On the orness of Bonferroni mean and its variants

This article addresses orness measures to reflect the or-like degree of the Bonferroni mean (BM) and its variants. Some properties of these operators associated with their orness measures are portrayed analytically. However, the general orness measure involves the multiple integrals with the integral fold number being the number of the aggregated elements and as a result, the computation becomes complicated when the number of the aggregated elements is large. Furthermore, the analytical formula of the orness measure often cannot be obtained. For this reason, this study concentrates on Monte Carlo simulation to validate the result. We estimate the two parameters of the BM for a predefined orness value and a fixed length of the input vector. Besides the theoretical study of orness measure related to BM and its variants, the article also explores the simulation-based results. To support this, we provide four numerical examples.     

Effectivity of copper and cadmium sulphide nanoparticles in mitotic and meiotic cells of Nigella sativa L. (black cumin) – can nanoparticles act as mutagenic agents?

The present investigation deals with wet chemical preparation and characterisation of copper (Cu) and cadmium sulphide (CdS) nanoparticles (NPs) (using UV–visible spectra, Fourier transform infra-red scattering, X-ray diffraction, dynamic light scattering, field emission scanning electron microscopy and transmission electron microscopy) and their effectivity on mitotic and meiotic cells of Nigella sativa L. (Ranunculaceae) in comparison to ethyl methanesulphonate (EMS) and gamma irradiations. The objective of the study is to foresee whether Cu- and CdS-NPs can induce similar type of chromosomal aberrations as that of EMS and gamma irradiations, or not. Dry seeds of N. sativa (2n = 12) are exposed to Cu- and CdS-NPs (0.25, 0.50 and 1.0 µg/ml; 3 and 6 h), EMS (0.25, 0.50 and 1.0%; 3 and 6 h) and doses of gamma irradiations (25, 50, 100, 200 and 300 Gy). Cu-NPs (range: 25.7 to 120.4 nm; 33.2 nm ± 9.6) and CdS-NPs (range: 29.4 to 115.7 nm; 37.8 nm ± 10.7) are both cubical to spherical in shape. NPs are found to induce similar responses as that of the studied conventional mutagens, in relation to physiological and chromosomal (mitotic and meiotic) attributes. Uptake of Cu- and CdS-NPs in seedlings is also studied using atomic absorption spectroscopy. Results suggest that Cu- and CdS-NPs can act as mutagenic agent, a pioneer report of its kind.     

Medium optimization for high yield production of extracellular human interferon-<Emphasis Type="Italic">γ</Emphasis> from <Emphasis Type="Italic">Pichia pastoris</Emphasis>: A statistical optimization and neural network-based approach

Medium development for high level expression of human interferon gamma (hIFN-γ) from Pichia pastoris (GS115) was performed with the aid of statistical and nonlinear modeling techniques. In the initial screening, gluconate and glycine were found to be key carbon and nitrogen sources, showing significant effect on production of hIFN-γ. Plackett-Burman screening revealed that medium components., gluconate, glycine, KH₂PO₄ and histidine, have a considerable impact on hIFN-γ production. Optimization was further proceeded with Box-Behnken design followed by artificial neural network linked genetic algorithm (ANN-GA). The maximum production of hIFN-γ was found to be 28.48mg/L using Box-Behnken optimization (R²=0.98), whereas the ANN-GA based optimization had displayed a better production rate of 30.99mg/L (R²=0.98), with optimal concentration of gluconate=50 g/L, glycine=10.185 g/L, KH₂PO₄=35.912 g/L and histidine 0.264 g/L. The validation was carried out in batch bioreactor and unstructured kinetic models were adapted. The Luedeking-Piret (L-P) model showed production of hIFN-γ was mixed growth associated with the maximum production rate of 40mg/L of hIFN-γ production.     

Neuro-Resistive Grid approach to trainable controllers: A pole balancing example

A new neural network approach is described for the task of pole-balancing, considered a benchmark learning control problem. This approach combines Barto, Sutton and Anderson's [1] Associative Search Element (ASE) with a Neuro-Resistive Grid (NRG) [2] acting as Adaptive Critic Element (ACE). The novel feature in NRG is that it provides evaluation of a state based on propagation of the failure information to the neighbours in the grid. NRG is updated only on a failure, and provides ASE with a continuous internal reinforcement signal by comparing the value of the present state to the previous state. The resulting system learns more rapidly and with fewer computations than that of Barto et al.[1]. To establish a uniform basis of comparison of algorithms for pole balancing, both the systems are simulated using benchmark parameters and tests specified in Geva and Sitte [3].     

Multi-objective optimization problem under fuzzy rule constraints using particle swarm optimization

In this paper, a fuzzy multi-objective programming problem is considered where functional relationships between decision variables and objective functions are not completely known to us. Due to uncertainty in real decision situations sometimes it is difficult to find the exact functional relationship between objectives and decision variables. It is assumed that information source from where some knowledge may be obtained about the objective functions consists of a block of fuzzy if-then rules. In such situations, the decision making is difficult and the presence of multiple objectives gives rise to multi-objective optimization problem under fuzzy rule constraints. In order to tackle the problem, appropriate fuzzy reasoning schemes are used to determine crisp functional relationship between the objective functions and the decision variables. Thus a multi-objective optimization problem is formulated from the original fuzzy rule-based multi-objective optimization model. In order to solve the resultant problem, a deterministic single-objective non-linear optimization problem is reformulated with the help of fuzzy optimization technique. Finally, PSO (Particle Swarm Optimization) algorithm is employed to solve the resultant single-objective non-linear optimization model and the computation procedure is illustrated by means of numerical examples.     

Weight computation of criteria in a decision-making problem by knowledge measure with intuitionistic fuzzy set and interval-valued intuitionistic fuzzy set

The aim of this study is to propose an objective method for determining weights of criteria (also called attributes) based on a new measure of intuitionistic fuzzy information, called knowledge measure, in a real-world multi-criteria decision-making problem under intuitionistic fuzzy and interval-valued intuitionistic fuzzy environment. To address this issue, we first analyze the existing entropy measures and show that their use in objective weight determination process may lead us to produce unreliable weights of criteria by citing appropriate examples. Then we analyze important properties of knowledge measure of intuitionistic fuzzy set (IFS) and also define knowledge measure for interval-valued intuitionistic fuzzy set. Then a new method to determine the weights of criteria is developed on the basis of knowledge measure where information about criteria weights is completely unknown and partly known. A real-life example is presented to illustrate the proposed weight determination method and a comparative analysis is carried out to indicate the practicality and effectiveness of knowledge-based weight-generation method under both intuitionistic fuzzy and interval-valued intuitionistic fuzzy environment. Finally, we formulate the axioms for knowledge measure associated with IFSs and we also propose families (classes) of knowledge measures.     

Evaluating the impact of service quality on the dynamics of customer satisfaction in the telecommunication industry of Jorhat,Assam

Telecommunication Systems - Service quality acts as an antecedent to customer satisfaction (CS). Evaluation of service quality in an enterprise is vital to improve productivity and increase CS....