Abstract: A method for optimizing a UI of an application in an electronic device is provided. The method includes detecting, by the electronic device, at least one first application installed in the electronic device, determining, by the electronic device, at least one data item associated with at least one UI of the at least one first application to be modified, modifying, by the electronic device, the at least one data item associated with the at least one UI of the at least one first application based on a level of proficiency of a user with an already used application in the electronic device, and displaying, by the electronic device, the at least one UI with the at least one modified data item of the at least one first application.

Abstract: A computerized method for providing a sentiment score by evaluating expressions of participants during a video meeting is provided herein. The computerized method comprising: a Sentiment Analysis (SA) module. The SA module is: (i) retrieving one or more recordings of a video meeting from the database of video meeting recordings of each participant in the video meeting and associating the one or more recordings with a participant; (ii) dividing each retrieved recording into segments; (iii) processing the segments in a Facial Expression Recognition (FER) system to associate each segment with a timestamped sequence of expressions for each participant in the video meeting; and (iv) processing each segment in an Artificial Neural Network (ANN) having a dense layer, by applying a prebuilt and pretrained deep learning model, to yield a sentiment score for each statement for each participant.

Abstract: A computerized method for providing a sentiment score by evaluating expressions of participants during a video meeting is provided herein. The computerized method comprising: a Sentiment Analysis (SA) module. The SA module is: (i) retrieving one or more recordings of a video meeting from the database of video meeting recordings of each participant in the video meeting and associating the one or more recordings with a participant; (ii) dividing each retrieved recording into segments; (iii) processing the segments in a Facial Expression Recognition (FER) system to associate each segment with a timestamped sequence of expressions for each participant in the video meeting; and (iv) processing each segment in an Artificial Neural Network (ANN) having a dense layer, by applying a prebuilt and pretrained deep learning model, to yield a sentiment score for each statement for each participant.

Abstract: A computerized method for providing a sentiment score by evaluating expressions of participants during a video meeting is provided herein. The computerized method comprising: a Sentiment Analysis (SA) module. The SA module is: (i) retrieving one or more recordings of a video meeting from the database of video meeting recordings of each participant in the video meeting and associating the one or more recordings with a participant; (ii) dividing each retrieved recording into segments; (iii) processing the segments in a Facial Expression Recognition (FER) system to associate each segment with a timestamped sequence of expressions for each participant in the video meeting; and (iv) processing each segment in an Artificial Neural Network (ANN) having a dense layer, by applying a prebuilt and pretrained deep learning model, to yield a sentiment score for each statement for each participant.

Abstract: A method for optimizing a UI of an application in an electronic device is provided. The method includes detecting, by the electronic device, at least one first application installed in the electronic device, determining, by the electronic device, at least one data item associated with at least one UI of the at least one first application to be modified, modifying, by the electronic device, the at least one data item associated with the at least one UI of the at least one first application based on a level of proficiency of a user with an already used application in the electronic device, and displaying, by the electronic device, the at least one UI with the at least one modified data item of the at least one first application.

Abstract: A computerized method for providing a sentiment score by evaluating expressions of participants during a video meeting is provided herein. The computerized method comprising: a Sentiment Analysis (SA) module. The SA module is: (i) retrieving one or more recordings of a video meeting from the database of video meeting recordings of each participant in the video meeting and associating the one or more recordings with a participant; (ii) dividing each retrieved recording into segments; (iii) processing the segments in a Facial Expression Recognition (FER) system to associate each segment with a timestamped sequence of expressions for each participant in the video meeting; and (iv) processing each segment in an Artificial Neural Network (ANN) having a dense layer, by applying a prebuilt and pretrained deep learning model, to yield a sentiment score for each statement for each participant.

Abstract: Disclosed herein is an improved process for the preparation of Lurasidone and its pharmaceutically acceptable salts via novel intermediate and use thereof for the preparation of an antipsychotic agent useful for the treatment of schizophrenia and bipolar disorder. Further, present invention provides a cost effective and eco-friendly process for producing Lurasidone hydrochloride of formula (I) substantially free of residual solvent(s) at industrial scale.

Abstract: Disclosed herein is an improved process for the preparation of Lurasidone and its pharmaceutically acceptable salts via novel intermediate and use thereof for the preparation of an antipsychotic agent useful for the treatment of schizophrenia and bipolar disorder. Further, present invention provides a cost effective and eco-friendly process for producing Lurasidone hydrochloride of formula (I) substantially free of residual solvent(s) at industrial scale.