Abstract: The device Brexwel based on photoplethysmography (PPG) is used to track changes in oxygen consumption in breast tissues which can detect early indicators of breast cancer. In order to ensure high sensitivity, good noise performance, simplicity, and the reduction of artefacts in PPG signals, the device has an accelerometer. Hot-spot detection is done using the Brexwel device's thermal camera. For multi-modal classification, sensor-based, thermal image-based, and patient medical history-based classification, the device is controlled by a mobile application. Through specially designed capabilities in the mobile application, the device identifies various breast problems based on certain thresholds from PPG sensor. It is possible to get above 80% accuracy and 90% sensitivity, according to the detailed analysis of multi-modal findings, including thermal, optical, and medical histories conducted on female subjects of various age groups under normal, benign and malignant category.

Abstract: Systems and methods for automated code analysis and tagging are disclosed. In one embodiment, a method for automated code analysis and tagging may include: (1) receiving, by a code annotation computer program executed by a computer processor, a training code snippet from a training codebase; (2) parsing, by the code annotation computer program, the training code snippet into a data structure; (3) quantifying, by the code annotation computer program, the data structure, (4) parsing, by the code annotation computer program, a docstring associated with the training code snippet into a plurality of keywords; (5) quantifying, by the code annotation computer program, the plurality of keywords; and (6) training, by the code annotation computer program, a code annotation model based on a similarity between the quantified data structure and a smoothing parameter for a Dirichlet prior smoothing estimate.

Abstract: Buses such as USB4 or Thunderbolt 4 buses may allow for device combinations that actually cannot be accommodated on the bus. A monitoring component, e.g., software and/or hardware component, such as an Operating System (OS) policy manager, may monitor a bus for events identifying changes to devices on the bus. The monitoring component may influence mode changes to hardware/software, such as to the USB configuration, device driver settings, attached device settings, and/or settings for devices attaching to the bus. Influenced changes facilitate accommodating changes to the devices attached to the bus. For example, if a display is attached and it would exceed available bus bandwidth, cause an excess system load, or cause some other problem, rather than fail to enumerate the display, instead hardware and/or software associated with the bus may be influenced to result in a resolution reduction for the display to accommodate it attaching to the bus.

Abstract: A system for training a machine learning framework to estimate depths of objects captured in 2-D images includes a first trained machine learning network and a second untrained or minimally trained machine learning framework. The first trained machine learning network is configured to analyze 2-D images of target spaces including target objects and to provide output indicative of 3-D positions of the target objects in the target spaces. The second machine learning network can be configured to provide an output responsive to receiving a 2-D input image. A comparator receives the outputs from the first and second machine learning networks based on a particular 2-D image. The comparator compares the output of the first trained machine learning network with the output of the second machine learning network. A feedback mechanism is operative to alter the second machine learning network based at least in part on the output of the comparator.

Abstract: The present disclosure provides a method for triggering elements in a network (301). The method comprising communicating a device trigger (DT) request to a network exposure function (NEF) (304), communicating a mobile management entity (MME) identifier (ID) request to a unified data management (UDM) (308), and obtaining an MME ID response including the MME ID from the UDM (308). The method comprising communicating the DT request and the MME ID to a service capabilities exposure function (SCEF) (306), communicating the DT request and the MME ID to an internet protocol short message (IPSM) gateway/short message service center (SMSC) (312), communicating the DT request to a mobile management entity (MME)/access and mobility management function (AMF) (316) based on the MME ID. The method comprising communicating by the MME/AMF (316), the DT request to a user equipment (UE) (318).

Abstract: Multi-object tracking in autonomous vehicles uses both camera data and LiDAR data for training, but not LiDAR data at query time. Thus, no LiDAR sensor is on a piloted autonomous vehicle. Example systems and methods rely on camera 2D object detections alone, rather than 3D annotations. Example systems/methods utilize a single network that is given a camera image as input and can learn both object detection and dense depth in a multimodal regression setting, where the ground truth LiDAR data is used only at training time to compute depth regression loss. The network uses the camera image alone as input at test time (i.e., when deployed for piloting an autonomous vehicle) and can predict both object detections and dense depth of the scene. LiDAR is only used for data acquisition and is not required for drawing 3D annotations or for piloting the vehicle.

