Abstract: A display system includes: an image acquisition unit that acquires each of a first image of a work site imaged by a first camera and a second image of the work site imaged by a second camera; a viewpoint position calculation unit that calculates a viewpoint position of worker; a luminance adjustment unit that adjusts luminance of at least one of the first image and the second image based on the viewpoint position; and a display control unit that combines the first image and the second image having the luminance adjusted and causes a display device to display the combined image.

Abstract: A vehicle front structure includes: a dash panel; a front side member; a suspension tower coupled to a upper part of the front side member; a dash cross member attached to the dash panel, the dash cross member being located at a more vehicle-upward position than a upper end of the suspension tower; and a suspension tower brace including a first coupling portion coupled to the upper end of the suspension tower and a second coupling portion coupled to the dash cross member. The first coupling portion is located at a more vehicle-downward position than the second coupling portion.

Abstract: Provided is a method capable of predicting the quality of cement in a short time period and with high accuracy. The method of predicting the quality or manufacturing conditions of cement through use of a neural network including an input layer and an output layer includes: performing learning of the neural network for a sufficiently large number of times of learning such that ?L<?M is obtained, using learning data and monitor data; then repeating the learning of the neural network until ?L??M is obtained while the number of times of learning is decreased; inputting specific observation data to the input layer of the neural network in which a judgment value for analysis degree obtained from the neural network after the learning is less than a preset value; and outputting an estimated value of specific evaluation data from the output layer of the neural network.

Abstract: Provided is a method capable of predicting the quality of cement in a short time period and with high accuracy. The method of predicting the quality or manufacturing conditions of cement through use of a neural network including an input layer and an output layer includes: performing learning of the neural network for a sufficiently large number of times of learning such that ?L<?M is obtained, using learning data and monitor data; then repeating the learning of the neural network until ?L??M is obtained while the number of times of learning is decreased; inputting specific observation data to the input layer of the neural network in which a judgment value for analysis degree obtained from the neural network after the learning is less than a preset value; and outputting an estimated value of specific evaluation data from the output layer of the neural network.