An Automatic Paperless Velocity Measuring and Recording System

2014 ◽  
Vol 889-890 ◽  
pp. 745-748
Author(s):  
Jian Sheng Cao ◽  
Wan Jun Zhang ◽  
Xin Hua Zeng

Automatic monitoring of hydrologic properties such as water velocity at short-time intervals is critical for understanding watershed eco-hydrological processes. This can also be used to study the laws of stream flows and interactions ecological process. The advent of modern electronic technology (and the near-perfection of especially sensor and data collection technologies), has made it possible to use automatic monitoring systems to continuously measure hydrologic properties at short-time intervals. This paper introduces one such paperless flow velocity measuring/recoding system. The system uses a photoelectric sensor that is mainly comprised of photoelectric velocity sensor and pulse recorder. The system uses propellers (with reflective panels and photoemission cells) to transform flow velocities into optical pulse signals. It also uses photosensitive tubes to transform optical pulse signals into electric pulse signals. The electric pulse counts (generated in unit time) are recorded via pulse recorders. This therefore accomplishes automatic monitoring and continuous recording of fluid flow velocity.

2016 ◽  
Vol 136 (12) ◽  
pp. 891-897 ◽  
Author(s):  
Katsuhiro Matsuda ◽  
Kazuhiro Misawa ◽  
Hirotaka Takahashi ◽  
Kenta Furukawa ◽  
Satoshi Uemura

Author(s):  
Elena Yu. Balashova ◽  
◽  
Lika I. Mikeladze ◽  
Elena K. Kozlova ◽  
◽  
...  

2019 ◽  
Vol 11 (24) ◽  
pp. 2991 ◽  
Author(s):  
Jin Yan ◽  
Mingyang Lv ◽  
Zhixing Ruan ◽  
Shiyong Yan ◽  
Guang Liu

A surge-type glacier is a special and dangerous type of glacier, which can advance quickly in a short-time with cycles. Glaciers in the Yangtze River headwater are generally acknowledged to be in a stable state. However, not all of those glaciers are stable. In this paper, five glaciers from the Yangtze River headwater glacier were selected as the experimental subjects, and multi-source remote sensing images were used to study and analyze the surge behavior over the past 30 years. Based on the Landsat series data, ERS-2, and ENVISAT radar data, this paper extracts the glacier centerline information, glacial area information, and glacial flow velocity during different time periods from 1988 to 2018, which are used to monitor the active periods of glacier surges. We found three surge-type glaciers in the study area. The glacial characteristics of the three glaciers showed some drastic changes, they can advance quickly nearly 800 m in active periods, their area change can reach 2.0 × 106 m2, and their flow velocity can suddenly increase by dozens of times. Surging periods and the initiated time of the three glaciers are different, which are locked in 1997, 2003, and 1997–1998. All those surges ended within one to two years. We suggest that the surges in this paper are dominated by hydrological conditions.


Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1213
Author(s):  
Ahmed Aljanad ◽  
Nadia M. L. Tan ◽  
Vassilios G. Agelidis ◽  
Hussain Shareef

Hourly global solar irradiance (GSR) data are required for sizing, planning, and modeling of solar photovoltaic farms. However, operating and controlling such farms exposed to varying environmental conditions, such as fast passing clouds, necessitates GSR data to be available for very short time intervals. Classical backpropagation neural networks do not perform satisfactorily when predicting parameters within short intervals. This paper proposes a hybrid backpropagation neural networks based on particle swarm optimization. The particle swarm algorithm is used as an optimization algorithm within the backpropagation neural networks to optimize the number of hidden layers and neurons used and its learning rate. The proposed model can be used as a reliable model in predicting changes in the solar irradiance during short time interval in tropical regions such as Malaysia and other regions. Actual global solar irradiance data of 5-s and 1-min intervals, recorded by weather stations, are applied to train and test the proposed algorithm. Moreover, to ensure the adaptability and robustness of the proposed technique, two different cases are evaluated using 1-day and 3-days profiles, for two different time intervals of 1-min and 5-s each. A set of statistical error indices have been introduced to evaluate the performance of the proposed algorithm. From the results obtained, the 3-days profile’s performance evaluation of the BPNN-PSO are 1.7078 of RMSE, 0.7537 of MAE, 0.0292 of MSE, and 31.4348 of MAPE (%), at 5-s time interval, where the obtained results of 1-min interval are 0.6566 of RMSE, 0.2754 of MAE, 0.0043 of MSE, and 1.4732 of MAPE (%). The results revealed that proposed model outperformed the standalone backpropagation neural networks method in predicting global solar irradiance values for extremely short-time intervals. In addition to that, the proposed model exhibited high level of predictability compared to other existing models.


