As per World Health Organization report which was released in the year of 2019,Diabetes claimed the lives of approximately 1.5 million individuals globally in 2019 and around 450 million people are affected by diabete...As per World Health Organization report which was released in the year of 2019,Diabetes claimed the lives of approximately 1.5 million individuals globally in 2019 and around 450 million people are affected by diabetes all over the world.Hence it is inferred that diabetes is rampant across the world with the majority of the world population being affected by it.Among the diabetics,it can be observed that a large number of people had failed to identify their disease in the initial stage itself and hence the disease level moved from Type-1 to Type-2.To avoid this situation,we propose a new fuzzy logic based neural classifier for early detection of diabetes.A set of new neuro-fuzzy rules is introduced with time constraints that are applied for thefirst level classification.These levels are further refined by using the Fuzzy Cognitive Maps(FCM)with time intervals for making thefinal decision over the classification process.The main objective of this proposed model is to detect the diabetes level based on the time.Also,the set of neuro-fuzzy rules are used for selecting the most contributing values over the decision-making process in diabetes prediction.The proposed model proved its efficiency in performance after experiments conducted not only from the repository but also by using the standard diabetic detection models that are available in the market.展开更多
This research proposes a more advanced way to address Combined Economic Emission Dispatch(CEED)concerns.Economic Load Dispatch(ELD)and Economic Emission Dispatch(EED)have been implemented to reduce generating unit fue...This research proposes a more advanced way to address Combined Economic Emission Dispatch(CEED)concerns.Economic Load Dispatch(ELD)and Economic Emission Dispatch(EED)have been implemented to reduce generating unit fuel costs and emissions.When both economics and emission tar-gets are taken into account,the dispatch of an aggregate cost-effective emission challenge emerges.This research affords a mathematical modeling-based analyti-cal technique for solving economic,emission,and collaborative economic and emission dispatch problems with only one goal.This study takes into account both the fuel cost target and the environmental impact of emissions.This bi-inten-tion CEED problem is converted to a solitary goal function using a price penalty factor technique.In this case,a metaheuristic and an environment-inspired,intel-ligent Spider Monkey Optimization technique(SMO)are used to address the CEED dilemma.By following the generator’s scheduling process,the SMO meth-od is used to regulate the output from the power generation system in terms of pollution and fuel cost.The Fission-Fusion social(FFS)structure of spider mon-keys promotes them to utilize a global optimization method known as SMO dur-ing foraging behaviour.The emphasis is mostly on lowering the cost of generation and pollution in order to improve the efficiency of the power system and han-dle dispatch problems with constraints.The economic dispatch has been reme-died,and the improved result demonstrates that the system’s performance is stable andflexible in real time.Finally,the system’s output demonstrates that the system has improved in resolving CEED difficulties.When compared to ear-lier investigations,the proposed model’sfindings have improved.As the gener-ating units,wind and solar are used to explore the CEED crisis in the IEEE 30 bus system.展开更多
This work investigates the performance of various forward error correction codes, by which the MIMO-OFDM system is deployed. To ensure fair investigation, the performance of four modulations, namely, binary phase shif...This work investigates the performance of various forward error correction codes, by which the MIMO-OFDM system is deployed. To ensure fair investigation, the performance of four modulations, namely, binary phase shift keying(BPSK), quadrature phase shift keying(QPSK), quadrature amplitude modulation(QAM)-16 and QAM-64 with four error correction codes(convolutional code(CC), Reed-Solomon code(RSC)+CC, low density parity check(LDPC)+CC, Turbo+CC) is studied under three channel models(additive white Guassian noise(AWGN), Rayleigh, Rician) and three different antenna configurations(2×2, 2×4, 4×4). The bit error rate(BER) and the peak signal to noise ratio(PSNR) are taken as the measures of performance. The binary data and the color image data are transmitted and the graphs are plotted for various modulations with different channels and error correction codes. Analysis on the performance measures confirm that the Turbo + CC code in 4×4 configurations exhibits better performance.展开更多
