Abstract: In an approach to jointly learning uncertainty-aware trend-informed neural network for a demand forecasting model, a machine learning model is trained to capture uncertainty in input forecasts. The uncertainty in a latent space is represented using an auto-encoder based neural architecture. The uncertainty-aware latent space is modeled and optimized to generate an embedding space. A time-series regressor model is learned from the embedding space. A machine learning model is trained for trend-aware demand forecasting based on said time-series regressor model.

Abstract: Embodiments are directed to a method and system of forecasting a disk drive survival period in a data storage network, by obtaining operating system data and manufacturer data for the disk drive to create a dataset, screening the dataset to identify a number of features to be selected for model creation, wherein the data set includes censored data and non-censored data, and performing, in an analytics engine, semi-parametric survival analysis on the data set using transfer learning on the model to provide a time-based failure prediction of the disk drive. A graphical user interface provides to a user the failure prediction in one of text form or graphical form.

Abstract: In an approach for forecasting environmental occlusion events, a processor receives a spatio-temporal zone of interest. A processor collects data associated with the spatio-temporal zone of interest. A processor builds a machine-learning model using the data. A processor generates an occlusion probability map for the spatio-temporal zone of interest based on the machine-learning model and enriched mathematical operators. A processor outputs the occlusion probability map.

Abstract: Methods, systems, and computer program products for auto-discovery of reasoning knowledge graphs in supply chains are provided herein. A computer-implemented method includes obtaining a spatiotemporal query related to a demand of at least one product in a supply chain; analyzing the spatiotemporal query to identify one or more parameters affecting the demand of the at least one product, wherein the one or more parameters comprise at least one of one or more climate parameters and one or more disruptive event parameters; generating a knowledge graph comprising information indicating an impact on the demand of the at least one product for at least a portion of the one or more parameters; and outputting, to a user interface, an explanation of a predicted demand forecast for the at least one product based at least in part on the knowledge graph.

Abstract: Methods, apparatus, and processor-readable storage media for estimating replication completion time using machine learning techniques are provided herein. An example computer-implemented method includes obtaining, from one or more data deduplication storage systems, data related to one or more historical replication operations; generating at least one curve fitting function by processing at least a portion of the obtained data using one or more machine learning techniques; generating an estimate for completion time of at least one unexecuted replication operation associated with at least one of the one or more data deduplication storage systems by processing input data from the at least one data deduplication storage system using the at least one curve fitting function; and performing one or more automated actions based at least in part on the generated estimate.

Abstract: The invention relates to methods, systems and computer program products for securing one time passwords (OTP) for use in OTP based authorization of electronic payment transactions. The invention involves transmission and display of an OTP at a user device in response to a prior determination that a user operating the user device is authorized to implement a payment transaction through a payment account associated with the payment transaction. The invention implements this through transmission to the user device associated with the identified payment account, a data message initiating a process for verification of identity of a user operating the user device. Responsive to determining that the user operating the user device is authorized to operate the payment account, displaying the OTP on the user device for implementation of the payment transaction.

Abstract: Method, apparatus, and computer program product are provided for estimating crop type and/or sowing date. In some embodiments, a historical crop growth time series and a plurality of simulated crop growth time series are determined, and the historical time series is matched against each simulated time series to determine an estimated crop type and/or sowing date. For example, one simulated time series may be determined for each crop type/sowing date combination within a set of one or more crop types and one or more sowing dates based on historical crop data. Each time series represents crop growth in an area of interest and comprises element(s) including crop-specific parameter(s), such as leaf area index (LAI). The historical time series may be determined based on remote sensor data. Each simulated time series may be determined using a crop growth simulation model and based on historical crop data, geospatial data, and weather data.

Abstract: A method for providing feedback between separate neural networks to predict crop yield of a polyculture by combining the crop yield predictions from the neural networks is described. The method includes configuring a set of neural networks, each neural network in the set of neural networks predicting crop yield for a respective crop from a set of crops based on a set of crop growth time series, one crop growth time series for each respective crop, the set of crops being grown in a polyculture. A crop simulator generates the set of crop growth time series based on application rates of farm inputs that are provided to the crop simulator. The method further includes determining a predicted crop yield of the polyculture at a timepoint after a predetermined duration by iteratively changing and applying application rates of farm inputs based on the crop growth time series.

Abstract: A smart lock system that includes a smart lock that electronically locks and unlocks a door and a server that outputs a command to the smart lock to lock or unlock the door via the internet in response to an instruction received via the internet from a user device. The user device may also (simultaneously) directly transmit an instruction to the smart lock (e.g., Bluetooth). The user device may also directly transmit an instruction to the smart lock to unlock the door in response to a determination that the user device is within a predefined geofenced region around the smart lock. The smart lock may also include a keypad. The smart lock may also include a camera that captures images and output those images to the server for transmittal to the user device. The smart may also include a motion sensor and capture images in response to detected motion.

