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The research presented herein tests the hypothesis that cumulative damage in the material under random dynamic compression will result in a reduction in the overall stiffness as well as an increase in the overall damping of the element.
The paper tests the hypothesis that cumulative damage in the material under random dynamic compression will result in a reduction in the overall stiffness as well as an increase in the overall damping of the structure.
The effectiveness of establishing the level of damage by quantifying the modal characteristics obtained from measuring the frequency response function (FRF) is critical and often depends of the type of structure being studied as well as the quality of the experimental data.
Relative Static Stiffness (%) . 0 Figure 5: Shift in the stiffness and correlation between static and dynamic stiffness Fig. 7 shows the average FRF data set as well as the corresponding natural frequencies (black dot) for a typical experiment (box 3).

Removal of coal-fired pollutants using a novel composite collector in a wet electrostatic precipitator Jian Zhao1, a, Jingcai Chang2,b, Jiaqiu Song2c,Aiping Tao3,d, Mingfeng Gao3,e 1 China Energy Conservation and Emission Reduction Co.
The new wet ESP device acts in synergy with WFGD and SCR systems for controlling coal-fired pollutants emissions and solves the adverse impacts caused by wet flue gas desulfurization (WFGD) and selective catalytic reduction (SCR) systems at the same time.
The data shown in Fig.5 (b) indicated that different emitters experienced significant differences in collection efficiency based on discharge energy, especially with shorter gas treatment time.
The data indicated that the characteristic of barbed wires served as emitter electrodes was superior to that of diamond-shaped wires.

This rapid development in consequence affects a reduction on the ground water supply.
Methodology A quantitative analysis was used in this study and the required data are as follows: (1) the annual precipitation and (2) the water need of the inhabitants.
Jakarta Rainfall Data.

It can be concluded that the reduction of the moisture content of the grain, is considered very complex and, depending on the method and drying conditions, can substantially provokes breaking and cracks, which reduces final product quality.
Me (d.b) R (mm) L (mm) o (oC) f (oC) t (min) 40 28.44% 0.04 0.18 0.083 1.25 1.61 26.8 39.8 1260 70 6.73% 0.07 0.25 0.044 1.25 1.61 26.6 67.0 950 Results and Discussion Based on the current experimental drying characteristic data, we plot moisture content and surface temperature kinetics.
By comparing the data between the two curves, it can be seen that the temperature of the drying air influences strongly the drying time, which can give rise to high temperature gradients in the solid, which induces thermal stresses and fast heating.

The analysis results showed that the structural behavior of fire-damaged RC beam was able to be simulated by using FE analysis with consideration of the reduction of material capacity due to fire.
On the structural side, enough test data to predict the shear behavior of element were not acquired due to the difficulty of test.
This can be converted to a reduced strength which will be data for structural analysis for the RC beam.

Computational experience on randomly generated data sets and an industrial case shows that improved genetic algorithm gives superior results than the genetic algorithm without improving for storage location assignment with ordering restriction.
The problem can be defined as: given P cargos, their average demand and planned inventory levels for T periods and the layout of the storage area divided into lattice of storage locations, the problem is to establish classes of products and allocate them to storage locations so that the total cost of order picking and storage space is minimized in a single command warehouse exploiting the reduction in area because of clubbing the parts into classes.
Computational experience on randomly generated data sets shows that superior crossover and mutation operators play a very important role in the performance of the GA.

Biosorption equilibrium data were best described by Langmuir isotherm model.
Conventional methods for removing metals from aqueous solutions include chemical precipitation, chemical oxidation or reduction, ion exchange, electrochemical treatment, reverse osmosis, membrane technologies and evaporation recovery.
Based on the correlation coefficient R2, it is clear that both the Langmuir(Fig 4) and Freundlich(Fig 5) isotherm models fitted with the experimental data well, and the former model was a better fit than the latter.

