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The result achieved is an application model, which can assist production process activities, especially in documenting and storing data transaction and also generating reports in accordance with organization’s needs.
Accounting information system can be defined as the sum of the people (lifever), equipment (hardware), computer programs (software), the stored data, means and methods of their organization (dataver), communications and network connections (netver) and organizational procedures (orgware) that enable the collection, sorting, recording, summarizing, storing data and information and the preparation and presentation of accounting information to interested users [10].
The management requires fast and accurate data to generate a report which is useful for management to make decision. 5.
It is essential to have accounting information systems of production processes with has integrated database and can distribute and also connect the data between head office and plant.
Industrial Management & Data Systems Vol. 112 (2012), pp. 502-518

Three functional modules: energy data collection, real-time data of monitoring energy, and analysis and release of the energy data System Architecture As shown in Fig.1, the energy system architecture is as follows: A centralized energy monitoring management center is set up in the factory (composed of energy server, database server and energy management software), and energy collection substations are set up in the electric power and thermal entrances.
The energy monitoring center collects and process the energy data through the energy substation; dynamic display of energy process parameters and equipment; display of alarm and trend; management and storage of historical data; remote control; the generation and print of energy statistical statement; Web publishing of the energy using information; realization of the connection and data exchange with other systems (MES and ERP); Fig.1 System Architecture of the Energy Management The network layer is responsible for the energy data transmission and the main uses the optical fiber ring network.
Have ETHERNET communication interface to transmit data upward, the ETHERNET/IP communication protocols and control center monitor the exchange data of the server in a real-time manner.
Have real time clock, which can transfer the data with time stamp marking.
In addition, the controller is equipped with 512M DDR2 SDRAM memory and 64M NOR FLASH memory, used to memorize the energy data.

Principle component analysis has two purposes: the first is data reduction, and the second is for revealing the relations between variables.
It assumes n samples and each sample has p characteristics (index), then the sample data set can be expressed as: (1) Steps of principle component analysis [6]: Step1: data standardization; standardize the original data first so as to eliminate dimension influence, thus gaining standardized data set .
Divide simulation data into two parts and take the data from 1990 to 2005 as training sample set data; data of 2006 to 2010 as test sample set data for the model; in order to eliminate influence to the prediction performance resulted from the dimension difference of the SVM prediction indicator data, it’s necessary to preliminarily process the input data before utilizing SVM to establish model for prediction; it will directly influence the training speed and water demand prediction accuracy.
This article conducts standardized processing to all the sample data with Eq.8 and normalizes all the data in interval [0, 1]
(8) refers to normalized data; xi refers to index series data; xmin, xmax respectively refer to the min and max value of the original series data.

The framework incorporated HLCCM is proposed in cloud computing based collaborative design environment and allows users to estimate the product data and other related information on a wide variety of application.
The product attributes strongly correlated with LCC factors are chosen as learning data in the HLCCM.
The cost factors considered would depend on the stage in which we want to use the model, the kind of information to be extracted from the model, the data available as input to the model and the product being designed.
Table 3: The predicted LCC results with 200 sample data using the HLCCS (MAPE) Conventional ANN HLCCS Training Validation Training Validation Life cycle energy cost 19.32% 28.51% 11.13% 16.17% Maintenance cost 7.14% 11.17% 4.27% 7.02% Average 13.23% 19.84% 7.70% 11.60% In Table 3, the HLCCM has higher prediction accuracy than BPNN for the validation data.
This distributed modeling paradigm is very different from centralized data repositories where users conform to a single standard and are required to check in on a regular basis to make sure their models are updated.

The welding parameters such as arc current and voltage were captured by using data logger and the stick-slip effect was analyzed.
The influence of stick-slip effect on welding is observed in the arc waveforms plotted from the data obtained from the data logger.
Welding Parameters kept constant Wire Feed Speed 7.7 m/min Travel Speed 0.7 m/min Arc Length 2 mm Stick Out Distance 10 mm Shielding Gas Ar 80%+CO2 20% Gas Flow Rate 18 litre per minute TVC data logger The Validation Center (TVC) data logger is an system which is able to record and analyse the welding parameters.
Using TVC data logger, though there were enough parameters which can be measured and analysed like temperature, gas flow rate, travel speed etc., for analysis the voltage, currrent and wire feed speed were sufficient.
Arc waveforms After getting the transient data of arc voltage, current and wire feed speed, the arc waveforms are plotted.

The survey data of each criterion is averaged to find the mean of satisfaction score.
The questionnaire surveyed data are analyzed by SPSS indicating the lack of understanding of the construction technique with prefabrication [1].
SPSS® (Statistical Package for the Social Science for Windows) is used to analyze the survey data.
The Levene’s test shows p-value <= 0.05, indicating that the survey data do not follow homogeneity of variance assumption for most criteria.
Welch and Brown-Forsythe tests are conducted when the survey data do not follow homogeneity of variance assumption to compare satisfaction mean score among habitat groups.

Study Method and Data Definition of Product Category.
Table 1 Data inventory of ceramic tile production Item Substance Unit Qty.
(1) Designating background data 1% of the contribution value to the environmental impact is taken as a “rule of choice”.
Process excluded 1 Field emission 1 Diopside production 2 Use of electric power 2 Use of feldspar 3 Use of diesel oil 3 Talc production 4 Use of soft coal 5 Use of natural gas 6 Water-sorted soil production 7 Feldspar sand production 8 Clay production 9 Quartz sand production 10 Road transport (2) Determining enterprise’s on-site process data Based on the above background process included, the enterprise shall collect corresponding on-site process data and raw material consumption data.
Collection range of the enterprise’s on-site process data as finalized is shown in Table 4.

Our data indicate that 25 kGray gamma irradiation reduces the osteoconductive and osteoinductive properties of the morselized human bone graft.
Statistical analysis (ANOVA and the Kruskal-Wallis test) of the individual data showed a significant difference between the 0, 15 kGray, and 25 kGray groups (Table 1).
Tetrachrome staining of the defects packed with the human bone grafts treated with 0 (a), 15 (b) or 25 kGray (c) gamma irradiation showing a dose-dependent reduction of new bone formation (light blue, solid arrow) around the implanted bone grafts (red, open arrow).

Wear properties of samples were discussed by tacking various wear testing data. 1.
Introduction Since speedup of train and reduction of cost to maintain the electric correcting system are strongly required in recent railway operation, studies on the carbon based contact strip materials and their wear phenomena become one of the important topics in the field of high-speed electric railways [1-3].
Ws = a E b Using data from the present investigation, coefficients a and b were calculated and listed in Table 3 for each wear condition.

Combined with the data from a hot strip factory, the elastic deformation of the HOFC work roll was analyzed following the influence coefficient method.
Original data.
(2) The curve can get quality products without modifying the primary equipments significantly and this practice accord with the pursuit of energy conservation and cost reduction