Abstract: An embodiment herein provides a method and network apparatus for determining an optimal uplink slot division in telecommunication network. The method comprises: detecting, by a network apparatus in telecommunication network, a list of radio bearers associated with plurality of UE; determining, a Buffer Occupancy (BO) of each radio bearer of a list of radio bearers associated with plurality of UE; determining, a BO threshold for each radio bearer from list of radio bearers; classifying, the list of radio bearer into plurality of radio bearer groups based on BO and BO threshold for each of the radio bearer; and determining, the optimal uplink slot division based on the plurality of radio bearer groups.

Abstract: A sign bit of a low-density parity-check (LDPC) codeword associated with a translation unit (TU) can be generated by performing an XOR operation on a RAIN drop corresponding to the TU and a raw read of the TU. The LDPC codeword can include a hard bit and three soft bits that include the sign bit. The LDPC codeword can be decoded using the hard bit and the three soft bits. A read recovery operation can be performed on the TU using the decoded LDPC codeword.

Abstract: An apparatus comprises at least one processing device configured to implement a multi-path layer in a host device, wherein the multi-path layer controls delivery of input-output (IO) operations from the host device to a storage system over selected ones of a plurality of paths through a network. The multi-path layer is configured, for each of at least a subset of the IO operations, to store at least a process identifier, a user identifier and an access type for the IO operation. The multi-path layer is further configured to perform analytics on the stored process identifiers, user identifiers and access types to detect an access pattern, and responsive to the detected access pattern having one or more designated characteristics associated with malware, to generate an alert. The alert may be generated by inserting security alert indicators into respective ones of the IO operations, for extraction therefrom by the storage system.

Abstract: A device to convert a detected voltage, that is indicative of current conducted by a switching circuit, to a series of electrical pulses that is indicative of electrical power dissipated by the switching circuit responsive to the current. The device includes a transconductor circuit including a first circuit to receive a reference current and a first reference voltage, and to obtain a transconductance based on an auto-generated bias current and the reference current and the first reference voltage, where a value of the transconductance is determined by the reference current and the first reference voltage. The transconductor circuit further includes a second circuit coupled to the first circuit to receive the detected voltage, and to generate a first current based on the detected voltage and the obtained transconductance.

Abstract: Systems, devices, and methods related to temperature sensors for electronic devices are provided. An example temperature sensor device includes analog temperature sensor circuitry to generate a plurality of voltages indicative of a temperature; an analog-to-digital converter (ADC) disposed downstream of the analog temperature sensing circuitry; switched-capacitor amplifier circuitry disposed before the ADC, the switched-capacitor amplifier circuitry comprising a single-ended amplifier to amplify the plurality of voltages with respect to a common voltage; a first switch coupled between the analog temperature sensor circuitry and the switched-capacitor amplifier circuitry to provide a sampling phase and an integration phase; and digital calculation circuitry to calculate a temperature value based on the plurality of amplified voltages.

Abstract: Systems and techniques are provided for wireless communications. A process can include determining that a quantity of a plurality of Mobile Terminated (MT) calls received within a first time period is greater than a first configured threshold. A process can include determining a subset of non-verified MT calls from the plurality of MT calls based on a call verification score for each respective MT call of the plurality of MT calls received within the first time period. A process can include determining that a quantity of non-verified MT calls included in the subset is greater than a second configured threshold. A process can include performing modem-level blocking based on determining a corresponding calling party identity associated with a non-verified MT call included in the subset.

