Simultaneous Rp-Hplc Method For Determination Of Betamethasone Dipropionate And Tolnaftate In Combined Semisolid Formulation

A new RP-HPLC method was developed for selective and simultaneous determination of betamethasone dipropionate and tolnaftate in combined semisolid formulation containing other components. Further, the proposed method was validated for linearity, precision (system precision, method precision, intermediate or inter-day precision), accuracy, stability in analytical solution, robustness or system suitability and ruggedness. The developed method exhibited the best results in terms of the aforesaid validation parameters. The other components and additives did not interfere in their determinations. The method was found to be selective, simple, economical, accurate, reproducible, rapid and reliable for routine estimation purpose of these drugs in combined semisolid formulations.

A scenario-based parametric analysis of the army personnel-to-assignment matching problem

Purpose This study aims to compare linear programming and stable marriage approaches to the personnel assignment problem under conditions of uncertainty. Robust solutions should exhibit reduced variability of solutions in the presence of one or more additional constraints or problem perturbations added to some baseline problems. Design/methodology/approach Several variations of each approach are compared with respect to solution speed, solution quality as measured by officer-to-assignment preferences and solution robustness as measured by the number of assignment changes required after inducing a set of representative perturbations or constraints to an assignment instance. These side constraints represent the realistic assignment categorical priorities and limitations encountered by army assignment managers who solve this problem semiannually, and thus the synthetic instances considered herein emulate typical problem instances. Findings The results provide insight regarding the trade-offs between traditional optimization and heuristic-based solution approaches. Originality/value The results indicate the viability of using the stable marriage algorithm for talent management via the talent marketplace currently used by both the U.S. Army and U.S. Air Force for personnel assignments.

A Construction Schedule Robustness Measure Based on Improved Prospect Theory and the Copula-CRITIC Method

A robustness measure is an effective tool to evaluate the anti-interference capacity of the construction schedule. However, most research focuses on solution robustness or quality robustness, and few consider a composite robustness criterion, neglecting the bounded rationality of subjective weights and inherent importance and nonlinear intercriteria correlations of objective weights. Therefore, a construction schedule robustness measure based on improved prospect theory and the Copula-criteria importance through intercriteria correlation (CRITIC) method is proposed. Firstly, a composite robustness criterion is established, including start time deviation rs and structural deviation rp for measuring solution robustness from project execution and completion probability rc for measuring quality robustness from the project result. Secondly, bounded rationality is considered, using prospect theory to calculate subjective weights, which is improved by the interval distance formula. Thirdly, the Copula-CRITIC method is proposed to determine objective weights incorporating both inherent importance and nonlinear intercriteria correlations. Finally, an information-entropy-based evidence reasoning method is applied to combine subjective and objective weights together while identifying their validity. An underground power station in China is used for a case study, whose robustness is measured using the proposed methods, single robustness criterion, and composite robustness criterion using traditional weighting methods. The comparison results verify the consistency, representativeness, and advantage of the proposed criterion and methods.

The performance of COR optimisation using different constraint handling strategies to solve ELD

This research compares the performance of Competitive Over Resources (COR) optimisation method using a different type of constraint handling strategy to solve the economic load dispatch (ELD) problem. Previously, most research focused on proposing various optimisation techniques using the Penalty Factor Strategy (PFS) to search for a better global optimum. The issue using the penalty factor is that it is difficult to find the correct tune of constant value that influences the algorithm to find the solution. The other technique is using Feasible Solution Strategy (FSS), the idea of which is to locate the infeasible particle to the feasible solution and avoid being trapped by the unsuccessful condition of constraint. This paper investigates the performance of PFS and FSS on the COR optimisation method for solving ELD. Both strategies have been tested on two standard test systems to compare the performance in terms of a global solution, robustness and convergence. The simulation shows that FSS is a better solution compared to PFS.

