on movement allowance signals received by the vehicle controller and used by the software of the vehicle controller during the movement of the vehicle to determine whether the vehicle is permitted to enter into segments of one or more routes.

Abstract: Embodiments provide techniques, including systems and methods, for improving the accuracy of location information for requestor and provider devices in an dynamic transportation matching system using local communications between computing devices. For example, embodiments allow a provider computing device to identify, pair, and/or communicate with a requestor computing device upon arrival near a request location for a ride matching request. The provider computing device may use signal strength measurements associated with signals received from the requestor computing device to identify a proximity to the requestor computing device and/or to triangulate an accurate location of the requestor computing device. Additionally, the provider computing device may use a combination of the location reported by the ride matching system and the signal strength of the paired connection to identify the location of the requestor computing device.

Abstract: A computer-implemented method that, in an embodiment, includes receiving a travel request from a traveler that includes a pickup and destination location and a number of travelers and analyzing the travel request and calculating routes for vehicles that are partially based on the pickup and destination location, the number of travelers, destination locations of travelers located in the vehicles, traffic conditions, minimizing a waiting time for the traveler, minimizing a travel time for the traveler, minimizing a travel time for the travelers located in the vehicles, and optimizing an aggregation of travelers on each of the plurality vehicles. In an embodiment, the plurality of vehicles includes 5 vehicles or more and based on the calculating, the method includes supplying a selected route to a selected vehicle and supplying to the traveler, identification information related to the selected vehicle thereby resulting in transportation of the traveler to the destination location.

Abstract: The inventive system and method address a long felt need for enhancing the efficiency of systems in the interactive conveyance industry for goods and services by providing for the filtering, selection and securing of conveyance services in accordance with one or more of client and representative preferences in substantially real time.

Abstract: A network based order fulfillment systems having an improved user interface at both a customer device and at an order fulfillment location employee device. Both customer and employee devices scan collect user input and other information using one or more sensors of the user devices to provide proper notifications to both the customer and the employee based on the actions of each. Location information for a customer computing device can be used to continually update ETA and time since arrival information displayed at the employee's computing device.

Abstract: A human interaction replacement evaluation system analyzes actions taken by a user with an application on a client device that provides features to replace human interaction services with computer-based services. The results of the action provide an indication of the success of a particular action supported by the application (e.g., whether the action has a positive or negative effect on a key performance indicator) or an indication of how likely the user is to be ready to adopt a particular computer-based service. Recommendations are then provided to the user of the application or a manager of the application indicating actions to use, actions that have negative or positive effects on a key performance indicator, and so forth.

Abstract: A system can access data about items for a store and generate a plan for configuring the store based on the accessed data. The system can further provide, for example, information for configuring reconfigurable shelving units so as to produce the layout of the store according to the plan.

Abstract: A method, computer system, and a computer program product for blockchain enabled crowdsourcing is provided. The present invention may include receiving an asset from a content provider. The present invention may also include deploying a smart contract based on the received asset, wherein the deployed smart contract includes a plurality of compensation rules. The present invention then may include partitioning the received asset into a plurality of fragments based on the deployed smart contract. The present invention may further include releasing the partitioned plurality of fragments into a blockchain network. The present invention may also include tracking each fragment within the released plurality of fragments using the smart contract.

Abstract: Computing device and method using machine learning to optimize operations of a processing chain of a food factory. The computing device collects data representative of characteristics of a product processed by the processing chain. At least some of the collected data are received from one or more sensor monitoring operations of the processing chain. The computing device determines at least one product characteristic value based on the collected data. The computing device executes the machine learning inference engine, which uses a predictive model for inferring command(s) for controlling processing appliance(s) of the processing chain based on inputs. The inputs comprise the at least one product characteristic value. The computing device transmits the command(s) to the processing appliance(s) of the processing chain. Examples of product characteristic values comprise: a product temperature, a product humidity level, a product geometric characteristic, a product weight, and a product defect measurement.