Fluids ◽  
2018 ◽  
Vol 3 (3) ◽  
pp. 63 ◽  
Author(s):  
Thomas Meunier ◽  
Claire Ménesguen ◽  
Xavier Carton ◽  
Sylvie Le Gentil ◽  
Richard Schopp

The stability properties of a vortex lens are studied in the quasi geostrophic (QG) framework using the generalized stability theory. Optimal perturbations are obtained using a tangent linear QG model and its adjoint. Their fine-scale spatial structures are studied in details. Growth rates of optimal perturbations are shown to be extremely sensitive to the time interval of optimization: The most unstable perturbations are found for time intervals of about 3 days, while the growth rates continuously decrease towards the most unstable normal mode, which is reached after about 170 days. The horizontal structure of the optimal perturbations consists of an intense counter-shear spiralling. It is also extremely sensitive to time interval: for short time intervals, the optimal perturbations are made of a broad spectrum of high azimuthal wave numbers. As the time interval increases, only low azimuthal wave numbers are found. The vertical structures of optimal perturbations exhibit strong layering associated with high vertical wave numbers whatever the time interval. However, the latter parameter plays an important role in the width of the vertical spectrum of the perturbation: short time interval perturbations have a narrow vertical spectrum while long time interval perturbations show a broad range of vertical scales. Optimal perturbations were set as initial perturbations of the vortex lens in a fully non linear QG model. It appears that for short time intervals, the perturbations decay after an initial transient growth, while for longer time intervals, the optimal perturbation keeps on growing, quickly leading to a non-linear regime or exciting lower azimuthal modes, consistent with normal mode instability. Very long time intervals simply behave like the most unstable normal mode. The possible impact of optimal perturbations on layering is also discussed.


2009 ◽  
Vol 56 (11) ◽  
pp. 2065-2074 ◽  
Author(s):  
J. Sarrazin ◽  
P. Rodier ◽  
M.K. Tivey ◽  
H. Singh ◽  
A. Schultz ◽  
...  

2014 ◽  
Vol 2014 ◽  
pp. 1-4 ◽  
Author(s):  
Vahid Yousefi Babadi ◽  
Leila Sadeghi ◽  
Kobra Shirani ◽  
Ali Akbar Malekirad ◽  
Mohammad Rezaei

Manganese (Mn) is a naturally occurring element and an essential nutrient for humans and animals. However, exposure to high levels of Mn may cause neurotoxic effects. Accumulation of manganese damages central nervous system and causes Parkinson’s disease-like syndrome called manganism. Mn neurotoxicity has been suggested to involve an imbalance between the DAergic and cholinergic systems. The pathological mechanisms associated with Mn neurotoxicity are poorly understood, but several reports have established it is mediated by changing of AChE activity that resulted in oxidative stress. Therefore we focused the effect of Mn in AChE activity in the rat’s brain by MnCl2injection intraperitoneally and analyzed their brains after time intervals. This study used different acute doses in short time course and different chronic doses at different exposing time to investigate which of them (exposing dose or time) is more important in Mn toxic effect. Results showed toxic effect of Mn is highly dose dependent and AChE activity in presence of chronic dose in 8 weeks reaches acute dose in only 2 days.


Author(s):  
Christian Herff ◽  
Dean J. Krusienski

AbstractClinical data is often collected and processed as time series: a sequence of data indexed by successive time points. Such time series can be from sources that are sampled over short time intervals to represent continuous biophysical wave-(one word waveforms) forms such as the voltage measurements representing the electrocardiogram, to measurements that are sampled daily, weekly, yearly, etc. such as patient weight, blood triglyceride levels, etc. When analyzing clinical data or designing biomedical systems for measurements, interventions, or diagnostic aids, it is important to represent the information contained within such time series in a more compact or meaningful form (e.g., noise filtering), amenable to interpretation by a human or computer. This process is known as feature extraction. This chapter will discuss some fundamental techniques for extracting features from time series representing general forms of clinical data.


1977 ◽  
Vol 162 (3) ◽  
pp. 493-499 ◽  
Author(s):  
R George ◽  
T Ramasarma

1. Administration of noradrenaline increased the incorporation of [1-14C]acetate into hepatic sterols and the activity of liver microsomal 3-hydroxy-3-methylglutaryl-CoA reductase. 2. The stimulation was observed at short time-intervals with a maximum at 4h and was progressive with increasing concentrations of noradrenaline. 3. Protein synthesis de novo was a necessary factor for the effect. 4. The stimulatory effect was not mediated through the adrenergic receptors, but appears to involve a direct action of the hormone within the hepatocyte.


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