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The theory and experiment data are contributed to the VLSI circuit design in the future.
With the reduction of the thickness of gate oxide layer, the gate tunneling current increases by three orders of magnitude from 10-9(A) to 10-6(A).
Fig. 2.1~2.2 highlights that the gate tunneling current increase with the reduction of the thickness of gate oxide layer.
[2] Mukhopadhyay, S., Neau, C., Cakici, R.T.: Gate Leakage Reduction for Scaled Devices Using Transistor Stacking.
Cakici: Gate leakage reduction for scaled devices using transistor stacking.

The dynamics model obtains unit data from the modal reduction results, and the calculation results are the boundary conditions of the stress recovery calculation.
Data of the block unit and crankshaft unit are obtained from modal reduction calculation on them, while before connecting rod unit is simulated by beam element automatically via simulation software, the size and mass of the connecting rod should be inputted.
The boundary conditions used in the dynamics calculation are usually load data.
The measured indicator diagram data are chosen as load boundary conditions for dynamics simulation.
Figure 5 shows the stress development chart of the points that has the least safety coefficient in that 3 dangerous areas, and their data are shown in Table 2.

Analysis on Strength Reduction Coefficient Strength reduction coefficient is the ratio of the residual bearing capacity of the compressive brace to buckling bearing capacity after the brace buckling in compression.
The strength reduction coefficients are average.
The relation curves between the reduction coefficients and the different slenderness ratios are shown in Fig. 5.
A new strength reduction formula of the compressive brace is proposed based on these data at 0.5%, 1%, 1.5% and 2% story drift level.
Strength reduction coefficient of the compressive braces curve At the same story drift ratio, the reduction factor increases with the increasing of the brace slenderness ratio.

In the AIS data, ship dynamic information has faster update frequency, sailing ship normal (2-12 seconds) broadcasts one ship dynamic message (including longitude, latitude, speed, heading, etc.)[1], therefore, vessel trajectory data is the majority in the AIS data.
However in fact, there are large numbers of redundant vessel trajectory data.
There are redundant, so we can take advantage of few trajectory data to replace a large number of AIS data on the whole voyage.
The advantages of angle tolerance algorithm are suitable for flat curve data compression.
The original data are total 6448 trajectory points.

Introduction In the backdrop of the world's energy crisis, automobile fuel economy has been increasingly attracting people's attention, and aerodynamic drag reduction will effectively reduce the fuel consumption.
The technology of CFD can simulate the conditions and obtain the data which experiments cannot [2].
Latin hypercube sampling (LHS) is a method of variance reduction which has been widely used in the fields of simulation, optimization calculations and reliability calculations [3].
Seen from the analysis of streamline distribution diagrams of the models, a smaller CD will be acquired by the backward movement of boundary layer separation points and the reduction of vortex area.
Considering aerodynamic characteristics, some measures can be taken to move vortex area backward or reduce the area of vortex in automobile style design for the purpose of aerodynamic drag reduction.

In this study, the reduction technique of stiffness matrix, which is refered to “transfer matrix method (TM)“, is developed to solve effectively the problem.
In this study, the reduction technique of stiffness matrix, which is refered to “transfer matrix method (TM)“, is developed to solve effectively the structural problem composed of curved and straight pipes.
Applying Eq. (2) to pipe number 1 firstly, we have, 1Zb=1F1Za (3) Fig. 1 Pipe system In order to transfer Eq. (1) to state vector in the relation for local coordinate fixed in pipe number 2, the rotation matrix Rθ1,2 is multiplied from left side to Eq. (1), which leads to, 2Za=Rθ1,21Zb→Rθ1,21F1Za (4) Repetition of this operation in sequence gives us the following: 2Za=Rθ1,21F1Za 3Za=Rθ2,32FRθ1,21F1Za 4Za=Rθ3,43FRθ2,32FRθ1,21F1Za ⋯⋯⋯⋯ Consequently, the transfer relation from pipe number 1 to N can be expressed by, NZa=i=2NRθi-1,ii-1F∙1Za (5) which allows us to calculate the state vector NZa for pipe number N as output data from the state vector 1Za for pipe number 1 as input data.
Fig. 6 Stress distributions in case of Fig. 7 Relationship between accuracy 40 mm inner diameter and pipe bend factor Fig. 8 Comparison in stress components between TM and FEM Conclusion In this study, the reduction technique of stiffness matrix, which is refered to “transfer matrix method (TM)“, is developed to solve effectively the structural problem composed of curved and straight pipes.

In the reaction tests, the OCs were submitted to successive reduction and oxidation cycles.
All these data were determined based on different times employed in the reduction stage, considering that the values corresponding ​​to the ratios between H2 and CO concentrations were calculated through GC and MS methods. 3.
Bulk nickel oxide showed a reduction between 260 to 560°C with a maximum at 400°C.
Temperature-programmed reduction profiles for OCs and bulk NiO.
It was also observed, during the redox cycles performance with smaller reduction times (3, 1.5 and 0.75 min, not shown in this work) that the time reduction at the reduction step reduces the carbon deposition by methane catalytic decomposition over Ni0 catalytic sites during the reduction of OC (CH4 ↔ C(s) + 2H2).

Meanwhile, the PIV system was employed to measure and analyze the experimental data.
Fig. 5 Relative circulation of different wingspans of data set 1# Fig. 5 depicts that the circulation increases between wingspan 1 and wingspan 17, despite of the reduction of the maximum velocity in Fig. 4.
The relative circulation process result of data set 11# shows in Fig. 7.
Fig. 8 Relative circulation variation of the six data sets When divide the statistical average of the last six data by the statistical average of the six maximum data, the percentage of the circulation reduction of the flow field will be derived.
Table 4 Circulation reduction of every data set Data set 7# 8# 9# 10# 11# 12# Circulation reduction 62% 60% 54% 64% 52% 57% Table 4 shows that the reduction of the circulation varies from 52% to 64% which powerfully proved the effectiveness of Rayleigh-Ludwieg instability in weakening the wake vortex compared to the circulation change of the main wing vortex in Fig. 5.

After that, selected samples were cold rolled to 30 and 75 % reduction.
Figure 2a shows the microhardness data of PA samples measured after aging at 100 °C versus aging time up to 6 days.
Figure 3 shows the DSC curve obtained at the heating rate of 10 °C/min for the cold rolled (to 30 and 75 % reductions) materials.
Figure 4 shows the microhardness data of both the deformed materials measured after ageing at 100 °C versus aging time up to several days.
Figure 4 The microhardness data of both the deformed materials measured after ageing at 100 °C versus aging time.

The measures provided to reduction energy consumption are taken on the basis of the approved revision of the European Parliament and Council Directive 2010/31/EU on energy performance of buildings of 2010.
The Airtightness of Energy Efficient Buildings The most powerful aspect of quality airtight building envelope is reduction of the amount of uncontrolled air leakage through building envelope and the associated reduction of heat loss and reduction overall building energy demands.
The value of n50 expresses airtightness in numbers, and indicates how often the air volume of the building concerned is exchanged per hour at a pressure difference of 50 Pa. [3] Verification of Statistical Dependence The basic data sample includes 150 of passive houses.
It is a secondary data from freely available and relevant resources - Database of Centre passive houses in the Czech Republic [4].
Spearman's rank correlation coefficient uses the rank of values of the monitored variables and it does not assume normality of the data. [3, 5] Values of the Spearman correlation coefficient of the non-parametric correlation range between <-1;1>.