Abstract: Methods and systems for generation of shape data for a set of electronic designs include inputting a set of shape data, where the set of shape data represents a set of shapes for a device fabrication process. A convolutional neural network is used on the set of shape data to determine a set of generated shape data, where the convolutional neural network comprises a generator trained with a set of pre-determined discriminators. The set of generated shape data comprises a scanning electron microscope (SEM) image.

Abstract: The invention proposes False targets caused by reflection position determining system and solution for the SSR which helps determine reflected real target's coordinate, reflector's coordinate and features, coordinate and features of the false target (multipath target) and using these data as the basis to build up the multipath target suppressing system, guaranteeing the detecting ability of the radar. The proposed system contains: Input data generating component; False target position (multipath position) determining component; Reflected signal power comparison calculating component; Displaying and data transferring component; Reflected multipath targets suppressing component.

Abstract: Methods and systems for compressing shape data for a set of electronic designs include inputting a set of shape data, where the shape data comprises mask designs. A convolutional autoencoder encodes the set of shape data, where the encoding compresses the set of shape data to produce a set of encoded shape data. The convolutional autoencoder is tuned for increased accuracy of the set of encoded shape data based on design rules for the set of electronic designs. The convolutional autoencoder comprises a set of parameters comprising weights, and the convolutional autoencoder has been trained to retain important information needed, based on the design rules for the set of electronic designs.

Abstract: Methods for generation of shape data for a set of electronic designs include inputting a set of shape data, where the set of shape data represents a set of shapes for a device fabrication process. A convolutional neural network is used on the set of shape data to determine a set of generated shape data, where the convolutional neural network comprises a generator trained with a pre-determined set of discriminators. The set of generated shape data comprises a scanning electron microscope (SEM) image.

Abstract: Methods for compressing shape data for a set of electronic designs include inputting a set of shape data, where the shape data comprises mask designs. A convolutional autoencoder encodes the set of shape data, where the encoding compresses the set of shape data to produce a set of encoded shape data. The convolutional autoencoder is tuned for increased accuracy of the set of encoded shape data based on design rules for the set of shape data. The convolutional autoencoder comprises a set of parameters comprising weights, and the convolutional autoencoder has been trained to determine what information to keep based on the weights.

Abstract: New platform technologies to actuate and sense force propagation in real-time for large sheets of cells are provided. In certain embodiments the platform comprises a device for the measurement of mechanical properties of cells or other moieties, where device comprises a transparent elastic or viscoelastic polymer substrate disposed on a rigid transparent surface; and a plurality of micromirrors disposed on or in said polymer substrate, wherein the reflective surfaces of the micromirrors are oriented substantially parallel to the surface of said polymer substrate. In certain embodiments the device comprises more than about 1,000,000, or more than about 10,000,000 micromirrors. In certain embodiments the micromirrors comprise a magnetic layer and/or a diffraction grating.

Abstract: The present disclosure relates to a smart and novel electronic hair clipper with a digital taper lever. Particularly, the electronic hair clipper includes a housing, a pair of clipper blades disposed on a top portion of the housing, and a digital taper lever disposed along an upper side portion of the housing near the clipper blades for electronically controlling a taper lever height.

Abstract: A system for collecting information through a plant includes a first remote detecting device attached to a first portion of the plant and configured to transmit a given signal directly through the plant; the plant, which constitutes a communication channel; a second remote detecting device attached to a second portion of the plant, which is different from the first portion, and configured to receive a signal indicative of the transmitted given signal; and a sink node that communicates with the second remote detecting device.

Abstract: A system configured to assist blockchain-based Internet of Things (IoT) applications connect with one another and share data securely and privately is described. The system includes an IoT network configured to interact with a blockchain network. The IoT network includes IoT systems, which include IoT devices that comprise sensors. The blockchain network includes a mainchain and sidechains. Each sidechain includes a consensus protocol that run on each node and is configured to increase data and synchronization between nodes. The consensus protocol utilizes a reasoning mechanism to enable each node to deduce states of events on other nodes, a gossip algorithm to synchronize data between nodes, and a vector clock algorithm in a knowledge graph deployed on every node to allow the event created during synchronization to be linked to the previous two events.

Abstract: An Automated Analysis and Warning of Optical Transmission (AWOT) between BBU unit and RRU of radio transmitting station accurately and quickly identifies errors on an optical transmission line, thereby reducing costs in terms of labor and equipment, and at the same time reducing service downtime of mobile communication systems.

