The broadband, narrow width, rectangular dielectric resonator antenna(RDRA) of aluminum nitride(εr=8.6) was designed and the effect of inclusion of air gap at the bottom of the dielectric resonator antenna(DRA),above...The broadband, narrow width, rectangular dielectric resonator antenna(RDRA) of aluminum nitride(εr=8.6) was designed and the effect of inclusion of air gap at the bottom of the dielectric resonator antenna(DRA),above the ground plane, was investigated. Gain around 7 dBi was obtained for DRA with air gap(DRAAG) over a broad bandwidth in upper X, Ku, and K bands. Further enhancement in gain could be obtained by placing a metal wall parallel to the length of DRA. However, due to the presence of metal wall, bandwidth was reduced. These structures with the metal wall are capable of operating over a wide band extending from Ku band to lower K band with the gain of around 10 dBi. CST Microwave Studio Software was used to simulate all these structures.Performance parameters of DRA with air gap were compared with several broadband DRA structures reported in recent literature. The proposed DRAAG with the metal wall in this paper is capable of operating over a wide bandwidth along with a significant gain.展开更多
Heterojunction Bipolar Transistors with SiGe base and Si emitter and collector have increasingly become important in high speed applications in electronics due to better performance of these devices with a modest incr...Heterojunction Bipolar Transistors with SiGe base and Si emitter and collector have increasingly become important in high speed applications in electronics due to better performance of these devices with a modest increase in complexity of fabrication process. Speed of these devices is mainly determined by transit time of minority carriers across the device. Base transit time is the most important component of the total transit time. An analytical model is developed here to predict the variation of base transit time with Ge content, base doping concentration, temperature, and other device parameters. Studies have been made for both uniform and exponential doping distributions with different Ge profiles in the base region. Band gap narrowing effect due to high doping concentration is also taken into account in the model.展开更多
In this paper, an extensive numerical study on pressure characteristics in the configuration of sudden expansion with central restriction and suction has been carried out. During study, Reynolds numbers (Re) are consi...In this paper, an extensive numerical study on pressure characteristics in the configuration of sudden expansion with central restriction and suction has been carried out. During study, Reynolds numbers (Re) are considered from 50 to 200, suction (S) from 2% to 10% of inlet mass flow, percentage of central restriction (CR) from 0% to 40% and aspect ratio (AR) from 2 to 6. The effects of each variable on average static pressure distribution and average stagnation pressure distribution have been studied in detail. The results have been compared with the configuration of plain sudden expansion, and sudden expansion with central restriction only. From the study, it is noted that maximum magnitude of average static pressure rise from throat increases with the increase in percentage of suction, flow Reynolds number and percentage of central restriction. This magnitude is higher at lower aspect ratio. Also, it is observed that maximum magnitude of average static pressure rise from throat is always more in case of suction configuration compared to the case of configuration of without suction. Average stagnation pressure drop at any section increases with the increase in percentage of suction and percentage of central restriction, but it decreases with the increase in Reynolds number. It is noted that higher pressure drop at any section occurs at higher aspect ratio. This pressure drop at a section is more in case of suction configuration compared to the case of without suction.展开更多
Partitional clustering techniques such as K-Means(KM),Fuzzy C-Means(FCM),and Rough K-Means(RKM)are very simple and effective techniques for image segmentation.But,because their initial cluster centers are randomly det...Partitional clustering techniques such as K-Means(KM),Fuzzy C-Means(FCM),and Rough K-Means(RKM)are very simple and effective techniques for image segmentation.But,because their initial cluster centers are randomly determined,it is often seen that certain clusters converge to local optima.In addition to that,pathology image segmentation is also problematic due to uneven lighting,stain,and camera settings during the microscopic image capturing process.Therefore,this study proposes an Improved Slime Mould Algorithm(ISMA)based on opposition based learning and