Virtual materials screening approaches have proliferated in the past decade,driven by rapid advances in first-principles computational techniques,and machine-learning algorithms.By comparison,computationally driven ma...Virtual materials screening approaches have proliferated in the past decade,driven by rapid advances in first-principles computational techniques,and machine-learning algorithms.By comparison,computationally driven materials synthesis screening is still in its infancy,and is mired by the challenges of data sparsity and data scarcity:Synthesis routes exist in a sparse,highdimensional parameter space that is difficult to optimize over directly,and,for some materials of interest,only scarce volumes of literature-reported syntheses are available.In this article,we present a framework for suggesting quantitative synthesis parameters and potential driving factors for synthesis outcomes.We use a variational autoencoder to compress sparse synthesis representations into a lower dimensional space,which is found to improve the performance of machine-learning tasks.To realize this screening framework even in cases where there are few literature data,we devise a novel data augmentation methodology that incorporates literature synthesis data from related materials systems.We apply this variational autoencoder framework to generate potential SrTiO_(3) synthesis parameter sets,propose driving factors for brookite TiO_(2) formation,and identify correlations between alkali-ion intercalation and MnO_(2) polymorph selection.展开更多
The integration of large-scale wind power brings challenges to the operation of integrated energy systems(IES).In this paper,a day-ahead scheduling model for IES with wind power and multi-type energy storage is propos...The integration of large-scale wind power brings challenges to the operation of integrated energy systems(IES).In this paper,a day-ahead scheduling model for IES with wind power and multi-type energy storage is proposed in a scenario-based stochastic programming framework.The structure of the IES consists of electricity,natural gas,and heating networks which are all included in the model.Operational constraints for IES incorporating multi-type energy storage devices are also considered.The constraints of the electricity network,natural gas network and heating network are formulated,and non-linear constraints are linearized.The calculation method for the correlation of wind speed between wind farms based on historical data is proposed.Uncertainties of correlated wind power were represented by creating multiple representative scenarios with different probabilities,and this was done using the Latin hyper-cube sampling(LHS)method.The stochastic scheduling model is formulated as a mixed integer linear programming(MILP)problem with the objective function of minimizing the total expected operation cost.Numerical results on a modified PJM 5-bus electricity system with a seven-node natural gas system and a six-node heating system validate the proposed model.The results demonstrate that multi-type energy storage devices can help reduce wind power curtailments and improve the operational flexibility of IES.展开更多
The ability to intelligently utilize resources to meet the need of growing diversity in services and user behavior marks the future of wireless communication systems. Intelligent wireless communications aims at enabli...The ability to intelligently utilize resources to meet the need of growing diversity in services and user behavior marks the future of wireless communication systems. Intelligent wireless communications aims at enabling the system to perceive and assess the available resources, to autonomously learn to adapt to the perceived wireless environment, and to reconfigure its operating mode to maximize the utility of the available resources. The perception capability and reconfigurability are the essential features of cognitive radio while modern machine learning techniques project great potential in system adaptation. In this paper, we discuss the development of the cognitive radio technology and machine learning techniques and emphasize their roles in improving spectrum and energy utility of wireless communication systems. We describe the state-of-the-art of relevant techniques, covering spectrum sensing and access approaches and powerful machine learning algorithms that enable spectrum and energy-efficient communications in dynamic wireless environments. We also present practical applications of these techniques and identify further research challenges in cognitive radio and machine learning as applied to the existing and future wireless communication systems.展开更多
Research on chip-scale atomic clocks （CSACs） based on coherent population trapping （CPT） is reviewed. The back- ground and the inspiration for the research are described, including the important schemes proposed t...Research on chip-scale atomic clocks （CSACs） based on coherent population trapping （CPT） is reviewed. The back- ground and the inspiration for the research are described, including the important schemes proposed to improve the CPT signal quality, the selection of atoms and buffer gases, and the development of micro-cell fabrication. With regard to the re- liability, stability, and service life of the CSACs, the research regarding the sensitivity of the CPT resonance to temperature and laser power changes is also reviewed, as well as the CPT resonance＇s collision and light of frequency shifts. The first generation CSACs have already been developed but its characters are still far from our expectations. Our conclusion is that miniaturization and power reduction are the most important aspects calling for further research.展开更多
