Abstract: A tissue ablation system employing a radiofrequency generator and a radiofrequency probe, where a generator controller can be employed to automate selected operational modes of the generator. The operational modes can include determining if the probe is connected to the generator, determining the location of the probe, and determining an impedance of the probe. The generator can also display multiple channels on a display element, and the controller can generate summary information of the ablation procedure, including information associated with probe impedance and temperature and the power supplied by the generator.

Abstract: A method includes receiving a series of video segments and providing the series of video segments as input to a first machine learning model to produce text data. The text data is provided as input to a second machine learning model to produce categorized text data that includes a classification indication. The classification indication is added to metadata of the video segment, and the categorized text data is provided as input to a third machine learning model to produce a semantic vector. The method also includes causing the video segment and the metadata that includes the classification indication to be stored at a location of a database based on the semantic vector, the database being configured to be searched based on a search query associated with the semantic vector.

Abstract: Systems and methods for determining device location properties of a wireless device, such as a smartphone, are provided. The system includes a processor configured to receive, via a plurality of wireless receivers arranged in a monitoring area, a wireless signal. The wireless signal is transmitted by the wireless device proximate to the subject. The wireless signal includes an identifier, such as a Bluetooth identifier, corresponding to the wireless device. The processor is further configured to determine CSI for a subject based on the received wireless signal. The processor is further configured to determine the one or more device location properties based on the determined CSI and a body-mass signature corresponding to the identifier. The one or more device location properties may include a relative location of the wireless device on the subject and/or an associated subject status.

Abstract: The disclosure describes semiconductors test systems and related methods for performing semiconductor die final testing. Semiconductor dies may be tested in at least two stages: wafer tests and final die tests. The systems and methods of the disclosure reduce the amount of final die tests that are performed on semiconductor dies, using data from the wafer tests. A semiconductor test system may include a test probe to collect wafer test data from wafers each having a plurality of dies. The dimensionality of the wafer test data may be reduced, and the dies may may be clustered into die clusters using the dimensionally reduced data. Each die cluster may be clustered based on a likelihood that the cluster includes a failed die. The die clusters may be refined into smaller die clusters. Optionally, the smaller die clusters may be used to select at least some dies for final die testing.

Abstract: A gel material and a multifunctional gel pad, and preparation methods thereof and use are provided. The gel material includes the following raw materials, in parts by mass: 18 parts to 21 parts of 2-acrylamido-2-methylpropane sulfonic acid sodium salt (AMPS-Na), 2 parts to 4 parts of acrylic acid, 0.04 parts to 0.08 parts of a cross-linking agent, 30 parts to 40 parts of a water absorbent, 1.5 parts to 2 parts of a reinforcing agent, 0.05 parts to 0.1 parts of sodium hydroxide, 0.01 parts to 0.05 parts of a photoinitiator, 0.3 parts to 0.6 parts of a cosolvent, and 15 parts to 20 parts of water.

Abstract: An exemplary system and method are disclosed for facilitating users in building programs through an assembly of physical objects. In some implementations, the exemplary system and method include (i) a plurality of physical coding blocks and (ii) an interface configured to recognize a combined sequence of physical blocks in the assembly, extract programming functions or logics from the recognized combined sequence, and generate compilable or interpretable code for a software development environment that can be compiled thereon into computer-readable instructions to program electronic devices.

Abstract: A virtual equipment recommendation method includes: displaying a set recommendation interface in a shooting game, the set recommendation interface including a first area, and the first area including at least one set option; displaying, in response to a selection operation on a first set option of the at least one set option, recommended virtual equipment corresponding to the first set option in a second area of the set recommendation interface, appearances of the wearable equipment and the shooting equipment displayed in the second area having a skin style corresponding to the first set option; and displaying, in response to an acquisition operation on first virtual equipment of the recommended virtual equipment, an acquisition of the first virtual equipment and setting an appearance of the first virtual equipment according to the skin style.

Abstract: A system for predictive queue management of a monitored area, including a controller having a processor and sensors installed within a connected lighting system at optimal locations, is provided. The optimal locations are generated by a sensor selection model based on selection training data and potential sensor locations. The sensors capture optimized sensor data corresponding to 2024/037908 individuals in the monitored area, and may include PIR sensors, SPT sensors, and/or RF sensors. The processor then generates, based on the optimized data and a forecasting model, a queue volume prediction including a number of individuals that will need a service in the monitored area during a predetermined future time window. The processor then generates, based on recommender inputs including at least the queue volume prediction, a recommendation including a number of queues needed to process the queue volume prediction.

Abstract: A system for providing a sound-based sensing of subjects comprising a network (10) of network devices (100) configured to perform a sound-based sensing. The network devices (100) are distributed in a sensing area (20) and communicate with each other based on RF signals. At least one network device (100) comprises a sound generator (120) to generate a sound signal (100) and/or a sound sensor (130) to detect the sound signal (101) from the sound generator (120) after a propagation through at least a portion of the sensing area (20) and to generate a sensing signal indicative of the detected sound signal. The sound generator (120) and the sound sensor (130) are arranged in different network devices (100). A sitting position detector (200) detects a sitting position of a subject in a sensing area based on the sensing signal from the sound sensor (130).

Abstract: A method and system for determining an emotional state of a user based on a radiofrequency, RF, based sensing system are disclosed. The system comprises a presence detection unit configured to receive presence data and to determine a presence of the user and a visitor in an environment. The system further comprises a controller configured to receive a first and second input indicative of the presence of the user and the visitor respectively. The controller is further configured to, when the user is present, set the RF-based sensing system to a first operating mode, and when the user and the visitor are present, switch the RF-based sensing system to a second operating mode, wherein, when set to the second operating mode, the RF-based sensing system operates according to a second set of RF-sensing parameters that enable to sense one or more physical and/or physiological parameters of the user.