differential evolution’s mutation strategy to perform illumination-free White Blood Cell(WBC)segmentation.The ISMA helps to overcome the local optima trapping problem of the partitional clustering techniques to some extent.This paper also performs a depth analysis by considering only color components of many well-known color spaces for clustering to find the effect of illumination over color pathology image clustering.Numerical and visual results encourage the utilization of illumination-free or color component-based clustering approaches for image segmentation.ISMA-KM and“ab”color channels of CIELab color space provide best results with above-99%accuracy for only nucleus segmentation.Whereas,for entire WBC segmentation,ISMA-KM and the“CbCr”color component of YCbCr color space provide the best results with an accuracy of above 99%.Furthermore,ISMA-KM and ISMA-RKM have the lowest and highest execution times,respectively.On the other hand,ISMA provides competitive outcomes over CEC2019 benchmark test functions compared to recent well-established and efficient Nature-Inspired Optimization Algorithms(NIOAs).展开更多
As fossil fuel stocks are being depleted,alternative sources of energy must be explored.Consequently,traditional thermal power plants must coexist with renewable resources,such as wind,solar,and hydro units,and all-da...As fossil fuel stocks are being depleted,alternative sources of energy must be explored.Consequently,traditional thermal power plants must coexist with renewable resources,such as wind,solar,and hydro units,and all-day planning and operation techniques are necessary to safeguard nature while meeting the current demand.The fundamental components of contemporary power systems are the simultaneous decrease in generation costs and increase in the available transfer capacity(ATC)of current systems.Thermal units are linked to sources of renewable energy such as hydro,wind,and solar power,and are set up to run for 24 h.By contrast,new research reports that various chaotic maps are merged with various existing optimization methodologies to obtain better results than those without the inclusion of chaos.Chaos seems to increase the performance and convergence properties of existing optimization approaches.In this study,selfish animal tendencies,mathematically represented as selfish herd optimizers,were hybridized with chaotic phenomena and used to improve ATC and/or reduce generation costs,creating a multi-objective optimization problem.To evaluate the performance of the proposed hybridized optimization technique,an optimal power flow-based ATC was enforced under various hydro-thermal-solar-wind conditions,that is,the renewable energy source-thermal scheduling concept,on IEEE 9-bus,IEEE 39-bus,and Indian Northern Region Power Grid 246-bus test systems.The findings show that the proposed technique outperforms existing well-established optimization strategies.展开更多
An analytical model is used to predict the effects of surface recombination current on the gain and transit time of GalnP/GaAs heterojunction bipolar transistors（HBTs）.The present analysis shows that consideration o...An analytical model is used to predict the effects of surface recombination current on the gain and transit time of GalnP/GaAs heterojunction bipolar transistors（HBTs）.The present analysis shows that consideration of the recombination current gives current gain values that are comparable to those of the experimental results.The dependence of current gain on temperature,base doping and emitter area are also analyzed,and the variation in collector current with emitter-base voltage,temperature and doping is considered.展开更多
Monitoring biosignals is crucial for intelligent health applications.Internet of Health Things(IoHT)provides a new path for monitoring the biosignals.Environment adaptive data dissemination is the primary requirement ...Monitoring biosignals is crucial for intelligent health applications.Internet of Health Things(IoHT)provides a new path for monitoring the biosignals.Environment adaptive data dissemination is the primary requirement for the deployment of time and space-efficient monitoring systems.Existing dew-based systems lack an opportunistic architecture of data-synchronization with the cloud.This paper proposes a model that makes efficient use of IoT and cloud-dew architecture for a sustainable health monitoring system.Wireless sensor nodes are used to monitor the biosignals dynamically.All accrued data is temporarily stored in the dew layer.It is synchronized with the cloud at a subsequent phase to achieve seamless accessibility and optimal scalability of the data.Data synchronization plays an essential role in the cloud dew framework.We have used the Gini index and Shannon entropy to ensure intelligent data synchronization with the cloud.Sometimes sensors produce erroneous data,which poses a significant threat to the sustainable health monitoring system.Fuzzy normal distribution with a triangular membership function has been used to clean up the data and filter out the outliers.Further,we compared the proposed MedGini model with the existing models and analyzed the system performance.MedGini is found to outperform others concerning cost and power consumption.展开更多
