Abstract: An effective strategy provides an intuitive starting point for an enterprise network agent to resolve issues before the issues increase the probability of an outage. Being able to predict whether and when a current anomalous state will transform into an outage is valuable to an enterprise network agent tasked with network administration, including monitoring the network; configuring the network; recommending software or hardware licenses, updates, or additions; obtaining software or hardware licenses or devices; generating reports and alerts; and launching countermeasures in association with the enterprise network.

Abstract: The present disclosure provides a robust and effective solution to an entity or an organization by enabling the entity to implement a system for 3D vision, and synthetic data generation of a retail product model. Further, the present disclosure aims at generating high-quality, photorealistic, large-scale domain-specific synthetic data. The system is equipped with synthetic simulation, digital twin creation, and synthetic data generation with automated annotations. Additionally, the system allows the training of artificial intelligence to reduce manual efforts and to facilitate the automation and personalization.

Abstract: The present invention provides solution to the above-mentioned problem in the art by providing a system and a method for an efficient and adaptive disease prediction system as a part of an expert-based online AI symptom-checker. The system may diagnose a wide variety of diseases accurately in an under 3-minute chatbot based conversation. The system architecture comprises of state-based components namely dialogue, patient, utterance, disease and symptom state. The disease prediction module may use a complex knowledge graph coupled with the state information to predict disease scores, predict disease scores based on various factors such as symptom coverage, relative disease importance, diseases priors, risk factors, lab tests, body organs and body systems and further provide mechanisms to arrive at a convergence based on factors such as confidence scores, questions asked and the like.

Abstract: An IC device may include a CMOS layer and memory layers at the frontside and backside of the CMOS layer. The CMOS layer may include one or more logic circuits with MOSFET transistors. The CMOS layer may also include memory cells, e.g., SRAM cells. A memory layer may include one or more memory arrays. A memory array may include memory cells (e.g., DRAM cells), bit lines, and word lines. A logic circuit in the CMOS layer may control access to the memory cells. A memory layer may be bonded with the CMOS layer through a bonding layer that includes conductive structures coupled to a logic circuit in the CMOS layer or to bit lines or word lines in the memory layer. An additional conductive structure may be at the backside of a MOSFET transistor in the CMOS layer and coupled to a conductive structure in the bonding layer.

Abstract: Encrypted poll responses from a group of users are validated homomorphically in an online polling system. Mathematical operations are performed on encrypted poll responses to produce validated encrypted results. The operations, when applied to plaintext of the encrypted poll response, normalize the plaintext when the poll response is valid, and nullify the plaintext when the poll response is invalid. The validated encrypted poll responses can be analyzed, without decryption, to provide a variety of results in encrypted format. The analysis may include summing the validated poll responses to produce a tally and may also be analyzed in accordance with associated cleartext metadata. Multiple sets of encrypted poll responses to multiple poll queries can be analyzed to determine relationships with respect to each other, in encrypted form, as well as in conjunction with cleartext parameters.

Abstract: Example embodiments relate to devices, systems, and methods involving three-dimensional time-of-flight/visible image sensors. An example embodiment includes a device that includes a plurality of time of flight sensor (ToF) pixels and a plurality of visible image sensor (VIS) pixels. The device also includes a ToF communication channel configured to provide ToF image data indicative of one or more ToF pixels and a VIS communication channel configured to provide VIS image data indicative of one or more VIS pixels. The plurality of ToF pixels and the plurality of VIS pixels are arranged along a plane. The plurality of ToF pixels is disposed in an arrangement among the plurality of VIS pixels.

Abstract: Present disclosure generally relates to location tracking and communication systems. More particularly, the present disclosure relates to systems and methods for predicting user location from radio data of telecommunication network. The system may utilize Global Positioning System (GPS) data along with Radio Frequency (RF) data obtained from interactions between the first computing device and network elements such as cells. The RF data along with the GPS data may be used for learned distance prediction models in AI engine. When the first computing device may be latched to a cell, the system via the first computing device can observe one or more neighbour cells. To estimate location of the user, predicted distances from cells and grids that can be served from each of cells may be used by system to estimate location of the user. System may use predicted distance from different cells to estimate the location of the user.

Abstract: The present invention provides solution to the above-mentioned problem in the art by providing a system and a method for efficiently identifying from a medical domain a plurality of entities that may be designed and engineered for a diagnostic reasoning system or symptom checker. The identified plurality of entities forms nodes of a knowledge graph and may be interconnected to each other with edges representing finely curated weights. The curated weights may form a dynamic repository that can constantly evolves to best reflect the latest medical knowledge. Apart from diseases and symptoms, the system is also capable of extending and scaling to other dimensions of medical knowledge. The knowledge graph thus developed is fundamental to the entire diagnostic system and is used by various components of the diagnostic engine to power the AI-based reasoning.

Abstract: Present disclosure generally relates to computer-assisted medical diagnosis systems, particularly, to system and method for generating adaptive medical queries to determine disease symptoms of a user. System receives inputs from user, in response to queries corresponding to symptoms of disease. Further, system extracts contextual attributes corresponding to medical context, from inputs and identifies batch-wise candidate attributes from extracted contextual attributes, and sorts batch-wise candidate attributes corresponding to each of symptoms. Furthermore, system maps symptoms in sorted batch-wise candidate attributes to disease, by searching medical knowledge database, and calculates disease-symptom weighted score. Additionally, system filters symptoms based on age and gender of user, and sorts symptoms based on calculated disease-symptom weighed score and inter-dependency on other attributes.

