scholarly journals Appendix G: Weighting Coefficient Vectorsλ andγ

2009 ◽  
pp. 659-673
Keyword(s):  
Weighting Coefficient

scholarly journals Empirical Framework for a Relative Sustainability Evaluation of Urbanization on the Water–Energy–Food Nexus Using Simultaneous Equation Analysis

2019 ◽  
Vol 16 (6) ◽  
pp. 901 ◽  
Author(s):  
Chihhao Fan ◽  
Chun-Yueh Lin ◽  
Ming-Che Hu
Keyword(s):  
Negative Impact ◽  
Model Simulation ◽  
Supply And Demand ◽  
Simultaneous Equation ◽  
Equation Model ◽  
Environmental Conservation ◽  
Population Increase ◽  
Weighting Coefficient ◽  
Energy Structure ◽  
On The Road

The water–energy–food (WEF) nexus attracts much attention due to the elevated public concern regarding environmental conservation and sustainability. As we head into a new era of civilization, population increase and modernized lifestyles have led to an increasing need for water, energy, and food. However, severe hydrological precipitation significantly impacts agricultural harvest, and such influence becomes more apparent under the influence of climate change. Meanwhile, the major method of electricity generation (i.e., fossil fuel burning) has a negative impact on the environment. These inevitable threats are crucial and have to be dealt with for a society on the road towards sustainability. In the present study, an integrated evaluation of the WEF nexus was conducted for two areas with different levels of urbanization using empirical multiple linear regression in a simultaneous equation model (SEM). By incorporating the collected data into the SEM, the weighting coefficient of each identified variable was obtained, and the nexus implication was assessed in model simulation at different scenarios considering the population growth, agro-technology advancement, energy structure improvement, and available water resources. In the simulated results, three observations were found: (1) the rural area is more sustainable than the urban one; (2) the sustainability for both the investigated areas is significantly subject to their water supply and demand; and (3) food production was found to have a less important effect on the sustainable development of the urban area. This study identified the key factors in the WEF nexus exploration, which are economically and environmentally important for resource allocation. An empirical model was developed to correlate sustainable achievement with WEF management, as well as strategic policies that should be implemented under the pressure of urbanization.

scholarly journals VLSI Architectures for Image Interpolation: A Survey

VLSI Design ◽  
2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
C. John Moses ◽  
D. Selvathi ◽  
V. M. Anne Sophia
Keyword(s):  
Large Scale ◽  
Piecewise Linear ◽  
Complementary Metal Oxide Semiconductor ◽  
Image Interpolation ◽  
Hardware Architecture ◽  
Oxide Semiconductor ◽  
Weighting Coefficient ◽  
Vlsi Architectures ◽  
Different Types ◽  
Memory Buffer

Image interpolation is a method of estimating the values at unknown points using the known data points. This procedure is used in expanding and contrasting digital images. In this survey, different types of interpolation algorithm and their hardware architecture have been analyzed and compared. They are bilinear, winscale, bi-cubic, linear convolution, extended linear, piecewise linear, adaptive bilinear, first order polynomial, and edge enhanced interpolation architectures. The algorithms are implemented for different types of field programmable gate array (FPGA) and/or by different types of complementary metal oxide semiconductor (CMOS) technologies like TSMC 0.18 and TSMC 0.13. These interpolation algorithms are compared based on different types of optimization such as gate count, frequency, power, and memory buffer. The goal of this work is to analyze the different very large scale integration (VLSI) parameters like area, speed, and power of various implementations for image interpolation. From the survey followed by analysis, it is observed that the performance of hardware architecture of image interpolation can be improved by minimising number of line buffer memory and removing superfluous arithmetic elements on generating weighting coefficient.

