Abstract: A computing device of predicting potential predicting potential defect-inducing factors within a semiconductor layout is provided. The computing device comprising: a machine learning module, calculating predicted measurement data corresponding to at least one first semiconductor layout image among a plurality of semiconductor layout mages after being trained based on the plurality of semiconductor layout images and corresponding real measurement data and an image explanation module generating an attribution map image of the predicted measurement data based on an image regression model utilizing an integrated gradient (IG) manner, analyzing the attribution map image and detecting elements within the attribution map image with attribution values with high sensitivity to the predicted measurement data as potential defect-inducing factors in advance.

Abstract: Provided are an ECM mimetic microcarrier comprising a positively charged recombinant adhesive protein genetically functionalized with a heparin binding motif which is capable of binding or sequestering growth factors and a negatively charged component, wherein the ECM mimetic microcarrier may be in the form of a mussel adhesive protein where extracellular matrix (ECM) protein derived integrin binding peptide motifs and GF binding peptide motifs are recombinantly incorporated into the mussel adhesive protein, and a use of the ECM mimetic microcarrier for stem cell expansion application.

Abstract: The vehicular wheel bearing includes a wheel hub; at least one inner ring; an outer ring; a plurality of rolling elements; an inboard-side sealing member; and an outboard-side sealing. The outboard-side sealing member includes a frame press-fitted to the outer ring and an elastic sealing part integrally attached to the frame. The frame includes a press-fitting part and a flange part bent and extending from the press-fitting part. The elastic sealing part includes a base part with which all or a part of the frame is covered, one or more of sealing lips formed to extend from the base part, an overmold part extending beyond an inner axial end portion of the press-fitting part of the frame and is mounted in close contact with an outer circumferential surface of the outer ring, and the overmold part is axially spaced apart from the press-fitting surface of the press-fitting part.

Abstract: Provided is a vaccine composition for preventing respiratory syncytial virus (RSV) infection, which is in the form of a liposome formulation including a RSV antigen, monophosphoryl lipid A (MLA), and/or a cobalt-porphyrin-phospholipid (CoPoP) conjugate. The vaccine composition exhibits excellent vaccine efficacy from a RSV antigen with enhanced immunogenicity and a combination of immune adjuvants for enhancing immune activity and antigen presentation.

Abstract: The present invention relates to novel fragments of AIMP1 protein and a composition for improving alopecia and promoting hair growth comprising the same, more specifically it relates to a polypeptide consisting of 4 to 21 consecutive amino acids from the amino acid sequence of SEQ ID NO: 1, wherein the polypeptide comprises the 28th to 31st amino acid residue (KEKA) of amino acid sequence of SEQ ID NO: 1, or a polypeptide consisting of an amino acid sequence having 70% or more sequence homology with the polypeptide; a polynucleotide encoding the polypeptide; a pharmaceutical, cosmetic and food composition for improving alopecia and promoting hair growth comprising the polypeptide.

Abstract: Provided is a simulation method performed by a process simulator, implemented with a recurrent neural network (RNN) including a plurality of process emulation cells, which are arranged in time series and configured to train and predict, based on a final target profile, a profile of each process step included in a semiconductor manufacturing process. The simulation method includes: receiving, at a first process emulation cell, a previous output profile provided at a previous process step, a target profile and process condition information of a current process step; and generating, at the first process emulation cell, a current output profile corresponding to the current process step, based on the target profile, the process condition information, and prior knowledge information, the prior knowledge information defining a time series causal relationship between the previous process step and the current process step.

Abstract: The present invention relates to novel fragments of AIMP1 protein and a composition for improving alopecia and promoting hair growth comprising the same, more specifically it relates to a polypeptide consisting of 4 to 21 consecutive amino acids from the amino acid sequence of SEQ ID NO: 1, wherein the polypeptide comprises the 28th to 31st amino acid residue (KEKA) of amino acid sequence of SEQ ID NO: 1, or a polypeptide consisting of an amino acid sequence having 70% or more sequence homology with the polypeptide; a polynucleotide encoding the polypeptide; a pharmaceutical, cosmetic and food composition for improving alopecia and promoting hair growth comprising the polypeptide.

Abstract: Protein substrates are provided comprising integrin binding motif and growth factor (GF) binding peptide motif that enable binding to and activation of both a growth factor receptor and an integrin, simultaneously or selectively. The substrate proteins may be in the form of a mussel adhesive protein where extracellular matrix (ECM) protein derived integrin binding peptide motifs and GF binding peptide motifs are recombinantly incorporated into the mussel adhesive protein. Also provided are use of the protein substrate for regulating cellular behavior including cell adhesion, migration, or proliferation which are essential process in bioprocess, wound healing, tissue engineering, and therapeutic application. In other embodiments, the present invention provides a method and composition of stabilizing and protecting a growth factor from protease digestion or internalization into cells (or cellular uptake) in order to maintain the persistent and durable function of growth factors.

Abstract: A method for analyzing a wafer map using a wafer map analyzer includes generating first wafer maps each displaying characteristics of a first wafer for a corresponding channel of a plurality of channels. The first wafer maps are auto-encoded together to extract a first feature. The method also includes determining whether the first feature is a valid pattern, classifying the type of the first feature based on unsupervised learning when the first feature is a valid pattern and extracting a representative image of features classified into the same type as the first feature.

Abstract: A semiconductor wafer fault analysis system includes: a database to store a first reference map, which is classified as a first fault type, and a second reference map, which is classified as a second fault type; a first auto-encoder/decoder to remove a noise corresponding to the first fault type from the first reference map to generate a first pre-processed reference map; a second auto-encoder/decoder to remove a noise corresponding to the second fault type from the second reference map to generate a second pre-processed reference map; and a fault type analyzer. The database is updated based on the first and second pre-processed reference maps, and the fault type analyzer is to classify a fault type of a target map based on the updated database. The target map is generated by measuring a target wafer.