以搜索引擎链接提取模块所要求的容错性、正确性、全面性、高效性和可扩展性为目标,提出了一种新的链接提取模型的设计思路。该模型将链接提取过程划分为信息提取、信息加工、信息分析和信息储存。信息的获取是通过HTM L(hypertex t m a...以搜索引擎链接提取模块所要求的容错性、正确性、全面性、高效性和可扩展性为目标,提出了一种新的链接提取模型的设计思路。该模型将链接提取过程划分为信息提取、信息加工、信息分析和信息储存。信息的获取是通过HTM L(hypertex t m arkup language)文法分析方法从文档中得到初始统一资源地址(un iform resourceiden tifier,UR I)数据;信息加工阶段通过运用UR I解析算法对初始数据进行精练;然后在信息分析过程中进一步加以筛选和过滤;最后将结果存储在一个灵活的数据结构中。通过对比测试证实这种新的链接提取模式比传统方法在各项指标上均具有明显优势。展开更多
We propose and fabricate a vertically integrated thermo-optic waveguide switch. It controls the optical path between two vertically stacked waveguides using the thermo-optic effect of optical polymer. The measured cro...We propose and fabricate a vertically integrated thermo-optic waveguide switch. It controls the optical path between two vertically stacked waveguides using the thermo-optic effect of optical polymer. The measured crosstalk is less than -10 dB.展开更多
The COVID-19 outbreak has already become a global pandemic and containing this rapid worldwide transmission is of great challenge.The impacts of temperature and humidity on the COVID-19 transmission rate are still und...The COVID-19 outbreak has already become a global pandemic and containing this rapid worldwide transmission is of great challenge.The impacts of temperature and humidity on the COVID-19 transmission rate are still under discussion.Here,we elucidated these relationships by utilizing two unique scenarios,repeated measurement and natural experiment,using the COVID-19 cases reported from January 23–February 21,2020,in China.The modeling results revealed that higher temperature was most strongly associated with decreased COVID-19 transmission at a lag time of 8 days.Relative humidity(RH)appeared to have only a slight effect.These findings were verified by assessing SARSCoV-2 infectivity under the relevant conditions of temperature(4C–37C)and RH(>40%).We concluded that temperature increase made an important,but not determined,contribution to restrain the COVID19 outbreak in China.It suggests that the emphasis of other effective controlling polices should be strictly implemented to restrain COVID19 transmission in cold seasons.展开更多
A simple fabrication method of self-aligned ridge waveguides with dielectric side buffers is demonstrated on +Z-cut LiNbO3. The ridge waveguide is fabricated by a combination of the annealed proton exchange process an...A simple fabrication method of self-aligned ridge waveguides with dielectric side buffers is demonstrated on +Z-cut LiNbO3. The ridge waveguide is fabricated by a combination of the annealed proton exchange process and the proton-exchanged wet etching technique.展开更多
We compared efficiencies of different PMD compensation feedback methods against transmission signal bandwidth, including NRZ, RZ, CRZ format under various duty cycles. We found that the critical factor determining the...We compared efficiencies of different PMD compensation feedback methods against transmission signal bandwidth, including NRZ, RZ, CRZ format under various duty cycles. We found that the critical factor determining the efficiency of PMD compensation is not the modulation format, but the spectral bandwidth of the transmission signal.展开更多
We propose a simple algorithm for the precise engineering of multi-channel gain profile of Raman amplifier. By employing a linear approximation in the pump interaction calculation, together with a semi-empirical pump ...We propose a simple algorithm for the precise engineering of multi-channel gain profile of Raman amplifier. By employing a linear approximation in the pump interaction calculation, together with a semi-empirical pump power correction using the simplistic output signal spectrum measurement, excellent gain engineering capability has been demonstrated for various target gain profiles, within +/- 0.4dB of error.展开更多
A model of subthreshold characteristics for both undoped and doped double-gate （DG） MOSFETs has been proposed. The models were developed based on solution of 2-D Poisson＇s equation using variable separa- tion techn...A model of subthreshold characteristics for both undoped and doped double-gate （DG） MOSFETs has been proposed. The models were developed based on solution of 2-D Poisson＇s equation using variable separa- tion technique. Without any fitting parameters, our proposed models can exactly reflect the degraded subthreshold characteristics due to nanoscale channel length. Also, design parameters such as body thickness, gate oxide thick- ness and body doping concentrations can be directly reflected from our models. The models have been verified by comparing with device simulations＇ results and found very good agreement.展开更多
We demonstrate a S/S+ band tunable thulium doped fiber laser (TTDFL) anchored on 50GHz ITU-T Grid. Over 57nm of tuning range (1454.9 ~ 1512.0 nm) covering most of the Thulium bandwidth and more than 8dBm output power ...We demonstrate a S/S+ band tunable thulium doped fiber laser (TTDFL) anchored on 50GHz ITU-T Grid. Over 57nm of tuning range (1454.9 ~ 1512.0 nm) covering most of the Thulium bandwidth and more than 8dBm output power has been obtained with the pigtailed solid etalon filter and dual wavelength (1.5μm and 1.4μm) pumping.展开更多