Structure Optimization Design for the Bed of Gear Hobbing Machine

2013 ◽  
Vol 765-767 ◽  
pp. 176-180
Author(s):  
Rong Chuang Zhang ◽  
Ao Xiang Liu ◽  
Jun Wang ◽  
Wan Shan Wang
Keyword(s):  
Optimization Design ◽  
Optimal Solution ◽  
Element Model ◽  
Weighting Coefficient ◽  
Design Parameters ◽  
Analytic Hierarchy ◽  
Design Variables ◽  
Gear Hobbing ◽  
Vibration Modal ◽  
Hierarchy Process

In the optimization design of the gear hobbing machine bed, the finite element model is build and the static analysis and vibration modal analysis are performed. Then sensitivity analysis is used to gain the main design parameters which influence the bed property most. Furthermore, the multi-objective optimization design of the bed is performed in ANSYS Workbench with these design parameters as the design variables. At last, after all optimum proposals are showed up, Analytic Hierarchy Process is used to determine the weighting coefficient, and the most optimal solution is found out. As a result, the dynamic and static performances of the machine bed are improved under control of the machine bed mass.

Imaging the Geology Ahead of a Tunnel Using Seismics and Adaptive Polarization Analysis

2020 ◽  
Vol 25 (2) ◽  
pp. 189-198
Author(s):  
Lei Chen ◽  
Chao Fu ◽  
Xinji Xu ◽  
Lichao Nie
Keyword(s):  
Time Window ◽  
Geophysical Methods ◽  
Weighting Coefficient ◽  
Tunnel Construction ◽  
Polarization Analysis ◽  
Polarization Direction ◽  
Tunnel Face ◽  
Seismic Method ◽  
Imaging Results ◽  
Geological Conditions

The seismic method is one of the main geophysical methods that are widely used to image the geology ahead of tunnels during tunnel construction. However, owing to the complex environment and limited observation aperture in a tunnel, symmetric false results (that appear in imaging results but not in the actual environment) frequently occur in imaging results. In a symmetric false reflection, false and true reflection points are axisymmetric around the tunnel axis. Such false results frequently cause errors in the interpretation of the geological conditions ahead of a tunnel face. To overcome this problem, a seismic method that uses adaptive polarization analysis was adopted to better image geological conditions. Based on an adaptive time window, the polarization characteristics of seismic signals were analyzed to calculate the main polarization direction. The symmetric false results in imaging results were suppressed by adopting a weighting coefficient based on the angle between the main polarization direction and ray direction. Numerical simulations revealed the superiority of the method when applied to synthetic data processing. Moreover, the method was applied to a diversion tunnel. The method successfully identified the fracture zones ahead of the tunnel face, thus significantly enhancing the safety of tunnel construction.

scholarly journals Design of Wideband Dual-Polarized Planar Antenna Using Multimode Concept

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Deqiang Yang ◽  
Huiling Zeng ◽  
Yubo Wen ◽  
Meng Zou ◽  
Jin Pan
Keyword(s):  
Frequency Band ◽  
Characteristic Pattern ◽  
Operating Frequency ◽  
Weighting Coefficient ◽  
Planar Antenna ◽  
High Isolation ◽  
Operating Band ◽  
Characteristic Modes ◽  
Physical Insight ◽  
Dual Polarized

A wideband dual-polarized planar antenna is designed and analyzed by using the theory of characteristic modes (TCM). The eigenvalue, eigencurrent, characteristic pattern, and modal weighting coefficient are analyzed to bring physical insight to this kind of antenna. The results demonstrate that there are two modes resonant in the operating band for each polarization, which have been combined to form a wider frequency band. A bandwidth of 60.2% (1.72–3.2 GHz) for VSWR < 1.5 with high isolation of 32 dB is achieved simultaneously. The size of the radiator structure is 0.33λ0× 0.33λ0× 0.22λ0(λ0refers to the center operating frequency).

