Triboelectric nanogenerators(TENGs)offer a selfsustaining power solution for marine regions abundant in resources but constrained by energy availability.Since their pioneering use in wave energy harvesting in 2014,nea...Triboelectric nanogenerators(TENGs)offer a selfsustaining power solution for marine regions abundant in resources but constrained by energy availability.Since their pioneering use in wave energy harvesting in 2014,nearly a decade of advancements has yielded nearly thousands of research articles in this domain.Researchers have developed various TENG device structures with diverse functionalities to facilitate their commercial deployment.Nonetheless,there is a gap in comprehensive summaries and performance evaluations of TENG structural designs.This paper delineates six innovative structural designs,focusing on enhancing internal device output and adapting to external environments:high space utilization,hybrid generator,mechanical gain,broadband response,multi-directional operation,and hybrid energy-harvesting systems.We summarize the prevailing trends in device structure design identified by the research community.Furthermore,we conduct a meticulous comparison of the electrical performance of these devices under motorized,simulated wave,and real marine conditions,while also assessing their sustainability in terms of device durability and mechanical robustness.In conclusion,the paper outlines future research avenues and discusses the obstacles encountered in the TENG field.This review aims to offer valuable perspectives for ongoing research and to advance the progress and application of TENG technology.展开更多
This paper studies the sensing base station(SBS)that has great potential to improve the safety of vehicles and pedestrians on roads.SBS can detect the targets on the road with communication signals using the integrate...This paper studies the sensing base station(SBS)that has great potential to improve the safety of vehicles and pedestrians on roads.SBS can detect the targets on the road with communication signals using the integrated sensing and communication(ISAC)technique.Compared with vehicle-mounted radar,SBS has a better sensing field due to its higher deployment position,which can help solve the problem of sensing blind areas.In this paper,key technologies of SBS are studied,including the beamforming algorithm,beam scanning scheme,and interference cancellation algorithm.To transmit and receive ISAC signals simultaneously,a double-coupling antenna array is applied.The free detection beam and directional communication beam are proposed for joint communication and sensing to meet the requirements of beamwidth and pointing directions.The joint timespace-frequency domain division multiple access algorithm is proposed to cancel the interference of SBS,including multiuser interference and duplex interference between sensing and communication.Finally,the sensing and communication performance of SBS under the industrial scientific medical power limitation is analyzed and simulated.Simulation results show that the communication rate of SBS can reach over 100 Mbps and the range of sensing and communication can reach about 500 m.展开更多
This paper presents a novel suspension support tailored for wind tunnel tests of spinning projectiles based on Wire-Driven Parallel Robot(WDPR),uniquely characterized by an SPM(Spinning Projectile Model)-centered mobi...This paper presents a novel suspension support tailored for wind tunnel tests of spinning projectiles based on Wire-Driven Parallel Robot(WDPR),uniquely characterized by an SPM(Spinning Projectile Model)-centered mobile platform.First,an SPM-centered mobile platform,featuring two redundant and another unconstrained Degree of Freedom(DOF),and its suspension support mechanism are designed together,collectively constructing a WDPR endowed with kinematic redundancy.Afterward,the kinematics of the mechanism,boundary equations for the redundant DOFs,and relevant kinematic performance indices are then proposed and formulated.The results from both prototype experiments and numerical assessments are presented.The capability of the support mechanism to replicate the complex coupled motions of the SPM is verified by the experimental results,while the proposed kinematics and boundary equations are also validated.Furthermore,it is revealed by numerical assessments that the redundant DOFs of the mobile platform exert a minimal impact on the kinematic performance of the suspension support.Finally,the optimal global attitude performance is obtained when these DOFs are set to zero if they are restricted to constants.However,local attitude performance can be further improved by the variable values.展开更多
