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Rough Set treats the knowledge as the division of the data based only on the data itself; discovering dependencies between data and generating classification rules; retaining minimum expression of pivotal information.
Rough Set treats the knowledge as the division of the data based only on the data itself; discovering dependencies between data and generating classification rules; retaining minimum expression of pivotal information [5]. 3.1 Knowledge base and knowledge systems S = (U, A, V, f) is an information system, U is the domain of object space; A is properties of finite non-empty set, , is the range of a ∈ A, f:U × A → V is an information function. 3.2 Define of indiscernible relation If P ∈ R, and P ≠ Q, ∩ P (P stands for intersection of all equivalence relation) is an equivalence relation, called indiscernible relation of P, and is denoted by ind (P): U / ind (P) is defined as the knowledge related to the equivalence relation P family, called P Basic Knowledge. 3.3 Approximate Sets [6] For the given Knowledge Base k = (U, R), X ⊆ U, for each subset, and an equivalence relation R ∈ ind (K), defined as two subsets: Lower approximation: Upper approximation: Collection is the R boundary
Indicator data must obtain from reliable sources with a high quality.
Five samples were randomly selected in the survey sample, and the sample data has been rough set rosetta software calculated padded data (see Table 2).
Fig. 1 Reduction of Suburban Residential Properties Calculate the “price”, “public service facilities” and “land use and planning”.

The mode shapes were combined after modal identification was performed to each data set to obtain the mode shapes of the entire bridge span.
To avoid noisy vibration, the test bed was cleared during data collection.
As a pretest, ambient vibration data were sampled for five minutes to verify the test setup and confirm the capability for accurate data collection.
After sample testing, data were collected for approximately 40 minutes from the ambient excitation of the bridge.
A sample of ambient vibration data is plotted in Fig. 4(a) at location “O” during test #2.

The box door with a warning sign, the intelligent low-voltage control box internal choose GPRS electricity integrated test instrument, the box internal also have electricity integrated acquisition instrument, with application GPRS field collection data function, and have a automation control interface, for transformer operation parameters and electricity information analysis, and for operation and management to provide a scientific basis.
Transformer station equipment selection in order to avoid maintenance, energy conservation and emissions reduction as the objective, adopt advanced technical indicators, modular products, to ensure its superior technical performance. 5) Convenient construction.
Each part of the rack combination adopt modular form, simple installation, transformer line adopt new design, connect line is simple, convenient. 6) Adopt intelligent control box. 7) Applicate multifunctional integrated acquisition instrument, share electricity data.
In order to achieve marketing and power distribution data sharing, adopt electricity integrated acquisition instrument , it has colleted low voltage side current, voltage, collected the power factor, the running time power and the total power operation data function, designs to have the function of the application GPRS field data collection, and has automation control interface.
According to the above data, research and development computer background management software, used for the analysis to data, provide users with the perfect "all the equipment life cycle management" service system, automatic prompt transformer whether over current, over voltage, low voltage, utilization, three-phase balance, power factor, power, 24 hours data figure, test cycle, etc, form various data reports, provide operation technical personnel for equipment technical analysis, provide marketers for power analysis .

An example of NoC is shown in Fig. 1, who works as follows: the packet of data from the source IP sent into the input channels of routers through the link, then will be sent forward to output channel by crossbar of the router, and then sent to the next router via a link or sent to the local IP core connected with the router, in which the crossbar will decide which channel the data will be exported by caching data packets and arbitration of router.
The task of router is to take the data packets injected to their destination via the data path statically or dynamic determined, specifically, the router will sent the data packet from an input port to one or more output ports.
Design of The router for NoC Router is one of the basic elements of the network on-chip, which is responsible for routing the packets from a network node to another in the network, and because that data transmissions with long-distance in the network are completed by the router, so it directly affects the performance of the entire network.
Data packets will be sent to the right virtual channel by judging ID of the virtual channel and control signals, then completed the scheduling of packets.
Latency Reduction of Global Traffic in Wormhole-Routed Meshes Using Hierarchical Rings for Global Routing.

In this work, three physical models (A I-III) are used to analyze the measured data.
The fit of the neutrality equation to the measured data is performed by a numerical calculation.
Even for higher temperatures, this model matches with the measured data.
The data points show the results of the fit of the neutrality equation using the analysis A I-III (Tab. 1).
The data points show the results of the fit of the neutrality equation using the models A I-III.

Software functions include signal acquisition, AD conversation, data storage,LCD display and data transmission.
The basic flow is human-computer interaction, information acquisition, calculation of concentration, concentration display, data storage and data transmission.
Finally, system transfers data to a PC via USB or Bluetooth.
This system can complete glucose signal acquisition, data display and data storage.
It can transfer data to PC.

Following the trend of energy saving and carbon reduction, many countries have been developing various energy-saving products to aggressively upgrade or replace electrical products with high energy consumption.
Experimental setup and analysis method The study mainly used the constructed clothes dryer performance testing and data measuring system to measure the tumbler status under different conditions and conducted analysis computation by the definition and mathematical model of tumbler efficiency.
In addition, the experimental data acquisition system was mainly composed of the temperature and relative humidity sensors (THP-B3T with an accuracy of ± 0.5˚C for temperature, ± 3.0% for humidity) installed at the inlet of the tumbler air side.
Meanwhile, the connection of sensors with data recorder can display and record data on the computer in real time for the calculation and analysis of tumbler efficiency by using the acquired experimental data.
After the experiment, analyze all the data including the data regarding temperature and humidity, standard fabric weight, design wind volume to furthermore calculate tumbler efficiency, and MER value.

Tessellated data can be applied to mathematically describe components such as lenses as well as geometric surfaces in the form of such facets.
In the course of testing, different types of geometric surfaces, each calculated using confocal data, were measured with the sensor model .
Because the surface is anisotropic, ten steel samples taken at different times in the course of the process are used to analyze the data.
Using the data stated here, the mean coefficients of correlation are calculated to be 66.3 % (), 73.4 % () and 67.9 % ().
Individual variances (Refer to parameter for , sample F) can be attributed to faulty data.

These parameters, extracted from in situ data, are then used to calibrate a model.
The time is synchronized by a GPS antenna, located on the terrace and connected to an ADSL line for the recovery of data.
Time data considered here are extracted of the November 16, 2008 event (magnitude Richter 2.5), the epicenter of which being situated away from Lourdes.
An exponential window is applied to the time data to reduce computational poles without influence of the damping estimates.
Then, thanks to the instrumentation of Ophite tower, we collect experimental data which enable us to recalibrate our models by identification.

Measuring data from all sensors were collected to the data logger.
Results and discussion Tab. 1 – Experimental and modeled data with residual t Cexp.
Experimental data consist of molar concentration growth of the carbon dioxide in water with time and modeled data are included also.
Calculated model parameters are based on measured experimental data, because sum of the squared differences between experimental and modeled data was set to be equal to minimum in Solver’s options and that’s the way how the Solver search parameters.
The Fig. 3 shows experimental data with mathematical model based on Eq. 6 and solved with MS Excel’s (2007) Solver in graphical form.