Search results

This paper deals with those disparate approaches, discussing exhaustively the process and application of hydroforming, providing sufficient data to make readers identify the burgeoning areas of research.
The implementation of the response surface, using the moving least square regression model aims to determine the optimal solution for the minimisation of thinning, reduction of underfilling and accuracy of the final fillet radius at the bulge zone corner [21].
Researchers can now think of cost reduction, thereby utilising this to the best extent possible, enabling batch and mass production.

Hydrogen desorption data revealed that samples prepared at 2 hour could release hydrogen at lower temperature (343°C) than those samples prepared at 30 min and 1 hour.
In practice reduction of particle size was achieved through high energy ball-milling [13, 14], nano-confinement of MgH2 in carbon template[15], melt-infiltration[16], chemical vapor deposition[17], hydrogen plasma metal reaction[18], salt reduction[14] and solvated atom dispersion[19].

The RRA temper with retrogression at 180°C for 60 min improved electrical conductivity remarkably (reached 21.0MS/m), with only a 3% reduction in strength below T6 temper.
Each datum is the average of three samples.
Based on these measurements, some RRA treatments with electrical conductivities close to that of T73 temper, and only with some small reductions in strength below T6 temper.

Vacuum data were reported by [11].
The orientation is LT unless noted and data reported by Gasem for chromate inhibition are included for comparison [2,3].
From the polarization data in Figure 1, the solution with lowest Cl and highest MoO42- contents creates the most stable passive film.
The upper bound fcrit suggested by these data is equal (15 Hz) for the low and high MoO42 levels examined.
The decreasing ∆K experiment at 10 Hz (Figure 2) did not show molybdate inhibition, certainly at ∆K higher then 3 MPa√m, consistent with the data in Figure 4 showing that this frequency was near fcrit upper bound for ∆K of 6 MPa√m and R of 0.65.

Friction stir spot welding (FSSW) is a relatively new welding technique which has already been successfully commercially applied on automotive aluminum alloys which, in turn, lead to significant energy savings and infrastructure cost-reductions.
Currently there is limited data on the mechanical properties and microstructure of friction stir spot welded steel thus the current aim was to investigate how these parameters chamged as a function of some critical process variables.

This method combines the rating similarity and the user context similarity in the electronic commerce recommendation process to improve the prediction accuracy by efficiently managing the problem of data sparsity.
Introduction With the continuous development of all kinds of information processing technology, more and more people can access the digital resources, therefore, how to from a mass of data is convenient, quick access to the required information would come very naturally become very concerned about the problem.
Input Calculating user rating similarity Calculating user context similarity Prediction and Recommendation Selecting neighbors Combining the two similarity Figure 1 The algorithm steps 1) similarity calculation of similarity1 users based on user characteristic data; 2) the use of collaborative filtering algorithm, based on the user's rating data, calculation between the user similarity based on similarity2 score; 3) calculate the user the final similarity: similarity = percent* similarity1 + (1 - percent) * similarity2, where percent is the characteristics of the user similarity in the final similarity calculation based on the proportion of; 4) by using similarity numerical prediction score combined with traditional numerical algorithm.
This method combines the rating similarity and the user context similarity in the electronic commerce recommendation process to improve the prediction accuracy by efficiently managing the problem of data sparsity.
Kelleher, Experiments in sparsity reduction: Using clustering in collaborative recommenders, in Procs. of the Thirteenth Irish Conference on Artificial Intelligence and Cognitive Science, pp. 144–149.

In order to analyze the influence of cavitaing flow in the nozzle hole on spray, a coupling spray simulation was carried out with the output data of cavitaing flow in nozzles using FIRE v2010.
Facing the energy crisis and environmental pollution, energy saving and emission reduction have been a strategic point of the development of internal-combustion engine.
A transient nozzle flow simulation was carried out and the simulating data was written to a file with a predefined temporal resolution.
Geometrical, temporal and flow data allow the mapping of nozzle orifice field to spray inlet, adopting a primary break-up model to initialize the droplet phases.
The data of spray tip penetration and SMD are shown in fig.9.

The stress velocity exponent was evaluated from the dynamic fatigue testing data.
The experimental data were least squares fitted to the Equation 3.
A reduction in modulus in water and saliva, as well as a change from unimodal to bimodal strength distribution indicates that the most danger flaw grows resulting from stress corrosion.
The values of n in the range from 11 to 23 are in consent with our previously obtained data on dynamic fatigue of HA ceramics in an isotonic solution containing 0.9% NaCl (n = 12) [7].
It follows from the data in the Table, that the presence of alkali-metal ions, chlorine and HCO3 in the solution has an insignificant effect on stress corrosion.

To regulate the influence of Eigen-FLS when data from a test speaker for eigen-decomposition is improper, this paper proposes an EigenMLLR-like Eigen-FLS approach.
The linear interpolation technique utilized in this work is particularly useful to deal with the problem of sparse training data for FLS model establishments.
Only the first K eigenfls are kept and are significant because they possess the most information from speech data, thus being capable of representing all considered variations.
However, sufficient adaptation data is required to ensure accurate MLLR transformation estimation.
The robustness of the estimated Eigen-FLS model using Eq. (4) for a new speaker against a relatively small number of training data could then be ensured.

Data analysis CMCC is a typical enterprise with data intensive, holding vast amounts of smart phone sales data.
Data District The main sales area.
Then removed all the irrelevant data.
Hence the subsequent research should focus on the use of data mining and data warehouse technology, in order to more effectively support data analysis.
ST-DBSCAN: An algorithm for clustering spatial–temporal data, Data & Knowledge Engineering, 2007, 60(1): 208-221