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Online since: July 2011
Authors: Pang Wen Ling
The analysis is performed on historical and present data, but the goal to make financial projections.
The analysis is performed on historical and present data, but the goal to make financial projections.
Introduction In the random data, whether the concealing doesn't behave to know of the regulation is one of the popular topics of data analysis.
The numbers of the history data for fractal interpolation to prediction is dependent on the prediction error needed.
C., Strahle: Turbulent combustion data analysis using fractals (AIAA paper #90-07291990)
The analysis is performed on historical and present data, but the goal to make financial projections.
Introduction In the random data, whether the concealing doesn't behave to know of the regulation is one of the popular topics of data analysis.
The numbers of the history data for fractal interpolation to prediction is dependent on the prediction error needed.
C., Strahle: Turbulent combustion data analysis using fractals (AIAA paper #90-07291990)
Attitude Measurement Low Frequency Error Identification and Compensation for Star Tracker with Gyros
Online since: October 2014
Authors: Yu Wang Lai, De Feng Gu, Jun Hong Liu, Wen Ping Li, Dong Yun Yi
To overcome this difficulty, the gyro data, which is sensitive to the attitude motion, was used to fit the measurement attitude data to obtain the reference attitude.
Generally, the random noise can be filtered with the gyro data.
To conquer this difficulty, the gyro data, which is sensitive to the satellite attitude motion, was used to fit the measurement quaternion data of the star tracker by the EKF to obtain the reference quaternion which can represent as good as possible the orbit track.
Acknowledgments The authors are grateful to Beijing Institute of Tracking and Telecommunication Technology for providing the CCD01 and the APS01 star trackers attitude observation data, the gyro data and the GPS observation data of STECE satellite.
Reduction of Low Frequency Error for SED36 and APS based HYDRA Star Trackers, Proc.6th Internat.
Generally, the random noise can be filtered with the gyro data.
To conquer this difficulty, the gyro data, which is sensitive to the satellite attitude motion, was used to fit the measurement quaternion data of the star tracker by the EKF to obtain the reference quaternion which can represent as good as possible the orbit track.
Acknowledgments The authors are grateful to Beijing Institute of Tracking and Telecommunication Technology for providing the CCD01 and the APS01 star trackers attitude observation data, the gyro data and the GPS observation data of STECE satellite.
Reduction of Low Frequency Error for SED36 and APS based HYDRA Star Trackers, Proc.6th Internat.
Online since: January 2012
Authors: Jiun Wei Wu, Jung Pin Wang, Hsi Chi Yang
The sludge dramatically causes the water pollution and storage reduction of a reservoir, threatening its functionality and operational life span.
From the material data in Tables 3 and 4, the weights of cement and fly ash used for W=160 kg/m3 (B2) is greater than W=140 kg/m3 (B1).
From the material data in Tables 3 and 4, the weight of fly ash used for W/B=0.28 (C1) is greater than W/B=0.32 (C2).
From the material data in Tables 3 and 4, when W/B=0.28 (C1), the weights of cement, fly ash and superplasticizer used for W=160 kg/m3 (B2) is greater than W=140 kg/m3 (B1).
Since S/N ratio is defined as the ratio between the square of mean and the variance, the increase of mean and the reduction of variance will make the S/N ratio bigger.
From the material data in Tables 3 and 4, the weights of cement and fly ash used for W=160 kg/m3 (B2) is greater than W=140 kg/m3 (B1).
From the material data in Tables 3 and 4, the weight of fly ash used for W/B=0.28 (C1) is greater than W/B=0.32 (C2).
From the material data in Tables 3 and 4, when W/B=0.28 (C1), the weights of cement, fly ash and superplasticizer used for W=160 kg/m3 (B2) is greater than W=140 kg/m3 (B1).
Since S/N ratio is defined as the ratio between the square of mean and the variance, the increase of mean and the reduction of variance will make the S/N ratio bigger.