Relative Average Deviation as Measure of Robustness in the Stochastic Project Scheduling Problem

In the Project Scheduling Problem (PSP), the solution robustness can be understood as the capacity that a baseline has to support the disruptions generated by unplanned events (risks). A robust baseline of the project can be obtained from redundancy based methods, which are considered proactive methods to solve the stochastic project scheduling problem. In this research, three redundancy based methods are evaluated and their performance is compared in terms of robustness. These methods add extra time to the original activities duration in order to face the eventualities that may appear during the project execution. In this article a new indicator to analyze the solution robustness to the Project Scheduling Problem with random duration of activities is proposed. This indicator called Relative Average Deviation (RAD) is defined as the margin of deviation of the activities’ start times in relation to their durations. The RAD is based in a traditional concept that seeks to minimize the value of the differences between the planned start times and the real executed start times. The planned start times were obtained from the project baseline generated by each redundancy based method and the real executed start times were obtained from a simulation process based on Monte Carlo technique. The new indicator was used to evaluate the robustness of three baselines generated by different methods but applied to the same case study. Finally, the results suggest that the Relative Average Deviation (RAD) facilitates the interpretation of the robustness concept because it focuses on analyzing the deviation margin associated with an activity.

Investigation of Stress-Strain Constitutive Behavior of Intermetallic Alloys

The study aims to estimate the stress-strain constitutive behavior of intermetallic compounds (IMCs) observed in a solder interconnect from experimental nanoindentation responses through a modified analysis procedure for improved solution robustness based on Cheng and Cheng's and Dao et al.'s models. On the basis of parametric finite element nanoindentation simulation and dimensional analysis together with the concept of representative strain, a set of universal dimensionless functions are established, by which a forward and reverse analysis algorithm are created to predict nanoindentation responses from given elastoplastic properties and vice versa, respectively. The proposed analysis procedure is validated through comparison with the experimental nanoindentation responses and limited literature data. The results show that the proposed analysis procedure is an effective means for plastic property characterization of micro/nanoscale IMCs. The representative strain is found to be 0.056, which differs from the Dao et al.'s and Giannakopoulos and Suresh's estimate. Besides, though generally brittle and hard in nature, the IMCs in a micro/nanoscale thickness show high plasticity, and comprise a yield strength surpassing most typical engineering metals.

Improved solution reliability through generalised finite integral methods

Model solution reliability is shown to be important for applications, where the computational method should accommodate a wide range of flow conditions through each model run without failure through instability or excessive run times. Such difficulties are linked to the use of poor assumptions in the derivation of models, in particular those neglecting energy solutions and the proper treatment of gradient discontinuities and shocks. Finite integral methods are introduced as a formal extension of longstanding traditional hydraulic analysis, leading through Control Element Lifetime Locus (CELL) Integral analysis to a new set of fundamental balance equations, the Full Hydraulic equations. These are then formulated for hydraulic streamtube analysis and discretised for separate numerical solutions for momentum and energy balances. Case studies for steady flow are referenced, where CELL energy balances improve solution robustness through a variable weighting scheme, accelerating convergence in comparison with widely used fixed weighting Upstream Differencing and Central Differencing schemes. A standard dambreak case study is then used to show the same robust system also copes with severe unsteady flow discontinuities, even while Courant Numbers are varied by orders of magnitude.

COMPARING MINIMUM NEIGHBORHOOD EVALUATION SCHEMES FOR FINDING SPATIALLY ROBUST SOLUTIONS

The common definition for robust solutions considers a solution robust if it remains optimal when the parameters defining the fitness function are perturbed. A second definition that can be found in the literature: robustness occurs when a solution can be varied spatially without a significant drop in fitness. We propose an alternative operational definition for spatial robustness: both the solution and the neighbourhood around the solution has fitness above a given threshold. With this new definition, we created a set of functions with useful properties to allow for the testing of solution robustness. The performance of a Genetic Algorithm (GA) is then evaluated based on its ability to identify multiple robust solutions based on the above robustness definition. Different neighbourhood evaluation schemes are identified from the literature and compared, with the minimum neighbour technique proving to be the most effective.