Learning Speed Enhancement of Iterative Learning Control with Advanced Output Data based on Parameter Estimation

Learning speed enhancement is one of the most important issues in learning control. If we can improve both learning speed and tracking performance, it will be helpful to the applicability of learning control. Considering these facts, in this paper, we propose a learning speed enhancement scheme for iterative learning control with advanced output data (ADILC) based on parameter estimation. We consider linear discrete-time non-minimum phase (NMP) systems, whose model is unknown, except for the relative degree and the number of NMP zeros. In each iteration, estimates of the impulse response are obtained from input-output relationship. Then, learning gain matrix is calculated from the estimates, and by using new learning gain matrix, learning speed can be enhanced. Simulation results show that the learning speed has been enhanced by applying the proposed method

Wearable System for Daily Activity Recognition Using Inertial and Pressure Sensors of a Smart Band and Smart Shoes

Human Activity Recognition (HAR) is a challenging task in the field of human-related signal processing. Owing to the development of wearable sensing technology, an emerging research approach in HAR is to identify user-performed tasks by using data collected from wearable sensors. In this paper, we propose a novel system for monitoring and recognizing daily living activities using an off-the-shelf smart band and two smart shoes. The system aims at providing a useful tool for solving problems regarding body part placement, fusion of multimodal sensors and feature selection for a specific set of activities. The system collects inertial and plantar pressure data at wrist and foot to analyze and then, extract, select important features for recognition. We construct and compare two predictive models of classifying activities from the reduced feature set. A comparison of the classification for each wearable device and a fusion scheme is provided to identify the best body part for activity recognition: either the wrist or the feet. This comparison also demonstrated the effective HAR performance of the proposed system

Assimilation of Precipitation Measurement Missions Microwave Radiance Observations With GEOS-5

The Global Precipitation Mission (GPM) Core Observatory satellite was launched in February, 2014. The GPM Microwave Imager (GMI) is a conically scanning radiometer measuring 13 channels ranging from 10 to 183 GHz and sampling between 65 S 65 N. This instrument is a successor to the Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI), which has observed 9 channels at frequencies ranging 10 to 85 GHz between 40 S 40 N since 1997. This presentation outlines the base procedures developed to assimilate GMI and TMI radiances in clear-sky conditions, including quality control methods, thinning decisions, and the estimation of, observation errors. This presentation also shows the impact of these observations when they are incorporated into the GEOS-5 atmospheric data assimilation system

All-Sky Microwave Imager Data Assimilation at NASA GMAO

Efforts in all-sky satellite data assimilation at the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center have been focused on the development of GSI configurations to assimilate all-sky data from microwave imagers such as the GPM Microwave Imager (GMI) and Global Change Observation Mission-Water (GCOM-W) Advanced Microwave Scanning Radiometer 2 (AMSR-2). Electromagnetic characteristics associated with their wavelengths allow microwave imager data to be relatively transparent to atmospheric gases and thin ice clouds, and highly sensitive to precipitation. Therefore, GMAOs all-sky data assimilation efforts are primarily focused on utilizing these data in precipitating regions. The all-sky framework being tested at GMAO employs the GSI in a hybrid 4D-EnVar configuration of the Goddard Earth Observing System (GEOS) data assimilation system, which will be included in the next formal update of GEOS. This article provides an overview of the development of all-sky radiance assimilation in GEOS, including some performance metrics. In addition, various projects underway at GMAO designed to enhance the all-sky implementation will be introduced

Assimilating All-Sky Microwave Radiance Data to Improve NASA GEOS Forecasts and Analysis