In this paper,a recurrent neural network(RNN)is used to estimate uncertainties and implement feedback control for nonlinear dynamic systems.The neural network approximates the uncertainties related to unmodeled dynami...In this paper,a recurrent neural network(RNN)is used to estimate uncertainties and implement feedback control for nonlinear dynamic systems.The neural network approximates the uncertainties related to unmodeled dynamics,parametric variations,and external disturbances.The RNN has a single hidden layer and uses the tracking error and the output as feedback to estimate the disturbance.The RNN weights are online adapted,and the adaptation laws are developed from the stability analysis of the controlled system with the RNN estimation.The used activation function,at the hidden layer,has an expression that simplifies the adaptation laws from the stability analysis.It is found that the adaptive RNN enhances the tracking performance of the feedback controller at the transient and steady state responses.The proposed RNN based feedback control is applied to a DC–DC converter for current regulation.Simulation and experimental results are provided to show its effectiveness.Compared to the feedforward neural network and the conventional feedback control,the RNN based feedback control provides good tracking performance.展开更多
We have studied the optical and magnetic properties of ytterbium implanted GaN epilayer grown on (0001) sapphire by metalorganic chemical vapor by deposition (MOCVD). Samples were implanted at room temperature with Yb...We have studied the optical and magnetic properties of ytterbium implanted GaN epilayer grown on (0001) sapphire by metalorganic chemical vapor by deposition (MOCVD). Samples were implanted at room temperature with Yb ions at dose 4 1015 cm-2 and energy of 150 keV. The implanted samples were annealed at 1000 C in N2 at atmospheric pressure to recover implantation damages. The photoluminescence (PL), PL excitation (PLE), and PL kinetics have been studied with continuous and pulse photo-excitations in 360-1100 nm spectral range at different temperatures. The characteristic Yb3+ ion emission spectra were observed in the spectral range between 970-1050 nm. Theoretical fittings of the experimental PL temperature and PL kinetics data suggest that Yb3+ ions are involved in at least two major luminescence centers. The PLE spectra indicate that excitation of the Yb3+ ion occurs via electron-hole pair generation and complex processes. Magnetization versus magnetic field curves shows an enhancement of magnetic order for Yb-implanted samples in 5 K to 300 K temperature range. The Yb-implanted GaN sample showing weak ferromagnetic behavior was compared with the ferromagnetic in situ doped GaYbN material.展开更多
Cognitive radio and cooperative communication can greatly improve the spectrum efficiency in wireless communications.We study a cognitive radio network where two secondary source terminals exchange their information w...Cognitive radio and cooperative communication can greatly improve the spectrum efficiency in wireless communications.We study a cognitive radio network where two secondary source terminals exchange their information with the assistance of a relay node under interference power constraints.In order to enhance the transmit rate and maintain fairness between two source terminals,a practical 2-phase analog network coding protocol is adopted and its optimal power allocation algorithm is proposed.Numerical results verify the superiority of the proposed algorithm over the conventional direct transmission protocol and 4-phase amplify-and-forward relay protocol.展开更多
The software engineering field has long focused on creating high-quality software despite limited resources.Detecting defects before the testing stage of software development can enable quality assurance engineers to ...The software engineering field has long focused on creating high-quality software despite limited resources.Detecting defects before the testing stage of software development can enable quality assurance engineers to con-centrate on problematic modules rather than all the modules.This approach can enhance the quality of the final product while lowering development costs.Identifying defective modules early on can allow for early corrections and ensure the timely delivery of a high-quality product that satisfies customers and instills greater confidence in the development team.This process is known as software defect prediction,and it can improve end-product quality while reducing the cost of testing and maintenance.This study proposes a software defect prediction system that utilizes data fusion,feature selection,and ensemble machine learning fusion techniques.A novel filter-based metric selection technique is proposed in the framework to select the optimum features.A three-step nested approach is presented for predicting defective modules to achieve high accuracy.In the first step,three supervised machine learning techniques,including Decision Tree,Support Vector Machines,and Naïve Bayes,are used to detect faulty modules.The second step involves integrating the predictive accuracy of these classification techniques through three ensemble machine-learning methods:Bagging,Voting,and Stacking.Finally,in the third step,a fuzzy logic technique is employed to integrate the predictive accuracy of the ensemble machine learning techniques.The experiments are performed on a fused software defect dataset to ensure that the developed fused ensemble model can perform effectively on diverse datasets.Five NASA datasets are integrated to create the fused dataset:MW1,PC1,PC3,PC4,and CM1.According to the results,the proposed system exhibited superior performance to other advanced techniques for predicting software defects,achieving a remarkable accuracy rate of 92.08%.展开更多
基金funding from the National Science Foundation Award#1534340DMREF that provided support to make this work possible+4 种基金support from the Office of Naval Research(ONR)under Contract No.N00014-16-1-2432the MIT Energy InitiativeNSF CAREER#1553284the Department of Energy’s Basic Energy Science Program through the Materials Project under Grant No.EDCBEEpartially supported by NSERC.