Abstract: Systems and methods are provided for evaluating workplace risk by associating sensors with individual members of a workforce to measure conditions affecting the individual. Data is obtained from the sensors for reoccurring work periods for each individual so that a risk analysis may be performed to derive a risk score. Probability of injury is calculated aggregating risk scores for multiple reoccurring work periods. The calculated probability of injury is used to quantify workplace risk for the at least one individual and an enterprise risk assessment is provided by combining the quantified risks for each individual.

Abstract: The present invention provides methods and systems for determining the play value of a playground, the challenge level of a playground, or both. In some embodiments, the methods and systems may propose modifications to a playground that would result in an effective and efficient increase in the play value of the playground, a desired increase or decrease in the challenge level of the playground, or both. Further, in some embodiments, the methods and systems may be configured to provide comparisons of various playgrounds in order to determine which playgrounds are of greatest play value. In some embodiments, the methods and systems may be incorporated into software that is configured for the design of playgrounds.

Abstract: Systems and methods of utilizing employee recognition programs to maximize employee return on investment. To maximize the employee return on investment effect of the available recognition products at a desired cost to the employer, systems and methods rank recognition categories and/or products, prescribing the top category and/or product or the top categories and/or products that will be beneficial in optimizing employee return on investment of an organization. The systems and methods for prescribing the category and/or product or categories and/or products can provide an estimate of how employee return on investment will be impacted by the prescribed recognition.

Abstract: A digital service evaluation system evaluates services and user sessions provided by a service, to provide an overall score of the service. The digital service evaluation system detects client sessions associated with one or more devices. The digital service evaluation system obtains a first plurality of scores associated with performance metrics of the client session, and calculates an overall score for the client session. The digital service evaluation system obtains a second plurality of scores and calculates a second overall score. The digital service evaluation system determines a weight for each performance metric based on the first and second plurality of scores and the overall scores. The digital service evaluation system uses the weights to determine which performance metric caused a change in the overall scores. The digital service evaluation system takes an action based on the determination that a performance metric caused a change in the overall scores.

Abstract: Systems and methods for tracking and ranking errors in computer systems may be used in e-commerce applications in order to identify errors that occur in e-commerce user sessions along with an estimate of potential lost revenues resulting from the error. The errors and associated lost revenues may allow prioritizing of which errors to address.

Abstract: A method and system for determining sentiment of an employee towards an organization comprises extracting structured and unstructured data from one or more structured data sources comprising structured datapoints and one or more unstructured data sources comprising unstructured datapoints. The method comprises building regression model on the plurality of structured datapoints to determine a relationship of structured datapoints amongst the structured datapoints, creating a first profile of the employee based on said relationship, creating a second profile of the employee by selecting one or more words from each unstructured datapoints by using a prestored vocabulary, assigning one or more scores, corresponding to said words, in context of corresponding each of the unstructured datapoints. Method comprises generating a matrix based on the first profile and the second profile indicating sentiments of employee towards organization.

Abstract: A method for retrieving content stored in a warehouse, the method may include: maintaining first content in boxes of a lowest shelf of a storage unit of the warehouse, while maintaining in boxes of higher shelves of the storage unit second content that is of less interest than the first content; accessing the boxes of the lowest shelf and providing the boxes to interfacing units, by a first robot; accessing the boxes of the higher shelves and providing the boxes to the interfacing units, by a second robot; wherein the first robot, when positioned at a lower position, is lower than a height of the lowest shelf; and wherein the second robot is higher than the height of the lowest shelf.

Abstract: Various embodiments of a system and method for generating a delivery plan for multi-tier delivery schemes are described. Embodiments may include generating a delivery plan for a region including multiple delivery locations. The delivery plan may specify at least one agent delivery route within the region. The delivery route may include at least one shipment acquisition location coinciding with an expected travel route of a vehicle conveying shipments. The agent delivery route may be traversed by an agent that is to deliver a specific group of shipments acquired from the vehicle at the shipment acquisition location. Embodiments may include selecting the specific group of shipments for delivery on the delivery route. The selecting is based on a time constraint for delivering the group of shipments to respective delivery locations along the delivery route, and historical delivery time information for previous deliveries to the delivery locations along the delivery route.