Research of capture mechanisms with strong capture adaptability and stable grasp is important to solve the problem of launch and recovery of torpedo-shaped autonomous underwater vehicles(AUVs).A multi-loop coupling ca...Research of capture mechanisms with strong capture adaptability and stable grasp is important to solve the problem of launch and recovery of torpedo-shaped autonomous underwater vehicles(AUVs).A multi-loop coupling capture mechanism with strong adaptability and high retraction rate has been proposed for the launch and recovery of torpedo-shaped AUVs with different morphological features.Firstly,the principle of capturing motion retraction is described based on the appearance characteristics of torpedo-shaped AUVs,and the configuration synthesis of the capture mechanism is carried out using the method of constrained chain synthesis.Secondly,the screw theory is employed to analyze the degree of freedom(DoF)of the capture mechanism.Then,the 3D model of the capture mechanism is established,and the kinematics and dynamics simulations are carried out.Combined with the capture orientation requirements of the capture mechanism,the statics and vibration characteristics analyses are carried out.Furthermore,considering the capture process and the underwater working environment,the motion characteristics and hydraulics characteristics of the capture mechanism are analyzed.Finally,a principle prototype is developed and the torpedo-shaped AUVs capture experiment is completed.The work provides technical reserves for the research and development of AUV capture special equipment.展开更多
A large language model(LLM)is constructed to address the sophisticated demands of data retrieval and analysis,detailed well profiling,computation of key technical indicators,and the solutions to complex problems in re...A large language model(LLM)is constructed to address the sophisticated demands of data retrieval and analysis,detailed well profiling,computation of key technical indicators,and the solutions to complex problems in reservoir performance analysis(RPA).The LLM is constructed for RPA scenarios with incremental pre-training,fine-tuning,and functional subsystems coupling.Functional subsystem and efficient coupling methods are proposed based on named entity recognition(NER),tool invocation,and Text-to-SQL construction,all aimed at resolving pivotal challenges in developing the specific application of LLMs for RDA.This study conducted a detailed accuracy test on feature extraction models,tool classification models,data retrieval models and analysis recommendation models.The results indicate that these models have demonstrated good performance in various key aspects of reservoir dynamic analysis.The research takes some injection and production well groups in the PK3 Block of the Daqing Oilfield as an example for testing.Testing results show that our model has significant potential and practical value in assisting reservoir engineers with RDA.The research results provide a powerful support to the application of LLM in reservoir performance analysis.展开更多
The importance of cybersecurity in contemporary society cannot be inflated,given the substantial impact of networks on various aspects of daily life.Traditional cybersecurity measures,such as anti-virus software and f...The importance of cybersecurity in contemporary society cannot be inflated,given the substantial impact of networks on various aspects of daily life.Traditional cybersecurity measures,such as anti-virus software and firewalls,safeguard networks against potential threats.In network security,using Intrusion Detection Systems(IDSs)is vital for effectively monitoring the various software and hardware components inside a given network.However,they may encounter difficulties when it comes to detecting solitary attacks.Machine Learning(ML)models are implemented in intrusion detection widely because of the high accuracy.The present work aims to assess the performance of machine learning algorithms in the context of intrusion detection,providing valuable insights into their efficacy and potential for enhancing cybersecurity measures.The main objective is to compare the performance of the well-knownML models using the UNSW-NB15 dataset.The performance of the models is discussed in detail with a comparison using evaluation metrics and computational performance.展开更多
With the increased accessibility of global trade information,transaction fraud has become a major worry in global banking and commerce security.The incidence and magnitude of transaction fraud are increasing daily,res...With the increased accessibility of global trade information,transaction fraud has become a major worry in global banking and commerce security.The incidence and magnitude of transaction fraud are increasing daily,resulting in significant financial losses for both customers and financial professionals.With improvements in data mining and machine learning in computer science,the capacity to detect transaction fraud is becoming increasingly attainable.The primary goal of this research is to undertake a comparative examination of cutting-edge machine-learning algorithms developed to detect credit card fraud.The research looks at the efficacy of these machine learning algorithms using a publicly available dataset of credit card transactions performed by European cardholders in 2023,comprising around 550,000 records.The study uses this dataset to assess the performance of well-established machine learning models,measuring their accuracy,recall,and F1 score.In addition,the study includes a confusion matrix for all models to aid in evaluation and training time duration.Machin learning models,including Logistic regression,random forest,extra trees,and LGBM,achieve high accuracy and precision in the credit card fraud detection dataset,with a reported accuracy,recall,and F1 score of 1.00 for both classes.展开更多