Abstract: An effective strategy provides an intuitive starting point for an enterprise network agent to resolve issues before the issues increase the probability of an outage. Being able to predict whether and when a current anomalous state will transform into an outage is valuable to an enterprise network agent tasked with network administration, including monitoring the network; configuring the network; recommending software or hardware licenses, updates, or additions; obtaining software or hardware licenses or devices; generating reports and alerts; and launching countermeasures in association with the enterprise network.

Abstract: The present invention provides a robust and effective solution to an entity or an organization by enabling them to implement a system for facilitating creation of a digital twin of a process unit which can perform constrained optimization of control parameters to minimize or maximize an objective function. The system can capture non-linearities of the industrial process while the current Industrial Process models try to approximate non-linear process using linear approximation, which are not as accurate as Neural Networks. The proposed system can further create an end-to-end differentiable digital twin model of a process unit, and uses gradient flows for optimization as compared to other digital twin models that are gradient-free.

Abstract: Example embodiments relate to reducing auto-exposure latency. An example embodiment includes a method of reducing auto-exposure latency. The method includes determining, by a processor, a first setting of an exposure parameter for a first frame to be captured by an image sensor. The first setting of the exposure parameter is determined based at least in part on characteristics of a previous frame captured by the image sensor. The first setting of the exposure parameter is determined during a first frame period associated with capturing the first frame. The method also includes initiating, by the processor, a first frame exposure operation based on the first setting of the exposure parameter. During the first frame exposure operation, the image sensor captures the first frame during the first frame period.

Abstract: This present disclosure proposes a system and method for providing a 3D computer vision-assisted frictionless self-checkout experience in a traditional retail store by using two RGB-D camera sensors and a conveyer belt. The disclosure provides a self-checkout counter (106) that enables a customer (102) to go through a self-service checkout process by simply placing the collected products one by one on a conveyer belt. One vertical and another horizontal RGB-D sensor (108) mounted in a housing frame attached towards the end of the conveyer belt capture RGB and depth image of each product passing through the housing and pass it to a product recognition engine (216). The engine (216) identifies the unique product along with its volumetric attributes processing the RGB-D data that is further compared with a master product database and processed for invoicing.

Abstract: Described are methods and systems that watermark text files in document or image formats using efficient encoding schemes. A unique identifier is encoded into a document by perturbing typographical properties of document elements, such as the lengths and widths of words, lines, or spaces, to encode multiple bits per element. Perturbations to the rendered dimensions of elements create patterns, digital watermarks, that can be decoded to recover the unique identifier, which can in turn be used to identify a user who disclosed or was otherwise responsible for a leaked document.

Abstract: A method and system for time series forecasting are described. Forecasting a time series, though uncertain, has a potential to improve decision-making. It gives a picture of what can probably be expected. A live time series typically has trend and seasonality as its innate characteristic features, randomness being obvious in real-time. Described embodiments address complexity in configuring zero-configuration workflow forecasting methods at production scale. Described embodiments address complexity in configurating domain independent forecasting methods at production scale.

Abstract: Obtaining one or more metrics associated with a network location. Determining, based on the one or more metrics and one or more prefatory check conditions, a prefatory status of the network location, the prefatory status indicating a benign status, malicious status, or a suspicious status. If the prefatory status of the network location indicates the benign status or the malicious status, providing a notification of the prefatory status in response to the prefatory status being determined. If the prefatory status of the network location indicates a suspicious status, obtaining a document object model of the network location. Obtaining a screenshot of an entire page of content at the network location. Generating a null hypothesis based on the document object model, the null hypothesis including a potential brand list, the potential brand list including one or more potential brands. Obtaining a set of reference images for each of the one or more potential brands of the potential brand list.

Abstract: Disclosed are techniques for integrated circuits (ICs). In an aspect, an IC package includes a package substrate having an upper surface, a lower surface, a first side, and a second side perpendicular to the first side. The package substrate includes a metallization structure. The IC package further includes an IC die attached to the upper surface of the package substrate; first package bumps on the lower surface of the package substrate; and second package bumps on the lower surface of the package substrate. The first package bumps are arranged adjacent to one another along a diagonal direction that is diagonal to the package substrate, and the second package bumps are arranged adjacent to one another along the diagonal direction.

Abstract: A method and system for time series forecasting are described. Forecasting a time series, though uncertain, has a potential to improve decision-making. It gives a picture of what can probably be expected. A live time series typically has trend and seasonality as its innate characteristic features, randomness being obvious in real-time. Described embodiments address complexity in configuring zero-configuration workflow forecasting methods at production scale. Described embodiments address complexity in configurating domain independent forecasting methods at production scale.

Abstract: The present disclosure relates to devices, light detection and ranging (lidar) systems, and vehicles involving solid-state, single photon detectors. An example device includes a substrate defining a primary plane and a plurality of photodetector cells disposed along the primary plane. The plurality of photodetector cells includes at least one large-area cell and at least one small-area cell. The large-area cell has a first area and the small-area cell has a second area and the first area is greater than the second area. The device also includes read out circuitry coupled to the plurality of photodetector cells. The read out circuitry is configured to provide an output signal based on incident light detected by the plurality of photodetector cells.

Abstract: The present invention provides a method and system for predicting tropospheric interference using a digital twin model for detecting tropospheric interference and suggesting actions for mitigating the effects of the tropospheric interference. The system (110) may include a machine learning engine (216) having a digital twin model to predict/score the likelihood of cell pairs having the tropospheric interference at a given point of time using cell configuration data, weather data, Hepburn data at that point of time by identifying cell pairs whose likelihood of interference is high. The system (110) is further configured to explore the effect of changing cell configuration parameters like remote electrical tilt and identify actions that can mitigate tropospheric interference with minimal impact on coverage.