The Shirbit polymetal prospect area is located in 30 km north-east of Ahar city within the Ahar-ore filed in around of Shivardagh batholith. Intrusion of granodiorite igneous bodies into the Eocene trachyte to andesite associated with pyroclastic interlayers caused widespread silicic, argillic and propylitic hydrothermal alteration associated with the Cu, Mo, Pb mineralization as quartz-sulfide (± oxide, carbonate, sulphate) vein and veinlets. Most of chalcopyrite, pyrite and molybdenite veins together with malachite, azurite and iron hydroxides were concentrated in the trachytic-andesitic units with silicic-argillic alteration. The turning point of this study includes investigating the possibility of LOG-LOG C-P method for separating geochemical anomalies of ore forming elements from the background, accurately determining the cut-off grade, decreasing the area of anomalies, and determining the number of stages of enrichment of elements in the study area compared to the multivariate statistical methods. For this purpose, 85 stream sediment samples taken from a systematic geochemical network were analyzed using ICP-MS method. In order to identify the susceptible mineralization areas by using of concentration-perimeter double LOGarithmic method, thee background values and anomalies were separated for each element in the region. Then, elemental anomaly maps were prepared and finally the distribution maps of the ore-forming elements were mapped and the relevant anomalies were distinguished. The results of using C-P fractal method indicates the presence of possible anomalies of Cu, Mo and Ti elements in the eastern, northeastern, and southwest parts of Shirbit area.

In certain statistical process control applications, quality of a process or product can be characterized by a function commonly referred to as profile. Some of the potential applications of profile monitoring are cases where quality characteristic of interest is modelled using binary, multinomial or ordinal variables. In this paper, profiles with multinomial response are studied. For this purpose, multinomial LOG it regression (MLR) is considered as the basis. Then, the MLR is converted to Poisson GLM with LOG link. Two methods including Multivariate exponentially weighted moving average (MEWMA) statistics, and Likelihood ratio test (LRT) statistics are proposed to monitor MLR profiles in phase II. Performances of these three methods are evaluated by average run length criterion (ARL). A case study from alloy fasteners manufacturing process is used to illustrate the implementation of the proposed approach. Results indicate satisfactory performance for the proposed method.

Zinc is the first modelling language which supports solver and technique independence. This means that a high level conceptual model can be automatically mapped into an appropriate low level design model for a specific solver or technique. To date, Zinc uses three different techniques to solve a model: Constraint Programming (CP), Local Search (LS), and Mixed Integer Programming (MIP). In this way, modellers can examine all solving techniques for their models and see which one gives them the best result. MIP solvers can only accept linear models. Therefore, to map a conceptual model to MIP solvers, the model must be linearized first. In this paper we explain the techniques used in Zinc to linearize high level data structures and expressions which may be appeared in a conceptual model. As a result, modellers can benefit of expressive modelling using nonlinear expressions as well as efficiency of MIP solvers.

pH control is a challenging problem due to its highly nonlinear nature. In this paper the performances of two different adaptive global linearizing controllers (GLC) are compared. Least squares technique has been used for identifying the titration curve. The first controller is a standard GLC based on material balances of each species. For implementation of this controller a nonlinear state estimator is used. Some modifications are proposed to avoid the singularity of the observer gain. The second controller is designed based on the reduced state equation. Through computer simulations, it has been shown that the performances of the second GLC is superior and it is more robust to process model mismatch. It should be also noted that the design of reduced state-based GLC is much easier and dose not need observer for implementation.