Abstract: A silicon nitride (SiNx) based anode is produced by combining a silicon precursor that includes cyclohexasilane and a nitrogen precursor. A doped silicon based anode is produced by combining a silicon precursor that includes cyclohexasilane and a dopant precursor selected from a boron precursor, a nitrogen precursor, a sulfur precursor, an aluminum precursor, a phosphorous precursor, and combinations thereof. Silicon nanowires are produced by depositing metallic nanoparticles on surfaces of carbon support particles and then depositing silicon from cyclohexasilane onto the carbon support particles. The silicon preferentially deposits onto the metallic nanoparticles to form silicon nanowires that extend off of the metallic nanoparticle away from the surfaces.

Abstract: A surface-modified quantum dot includes a silicon quantum dot, a polycyclic dye moiety, and a linking moiety that bonds the polycyclic dye moiety to the silicon quantum dot.

Abstract: The present disclosure relates to methods of analyzing works of art for purposes of authentication or attribution. Such methods may be implemented by receiving digital image data associated with a work of art, identifying a plurality of artist's strokes formed along a surface of the work of art, segmenting the plurality of strokes into a plurality of individual strokes, analyzing the plurality of individual strokes to determine stroke characteristics, and comparing the stroke characteristics to stroke characteristics derived from one or more computational models based on known works of art.

Abstract: A method includes producing a substituted cyclosilane by combining in a solvent the following: (i) halogenated cyclosilane, (ii) at least one of tri-alkyl or tri-aryl silane, and (iii) a complexing agent that includes at least one of ammonium halide or phosphonium halide. The halogenated cyclosilane reacts to produce the substituted cyclosilane.

Abstract: A method and system for generating music uses artificial intelligence to analyze existing musical compositions and then creates a musical composition that deviates from the learned styles. Known musical compositions created by humans are presented in digitized form along with a style designator to a computer for analysis, including recognition of musical elements and association of particular styles. A music generator generates a draft musical composition for similar analysis by the computer. The computer ranks such draft musical composition for correlation with known musical elements and known styles. The music generator modifies the draft musical composition using an iterative process until the resulting musical composition is recognizable as music but is distinctive in style.

Abstract: A method and system for automatically generating a video stream synchronized with and reactive to an input audio stream uses one or more still or video images as a source of imagery. The system learns a latent representation of the source imagery and generates a visualization synchronized to, and reactive with, the input audio. A computer divides the audio stream into successive audio frames each characterized by a spectrogram. The computer generates a series of graphics of such latent representation according to the spectrogram of each audio frame. The computer pairs each audio frame with its corresponding graphic to generate an ordered series of graphics. The series of generated graphics can be displayed to accompany the audio in real-time or coupled with the audio stream to provide an audiovisual work that can be transmitted or digitally stored.

Abstract: The present disclosure relates to methods of analyzing works of art for purposes of authentication or attribution. Such methods may be implemented by receiving digital image data associated with a work of art, identifying a plurality of artist's strokes formed along a surface of the work of art, segmenting the plurality of strokes into a plurality of individual strokes, analyzing the plurality of individual strokes to determine stroke characteristics, and comparing the stroke characteristics to stroke characteristics derived from one or more computational models based on known works of art.

Abstract: The present disclosure relates to methods of analyzing works of art for purposes of authentication or attribution. Such methods may be implemented by receiving digital image data associated with a work of art, identifying a plurality of artist's strokes formed along a surface of the work of art, segmenting the plurality of strokes into a plurality of individual strokes, analyzing the plurality of individual strokes to determine stroke characteristics, and comparing the stroke characteristics to stroke characteristics derived from one or more computational models based on known works of art.

Abstract: A method and system for generating music uses artificial intelligence to analyze existing musical compositions and then creates a musical composition that deviates from the learned styles. Known musical compositions created by humans are presented in digitized form along with a style designator to a computer for analysis, including recognition of musical elements and association of particular styles. A music generator generates a draft musical composition for similar analysis by the computer. The computer ranks such draft musical composition for correlation with known musical elements and known styles. The music generator modifies the draft musical composition using an iterative process until the resulting musical composition is recognizable as music but is distinctive in style.