Abstract: A method of modulating an optical camera communication (OCC) signal by an OCC transmission node in an OCC system includes acquiring a binary data signal, grouping the binary data signal for every k bits to convert the binary data signal into a global phase shift signal having an integer value from 0 to M?1 (=2k?1), generating a data signal group by mapping the global phase shift signal to first to Mth mapping sequences in the form of an n*M/2-bit sequence based on a preset symbol group mapping table, generating a pulse wave signal by modulating the data signal group, and blinking each of a plurality of light sources included in the OCC transmission node according to the pulse wave signal. Accordingly, performance of the communication system may be improved.

Abstract: Described are magnetocaloric materials comprising manganese, iron, phosphorus, silicon, carbon and optionally one or both of nitrogen and boron, and processes for producing said magnetocaloric materials.

Abstract: Methods for generation of shape data for a set of electronic designs include inputting a set of shape data, where the set of shape data represents a set of shapes for a device fabrication process. A convolutional neural network is used on the set of shape data to determine a set of generated shape data, where the convolutional neural network comprises a generator trained with a pre-determined set of discriminators. The set of generated shape data comprises a scanning electron microscope (SEM) image.

Abstract: Methods for training a convolutional neural network to register images for electronic designs include inputting a first pair of images aligned in a first modality and a second pair of images aligned in a second modality. An affine transformation is generated with a convolutional neural network, using one image from the first pair of images and one image from the second pair of images. The one image from the first pair of images is in the first modality and the one image from the second pair of images is in the second modality. Methods for registering images for electronic designs include inputting a pair of images, wherein the pair of images comprises a computer aided design (CAD) image and a scanning electron microscope (SEM) image. The CAD image is registered to the SEM image, using a trained convolutional neural network. The trained convolutional neural network further comprises an affine transformation.

Abstract: Compositions comprising activated topoisomerase adaptors (TOPO-adaptors) and methods of using the activated TOPO-adaptors are provided for preparing a library of target DNA duplexes derived from sample polynucleotides (e.g., DNA, RNA) for the streamlined preparation of a large number of samples. Such libraries may be used for Next Generation Sequencing (NGS).

Abstract: Methods for fracturing or mask data preparation are disclosed in which a set of single-beam charged particle beam shots is input; a calculated image is calculated using a neural network, from the set of single-beam charged particle beam shots; and a set of multi-beam shots is generated based on the calculated image, to convert the set of single-beam charged particle beam shots to the set of multi-beam shots which will produce a surface image on the surface. Methods for training a neural network include inputting a set of single-beam charged particle beam shots; calculating a set of calculated images using the set of single-beam charged particle beam shots; and training the neural network with the set of calculated images.

Abstract: Methods for compressing shape data for a set of electronic designs include inputting a set of shape data, where the shape data comprises mask designs. A convolutional autoencoder encodes the set of shape data, where the encoding compresses the set of shape data to produce a set of encoded shape data. The convolutional autoencoder is tuned for increased accuracy of the set of encoded shape data based on design rules for the set of shape data. The convolutional autoencoder comprises a set of parameters comprising weights, and the convolutional autoencoder has been trained to determine what information to keep based on the weights.

Abstract: Methods for generation of shape data for a set of electronic designs include inputting a set of shape data, where the set of shape data represents a set of shapes for a device fabrication process. A convolutional neural network is used on the set of shape data to determine a set of generated shape data, where the convolutional neural network comprises a generator trained with a pre-determined set of discriminators. The set of generated shape data comprises a scanning electron microscope (SEM) image.

Abstract: A method and an apparatus for filling a gap by using an atomic layer deposition (ALD) method are provided. The method includes forming a first reaction inhibition layer by adsorbing a reaction inhibitor onto a side wall of the gap, forming a first precursor layer by adsorbing a first reactant onto the bottom of the gap and the side wall of the gap around the bottom of the gap, and forming a first atomic layer on the bottom of the gap and the side wall of the gap around the bottom of the gap. The reaction inhibitor includes a precursor material that does not react with a second reactant. The first reaction inhibition layer may have a density gradient in which a density of the reaction inhibitor decreases toward a bottom of the gap. The forming the first atomic layer includes adsorbing the second reactant onto the first precursor layer.