The chemical bath deposition (CBD) technique was used for the synthesis of the tin oxide (SnO2) thin films. X-ray diffraction (XRD) was employed to find the crystallite size by using Debye Scherrer’s formula. The sur...The chemical bath deposition (CBD) technique was used for the synthesis of the tin oxide (SnO2) thin films. X-ray diffraction (XRD) was employed to find the crystallite size by using Debye Scherrer’s formula. The surface morphology of SnO2 films was analyzed by the scanning electron microscopic (SEM) studies. The FT-IR spectrum exhibits the strong presence of SnO2. The optical properties of the SnO2 thin films were determined using UV-Visible spectrum. The dielectric studies were carried out at different frequencies and at different temperatures for the prepared SnO2 thin films. Further, electronic properties, such as valence electron plasma energy, average energy gap or Penn gap, Fermi energy and electronic polarizability of the SnO2 thin films, were determined. The ac conductivity of the SnO2 thin films increases with increase in temperature and frequency. The activation energy was determined by using dc electrical conductivity measurement. The Hall properties were also calculated.展开更多
Aim: Lignocelluloytic enzymes are the largest class of hydrolase enzyme which utilizes the plant biomass to produce renewable sources. Hence practices for larger production of these enzymes at lower cost received much...Aim: Lignocelluloytic enzymes are the largest class of hydrolase enzyme which utilizes the plant biomass to produce renewable sources. Hence practices for larger production of these enzymes at lower cost received much attention for industrial use. Hence this paper deals with expression and purification of cellobiohydrolase gene from Penicillium funiculosum NCL1. Methods & Results: A cellobiohydrolase gene, cbhII of Penicillium funiculosum NCL1 was cloned and expressed in Pichia pastoris X33. Two exons of the cbhII gene were amplified separately and fused by overlap extension PCR. The fused product was cloned in yeast expression vector pPICZαA and expressed in P. pastoris under the control of the AOX1 promoter. P. pastoris transformants expressing recombinant cellobiohydrolase were selected on CMC agar plate and their ability to produce the cellobiohydrolase was evaluated in flask cultures. P. pastoris X33 (pPICbh6) efficiently secreted the recombinant cellobiohydrolase into the medium and produced the cellobiohydrolase activity (5 U/ml) after 96 h of growth. The recombinant cellobiohydrolase produced by P. pastoris (pPICBH6) showed maximum activity at pH 4.0 and temperature 50°C and higher specificity in hydrolysis of filter-paper.展开更多
This paper presents an application of GRADE Algorithm based approach along with PV analysis to solve multi objective optimization problem of minimizing real power losses, improving the voltage profile and hence enhanc...This paper presents an application of GRADE Algorithm based approach along with PV analysis to solve multi objective optimization problem of minimizing real power losses, improving the voltage profile and hence enhancing the performance of power system. GRADE Algorithm is a hybrid technique combining genetic and differential evolution algorithms. Control variables considered are Generator bus voltages, MVAR at capacitor banks, transformer tap settings and reactive power generation at generator buses. The optimal values of the control variables are obtained by solving the multi objective optimization problem using GRADE Algorithm programmed using M coding in MATLAB platform. With the optimal setting for the control variables, Newton Raphson based power flow is performed for two test systems, viz, IEEE 30 bus system and IEEE 57 bus system for three loading conditions. Minimization of Real power loss and improvement of voltage profile obtained are compared with the results obtained using firefly and particle swarm optimization (PSO) techniques. Improvement of Loadability margin is established through PV curve plotted using continuation power flow with the real power load at the most affected bus as the bifurcation parameter. The simulated output shows improved results when compared to that of firefly and PSO techniques, in term of convergence time, reduction of real power loss, improvement of voltage profile and enhancement of loadability margin.展开更多
The present study revealed proliferation of macro-algae modifying coral reef ecosystems in a different manner due to diseases and sedimentations in the Mandapam group of islands in the Gulf of Mannar. Benthic surveys ...The present study revealed proliferation of macro-algae modifying coral reef ecosystems in a different manner due to diseases and sedimentations in the Mandapam group of islands in the Gulf of Mannar. Benthic surveys were conducted with major attack of seven coral reefs diseases with high sedimentation rate, nine species of fleshy macro-algae(Turbinaria ornata, Turbinaria conaides, Caulerpa scalpelliformis, Caulerpa racemosa, Kappaphycus alvarezii, Padina gymnosphora, Sargassum wightii, Ulva reticulata and Calurpa lentillifera) proliferation against major corals life forms(Acropora branching, Acropora digitate, Acropora tabulate, coral massive, coral submassive, coral foliose and coral encrusting). The results confirm that diseased corals most favor to macro-algae growth(15.27%) rather than the sedimentation covered corals(8.24 %). In the degradation of coral life forms, massive corals were more highly damaged(7.05%) than any other forms. Within a short period of time(May to September), coral coverage shrank to 17.4% from 21.9%, macro-algae increased 23.51% and the average sedimentation rate attained 77.52 mg cm^(-2) d^(-1) with persisting coral reef diseases of 17.59%. The Pearson correlation showed that the coral cover decreased with increasing macro-algae growth, which was statistically significant(r =-0.774, n = 100, P < 0.0005). The proliferation of the various macro-algae C. scalpellifrmis, T. ornata, C. racemosa, T. conaides, U. reticulata, S. wightii, K. alvarezii, P. gymnosphora and C. lentillifera increased with percentages of 6.0, 5.8, 5.7, 4.9, 4.2, 3.7, 2.7 and 1.9, respectively. If this trend continues, the next generation of new recruit corals will undoubtedly lead to a phase shift in Gulf of Mannar corals.展开更多
