Abstract: The invention relates to a process for preparing heterocyclic amide derivatives, to novel polymorphic forms obtained from said process and the use of said polymorphic forms for use in the treatment and prophylaxis of cancer.

Abstract: A system for strabismus assessment and a method of strabismus assessment. The system comprises a display module arranged to display a visual stimulus to be observed by an observer; an image capturing module arranged to record a plurality of images of at least one eye of the observer observing the visual stimulus; and a processing module arranged to determine an ocular misalignment condition of the observer based on the plurality of images recorded by the image capturing module.

Abstract: The present disclosure provides a method and an apparatus for recommending a travel way. The method includes: obtaining historical travel data; determining a plurality of correlations between respective travel ways according to the historical travel data; generating a vector corresponding to each travel way according to the plurality of correlations between respective travel ways; performing learning on an initial vector corresponding to each user and an initial vector corresponding to each starting-and-arrival pair according to the vector corresponding to each travel way and the historical travel data, to obtain a vector corresponding to each user and a vector corresponding to each starting-and-arrival pair; and recommending a travel way according to the vector corresponding to each travel way, the vector corresponding to each user and the vector corresponding to each starting-and-arrival pair.

Abstract: The present disclosure provides a method and an apparatus for recommending a travel way. The method includes: obtaining historical travel data; determining a plurality of correlations between respective travel ways according to the historical travel data; generating a vector corresponding to each travel way according to the plurality of correlations between respective travel ways; performing learning on an initial vector corresponding to each user and an initial vector corresponding to each starting-and-arrival pair according to the vector corresponding to each travel way and the historical travel data, to obtain a vector corresponding to each user and a vector corresponding to each starting-and-arrival pair; and recommending a travel way according to the vector corresponding to each travel way, the vector corresponding to each user and the vector corresponding to each starting-and-arrival pair.

Abstract: An automated outlier detection system implements an unsupervised set of processes to determine feature subspaces from a dataset; determine candidate exploratory actions, where each candidate exploratory action is a specific combination of a feature subspace and a parameterized instance of an outlier detection algorithm; and identify a set of optimal exploratory actions to recommend for execution on the dataset from among the candidate exploratory actions. Outlier scores obtained as a result of execution of the set of optimal exploratory actions are processed to obtain one or more outlier views such that each outlier view represents a consistent characterization of outliers by each optimal exploratory action corresponding to that outlier view.

Abstract: Convergence times associated with simulated annealing based (SA-based) optimization in wireless networks can be reduced by introducing an additional local or cell-level evaluation step into the evaluation of global solutions. In particular, new local solutions may be evaluated based on local performance criteria when the new solutions are in a global solution deemed to have satisfied a global performance criteria. New local solutions that satisfy their corresponding local performance criteria remain in the new global solution. New local solutions that do not satisfy their corresponding local performance criteria are replaced with a corresponding current local solution from a current global solution, thereby modifying the new global solution. The resulting modified global solution includes both new local solutions and current local solutions prior to being accepted as the current global solution for the next iteration.

Abstract: A computer program product is provided for estimating algorithm run times given parameters of the algorithm, specifications of an architecture on which the algorithm will execute and dimensions of a data set which will be input into the algorithm. The computer program product includes instructions to cause a processing circuit to create training data sets, generate run time data of executions of instances of the algorithm on the architecture for each training data set, identify model-usable features, generate a map of the model-usable features to an expression of the run time data and iteratively tuning the model-usable features toward improving map accuracy until a target map accuracy is achieved, develop a predictive model based on iteratively tuned versions of the model-usable features and estimate a run time of an execution of the algorithm on a new data set and on a new architecture using the predictive model.

Abstract: An automated outlier detection system implements an unsupervised set of processes to determine feature subspaces from a dataset; determine candidate exploratory actions, where each candidate exploratory action is a specific combination of a feature subspace and a parameterized instance of an outlier detection algorithm; and identify a set of optimal exploratory actions to recommend for execution on the dataset from among the candidate exploratory actions. Outlier scores obtained as a result of execution of the set of optimal exploratory actions are processed to obtain one or more outlier views such that each outlier view represents a consistent characterization of outliers by each optimal exploratory action corresponding to that outlier view.