Today, in the field of computer networks, new services have been developed on the Internet or intranets, including the mail server, database management, sounds, videos and the web server itself Apache. The number of s...Today, in the field of computer networks, new services have been developed on the Internet or intranets, including the mail server, database management, sounds, videos and the web server itself Apache. The number of solutions for this server is therefore growing continuously, these services are becoming more and more complex and expensive, without being able to fulfill the needs of the users. The absence of benchmarks for websites with dynamic content is the major obstacle to research in this area. These users place high demands on the speed of access to information on the Internet. This is why the performance of the web server is critically important. Several factors influence performance, such as server execution speed, network saturation on the internet or intranet, increased response time, and throughputs. By measuring these factors, we propose a performance evaluation strategy for servers that allows us to determine the actual performance of different servers in terms of user satisfaction. Furthermore, we identified performance characteristics such as throughput, resource utilization, and response time of a system through measurement and modeling by simulation. Finally, we present a simple queue model of an Apache web server, which reasonably represents the behavior of a saturated web server using the Simulink model in Matlab (Matrix Laboratory) and also incorporates sporadic incoming traffic. We obtain server performance metrics such as average response time and throughput through simulations. Compared to other models, our model is conceptually straightforward. The model has been validated through measurements and simulations during the tests that we conducted.展开更多
The diagnosis and prognosis of cardiovascular diseases are critical medical responsibilities that assist cardiologists in correctly classifying patients and treating them accordingly.The utilization of machine learnin...The diagnosis and prognosis of cardiovascular diseases are critical medical responsibilities that assist cardiologists in correctly classifying patients and treating them accordingly.The utilization of machine learning in the medical domain has witnessed a notable surge due to its ability to discern patterns from vast amounts of data.Machine learning algorithms that can categorize cases of cardiovascular illness may help doctors reduce the number of wrong diagnoses.This research investigates the efficacy of different machine learning algorithms in predicting cardiovascular disease in accordance with risk factors.This study utilizes a variety of machine learning models,including Logistic Regression,Random Forest,Decision Tree,Extra Trees classifier,Support Vector Machine(SVM),XGBoost(XGB),Light Gradient Boosting Machine(LGBM),GaussianNB,and Multilayer Perceptron(MLP).The machine learning models are applied to a concrete dataset acquired from Kaggle.The models underwent training using a dataset that was partitioned into an 80:20 ratio.Machine learning model evaluation involves the utilization of performance measurements such as Accuracy,Precision,Recall,and ROC curves.An exhaustive evaluation is carried out to gauge the efficacy of the models.展开更多
In today’s information age,video data,as an important carrier of information,is growing explosively in terms of production volume.The quick and accurate extraction of useful information from massive video data has be...In today’s information age,video data,as an important carrier of information,is growing explosively in terms of production volume.The quick and accurate extraction of useful information from massive video data has become a focus of research in the field of computer vision.AI dynamic recognition technology has become one of the key technologies to address this issue due to its powerful data processing capabilities and intelligent recognition functions.Based on this,this paper first elaborates on the development of intelligent video AI dynamic recognition technology,then proposes several optimization strategies for intelligent video AI dynamic recognition technology,and finally analyzes the performance of intelligent video AI dynamic recognition technology for reference.展开更多
Microbial fuel cell(MFC)is a kind of promising clean power supply energy equipment,but serious nonlinearities and disturbances exist when the MFC runs,and it is an important topic to guarantee that the output voltage ...Microbial fuel cell(MFC)is a kind of promising clean power supply energy equipment,but serious nonlinearities and disturbances exist when the MFC runs,and it is an important topic to guarantee that the output voltage reaches the setting value quickly and smoothly.Regulating the feeding flow is an effective way to achieve this goal,and especially,the satisfactory results can be achieved by regulating anode feeding flow.In this work,a feedforward fuzzy logic PID algorithm is proposed.The fuzzy logic system is introduced to deal with the non-linear dynamics of MFC,and corresponding PID parameters are calculated according to defuzzification.The magnitude value of the current density is used to simulate the value of the external load.The simulation results indicate that the MFC output voltage can track the setting value quickly and smoothly with the proposed feedforward fuzzy logic PID algorithm.The proposed algorithm is more efficient and robust with respect to anti-disturbance performance and tracking accuracy than other three control methods.展开更多
