International Business Machines Corporation

Samsung Electronics Co., Ltd.

Amar Prakash Azad

Karthik Sankaranarayanan

Abhijit Mishra

Parag Jain

Harshit Kumar

Larisa Shwartz

Shivkumar Kalyanaraman

Ajay Gupta

Jagabondhu Hazra

Manikandan Padmanaban

Raghav Batta

Arzad Alam Kherani

Karthik Rangaraj Manavalan

Prateeti Mohapatra

Kalyan Dasgupta

Youngsoo Kim

Jinho Hwang

Amith Singhee

Mathieu Sinn

Michael Elton Nidd

Vijay Arya

Kiran Bynam

Alberto Giammaria

Sujit Jos

Amitkumar Manoharrao Paradkar

Amit Dhurandhar

Umamaheswari C Devi

Gargi Banerjee Dasgupta

Manoj Choudhary

Pooja Aggarwal

Pritam S Gundecha

Saneem Ahmed Chemmengath

Jakub Krchák

Ronny Luss

Vincent Lonij

Suranjana Samanta

Rashmi Mittal

Eyal Shnarch

Kannan Govindan

Nikhil Verma

Sandhya Patil

Taeseok Kim

A method, computer program product and system are provided to generate perturbed text is provided. A processor receives a string of text from a user. A processor determines one or more classifications for at least one word in the string of text by a classification model. A processor determines a plurality of perturbations of the at least one word based on the one or more classifications, where the plurality of perturbations do not share the same one or more classifications as the at least one word in the string of text. A processor selects a perturbation of the string of text based on (i) an edit distance between the string of text and the plurality of perturbations, and (ii) a fluency metric for each of the plurality of perturbations. A processor provides the perturbation of the string of text to the user.

System and method for generating contrastive explanations for text guided by attributes

Methods, systems, and computer program products for mining multi-party collaboration platforms to create triaging trees and playbooks are provided herein. A computer-implemented method includes obtaining, from a multi-user platform, conversations related to at least one technical issue; generating a plurality of triaging trees by analyzing the conversations, wherein each of the triaging trees stores information corresponding to temporal sequences of steps related to diagnosing and resolving said at least one technical issue; and deriving a playbook for resolving said at least one technical issue at least in part by combining two or more of the plurality of triaging trees.

Mining multi-party collaboration platforms to create triaging trees and playbooks

Methods, systems and computer program products for multi-style text transformation are provided herein. A computer-implemented method includes selecting at least one set of style specifications for transforming at least a portion of input text. The at least one set of style specifications include one or more target writing style domains selected from a plurality of writing style domains, weights for each of the target writing style domains representing relative impact of the target writing style domains for transformation of at least a portion of the input text, and weights for each of a set of linguistic aspects for transformation of at least a portion of the input text. The computer-implemented method also includes generating one or more style-transformed output texts based at least in part on the at least one set of style specifications utilizing at least one unsupervised neural network.

Controllable style-based text transformation

In an approach to risk prediction for bug-introducing changes, a computer retrieves one or more historic pull requests. A computer determines a unique file linking for each file included in the historic pull requests. A computer generates a file risk dataset. A computer performs chronological partitioning on the file risk dataset. A computer determines bug-introducing changes in the file risk dataset. A computer computes a collaborative file association between two or more of the files in the file risk dataset. A computer labels each of the files in the file risk dataset with an associated risk of introducing a bug. A computer generates a labelled file risk inducing ground truth dataset. A computer inputs the labelled file risk inducing ground truth dataset to a file risk prediction model. A computer extracts pull request features from the historic pull requests. A computer generates a pull request risk prediction model.

Pull request risk prediction for bug-introducing changes

Methods, systems, and computer program products for unsupervised tunable stylized text transformations are provided herein. A computer-implemented method includes identifying amendable portions of input text by processing at least a portion of the input text using at least one neural network; determining stylistic text modifications to the amendable portions of the input text, the text modifications encompassing a set of stylistic parameters, wherein said determining comprises processing at least a portion of the set of stylistic parameters using at least one neural network; generating a stylized output set of text by transforming at least a portion of the input text, wherein said transforming comprises modifying at least one of the amendable portions of the input text via at least one of the stylistic text modifications encompassed by the set of stylistic parameters; and outputting the stylized output set of text to at least one user.

Unsupervised tunable stylized text transformations

Methods, computer program products, and/or systems are provided that perform the following operations: in an information technology (IT) management system, grouping one or more ongoing service failure events into a service failure record; identifying a representative event for the service failure record; identifying one or more conversations that relate to the one or more ongoing service events; computing, using a similarity algorithm, feature similarity scores for respective conversations of the one or more conversations based, at least in part, on the features associated with the representative event and features associated with the respective conversations; linking a subset of the one or more conversations to the one or more ongoing service events in the service failure record based, at least in part, on the computed feature similarity scores; and providing the service failure record to a collaboration platform utilized in addressing the one or more ongoing service events.