Abstract: Dynamic generation of climate projections is provided. The method comprises receiving past climate data of a first spatial resolution. The past climate data of the first spatial resolution is converted to past climate data of a second spatial resolution. A machine learning model is trained with a deep learning algorithm with a training set of the data to generate a trained model object that maps a relationship between the past climate data of the first spatial resolution and the first climate data of the second spatial resolution. The trained model object is validated with a validation set of the data. The trained model object is applied to climate projections of the second spatial resolution to generate climate projections of the first spatial resolution.

Abstract: Multi-object tracking in autonomous vehicles uses both camera data and LiDAR data for training, but not LiDAR data at query time. Thus, no LiDAR sensor is on a piloted autonomous vehicle. Example systems and methods rely on camera 2D object detections alone, rather than 3D annotations. Example systems/methods utilize a single network that is given a camera image as input and can learn both object detection and dense depth in a multimodal regression setting, where the ground truth LiDAR data is used only at training time to compute depth regression loss. The network uses the camera image alone as input at test time (i.e., when deployed for piloting an autonomous vehicle) and can predict both object detections and dense depth of the scene. LiDAR is only used for data acquisition and is not required for drawing 3D annotations or for piloting the vehicle.

Abstract: Methods and systems for connecting data with non-standardized schemas in connected graph data exchanges. For example, the system generates a custom data structure corresponding to a user identifier for a user profile that includes pointers between user profile attributes (e.g., individual fields/categories within the user profile) and existing assets in a connected graph (e.g., an existing application, software profile for an application, data set, connections, etc.). The system then connects the custom data structure corresponding to the user identifier to the existing assets in the connected graph.

Abstract: Aspects of the present disclosure relate to wireless communications, and more particularly, to techniques that may help mitigate service loss for a UE (e.g., in DSDA mode) due to temperature rise. According to certain aspects, a UE detects, while operating in a multi subscriber identity module (SIM) mode with at least a first subscriber (SUB) and a second subscriber (SUB) active on a first radio access technology (RAT), that the UE has reached a first temperature threshold less than a second temperature threshold at which the UE limits service in the first RAT and greater than a third temperature threshold associated with a temperature mitigation level. The UE then takes action to move the first SUB to a second RAT in response to the detecting.

Abstract: Systems, devices, and methods related to temperature sensors for electronic devices are provided. An example temperature sensor device includes analog temperature sensor circuitry to generate a plurality of voltages indicative of a temperature; an analog-to-digital converter (ADC) disposed downstream of the analog temperature sensing circuitry; switched-capacitor amplifier circuitry disposed before the ADC, the switched-capacitor amplifier circuitry comprising a single-ended amplifier to amplify the plurality of voltages with respect to a common voltage; a first switch coupled between the analog temperature sensor circuitry and the switched-capacitor amplifier circuitry to provide a sampling phase and an integration phase; and digital calculation circuitry to calculate a temperature value based on the plurality of amplified voltages.

Abstract: Systems and methods for detecting code duplication are disclosed. In one embodiment, a method for detecting exact code snippet duplicates may include: (1) representing, by a code duplication detection computer program, each of a plurality of code snippets in a codebase as an abstract syntax trees; (2) featurizing, by the code duplication detection computer program, the abstract syntax trees into corpus feature vectors by converting the abstract syntax tree into vector representations; (3) generating, by the code duplication detection computer program, dense feature vectors from the corpus feature vectors using a dimension reduction technique; (4) identifying, by the code duplication detection computer program, exact duplicate code snippet matches by apply density-based clustering to the dense feature vectors; and (5) tagging, by the code duplication detection computer program, the exact duplicate code snippets.

Abstract: Techniques for generating a simulated application programming interface (API) may include generating simulations of APIs that provide stateful interactions. The simulations may be generated based on API specifications and/or other API parameters (e.g. from a user). The API simulations may be deployed to individual tenancies that provide dedicated resources for the simulation. The simulations may be further secured by anonymizing or scrubbing data used in the simulation by removing non-public information from data provided for the simulation. Additionally, or alternatively, dummy data may be generated that is free of non-public information. A demo site (e.g., a mocked frontend) may be generated that facilitates access to the simulated API and allow a real-world evaluation of the simulated API by a user.