Abstract: An example embodiment involves rules related to repairing software programs, wherein the rules associate indications of software program failures with repair applications that are configured to correct the software program failures. One or more processors are configured to: (i) receive, by a predictive model, a representation of an execution history of a particular software program, wherein the predictive model has been trained on a corpus of execution histories of the software programs; (ii) generate, by the predictive model and from the execution history, a failure prediction for the particular software program; (iii) receive, by an automated repair controller application, the failure prediction from the predictive model; (iv) based on applying the rules to the failure prediction, determine, by the automated repair controller application, a repair application from the repair applications; and (v) cause, by the automated repair controller application, the repair application to be executed within the network.

Abstract: A method performs time-synchronization between a master clock and a plurality of slave clocks. The method performs a forward time-synchronization from the master clock to the plurality of slave clocks. Further, the method performs a reverse time-synchronization from the plurality of slave clocks to a corresponding plurality of validator clocks. In addition, the method validates the time-synchronization between the plurality of slave clocks, notably between the master clock and the plurality of slave clocks, based on the plurality of validator clocks.

Abstract: An embodiment may involve a server-side log collected by a server device, where the server-side log includes a set of entries indicating a unique identifier, and wherein the unique identifier is assigned to a work item of a server-based application executed by the server device. The embodiment may further involve one or more processors configured to: receive, from a client device disposed upon a network, a client-side log, wherein the client-side log includes operational data related to usage of a client-based application executed by the client device; identify, from the operational data, the client-based application and one or more activities performed by the client-based application; determine that the one or more activities are related to the unique identifier; based on the one or more activities, determine an action that can be taken to improve efficacy of the server-based application; and write, to the persistent storage, a representation of the action.

Abstract: Described herein are exemplary systems and methods for the optimization of shipping cartons relative to the contents of orders to be placed therein. An exemplary carton optimization method evaluates a sample size of orders received at a given location and then determines an optimal carton set that includes at least one feasible carton for each order, while also minimizing shipping costs based on dimensional weighing-based pricing by reducing the dimensional weight, thereby minimizing void space and increasing the carton space utilization percentage. An exemplary carton optimization method may be further customized to optimize a carton set for an order, based on the cartons already available at a given warehouse or other site. As a result, cartons are utilized and designed more efficiently at the site.

Abstract: A method for predicting sales order comprises the following steps: Step 1: obtaining information of multiple inquiry cases, and building inquiry original dataset based on the information of inquiry cases; step 2: randomly and with replacement, drawing m training samples from the inquiry original dataset as a training set; step 3: randomly selecting N features from the original dataset, training the selected features through the training set, and building a decision tree; step 4: repeating the steps 2 and 3 to build a total of Y decision trees to form a random forest model; step 5: importing the data to be predicted into the random forest model, and each decision tree votes on the imported data, and the probability of winning the sales order is determined based on the voting results. The invention can predict the probability of winning sales orders during the customer inquiry stage.

Abstract: An example embodiment involves rules related to repairing software programs, wherein the rules associate indications of software program failures with repair applications that are configured to correct the software program failures. One or more processors are configured to: (i) receive, by a predictive model, a representation of an execution history of a particular software program, wherein the predictive model has been trained on a corpus of execution histories of the software programs; (ii) generate, by the predictive model and from the execution history, a failure prediction for the particular software program; (iii) receive, by an automated repair controller application, the failure prediction from the predictive model; (iv) based on applying the rules to the failure prediction, determine, by the automated repair controller application, a repair application from the repair applications; and (v) cause, by the automated repair controller application, the repair application to be executed within the network.

Abstract: At least service task data and application utilization data are collected. The collected data is analyzed to determine a utilization pattern. Based on the determined utilization pattern, a computer automation opportunity is automatically identified. An automatically generated recommendation of an automation solution among a plurality of automation solution candidates is provided for the identified computer automation opportunity.

Abstract: A method and system for product processing price prediction based on multiple regression model includes: gathering multiple product data, building product original dataset, the data includes product quantity, surface area, processing complexity, product X axis length, product Y axis length, product Z axis length, tool utilization rate, product tolerance level, product machinability, material unit price, material density and price; building a multiple linear regression model based on the product original dataset; the product original dataset is divided into a training subset and a testing subset, the multiple linear regression model is trained through the training subset, the accuracy of the multiple linear regression model is verified by the testing subset, and the multiple linear regression model is adjusted according to the testing result to determine the final multiple linear regression model.

Abstract: An embodiment may involve a server-side log collected by a server device, where the server-side log includes a set of entries indicating a unique identifier, and wherein the unique identifier is assigned to a work item of a server-based application executed by the server device. The embodiment may further involve one or more processors configured to: receive, from a client device disposed upon a network, a client-side log, wherein the client-side log includes operational data related to usage of a client-based application executed by the client device; identify, from the operational data, the client-based application and one or more activities performed by the client-based application; determine that the one or more activities are related to the unique identifier; based on the one or more activities, determine an action that can be taken to improve efficacy of the server-based application; and write, to the persistent storage, a representation of the action.

Abstract: A system and method for developing optimized cargo transportation solutions. The system may include a number of different modules (programs) that may be executed individually, or in series when an exemplary system includes the programs operating sequentially. Input to the programs may be obtained from the shipment files of an entity for whom a transportation solution is being created. The output of one program may act as at least a partial input to the next program when the programs are executed sequentially. One or more of the programs may employ optimization procedures such as ant colony optimization procedures and/or local improvement heuristics. The systems and methods are provided to determine a most cost effective shipping solution for given cargo.