The network on chip（NoC）is used as a solution for the communication problems in a complex system on chip（SoC）design.To further enhance performances,the NoC architectures,a high level modeling and an evaluation met...The network on chip（NoC）is used as a solution for the communication problems in a complex system on chip（SoC）design.To further enhance performances,the NoC architectures,a high level modeling and an evaluation method based on OPNET are proposed to analyze their performances on different injection rates and traffic patterns.Simulation results for general NoC in terms of the average latency and the throughput are analyzed and used as a guideline to make appropriate choices for a given application.Finally,a MPEG4 decoder is mapped on different NoC architectures.Results prove the effectiveness of the evaluation method.展开更多
This paper presents RTSS simulation software with the capability for graphical model building and animation display. The RTSS simulation software consists of three separated parts: the simulation kernel, the model bui...This paper presents RTSS simulation software with the capability for graphical model building and animation display. The RTSS simulation software consists of three separated parts: the simulation kernel, the model building program and the result post processing program. The RTSS may run in the client/server mode. The main features of the RTSS software are more modular, more flexible and easier to upgrade. RTSS is built on object oriented technology, so it has more flexibility. The RTSS model of a system is an open queueing network. For modeling various data acquisition systems, communication networks and flexible manufacturing systems at different abstraction levels, RTSS has proven to be an extremely useful tool for performance analysis.展开更多
A numerical simulation model of plenoptic sensor aberration wavefront detection is established to simulate and analyze the detection performance of plenoptic sensor aberration wavefront for different turbulence intens...A numerical simulation model of plenoptic sensor aberration wavefront detection is established to simulate and analyze the detection performance of plenoptic sensor aberration wavefront for different turbulence intensities.The results show that the plenoptic sensor can achieve better distortion wavefront detection,and its wavefront detection accuracy improves with turbulence intensity.The unique optical structure design of the plenoptic sensor makes it more suitable for aberration wavefront detection in strong turbulent conditions.The wavefront detection performance of the plenoptic sensor is not only related to its wavefront reconstruction algorithm but also closely related to its structural parameter settings.The influence of structural parameters on the wavefront detection accuracy of plenoptic sensors under different turbulence intensities is simulated and analyzed.The variation law of wavefront detection accuracy and structural parameters under different turbulence intensities is summarized to provide a reference for the structural design and parameter optimization of plenoptic sensors.展开更多
The theoretical positioning accuracy of multilateration(MLAT) with the time difference of arrival(TDOA) algorithm is very high. However, there are some problems in practical applications. Here we analyze the location ...The theoretical positioning accuracy of multilateration(MLAT) with the time difference of arrival(TDOA) algorithm is very high. However, there are some problems in practical applications. Here we analyze the location performance of the time sum of arrival(TSOA) algorithm from the root mean square error(RMSE) and geometric dilution of precision(GDOP) in additive white Gaussian noise(AWGN) environment. The TSOA localization model is constructed. Using it, the distribution of location ambiguity region is presented with 4-base stations. And then, the location performance analysis is started from the 4-base stations with calculating the RMSE and GDOP variation. Subsequently, when the location parameters are changed in number of base stations, base station layout and so on, the performance changing patterns of the TSOA location algorithm are shown. So, the TSOA location characteristics and performance are revealed. From the RMSE and GDOP state changing trend, the anti-noise performance and robustness of the TSOA localization algorithm are proved. The TSOA anti-noise performance will be used for reducing the blind-zone and the false location rate of MLAT systems.展开更多
This paper focuses on the methodology analysis for the stability and the corresponding tracking performance of a closed-loop digital jump linear control system with a stochastic switching signal. The method is applied...This paper focuses on the methodology analysis for the stability and the corresponding tracking performance of a closed-loop digital jump linear control system with a stochastic switching signal. The method is applied to a flight control system. A distributed recoverable platform is implemented on the flight control system and subject to independent digital upsets. The upset processes are used to stimulate electromagnetic environments. Specifically, the paper presents the scenarios that the upset process is directly injected into the distributed flight control system, which is modeled by independent Markov upset processes and independent and identically distributed （IID） processes. A theoretical performance analysis and simulation modelling are both presented in detail for a more complete independent digital upset injection. The specific examples are proposed to verify the methodology of tracking performance analysis. The general analyses for different configurations are also proposed. Comparisons among different configurations are conducted to demonstrate the availability and the characteristics of the design.展开更多