Dormant Cardiovascular diseases(CVDs)are found to take a death toll of 17.9 million every year worldwide.We propose an application that reads the heart beat using pulse sensor.The system accumulates and analyzes data ...Dormant Cardiovascular diseases(CVDs)are found to take a death toll of 17.9 million every year worldwide.We propose an application that reads the heart beat using pulse sensor.The system accumulates and analyzes data using Arduino based analyzer.The analyzer reads the pattern of heart-beat using fuzzy-normal distribution to find out whether the data belong to a normal heart or a damaged heart.The analyzer can efficiently indicate the occurrence of Bradicardia or atrial fibrillation or no disease.We have proposed an app‘StepSuggest’that can suggest the user about the number of steps he/she should walk during workout.展开更多
文摘The broadband, narrow width, rectangular dielectric resonator antenna(RDRA) of aluminum nitride(εr=8.6) was designed and the effect of inclusion of air gap at the bottom of the dielectric resonator antenna(DRA),above the ground plane, was investigated. Gain around 7 dBi was obtained for DRA with air gap(DRAAG) over a broad bandwidth in upper X, Ku, and K bands. Further enhancement in gain could be obtained by placing a metal wall parallel to the length of DRA. However, due to the presence of metal wall, bandwidth was reduced. These structures with the metal wall are capable of operating over a wide band extending from Ku band to lower K band with the gain of around 10 dBi. CST Microwave Studio Software was used to simulate all these structures.Performance parameters of DRA with air gap were compared with several broadband DRA structures reported in recent literature. The proposed DRAAG with the metal wall in this paper is capable of operating over a wide bandwidth along with a significant gain.
文摘Heterojunction Bipolar Transistors with SiGe base and Si emitter and collector have increasingly become important in high speed applications in electronics due to better performance of these devices with a modest increase in complexity of fabrication process. Speed of these devices is mainly determined by transit time of minority carriers across the device. Base transit time is the most important component of the total transit time. An analytical model is developed here to predict the variation of base transit time with Ge content, base doping concentration, temperature, and other device parameters. Studies have been made for both uniform and exponential doping distributions with different Ge profiles in the base region. Band gap narrowing effect due to high doping concentration is also taken into account in the model.
文摘In this paper, an extensive numerical study on pressure characteristics in the configuration of sudden expansion with central restriction and suction has been carried out. During study, Reynolds numbers (Re) are considered from 50 to 200, suction (S) from 2% to 10% of inlet mass flow, percentage of central restriction (CR) from 0% to 40% and aspect ratio (AR) from 2 to 6. The effects of each variable on average static pressure distribution and average stagnation pressure distribution have been studied in detail. The results have been compared with the configuration of plain sudden expansion, and sudden expansion with central restriction only. From the study, it is noted that maximum magnitude of average static pressure rise from throat increases with the increase in percentage of suction, flow Reynolds number and percentage of central restriction. This magnitude is higher at lower aspect ratio. Also, it is observed that maximum magnitude of average static pressure rise from throat is always more in case of suction configuration compared to the case of configuration of without suction. Average stagnation pressure drop at any section increases with the increase in percentage of suction and percentage of central restriction, but it decreases with the increase in Reynolds number. It is noted that higher pressure drop at any section occurs at higher aspect ratio. This pressure drop at a section is more in case of suction configuration compared to the case of without suction.
基金This work has been partially supported with the grant received in research project under RUSA 2.0 component 8,Govt.of India,New Delhi.