文摘As per World Health Organization report which was released in the year of 2019,Diabetes claimed the lives of approximately 1.5 million individuals globally in 2019 and around 450 million people are affected by diabetes all over the world.Hence it is inferred that diabetes is rampant across the world with the majority of the world population being affected by it.Among the diabetics,it can be observed that a large number of people had failed to identify their disease in the initial stage itself and hence the disease level moved from Type-1 to Type-2.To avoid this situation,we propose a new fuzzy logic based neural classifier for early detection of diabetes.A set of new neuro-fuzzy rules is introduced with time constraints that are applied for thefirst level classification.These levels are further refined by using the Fuzzy Cognitive Maps(FCM)with time intervals for making thefinal decision over the classification process.The main objective of this proposed model is to detect the diabetes level based on the time.Also,the set of neuro-fuzzy rules are used for selecting the most contributing values over the decision-making process in diabetes prediction.The proposed model proved its efficiency in performance after experiments conducted not only from the repository but also by using the standard diabetic detection models that are available in the market.
文摘This research proposes a more advanced way to address Combined Economic Emission Dispatch(CEED)concerns.Economic Load Dispatch(ELD)and Economic Emission Dispatch(EED)have been implemented to reduce generating unit fuel costs and emissions.When both economics and emission tar-gets are taken into account,the dispatch of an aggregate cost-effective emission challenge emerges.This research affords a mathematical modeling-based analyti-cal technique for solving economic,emission,and collaborative economic and emission dispatch problems with only one goal.This study takes into account both the fuel cost target and the environmental impact of emissions.This bi-inten-tion CEED problem is converted to a solitary goal function using a price penalty factor technique.In this case,a metaheuristic and an environment-inspired,intel-ligent Spider Monkey Optimization technique(SMO)are used to address the CEED dilemma.By following the generator’s scheduling process,the SMO meth-od is used to regulate the output from the power generation system in terms of pollution and fuel cost.The Fission-Fusion social(FFS)structure of spider mon-keys promotes them to utilize a global optimization method known as SMO dur-ing foraging behaviour.The emphasis is mostly on lowering the cost of generation and pollution in order to improve the efficiency of the power system and han-dle dispatch problems with constraints.The economic dispatch has been reme-died,and the improved result demonstrates that the system’s performance is stable andflexible in real time.Finally,the system’s output demonstrates that the system has improved in resolving CEED difficulties.When compared to ear-lier investigations,the proposed model’sfindings have improved.As the gener-ating units,wind and solar are used to explore the CEED crisis in the IEEE 30 bus system.
文摘This work investigates the performance of various forward error correction codes, by which the MIMO-OFDM system is deployed. To ensure fair investigation, the performance of four modulations, namely, binary phase shift keying(BPSK), quadrature phase shift keying(QPSK), quadrature amplitude modulation(QAM)-16 and QAM-64 with four error correction codes(convolutional code(CC), Reed-Solomon code(RSC)+CC, low density parity check(LDPC)+CC, Turbo+CC) is studied under three channel models(additive white Guassian noise(AWGN), Rayleigh, Rician) and three different antenna configurations(2×2, 2×4, 4×4). The bit error rate(BER) and the peak signal to noise ratio(PSNR) are taken as the measures of performance. The binary data and the color image data are transmitted and the graphs are plotted for various modulations with different channels and error correction codes. Analysis on the performance measures confirm that the Turbo + CC code in 4×4 configurations exhibits better performance.
文摘The chemical bath deposition (CBD) technique was used for the synthesis of the tin oxide (SnO2) thin films. X-ray diffraction (XRD) was employed to find the crystallite size by using Debye Scherrer’s formula. The surface morphology of SnO2 films was analyzed by the scanning electron microscopic (SEM) studies. The FT-IR spectrum exhibits the strong presence of SnO2. The optical properties of the SnO2 thin films were determined using UV-Visible spectrum. The dielectric studies were carried out at different frequencies and at different temperatures for the prepared SnO2 thin films. Further, electronic properties, such as valence electron plasma energy, average energy gap or Penn gap, Fermi energy and electronic polarizability of the SnO2 thin films, were determined. The ac conductivity of the SnO2 thin films increases with increase in temperature and frequency. The activation energy was determined by using dc electrical conductivity measurement. The Hall properties were also calculated.