Abstract: Systems and methods which provide known shipper information in association with unknown shipper indicia as disclosed. Embodiments operate to collect information regarding a shipper and associate the shipper information with unknown shipper indicia. Where shipper information satisfactory to a known shipper requirement has not otherwise been collected, embodiments operate to perform a transaction matrix analysis to determine a shipper identification risk level. Such transaction matrix analysis may operate to analyze multiple pieces of shipper information (e.g., collected from different sources) to provide a determination as to a level of risk that the shipper information correctly and/or uniquely identifies the shipper.

Abstract: A parcel processing system configured to support automated parcel processing. For example, the system can be configured to select a permitted shipping service level from among the plurality of permitted shipping service levels based on a plurality of rules, control the sorting of the parcel into one of a plurality of shipping containers, and bill customers.

Abstract: Systems and methods which provide shipping management system shipping documentation generation operation which spawns intelligent generation subprocesses are described. The intelligent generation subprocesses of embodiments facilitate autonomous shipping documentation generation functionality of a concatenated shipping documentation generation process. A user may initiate a shipping documentation generation process, whereby an intelligent generation subprocess is spawned, and thereafter the user may be freed to perform one or more independent operation and/or interaction with the shipping management system. One or more verifications, checks, warnings, and/or the like are suspended and one or more parameter, input, selection, and/or the like are defaulted for operation of an intelligent generation subprocess of embodiments. Embodiments implement a documentation queue to provide historical information with respect to intelligent generation subprocess operation.

Abstract: A system and method for en-route business selection, routing, and order preparation timing. The system is a cloud-based network containing an optimization server, portals for restaurants, customers, and drivers to enter their information, and an optimization engine which determines optimal pickup and delivery times for delivery drivers based on a multitude of variables associated with the business enterprises and delivery driver availability. The system may be accessed through web browsers or purpose-built computer and mobile phone applications.

Abstract: A method, computing system, and computer program product are provided. Items at a source location are detected and classified, with respect to fragility and perishability, based on characteristics of the each respective item and is performed by trained machine learning models. Item boundaries are predicted based on applying respective data regarding points on a surface of the each respective item to a trained second machine learning model to predict the item boundaries. The each respective item is classified into a respective group with respect to an available volume of the cargo space based on sensor data of the cargo space, the classified fragility and perishability, the predicted item boundaries, and a third machine learning model. An arrangement of the items in the cargo space is determined based on the group classifications and a corresponding destination location associated with the each respective item and is visualized relative to the cargo space.

Abstract: The present disclosure is directed to systems and methods for updating asset ownership for telematics-enabled machinery. In some embodiments, the updating asset ownership system comprises asset entities that transmit telemetry data. A communication interface of the updating asset ownership system can receive the telemetry data. An asset ownership data store of the updating asset ownership system can be configured to store asset owner data that identify designated owners associated with the asset entities. An asset ownership comparator of the updating asset ownership system can process the received telemetry data. Based on the processing, the asset ownership comparator can update designated owners of asset entities stored in the asset ownership data store.

Abstract: At the time of manufacture of medical items that are to be consumed during patient care, a unique identification number is assigned to each item and the number is encoded in an RFID tag attached to the item. The manufacturer registers the unique identification number for each individual medical item in a Unique Device Identification (UDI) Serialized Tracking Database. The UDI Serialized Tracking Database maps each unique identification number to each item's UDI number that has been assigned by the Food and Drug Administration. As each item is consumed during medical treatment and its cost is billed to payers, the unique identification number of the item is reported and verified. This provides for detection of certain types of fraud in the dispensing of medical items by validating that necessary supplies were actually used during patient care.

