Abstract: A multidimensional knowledge transfer model for predicting CTR of a computational ad, the multidimensional knowledge transfer model comprises: a pre-processor for building an ad group node graph based on similarities among ad group nodes, an ad campaign node graph from merging the ad group node graph, and an ad account node graph from merging the ad campaign node graph. The multidimensional knowledge transfer model further comprises a multi-knowledge CTR prediction model for each of the ad account, ad campaign, and ad group layers. The multi-knowledge CTR prediction model predicts the respective node's CTR from the ad account node graph, ad campaign node graph, or ad group node graph, features of the audience group, and features of the node having its CTR predicted appended with the hidden vector of its parent node extracted from the upper layer multi-knowledge CTR prediction model.

Abstract: A 3D building model generator has a server that constructs a 3D texture model for each floor in a building by extruding a 2D floor plan to 3D using user-inputted heights, and adding photos captured by a smartphone or mobile device as textures to image planes for surfaces in the 3D model. The server displays on the smartphone a floor-plan portion, or a virtual 3D display based on the camera orientation with a facing wall highlighted and confirmed by a smartphone user. The user moves mapping points overlaid upon the photo to wall corners to map the photo to the facing surface in the model. The user flags rooms and exits such as doors and elevators as walkable. The server stacks the 3D texture model for the floors and connects them into a walkable network of the rooms and exits that are flagged as walkable. Hashing removes duplicate floorplans.

Abstract: A line-scanning three-dimensional sensing system measures a surface profile of an object. In the system, a dispersion optical module (DOM) performs a forward optical process of chromatically dispersing a polychromatic linear light beam into constituent narrowband linear light beams (CNLLBs) and focusing the CNLLBs on different focal planes to form a rainbow light pattern for illuminating a scanned surface of the object. The illuminated object displays an information-bearing color image (IBCI) containing height information of the scanned surface. The DOM captures the IBCI, and performs a backward optical process of optically condensing the captured IBCI to form an elongated light pattern. The backward optical process is an inverse of the forward one. A slit spatially filters the elongated light pattern to form an output light line. A height profile of the scanned surface is obtained by analyzing a spectral content at each point of the output light line.

Abstract: A method for detecting and tracking target object in a captured video using convolutional neural network (CNN) is provided. The method includes: inputting image data into a detecting model to generate detection results, wherein the detecting model is constructed by the CNN; inputting the image data into tracking models to generate tracking results; performing detection score enhancement operation according to the detection results and the tracking results to obtain enhanced detection results; matching the enhanced detection results and the tracking results by a matching operation; processing matched results and unmatched target detection results and unmatched target tracking results; and selectively updating the tracking models using tracking reliability estimation according to the matched results.

Abstract: A computer-implemented method for compliance checking related to goods in import supply chain logistics is provided, including: adding received legality data elements into a blockchain ledger corresponding to an importation of the goods; establishing a smart contract of the blockchain ledger; adding received sensing data elements corresponding to the smart contract into the blockchain ledger; adding electronic lock (e-Lock) status data corresponding to the smart contract into the blockchain ledger; and adding one or more inspection results corresponding to the smart contract into the blockchain ledger. Furthermore, determining, by the smart contract, whether the goods are within the compliance according to the received legality data elements, the received sensing data elements, the e-Lock status data and the one or more inspection results, wherein in response to determining that the goods are within the compliance, unsealing the e-Locks by sending a control signal to the e-Locks.

Abstract: A Hybrid TEE device allows a Trusted Execution Environment (TEE) by incorporating hardware comprising a Cache Purging Controller, a Memory Isolation Gateway, and a Memory Clean Up into a System on a Chip device, a general purpose computing device, or a special purpose or proprietary computing or electronic device. The addition of the hardware enables a method of protecting the Trusted Execution Environment and thus reducing vulnerability to malicious software or other program code.

