20-inch photomultiplier tube timing study for JUNO

Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator neutrino detector now under construction at Jiangmen, Guangdong, China for determination of neutrino mass ordering with 3% energy resolution at 1 MeV, a precise measurement of neutrino oscillation parameters, and other neutrino physics. The central detector is made up of a 35.4-meter diameter acrylic sphere which contains 20 kton of liquid scintillator and is surrounded by about 18k 20-inch photomultiplier tubes (PMTs). The PMTs performance is one of the JUNO’s key successes to reach the high resolution goal. In this study, the PMT characteristic and its timing related responses were determined via the PMT generated signals, extracted from the PMT in a scanning station system. About 2,400 of micro-channel plate PMTs (MCP-PMTs) and dynode PMTs were analyzed for their responses with LED source such as rise time, fall time, transit time spread (TTS), gain, etc., which relate to photon incident on different positions of PMT’s glass surface. Furthermore, we also observed the fluctuation of PMT performance under magnetic field which can decrease the PMT photon detection efficiency (PDE).

Fall Recognition System to Determine the Point of No Return in Real-Time

In this study, we collected data on human falls, occurring in four directions while walking or standing, and developed a fall recognition system based on the center of mass (COM). Fall data were collected from a lower-body motion data acquisition device comprising five inertial measurement unit sensors driven at 100 Hz and labeled based on the COM-norm. The data were learned to classify which stage of the fall a particular instance belongs to. It was confirmed that both the representative convolutional neural network learning model and the long short-term memory learning model were performed within a time of 10 ms on the embedded platform (Jetson TX2) and the recognition rate exceeded 94%. Accordingly, it is possible to verify the progress of the fall during the unbalanced and falling steps, which are classified by subdividing the critical step in which the real-time fall proceeds with the output of the fall recognition model every 10 ms. In addition, it was confirmed that a real-time fall can be judged by specifying the point of no return (PONR) near the point of entry of the falling down stage.

Real time fall detection using infrared cameras and reflective tapes under day/night luminance

Falls are the leading cause of injuries and death in elderly individuals who live alone at home. The core service of assistive living technology is to monitor elders’ activities through wearable devices, ambient sensors, and vision systems. Vision systems are among the best solutions, as their implementation and maintenance costs are the lowest. However, current vision systems are limited in their ability to handle cluttered environments, occlusion, illumination changes throughout the day, and monitoring without illumination. To overcome these issues, this paper proposes a 24/7 monitoring system for elders that uses retroreflective tape fabricated as part of conventional clothing, monitored through low-cost infrared (IR) cameras fixed in the living environment. IR camera records video even when there are changes in illumination or zero luminance. For classification among clutter and occlusion, the tape is considered as a blob instead of a human silhouette; the orientation angle, fitted through ellipse modeling, of the blob in each frame allows classification that detects falls without pretrained data. System performance was tested using subjects in various age groups and “fall” or “non-fall” were detected with 99.01% accuracy.

Estimation and Analysis of Higher-Order Harmonics in Advanced Integrated Circuits to Implement Noise-Free Future-Generation Micro- and Nanoelectromechanical Systems

This work deals with the analysis of spectrum generation from advanced integrated circuits in order to better understand how to suppress the generation of high harmonics, especially in a given frequency band, to design and implement noise-free systems. At higher frequencies, the spectral components of signals with sharp edges contain more energy. However, current closed-form expressions have become increasingly unwieldy to compute higher-order harmonics. The study of spectrum generation provides an insight into suppressing higher-order harmonics (10th order and above), especially in a given frequency band. In this work, we discussed the influence of transistor model quality and input signal on estimates of the harmonic contents of switching waveforms. Accurate estimates of harmonic contents are essential in the design of highly integrated micro- and nanoelectromechanical systems. This paper provides a comparative analysis of various flip-flop/latch topologies on different process technologies, i.e., 130 and 65 nm. An FFT plot of the simulated results signifies that the steeper the spectrum roll-off, the lesser the content of higher-order harmonics. Furthermore, the results of the comparison illustrate the improvement in the rise time, fall time, clock-Q delay and spectrum roll-off on the better selection of slow-changing input signals and more accurate transistor models.

Modifications to the Effective Sample Area in Data Acquired by 2-Dimensional Video Disdrometers

<p>The 2-Dimensional Video Disdrometer (manufactured by Joanneum Research) is an instrument widely used for ground validation and precipitation microphysics studies. This instrument is capable of reporting back multiple properties of each detected hydrometeor; fields in the data record include arrival time, fall velocity, oblateness, mass-weighted equivalent diameter, detection position, and estimated detector sample area for each detected drop.</p><p>The last of these variables is necessary for using the data record to reliably estimate the instantaneous rain rate and total accumulations; it varies from detected drop to detected drop because a detected hydrometer must be fully enclosed within a fixed sample area to be successfully characterized by the instrument; this means that larger droplets have a smaller region that their centers can fall through and still be accurately measured. Careful analysis reveals that improvements can be made to the manufacturer’s calculation of this drop-dependent effective sample area.</p><p>These improvements are related to four key observations. (1) Due to the optical geometry of the instrument, not every pixel comprising the detection area has the same size. (2) The manufacturer’s algorithm makes some sub-optimal corrections for accounting for the detection area boundary. (3) The assumed extent of the full detection area field-of-view has been found to be slightly inaccurate. (4) There is a recently found anomaly that intermittently renders part of the detection area insensitive to reliable drop detection.</p><p>Here, we present a review of these observations, outline the structure of a simple post-processing algorithm developed to adjust the effective sampling area for each drop, and present results quantifying the overall impact on precipitation accumulations for a data record incorporating over 200 million detected raindrops.</p>