A 5.8 GHz Low Noise Amplifier for Wireless LAN Applications in Silicon Bipolar Technology

A monolithic integrated low-noise amplifier for operation in the 5.8-GHzband is described. Two different versions have been implemented where the biasing wasadapted to allow operation over a different range of supply voltage. At 5-V, theamplifiers gain is about 17-dB, with a noise figure of 4.2-dB and 1-dB compressionpoint at –15-dBm input power. The circuits have been designed utilizing a0.6-micron silicon bipolar production technology, featuring npn transistors with and of about20-GHz.     

Optimum lipid production using agro-industrial wastewater treated microalgae as biofuel substrate

Abundant wastewater discharges from palm oil industries in tropical nations being a valuable resource of biodiesel need proper exploration. Research hinted that such wastewater as economical nutrient source or substrate can support the cultivation of microalgae. In this experiment, we have tested the growth and lipid production of five different microalgal strains in palm oil mill effluent (POME). POME as a biofuel substrate is demonstrated to be lucrative for microalgae-assisted lipids production. POME is rich in macro- and micronutrients can be used as a growth medium for algal growth in order to reduce the growth medium cost and environmental pollutions. Among the five microalgal strains tested, Chlorella sorokiniana revealed optimum biomass and lipid production. The productivity was evaluated in terms of chlorophyll content, growth rate, biomass, and lipid content, which discerned to be 0.099/day, 8.0 mg/L day and 2.68 mg/mg cell dry weight (CDW). Furthermore, in this study, an optimization study was carried out to enhance the microalgae to produce high lipid content using carbon-to-nitrogen ratio and different light/dark periods. The presence of nitrogen combined glucose (with a carbon-to-nitrogen ratio 100:7) as an alternative source to carbon displayed higher lipid production of 2.68 (mg/mg CDW) by C. sorokiniana. This study confirms that 8:16 h light/dark condition at C:TN ratio of 100:7 supported to produce high lipid content of 17 mg lipid/mg CDW. The above results revealed that POME could be a suitable growth media for the alga C. sorokiniana to improve the maximum lipid yield for biofuels production.     

Scheduling with an outsourcing option on both manufacturer and subcontractors

This paper addresses a single-stage scheduling problem with outsourcing allowed where each job can be either scheduled for in-house production or outsourced to one of the outside subcontractors available. The manufacturer has an unrelated parallel machine system, and each subcontractor has its own single machine. Subcontractors are capable to process all the jobs. Unlike most of past research, our study considers the joint scheduling of both in-house and outsourced jobs simultaneously. The objective is to minimize sum of the total weighted completion time and total outsourcing cost. An integer programming formulation is presented and then improved through an optimality property on job orders. A heuristic algorithm is also introduced to decompose the problem into smaller and easier subproblems and solve them to optimality.     

A novel adaptive fuzzy predictive control for hybrid systems with mixed inputs

This paper proposes a new adaptive nonlinear model predictive control (NMPC) methodology for a class of hybrid systems with mixed inputs. For this purpose, an online fuzzy identification approach is presented to recursively estimate an evolving Takagi–Sugeno (eTS) model for the hybrid systems based on a potential clustering scheme. A receding horizon adaptive NMPC is then devised on the basis of the online identified eTS fuzzy model. The nonlinear MPC optimization problem is solved by a genetic algorithm (GA). Diverse sets of test scenarios have been conducted to comparatively demonstrate the robust performance of the proposed adaptive NMPC methodology on the challenging start-up operation of a hybrid continuous stirred tank reactor (CSTR) benchmark problem.     

Modified self-organising maps with a new topology and initialisation algorithm

Mapping quality of the self-organising maps (SOMs) is sensitive to the map topology and initialisation of neurons. In this article, in order to improve the convergence of the SOM, an algorithm based on split and merge of clusters to initialise neurons is introduced. The initialisation algorithm speeds up the learning process in large high-dimensional data sets. We also develop a topology based on this initialisation to optimise the vector quantisation error and topology preservation of the SOMs. Such an approach allows to find more accurate data visualisation and consequently clustering problem. The numerical results on eight small-to-large real-world data sets are reported to demonstrate the performance of the proposed algorithm in the sense of vector quantisation, topology preservation and CPU time requirement.     

Terahertz fluorescence quantum beats in a dye solution

Time-resolved fluorescence of a dye molecule in liquid solution at room temperature, monitored with femtosecond resolution, reveals small-amplitude quantum beats with subpicosecond periods and picosecond damping. Specifically, the observation of damped ripples on the electronic fluorescence of a large dye molecule oxazine 1 (MW=324) in different liquid solvents (methanol, water) manifesting terahertz vibrational quantum beats is reported     

Estimating botnet virulence within mathematical models of botnet propagation dynamics

Mathematical models of botnet propagation dynamics are increasingly deemed to have potential for significant contribution to botnet mitigation. Botnet virulence, which comprises network vulnerability rate and network infection rate, is a key factor in those models. In this paper we discuss a practical approach that draws on epidemiological models in biology to estimate the botnet virulence in a network. Our research provides mathematical models of botnet propagation dynamics with concrete measures of botnet virulence, which make those models practical and hence employable in mitigation of real world botnets in a timely fashion. The approach is based on random sampling and follows a novel application of statistical learning and inference in a botnet-versus-network setting. We have implemented this research in the Matlab programming language. In this paper, we discuss an experimental evaluation of the effectiveness of this research with respect to botnet propagation dynamics realistically simulated in a GTNetS network simulation platform.     

Moisture and heat transfer in hybrid weft knitted fabric with artificial intelligence

One of the most important properties of clothes is their ability to help the body's thermal system to keep the body temperature in its natural range, even if the environmental conditions or physical activities are outside the body's ideal range. Perspiring is one of the most important effects of physical activities in warm weather for shedding the body's excessive heat. Therefore, the basic requirement of a fabric worn next to the skin is to transfer this moisture to the atmosphere to reach comfort through the avoidance of a feeling of wetness and clamminess and also through the generation of a situation for the best surface evaporation of moisture. The main goal of this study was to achieve a kind of fabric that guarantees comfort for the body by good heat and moisture transport. To achieve this goal, a group of double‐surface fabrics containing hydrophilic and hydrophobe fibers were knitted, and their simultaneous heat and moisture transport was evaluated with the help of a perspiration‐simulation machine; the results were analyzed as transfer process plots. Also, the transmission of heat and moisture was evaluated for all of the samples by differential modeling as an artificial neural network. Effective parameters on heat and moisture transfer were taken into consideration with modeling and statistical methods. The results were analyzed to find a suitable fabric with optimum comfort. The final results showed that a fabric made of micropolyester filaments and cotton yarns on the bottom and top surfaces, respectively, had the best heat and moisture transfer. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009