A system designed for supporting the network performance analysis and forecast effort is presented, based on the combination of offline network analysis and online real-time performance forecast. The off-line analysis...A system designed for supporting the network performance analysis and forecast effort is presented, based on the combination of offline network analysis and online real-time performance forecast. The off-line analysis will perform analysis of specific network node performance, correlation analysis of relative network nodes performance and evolutionary mathematical modeling of long-term network performance measurements. The online real-time network performance forecast will be based on one so-called hybrid prediction modeling approach for short-term network, performance prediction and trend analysis. Based on the module design, the system proposed has good intelligence, scalability and self-adaptability, which will offer highly effective network performance analysis and forecast tools for network managers, and is one ideal support platform for network performance analysis and forecast effort.展开更多
Emulation platforms are critical for evaluation and verification in the research of networking technologies and protocols for space networks(SN).High fidelity emulating technologies have been extensively studied for S...Emulation platforms are critical for evaluation and verification in the research of networking technologies and protocols for space networks(SN).High fidelity emulating technologies have been extensively studied for SN in earlier work,while little emphasis has been placed on the performance evaluation part.In this paper,the design of a network performance analysis architecture is presented,with which high-speed network traffic can be captured and indexed,and the performance of the emulated SN can be well analyzed and evaluated.This architecture comprises three components,namely capture layer,storage layer and analysis layer.Analytic Hierarchy Process(AHP)and several analysis methods are adopted to evaluate the network performance comprehensively.In the implementation of the proposed architecture,configuration optimization and parallel processing are applied to handle large amount of high-speed network traffic.Finally,experiment results through the analysis system exhibits the effectiveness of the proposed architecture.展开更多
Electrodynamic tethered deorbit technology is a novel way to remove abandoned spacecrafts like upper stages or unusable satellites. This paper investigates and analyses the deorbit performance and mission applicabilit...Electrodynamic tethered deorbit technology is a novel way to remove abandoned spacecrafts like upper stages or unusable satellites. This paper investigates and analyses the deorbit performance and mission applicability of the electrodynamic tethered system. To do so, the electrodynamic tethered deorbit dynamics with multi-perturbation is firstly formulated, where the Earth magnetic field, the atmospheric drag, and the Earth oblateness effect are considered. Then, the key system parameters, including payload mass, tether length and tether type, are analyzed by numerical simulations to investigate their influences on the deorbit performance and to give the setting principles for choosing system parameters. Based on this and given an appropriate group of system parameters, numerical simulations are undertaken to study the impact of the mission parameters, including orbit height and orbit inclination, and thus to investigate the mission applicability of the electrodynamic tethered deorbit technology.展开更多
The model of a three-terminal thermoelectric refrigerator with ideal tunneling quantum dots is established. It consists of a cavity connected to two quantum dots embedded between two electron reservoirs at different t...The model of a three-terminal thermoelectric refrigerator with ideal tunneling quantum dots is established. It consists of a cavity connected to two quantum dots embedded between two electron reservoirs at different temperatures and chemical potentials. According to the Landauer formula the expressions for the heat current, the cooling rate and the coefficient of performance （COP） are derived analytically. The performance characteristic curves of the cooling rate versus the coefficient of performance are plotted with numerical calculation. The optimal regions of the cooling rate and the COP are determined. Moreover, we optimize the cooling rate and the COP with respect to the position of energy level of the right quantum dot, respectively. The influence of the width of energy level and the temperature ratio on performance of the three-terminal thermoelectric refrigerator is analyzed. Lastly, when the width of energy level is small enough, the optimal performance of the refrigerator is discussed in detail.展开更多
基金supported by the National Key R&D Project from Ministry of Science and Technology,China(2021YFA1201603)National Natural Science Foundation of China(52073032 and 52192611)the Fundamental Research Funds for the Central Universities.
