Abstract: A refrigeration system and a lubricating method thereof. The refrigeration system (100) includes: a compressor (110), a condenser (120), an evaporator (130), and a lubrication circuit (200), the lubrication circuit including a post-lubrication flow path (230,240,260) connected from the compressor into the condenser and the evaporator respectively; and a pre-lubrication flow path (210,220,250) connected from the condenser and the evaporator into the compressor respectively; wherein after flowing from the condenser via the pre-lubrication flow path to the compressor for lubrication, a part of refrigerant for lubrication can flow back to the evaporator via the post-lubrication flow path; or after flowing from the evaporator via the pre-lubrication flow path to the compressor for lubrication, the part of refrigerant for lubrication can flow back to the condenser via the post-lubrication flow path.

Abstract: An optical system may include a light source to provide a beam of light. The optical system may include a reflector to receive and redirect the beam of light. The optical system may include a light gate having an opening to permit the beam of light, from the reflector, to travel through the opening. The optical system may include a light sensor to receive a portion of the beam of light after the beam of light travels through the opening, and convert the portion of the beam of light to a signal. The optical system may include a processing device to determine whether a notch of a wafer is in an allowable position based on the signal.

Abstract: A computer-implemented framework and/or system for cyberbullying detection is disclosed. The system includes two main components: (1) A representation learning network that encodes the social media session by exploiting multi-modal features, e.g., text, network, and time; and (2) a multi-task learning network that simultaneously fits the comment inter-arrival times and estimates the bullying likelihood based on a Gaussian Mixture Model. The system jointly optimizes the parameters of both components to overcome the shortcomings of decoupled training. The system includes an unsupervised cyberbullying detection model that not only experimentally outperforms the state-of-the-art unsupervised models, but also achieves competitive performance compared to supervised models.

Abstract: This document relates to training of machine learning models. One example method involves providing a machine learning model having a first classification layer, a second classification layer, and an encoder that feeds into the first classification layer and the second classification layer. The example method also involves obtaining first training examples having explicit labels and second training examples having inferred labels. The inferred labels are based at least on actions associated with the second training examples. The example method also involves training the machine learning model using the first training examples and the second training examples using a training objective that considers first training loss of the first classification layer for the explicit labels and second training loss of the second classification layer for the inferred labels. The method also involves outputting a trained machine learning model having the encoder and the first classification layer.

Abstract: Various embodiments of systems and methods for cross media joint friend and item recommendations are disclosed herein.

Abstract: This document relates to training of machine learning models. One example method involves providing a machine learning model having a first classification layer, a second classification layer, and an encoder that feeds into the first classification layer and the second classification layer. The example method also involves obtaining first training examples having explicit labels and second training examples having inferred labels. The inferred labels are based at least on actions associated with the second training examples. The example method also involves training the machine learning model using the first training examples and the second training examples using a training objective that considers first training loss of the first classification layer for the explicit labels and second training loss of the second classification layer for the inferred labels. The method also involves outputting a trained machine learning model having the encoder and the first classification layer.

Abstract: Various embodiments of a computer-implemented system which learns textual representations while filtering out potentially personally identifying data and retaining semantic meaning within the textual representations are disclosed herein.

Abstract: Various embodiments of systems and methods for cross media joint friend and item recommendations are disclosed herein.

Abstract: Detecting fake news involves analyzing a distribution of publishers who publish many news articles, analyzing a distribution of various topics relating to the published news articles, analyzing a social media context relating to the published news articles, and detecting fake news articles among the news articles based on the analysis of the distribution of publishers, the analysis of the distribution of the various topics, and the analysis of the social media context.

Abstract: A computer-implemented framework and/or system for cyberbullying detection is disclosed. The system includes two main components: (1) A representation learning network that encodes the social media session by exploiting multi-modal features, e.g., text, network, and time; and (2) a multi-task learning network that simultaneously fits the comment inter-arrival times and estimates the bullying likelihood based on a Gaussian Mixture Model. The system jointly optimizes the parameters of both components to overcome the shortcomings of decoupled training. The system includes an unsupervised cyberbullying detection model that not only experimentally outperforms the state-of-the-art unsupervised models, but also achieves competitive performance compared to supervised models.

