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The reduction capacity estimated by integrating the reduction current at the initial cycle was 300 mA h (g-tetratitanate) -1.
The capacity of 300 and 170 mA h g -1 corresponds to the reduction/oxidation of approximately 90% and 50% of Ti, respectively.
The data shown below were taken after fifth cycle.
Figure 4 shows reduction peak current density of the obtained thin film on cyclic voltammograms measured at various sweep rates.
Reduction peak current density of the obtaind thin film on cyclic voltammograms measured at various sweep rates.

The stiffness reduction factor equals lateral stiffness of authentic strips divided by lateral stiffness of imaginary ones, which should be gotten through experiments.
It is used to characterize the reduction of lateral stiffness of components compared with ones fixed at both ends and provide reference for subsequent calculation.
It is obvious that the experiment values of yield bearing capacity were very close to the predicted value and we can get the stiffness reduction factor mentioned before.
We can see that the smaller the aspect ratio is, the smaller the stiffness reduction factor will be.
Molch, et al., Identifying damage caused by the 2008 Wenchuan earthquake from VHR remote sensing data, J.

So we the authors of this research paper attempted to develop a soft computing technique to prognosticate CBR value by using Artificial Neural Network (ANN), a data driven technique.
They operate as black-box, model-free and adaptive tools to capture and learn significant structure in data.
Jakasa, et al), Neural networks for profiling stress history of clays from PCPT data (Pradeep U.
From our study we can conclude that ANN could be a good mathematical tool for prediction of CBR values, using data pattern rather than complicated laboratory procedures.
Dudani (2002), “Neural Networks for profiling stress history of clays from PCPT data”. journal of geotechnical geoenvironmental engineering, VOL 128, NO 7, July, 2002, pp 569-578

We have applied our proposal to text data mining in bioinformatics.
This technique is generally referred to as text data mining.
Due to the sheer size of extracted data, however, it is impossible to check for every individual piece of data.
In this new visualization paradigm, we implemented the method to take the union of the data from the previous time-stamped data, to filter less-frequent data and to emphasize high occurrence data.
We utilized the 3 rd dimension to display colorbanded rods for abstracting unstructured source data; and to display different time-stamped data for visualizing the history-line of the discovery process.

The base case of the system consists of the following data: Table 1.
Load Models Based on Consumption Profiles Description: This approach uses previously defined load profiles, based on historical data or market research, to model EV behavior.
Through training with historical data, neural networks can learn to identify complex patterns and predict future behavior.
Real-Time Simulation Models Description: These models allow for real-time simulation of the impact of EV load on the distribution network, using real-time data from sensors and monitoring systems.
Ziras, “A review of data sources for electric vehicle integration studies,” Renew.

The Research on Key Issues of Analysis of Basketball Vedio Fei Liu1, a 1 University of Electronic Science and Technology of China ,China a liufeiliuzhi@163.com Keywords: Sport video analysis, Shot segmentation, Shot coarse classification, Location of scoreboard Abstract: With the advent of multimedia technology and the information superhighway, storage and transmission of digital video is no longer a difficult job, different sports events directly led to the explosive growth of sports video data and therefore efficient sports video analysis is necessary.
Quantification and HSV Color Space Dimensionality Reduction.
HSV Histogram-based Dimension Reduction Shot Segmentation Algorithm.
Conclusions With the massive growth of sports video data, sports video analysis of urgency is growing.

According to foreign-related test data, mobile and equipment to reduce the weight of 10% each, can reduce energy consumption by 5% -8%, so the support vehicles carry lightweight design is necessary [1].
Fig. 4 Displacement nephogram Fig. 5 The stress deprogram Effect analysis Heavy duty rack weight made of 40Mn2 steel is 40.38kg; while for MC nylon light frame weight is only 22.5kg, compared with the heavy duty rack, weight reduction of 44.3%.
A whole column extending support vehicle loading machine equipped with the number at more than ten, which can complete the reduction, amounted to more than 226.8kg.
If the lightweight consider car, then ten support vehicle total weight reduction of 697.8kg, tractor traction on the supporting vehicle will be reduced.
Moreover, in the resources, energy and environmental problems have become increasingly prominent today, lightweight design to contribute to energy-saving emission reduction, environmental protection, promote the coordinated development of economy, society and environment, is worthy of promotion.

Data are collected in the form of points and the resulting file is called "point cloud" (Figure 1).
Because the automotive industry requires a high degree of accuracy, we can use only certain types of mechatronic systems of integrated control 3D with a laser and it is necessary a fairly high threshold of the data quality, the tolerances accepted in most cases being between ± 0.001 mm and ± 0.01 mm [11].
The scanned data can be transferred to any CAD file format and is accessible to a large number of equipment.
After a product has been made physically, it can be scanned and the resulting data can be compared with the geometric patterns and deviations (errors) up against the initial geometric model can be precisely determined [2].
Godin, "Accurate 3D acquisition of freely moving objects" in 2nd International Symposium on 3D Data Processing, Visualization, and Transmission, Thessaloniki, Greece.

The reduction in economic losses were compared caused by earthquake of various intensities for economic assessment of building seismic design code.
Thus, the above data should be processed accordingly.
Other data were processed in the same way.
The reduction in seismic damage loss was the difference between the loss before the reinforcement and that after the reinforcement.
Thus, the reduction in economic loss after reinforcement to fortification intensity 8 was 133 thousand RMB, and the economic benefit was 1.07.

Figure 1: X-Ray diffraction pattern of CCTO samples sintered at variation temperature Table 1: Lattice parameter,a of CCTO samples sintered at four different temperature Temperature (oC) Lattice Parameter, a (Å) 950 7.391 1000 7.390 1050 7.392 1100 7.391 The lattice parameter a, of all CCTO samples obtained from XRD’s data are tabulated in Table 1.
Dielectric constant, ε’ and dielectric loss, tan δ of all CCTO samples can be derived from impedance spectroscopy data.
Thus this reduction in defect density explains the initial reduction in the grain conductivity of the sample sintered at 1000oC.
This could be attributed to the reduction in secondary phases such as CuO and CaTiO2, which are present between the grains of CCTO [11].
Thus reduction in the conducting phases at higher sintering temperatures could explain the higher grain boundary resistance values of the samples.