Online since: September 2011
Authors: Peng Xu, Jun Han, Jing Yu Wang, Chang Shu
However, due to the hospital information system data-processing complex, high-throughput, data, delete / update / insert operation frequently, while up to the efficient data processing, timely and accurate characteristics, sometimes leads to low hospital information systems efficiency, so how to improve the performance of the hospital information system, improve the system throughput and reduce user wait time, optimize the hospital information system is the primary problem.
(3) The number of hit sort field, the system global area (SGA) values and data storage technologies
In shared pool store high-speed buffer memory and data dictionary caches SQL statements.
If the shared pool is too small, then when the user process access the data, it is possible to find no data, have to read the information on the disk.
SQL is a structured query language, its implementing process includes the statement analysis, statement execution, the statement reads data three stages.
(3) The number of hit sort field, the system global area (SGA) values and data storage technologies
In shared pool store high-speed buffer memory and data dictionary caches SQL statements.
If the shared pool is too small, then when the user process access the data, it is possible to find no data, have to read the information on the disk.
SQL is a structured query language, its implementing process includes the statement analysis, statement execution, the statement reads data three stages.
Online since: December 2012
Authors: Jing Jie Chen, Shu Jie Qian
According to data released by the Civil Aviation Authority, the airport energy consumption accounted for about 3% of the total energy consumption of the civil aviation industry.
Collection of indicator data.
The raw indicator data in coal consumption, electricity consumption, gas consumption, water consumption, carbon emissions and general waste recycling amount of quantitative data, data sources for the field research.
In order to facilitate the selection of the reference sequence and associated calculation of the raw data ,we normalize the raw data into a dimensionless, at the same level, the positive data that can be added.
The normalized raw data is shown in Table 3.
Collection of indicator data.
The raw indicator data in coal consumption, electricity consumption, gas consumption, water consumption, carbon emissions and general waste recycling amount of quantitative data, data sources for the field research.
In order to facilitate the selection of the reference sequence and associated calculation of the raw data ,we normalize the raw data into a dimensionless, at the same level, the positive data that can be added.
The normalized raw data is shown in Table 3.
Online since: May 2016
Authors: Joachim Ohlert, August Sprock, Peter Sudau
The "threesome" comprising availability, ability to evaluate and accuracy of data will continue in the future to retain its strong significance.
Furthermore, competence in making data from various sources and in various forms available on a common basis and interlinking these data in a suitable manner will become increasingly important.
· Operation is simple and the transparency is high because the respective data required for the various user groups can be provided in a targeted manner (data compression)
This system makes it possible to record, compress, evaluate and store measured data.
The calculated data are shown with the green triangles and are in accordance with the measured data (red squares).This makes it possible for the mill owner to produce higher-strength materials or to reduce the content of alloying elements if the strength is to remain unchanged.
Furthermore, competence in making data from various sources and in various forms available on a common basis and interlinking these data in a suitable manner will become increasingly important.
· Operation is simple and the transparency is high because the respective data required for the various user groups can be provided in a targeted manner (data compression)
This system makes it possible to record, compress, evaluate and store measured data.
The calculated data are shown with the green triangles and are in accordance with the measured data (red squares).This makes it possible for the mill owner to produce higher-strength materials or to reduce the content of alloying elements if the strength is to remain unchanged.
Online since: December 2012
Authors: Ya Guang Wang, Zhen Yun Liao, Xiu Fen Fu
Introduction
In order to adapt to the new needs of information processing, data mining is a new information analysis technology which has already entered into practical phase in the current data warehouse environment.
Data mining, also known as knowledge discovery in database is a process extracting something unknow and embedded in advance, but potentially useful knowledge and information from the large, noisy, incomplete, ambiguous, random data, its main purpose is mining some value knowledge on customer from the mass data .
Mining of association rules is a very important research direction in data mining .
As shown in Fig.1 is the use of randomly generated data process.