文摘Aim: Lignocelluloytic enzymes are the largest class of hydrolase enzyme which utilizes the plant biomass to produce renewable sources. Hence practices for larger production of these enzymes at lower cost received much attention for industrial use. Hence this paper deals with expression and purification of cellobiohydrolase gene from Penicillium funiculosum NCL1. Methods & Results: A cellobiohydrolase gene, cbhII of Penicillium funiculosum NCL1 was cloned and expressed in Pichia pastoris X33. Two exons of the cbhII gene were amplified separately and fused by overlap extension PCR. The fused product was cloned in yeast expression vector pPICZαA and expressed in P. pastoris under the control of the AOX1 promoter. P. pastoris transformants expressing recombinant cellobiohydrolase were selected on CMC agar plate and their ability to produce the cellobiohydrolase was evaluated in flask cultures. P. pastoris X33 (pPICbh6) efficiently secreted the recombinant cellobiohydrolase into the medium and produced the cellobiohydrolase activity (5 U/ml) after 96 h of growth. The recombinant cellobiohydrolase produced by P. pastoris (pPICBH6) showed maximum activity at pH 4.0 and temperature 50°C and higher specificity in hydrolysis of filter-paper.
文摘This paper presents an application of GRADE Algorithm based approach along with PV analysis to solve multi objective optimization problem of minimizing real power losses, improving the voltage profile and hence enhancing the performance of power system. GRADE Algorithm is a hybrid technique combining genetic and differential evolution algorithms. Control variables considered are Generator bus voltages, MVAR at capacitor banks, transformer tap settings and reactive power generation at generator buses. The optimal values of the control variables are obtained by solving the multi objective optimization problem using GRADE Algorithm programmed using M coding in MATLAB platform. With the optimal setting for the control variables, Newton Raphson based power flow is performed for two test systems, viz, IEEE 30 bus system and IEEE 57 bus system for three loading conditions. Minimization of Real power loss and improvement of voltage profile obtained are compared with the results obtained using firefly and particle swarm optimization (PSO) techniques. Improvement of Loadability margin is established through PV curve plotted using continuation power flow with the real power load at the most affected bus as the bifurcation parameter. The simulated output shows improved results when compared to that of firefly and PSO techniques, in term of convergence time, reduction of real power loss, improvement of voltage profile and enhancement of loadability margin.
基金the National Remote Sensing Center, ISRO-Hyderabad for providing financial supports
文摘The present study revealed proliferation of macro-algae modifying coral reef ecosystems in a different manner due to diseases and sedimentations in the Mandapam group of islands in the Gulf of Mannar. Benthic surveys were conducted with major attack of seven coral reefs diseases with high sedimentation rate, nine species of fleshy macro-algae(Turbinaria ornata, Turbinaria conaides, Caulerpa scalpelliformis, Caulerpa racemosa, Kappaphycus alvarezii, Padina gymnosphora, Sargassum wightii, Ulva reticulata and Calurpa lentillifera) proliferation against major corals life forms(Acropora branching, Acropora digitate, Acropora tabulate, coral massive, coral submassive, coral foliose and coral encrusting). The results confirm that diseased corals most favor to macro-algae growth(15.27%) rather than the sedimentation covered corals(8.24 %). In the degradation of coral life forms, massive corals were more highly damaged(7.05%) than any other forms. Within a short period of time(May to September), coral coverage shrank to 17.4% from 21.9%, macro-algae increased 23.51% and the average sedimentation rate attained 77.52 mg cm^(-2) d^(-1) with persisting coral reef diseases of 17.59%. The Pearson correlation showed that the coral cover decreased with increasing macro-algae growth, which was statistically significant(r =-0.774, n = 100, P < 0.0005). The proliferation of the various macro-algae C. scalpellifrmis, T. ornata, C. racemosa, T. conaides, U. reticulata, S. wightii, K. alvarezii, P. gymnosphora and C. lentillifera increased with percentages of 6.0, 5.8, 5.7, 4.9, 4.2, 3.7, 2.7 and 1.9, respectively. If this trend continues, the next generation of new recruit corals will undoubtedly lead to a phase shift in Gulf of Mannar corals.
