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This study deals with the emission of methane in relation to changing environmental conditions and human impact, in three mangrove ecosystems of south India. Time-varying¯uxes of methane adopting the close chamber technique were used to estimate CH 4 emission from an unpolluted site (Pichavaram mangroves) and two polluted sites viz. (1) Ennore Creek mangroves (affected by fertilizer ef¯uents and crude oil discharges) and (2) Adyar estuary mangroves (affected by the discharges of organic and industrial wastes), covering monthly and seasonal variations. The results indicate annual average CH 4 emissions of 7.4, 5.02 and 15.4 mg m )2 h )1 from the sediment±water interface of the Pichavaram, Ennore Creek and Adyar estuary respectively. Emission characteristics obtained at Pichavaram mangroves represent a natural variability with changing physico-chemical factors, whereas the emission characteristics at Ennore Creek and Adyar estuary mangroves show anthropogenic in¯uence. Several environmental factors such as oxygen availability, organic matter, soil physical and chemical properties, in addition to human-mediated interventions have been identi®ed as in¯uencing emission rates in the mangrove ecosystems. Preliminary CH 4 emission estimates for the mangrove ecosystems along the Indian subcontinent and the tropical and subtropical coastline of the world by linear extrapolation based on surface area range from 0.05 to 0.37 and 2.8 to 19.25 Tg CH 4 year )1 respectively. Our results also highlight the impact of human activities on future emission of methane from the mangrove ecosystems.

Abstract-The main objective of this paper is to develop a new algorithm for scheduling real time tasks. Real time scheduling algorithms such as rate monotonic and deadline monotonic plays an important role in scheduling real time tasks in a real time environment .There are some cases where may arise inconsistencies such as tasks having less task period but their execution is not very important. In this case, when scheduled under rate monotonic algorithm the cpu unnecessarily spends time in scheduling the tasks that are not uttermost importance. The proposed algorithm eliminate this drawback and combines the advantages of both Rate monotonic and Deadline monotonic algorithms. It also incorporates a priority component which is specified by the user which denotes the importance of tasks in the system.

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This paper presented the brushless direct current motor torque ripple reduction based on the speed and torque control using hybrid technique. The dynamic behavior of the brushless direct current motor is analyzed in terms of the parameters such as the speed, current, back electromotive force and torque. Based on the parameters, the motor speed is controlled and minimized the torque ripples. For controlling the speed of the brushless direct current motor is utilized the fractional-order proportional-integral-derivative controller for generating the optimal control pulses. With the use of fractional-order proportional-integral-derivative controller, the optimal gain parameters are needed to reduce the torque ripples and control the speed of brushless direct current motor. By utilizing the hybrid technique, the gain parameters are utilized to analyze the optimal gain parameters of fractional-order proportional-integralderivative controller. The hybrid technique is the combination of adaptive neuro-fuzzy inference system with firefly algorithm. The proposed strategy is simple in structure and robust to reduce the complexities of the mathematical computations. Initially, the nature inspired optimization algorithm of firefly algorithm is analyzed for finding the error function. In addition, the efficient adaptive neuro-fuzzy inference system controller which becomes an integrated method of approach is performed to control the error functions in order to yields excellent optimized gain values. After that, the control signals are applied to the input of voltage source converter of brushless direct current motor. With this control strategy, the harmonics and torque ripples are minimized. Based on the proposed control strategy, the speed and torque performance is analyzed. The effectiveness of the proposed technique is implemented in MATLAB/Simulink platform and evaluates their performance. The performance analysis of the proposed method is demonstrated and contrasted with the existing techniques such as bat algorithm, particle swarm optimization algorithm and ant-lion optimizer algorithm with fractional-order proportional-integral-derivative controller techniques. KeywordsBrushless direct current motor, torque ripple minimization, speed and torque control, pulse-width modulation, fractional-order proportional-integral-derivative controller, adaptive neuro-fuzzy inference system, firefly algorithm Date