Improving Magnitude Response of Comb Two-Stage Structure Using Simple Multiplierless Filters

Author(s):  
G. Jovanovic Dolecek
2008 ◽  
Vol E91-C (6) ◽  
pp. 894-902
Author(s):  
T. SATO ◽  
I. MATSUMOTO ◽  
S. TAKAGI ◽  
N. FUJII
Keyword(s):  

2019 ◽  
Vol 297 (11-12) ◽  
pp. 1507-1517 ◽  
Author(s):  
Manuchar Gvaramia ◽  
Gaetano Mangiapia ◽  
Vitaliy Pipich ◽  
Marie-Sousai Appavou ◽  
Sebastian Jaksch ◽  
...  

Abstract While spherical particles are the most studied viscosity modifiers, they are well known only to increase viscosities, in particular at low concentrations of approx. 1%. Extended studies and theories on non-spherical particles in simple fluids find a more complicated behavior, but still a steady increase with increasing concentration. Involving platelets in combination with complex fluids—in our case, a bicontinuous microemulsion—displays an even more complex scenario that we analyze experimentally and theoretically as a function of platelet diameter using small angle neutron scattering, rheology, and the theory of the lubrication effect, to find the underlying concepts. The clay particles effectively form membranes in the medium that itself may have lamellar aligned domains and surfactant films in the case of the microemulsion. The two-stage structure of clay and surfactant membranes explains the findings using the theory of the lubrication effect. This confirms that layered domain structures serve for lowest viscosities. Starting from these findings and transferring the condition for low viscosities to other complex fluids, namely crude oils, even lowered viscosities with respect to the pure crude oil were observed. This strengthens our belief that also here layered domains are formed as well. This apparent contradiction of a viscosity reduction by solid particles could lead to a wider range of applications where low viscosities are desired. The same concepts of two-stage layered structures also explain the observed conditions for extremely enhanced viscosities at particle concentrations of 1% that may be interesting for the food industry.


2018 ◽  
Vol 28 (9) ◽  
pp. 2570-2582 ◽  
Author(s):  
Jungsoon Choi ◽  
Andrew B Lawson

In space–time epidemiological modeling, most studies have considered the overall variations in relative risk to better estimate the effects of risk factors on health outcomes. However, the associations between risk factors and health outcomes may vary across space and time. Especially, the temporal patterns of the covariate effects may depend on space. Thus, we propose a Bayesian two-stage spatially dependent variable selection approach for space–time health data to determine the spatially varying subsets of regression coefficients with common temporal dependence. The two-stage structure allows reduction of the spatial confounding bias in the estimates of the regression coefficients. A simulation study is conducted to examine the performance of the proposed two-stage model. We apply the proposed model to the number of inpatients with lung cancer in 159 counties of Georgia, USA.


2016 ◽  
Vol 119 ◽  
pp. 91-107 ◽  
Author(s):  
Xiangmin Ma ◽  
Yuanfu Shao ◽  
Zhen Wang ◽  
Mengzhuo Luo ◽  
Xianjia Fang ◽  
...  

2020 ◽  
Vol 54 (6) ◽  
pp. 1657-1671
Author(s):  
Samaneh Esfidani ◽  
Farhad Hosseinzadeh Lotfi ◽  
Shabnam Razavyan ◽  
Ali Ebrahimnejad

Two-stage production systems are often encountered in many real applications where the production process is divided into two processes. In contrast to the conventional data envelopment analysis (DEA) models, two-stage DEA models take the operations of the internal processes into account. A number of studies have used two-stage DEA models in order to evaluate the performance of decision making units (DMUs) having a network structure. In this paper, we use a non-radial DEA model called the network slacks-based measure (NSBM) model to measure the efficiency of a system with a multi-period two-stage structure. Then we describe the properties of the proposed model in details. Moreover, we shall decompose the overall efficiency of the system over a number of time periods as a weighted average of the efficiency in each period. The efficiency of the stages, in respect to the entire periods shall be decomposed in terms of the weighted average efficiency of the stages in each period. Finally, the real data of Mellat bank branches in Tehran extracted from extant literature is used to illustrate the proposed approach.


Micromachines ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 198 ◽  
Author(s):  
Yi Cui ◽  
Yongbo Zhang ◽  
Yuliang Huang ◽  
Zhihua Wang ◽  
Huimin Fu

Indoor navigation has been developing rapidly over the last few years. However, it still faces a number of challenges and practical issues. This paper proposes a novel WiFi/MEMS integration structure for indoor navigation. The two-stage structure uses the extended Kalman filter (EKF) to fuse the information from WiFi/MEMS sensors and contains attitude-determination EKF and position-tracking EKF. In the WiFi part, a partition solution called “moving partition” is originally proposed in this paper. This solution significantly reduces the computation time and enhances the performance of the traditional Weighted K-Nearest Neighbors (WKNN) method. Furthermore, the direction measurement is generated utilizing WiFi positioning results, and a “turn detection” is implemented to guarantee the effectiveness. The navigation performance of the presented integration structure has been verified through indoor experiments. The test results indicate that the proposed WiFi/MEMS solution works well. The root mean square (RMS) position error of WiFi/MEMS is 0.7926 m, which is an improvement of 20.59% and 36.60% when compared to MEMS and WiFi alone. Besides, the proposed algorithm still performs well with very few access points (AP) available and its stability has been proven.


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