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There is a sufficient number of literary data devoted to the dissolution of DSP in acid, in relation to the red mud there is a number of patents [21].
Based on the preliminary data a new flow-sheet (Fig. 1) is suggested for enrichment of valuable components of the concentrate obtained from the low-grade copper ore with thin impregnation of sulfide components.
Reduction of L:S ratio allows to reduce the amount of acid consumed by reducing the initial pH of the solution, but its increase reduces diffusion difficulties, which can contribute to a more complete extraction of the components into the solution.
Otherwise, its reduction increases the extraction of aluminum into the solution, so the best option would be L:S = 5, but at this value of this parameter greatly deteriorates the filterability of the solid phase, which is apparently due to the precipitation of amorphous silica from the solution, so the best option is W:T = 7.

Steel production processes general composed of raw material storage, original, fuel processing, reduction iron making, oxidation steelmaking, solidification of liquid steel, billet reheating, the billet thermal pressure processing and other processes.
Though abstract steel production process as the input – output process of ferrite material flow, the input – output process of energy flow, the interaction process of ferrite flow - energy flow, it is conducive to research dynamic behavior and effect of material flow and the energy flow in the production process of the iron and steel enterprise, as well as the interaction mechanism between these, efforts to seek new solution of energy saving, emission reduction and elimination of waste for steel enterprise.
It’s needed to prepare some initial group data of starting search point.
Case and the result of the operation According to a city’s actual situation in a steel enterprise logistics mode, a steel enterprise production data’s need and its competitive business environment, case data has been make appropriate simulation processing on the basis of empirical research, and further elaborated the research thinking and calculation method of the model.

The demographic data of the amputee persons is shown in the Table 1.
The trained classified trees predict the responses for new data.
The injection of the randomness into the data set is by bootstrapping of original data sample and to split each node into tree by selecting subset of features.
The sample of training data out of the bootstrap is called the out of bag (OBB).
[24] Merletti, R, Standards for Reporting EMG Data.

To study the accuracy and characteristics of neural network prediction calculation, 18 data sets were used as training samples and the No.6 and No.16 data sets were used as the validation data. 2.3 Neural network setting BP neural network was set to have three layers.
Take No.6 data set’s test values for example: Figure 1 shows the error percentage in calculation of the predictive values of No.6 data set when the number of calculation times was below 1000.
Wherein No.6 data set’s calculation error in 29 times vibrated within -20%~+20%; No.16 data set’s calculation error in 26 times vibrated within -20%~+20%.
Fig 4 :Data Processing Flow Chart Take No.6 data set for example and showcase its processing (the other three values are in similar case, you can calculate on your own).
Teaching Evaluation System through Network Based on Data Mining[J].

Greenhouse Effect Reduction Through Sustainable Magnesium Oxide Eco-cement Products Wu Yaoa, Yukun Yangb, Mengxue Wuc Key laboratory of Advanced Civil Engineering Materials (Tongji University), MOE, Shanghai 201804, China ayaowuk@tongji.edu.cn, byangyukuntju@163.com, cwmx_129@163.com Key Words: Eco-cement, CO2 absorption ability, mechanical performance Abstract.
Therefore the aim of this paper was to conduct experiments on eco-cement and collect data to investigate: (1) carbon dioxide sequestration ability of the eco-cement, and calculation on the CO2 absorption amount; (2) mechanical properties for practical application; (3) expansion tests to ensure the stability and soundness.

This paper describes the measurement of the parameters of the experiment, the problems in the analysis of experimental data processing and experimental error.
The flow pattern and pressure drop of flow boiling, heat flux and heat transfer coefficient of relations are studied by analysis of the experimental data.
Introduction The scholars have studied flow boiling phenomenon in micro-channels for decades, who got a lot of experimental data about heat transfer and the identification.
Conclusion The experimental data are translated, and visualization of the results combine can obtain the vertical rectangular fine channels within the flow regime transition criteria.
This paper describes the collation and analysis of the collected data obtained, observed flow pattern definition and exploration and visualization experiment. 6.

The orientation data obtained by EBSD are displayed in Rodrigues-Frank space using alternative reference frames [3,4].
At this temperature, a 50 % reduction (corresponding to an effective strain of 0.8) was applied in order to refine the microstructure by recrystallisation of the austenite.
The latter reductions were applied below the austenite "no-recrystallisation" temperature Tnr, so that the "pancaked" grain shape was retained, together with most of the dislocations introduced by the deformation.
The mean misorientation of a set of such data is then defined as the mean of the misorientation of each datum point with respect to the mean orientation.

These authors reported encouraging correlations between their test results and the theoretical data obtained by numerical modeling based on the plane-section bending assumption.
The predictions of ultimate moment based on this model were found to correlate reasonably well with the test data reported by Cairns and Zhao [1], with the overall average of predicted moment/measured moment being 1.09.
By using the test data obtained by himself as well as the experimental data reported by others [1, 5], Senussi’s proposed model was shown to provide very encouraging correlations with the test data based on large scale beams made of normal strength concrete (NSC), covering a reasonable range of first order beam design parameters- hence, demonstrating the reasonable generality of his proposed model.
The value of Pk , which was, by examining the load versus strain gauge reading plots, found to be associated with the initiation of yielding of main tensile steel, had to be estimated from the indiviual load versus deflection test data, and this required that a judgement of the exact location where the kink starts to be specified which may have caused a minor degree of inaccuracy in the quoted value(s): the load versus deflection data, for both series S and P, are given in Fig. 2 and Fig. 3, respectively.
For each of the two series, S and P, the load versus deflection data for the control beam as well as the load versus deflection data for its associated damaged specimens are, then, presented together (for comprasion purposes) in the same diagram, Fig. 2 and Fig. 3.

The aim is to verify the functionality of the coupling and, based on the comparison of measured and theoretical data, to define the critical points of the composite and, thus, provide a basis for design optimisation in order to maximise the monitored parameters.
Collection of the data took place continuously from October 2018 to August 2019, with the aim to describe changes in deformation, stress and temperature of the composite from the production phase to the final/operational state.
Based on the evaluation of the measured data, the problematic places/points were subsequently defined in terms of the steel envelope coupling and concrete filling functionality.
Based on these processes, it is possible to conclude that there is a reduction in the cohesion of the contact, as a result of which the coupling mandrel is ‘activated’ (increased in deformation).

Reductions of 3:1 were applied at 300 and 350ºC up to six passes (6p).
Table 1 shows applied force (Fmax, in kN), (sub)grain data (from TEM) and Hardness Vickers HV for a set of ECAPed samples.
Regarding ARB samples, Fig. 1 shows (sub)grain data from TEM observations with a 3:1 thickness reduction at processing temperatures of 300 and 350˚C.
At 400ºC both ef and YS data show that GBS is no longer operating and a change to a slip creep mechanism takes place.
This is clear when different processing temperatures are taken into account, as it is represented in Fig. 4b, for the same ECAP data of Fig. 4a, for which no (sub)grain size can be predicted from total applied strain data.