Abstract: An automated outlier detection system implements an unsupervised set of processes to determine feature subspaces from a dataset; determine candidate exploratory actions, where each candidate exploratory action is a specific combination of a feature subspace and a parameterized instance of an outlier detection algorithm; and identify a set of optimal exploratory actions to recommend for execution on the dataset from among the candidate exploratory actions. Outlier scores obtained as a result of execution of the set of optimal exploratory actions are processed to obtain one or more outlier views such that each outlier view represents a consistent characterization of outliers by each optimal exploratory action corresponding to that outlier view.

Abstract: A computer program product is provided for estimating algorithm run times given parameters of the algorithm, specifications of an architecture on which the algorithm will execute and dimensions of a data set which will be input into the algorithm. The computer program product includes instructions to cause a processing circuit to create training data sets, generate run time data of executions of instances of the algorithm on the architecture for each training data set, identify model-usable features, generate a map of the model-usable features to an expression of the run time data and iteratively tuning the model-usable features toward improving map accuracy until a target map accuracy is achieved, develop a predictive model based on iteratively tuned versions of the model-usable features and estimate a run time of an execution of the algorithm on a new data set and on a new architecture using the predictive model.

Abstract: An automated outlier detection system implements an unsupervised set of processes to determine feature subspaces from a dataset; determine candidate exploratory actions, where each candidate exploratory action is a specific combination of a feature subspace and a parameterized instance of an outlier detection algorithm; and identify a set of optimal exploratory actions to recommend for execution on the dataset from among the candidate exploratory actions. Outlier scores obtained as a result of execution of the set of optimal exploratory actions are processed to obtain one or more outlier views such that each outlier view represents a consistent characterization of outliers by each optimal exploratory action corresponding to that outlier view.

Abstract: A method for determining cell states to adjust antenna configuration parameters includes receiving, at a radio access nodes in a network, measurement reports from a plurality of user equipment devices. The radio access node performs a weak coverage analysis in response to the measurement reports to determine whether a cell provided by the radio access node is assigned a good coverage state or a weak coverage state. The radio access node performs an overshooting analysis in response to the measurement reports to determine whether the cell provided by the radio access node is assigned an overshooter state or a non-overshooter state. The radio access node performs an interference analysis in response to the measurement reports to determine whether the cell provided by the radio access node is assigned an interferer state or a non-interferer state.

Abstract: An automated outlier detection system implements an unsupervised set of processes to determine feature subspaces from a dataset; determine candidate exploratory actions, where each candidate exploratory action is a specific combination of a feature subspace and a parameterized instance of an outlier detection algorithm; and identify a set of optimal exploratory actions to recommend for execution on the dataset from among the candidate exploratory actions. Outlier scores obtained as a result of execution of the set of optimal exploratory actions are processed to obtain one or more outlier views such that each outlier view represents a consistent characterization of outliers by each optimal exploratory action corresponding to that outlier view.

Abstract: Convergence times associated with simulated annealing based (SA-based) optimization in wireless networks can be reduced by introducing an additional local or cell-level evaluation step into the evaluation of global solutions. In particular, new local solutions may be evaluated based on local performance criteria when the new solutions are in a global solution deemed to have satisfied a global performance criteria. New local solutions that satisfy their corresponding local performance criteria remain in the new global solution. New local solutions that do not satisfy their corresponding local performance criteria are replaced with a corresponding current local solution from a current global solution, thereby modifying the new global solution. The resulting modified global solution includes both new local solutions and current local solutions prior to being accepted as the current global solution for the next iteration.

Abstract: A method for determining cell states to adjust antenna configuration parameters includes receiving, at a radio access nodes in a network, measurement reports from a plurality of user equipment devices. The radio access node performs a weak coverage analysis in response to the measurement reports to determine whether a cell provided by the radio access node is assigned a good coverage state or a weak coverage state. The radio access node performs an overshooting analysis in response to the measurement reports to determine whether the cell provided by the radio access node is assigned an overshooter state or a non-overshooter state. The radio access node performs an interference analysis in response to the measurement reports to determine whether the cell provided by the radio access node is assigned an interferer state or a non-interferer state.