Abstract: Described is a method and device for detecting a DTX state at a UCI receiver in a wireless communication system. The method comprises receiving a linear block encoded signal on an uplink at said UCI receiver and processing the received signal after resource element (RE) demapping to generate a soft bit sequence {right arrow over (s)}. The method includes selecting a plurality of bits in said generated soft bit sequence {right arrow over (s)} as comparison bits and comparing said selected comparison bits to corresponding bits in a reconstructed soft bit sequence {right arrow over (r)}. The reconstructed soft bit sequence {right arrow over (r)} is generated from a plurality of bits selected as reconstruction bits in said generated soft bit sequence {right arrow over (s)}.

Abstract: Described is a method of setting up a direct connection between edge sites on a 5G communications network. The method comprises: configuring 5G network functions (NFs) in the 5G communications network; configuring 5G NFs at the edge sites, if not already configured; and based on said configured NFs, setting up a direct tunnel between the edge sites according to a pre-defined tunnel policy.

Abstract: Systems and methods which provide for auditable data are described. Data management systems of embodiments facilitate storage and management of various data (e.g., information regarding transactions, customers, infrastructure, geographic locations, medical records, etc.) for supporting data creation, manipulation, storing, and/or sharing by and among different parties. Users may create new and/or update data, digitally sign the data, and store the digital signature and data on immutable storage using data structures of a data management system. A data structure in which data and associated metadata is stored on immutable storage in association with a digital signature corresponding to the data and user may be used in providing data traceability and auditability. Snapshots of merged data may be implemented with respect to data having many updates to avoid delays in merging update data for queries for that data. A collaborative rating mechanism may provide trust levels with respect to the data.

Abstract: Described is a method of calibrating a camera. The method comprises defining an area observed in a field of view (FOV) of the camera as a region of interest (ROI). The method includes selecting a plurality of physical reference points in said ROI and obtaining for each reference point physical position coordinates. The method also includes obtaining from said camera FOV or camera image data pixel locations for each point of reference and pairing each pixel location with the physical position coordinates of its respective reference point. Then, a relationship is derived from the paired pixel locations and physical position coordinates to enable a selected or identified pixel location in the camera FOV or camera image data to be transformed to physical position coordinates for a corresponding physical location in said ROI.

Abstract: The present invention provides a method and a system for remote imaging of explosive gases in an area. The method comprises: illuminating the area with a light source having a uniform light intensity distribution over an infrared wavelength range; acquiring images of the illuminated area with an image sensor through gas detection filters having bandpass central wavelength corresponding to absorption curves of target gases respectively; determining existence of the target gases based on the acquired images; predicting distribution of gas concertation for existing target gases respectively by using a non-linear prediction model; and constructing gas distribution images of the area based on the predicted distribution of gas concertation. The present invention can recognize different gases with overlapping absorption curves and provide more accurate prediction of gas concentrations.

Abstract: A method for classifying a glass object via acoustic analysis by a classifying apparatus is provided. The method including: receiving, by a processor, sound data of a knock sound generated by applying a knocking operation on the glass object; determining, by the processor, a type of the glass object by performing a knock-sound analysis to the sound data, wherein the type of the glass object includes an organic glass and an inorganic glass; if the type of the glass object is determined as the inorganic glass, receiving, by the processor, echo data of an echo induced by applying an ultrasonic-echo operation on the glass object; and determining, by the processor, a further type of the glass object by performing an echo-decay analysis to the echo data, wherein the further type of the glass object includes a crystal glass, a borosilicate glass and a soda-lime glass.

Abstract: Described is a method of controlling movement of a mobile robot in the event of a localization failure. The method comprises, on an occurrence of the localization failure, receiving an image from an image sensor of the mobile robot. The method includes splitting received image into at least two vertical portions and determining if one of said at least two vertical portions is indicative of a passable path. The method includes controlling the mobile robot to travel along the passable path indicated by a selected one of said at least two vertical portions.

Abstract: A method for removing stale context in a service instance, comprising: generating a user message according to UID and request instruction of received request data; routing the user message to first service instance; if target context corresponding to the user ID is saved in a global cache of a database, loading the target context from the global cache; when the loaded target context does not belong to the first service instance, setting the loaded target context to belong to the first service instance, wherein the set target context is saved into a first local cache and the global cache; and instructing to remove one or more invalid target contexts corresponding to the user ID from one or more other service instances, wherein the invalid target contexts are target contexts which do not belong to the first service instance, such that stale contexts which are the invalid target context are removed.