Abstract: An embodiment includes storage containing configuration and operational data related to a managed network, an action configurator application, and an action execution application. The embodiment also includes one or more processors configured to: receive, by way of the action configurator application, a specification of an action type; receive, by way of the action configurator application, a specification of an input source for actions generated using the action type; receive, by way of the action configurator application, a specification of one or more target users and an output modality for the actions; receive, by way of the action configurator application, a specification of a condition that causes the actions to be generated; determine, that the condition has been satisfied; and cause the action execution application to execute the action generator on the input source, and produce an output for one of the target users by way of the output modality.

Abstract: A system and method is disclosed for performance analysis of processes in a managed network. Processes may be represented as sets of activities, and an audit database may be configured for logging activities within the managed network. Database may include fields to identify process instances, process classes, process states, and process transitions. A server device may receive a request from a client device to view information representative of multiple process instances. The server device may select a plurality of process instances according to filter criteria applied to the data fields of the audit database records, and generate a graphical representation of interconnections between the one or more data fields of the selected plurality based on a statistical analysis of the one or more data fields of the audit database records corresponding to the selected plurality of process instances. The server may then transmit the graphical representation to the client device.

Abstract: A system may include persistent storage containing representations of requests associated with a managed network. The persistent storage may include lists of capabilities associated with agents, and each request may include a textual description of a situation experienced by a user and a resolution of the situation by a particular agent. A computing device may obtain a set of requests from the persistent storage, apply an unsupervised machine learning clustering technique to textual descriptions included in the set of requests, and arrange the requests into groups such that each group contains requests including textual descriptions with at least a threshold degree of similarity to one another. The computing device may perform, for the requests in a particular group, a textual analysis on associated resolutions to identify capabilities used by agents to resolve the requests, and update the lists of capabilities to associate the capabilities with agents that used them.

Abstract: A remote network management platform may include persistent storage containing: (i) data related to a managed network, and (ii) a persona of a user. The remote network management platform may also include a platform application associated with a web-based user interface and using a portion of the data. The remote network management platform may also include a recommendation engine with access to a set of rules or a machine learning (ML) model corresponding to the platform application. The recommendation engine may be configured to: (i) read, from the persistent storage, the portion of the data and the persona; (ii) apply, to the portion of the data and the persona, the set of rules or the ML model to generate one or more recommendations; and (iii) transmit, by way of the web-based user interface and to the user, representations of the one or more recommendations.

Abstract: Exemplary system and method embodiments described and shown herein are directed to optimizing warehouse picking operations. Exemplary system and method embodiments employ order allocation optimization and/or order grouping optimization that are individually or collectively usable to allocate and group warehouse orders in a manner that minimizes picker travel and maximizes labor productivity.

Abstract: A method for transaction authorization includes generation of a master authentication code based on an authorization request for a transaction by a server. The transaction is initiated by a user by way of a transaction application installed on a user-computing device. The server splits the master authentication code into a first authentication code and a second authentication code. The first authentication code is communicated to the transaction application and the second authentication code is communicated to the user by the server. The transaction application generates a response code based on the first authentication code and the second authentication code. The server receives the response code from the transaction application and processes the transaction based on a match between the response code and the master authentication code.

Abstract: A remote network management platform may include persistent storage containing: (i) data related to a managed network, and (ii) a persona of a user. The remote network management platform may also include a platform application associated with a web-based user interface and using a portion of the data. The remote network management platform may also include a recommendation engine with access to a set of rules or a machine learning (ML) model corresponding to the platform application. The recommendation engine may be configured to: (i) read, from the persistent storage, the portion of the data and the persona; (ii) apply, to the portion of the data and the persona, the set of rules or the ML model to generate one or more recommendations; and (iii) transmit, by way of the web-based user interface and to the user, representations of the one or more recommendations.

Abstract: Indicator values are anonymously aggregated in a multi-instance computing environment. Aggregations of indicator values are received from customer instances in a multi-instance computing environment. At least one of the aggregations of indicator values is generated by a respective customer instance of the customer instances based on indicator values generated by the respective customer instance. The aggregations of indicator values are filtered to produce filtered aggregations, and the filtered aggregations are aggregated according to characteristics associated with at least some of the customer instances to generate global indicator values. Each global indicator value is generated from one or more of the filtered aggregations that are greater than a minimum threshold. One or more of the global indicator values may then be transmitted to a customer instance of the customer instances having a characteristic corresponding to those global indicator values.

Abstract: Exemplary system and method embodiments described and shown herein are directed to optimizing warehouse picking operations. Exemplary system and method embodiments employ order allocation optimization and/or order grouping optimization that are individually or collectively usable to allocate and group warehouse orders in a manner that minimizes picker travel and maximizes labor productivity.

Abstract: A system and method is disclosed for performance analysis of processes in a managed network. Processes may be represented as sets of activities, and an audit database may be configured for logging activities within the managed network. Database may include fields to identify process instances, process classes, process states, and process transitions. A server device may receive a request from a client device to view information representative of multiple process instances. The server device may select a plurality of process instances according to filter criteria applied to the data fields of the audit database records, and generate a graphical representation of interconnections between the one or more data fields of the selected plurality based on a statistical analysis of the one or more data fields of the audit database records corresponding to the selected plurality of process instances. The server may then transmit the graphical representation to the client device.