文摘Virtual materials screening approaches have proliferated in the past decade,driven by rapid advances in first-principles computational techniques,and machine-learning algorithms.By comparison,computationally driven materials synthesis screening is still in its infancy,and is mired by the challenges of data sparsity and data scarcity:Synthesis routes exist in a sparse,highdimensional parameter space that is difficult to optimize over directly,and,for some materials of interest,only scarce volumes of literature-reported syntheses are available.In this article,we present a framework for suggesting quantitative synthesis parameters and potential driving factors for synthesis outcomes.We use a variational autoencoder to compress sparse synthesis representations into a lower dimensional space,which is found to improve the performance of machine-learning tasks.To realize this screening framework even in cases where there are few literature data,we devise a novel data augmentation methodology that incorporates literature synthesis data from related materials systems.We apply this variational autoencoder framework to generate potential SrTiO_(3) synthesis parameter sets,propose driving factors for brookite TiO_(2) formation,and identify correlations between alkali-ion intercalation and MnO_(2) polymorph selection.
基金This paper was supported in part by National Natural Science Foundation of China(Grant No.51677022,51607033,and 51607034)National Key Research and Development Program of China(2017YFB0903400)+1 种基金Integrated Energy System Innovation Team of Jilin Province(20180519015JH)and International Clean Energy Talent Programme(iCET)of China Scholarship Council.
文摘The integration of large-scale wind power brings challenges to the operation of integrated energy systems(IES).In this paper,a day-ahead scheduling model for IES with wind power and multi-type energy storage is proposed in a scenario-based stochastic programming framework.The structure of the IES consists of electricity,natural gas,and heating networks which are all included in the model.Operational constraints for IES incorporating multi-type energy storage devices are also considered.The constraints of the electricity network,natural gas network and heating network are formulated,and non-linear constraints are linearized.The calculation method for the correlation of wind speed between wind farms based on historical data is proposed.Uncertainties of correlated wind power were represented by creating multiple representative scenarios with different probabilities,and this was done using the Latin hyper-cube sampling(LHS)method.The stochastic scheduling model is formulated as a mixed integer linear programming(MILP)problem with the objective function of minimizing the total expected operation cost.Numerical results on a modified PJM 5-bus electricity system with a seven-node natural gas system and a six-node heating system validate the proposed model.The results demonstrate that multi-type energy storage devices can help reduce wind power curtailments and improve the operational flexibility of IES.
基金support from the National Science Foundation under Grants 1443894,1560437,and 1731017Louisiana Board of Regents under Grant LEQSF(2017-20)-RD-A-29a research gift from Intel Corporation
文摘The ability to intelligently utilize resources to meet the need of growing diversity in services and user behavior marks the future of wireless communication systems. Intelligent wireless communications aims at enabling the system to perceive and assess the available resources, to autonomously learn to adapt to the perceived wireless environment, and to reconfigure its operating mode to maximize the utility of the available resources. The perception capability and reconfigurability are the essential features of cognitive radio while modern machine learning techniques project great potential in system adaptation. In this paper, we discuss the development of the cognitive radio technology and machine learning techniques and emphasize their roles in improving spectrum and energy utility of wireless communication systems. We describe the state-of-the-art of relevant techniques, covering spectrum sensing and access approaches and powerful machine learning algorithms that enable spectrum and energy-efficient communications in dynamic wireless environments. We also present practical applications of these techniques and identify further research challenges in cognitive radio and machine learning as applied to the existing and future wireless communication systems.
