Abstract: Disclosed are integrated DFOS/DAS systems, methods, and structures that employ a large-scale pretrained recognition model we refer to as an “acoustic-language model”, which is pretrained with natural-language supervision (“contrastive language-audio pretraining”. The acoustic-language model comprises two primary components: an acoustic encoder and a text encoder. These encoders are pretrained using a cross-modal approach on a vast dataset of acoustic features (such as images created from log Mel spectrograms) and their corresponding textual captions. When acoustic features and/or languages are input into their respective encoders within the model, they generate corresponding embedding vectors. Both embedding vectors are then linked in a joint multimodal space using linear projections.

Abstract: The invention discloses a multi-functional breathing tube for humidification without water. It includes a breathing mask, the breathing mask is connected with a sputum ejector, the sputum ejector is connected with an anhydrous humidifier atomizer, and the anhydrous humidifier atomizer is connected with a medicated bin. The medicated bin is connected with a breathing hose, the breathing hose is connected with an air source device, and the gas output by the air source device is oxygen. The sputum ejector is connected with the anhydrous humidifier atomizer. The pendulum ball in the sputum ejector resonates with the sputum during the patient's deep exhalation to assist the sputum excretion from the patient's body.

Abstract: Aspects of the present disclosure describe Rayleigh-based DTSS that utilizes few-mode fiber (FMF), which supports multiple spatial modes. For each spatial mode, a wavelength-scanning configuration gives the relative wavelength (or frequency) shift between two consecutive measurements. The temperature and strain changes can therefore be separated through different temperature/strain sensitivities of various mode-pairs. Advantageously, Rayleigh-based DTSS according to aspects of the present disclosure removes temperature-strain ambiguity, enhances measurement accuracy, reduces errors. and enables new features for multi-parameter sensing.

Abstract: Methods and systems for acoustic sensing include determining sensing locations along a fiber to generate a beam pattern that is directed to an acoustic source. An optical pulse is transmitted on the fiber. Optical phase of backscattering light is measured from the sensing locations on the fiber. An output signal is generated by combining the measured optical phase according to the beam pattern.

Abstract: A method for time synchronization using distributed fiber optic sensing (DFOS) that employs several trusted time beacons that are attached to the DFOS sensing fiber which in turn is connected to the DFOS interrogator. The beacons transmit their signal via two different mediums, (1) wirelessly to sensor nodes in the coverage area, and (2) through vibrations on fiber to the DFOS/DAS system located at a trusted area such as the central office. Wireless broadcast to nearby sensors includes a timestamp and beacon ID. All the sensors in the field use one of the beacons in their vicinity (the one with the strongest signal) as their time reference and send the data back with the corresponding beacon index.

Abstract: Disclosed are systems and methods directed to a MIMO method that detects and localizes an object without requiring the object to emit a sound. Operationally, multiple speakers generate tone signals at different frequencies, while multiple acoustic sensors demodulate the complex amplitude of each frequency. By monitoring the feature variation of the relative phase (or intensity) vector from the complex amplitude, our method detects or localizes movement of the object. For large-scale applications, a fiber-optic system and method that employs distributed acoustic sensing (DAS) in which an optical fiber is used as one or more acoustic sensors located at points along the length of the optical fiber. A single DAS system provides numerous sensors using only a single optical fiber thereby enabling perfect synchronization and centralized signal processing. Notably, with such a DAS arrangement, cost and complexity is significantly reduced, while privacy is preserved.

Abstract: Disclosed are systems, methods, and structures that mitigate accumulative error in relative-measurement DFOS by employing, for each segment of the DFOS arrangement that records a certain number of an earlier estimation of each spatial segment. A predictive model in each buffer learns trends from the recorded history and predicts an output from the previous history. The reference is also updated using the prediction from the buffer. Systems, methods, and structures according to the present disclosure include the buffer structure that records a certain number of earlier estimations for each segment, a predictive model in each buffer that predicts the output of each segment according to the earlier estimations, reference updates using the prediction from the buffer tracker and workflow of real-time data processing with the buffer structure and tracker.

