Performance of orthogonal frequency division multiplexing based M-ary quadrature amplitude modulation in asymmetrical dual-hop mixed RF-FSO transmission system

This paper investigates the performance of a dual-hop mixed relay system with radio frequency (RF) and free-space optics (FSO) communication under the effect of pointing error (PE) and atmospheric turbulence (AT). This paper considers a system where RF and FSO links are cascaded. The RF link is modeled by Nakagami-m fading, and the FSO link is modeled as gamma–gamma (G-G) fading channel. Both the channel models use orthogonal frequency division multiplexing (OFDM) with M-ary quadrature amplitude modulation (QAM). The expressions for probability density function, cumulative distribution function, signal-to-noise ratio, and ergodic capacity are derived. The moment generating function (MGF) of fading and the bit error rate (BER) of the OFDM-based M-ary QAM scheme is derived in terms of Meijer's G-function. It has been observed that, in fixed gain relay systems, the modulation scheme's BER is dominated by the SNR of the RF link. While in a variable gain relay system, the turbulence conditions of the FSO system affect the SNR and the BER of the modulation method. The feasibility of heterodyne detection and intensity modulation direct detection (IM/DD) is analyzed in terms of outage probability and ergodic capacity. The results can be used to choose the optimal modulation order and relay system for QAM-OFDM-based optical wireless systems.     

Purification,characterization, antibacterial activity and N-terminal sequencing of buffalo-milk lysozyme

Lysozyme from buffalo milk was purified to homogeneity and its N-terminal amino acid sequence, biochemical properties and antibacterial spectrum were determined. The purification procedure, comprising ion-exchange chromatography using CM-cellulose and size-exclusion chromatography using Sephadex G-50, conferred 8622-fold purification and 39.3% recovery of lysozyme. The purified enzyme migrated as a single band on sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) and native PAGE. Immunological purity of lysozyme preparation was confirmed by immuno-electrophoresis. Molecular weight of buffalo-milk lysozyme as determined by SDS-PAGE was 16 kDa and its amino acid composition was determined by reverse phase high performance liquid chromatography (HPLC). The sequence of 23 amino acid residues at the N-terminal end showed 56.5% homology with bovine milk lysozyme and 30.4% with equine milk lysozyme. The specific activity of buffalo milk lysozyme was ten-times that of bovine milk lysozyme. Buffalo-milk lysozyme was active over a wide range of pH and its activity was strongly influenced by molarity of the medium. Antibacterial activity of buffalo-milk lysozyme was determined against 11 species of bacteria; out of seven Gram-positive bacteria tested, four were inhibited, while Gram-negative bacteria were resistant.     

Management of Multipurpose Multireservoir Using Fuzzy Interactive Method

In this paper a fuzzy interactive method is proposed for efficient management of multipurpose multireservoir problems. The proposed method provides an option to decision maker (DM) to work in an interactive manner to achieve the conflicting objectives as close to their desired values as is practically feasible. In each iteration, fuzzy membership functions of various objectives are framed and combined into a single objective using the product operator. The single objective nonlinear optimization model thus framed in each iteration is numerically solved using genetic algorithm. The solution provides the values of the objectives which can be actually achieved keeping in view their aspired values as provided by DM. At the end of each iteration, DM has the option to modify the aspired values of one or more objectives keeping in view the results obtained by the algorithm thus far. The algorithm is stopped when DM feels satisfied with the results. The working of the proposed method has been demonstrated on the mathematical model of a realistic multipurpose multireservoir system taken from literature.     

An improved algorithm for connectivity analysis of distribution networks

In the present paper, an efficient algorithm for connectivity analysis of moderately sized distribution networks has been suggested. Algorithm is based on generation of all possible minimal system cutsets. The algorithm is efficient as it identifies only the necessary and sufficient conditions of system failure conditions in n-out-of-n type of distribution networks. The proposed algorithm is demonstrated with the help of saturated and unsaturated distribution networks. The computational efficiency of the algorithm is justified by comparing the computational efforts with the previously suggested appended spanning tree (AST) algorithm. The proposed technique has the added advantage as it can be utilized for generation of system inequalities which is useful in reliability estimation of capacitated networks.     