文摘Partitional clustering techniques such as K-Means(KM),Fuzzy C-Means(FCM),and Rough K-Means(RKM)are very simple and effective techniques for image segmentation.But,because their initial cluster centers are randomly determined,it is often seen that certain clusters converge to local optima.In addition to that,pathology image segmentation is also problematic due to uneven lighting,stain,and camera settings during the microscopic image capturing process.Therefore,this study proposes an Improved Slime Mould Algorithm(ISMA)based on opposition based learning and differential evolution’s mutation strategy to perform illumination-free White Blood Cell(WBC)segmentation.The ISMA helps to overcome the local optima trapping problem of the partitional clustering techniques to some extent.This paper also performs a depth analysis by considering only color components of many well-known color spaces for clustering to find the effect of illumination over color pathology image clustering.Numerical and visual results encourage the utilization of illumination-free or color component-based clustering approaches for image segmentation.ISMA-KM and“ab”color channels of CIELab color space provide best results with above-99%accuracy for only nucleus segmentation.Whereas,for entire WBC segmentation,ISMA-KM and the“CbCr”color component of YCbCr color space provide the best results with an accuracy of above 99%.Furthermore,ISMA-KM and ISMA-RKM have the lowest and highest execution times,respectively.On the other hand,ISMA provides competitive outcomes over CEC2019 benchmark test functions compared to recent well-established and efficient Nature-Inspired Optimization Algorithms(NIOAs).
文摘As fossil fuel stocks are being depleted,alternative sources of energy must be explored.Consequently,traditional thermal power plants must coexist with renewable resources,such as wind,solar,and hydro units,and all-day planning and operation techniques are necessary to safeguard nature while meeting the current demand.The fundamental components of contemporary power systems are the simultaneous decrease in generation costs and increase in the available transfer capacity(ATC)of current systems.Thermal units are linked to sources of renewable energy such as hydro,wind,and solar power,and are set up to run for 24 h.By contrast,new research reports that various chaotic maps are merged with various existing optimization methodologies to obtain better results than those without the inclusion of chaos.Chaos seems to increase the performance and convergence properties of existing optimization approaches.In this study,selfish animal tendencies,mathematically represented as selfish herd optimizers,were hybridized with chaotic phenomena and used to improve ATC and/or reduce generation costs,creating a multi-objective optimization problem.To evaluate the performance of the proposed hybridized optimization technique,an optimal power flow-based ATC was enforced under various hydro-thermal-solar-wind conditions,that is,the renewable energy source-thermal scheduling concept,on IEEE 9-bus,IEEE 39-bus,and Indian Northern Region Power Grid 246-bus test systems.The findings show that the proposed technique outperforms existing well-established optimization strategies.
文摘An analytical model is used to predict the effects of surface recombination current on the gain and transit time of GalnP/GaAs heterojunction bipolar transistors（HBTs）.The present analysis shows that consideration of the recombination current gives current gain values that are comparable to those of the experimental results.The dependence of current gain on temperature,base doping and emitter area are also analyzed,and the variation in collector current with emitter-base voltage,temperature and doping is considered.
文摘Monitoring biosignals is crucial for intelligent health applications.Internet of Health Things(IoHT)provides a new path for monitoring the biosignals.Environment adaptive data dissemination is the primary requirement for the deployment of time and space-efficient monitoring systems.Existing dew-based systems lack an opportunistic architecture of data-synchronization with the cloud.This paper proposes a model that makes efficient use of IoT and cloud-dew architecture for a sustainable health monitoring system.Wireless sensor nodes are used to monitor the biosignals dynamically.All accrued data is temporarily stored in the dew layer.It is synchronized with the cloud at a subsequent phase to achieve seamless accessibility and optimal scalability of the data.Data synchronization plays an essential role in the cloud dew framework.We have used the Gini index and Shannon entropy to ensure intelligent data synchronization with the cloud.Sometimes sensors produce erroneous data,which poses a significant threat to the sustainable health monitoring system.Fuzzy normal distribution with a triangular membership function has been used to clean up the data and filter out the outliers.Further,we compared the proposed MedGini model with the existing models and analyzed the system performance.MedGini is found to outperform others concerning cost and power consumption.
文摘Dormant Cardiovascular diseases(CVDs)are found to take a death toll of 17.9 million every year worldwide.We propose an application that reads the heart beat using pulse sensor.The system accumulates and analyzes data using Arduino based analyzer.The analyzer reads the pattern of heart-beat using fuzzy-normal distribution to find out whether the data belong to a normal heart or a damaged heart.The analyzer can efficiently indicate the occurrence of Bradicardia or atrial fibrillation or no disease.We have proposed an app‘StepSuggest’that can suggest the user about the number of steps he/she should walk during workout.