The approaches such as the carrier number and the Hooge mobility fluctuations used for the analysis of the noise sources are illustrated through experimental data obtained on advanced CMOS generations.
The approaches such as the carrier number (CNF) and the Hooge mobility (HMF) fluctuations used for the analysis of noise sources will be presented and illustrated through experimental data obtained on advanced CMOS generations.
The value of a is about 10 times lower than for pure SiO2 gate dielectric, which could be due to the deeper trap location, resulting in a more remote character of the Coulomb scattering and, in turn, a reduction of a.

The honeycomb core Design of Modular based Wine Packaging Wu Jian1,a, Du Yanping2,b, Zhang Yang 3,c (1, 2, 3, Beijing Institute of Graphic Communication, Beijing, 102600) azaonin@126.com, bduyanping@bigc.edu.cn, czhangyang@bigc.edu.cn Keywords: Honeycomb core, Modular, Wine Package, Honeycomb Structure Abstract: Use the standard 750ml bottle of red wine packaging design to explore the honeycomb core module of digital design and green manufacturing approach to virtual design and virtual manufacturing of new structural approach to packaging product development, through the final product form of reverse thrust reversers honeycomb core module data and processing forms, and finally the use of CNC machining centers cellular module manufacture.
To 750ml standard bottle as a model for wine packaging design innovation, exploring honeycomb core module based on digital design and green manufacturing methods to three-dimensional software for virtual design, virtual assembly product function modules for cellular manufacturing approach to new product development package structure , product user experience departure, according to the module's unique cellular material of the appearance of the product packaging and liner cushioning material integrated design, in order to achieve a unique visual beauty and a smooth user experience, through the final product form cellular reverse thrust reversers Core module data and processing forms, and finally the use of CNC machining centers CNC machining cell module production, from processing, packaging, transportation, recycling the complete product life cycle of sustainable redesign.
Comprehensive consideration of the above factors, to achieve the structural honeycomb core module innovation, we must simplify the model, from design concept and user experience reduction products, starting from the product usage scenarios thrust reversers, clear goals and tasks designed to stimulate groundbreaking thinking, in order to obtain product development success.

However, when we happy for the achievement, in front of the “strange phenomenon” in reality, we run into another confusion; front one side, people are trying to enhance and improve the earth observing technology and measuring technology in the hope of getting more and more remote sensing image data, besides a mass of earth observation data has been acquired or in processing.
Assume the offerable parallel computing nodes numbers are K, then separate the original image into K pieces with the same size by rows or columns, distribute K data blokes into K nodes separately with the data provided by MPICH, each node doing feature extraction respectively to each data block, and collect the features by the MPICH provided functions, finally achieve the resulting image by clustering in the main process.
Table1 records the experimental data, each of which is the average of three times.
Figure5 shows the Comparison of experimental data to the different number of nodes.
The procedure of parallel processing // Broadcast arguments MPI_Bcast(&height, 1, MPI_INT, mainprocessid, MPI_COMM_WORLD); MPI_Bcast(&width, 1, MPI_INT, mainprocessid, MPI_COMM_WORLD); // Send image data MPI_Scatter(imagedata, myheight*width, MPI_UNSIGNED_CHAR, data, myheight*width, MPI_UNSIGNED_CHAR, mainprocessid, MPI_COMM_WORLD); // Get Symbiosis and Get Statistical Features in each node GetSymbiosis(SimpleSysMatrix, data_in, WndSize, WndSize, 1, 1); GetStatisticalFeatures(Feature, data_in, WndSize, SimpleSysMatrix, tag); // Gather feature data MPI_Gather(Feature1, dimen * myheight*width/WndSize/WndSize, MPI_DOUBLE, recvfeature1, dimen * myheight*width/WndSize/WndSize, MPI_DOUBLE, mainprocessid, MPI_COMM_WORLD); // Cluster Cluster_KMeans(recvfeature, numprocs * myheight*width/WndSize/WndSize, dimen, result, classnumber); Figure 2.