Abstract: One embodiment provides a computer implemented method of estimating replication completion time. The method includes creating a historical dataset of prior replication data; determining a set of replication parameters to consider; inputting the historical dataset and the set of replication parameters to a replication completion time estimator module; generating a replication completion time prediction based on the historical dataset and the set of replication parameters; and generating a confidence prediction corresponding to the replication completion time prediction.

Abstract: In an approach for forecasting environmental occlusion events, a processor receives a spatio-temporal zone of interest. A processor collects data associated with the spatio-temporal zone of interest. A processor builds a machine-learning model using the data. A processor generates an occlusion probability map for the spatio-temporal zone of interest based on the machine-learning model and enriched mathematical operators. A processor outputs the occlusion probability map.

Abstract: A smart lock system that includes a smart lock that electronically locks and unlocks a door and a server that outputs a command to the smart lock to lock or unlock the door via the internet in response to an instruction received via the internet from a user device. The user device may also (simultaneously) directly transmit an instruction to the smart lock (e.g., via Bluetooth). The user device may also directly transmit an instruction to the smart lock to unlock the door in response to a determination that the user device is within a predefined geofenced region around the smart lock. The smart lock may also include a keypad. The smart lock may also include a camera that captures images and output those images to the server for transmittal to the user device. The smart may also include a motion sensor and capture images in response to detected motion.

Abstract: The exemplary embodiments disclose a system and method, a computer program product, and a computer system for generating an agriculture map of a region of land. The exemplary embodiments may include collecting agricultural data of one or more sub-regions of the region of land, wherein the agricultural data includes classified data and unclassified data, extracting one or more features from the collected classified agricultural data, training one or more models based on the extracted one or more features, and generating an agricultural map of the region of land based on applying the one or more models to the collected unclassified agricultural data.

Abstract: Embodiments are directed to a method and system of forecasting a disk drive survival period in a data storage network, by obtaining operating system data and manufacturer data for the disk drive to create a dataset, screening the dataset to identify a number of features to be selected for model creation, wherein the data set includes censored data and non-censored data, and performing, in an analytics engine, semi-parametric survival analysis on the data set using transfer learning on the model to provide a time-based failure prediction of the disk drive. A graphical user interface provides to a user the failure prediction in one of text form or graphical form.

Abstract: A method for facilitating payment transactions includes receiving a transaction request for a payment transaction initiated at a payment terminal device using a transaction card of a user. A predefined category of the user is identified based on the transaction request and a service application is remotely activated in a first operation mode on a user device of the user such that the first operation mode is associated with the identified predefined category. Payment transaction messages associated with the payment transaction are communicated to the activated service application, which translates the payment transaction messages to a predefined message format. In response to the payment transaction messages, first authentication information is received from the activated service application such that the first authentication information is entered by the user in the predefined message format. The payment transaction is processed based on successful authentication of the user.

Abstract: Embodiments described herein relate to a method for probabilistically forecasting the state of hardware components. The method may include obtaining data items corresponding to a hardware component and performing an analysis of the hardware component. The analysis may include making a variety of probability predictions as to whether a label from among a set of possible labels is likely to be the correct label. The set of probabilities from the aforementioned analysis are then analyzed to determine which predicted label has the tightest range, and the prediction with the tightest range for a certain label is displayed to a user in a ranked fashion that includes a quantity of such probability prediction ranges. Such a display may allow an administrator to take action as to which hardware components should be replaced and in what order.

Abstract: According to one embodiment, a method, computer system, and computer program product for detecting and managing anomalies in one or more sensors is provided. The present invention may include simulating, by one or more environmental models, an expected output of the one or more sensors; responsive to identifying that an actual output of the one or more sensors differs from the expected output by a threshold value, detecting one or more anomalous sensors; and performing one or more actions to manage the one or more anomalous sensors based on the presence of the one or more sensors within a plurality of anomaly reaction zones.

Abstract: Method, apparatus, and computer program product are provided for estimating crop pest risk and/or crop disease risk at sub-farm level. In some embodiments, a farm region is determined based on farm definition data, and input data associated with the farm region are retrieved from a plurality of data sources. The input data may include a plurality of pixel sets. In some embodiments, for each pixel set, crop risk data are determined based on the input data using one or more spatiotemporal regression models. The crop risk data may include an estimate of crop pest risk and/or crop disease risk for each pixel set. In some embodiments, the farm region is categorized into a plurality of sub-farms each defining a risk level category for that sub-farm based on the crop risk data. In some embodiments, the sub-farms are displayed as a visual heat-map, along with recommended antidote options.

Abstract: Methods, apparatus, and processor-readable storage media for estimating replication completion time using machine learning techniques are provided herein. An example computer-implemented method includes obtaining, from one or more data deduplication storage systems, data related to one or more historical replication operations; generating at least one curve fitting function by processing at least a portion of the obtained data using one or more machine learning techniques; generating an estimate for completion time of at least one unexecuted replication operation associated with at least one of the one or more data deduplication storage systems by processing input data from the at least one data deduplication storage system using the at least one curve fitting function; and performing one or more automated actions based at least in part on the generated estimate.