Abstract: A news article may include sentences and have associated comments. A embodiment determines semantic correlation between each sentence and each comment to generate correlation degrees between the sentences and the comments, determines sentence attention weights of the sentences and comment attention weights of the comments based on the correlation degrees, and detect whether the news article is fake based on latent representations of the sentences and the comments, the sentence attention weights and the comment attention weights. A list of sentences and a list of comments may be selected based on the sentence attention weights and the comment attention weights, respectively, to provide explanation for a detection result.

Abstract: This document relates to training of machine learning models. One example method involves providing a machine learning model having a first classification layer, a second classification layer, and an encoder that feeds into the first classification layer and the second classification layer. The example method also involves obtaining first training examples having explicit labels and second training examples having inferred labels. The inferred labels are based at least on actions associated with the second training examples. The example method also involves training the machine learning model using the first training examples and the second training examples using a training objective that considers first training loss of the first classification layer for the explicit labels and second training loss of the second classification layer for the inferred labels. The method also involves outputting a trained machine learning model having the encoder and the first classification layer.

Abstract: Various embodiments of a computer-implemented system which learns textual representations while filtering out potentially personally identifying data and retaining semantic meaning within the textual representations are disclosed herein.

Abstract: Detecting fake news involves receiving a plurality of allegedly real news stories and allegedly fake news stories from one or more websites, receiving a plurality of user posts to a social media platform relating to the plurality of allegedly real news stories and allegedly fake news stories; receiving a plurality of user engagements related to the plurality of user posts, receiving user profile information, and social media network information, for users creating the plurality of user posts to the social media platform, and users participating in the engagements related to the plurality of user posts, and classifying each of the received plurality of allegedly real news stories and allegedly fake news stories as one of a real news story and a fake news story based on the analyzed content and analyzed social media context.

Abstract: Various embodiments of systems and methods for cross media joint friend and item recommendations are disclosed herein.

Abstract: Detecting fake news involves analyzing a distribution of publishers who publish many news articles, analyzing a distribution of various topics relating to the published news articles, analyzing a social media context relating to the published news articles, and detecting fake news articles among the news articles based on the analysis of the distribution of publishers, the analysis of the distribution of the various topics, and the analysis of the social media context.

Abstract: This invention discloses a solution based synthesis of cesium tin tri-iodide (CsSnI3). More specifically, the CsSnI3 is fabricated in an organic Perovskite precursor solvent. CsSnI3 are ideally suited for a wide range of applications such as light emitting and photovoltaic devices.

Abstract: A driving device of a liquid crystal display (LCD) utilized for preventing noises of a clock signal from causing error operation of a shift register is disclosed. The driving device includes a shift register, a reception terminal, a noise elimination circuit and a control signal generation circuit. The reception terminal is utilized for receiving a first clock signal. The noise elimination circuit is coupled to the reception terminal, and is utilized for eliminating noises of the first clock signal and delaying the first clock signal for a preset time to generate a second clock signal. The control signal generation circuit is coupled to the reception terminal, the noise elimination circuit and the shift register, and is utilized for generating a first control signal and a second control signal to control the shift register.

Abstract: An all-digital clock generator includes a digitally-controlled clock generator and a processing unit. The digitally-controlled clock generator generates a clock signal in response to an enable signal and a digital signal. The processing unit has a frequency multiplier and a reference signal having a period, digitizes the period to generate a quantized signal, generates the digital signal according to the quantized signal and the frequency multiplier, and generates the enable signal according to the reference signal, the clock signal and the frequency multiplier.

Abstract: A biostimulative illumination apparatus for treating patient tissues includes at least one light emitting diode which can generate at least one narrow-pulse focused wave band suitable to be used as low-power and non-parallel focused light beams for biostimulative illumination. The wave length of the focused light beam is from 600 nm to 850 nm, the energy density of the focused light beams is from 2 Joule/cm' to 16 Joule/cm' and the divergence angle of the light beams is between 1° to 7° that includes 1°, 2°, 3°, 4°, 5°, 6° and 7°.