Abstract: A power tool including a housing, a motor supported within the housing and including an output shaft, a transmission assembly, and an impact mechanism. The motor is configured to rotationally drive the output shaft. The transmission assembly is configured to be rotationally driven by the output shaft. The impact mechanism includes a camshaft configured to be rotationally driven by the transmission assembly, a hammer, and an anvil. The camshaft has a groove, and at least a portion of the groove is defined by an equation selected from a group consisting of: trigonometric equations and higher order differential equations. The hammer is coupled to the camshaft by a cam ball received in the groove. The anvil is configured to receive intermittent rotational impacts from the hammer.

Abstract: Double patterning techniques described herein may reduce corner rounding, etch loading, and/or other defects that might otherwise arise during formation of a deep trench isolation (DTI) structure in a pixel array. The double patterning techniques include forming a first set of trenches in a first direction and forming a second set of trenches in a second direction in a plurality of patterning operations such that minimal to no etch loading and/or corner rounding is present at and/or near the intersections of the first set of trenches and the second set of trenches.

Abstract: A nutrunner includes a housing, a motor with an output shaft rotatable about a first axis, a head including an output drive rotatable about a second axis, a transmission including a ring gear rotatable about the first axis, and a clutch mechanism. The clutch mechanism includes an adjustment collar rotatable about the first axis, rolling elements engaged with the ring gear, and a spring between the adjustment collar and the ring gear to bias the rolling elements into engagement with the ring gear. The clutch mechanism is configured to prevent the ring gear from rotating when a torque applied to the ring gear is less than a torque threshold, and to permit the ring gear to rotate when a torque applied to the ring gear is greater than or equal to the torque threshold. Rotation of the adjustment collar about the first axis adjusts the torque threshold.

Abstract: A data processing method applied in a data center is provided.

Abstract: The federated learning system includes a moderator and client devices. Each client device performs a method for verifying model update as follows: receiving a hash function and a general model; training a client model according to the general model and raw data; calculating a difference as an update parameter between the general model and the client model, sending the update parameter to the moderator; inputting the update parameter to the hash function to generate a hash value; sending the hash value to other client devices, and receiving other hash values; summing all the hash values to generate a trust value; receiving an aggregation parameter calculated according to the update parameters; inputting the aggregation parameter to the hash function to generate a to-be-verified value; and updating the client model according to the aggregation parameter when the to-be-verified value equals the trust value.

Abstract: The present disclosure provides a method including: generating a first private key and a public key according to a parameter set of full homomorphic encryption; encrypting test data and label by the public key to generate test data ciphertext and label ciphertext; generating a smart contract executed by a blockchain system, and transferring control of an amount of cryptocurrency from a first cryptocurrency account to the blockchain; receiving a result of a verification to a model ciphertext; when the result indicates that the model ciphertext does not pass the verification, retrieving the control of the amount of cryptocurrency; and when the result indicates that the model ciphertext passes the verification, receiving the model ciphertext and a second private key from the blockchain system, and decrypting, according to the first and second private keys, the model ciphertext to generate a model to infer the test data.

Abstract: A method for evaluating robots in simulation, when executed on a computing device, involves the following steps: obtaining a robot description file created based on the physical properties of a robot, obtaining an environment description file created based on an environment, and obtaining an obstacle description file. A physics simulation engine creates a virtual environment based on the environment description file and obstacle description file. A virtual robot is created based on the robot description file. When the virtual robot navigates from the starting area to the ending area within the virtual environment based on navigation information, the physics simulation engine outputs simulation information. The robot navigation program generates and sends navigation information to the physics simulation engine based on the simulation information. When the virtual robot reaches the ending area, the physics simulation engine outputs evaluation information.

Abstract: A method of establishing application permissions includes utilizing a computing device to execute the following steps: requesting a first permission; determining whether the first permission exists in a plurality of application permissions in a permission table; obtaining the first permission when the first permission exists in the plurality of application permissions in the permission table; and reviewing the first permission when the first permission does not exist in the plurality of application permissions in the permission table.

Abstract: A segmentation model training method is disclosed. The segmentation model includes the following operations: inputting several first sample groups of a large sample set to a data augmentation model to generate several augmentation sample groups; generating several mix sample groups based on several second sample groups of a small sample set; inputting several mix sample groups to the data augmentation model to generate several augmentation mix sample groups; and training a segmentation model according to several augmentation sample groups and several augmentation mix sample groups, including: performing pre-training to the segmentation model according to several augmentation sample groups; and performing fine-tuning training to the segmentation model corresponding to several augmentation mix sample groups.

Abstract: A data processing method applied in a data center is provided.