文摘Triboelectric nanogenerators(TENGs)offer a selfsustaining power solution for marine regions abundant in resources but constrained by energy availability.Since their pioneering use in wave energy harvesting in 2014,nearly a decade of advancements has yielded nearly thousands of research articles in this domain.Researchers have developed various TENG device structures with diverse functionalities to facilitate their commercial deployment.Nonetheless,there is a gap in comprehensive summaries and performance evaluations of TENG structural designs.This paper delineates six innovative structural designs,focusing on enhancing internal device output and adapting to external environments:high space utilization,hybrid generator,mechanical gain,broadband response,multi-directional operation,and hybrid energy-harvesting systems.We summarize the prevailing trends in device structure design identified by the research community.Furthermore,we conduct a meticulous comparison of the electrical performance of these devices under motorized,simulated wave,and real marine conditions,while also assessing their sustainability in terms of device durability and mechanical robustness.In conclusion,the paper outlines future research avenues and discusses the obstacles encountered in the TENG field.This review aims to offer valuable perspectives for ongoing research and to advance the progress and application of TENG technology.
基金supported in part by the National Natural Science Foundation of China under Grant U21B2014,Grant 92267202,and Grant 62271081.
文摘This paper studies the sensing base station(SBS)that has great potential to improve the safety of vehicles and pedestrians on roads.SBS can detect the targets on the road with communication signals using the integrated sensing and communication(ISAC)technique.Compared with vehicle-mounted radar,SBS has a better sensing field due to its higher deployment position,which can help solve the problem of sensing blind areas.In this paper,key technologies of SBS are studied,including the beamforming algorithm,beam scanning scheme,and interference cancellation algorithm.To transmit and receive ISAC signals simultaneously,a double-coupling antenna array is applied.The free detection beam and directional communication beam are proposed for joint communication and sensing to meet the requirements of beamwidth and pointing directions.The joint timespace-frequency domain division multiple access algorithm is proposed to cancel the interference of SBS,including multiuser interference and duplex interference between sensing and communication.Finally,the sensing and communication performance of SBS under the industrial scientific medical power limitation is analyzed and simulated.Simulation results show that the communication rate of SBS can reach over 100 Mbps and the range of sensing and communication can reach about 500 m.
基金supported by the National Natural Science Foundation of China(No.12072304).
文摘This paper presents a novel suspension support tailored for wind tunnel tests of spinning projectiles based on Wire-Driven Parallel Robot(WDPR),uniquely characterized by an SPM(Spinning Projectile Model)-centered mobile platform.First,an SPM-centered mobile platform,featuring two redundant and another unconstrained Degree of Freedom(DOF),and its suspension support mechanism are designed together,collectively constructing a WDPR endowed with kinematic redundancy.Afterward,the kinematics of the mechanism,boundary equations for the redundant DOFs,and relevant kinematic performance indices are then proposed and formulated.The results from both prototype experiments and numerical assessments are presented.The capability of the support mechanism to replicate the complex coupled motions of the SPM is verified by the experimental results,while the proposed kinematics and boundary equations are also validated.Furthermore,it is revealed by numerical assessments that the redundant DOFs of the mobile platform exert a minimal impact on the kinematic performance of the suspension support.Finally,the optimal global attitude performance is obtained when these DOFs are set to zero if they are restricted to constants.However,local attitude performance can be further improved by the variable values.
基金supported by the Natural Science Foundation of Jiangsu Province of China(Grant No.BK20220649)the Natural Science Foundation of the Jiangsu Higher Education Institutions(Grant No.23KJB460010)+1 种基金the Key R&D Program of Jiangsu Province(Grant No.BE2022062)Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.SJCX23_2143).