Abstract: Provided is a method and system for controlling data transmission in a 5G-V2X network. The 5G-V2X network has at least one defined geographical area including a plurality of traffic sensing devices (TSDs). Each of the TSDs is configured to provide data over one or more 5G channels to a V2X processing system via an edge gateway module (EGW) of the defined geographical area. The EGW includes a transmission controller (TC). The method comprises the TC dynamically adjusting a data transmission frequency of at least one TSD of the plurality of TSDs in accordance with a transmission control policy.

Abstract: A multi-functional, computer-aided gastroscopy system optimized with integrated AI solutions is disclosed. The system makes use of multiple deep-learning neural models to achieve low latency and high-performance requirements for multiple tasks. The optimization is made at three levels: architectural, modular and functional level. At architectural level, the models are designed in such a way that it is able to accomplish HP infection classification and detection of some lesions for one inference in order to reduce computation costs. At modular level, as a sub-model of HP infection classification, the site recognition model is optimized with temporal information. It not only improves the performance of HP infection classification, but also plays important roles for lesion detection and procedure status determination. At functional level, the inference latency is minimized by configuration and resource aware optimization.

Abstract: A movable camera travels along an inspection path for optically inspecting an inspection surface of an object for defect detection. In planning the inspection path, a set of viewpoints on the inspection surface is generated. Each viewpoint is associated with a patch, which is a largest area of the inspection surface within a field of view (FOV) of the camera when the camera is located over the viewpoint for capturing an image of FOV. An effective region of the patch is advantageously predicted by a neural network according to a three-dimensional geometric characterization of the patch such that the predicted effective region is valid for defect detection based on the captured image. A valid area is one whose corresponding area on the captured image is not blurred and is neither underexposed nor overexposed. The inspection path is determined according to respective effective regions associated with the set of viewpoints.

Abstract: A lossless data compressor prevents normalization overruns on-the-fly as symbol occurrence counts are rounded to generate symbol frequencies, allowing an encoding table generator to generate encoding table entries without waiting for the symbol frequency table to finish filling. Rounding errors are accumulated as symbols are normalized and compensated for by reducing a symbol frequency when the symbol frequency is at least 2 and the accumulated errors have exceeded a threshold. The symbol frequency is also reduced when the number of remaining states in the encoding table is insufficient for a number of remaining unprocessed symbols and states for a current encoding table entry. Since error compensation occurs as symbols are being normalized, encoding table generation is not forced to wait for all symbols in the block to be processed, reducing latency. Three pipeline stages can operate on three input blocks: symbol counting, normalization/error compensation/encoding table generation, and data encoding.

Abstract: Described is a method of identifying a short-circuit (SC) like event in a circuit breaker (CB). The method comprises sampling an incoming current to the CB to determine a maximum value of a slope of a curve of the incoming current. The method includes sampling the incoming current again before a level of the incoming current reaches a predetermined, preset, selected, or calculated SC threshold value THSC for the CB. The method involves determining from the sampled incoming current that a value of the slope of the incoming current has changed from its maximum slope value to a lower slope value to thereby determine that the incoming current is indicative of a SC like event and does not comprise a real SC event.

Abstract: Used batteries are screened based on a measured Sectional Constant-Current Impulse Ratio (SCCIR). A used battery is partially charged over a small voltage range using a Constant Current (CC) until a voltage target is reached, and the current integrated to obtain the CC charge applied, Qcc. Then the battery continues to be charged using a Constant Voltage (CV) of the voltage target until the charging current falls to a midrange current target before the battery is fully charged. The current is integrated over the CV period to obtain the CV charge applied, Qcv. The measured SCCIR is the ratio of Qcc to (Qcc+Qcv) and is input to a calibration curve function to obtain a modeled State of Health (SOH) value for sorting. The calibration curve function is obtained by aging new batteries to obtain SCCIR and SOH data that are modeled using a neural network.