A platform for design of a lighting installation generally includes an automated search engine for retrieving and storing a plurality of lighting objects in a lighting object library and a lighting design environment providing a visual representation of a lighting space containing lighting space objects and lighting objects. The visual representation is based on properties of the lighting space objects and lighting objects obtained from the lighting object library. A plurality of aesthetic filters is configured to permit a designer in a design environment to adjust parameters of the plurality of lighting objects handled in the design environment to provide a desired collective lighting effect using the plurality of lighting objects.

A platform for design of a lighting installation generally includes an automated search engine for retrieving and storing a plurality of lighting objects in a lighting object library and a lighting design environment providing a visual representation of a lighting space containing lighting space objects and lighting objects. The visual representation is based on properties of the lighting space objects and lighting objects obtained from the lighting object library. A plurality of aesthetic filters is configured to permit a designer in a design environment to adjust parameters of the plurality of lighting objects handled in the design environment to provide a desired collective lighting effect using the plurality of lighting objects.

A platform for design of a lighting installation generally includes an automated search engine for retrieving and storing a plurality of lighting objects in a lighting object library and a lighting design environment providing a visual representation of a lighting space containing lighting space objects and lighting objects. The visual representation is based on properties of the lighting space objects and lighting objects obtained from the lighting object library. A plurality of aesthetic filters is configured to permit a designer in a design environment to adjust parameters of the plurality of lighting objects handled in the design environment to provide a desired collective lighting effect using the plurality of lighting objects.

The present disclosure is related to automatic content generation. In one example, user interactions, associated with a target business process software application, are captured and stored. Further in this example, one or more scenarios of using the target business process software application are determined from the captured and stored user interactions. A set of rules are then formed and stored in a rules repository to generate the content. The content is then automatically generated using the captured and stored user interactions, the determined one or more scenarios of using the target business process software application and/or the stored set of rules.

Embodiments of the disclosure are drawn to apparatuses, systems, methods for performing operations associated with machine learning. Machine learning operations may include processing a data set, training a machine learning algorithm, and applying a trained algorithm to a data set. Some of the machine learning operations, such as pattern matching operations, may be performed within a memory device.

Embodiments of the disclosure are drawn to apparatuses, systems, methods for performing operations associated with machine learning. Machine learning operations may include processing a data set, training a machine learning algorithm, and applying a trained algorithm to a data set. Some of the machine learning operations, such as pattern matching operations, may be performed within a memory device.

In one aspect, the present disclosure relates to a method which comprises obtaining a set of software change process parameters characterizing the particular process, based on the obtained set of software change process parameters, selecting hot spot information corresponding to the obtained set of software change process parameters, the hot spot information being based on a statistical analysis of previous software change processes and wherein the hot spot information identifies one or more steps of the multiple steps of the process during which problems have occurred in the previous processes, providing the hot spot information to the host computer system for use in the software change process and obtaining status information relating to the software change process at multiple times during the execution of the software change process, a level of detail of the status information being increased for steps of the process identified in the hot spot information.

System pre-processes and computes class distribution of decision attribute and statistics for discretization of continuous attributes through use of compute buckets. System computes the variability of each of the attributes and considers only the non-zero variability attributes. System computes the discernibility strength of each attribute. The software system generates size 1 patterns using compute bucket and calculates if each pattern of size 1 is a reliable pattern for any class. The system calculates if reliable pattern of size 1 is a significant pattern for any class. The system generates size k patterns from size k−1 patterns checking for significance of size k patterns and refinability. The system readjusts pattern statistics for only significant patterns for size k−1 patterns. The system computes a cumulative coverage of the sorted relevant patterns of up to size k by finding out the union of records of that particular class.

Embodiments of the disclosure are drawn to apparatuses, systems, methods for an internet of things (IoT) system to include edge devices that perform at least some functions without communicating with a cloud computing system. An edge device may include a memory with on-memory pattern matching capabilities. The edge device may perform pattern matching operations on data collected by the edge device or sensors in communication with the edge device. Based on results of the pattern matching operations, the edge device may perform various functions, such as transmitting data to the cloud computing system, activating an alarm, and/or changing a frequency at which data is transmitted.

Embodiments of the disclosure are drawn to apparatuses, systems, methods for an internet of things (IoT) system to include edge devices that perform at least some functions without communicating with a cloud computing system. An edge device may include a memory with on-memory pattern matching capabilities. The edge device may perform pattern matching operations on data collected by the edge device or sensors in communication with the edge device. Based on results of the pattern matching operations, the edge device may perform various functions, such as transmitting data to the cloud computing system, activating an alarm, and/or changing a frequency at which data is transmitted.