The efficiency and accuracy of probability diagram, spatial statistic and fractal methods in the identification of shear zone gold mineralization: a case study of the Saqqez gold ore district,NW Iran

In this study,geochemical anomaly separation was carried out with methods based on the distribution model,which includes probability diagram(MPD),fractal(concentration-area technique),and U-statistic methods.The main objective is to evaluate the efficiency and accuracy of the methods in separation of anomalies on the shear zone gold mineralization.For this purpose,samples were taken from the secondary lithogeochemical environment(stream sediment samples)on the gold mineralization in Saqqez,NW of Iran.Interpretation of the histograms and diagrams showed that the MPD is capable of identifying two phases of mineralization.The fractal method could separate only one phase of change based on the fractal dimension with high concentration areas of the Au element.The spatial analysis showed two mixed subpopulations after U=0 and another subpopulation with very high U values.The MPD analysis followed spatial analysis,which shows the detail of the variations.Six mineralized zones detected from local geochemical exploration results were used for validating the methods mentioned above.The MPD method was able to identify the anomalous areas higher than 90%,whereas the two other methods identified 60%(maximum)of the anomalous areas.The raw data without any estimation for the concentration was used by the MPD method using aminimum of calculations to determine the threshold values.Therefore,the MPD method is more robust than the other methods.The spatial analysis identified the detail soft hegeological and mineralization events that were affected in the study area.MPD is recommended as the best,and the spatial U-analysis is the next reliable method to be used.The fractal method could show more detail of the events and variations in the area with asymmetrical grid net and a higher density of sampling or at the detailed exploration stage.

Coefficient Diagram Method Based Load Frequency Control for a Modern Power System

increasing penetration of renewable energy sources with a wide range of operating conditions causing power system uncertainties, conventional controllers are incapable of providing proper performance to keep the system stable. However, controllable or dispatchable loads such as electric vehicles （EVs） and heat pumps （HPs） can be utilized for supplementary frequency control. This paper shows the ability of plug-in hybrid EVs, HPs, and batteries （BTs） to contribute in the frequency control of an isolated power system. Moreover, we propose a new online intelligent approach by using a coefficient diagram method （CDM） to enhance the system performance and robustness against uncertainties. The performance of the proposed intelligent CDM control has been compared with the proportional-integral （PI） controller and the superiority of the proposed scheme has been verified in Matiab/Simulink programs.

Two New Control Signal Approaches for Obtaining the MRAS-CDM and a Real-time Application

The coefficient diagram method （CDM） is one of the most effective control design methods. It creates control systems that are very stable and robust with responses without the overshoot and small settling time. Furthermore, all control parameters of the control systems are changed by varying some adjustment parameters in CDM depending on the demands. The model reference adaptive systems （MRAS） are the systems that follow and change the control parameters according to a given model reference system. There are several methods to combine the CDM with MRAS. One of these is to use the MRAS parameters as a gain of the CDM parameters. Another is to directly use the CDM parameters as the MRAS parameters. In the industrial applications, the system parameters can be changed frequently, but if the controller, by self-tuning, recalculates and develops its own parameters continuously, the system becomes more robust. Also, if the poles of the controlled systems approach the jw axis, the response of the closed-loop MRAS becomes more and more insufficient. In order to obtain better results, CDM is combined with a self-tuning model reference adaptive system. Systems controlled by a model reference adaptive controller give responses with small or without overshoot, have small settling times, and are more robust. Thus, in this paper, a hybrid combination of MRAS and CDM is developed and two different control structures of the control signal are investigated. The two methods are compared with MRAS and applied to real-time process control systems.

Single-peak distribution model of particulate size for welding aerosols

A large number of particulate size distributions of welding aerosols are measured by means of DMPS method, several distribution types are presented. Among them the single peak distribution is the basic composing unit of particulate size. The research on the mathematic models and distributions functions shows that the single peak distribution features the log normal distribution. The diagram estimating method (DEM) is a concise approach to dealing with distribution types, obtaining distribution functions for the particulate sizes of welding aerosols. It proves that the distribution function of particulate size possesses the extending property, being from quantity distribution to volume, as well as high order moment distributions, with K S method verifying the application of single peak distribution and of DEM.

Numerical Fitting of Planar Photographic Images with Spherical Voronoi Diagrams

There are many phenomena that generate polygonal tessellations on surfaces of 3D objects. One interesting example is the jackfruit, a multiple fruit found in the tropics. A recent study found the best-fit spherical Voronoi diagram from a photo of jackfruit skin, but the optimization was relative to the radius of the sphere and the height of the spikes. In this study, we propose a method for adjusting the position of the center of the sphere in addition to these parameters. Experiments were conducted using both ideal and real data. However, convergence with real data has not been confirmed due to relaxation of the convergence condition.

Studies on the Refolding of Egg White Lysozyme Denatured by Urea Using ＂Phase Diagram＂ Method of Fluorescence

The refolding of reduced and non-reducing egg white lysozymes in a urea solution was studied by a ＂phase diagram＂ method of fluorescence. The result showed that in the refolding of the reduced egg white lysozyme, an intermediate state of an egg white lysozyme exists at the urea concentrations in a final renaturation solution being about 4.5 mol/L, their refolding follows a three-state model; while in the refolding of the non-reducing egg white lysozyme, two intermediate states exist at the urea concentrations being separately 4.0 and 2.5 mol/L, and their refolding follows a four-state model. Through the comparison between the unfolding and refolding of an egg white lysozyme in the urea solution, it was found that both of the refolding of reduced and non-reducing egg white lysozyme molecules was irreversible to their unfolding in the urea solution. Finally, a suggested refolding was separately presented for the reduced and non-reducing egg white lysozymes in the urea solution.