Abstract: Techniques for intelligently predicting bundles of replacement parts. A plurality of maintenance events for a plurality of replacement parts are determined based on historical data related to the plurality of replacement parts. Each maintenance event of the plurality of maintenance events corresponds with one or more of the replacement parts. A plurality of clusters of replacement parts are generated based on the plurality of maintenance events. A plurality of bundles of replacement parts are predicted based on the clusters. Each bundle includes a plurality of replacement parts.

Abstract: An information exchange platform referred to as a Trading Grid (TG) may perform relationship-based data processing utilizing a trading partner (TP) graph that describes relationships amongst operating units (OUs) on the TG. When the TG receives a request from an OU to exchange data with a TP, the TG accesses the TP graph and determines a relationship between the OU and their TP as reflected in the TP graph. The TP graph is maintained and controlled by the system independently of the OU and the TP. The TG may route the data based on instructions associated with the relationship that is reflected in the TP graph. The instructions associated with the relationship may specify network based services provided by the TG. An orchestration component may operate to orchestrate the performance of the network based services. The TG then communicates the processed and/or produced data to the TP.

Abstract: A method to automatically classify emails may include generating multiple entity data objects using entities identified in receiver and sender fields of emails and categorizing the multiple entity data objects into a first set of data objects and a second set of data objects. The method may also include extracting all tokens from each email and searching the extracted tokens for tokens associated with the data objects of the first set of data objects. The method may further include identifying the emails that include the extracted tokens that are associated with the data objects of the first set of data objects, identifying a particular data object of the first set of data objects to which an identified email corresponds, and automatically classifying the identified email in the first category in response to identifying the particular data object of the first set of data objects to which an identified email corresponds.

Abstract: The disclosure provides a method, system, and a software program product for assisting a user and/or managing tasks of the user, by a mobile secretary cloud application configured to operate in a mobile client device and cloud server network. The mobile secretary cloud application reads data from another software application and operates at least one of another application and a third application based on the read data. Further, Artificial intelligence is utilized by the mobile secretary cloud application for operating another application and the third application.

Abstract: A system is disclosed for managing services at a customer location. The system may have at least one offboard utility meter, a communication device, and a controller in communication with the at least one offboard utility meter via the communication device. The controller may be configured to receive information from the at least one offboard utility meter during a waste service activity at the customer location by a waste service vehicle and to determine based on the information from the at least one offboard utility meter a fee associated with at least one utility service provided at the customer location. The controller may also be configured to generate at least one invoice for the waste service activity and for the fee associated with the at least one utility service.

Abstract: This application relates to a data processing method and apparatus, a computer device, and a storage medium. The method includes: detecting, for each block in a first block file, a to-be-maintained transaction record in the block; selecting, from a hash tree of the block, nodes used for proving that the transaction record belongs to the block; constructing a node maintenance tree according to the selected nodes; storing the transaction record at a corresponding leaf node of the node maintenance tree; updating an association between a block head of the block and the node maintenance tree storing the transaction record to a second block file, the block head of the block being adjacent to a block head of a previous block in the second block file; and deleting the first block file after the update processing for the each block is completed. The solutions of this application can save storage resources.

Abstract: There may be provided a secure ledger network for executing cryptocurrency transactions, the secure ledger network includes at least one hardware processor, a non-transitory machine-readable storage medium having an executable computer readable program code, the at least one hardware processor configured to execute the computer-readable program code to: receive, by the secure ledger network, a request to validate a smart contract that determines at least one rule for performing a transaction related to a first cryptocurrency token, wherein an execution of the transaction comprising determining a price of the first cryptocurrency token based on a status of the first cryptocurrency token, and a status of an other cryptocurrency token; determine whether to validate the smart contract; when determining to validate the smart contract then updating a secure ledger maintained by the secure ledger network with the smart contract; receiving, by the secure ledger network, a request to execute a transaction related to t