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Silicone nitride powder was produced at own laboratory conditions by carbothermal reduction-nitriding of silica of which was presented elsewhere.
Carbothermal reduction nitriding process is able to produce reasonable silicone nitride powder for subsequent compaction and sintering steps.
In the present work, carbothermal reduction nitriding conversion of a raw material without any sintering additives was studied.
Silicone nitride powder was produced at own laboratory conditions by carbothermal reduction-nitriding of silica of which was presented elsewhere [25-27].
The crystalline phases in the sintered samples were identified using data for inorganic substances diffraction files complied by JCPDS.

The BaTiO3-added Ni green bodies were fabricated through cold isostatic pressing, and then sintered to 1300°C in a reduction atmosphere.
One of the various capacitor architectures is the multilayer ceramic capacitors (MLCCs) with Ni base metal electrodes (BMEs), and these have been increasingly produced to meet the exacting requirements for miniaturization, high capacitance, and cost reduction [2,3].
The BaTiO3-added Ni green bodies were fabricated through cold isostatic pressing (CIP) with 200 MPa, and then sintered at 1300°C in a reduction atmosphere.
The shrinkage behavior of the fabricated green bodies according to volume ratio was investigated by checking the amount of shrinkage in length (x direction) and width (y direction) of samples, from 700 to 1300°C with 300°C interval in a reduction atmosphere.
Solid curves are data fits.

It causes also strength reduction of the woods and losses of the load bearing capacity of the structures, and has to be taken into account in the static assessments. 1 INTRODUCTION Many structures resting on pile foundations, which are surrounded by water in the soil for decades or centuries.
In Table 1 and Fig. 8 the key data of the measured penetration depths are given in percent of the cross-sectional weakening.
The resulting reduction of load bearing capacity is only about 20%.
The reduction of the load bearing capacity due to a low circumferential wood destruction by bacterial wood degradation, ranging up to 2 cm deep, is max. 20%.
As determined on the cores the maximum cross-section reduction is 40%.

Laboratory structure and data acquisition The laboratory structure used in the experiments is shown in Fig. 2.
Accelerations were measured in the direction of shaking at 400Hz using a computer fitted with a data-logging card.
All data was filtered with a zero phase shift 50Hz low pass filter.
Afterwards the acceleration data was decimated by a factor of four for modal analysis and eight for time series modeling.
The acceleration time history of each storey was modelled using an AR(12) model with no data normalizing procedures applied.

The basic idea of KPCA [5] is to map the data in initial space into higher-dimensional feature space F with nonlinear mapping function where the PCA method is used to analyze the data.
Assuming mean of mapping data is zero, KPCA solves the eigenvalue problem (1)
Data collection and original feature vector extraction.
Each category takes 150 group (450 groups in all) data as sample.
Dimension reduction by KPCA.

The wireless module SIM300 transfers data to the primary station by its GPRS function.
The primary station and slave station using RS485 differential communication to improve data transmission reliability.
Above to ensure SIM300 module to work, then you can realize the GPRS connection through use MCU to send AT commands to control the SIM300.If the connection is successful, send data to the SIM300 module will be returned other data, according to the data returned can know the SIM300 working condition.
If the returned data is "CONNECT OK", which proved connection is successful and you can exchange data.
The wireless module SIM300 transfers data to the primary station by its GPRS function.

However, it is impossible to obtain fire thermal parameters quantitative data from actual building fires.
To enhance user-friendliness, the IN-FORM interface feature was added in 2001, and can integrate user-entered data with computation modules to facilitate parameter setup, modification of equation solution, and presentation of simulation results.
Result and Discussion This study used various HRRs to discuss the temperature distribution of a beam when two and three sides are exposed to fire, and analyzed the reduction of beam strength of various cross sections as the temperature changed.
As ignition source HRR increases, the level of strength reductions at the beam will gradually reduce.
The analyzing method in this study can focus on the level of strength reduction after a beam is exposed to fire, with which users can accomplish the following: 1. understand whether the original structural strength changed after fire exposure, and 2. identify weaker beam sections for structural reinforcement.

Data base from NGA-west1 and the preliminary grouping Data base from NGA (Next Generation Attenuation) program in the United States are adopted in this paper.
Totally 1513 recording sets during 64 earthquakes with magnitude 4.2 to 7.9 from 1952 to 2003, are chosen with 4 criterions, PGA no less than 200 gals, recorded at ground or at basement or the first floor in building less than three stories, data on site condition is available, and data of response spectra, earthquake parameters, data of observation stations are also available.
Recording data is not adopted if there is no vertical record in a set.
Of course, the spectral ratio in eq. (1) was obtained from data base with some differences from the one adopted in this paper.
A new data base with much more records was released in 2012 as NGA-west2 by NGA project.

The smartphone sends precise commands to the Arduino to start and stop data collection at specific times.
Real-time data was obtained on the execution of the passing technique by the athletes.
From both tools, relevant data are obtained, such as those shown in Table 2.
Data were obtained such as: The average weight, around 66.71 kg, and the standard deviation of 10.70 kg reflects the dispersion of the data with respect to this mean, highlighting the variability in individual weights.
From these data, we can observe significant differences in the correlations between the variables analyzed.

Data collecting and processing.
Data saving, displaying and playback.
The history data can be reviewed to facilitate data analysis.
Data real-time display area.
Data synthesis display area.By the end of test, all kinds of test data collected by measurement and control system were displayed by synthesis in data synthesis display area.