基金Project support by the National Natural Science Foundation of China(Grant No.11074012)
文摘Research on chip-scale atomic clocks （CSACs） based on coherent population trapping （CPT） is reviewed. The back- ground and the inspiration for the research are described, including the important schemes proposed to improve the CPT signal quality, the selection of atoms and buffer gases, and the development of micro-cell fabrication. With regard to the re- liability, stability, and service life of the CSACs, the research regarding the sensitivity of the CPT resonance to temperature and laser power changes is also reviewed, as well as the CPT resonance＇s collision and light of frequency shifts. The first generation CSACs have already been developed but its characters are still far from our expectations. Our conclusion is that miniaturization and power reduction are the most important aspects calling for further research.
文摘We propose and fabricate a vertically integrated thermo-optic waveguide switch. It controls the optical path between two vertically stacked waveguides using the thermo-optic effect of optical polymer. The measured crosstalk is less than -10 dB.
基金We would like to express our gratitude for discussions with the researchers from the environmental exposure and human health working group of the China Cohort Consortium(http://chinacohort.bjmu.edu.cn/),as well as special thanks to Dr.Ping Zhong and Dr.Wentao Wang for their instructive guidance.This work was supported by the National Key Research and Development Program,P.R.China(Grant No.2020YFC0846300 and 2020YFC0846200)the National Natural Science Foundation of China(Grant No.41771527,41922057).
文摘The COVID-19 outbreak has already become a global pandemic and containing this rapid worldwide transmission is of great challenge.The impacts of temperature and humidity on the COVID-19 transmission rate are still under discussion.Here,we elucidated these relationships by utilizing two unique scenarios,repeated measurement and natural experiment,using the COVID-19 cases reported from January 23–February 21,2020,in China.The modeling results revealed that higher temperature was most strongly associated with decreased COVID-19 transmission at a lag time of 8 days.Relative humidity(RH)appeared to have only a slight effect.These findings were verified by assessing SARSCoV-2 infectivity under the relevant conditions of temperature(4C–37C)and RH(>40%).We concluded that temperature increase made an important,but not determined,contribution to restrain the COVID19 outbreak in China.It suggests that the emphasis of other effective controlling polices should be strictly implemented to restrain COVID19 transmission in cold seasons.
文摘A simple fabrication method of self-aligned ridge waveguides with dielectric side buffers is demonstrated on +Z-cut LiNbO3. The ridge waveguide is fabricated by a combination of the annealed proton exchange process and the proton-exchanged wet etching technique.
文摘We compared efficiencies of different PMD compensation feedback methods against transmission signal bandwidth, including NRZ, RZ, CRZ format under various duty cycles. We found that the critical factor determining the efficiency of PMD compensation is not the modulation format, but the spectral bandwidth of the transmission signal.
文摘We propose a simple algorithm for the precise engineering of multi-channel gain profile of Raman amplifier. By employing a linear approximation in the pump interaction calculation, together with a semi-empirical pump power correction using the simplistic output signal spectrum measurement, excellent gain engineering capability has been demonstrated for various target gain profiles, within +/- 0.4dB of error.
基金Project supported by the Fund of Liaoning Province Education Department(No.L2012028)
文摘A model of subthreshold characteristics for both undoped and doped double-gate （DG） MOSFETs has been proposed. The models were developed based on solution of 2-D Poisson＇s equation using variable separa- tion technique. Without any fitting parameters, our proposed models can exactly reflect the degraded subthreshold characteristics due to nanoscale channel length. Also, design parameters such as body thickness, gate oxide thick- ness and body doping concentrations can be directly reflected from our models. The models have been verified by comparing with device simulations＇ results and found very good agreement.
文摘We demonstrate a S/S+ band tunable thulium doped fiber laser (TTDFL) anchored on 50GHz ITU-T Grid. Over 57nm of tuning range (1454.9 ~ 1512.0 nm) covering most of the Thulium bandwidth and more than 8dBm output power has been obtained with the pigtailed solid etalon filter and dual wavelength (1.5μm and 1.4μm) pumping.
基金supported in part by Khalifa University of Science and Technology (KUST),United Arab Emirates under Award CIRA-2020-013.
