A method for building and using soil models that determine soil properties from soil spectrum data is provided. In an embodiment, building soil model may be accomplished using soil spectrum data received via hyperspectral sensors from a land unit. A processor updates the soil spectrum data by removing interference signals from the soil spectrum data. Multiple ground sampling locations within the land unit are then determined based on the updated soil spectrum data. Soil property data are obtained from ground sampling at the ground sampling locations. Soil models that correlate the updated soil spectrum data with the soil property data are created based on the updated soil spectrum data and the soil property data. The soil models are sent to a storage for future use.

A method includes receiving a pattern layout for a mask, shrinking the pattern layout to form a shrunk pattern, determining centerlines for each of a plurality of features within the shrunk pattern, and snapping the centerline for each of the plurality of features to a grid. The grid represents a minimum resolution size of a mask fabrication tool. The method further includes, after snapping the centerline for each of the plurality of features to the grid, fabricating the mask with the shrunk pattern.

A method for determining national crop yields during the growing season is provided. In an embodiment, a server computer system receives agricultural data records for a particular year that represent covariate data values related to plants at a specific geo-location at a specific time. The system aggregates the records to create geo-specific time series for a geo-location over a specified time. The system creates aggregated time series from a subset of the geo-specific time series. The system selects a representative feature from the aggregated time series and creates a covariate matrix for each specific geographic area in computer memory. The system determines a specific crop yield for a specific year using linear regression to calculate the specific crop yield from the covariate matrix. The system determines a forecasted crop yield for the specific year using a sum of the specific crop yields for the specific year, as adjusted.

A logic circuit including first and second inverters, first and second NAND circuits, a transmission gate, and a transmission-gate-substitute (TGS) circuit, and wherein: for each of the first and second NAND circuits, a first input is configured to receive corresponding first and second data signals, and a second input is configured to receive an enable signal; the first inverter is configured to receive an output of the first NAND circuit; the transmission gate and the TGS circuit are arranged as a combination circuit which is configured to receive an output of the second NAND circuit as a data input, and outputs of the first inverter and the second NAND circuit as control inputs; the second inverter is configured to receive an output of the combination circuit; and an output of the second inverter represents one of an enable XOR (EXOR) function or an enable XNR (EXNR) function.

A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, perform certain acts. The acts can include obtaining information about a trailer that has been partially loaded with preloaded stacks in a manner that deviates from an original load design. The trailer is being loaded with stacks of pallets comprising the preloaded stacks and unloaded stacks. The acts also can include determining positions of empty floor spots remaining in the trailer. The acts additionally can include determining a first portion of an incremental load design for the unloaded stacks using a gap-filling pattern behind an uneven rear edge of the preloaded stacks. The acts further can include determining a second portion of the incremental load design. The acts additionally can include updating the incremental load design based on an overall load design of the trailer. The acts further can include outputting at least the incremental load design, as updated. The incremental load design can specify a respective floor spot assignment for each of the unloaded stacks. Other embodiments are described.

The invention relates to the technical field of computer-aided design of integrated circuits, and provides a two-step X-architecture Steiner minimum tree construction method for very large scale integration (VLSI). Based on the advantages of an X-architecture model and a particle swarm optimization technique, the method is implemented through two steps: (1) the stage of social learning discrete particle swarm search, which comprises: using an edge-vertex encoding strategy capable of maintaining optimal topological information of particles, designing a fitness function taking wirelength into consideration; and using a chaotic decreasing mutation strategy and a new social learning strategy to design a new discrete particle swarm update formula; and (2) a stage of wirelength optimization, which comprises: designing a local topological optimization strategy to minimize the wirelength of an X-architecture Steiner tree. The method guarantees short total wirelength of nets and has high stability, thus being able to construct a high-quality X-architecture Steiner minimum tree.

A method and an apparatus for setting an evacuation exit under a crowd emergency evacuation scenario are provided. A simulation model is constructed based on a social force model, and a behavior parameter of an evacuating crowd under the crowd emergency evacuation scenario is obtained by a numerical approximation method with actual trajectory data of individuals in the evacuating crowd under a specific emergency evacuation scenario as a reference; an evacuation exit set is set, an integer programming solution for evacuation exit decision under the emergency evacuation scenario is constructed, and a total evacuation cost of the evacuation exit is obtained based on the simulation model; and reduction of the total evacuation cost is taken as an optimization target to construct an emergency evacuation optimization model based on constraint conditions, and the emergency evacuation optimization model is solved to obtain a recommended integer programming solution for evacuation exit decision.

Various examples are provided related to automated chip design, such as a pareto-optimization framework for automated network-on-chip design. In one example, a method for network-on-chip (NoC) design includes determining network performance for a defined NoC configuration comprising a plurality of n routers interconnected through a plurality of intermediate links; comparing the network performance of the defined NoC configuration to at least one performance objective; and determining, in response to the comparison, a revised NoC configuration based upon iterative optimization of the at least one performance objective through adjustment of link allocation between the plurality of n routers. In another example, a method comprises determining a revised NoC configuration based upon iterative optimization of at least one performance objective through adjustment of a first number of routers to obtain a second number of routers and through adjustment of link allocation between the second number of routers.

A method for generating a tool designed to interact with an object includes obtaining a model of the object, the model including at least a geometry of the object. A criterion set including at least one criterion for the tool is determined, and a virtual tool fulfilling the criterion set is created. An attribute reflecting a simulated interaction between the model and the virtual tool is calculated to thereby obtain an attribute value. On the basis of the attribute value, a to-be-fabricated virtual tool is appointed, and a corresponding tool is fabricated. By means of the present method, the performances of candidate tools can be evaluated before the fabrication of the same. Based on the evaluation, it can be decided whether, and which one, of the candidate tools shall be fabricated.

A method for optimizing the energy expenditure and the comfort of a building, including comfort systems provided with an online consumption sensor, local environment data sensors associated with an identifier of a zone of the building, and at least one server for collecting and recording the timestamped data remotely includes the following steps: constructing and saving a simplified digital model of the thermal behavior of the building; a step of calibrating the simplified digital model calculated during the preceding step; a step of validating the calibrated digital model calculated during the preceding step by comparing the digital variables obtained by predictive processing of the calibrated model and the digital variables stored by the server over a period of a few days; a step of calculating digital parameters for resource allocation by applying a Pareto optimum calculation applied to the validated calibrated digital model.