A random sequence generation of defined values may be provided. A method comprises pre-loading a RAM block with an initial list comprising the defined values of a sequence of values to be updated, and shuffling the defined values of the sequence using a counter and a random offset for indices in the list.

A system performs cloud-based fire protection. The system receives, by a cloud platform, data from one or more initiating devices. The system stores the data in a persistent data storage of the cloud platform over a period of time. The system applies machine learning to the data to build or adjust a predictive detection model. The system processes, by computing resources of the cloud platform, the data using the predictive detection model to determine an existence of a safety event. The system then transmits, to at least one notification device, an event notification in response to the existence of the safety event.

A system performs cloud-based fire protection. The system receives, by a cloud platform, data from one or more initiating devices. The system stores the data in a persistent data storage of the cloud platform over a period of time. The system applies machine learning to the data to build or adjust a predictive detection model. The system processes, by computing resources of the cloud platform, the data using the predictive detection model to determine an existence of a safety event. The system then transmits, to at least one notification device, an event notification in response to the existence of the safety event.

Identifying pathways that are significantly impacted in a given condition is a crucial step in the understanding of the underlying biological phenomena. All approaches currently available for this purpose calculate a p-value that aims to quantify the significance of the involvement of each pathway in the given phenotype. These p-values were previously thought to be independent. Here, we show that this is not the case, and that pathways can affect each other's p-values through a “crosstalk” phenomenon that affects all major categories of existing methods. We describe a novel technique able to detect, quantify, and correct crosstalk effects, as well as identify novel independent functional modules. We assessed this technique on data from four real experiments coming from three phenotypes involving two species.

A design application receives an exemplary design from an end-user having one or more functional attributes relevant to solving a design problem. The design application then generates a set of labels that describes the functional attributes of the exemplary design. Based on the set of labels, the design application explores a functional space to retrieve one or more system classes having functionally descriptive labels that are similar to the set of labels generated for the exemplary design. The one or more system classes include different approaches to solving the design problem, and represent systems having at least some functional attributes in common with the exemplary design.

A design application receives an exemplary design from an end-user having one or more functional attributes relevant to solving a design problem. The design application then generates a set of labels that describes the functional attributes of the exemplary design. Based on the set of labels, the design application explores a functional space to retrieve one or more system classes having functionally descriptive labels that are similar to the set of labels generated for the exemplary design. The one or more system classes include different approaches to solving the design problem, and represent systems having at least some functional attributes in common with the exemplary design.

A method for manufacturing a part by additive manufacturing, the part to be manufactured including at least one portion to be held forming an angle of less than 45° with respect to a building direction of the part to be manufactured, the portion to be held having a first lateral surface and a second lateral surface opposite each other, the method comprising the steps of: providing a digital model of the part to be manufactured, adding to the digital model at least one holding element positioned on one side of the portion to be held, so as to be in contact with said first lateral surface or said second lateral surface.

A design engine implements a probabilistic approach to generating designs that exposes automatically-generated design knowledge to the user during operation. The design engine interactively generates successive populations of designs based on a problem definition associated with a design problem and/or a previously-generated population of designs. During the above design process, the design engine generates a design knowledge graphical user interface (GUI) that graphically exposes various types of design knowledge to the user. In particular, the design engine generates a design variable dependency GUI that visualizes various dependencies between designs variables. The design engine also generates a design evolution GUI that animates the evolution of designs across the successive design populations. Additionally, the design engine generates a design exploration GUI that facilitates the user exploring various statistical properties of automatically-generated designs.

A design engine implements a probabilistic approach to generating designs that exposes automatically-generated design knowledge to the user during operation. The design engine interactively generates successive populations of designs based on a problem definition associated with a design problem and/or a previously-generated population of designs. During the above design process, the design engine generates a design knowledge graphical user interface (GUI) that graphically exposes various types of design knowledge to the user. In particular, the design engine generates a design variable dependency GUI that visualizes various dependencies between designs variables. The design engine also generates a design evolution GUI that animates the evolution of designs across the successive design populations. Additionally, the design engine generates a design exploration GUI that facilitates the user exploring various statistical properties of automatically-generated designs.

A computer-aided design (CAD) system enables physical articles to be customized via printing or embroidering and enables digital content to be customized and electronically shared. A CAD user interface may be generated that includes an image of a model of an article of manufacture and a customizable template. The customizable template may include user customizable design areas. One or more defined rules associated with respective customizable areas may be accessed. In response to a user selection of a default content item and a corresponding rule, content items may be automatically used to populate other template design areas and/or change a color of one or content items. Manufacturing instructions corresponding to the user customizations may be transmitted to a printing system using a file that includes location, rotation, and/or scale data.