Discovering insights and/or resolutions from collaborative conversations

The present invention provides a method, system, and computer program product of modeling and calculating aggregate power of a set of renewable energy source stations using power output from representative renewable energy source stations. In an embodiment, the present invention includes receiving location, power output time series, and weather time series data of renewable energy source stations in a geographic region and aggregate power output time series data for the geographic region, for each cluster of stations, normalizing the aggregate power value to a representative renewable energy source station, learning a regression model, and de-normalizing a normalized aggregate output power model with respect to a maximum possible power value, and applying a combined model to the received data and power output of representative renewable energy source stations for a particular day, resulting in a total aggregate power value of the renewable energy source stations for the particular day.

Modeling and calculating normalized aggregate power of renewable energy source stations

Methods, systems, and computer program products are provided herein in connection with IoT-enabled solar PV health monitoring and advising related thereto. A computer-implemented method includes obtaining current-voltage samples corresponding to solar photovoltaic modules by triggering switch circuitry between (i) an inverter attributed to the solar photovoltaic modules and (ii) a current-voltage tracer; detecting one or more anomalies in the obtained current-voltage samples by applying machine learning techniques to the obtained current-voltage samples; automatically performing a root cause analysis on the detected anomalies by (i) converting the obtained current-voltage samples to sequential data, (ii) applying a sequence classifier to the sequential data, and (iii) identifying a pre-determined anomaly class comparable to the sequential data based on the application of the sequence classifier; and automatically generating and outputting a suggestion for remedial action based on the identified pre-determined anomaly class.

Internet of things-enabled solar photovoltaic health monitoring and advising related thereto

Methods, systems and computer program products for multi-style text transformation are provided herein. A computer-implemented method includes obtaining input text and selecting a set of style specifications for transforming the input text. The set of style specifications include one or more target writing style domains selected from a plurality of writing style domains, weights for each of the target writing style domains representing relative impact of the target writing style domains for transformation of the input text, and weights for each of a set of linguistic aspects for transformation of the input text. The computer-implemented method also includes generating one or more style-transformed output texts based at least in part on the set of style specifications utilizing an unsupervised neural network.

One embodiment provides a method, including: receiving configuration input for a solar structure; the configuration input comprising (i) a geographical location, (ii) module configuration input, and (iii) reflector configuration input; identifying the position of the sun; determining an angle between the solar reflector and the solar module corresponding to a predetermined power gain for the solar module, wherein the determining comprises (i) identifying the corresponding area of the solar module that is illuminated by the solar reflector and (ii) totaling the contributions from each of the solar reflectors to calculate an irradiance for each solar cell; adjusting the angles of at least some of the solar reflectors with respect to the solar module to angles determined to correspond to the predetermined power gain using at least one actuator; and dynamically changing how the solar cells are electrically connected together to form a plurality of strings.

Solar structure

Methods, systems, and computer program products for unsupervised tunable stylized text transformations are provided herein. A computer-implemented method includes identifying stylistically amendable portions of input text by applying at least one neural network to the input text; determining stylistic text modifications to the amendable portions of the input text, the text modifications encompassing a set of stylistic parameters, wherein the determining comprises applying at least one neural network to the set of stylistic parameters; generating a stylized output set of text by transforming the input text, wherein the transforming comprises modifying at least one of the stylistically amendable portions of the input text via at least one of the stylistic text modifications encompassed by the set of stylistic parameters; and outputting the stylized output set of text to a user.

A method and apparatus for optimizing channel access by an access point (AP) in a wireless local area network is provided, the method comprises transmitting first information to a station, and receiving second information from the station while transmitting the first information to the station, wherein the first information and the second information includes at least one of a request to send (RTS) frame, clear to send (CTS) frame, acknowledgement information, and data, respectively.

Method and system for optimizing channel access in a wireless local area network

Methods, systems, and computer program products for cognitively predicting dust deposition on solar photovoltaic modules are provided herein. A computer-implemented method includes deriving, with respect to solar photovoltaic modules, dust parameters from image data, and estimating, for a given future time at a current module orientation, an amount of surface area of the modules that will be covered by dust and a yield loss of the modules associated with dust coverage. The method also includes forecasting, for the given future time at each of one or more modified module orientations, an amount of surface area of the modules that will be covered by dust and a yield loss of the modules associated with dust coverage. Further, the method includes generating an instruction to change the orientation of at least one of the modules, and outputting the instruction to at least one actuation system associated with the modules.

Cognitively predicting dust deposition on solar photovoltaic modules

A method and apparatus for a collision-free carrier sense multiple access (CSMA) are provided. The method of a node associated with a beacon enabled carrier sense multiple access (CSMA)-based wireless communication network through an access point (AP) includes receiving a beacon from the AP, the beacon comprising a back-off prime number and a beacon random number, and generating a back-off interval based on the beacon random number, the back-off prime number, a mapped identification (ID) of the node, and a current time slot of a frame of the beacon. The method and apparatus provide a collision-free CSMA scheme for a beacon enabled CSMA-based wireless communication network. In the collision-free CSMA scheme, uniformly distributed back-off intervals may be generated in a distributed fashion at each node for a CSMA-based wireless communication network. The back-off intervals may be correlated among the nodes even though the nodes do not communicate with each other.

Method and apparatus to achieve collision-free random access

Growing community of inventors

Bengaluru, India

Amar Prakash Azad