Motion Control of a Hyper Redundant Manipulator Built by Serially Connecting Many Parallel Mechanism Units with a Few DOF

2010 ◽  
Vol 4 (4) ◽  
pp. 364-371 ◽  
Author(s):  
Nobuyuki Iwatsuki ◽  
◽  
Norifumi Nishizaka ◽  
Koichi Morikawa ◽  
Koji Kondoh ◽  
...  
Keyword(s):  
Motion Control ◽  
Kinematic Analysis ◽  
Parallel Mechanism ◽  
Inverse Kinematic ◽  
Weighting Coefficient ◽  
Redundant Manipulator ◽  
Output Displacement ◽  
Spatial Parallel Mechanism ◽  
Inverse Kinematic Analysis ◽  
Forward Kinematic

This paper describes the kinematic analysis and motion control of a hyper redundant robot built by serially connecting many units with a few DOF. Each unit of the manipulator is a spatial parallel mechanism with 3 DOF and is composed of 2 stages connected with 3 linear actuators, 7 spherical joints, and a center rod. The forward kinematic analysis of the manipulator based on the forward kinematics of each unit by numerical calculation was carried out. The inverse kinematic analysis, the iterative calculation so as to converge output error while output displacement is distributed into each unit with weighting coefficient, was proposed and formulated. Motion control of the robot was theoretically and experimentally examined based on the inverse kinematics. It was confirmed that a prototype with 3 units could generate the desired trajectories.

An Improved Particle Swarm Optimization

2013 ◽  
Vol 380-384 ◽  
pp. 1542-1545
Author(s):  
Yi Ni Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Weighting Coefficient ◽  
Random Disturbance ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Disturbance Term

By analyzing the current Particle Swarm Optimization, especially the analysis of weighting coefficient descending and random disturbance term improving, an improved Particle Swarm Optimization combining periodic weighting adjustment and random disturbance was put forward and its effectiveness is verified by experiments in this article.

Wind Speed Forecasting Based on Variable Weight Combination Model of Neural Network and Grey Model

2012 ◽  
Vol 217-219 ◽  
pp. 2654-2657
Author(s):  
Jian Zhang ◽  
Lun Nong Tan
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Wind Speed ◽  
Wind Farms ◽  
Grey Model ◽  
Weighting Coefficient ◽  
Forecasting Accuracy ◽  
Wind Speed Forecasting ◽  
Variable Weight ◽  
Artificial Neural Network Ann

The wind speed forecasting accuracy of artificial neural network(ANN) and grey model(GM) is poorly satisfied. Thus, we proposed a new variable weight combined (VWC) model, which was based on the ANN and GM, to improve the wind speed forecasting accuracy. VWC used weighting coefficient of different time to fit the two single models. The forecasting accuracy of VWC is higher than either of the two single models, and is also higher than the unchanged weight combination(UWC) model. Our data show a new method for wind speed forecasting and the reduction of auxiliary service costs of wind farms.

FBG Intrusion Recognition Algorithm Based on SVM

2012 ◽  
Vol 591-593 ◽  
pp. 1422-1427 ◽  
Author(s):  
Jian Wang
Keyword(s):  
Optical Fiber ◽  
Frequency Band ◽  
Time Domain ◽  
Recognition Algorithm ◽  
Vibration Sensor ◽  
Weighting Coefficient ◽  
Support Vector ◽  
Fiber Grating ◽  
University Of Technology

The perimeter security alarm system, with the core of vibration sensor based on FBG optical fiber invented by Wuhan University of Technology optical fiber research center, uses the changes of optical fiber grating stress wavelength to detect intrusion. As FBG wavelengths change when under stress, the intrusion detection is identified by the combination of signals time domain and frequency band domain. However, it is difficult to classify the data of signals time domain and frequency band domain because of the complexity of the actual conditions and the diversity of interference and intrusion. Therefore, applying SVM to train and process the classification features extracted from the various data acquisition can help to obtain the corresponding support vector and weighting coefficient. As a result, the effective classification of the field test data can be achieved by using SVM template method.

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