Data mining association rules in a highly efficient Apriori algorithm in Chinese
Data mining, also known as knowledge discovery in database is a process extracting something unknow and embedded in advance, but potentially useful knowledge and information from the large, noisy, incomplete, ambiguous, random data, its main purpose is mining some value knowledge on customer from the mass data .
Mining of association rules is a very important research direction in data mining .
As shown in Fig.1 is the use of randomly generated data process.
Data mining association rules in a highly efficient Apriori algorithm in Chinese
Online since: February 2013
Authors: Jiong Zhou, La Li
But it also create the most serious defect--impersonality giving weight make this method is too dependent on the data, data collection has difficulties may influenced the evaluation result.
Data Envelopment Analysis, DEA.
It can grasp the potential law between the two through pre-written a batch of mutual corresponding input-output data analysis, using new input data to calculate output result according to the law.
This method is good at processing the periodically, secular, high order, nonlinear time-varying problem and it can still research in the condition of lacking data.
Factor analysis is too dependent on the data and AHP has the disadvantages of identifying weight subjectively.
Data Envelopment Analysis, DEA.
It can grasp the potential law between the two through pre-written a batch of mutual corresponding input-output data analysis, using new input data to calculate output result according to the law.
This method is good at processing the periodically, secular, high order, nonlinear time-varying problem and it can still research in the condition of lacking data.
Factor analysis is too dependent on the data and AHP has the disadvantages of identifying weight subjectively.
Online since: August 2013
Authors: Fan Jin Zeng, Hui Li, Li Ding
Varchar is a variable-length character data, the length does not exceed 8KB; Char is a fixed-length character data, the length does not exceed 8KB; More than 8KB ASCII data can use the Text data type is stored.
The character data type selection varchar
The Int type storage data range is greater than the range of data types are stored in Smallint, and the Smallint type storage data range greater than the range of Tinyint types of stored data.
Currency data type Money and Smallmoney, Money type occupies 8 bytes of storage, Smallmoney data type occupy 4 bytes of storage.
By creating a unique index to ensure the uniqueness of the data of each row in the database table; Accelerate the speed of data retrieval, which is also the main reason to create the index; Connection between the table and table acceleration, particularly in achieving the integrity of the data reference particularly meaningful; Grouping and sorting clause for data retrieval, the same significant reduction in the time of the query grouping and sorting; Hidden by the index query optimization, to improve system performance [8,9].
The character data type selection varchar
The Int type storage data range is greater than the range of data types are stored in Smallint, and the Smallint type storage data range greater than the range of Tinyint types of stored data.
Currency data type Money and Smallmoney, Money type occupies 8 bytes of storage, Smallmoney data type occupy 4 bytes of storage.
By creating a unique index to ensure the uniqueness of the data of each row in the database table; Accelerate the speed of data retrieval, which is also the main reason to create the index; Connection between the table and table acceleration, particularly in achieving the integrity of the data reference particularly meaningful; Grouping and sorting clause for data retrieval, the same significant reduction in the time of the query grouping and sorting; Hidden by the index query optimization, to improve system performance [8,9].
Online since: October 2006
Authors: I. Cambero, F.J. Alonso, David Rodríguez Salgado
Data were
acquired taking into account an expected life depending on the cutting conditions.
These signals were processed and logged via a data acquisition card connected directly to a PC.
The same type of network was used to develop a TCMS with the experiment data.
The key issue in many monitoring systems is the reduction of large flows of data from numerous sensors to a few well-correlated features that can be used for process monitoring.
Of the 42 observations given in table 2, the data that are presented in normal type were used to train the network (30 observations) and the data in italics type for validation (12 observations).
These signals were processed and logged via a data acquisition card connected directly to a PC.
The same type of network was used to develop a TCMS with the experiment data.
The key issue in many monitoring systems is the reduction of large flows of data from numerous sensors to a few well-correlated features that can be used for process monitoring.
Of the 42 observations given in table 2, the data that are presented in normal type were used to train the network (30 observations) and the data in italics type for validation (12 observations).