Abstract: Various embodiments of the disclosure relate to an apparatus for supporting automatic speech recognition in an electronic device capable of performing natural language processing, and an operating method thereof. To this end, based on one or more partial texts recognized sequentially from an audio signal input from a microphone, the electronic device may identify an utterance type for the input audio signal. The electronic device may adaptively determine a hangover time, based on the utterance type, and may detect an end of an utterance of the audio signal by applying the determined hangover time.

Abstract: A method and device with defect detection are included. In one general aspect, a method performed by an electronic device includes determining, by the electronic device, an operation mode among different operation modes, wherein the electronic device is configured to implement the operation modes for determining wafer defects by processing semiconductor wafer images, and determining, by the electronic device, based on an indication of the determined operation mode, whether a semiconductor image, among the semiconductor wafer images, is defective.

Abstract: Embodiments herein disclose a method for identifying co-evolving sites and and at least one substituent amino acid residue. The method includes obtaining a current state of a protein and an ancestral state of the protein. Further, the method includes determining at least one amino acid substitution along with at least one co-evolving site associated with the protein based on the current state of the protein and the ancestral state of the protein. Further, the method includes assessing the at least one amino acid substitution as a function of a nucleotide substitution in the protein. Further, the method includes assessing at least one co-evolving site substitution based on the at least one assessed amino acid substitution. Further, the method includes identifying the co-evolving sites and at least one substituent amino acid residue.

Abstract: Methods and systems for annotating regulatory regions of a microbial genome. A method disclosed herein includes extracting data related to at least one promoter of the regulatory regions of the microbial genome, wherein the data includes at least one promoter sequence and data available for at least one promoter subtype. Based on extracted at least one feature of the at least one promoter sequence, the method further includes configuring at least one predictive model using the deep learning based neural network to predict the at least one promoter subtype associated with the at least one promoter sequence. The method further includes annotating at least one unknown promoter sequence into the at least one promoter subtype using the at least one configured predictive model.

Abstract: A method for predicting a change in a functional property of a biomolecule includes obtaining a plurality of biomolecules and mutation data associated with at least one functional property; determining a net change in the at least one functional property based on at least one parameter associated with the mutation data for each biomolecule at a site; encoding a plurality of sequenced features for the mutation data associated with each biomolecule; configuring a prediction model to detect a relationship of the sequence features and the net change in the at least one functional property of the mutation data associated with each biomolecule; and predicting a change in the at least one functional property of a target biomolecule based on the prediction model for the mutation data at a user specified site.