Abstract: Disclosed are systems, methods, and structures that provide more accurate temperature measurements and/or derived measurements using distributed fiber optic sensing (DFOS) systems and methods. DFOS systems and methods according to aspects of the present disclosure employ distributed fiber optic sensing that determines real-time temperature changes and vehicle trajectories from two-dimensional (2D) DFOS data with very few labeled data. The 2D data is first divided into multiple grids and then pre-processed with image distortion methods to enrich diversity of temperature change patterns. The transformed grids are used to pre-train a masked autoencoder, which advantageously does not require labels. The encoder of the autoencoder learns intrinsic features of temperature and traffic patterns, which are later connected to an estimation network to solve downstream tasks trained on a small set of labeled data.

Abstract: Physimetric-based data security for coded distributed temperature sensing (DTS) in which physimetric information is extracted from a coded-DTS interrogator which is unique for each interrogator at each operating run time—and used to reconstruct a final temperature determination from DTS data. The physimetric information includes coded-DTS pulse code and coded-DTS pulse profile information as a key to permit secure sharing with authorized users. The pulse code and pulse profile information are encrypted and made available to an authorized user. The authorized user can then decrypt the pulse code and pulse profile information and subsequently use this key information (pulse profile and pulse code files) to retrieve temperature information from for example, a remote computer providing a continuous raw data feed—without being susceptible to eavesdropping.

Abstract: Cognitive determination of whether a message is suitable for sending over a data communications network can include extracting tokens from the message prior to transmitting the message. One or more intended recipients of the message can be determined from the tokens. A machine learning classification model corresponding to the one or more recipients of the message can be selected. The machine learning classification model can be constructed based on tokens extracted from prior messages, which are combined to create a plurality of documents for training the machine learning classification model. The one or more tokens extracted from the message can be classified using the machine learning classification model. An alert message can be generated in response to determining based on the classifying that the message is unsuited for sending.

Abstract: The present disclosure provides a power management method, a power management device (10), an energy management device (70), an energy system (100), and a storage medium (300). The power management method includes: obtaining first generated power of the first power generation device (30) and consumed power of the one or more loads (200); controlling, when the first generated power is greater than the consumed power, the energy storage device (50) to store power; and outputting, based on a determined electricity selling period, electric quantity of the energy storage device (50) to a power grid (400) during the electricity selling period.

Abstract: Provided are a control method for a home energy system (100), an energy system, an energy management device, and a computer-readable storage medium. The control method includes: when the home energy system (100) is in a grid-connected state and a non-time-shifting power generation device is in a power-supply state, obtaining net power of the home energy system (100) during each power consumption time period of a current day, and when the net power is smaller than zero, controlling, based on an electricity price of the public grid (20), the home energy system (100) to be power by an energy storage device (12) or by the public grid (20); and when the net power is greater than zero, controlling the power generation device to output electric energy to the energy storage device (12) or the public power grid (20).

Abstract: A composite electrochromic material, a preparation method therefor and an application thereof, the material comprising a core layer, a skin layer having an electrochromic function, and a light-transmitting protective layer formed by a flexible polymer material, that are arranged in sequence. The material of the core layer comprises a fluid conductive mixture, which comprises liquid metal and carboxylated carbon nanotubes. The preparation method comprises: carrying out spinning by co-extrusion using a three-channel nozzle to form hollow double-layer fibers each having a skin layer and a protective layer as well as a cavity, injecting the conductive mixture into the cavity of the hollow double-layer fiber. The material has excellent deformation ability, stable and sensitive color changing function, and a controllable deformation degree. The material has a stable color changing function even in the case of severe defomation, good fatigue resistance, and is suitable for the preparation of intelligent textiles.

