Abstract: The invention relates to method and system for enhancing computer network security. The method includes receiving a plurality of requests from client devices to avail a plurality of responses from services running on servers; determining a URL pattern for each of the plurality of requests based on URL associated with that request; determining a request data signature for each of the plurality of requests or a response data signature for each of the plurality of responses based on a set of request parameters associated with that request or based on a set of response parameters associated with that response, respectively, using a first machine learning model; and determining an authenticity of each of the plurality of requests based on the URL pattern and the data signature associated with that request, or an authenticity of each of the plurality of responses based on the data signature associated with that response.

Abstract: A method and system of providing assistance during an operation performed on an equipment by a smart assistance device. A first set of image frames and a second set of image frames corresponding to forward steps and reverse steps respectively performed during the operation are received from an imaging device. Parts of the equipment are detected in each of first set of image frames and tagged. The smart assistance device detects parts of the equipment present in an image frame for each of the second set of the image frames. A discrepancy is determined in the reverse steps by comparing the parts of the equipment present in the frame of the second set of the image frames with the parts tagged in the corresponding first image frame of the first set of image frames. A notification and recommendation is provided to correct the discrepancy.

Abstract: A method and system dynamically predicting driving range of vehicles is disclosed. In some embodiments, the method includes dynamically determining real-time values corresponding to in-transit parameters associated with vehicle; and determining, via trained Machine Learning (ML) model, variance in in-transit parameters when compared with pre-defined parameters. Determining the variance includes identifying overlapping subset of parameters between in-transit parameters and pre-defined parameters; identifying non-overlapping subset of parameters between in-transit parameters and pre-defined parameters; determining difference in each of the real-time values determined for overlapping subset of parameters with corresponding optimal value; and computing variance based on non-overlapping subset of parameters and difference in real-time values determined for the overlapping subset of parameters.

Abstract: A method and system of providing assistance during an operation performed on an equipment by a smart assistance device. A first set of image frames and a second set of image frames corresponding to forward steps and reverse steps respectively performed during the operation are received from an imaging device. Parts of the equipment are detected in each of first set of image frames and tagged. The smart assistance device detects parts of the equipment present in an image frame for each of the second set of the image frames. A discrepancy is determined in the reverse steps by comparing the parts of the equipment present in the frame of the second set of the image frames with the parts tagged in the corresponding first image frame of the first set of image frames. A notification and recommendation is provided to correct the discrepancy.

Abstract: The invention relates to method and system for enhancing computer network security. The method includes receiving a plurality of requests from client devices to avail a plurality of responses from services running on servers; determining a URL pattern for each of the plurality of requests based on URL associated with that request; determining a request data signature for each of the plurality of requests or a response data signature for each of the plurality of responses based on a set of request parameters associated with that request or based on a set of response parameters associated with that response, respectively, using a first machine learning model; and determining an authenticity of each of the plurality of requests based on the URL pattern and the data signature associated with that request, or an authenticity of each of the plurality of responses based on the data signature associated with that response.

Abstract: Disclosed is a system for delegating access of sensitive information by a user device to a requestor device through a central server. A receiving module receives a first token Identification (ID) generated by the user device in an offline mode and a request, comprising a second token ID, from the requestor device. A validation module validates the request by comparing the first token ID and the second token ID. An identification module identifies a subset of the sensitive information based on a profile of the requestor, when the first token ID is matched with the second token ID. A watermarking module watermarks the subset of the sensitive information with a set of variables to generate watermarked sensitive information. Upon generating the watermarked sensitive information, the access delegation module delegates the access of the watermarked sensitive information to the requestor device.

Abstract: Monitoring the use of motorized recreational vehicles and digitally verifying claims related to the use of motorized recreational vehicles including providing insurance for motorized recreational vehicles in response to an indication that the motorized recreational vehicles have entered a region requiring insurance

Abstract: Disclosed is a system for delegating access of sensitive information by a user device to a requestor device through a central server. A receiving module receives a first token Identification (ID) generated by the user device in an offline mode and a request, comprising a second token ID, from the requestor device. A validation module validates the request by comparing the first token ID and the second token ID. An identification module identifies a subset of the sensitive information based on a profile of the requestor, when the first token ID is matched with the second token ID. A watermarking module watermarks the subset of the sensitive information with a set of variables to generate watermarked sensitive information. Upon generating the watermarked sensitive information, the access delegation module delegates the access of the watermarked sensitive information to the requestor device.

Abstract: Ophthalmic composition for the correction of presbyopia. Composition consisting of 2% Pilocarpine, characterized by being diluted to 1% with sterile Balanced Salt Solution (BSS), obtaining 1% pilocarpine (2.5 ml)+bromfenac, 1.8 mgrs of bromfenac (2.5 ml)+sterile Balanced Salt Solution (BSS) (2.5 ml), finally obtaining eye drops of 7.5 ml. It is also possible to obtain a 1.5% and 2% pilocarpine.

Abstract: Ophthalmic composition for the correction of presbyopia. Composition consisting of 2% Pilocarpine, characterized by being diluted to 1% with sterile Balanced Salt Solution (BSS), obtaining 1% pilocarpine (2.5 ml)+bromfenac, 1.8 mgrs of bromfenac (2.5 ml)+sterile Balanced Salt Solution (BSS) (2.5 ml), finally obtaining eye drops of 7.5 ml. It is also possible to obtain a 1.5% and 2% pilocarpine.

Abstract: A method of preparing a frozen, batter-coated food product that eliminates pre-frying, which is the most problematic stage of the conventional industrial process for manufacturing frozen batter-coated food products. The food product is pre-dusted and a prepared batter is applied to the dusted food. The batter contains a cellulose derivative that enables the batter to coagulate in a hot water bath or in the presence of water vapor. The batter coating covering the food is coagulated in a hot water bath, the coagulated, batter-coated food is heated in a traditional, microwave or infrared oven so that the coagulated batter coating layer does not melt on cooling, and the product is then cooled and frozen.