Abstract: A communication system, a remote terminal unit, and an authentication method thereof are provided. The remote terminal unit includes a processing module. The processing module includes a first processing unit and a first storage unit. The first storage unit is coupled to the first processing unit. In response to a trigger unit being enabled, the first processing unit operates in a provision mode to allow an input/output module and the processing module to establish trust. In response to the trigger unit being disabled, the first processing unit operates in a running mode to prohibit another input/output module that has not yet established trust from connecting with the processing module.

Abstract: A system for real-time animation interactive editing is provided. The system for real-time animation interactive editing includes a physics simulation platform and an animation processing device. The animation processing device includes an animation editing circuit and a comparison processing circuit. The animation editing circuit is configured to obtain a motion animation associated with a robot and provide the motion animation to the physics simulation platform, such that the physics simulation platform performs a simulation processing based on the motion animation to generate a simulation result. The comparison processing circuit is configured to real-time obtain the simulation result generated by the physics simulation platform, and compare the simulation result with the motion animation to generate a comparison result.

Abstract: A capacitor includes cup-shaped lower electrodes disposed on a substrate, a capacitor dielectric layer conformally covering inner surfaces and outer surfaces of the cup-shaped lower electrodes, and a support layer disposed between outer surfaces of the cup-shaped lower electrodes to connect the cup-shaped lower electrodes. The capacitor further includes an annealed oxide layer, which is interposed between the inner surfaces of the cup-shaped lower electrodes and the capacitor dielectric layer, and is also interposed between a portion of the outer surfaces of the cup-shaped lower electrodes and the capacitor dielectric layer. A method for forming the capacitor is also provided.

Abstract: Double patterning techniques described herein may reduce corner rounding, etch loading, and/or other defects that might otherwise arise during formation of a deep trench isolation (DTI) structure in a pixel array. The double patterning techniques include forming a first set of trenches in a first direction and forming a second set of trenches in a second direction in a plurality of patterning operations such that minimal to no etch loading and/or corner rounding is present at and/or near the intersections of the first set of trenches and the second set of trenches.

Abstract: The present disclosure provides a multi-manifold embedding learning method, which includes steps as follows. The ID training data are used to train the multi-manifold embedding learning model, and then the parameters of the multi-manifold embedding learning model are frozen to obtain the trained multi-manifold embedding learning model; the test data are fed to the trained multi-manifold embedding learning model, so as to use a threshold to distinguish out-of-distribution samples from ID samples.

Abstract: The present disclosure relates to the technical field of medicaments. Particularly, the present disclosure provides a pharmaceutical combination/composition comprising a phosphodiesterase type 5 (PDE5) inhibitor, arginine, and N-acetylcysteine and its applications in treating cardiovascular diseases and erectile dysfunction.

Abstract: A method of implanting a cerebrospinal fluid-access device is provided. The method can include interlocking the device onto a delivery assembly to keep the device fixed longitudinally on the delivery assembly, advancing the delivery assembly into the cerebrospinal fluid space, and releasing the interlock to allow the delivery assembly to be removed while leaving the device implanted in the cerebrospinal fluid.

Abstract: A device for accessing a cerebrospinal fluid of a patient is provided. The device can include a central conduit that defines a central bore, which extends from a proximal end of the device to a distal end of the device. The device can further include a shunting port on the central conduit and within a longitudinal distance of 6 mm from the distal end of the device. The device further include a sealing membrane at the proximal end that forms a fluidic seal at the proximal end of the central bore.

Abstract: An optimization method for data flow includes converting a plurality of extract-transform-load (ETL) scripts into a data flow diagram, wherein the data flow diagram includes a plurality of data lineages, with each data lineage including a plurality of data nodes; performing a first merging process, which repeatedly identifies at least two data lineages with the same nodes and merges them into a data family until any two of the data lineages do not have the same nodes; performing a second merging process, which calculates a column similarity of a pair of node, wherein the pair of nodes includes two adjacent data nodes within a data lineage; when the column similarity exceeds a threshold, merging the two data nodes; when the column similarity of the pair of nodes falls below the threshold, the data flow diagram is optimized, which is then converted into ETL scripts accordingly.

Abstract: A machine learning training device is disclosed. The machine learning training device includes a virtual hard anchor generation circuit, a classification circuit and a training circuit. The virtual hard anchor generation circuit is configured to generate several virtual hard anchors according to several easy samples classified into several types. The virtual hard anchors respectively correspond to one of the several types. The classification circuit is configured to classify several hard samples into several types according to virtual hard anchors. Parts of the hard samples classified into several types are several clean hard samples. Another parts of the hard samples that are not classified into several types are several noisy hard samples. The training circuit is configured to perform machine learning training according to several easy samples and several clean hard samples.