Abstract: The invention relates to an apparatus for controlling radiofrequency sensing and audio sensing of a network. The network (100) comprises a plurality of network devices (111, 112, 113, 114), e.g. smart lights, and is adapted to perform radiofrequency sensing and audio sensing utilizing one or more of the network devices. A context parameter providing unit (121) provides context parameters, wherein the context parameters are indicative of a context in which the radiofrequency sensing and the audio sensing is performed. A controlling unit (122) controls the radiofrequency sensing and the audio sensing of the network in dependency of each other based on the context parameters. This allows for an improved monitoring of an area.

Abstract: A detection system (10) and a detection method (2000) are disclosed herein. The system includes a PIR sensor (12) positioned in an area comprising a plurality of sub-areas, the motion sensor comprising an optical device (22) having a plurality of sub-lenses (26, 28, 30), each sub-lens of the plurality of sub-lenses having a field of view (FOV) corresponding to a sub-area of the plurality of sub-areas. The system further includes at least one processor (32) coupled to the PIR sensor and configured to: activate the plurality of sub-lenses to generate a total sensor FOV comprising each FOV of the plurality of sub-lenses; and dynamically control the plurality of sub-lenses to subdivide the total sensor FOV, wherein the subdivided sensor FOV is smaller than the total sensor FOV.

Abstract: A system (100) and method (500) for tracking a position of a subject (110) in an indoor space (120) are provided. The system comprises light sources (130) configured to emit modulated illumination, a scanning device (140) configured to receive the modulated illumination and obtain position information of the scanning device, a wireless communication system (160), a mobile device (170) arranged to be portable by the subject and connectable to the wireless communication system, wherein the mobile device is configured to generate its position data (180) via the wireless communication system, wherein a processor (200) of the system, as a function of at least one predetermined condition (230a-e), is configured to, register a position of the subject based on a position of the scanning device, or obtain position data of the mobile device, and/or register a position of the subject based on the position data of the mobile device.

Abstract: A method can include identifying a first set of data columns in a first data domain and a second set of data columns in a second data domain that are similar. The method can further include selecting a first subset of data columns in the first data domain and a second subset of data columns in the second data domain that have matching parameters. The method can further include arranging the first subset of data columns and the second set of data columns into a multi-domain dataset. Each column in the multi-domain dataset can be classified into structured data or unstructured data. The structured data can be used for training a machine learning model. The method can further include replacing under-performing features in the second data domain before replacing under-performing features in the first data domain. The method can further include re-training the machine learning model after replacing under-performing features.

Abstract: A system for determining a sleep posture of a user during a sleep session, the system comprising: one or more sensors from a plurality of sensors configured to measure a signal indicative of a motion of the user; and a controller configured to receive the signals from the one or more sensors indicative of a motion of the user; determine a turnover event from a predetermined plurality of reference turnover events based on the received signal; determine the sleep posture of the user from a predetermined plurality of reference sleep postures based on the turnover events.

Abstract: A method includes receiving a series of video segments and providing the series of video segments as input to a first machine learning model to produce text data. The text data is provided as input to a second machine learning model to produce categorized text data that includes a classification indication. The classification indication is added to metadata of the video segment, and the categorized text data is provided as input to a third machine learning model to produce a semantic vector. The method also includes causing the video segment and the metadata that includes the classification indication to be stored at a location of a database based on the semantic vector, the database being configured to be searched based on a search query associated with the semantic vector.

Abstract: A system for determining occupancy in an environment is provided. The system includes plurality of sensor bundles, with each bundle including a presence sensor and a motion sensor. The system further includes a controller in communication with each sensor bundle. The controller is configured to designate one of the sensor bundles as presence triggered if persons are present within a field of view of the presence sensor. The controller is further configured to designate one of the sensor bundles as motion triggered if persons are moving within a field of view of the motion sensor. The controller is further configured to determine a triggered bundle count of the sensor bundles which are both presence triggered and motion triggered. The controller is further configured to determine an occupancy count for the environment based upon the triggered bundle count.

Abstract: A sensor system (100) for monitoring a storage space comprising a plurality of items, comprising sensor(s) (110) configured to register occupancy of objects (120) in a plurality of zones (130) of the storage space, wherein each zone of the plurality of zones is associated with a respective hierarchic order, A, B, C, a processor (140) configured to determine a level of occupancy of the objects in at least two zones, compare a first level of occupancy of the objects of the first zone with a second level of occupancy of the objects of the second zone, and an alarm (150) configured to generate an alarm signal if the first level of occupancy of the first zone of the first hierarchic order, A, is lower than the second level of occupancy of the second zone of the second hierarchic order, B.

Abstract: Method and system for identifying design templates that match an input query are disclosed. The method includes: receiving a design search query; performing a template search based on the design search query, the template search returning a first template design, the first template design including a target image; processing the design search query to generate an image search query; performing an image search based on the image search query, the image search returning a candidate image; and generating a new design. The new design is based on the first template design and includes the candidate image instead of the target image.

Abstract: A system (100) for obfuscation of a position of at least one subject (110) in an indoor space (120), comprising a plurality of light sources (130) configured to emit modulated illumination, a mobile device (150) arranged to be portable by the at least one subject, configured to capture image(s) (156) comprising the modulated illumination, a server (160) configured to receive first image(s) (152) and determine a location of the mobile device(s), receive information related to zone(s) of the indoor space, predetermined privacy level(s) and privacy threshold level(s), and to perform a processing of the image(s) and a determination of an accuracy of the location of the mobile device(s), train a machine learning, ML, model by inputting the determined accuracy, wherein the mobile device is further configured to perform a processing of a captured second image(s) (154) by the trained ML model.