文摘In this paper,a recurrent neural network(RNN)is used to estimate uncertainties and implement feedback control for nonlinear dynamic systems.The neural network approximates the uncertainties related to unmodeled dynamics,parametric variations,and external disturbances.The RNN has a single hidden layer and uses the tracking error and the output as feedback to estimate the disturbance.The RNN weights are online adapted,and the adaptation laws are developed from the stability analysis of the controlled system with the RNN estimation.The used activation function,at the hidden layer,has an expression that simplifies the adaptation laws from the stability analysis.It is found that the adaptive RNN enhances the tracking performance of the feedback controller at the transient and steady state responses.The proposed RNN based feedback control is applied to a DC–DC converter for current regulation.Simulation and experimental results are provided to show its effectiveness.Compared to the feedforward neural network and the conventional feedback control,the RNN based feedback control provides good tracking performance.
基金Project supported by the 1804 Fund grant of Ohio University and the US Department of Energy (DE-AC02-05CH11231)
文摘We have studied the optical and magnetic properties of ytterbium implanted GaN epilayer grown on (0001) sapphire by metalorganic chemical vapor by deposition (MOCVD). Samples were implanted at room temperature with Yb ions at dose 4 1015 cm-2 and energy of 150 keV. The implanted samples were annealed at 1000 C in N2 at atmospheric pressure to recover implantation damages. The photoluminescence (PL), PL excitation (PLE), and PL kinetics have been studied with continuous and pulse photo-excitations in 360-1100 nm spectral range at different temperatures. The characteristic Yb3+ ion emission spectra were observed in the spectral range between 970-1050 nm. Theoretical fittings of the experimental PL temperature and PL kinetics data suggest that Yb3+ ions are involved in at least two major luminescence centers. The PLE spectra indicate that excitation of the Yb3+ ion occurs via electron-hole pair generation and complex processes. Magnetization versus magnetic field curves shows an enhancement of magnetic order for Yb-implanted samples in 5 K to 300 K temperature range. The Yb-implanted GaN sample showing weak ferromagnetic behavior was compared with the ferromagnetic in situ doped GaYbN material.
基金Acknowledgements The work was supported by National Natural Science Foundation of China （Grant No.60972008）. The corresponding author is Jiang Wei.
文摘Cognitive radio and cooperative communication can greatly improve the spectrum efficiency in wireless communications.We study a cognitive radio network where two secondary source terminals exchange their information with the assistance of a relay node under interference power constraints.In order to enhance the transmit rate and maintain fairness between two source terminals,a practical 2-phase analog network coding protocol is adopted and its optimal power allocation algorithm is proposed.Numerical results verify the superiority of the proposed algorithm over the conventional direct transmission protocol and 4-phase amplify-and-forward relay protocol.
基金supported by the Center for Cyber-Physical Systems,Khalifa University,under Grant 8474000137-RC1-C2PS-T5.
文摘The software engineering field has long focused on creating high-quality software despite limited resources.Detecting defects before the testing stage of software development can enable quality assurance engineers to con-centrate on problematic modules rather than all the modules.This approach can enhance the quality of the final product while lowering development costs.Identifying defective modules early on can allow for early corrections and ensure the timely delivery of a high-quality product that satisfies customers and instills greater confidence in the development team.This process is known as software defect prediction,and it can improve end-product quality while reducing the cost of testing and maintenance.This study proposes a software defect prediction system that utilizes data fusion,feature selection,and ensemble machine learning fusion techniques.A novel filter-based metric selection technique is proposed in the framework to select the optimum features.A three-step nested approach is presented for predicting defective modules to achieve high accuracy.In the first step,three supervised machine learning techniques,including Decision Tree,Support Vector Machines,and Naïve Bayes,are used to detect faulty modules.The second step involves integrating the predictive accuracy of these classification techniques through three ensemble machine-learning methods:Bagging,Voting,and Stacking.Finally,in the third step,a fuzzy logic technique is employed to integrate the predictive accuracy of the ensemble machine learning techniques.The experiments are performed on a fused software defect dataset to ensure that the developed fused ensemble model can perform effectively on diverse datasets.Five NASA datasets are integrated to create the fused dataset:MW1,PC1,PC3,PC4,and CM1.According to the results,the proposed system exhibited superior performance to other advanced techniques for predicting software defects,achieving a remarkable accuracy rate of 92.08%.
