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.

We give an algorithm, called T*, for finding the k shortest simple paths connecting a certain pair of nodes, s and t, in a acyclic digraph. First the nodes of the graph are labeled according to the topoLOGical ordering. Then for node i an ordered list of simple s - i paths is created. The length of the list is at most k and it is created by using tournament trees. We prove the correctness of T* and show that its worst-case complexity is O (m+kn LOG d) in which n is the number of nodes and m is the number of arcs and d is the mean degree of the graph. The algorithm has a space complexity of O (kn) which entails an important improvement in space complexity. An experimental evaluation of T* is presented which confirms the advantage of our algorithm compared to the most efficient k shortest paths algorithms known so far.

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.

Background and the purpose of the study: Partition coefficients (LOG D and LOG P) and molecular surface area (PSA) are potential predictors of the intestinal permeability of drugs. The aim of this investigation was to evaluate and compare these intestinal permeability indicators.Methods: Aqueous solubility data were obtained from literature or calculated using ACD/Labs and ALOGPS. Permeability data were predicted based on LOG P, LOG D at pH 6.0 (LOG D6.0), and PSA.Results: Metoprolol’s LOG P, LOG D6.0 and a PSA of<65 A correctly predicted 55.9%, 50.8% and 54.2% of permeability classes, respectively. Labetalol’s LOG P, LOG D6.0, and PSA correctly predicted 54.2%, 64.4% and 61% of permeability classes, respectively. LOG D6.0 correlated well (81%) with Caco-2 permeability (Papp). Of the list of national essential medicines, 135 orally administered drugs were classified into biopharmaceutical classification system (BCS). Of these, 57 (42.2%), 28 (20.7%), 44 (32.6%), and 6 (4.4%) were class I, II, III and IV respectively.Conclusion: LOG D6.0 showed better prediction capability than LOG P. Metoprolol as permeability internal standard was more conservative than labetalol.

In this paper, we present a modified LOG Burr XII (MLBXII) distribution developed on the basis of a generalized LOG Pearson differential equation. This dis-tribution is also obtained from a compounding mixture of distributions. Moments, inequality measures, uncertainty measures and reliability measures are theoretically established. Characterizations of MLBXII distribution are also studied via different techniques. Parameters of MLBXII distribution are estimated using the maximum likelihood method. Goodness of fit of this distribution through different methods is studied.