Abstract: In a controller and a machine learning device capable of suppressing an influence of an abnormal value based on noise, etc., the machine learning device included in the controller includes a state observation unit for acquiring input data including at least one of internal data and external data of the manufacturing machine controlled by the controller, an input safety circuit for detecting an abnormality in the input data and outputting safe input data, a machine learning unit for executing learning of a learning model and inference using the learning model based on the safe input data and outputting inference data as an inference result, an output safety circuit for detecting an abnormality in the inference data and outputting safe inference data, and an output unit for outputting output data based on the safe inference data.

Abstract: In order to improve aggregation property of a PPR protein, the A6 amino acid of the 1st PPR motif from the N-terminus (M1) is made more hydrophilic. Further, the A9 amino acid of M1 is made to be a hydrophilic amino acid or glycine. The A6 amino acid is preferably asparagine or aspartic acid, and the A9 amino acid is preferably glutamine, glutamic acid, lysine, or glycine. Proteins containing such a PPR motif as M1 motif may have not only improved aggregation property, but also high binding power to a target nucleic acid.

Abstract: In a controller and a machine learning device capable of suppressing an influence of an abnormal value based on noise, etc., the machine learning device included in the controller includes a state observation unit for acquiring input data including at least one of internal data and external data of the manufacturing machine controlled by the controller, an input safety circuit for detecting an abnormality in the input data and outputting safe input data, a machine learning unit for executing learning of a learning model and inference using the learning model based on the safe input data and outputting inference data as an inference result, an output safety circuit for detecting an abnormality in the inference data and outputting safe inference data, and an output unit for outputting output data based on the safe inference data.

Abstract: An abnormality detection apparatus includes a machine learning apparatus for learning waveform data concerning a physical quantity detected when a machine tool is normally operating. The machine learning apparatus observes the waveform data concerning the physical quantity detected when the machine tool is normally operating, as a state variable indicating a current environmental state, and learns a feature of the waveform data concerning the physical quantity detected when the machine tool is normally operating, using the observed state variable.

Abstract: An electric motor, the insulating performance of the coil of which is high, contains no voids or few voids in the stator core. The coil 3 is wrapped in the sheet of insulating paper 4, which is open to the opening portion side of the slot 2 of the stator core 1, and is inserted into the slot 2. After that, molding is conducted by the insulating resin 5. When the resin 5 is entered into the slot 5, air is discharged from the slot to the opening portion. Nothing blocks this flow of air. Therefore, the generation of voids such as cavities and empty holes can be prevented, and the coil 3 can be insulated in the slot 2 under the condition that no voids are generated or the generation of voids is reduced. As no voids are generated, the dielectric strength can be enhanced. Further, the number of manufacturing processes can be decreased and the quantity of insulating paper used can be also decreased. Accordingly, it is possible to obtain an electric motor with a lower manufacturing cost.

Abstract: An electric motor with a stator structure having a high thermal conductivity from coils to a stator core, and capable of suppressing vibration of coils and adjusting an output torque and a cogging amount of the motor. A stator core is provided at its inner periphery with main teeth extending radially and spaced at regular intervals from one another. Auxiliary teeth are provided in slots formed between adjacent main teeth. Coils are arranged such that, when wound around the main teeth, their outer peripheral faces are in close contact with the auxiliary teeth. Since the coils are in contact at their central portions with the main teeth and in close contact at their outer peripheral portions with the auxiliary teeth, heat generated from the coils energized is efficiently conducted to the stator core, and removed by cooling devices provided at outer peripheral portions of the stator, thereby cooling the motor. Since the coils are fixedly held between the main and auxiliary teeth, vibration can be prevented.