Abstract: A system and method for authentication code generation based on adversarial machine learning are provided in this disclosure. The method includes a defensive authentication code generation system, an authentication code formation module, an authentication code scheduling module, an authentication-code adversarial processing center, an attack sample generation module, a verification and error reporting system, a division module, a grouping and distribution system, a category checking module, a data recording unit, a detection module and an integration terminal. In the system and method for authentication code generation based on adversarial machine learning according to the disclosure, attack scenes are simulated for continuous training for the authentication code, error-reporting data are recorded and optimized into the defensive authentication code generation system, so as to improve defense performance of the authentication code.

Abstract: Disclosed are systems, methods, and structures employing a distributed fiber optic sensing (DFOS)/distributed acoustic sensing (DAS) system operating as an underwater wireless acoustic antenna in which an optical fiber sensor cable serves as a distributed acoustic antenna that receives multiple data from transmitters using an optical interrogator. Sensing channels, in the form of acoustic-antenna-array systems are located near transmitters taking advantage of the fact that these channels are automatically synchronized. The sensing channels may also be manually selected from software controlling the interrogator, and acoustic repeaters may be introduced as one data transmission mechanism. Acoustic tata transmission using an orthogonal frequency division multiplexed (OFDM) signal is demonstrated as a cure for data transmission using a DAS, such as multipath fading impacting bit error rate (BER) and limitations in acoustic transmission bandwidth.

Abstract: Disclosed are vehicle-infrastructure interaction systems and methods employing a distributed fiber optic sensing (DFOS) system operating with pre-deployed fiber-optic telecommunication cables buried alongside/proximate to highways/roadways which provide 24/7 continuous information stream of vehicle traffic at multiple sites; only require a single optical sensor cable that senses/monitors multiple locations of interest and multiple lanes of traffic; the single optical sensor cable measures multiple related information (multi-parameters) about a vehicle, including driving speed, wheelbase, number of axles, tire pressure, and others, that can be used to derive secondary information such as weight-in-motion; and overall information about a fleet of vehicles, such as traffic congestion or traffic-cargo volume. Different from merely traffic counts, our approach can provide the count grouped by vehicle-types and cargo weights.

Abstract: Aspects of the present disclosure describe systems, methods, and structures for distributed temperature sensing that employ joint wavelet denoising to achieve desirable signal-to-noise ratio(s) over extended sensor fiber distances.

Abstract: Certain aspects of the present disclosure provide techniques for committing log data in an application to a log data repository. An example method generally includes receiving, from an application, data to be committed to a remote storage location. A type of the received data is determined. The type of the received data is generally associated with a prioritization level and a compression mechanism to be used in committing the data to the remote storage location. An application execution context associated with the received data is determined. At a dispatch time associated with the prioritization level of the received data and the application execution context associated with the received data, a compressed data payload is generated and transmitted to the remote storage location. Generally, to compress the data payload, at least the received data is generally compressed based on the determined compression mechanism.

Abstract: Method for source localization for cable cut prevention using distributed fiber optic sensing (DFOS)/distributed acoustic sensing (DAS) is described that is robust/immune to underground propagation speed uncertainty. The method estimates the location of a vibration source while considering any uncertainty of vibration propagation speed and formulates the localization as an optimization problem, and both location of the sources and the propagation speed are treated as unknown. This advantageously enables our method to adapt to variances of the velocity and produce a better generalized performance with respect to environmental changes experienced in the field. Our method operates using a DFOS system and AI techniques as an integrated solution for vibration source localization along an entire optical sensor fiber cable route and process real-time DFOS data and extract features that are related to a location of a source of vibrations that may threaten optical fiber facilities.

Abstract: A system and method for authentication code generation based on adversarial machine learning are provided in this disclosure. The method includes a defensive authentication code generation system, an authentication code formation module, an authentication code scheduling module, an authentication-code adversarial processing center, an attack sample generation module, a verification and error reporting system, a division module, a grouping and distribution system, a category checking module, a data recording unit, a detection module and an integration terminal. In the system and method for authentication code generation based on adversarial machine learning according to the disclosure, attack scenes are simulated for continuous training for the authentication code, error-reporting data are recorded and optimized into the defensive authentication code generation system, so as to improve defense performance of the authentication code.