Abstract: One embodiment provides a computer implemented method, including: receiving interaction logs of a plurality of services of an application running on a system; generating an interaction graph identifying interactions between at least the at least one of the plurality of services and other of the plurality of services, wherein the identifying comprises identifying a frequency of interactions between services; determining constraints between at least the at least one of the plurality of services and the other of the plurality of services, wherein the constraints identify services that are dependent upon other services of the plurality of services and a compatibility of services with respect to other services of the plurality of services; and creating a remediation plan for updating the at least one of the plurality of services, wherein the remediation plan identifies a time for updating the at least one of the plurality of services.

Abstract: One embodiment provides a computer implemented method, including: receiving an application to be deployed on a container-based environment; obtaining a specification for the application including information regarding a portion of the application contained within a given container; extracting portion information corresponding to connections between different portions of the application and interferences between different portions of the application; identifying affinity indicators and anti-affinity indicators for the portions of the application, wherein the affinity indicators are based upon the connections between different portions of the application and wherein the anti-affinity indicators are based upon the interferences between different portions of the application; and constructing affinity rules and anti-affinity rules for the containers by combining the affinity indicators to construct affinity rules and combining the anti-affinity indicators to construct anti-affinity rules.

Abstract: A method, system, and computer program product to manage a network comprising a plurality of interconnected components are described. The method includes obtaining a set of all the components that are part of the network over time, and identifying one or more repeating patterns of components among the set of all the components as corresponding lower-level definitions to generate a hierarchical set of all the components. The method also includes obtaining time-varying information regarding topology and operational values within the network, and creating a representation of the network at a set of times based on the hierarchical set of all the components and the time-varying information.

Abstract: One embodiment provides a computer implemented computer implemented method, including: receiving information describing an application to be split into a plurality of modules to be hosted on a remote services environment; identifying a plurality of possible sets of modules for splitting the application; providing a visualization of the application split into modules, wherein the visualization displays different possible sets of modules as different layers within the visualization; and splitting, responsive to receiving user input within the visualization selecting one of the different layers, the application into one of the different possible sets of modules based upon the one of the different layers.

Abstract: Methods, systems, and computer program products for anomaly and mode inference from time series data are provided herein. A computer-implemented method includes receiving time-series sensor data for each one of a group of devices; extracting a set of states for each device in the group from the time-series sensor data; constructing a state-transition graph for each of the devices, wherein each of the state-transition graphs comprises nodes corresponding to each state in the set and edges corresponding to a probability of transition between the extracted states over time; identifying, for each set, a given state as one of: a mode, a normal state and an anomalous state based on the state-transition graph; and detecting one or more anomalous devices in the group by computing similarities between different devices in the group, based at least in part on the determined state-transition graphs.

Abstract: In an approach for an indoor survey data collection, a processor generates reference points based on a site map and an accuracy requirement. A processor collects data at each reference point through a data collecting agent. A processor detects an outlier at the reference points using a feedback from the data collecting agent during the data collection and a database. A processor eliminates the detected outlier and rectifies the data.

Abstract: A method for guided design generation includes receiving a plurality of image samples for an intended design and generating a first plurality of images by providing a positive latent vector to a first layer out of a plurality of layers and a negative latent vector to remaining layers out of the plurality of layers. Responsive to receiving a first image selection, identifying the first layer out of the plurality of layers generated the first image includes a feature of interest. Determining a feature expression variation for the feature of interest in latent space based on the ranking of a first plurality of generated sample images, wherein the first plurality of generated sample images includes the feature of interest. Responsive to receiving a second plurality of images for a plurality of base features, generating an initial design based on the feature of interest and the plurality of base features.

Abstract: 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.

Abstract: One embodiment provides a computer implemented method, including: receiving an application including a plurality of services to be hosted on a remote services environment; obtaining, a resource profile identifying a usage of a resource by a given service of the plurality of services over a period of time; splitting, based upon the resource profile corresponding to a given service, the given service into a plurality of service slices; selecting, for each of the plurality of service slices an incarnation fulfilling a resource demand requirement and a service-performance-offering, wherein an incarnation has a total demand value based upon a resource capacity of a node at the remote services environment; and assigning, for each of the plurality of service slices the incarnation selected to at least one node within the remote services environment based upon the resource capacity of the at least one node.

