Abstract: Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously extend DFOS techniques to anomaly detection using optical magnetism switches (OMC) that are integrated into the DFOS system.

Abstract: An electrostatic discharge protection circuit includes an electrostatic discharge clamp between a first rail and a second rail, a trigger device configured to activate the electrostatic discharge clamp in response to an electrostatic discharge event, and a charge dissipation element between the first rail and the second rail to dissipate a residual charge at an input of the trigger device.

Abstract: Aspects of the present disclosure describe optical fiber sensing systems, methods and structures disclosing a distributed optical fiber sensor network constructed on a switched optical fiber telecommunications infrastructure to detect temperatures, acoustic effects, and vehicle traffic—among others—demonstrated with a number of different network topologies.

Abstract: A fiber optic sensing technology for vehicle run-off-road incident automatic detection by an indicator of sonic alert pattern (SNAP) vibration patterns. A machine learning method is employed and trained and evaluated against a variety of heterogeneous factors using controlled experiments, demonstrating applicability for future field deployment. Extracted events resulting from operation of our system may be advantageously incorporated into existing management systems for intelligent transportation and smart city applications, facilitating real-time alleviation of traffic congestion and/or providing a quick response rescue and clearance operation.

Abstract: Distributed fiber optic sensing (DFOS) systems, methods and structures for determining the proximity of vibration sources located perpendicular to a sensor fiber that is part of the DFOS system that may potentially threaten/damage or otherwise compromise the sensor fiber itself. Systems, methods, and structures according to aspects of the present disclosure employ Artificial Intelligence (AI) methodology(ies) that use as input a fundamental physical understanding of wave propagation and attenuation in the ground along with Bayesian inference and Maximum Likelihood Estimation (MLE) techniques for estimating/determining the proximity of potentially damaging vibration sources to the optical sensor fiber.

Abstract: Aspects of the present disclosure describe an unsupervised context encoder-based fiber sensing method that detects anomalous vibrations proximate to a sensor fiber that is part of a distributed fiber optic sensing system (DFOS) such that damage to the sensor fiber by activities producing and anomalous vibrations are preventable. Advantageously, our method requires only normal data streams and a machine learning based operation is utilized to analyze the sensing data and report abnormal events related to construction or other fiber-threatening activities in real-time. Our machine learning algorithm is based on waterfall image inpainting by context encoder and is self-trained in an end-to-end manner and extended every time the DFOS sensor fiber is optically connected to a new route. Accordingly, our inventive method and system it is much easier to deploy as compared to supervised methods of the prior art.

Abstract: Metal complexes including cyclopentadienyl ligands and methods of using such metal complexes to prepare metal-containing films are provided.

Abstract: Aspects of the present disclosure describe systems, methods and structures for determining any location on a deployed fiber cable from an optical time domain reflectometry (OTDR) curve using a movable mechanical vibration source to stimulate tiny vibration of fiber in deployed fiber cable along the cable route and a fiber sensing system at a central office to detect the vibration(s). Latitude and longitude of the location(s) of the vibration source is measured with a GPS device and a dynamic-OTDR distance is measured at central office (CO) simultaneously. The collected GPS location data and corresponding dynamic-OTDR distance data are paired and saved into a database. This saved data may be processed to graphically overlie a map thereby providing exact cable location on the map thereby providing carriers/service providers the ability to improve fiber fault location on a deployed fiber cable much faster and more accurately than presently possible using methods available in the art.

Abstract: A device may receive, from a fiber sensor device, sensing data associated with a fiber optic cable, the sensing data being produced by an activity that poses a threat of damage to the fiber optic cable, and the sensing data identifying: amplitudes of vibration signals, frequencies of the vibration signals, patterns of the vibration signals, times associated with the vibration signals, and locations along the fiber optic cable associated with the vibration signals. The device may process, with a machine learning model, the sensing data to determine a threat level of the activity to the fiber optic cable, the machine learning model having been trained based on historical information regarding detected vibrations, historical information regarding sources of the detected vibrations, and historical information regarding threat levels to the fiber optic cable. The device may perform one or more actions based on the threat level to the fiber optic cable.

Abstract: A device is disclosed herein. The device includes an electrostatic discharge (ESD) protection switch and an ESD driver. The ESD driver is configured to receive a first voltage and a second voltage. When a voltage difference between the first voltage and the second voltage is higher than a first voltage threshold, the ESD driver outputs a first trigger signal to turn on the ESD protection switch. When the voltage difference between the first voltage and the second voltage is lower than a second voltage threshold, the ESD driver outputs a second trigger signal to turn on the ESD protection switch.

Abstract: Metal complexes including cyclopentadienyl ligands and methods of using such metal complexes to prepare metal-containing films are provided.

Abstract: A virtual and real image fusion method is disclosed. The method comprises the following operations: obtaining a picture of a three dimensional space by a first camera, in which the picture comprises a screen picture and a tag picture of an entity tag and the screen picture is projected on the entity tag; obtaining a corresponding point data of the entity tag on the screen picture according to the picture by a processor; obtaining a spatial correction parameter according to the corresponding point data by the processor; and displaying an image on the screen picture according to the spatial correction parameter by the processor.

Abstract: An electrostatic discharge protection circuit includes an electrostatic discharge clamp between a first rail and a second rail, a trigger device configured to activate the electrostatic discharge clamp in response to an electrostatic discharge event, and a charge dissipation element between the first rail and the second rail to dissipate a residual charge at an input of the trigger device.

Abstract: Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously utilize existing telecommunications facilities that serve as not only to convey telecommunications traffic—but as a sensor medium providing useful sensory information. In sharp contrast to the prior art—a DFOS system when so deployed may advantageously exploit network topologies and optical switches to provide novel sensing features including the detection of environmental events including acoustic, temperature, and vibrational events that may be indicative of societal activity including traffic and/or emergency events.

Abstract: A method of manufacturing circuit board structure includes operations below. First, a first substrate is provided. A first wire structure is formed on the first substrate, in which the first wire structure includes a first wire having a first height and a second wire having a second height, and the first height is greater than the second height. A liquid crystal polymer layer is then formed on the first substrate and covers the first wire structure.

Abstract: Aspects of the present disclosure describe distributed fiber optic sensing (DFOS) systems, methods, and structures that advantageously enable anomaly detection resulting from construction—or other activity based on image processing that may advantageously detect/notify/prevent damage to a fiber optic network infrastructure before such damage occurs.

Abstract: An electrostatic discharge protection circuit includes an electrostatic discharge clamp between a first rail and a second rail, a trigger device configured to activate the electrostatic discharge clamp in response to an electrostatic discharge event, and a charge dissipation element between the first rail and the second rail to dissipate a residual charge at an input of the trigger device.

Abstract: This disclosure provides a perovskite light-emitting diode with an adjustable light field, including a glass layer, an anode, a hole transport layer, an emission layer, an electron transport layer and a cathode in sequence from top to bottom. The electron transport layer is provided with a periodic nano-grating structure.

Abstract: Aspects of the present disclosure describe single mode fiber distributed temperature sensing (DTS) with improved noise characteristics employing superluminescent emitting diodes (SLEDs) and/or amplified spontaneous emission (ASE) light sources.

Abstract: Methods and systems for training a neural network include generate an image of a mask. A copy of an image is generated from an original set of training data. The copy is altered to add the image of a mask to a face detected within the copy. An augmented set of training data is generated that includes the original set of training data and the altered copy. A neural network model is trained to recognize masked faces using the augmented set of training data.