The NASA Global Modeling and Assimilation Office (GMAO) has been pursuing efforts to utilize all-sky (clear+cloudy+precipitating) MW radiance data and has developed a system to assimilate all-sky GPM Microwave Imager (GMI) radiance data in the Goddard Earth Observing System (GEOS) during the last PMM funding period. The system provides additional constraints on the analysis process near the storm regions and adjusts the geophysical parameters such as precipitation, cloud, moisture, surface pressure, and wind by combining information from GMI radiance measurements and model forecasts in an optimal manner. The system proved that assimilating the GMI all-sky radiance data improve the GEOS atmospheric analyses and forecasts. This all-sky data framework has been included in the GEOS Forward Processing (FP) system since July 11, 2018 and assimilates all-sky GMI data in real-time for GEOS global analysis and forecast production at the GMAO. We are currently extending this all-sky GMI radiance data assimilation system to assimilate more all-sky MW radiance data from other sensors such as the Microwave Humidity Sounder (MHS), the Advanced Technology Microwave Sounder (ATMS), the Special Sensor Microwave Imager/Sounder (SSMIS), Advanced Microwave Scanning Radiometer 2 (AMSR2), and the Sounder for Atmospheric Profiling of Humidity in the Intertropics by Radiometery (SAPHIR) onboard the GPM constellation spacecrafts. Preliminary results from this extended all-sky system show increased benefit from cloud- and precipitation-affected MW radiances with much larger spatial and temporal coverages compared to the all-sky system assimilating GMI alone and improved GEOS forecast skills especially for lower tropospheric humidity fields

A Study of Micronucleus Induction with Methyl Formate and 2-Methylbutane in Bone Marrow Cells of Male ICR Mice

Objectives: We investigated the genotoxicity of two chemicals, methyl formate and 2-methylbutane, using male ICR mice bone marrow cells for the screening of micronucleus induction. Although these two chemicals have already been tested numerous times, a micronucleus test has not been conducted and the amounts used have recently been increased.Methods: 7 week male ICR mice were tested at dosages of 250, 500, and 1,000mg/kg for methyl formate and 500, 1,000, and 2,000mg/kg for 2-methlybutane, respectively. After 24 hours of oral administration with the two chemicals, the mice were sacrificed and their bone marrow cells were prepared for smearing slides.Results: As a result of counting the micronucleated polychromatic erythrocyte (MNPCE) of 2,000 polychromatic erythrocytes (PCE), all treated groups expressed no statistically significant increase of MNPCE compared to the negative control group. There were no clinical signs related with the oral exposure of these two chemicals.Conclusion: It was concluded that the two chemicals did not induce micronucleus in the bone marrow cells of ICR mice, and there was no direct proportion with dosage. These results indicate that the two chemicals have no mutagenic potential under each study condition

Clinical Implications of Residual Urine in Korean Benign Prostatic Hyperplasia (BPH) Patients: A Prognostic Factor for BPH-Related Clinical Events

Purpose Although post-void residual urine (PVR) is frequently utilized clinically in patients with benign prostatic hyperplasia (BPH), mainly because of its procedural simplicity, its role as a clinical prognostic factor, predictive of treatment goals, is still under much dispute. We investigated the predictive value of PVR for BPH-related clinical events including surgery, acute urinary retention (AUR), and admission following urinary tract infection (UTI). Methods From January to June of 2006, patients over 50 years of age who were diagnosed with BPH for the first time at the outpatient clinic and were then treated for at least 3 years with medications were enrolled in this study. The variables of patients who underwent surgical intervention for BPH, had occurrences of AUR, or required admission due to UTI (Group 1, n=43) were compared with those of patients who were maintained with medications only (Group 2, n=266). Results Group 1 had a significantly higher PVR, more severe symptoms, and a larger prostate at the time of the initial diagnosis in both the univariate and the multivariate analysis. In the 39 patients who underwent BPH-related surgery, although there was a significant change in Qmax at the time of surgery (mean, 13.1 months), PVR and the symptom score remained unchanged compared with the initial evaluation. In the receiver-operating characteristic curve analysis, the area under the curve of Group 1 was in the order of prostate volume (0.834), PVR (0.712), and symptom score (0.621). When redivided by arbitrarily selected PVR cutoffs of 50 mL, 100 mL, and 150 mL, the relative risk of clinical BPH progression was measured as 3.93, 2.61, and 2.11. Conclusions These data indicate that, in the symptomatic Korean population, increased PVR at baseline is a significant indicator of BPH-related clinical events along with increased symptom score or prostate volume