Abstract: A method and system for generating art uses artificial intelligence to analyze existing art forms and then creates art that deviates from the learned styles. Known art created by humans is presented in digitized form along with a style designator to a computer for analysis, including recognition of artistic elements and association of particular styles. A graphics processor generates a draft graphic image for similar analysis by the computer. The computer ranks such draft image for correlation with artistic elements and known styles. The graphics processor modifies the draft image using an iterative process until the resulting image is recognizable as art but is distinctive in style.

Abstract: A method and system for generating art uses artificial intelligence to analyze existing art forms and then creates art that deviates from the learned styles. Known art created by humans is presented in digitized form along with a style designator to a computer for analysis, including recognition of artistic elements and association of particular styles. A graphics processor generates a draft graphic image for similar analysis by the computer. The computer ranks such draft image for correlation with artistic elements and known styles. The graphics processor modifies the draft image using an iterative process until the resulting image is recognizable as art but is distinctive in style.

Abstract: The present disclosure relates to methods of analyzing works of art for purposes of authentication or attribution. Such methods may be implemented by receiving digital image data associated with a work of art, identifying a plurality of artist's strokes formed along a surface of the work of art, segmenting the plurality of strokes into a plurality of individual strokes, analyzing the plurality of individual strokes to determine stroke characteristics, and comparing the stroke characteristics to stroke characteristics derived from one or more computational models based on known works of art.

Abstract: This present disclosure describes a novel computational method for assessing fee creativity of human-generated and machine-generated creative products, such as paintings, sculptures, poetry, music, etc. The proposed computational method and algorithm is based on constructing a network between creative products and using this network to infer the originality arid influence of its nodes.

Abstract: A video conferencing system and method which automatically determines the appropriate preset camera parameters corresponding to participants participating in the video conference. A camera zooms out or pans the video conference space and looks for participants based on their faces. When a participant is detected, the preset camera parameters for that participant are calculated for when the center of the participant is in the center of the camera's view. This is continued for all the participants in the room. The optimal position for each participant and corresponding camera parameters are determined based on cultural preferences. Updates in the presets can be made periodically by the camera zooming out or panning the room. Multiple cameras can be used to continually update the presets.

Abstract: In order to detect a face disposed within a digital image, the pixels of the image are grouped based on whether they are skin color. The edges of the skin colored areas are removed by eliminating pixels that have surrounding pixels with a high variance in the luminance component. The resulting connected components are classified to determine whether they could include a face. The classification includes examining: the area of the bounding box of the component, the aspect ratio, the ratio of detected skin to the area of the bounding box, the orientation of elongated objects, and the distance between the center of the bounding box and the center of mass of the component. Components which are still considered facial candidates are mapped on to a graph. The minimum spanning trees of the graphs are extracted and the corresponding components which remain are again classified for whether they could include a face.

Abstract: In order to detect a face disposed within a digital image, the pixels of the image are grouped based on whether they are skin color. The edges of the skin colored areas are removed by eliminating pixels that have surrounding pixels with a high variance in the luminance component. The resulting connected components are classified to determine whether they could include a face. The classification includes examining: the area of the bounding box of the component, the aspect ratio, the ratio of detected skin to the area of the bounding box, the orientation of elongated objects, and the distance between the center of the bounding box and the center of mass of the component. Components which are still considered facial candidates are mapped on to a graph. The minimum spanning trees of the graphs are extracted and the corresponding components which remain are again classified for whether they could include a face.

Abstract: In order to detect a face disposed within a digital image, the pixels of the image are grouped based on whether they are skin color. The edges of the skin colored areas are removed by eliminating pixels that have surrounding pixels with a high variance in the luminance component. The resulting connected components are classified to determine whether they could include a face. The classification includes examining: the area of the bounding box of the component, the aspect ratio, the ratio of detected skin to the area of the bounding box, the orientation of elongated objects, and the distance between the center of the bounding box and the center of mass of the component. Components which are still considered facial candidates are mapped on to a graph. The minimum spanning trees of the graphs are extracted and the corresponding components which remain are again classified for whether they could include a face.