Abstract: A computer-implemented method includes receiving, by a processor, real time operation data related to an application, identifying components of the application based on the operation data, extracting relationships and interdependencies between the components, and generating a graph of the identified components, the relationships and the interdependencies. The method also includes determining one or more dynamic metrics of the identified components, the one or more dynamic metrics indicative of interactions between the components, extracting statistical information describing at least one of performance and resource consumption based on the operation data, incorporating the dynamic metrics into the graph, determining a behavior of at least one component based on a pattern of appearance of the at least one component in the graph, and generating a model of the application based on the identified components and the determined behaviors.

Abstract: Methods, systems, and computer program products for data filtering with fuzzy attribute association are provided herein. A computer-implemented method includes obtaining one or more rules, specified by an expert, that define a partial ranking of a plurality of fuzzy pairings between (i) a plurality of item attributes for items in a data catalog and (ii) a plurality of user attributes related to said items; generating an interactive session with the expert to resolve one or more ambiguities in the one or more rules; and deriving a scoring function based at least in part on (i) the one or more rules and (ii) the resolved one or more ambiguities, wherein the scoring function generates a comparative score between any two items of said data catalog for a given one of the users associated with the plurality of attributes.

Abstract: One embodiment provides a method, including: receiving a client fashion catalog comprising a plurality of images of client wearable products; creating a market fashion catalog comprising a plurality of market wearable products identified from sources other than the client fashion catalog, wherein the creating comprises (i) accessing a plurality of secondary sources, (ii) capturing information corresponding to market wearable products from the plurality of secondary sources, and (iii) aggregating the information to create the market fashion catalog; generating, for each market wearable product, (iv) a desirability score and (v) a multi-modal description of characteristics; producing, for the market wearable products, by utilizing the multi-modal descriptions, a similarity score indicating how similar the market wearable product is to products within the client fashion catalog, wherein the producing comprises comparing market wearable products to client wearable products; and providing a recommendation for a ch

Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.

Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.

Abstract: One embodiment provides a method, including: receiving a clothing design, wherein the clothing design identifies attributes of an article of clothing; accessing a plurality of information sources having sentiments regarding attributes of pieces of clothing, wherein each of the plurality of information sources is assigned to one of a plurality of geographical regions; identifying location-dependent attributes of the pieces of clothing, wherein the location-dependent attributes comprise clothing attributes whose corresponding user sentiments vary across at least a subset of the geographical regions; and recommending, based upon the location-dependent attributes and a targeted geographical region in which the article of clothing is to be sold, parameter values for the attributes of the article of clothing, wherein the recommending comprises correlating (i) the targeted geographical region with (ii) location-dependent attributes having a positive sentiment within the targeted geographical region.

Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for predictive maintenance of refrigeration cases. A computer collects a temperature time series for a refrigeration case and, based on the temperature time series, learns a refrigeration case signature for both non-frost and defrost cycles. The computer generates features based on the refrigeration case signature and compares the refrigeration case signature to real time, or observed, temperatures and features using a rule-based and/or machine learning framework. Based on determining that the real time data varies beyond a threshold from the refrigeration case signature, the computer identifies a failure symptom of the refrigeration case and diagnoses a root cause of the symptom or failure. In addition, the computer may activate an alarm and open a work order corresponding to the root cause of the symptom or failure.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for predictive maintenance of refrigeration cases. A computer collects a temperature time series for a refrigeration case and, based on the temperature time series, learns a refrigeration case signature for both non-frost and defrost cycles. The computer generates features based on the refrigeration case signature and compares the refrigeration case signature to real time, or observed, temperatures and features using a rule-based and/or machine learning framework. Based on determining that the real time data varies beyond a threshold from the refrigeration case signature, the computer identifies a failure symptom of the refrigeration case and diagnoses a root cause of the symptom or failure. In addition, the computer may activate an alarm and open a work order corresponding to the root cause of the symptom or failure.

Abstract: A neural network based search system is provided. A first digital image is analyzed by a user device. A targeted object in the first digital image is determined based, at least in part, on (i) the characteristics of the first digital image and (ii) the features of the targeted object. A vector array is generated based, at least in part, on (i) the first digital image and (ii) the targeted object. The vector array is analyzed by the user device. The targeted object is determined based, at least in part, by the vector array. A plurality of digital images is identified based, at least in part, on the similarity of the plurality of digital images and (i) the first digital image and (ii) the targeted object responsive to identifying a plurality of digital images, a query processing is generated. The query map is generated on a user device.

Abstract: In an approach for an indoor survey data collection, a processor generates reference points based on a site map and an accuracy requirement. A processor collects data at each reference point through a data collecting agent. A processor detects an outlier at the reference points using a feedback from the data collecting agent during the data collection and a database. A processor eliminates the detected outlier and rectifies the data.