Hybrid approach for congestion management using optimal placement of distributed generator

Congestion management (CM) in a large power system network is a difficult task which can be solved by placing one or more distributed generators (DGs) on congested lines. The first concern is to determine the exact location of congested line for the placement of optimal size of DG so that cost can be minimised. In this work, hybridisation of firefly technique and differential evolution optimisation search has been proposed, which manages congestion effectively by rescheduling of generators satisfying the system constraints both technically and economically in the deregulated market scenario. To validate the proposed hybrid approach, results have been compared with firefly optimisation technique results. It is observed that the hybrid approach is an efficient tool in handling CM resulting in a secure operation to reduce flows in the heavily loaded lines with low system loss and increasing power capability with improved stability of network by controlling power flows in the network.     

Structural and thermal characterization of CaO–MgO–SiO2–P2O5–CaF2 glasses

The influence of varying the CaO/MgO ratio on the structure and thermal properties of CaO–MgO–SiO₂–P₂O₅–CaF₂ glasses was studied in a series of eight glass compositions in the glass forming region of diopside (CaMgSi₂O₆)–fluorapatite [Ca₅(PO₄)₃F]–wollastonite (CaSiO₃) ternary system. The melt-quenched glasses were characterized for their structure by infrared spectroscopy (FTIR) and magic angle spinning (MAS)-nuclear magnetic resonance (NMR) spectroscopy. Silicon is predominantly present as Q² (Si) species, while phosphorus tends to coordinate in orthophosphate environment. The sintering and crystallization parameters of the glasses were obtained from differential thermal analysis (DTA) while crystalline phase fractions in the sintered glass–ceramics were analyzed by X-ray diffraction adjoined with Rietveld refinement. Diopside, fluorapatite, wollastonite and pseudowollastonite crystallized as the main crystalline phases in all the glass–ceramics with their content varying with respect to variation in CaO/MgO ratio in glasses. The implications of structure and sintering behaviour of glasses on their bioactivity were discussed.     

Morita therapy: Its basic features and cognitive intervention for anxiety treatment.

Describes Morita therapy as being centered around positive reinterpretation of anxiety in order to stimulate attentional, attitudinal, and behavioral change in self-preoccupied anxious clients. It promotes clients' behavioral commitment to constructive and productive activities. The shinkeishitsusho disposition is regarded as a combination of predispositional nervousness and hypersensitivity and learned and habituated cognitive patterns of anxious self-preoccupation. The aim of the therapy is not to reject the nervous disposition but to modify clients' dysfunctional cognitive and behavioral patterns to reduce unproductive self-preoccupation. The therapy promotes clients' acceptance of their predispositional nervous sensitivity and anxiousness, not as personal weaknesses but as potentially functional and constructive qualities as they are redirected toward concrete tasks and realistic action-taking. Therapeutic progress is thus initiated when clients take a positive view of their previously rejected nervous dispositions and successfully apply it to practical activities for productive purposes. Similarities and differences between Morita therapy and rational-emotive therapy are noted. (39 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Artificial bee colony based energy‐aware resource utilization technique for cloud computing

Cloud computing is a form of distributed computing, which promises to deliver reliable services through next‐generation data centers that are built on virtualized compute and storage technologies. It is becoming truly ubiquitous and with cloud infrastructures becoming essential components for providing Internet services, there is an increase in energy‐hungry data centers deployed by cloud providers. As cloud providers often rely on large data centers to offer the resources required by the users, the energy consumed by cloud infrastructures has become a key environmental and economical concern. Much energy is wasted in these data centers because of under‐utilized resources hence contributing to global warming. To conserve energy, these under‐utilized resources need to be efficiently utilized and to achieve this, jobs need to be allocated to the cloud resources in such a way so that the resources are used efficiently and there is a gain in performance and energy efficiency. In this paper, a model for energy‐aware resource utilization technique has been proposed to efficiently manage cloud resources and enhance their utilization. It further helps in reducing the energy consumption of clouds by using server consolidation through virtualization without degrading the performance of users’ applications. An artificial bee colony based energy‐aware resource utilization technique corresponding to the model has been designed to allocate jobs to the resources in a cloud environment. The performance of the proposed algorithm has been evaluated with the existing algorithms through the CloudSim toolkit. The experimental results demonstrate that the proposed technique outperforms the existing techniques by minimizing energy consumption and execution time of applications submitted to the cloud. Copyright © 2014 John Wiley & Sons, Ltd.