Abstract: The present invention relates to novel polypeptides having a skin whitening activity and use thereof. More particularly, the present invention relates to an isolated polypeptide consisting (essentially) of any one amino acid sequence selected from the group consisting of SEQ ID NO: 1, SEQ ID NO: 3, SEQ ID NO: 5, and SEQ ID NO: 7, a skin whitening cosmetic composition comprising the polypeptide as an active ingredient, or a pharmaceutical composition for preventing or treating a pigmentation disease.

Abstract: A method for analyzing a wafer map using a wafer map analyzer includes generating first wafer maps each displaying characteristics of a first wafer for a corresponding channel of a plurality of channels. The first wafer maps are auto-encoded together to extract a first feature. The method also includes determining whether the first feature is a valid pattern, classifying the type of the first feature based on unsupervised learning when the first feature is a valid pattern and extracting a representative image of features classified into the same type as the first feature.

Abstract: Provided is a simulation method performed by a process simulator, implemented with a recurrent neural network (RNN) including a plurality of process emulation cells, which are arranged in time series and configured to train and predict, based on a final target profile, a profile of each process step included in a semiconductor manufacturing process. The simulation method includes: receiving, at a first process emulation cell, a previous output profile provided at a previous process step, a target profile and process condition information of a current process step; and generating, at the first process emulation cell, a current output profile corresponding to the current process step, based on the target profile, the process condition information, and prior knowledge information, the prior knowledge information defining a time series causal relationship between the previous process step and the current process step.

Abstract: Provided are a surfactant adhesive protein comprising an amphiphilic peptide, as a surfactant adhesive protein, at the carbon or amine terminal, a silicone oil and an anticancer composition comprising the surfactant adhesive, where the surfactant adhesive enables homogeneous dispersion of hydrophilic or hydrophobic particles in a hydrophobic or hydrophilic solvent on the basis of strong adhesive strength of the mussel adhesive protein, and the surface adhesive can be favorably used as a surface coating agent requiring antibacterial or antiviral functions as well as a cosmetic product or an ink.

Abstract: Provided is a simulation method performed by a process simulator, implemented with a recurrent neural network (RNN) including a plurality of process emulation cells, which are arranged in time series and configured to train and predict, based on a final target profile, a profile of each process step included in a semiconductor manufacturing process. The simulation method includes: receiving, at a first process emulation cell, a previous output profile provided at a previous process step, a target profile and process condition information of a current process step; and generating, at the first process emulation cell, a current output profile corresponding to the current process step, based on the target profile, the process condition information, and prior knowledge information, the prior knowledge information defining a time series causal relationship between the previous process step and the current process step.

Abstract: A method for detecting defects in a semiconductor device includes pre-training a pre-trained convolutional neural network (CNN) model using a sampled clean data set extracted from a first data set; training a normal convolutional neural network model and a label-noise convolutional neural network model using first data of the first data set and the pre-trained convolutional neural network model. The method also includes outputting a first prediction result on whether second data of a second data set is good or bad using the second data and the normal convolutional neural network model; and outputting a second prediction result on whether second data is good or bad using the second data and the label-noise convolutional neural network model. The first prediction result is compared with the second prediction result to perform noise correction when there is a label difference. Third data created as results of the noise correction is added to the sampled clean data set.

Abstract: The present invention relates to an antibody specifically binding to a tryptophanyl-tRNA synthetase (WRS) protein and, more specifically, to: an antibody, or a fragment of the antibody, specifically binding to a polypeptide of an amino acid sequence represented by SEQ ID NO: 2 in a WRS protein; a polynucleotide encoding the antibody and a vector comprising same; a cell transformed using same; and a use thereof.

Abstract: The present invention relates to an antibody specifically binding to a WRS (tryptophanyl-tRNA synthetase) protein, and a use thereof. More specifically, the present invention pertains to an antibody specifically binding to a polypeptide of an amino acid sequence represented by SEQ ID NO:2 in the WRS (tryptophanyl-tRNA synthetase) protein, or a fragment of the antibody, a polynucleotide encoding the antibody, a vector comprising the polynucleotide, a cell transformed using the vector, and a use of the cell.

Abstract: The present invention relates to a colorectal cancer diagnostic composition and method for detecting a diagnostic marker, more specifically to a colorectal cancer diagnostic composition comprising one or more mRNAs selected from the group consisting of lysyl-tRNA synthetase (KRS) and aminoacyl-tRNA synthetase complex-interacting multifunctional protein 1 (AIMP1) of a preparation for measuring protein expression levels thereof, and a method for detecting a marker form a sample obtained from a test subject in order to provide information necessary for diagnosing colorectal cancer. The colorectal cancer diagnostic marker comprising KRS and AIMP1, according to the present invention, has raised expression levels of same in the serum of a colorectal cancer patient in comparison to a normal control group. Therefore, whether colorectal cancer is present can be accurately and rapidly determined by measuring the expression levels of one or more markers selected from the group consisting of KRS and AIMP1.

Abstract: The present invention relates to novel fragments of AIMP1 protein and a composition for improving alopecia and promoting hair growth comprising the same, more specifically it relates to a polypeptide consisting of 4 to 21 consecutive amino acids from the amino acid sequence of SEQ ID NO: 1, wherein the polypeptide comprises the 28th to 31st amino acid residue (KEKA) of amino acid sequence of SEQ ID NO: 1, or a polypeptide consisting of an amino acid sequence having 70% or more sequence homology with the polypeptide; a polynucleotide encoding the polypeptide; a pharmaceutical, cosmetic and food composition for improving alopecia and promoting hair growth comprising the polypeptide.