文摘Research of capture mechanisms with strong capture adaptability and stable grasp is important to solve the problem of launch and recovery of torpedo-shaped autonomous underwater vehicles(AUVs).A multi-loop coupling capture mechanism with strong adaptability and high retraction rate has been proposed for the launch and recovery of torpedo-shaped AUVs with different morphological features.Firstly,the principle of capturing motion retraction is described based on the appearance characteristics of torpedo-shaped AUVs,and the configuration synthesis of the capture mechanism is carried out using the method of constrained chain synthesis.Secondly,the screw theory is employed to analyze the degree of freedom(DoF)of the capture mechanism.Then,the 3D model of the capture mechanism is established,and the kinematics and dynamics simulations are carried out.Combined with the capture orientation requirements of the capture mechanism,the statics and vibration characteristics analyses are carried out.Furthermore,considering the capture process and the underwater working environment,the motion characteristics and hydraulics characteristics of the capture mechanism are analyzed.Finally,a principle prototype is developed and the torpedo-shaped AUVs capture experiment is completed.The work provides technical reserves for the research and development of AUV capture special equipment.
基金Supported by the National Talent Fund of the Ministry of Science and Technology of China(20230240011)China University of Geosciences(Wuhan)Research Fund(162301192687)。
文摘A large language model(LLM)is constructed to address the sophisticated demands of data retrieval and analysis,detailed well profiling,computation of key technical indicators,and the solutions to complex problems in reservoir performance analysis(RPA).The LLM is constructed for RPA scenarios with incremental pre-training,fine-tuning,and functional subsystems coupling.Functional subsystem and efficient coupling methods are proposed based on named entity recognition(NER),tool invocation,and Text-to-SQL construction,all aimed at resolving pivotal challenges in developing the specific application of LLMs for RDA.This study conducted a detailed accuracy test on feature extraction models,tool classification models,data retrieval models and analysis recommendation models.The results indicate that these models have demonstrated good performance in various key aspects of reservoir dynamic analysis.The research takes some injection and production well groups in the PK3 Block of the Daqing Oilfield as an example for testing.Testing results show that our model has significant potential and practical value in assisting reservoir engineers with RDA.The research results provide a powerful support to the application of LLM in reservoir performance analysis.
文摘The importance of cybersecurity in contemporary society cannot be inflated,given the substantial impact of networks on various aspects of daily life.Traditional cybersecurity measures,such as anti-virus software and firewalls,safeguard networks against potential threats.In network security,using Intrusion Detection Systems(IDSs)is vital for effectively monitoring the various software and hardware components inside a given network.However,they may encounter difficulties when it comes to detecting solitary attacks.Machine Learning(ML)models are implemented in intrusion detection widely because of the high accuracy.The present work aims to assess the performance of machine learning algorithms in the context of intrusion detection,providing valuable insights into their efficacy and potential for enhancing cybersecurity measures.The main objective is to compare the performance of the well-knownML models using the UNSW-NB15 dataset.The performance of the models is discussed in detail with a comparison using evaluation metrics and computational performance.
文摘With the increased accessibility of global trade information,transaction fraud has become a major worry in global banking and commerce security.The incidence and magnitude of transaction fraud are increasing daily,resulting in significant financial losses for both customers and financial professionals.With improvements in data mining and machine learning in computer science,the capacity to detect transaction fraud is becoming increasingly attainable.The primary goal of this research is to undertake a comparative examination of cutting-edge machine-learning algorithms developed to detect credit card fraud.The research looks at the efficacy of these machine learning algorithms using a publicly available dataset of credit card transactions performed by European cardholders in 2023,comprising around 550,000 records.The study uses this dataset to assess the performance of well-established machine learning models,measuring their accuracy,recall,and F1 score.In addition,the study includes a confusion matrix for all models to aid in evaluation and training time duration.Machin learning models,including Logistic regression,random forest,extra trees,and LGBM,achieve high accuracy and precision in the credit card fraud detection dataset,with a reported accuracy,recall,and F1 score of 1.00 for both classes.
文摘Today, in the field of computer networks, new services have been developed on the Internet or intranets, including the mail server, database management, sounds, videos and the web server itself Apache. The number of solutions for this server is therefore growing continuously, these services are becoming more and more complex and expensive, without being able to fulfill the needs of the users. The absence of benchmarks for websites with dynamic content is the major obstacle to research in this area. These users place high demands on the speed of access to information on the Internet. This is why the performance of the web server is critically important. Several factors influence performance, such as server execution speed, network saturation on the internet or intranet, increased response time, and throughputs. By measuring these factors, we propose a performance evaluation strategy for servers that allows us to determine the actual performance of different servers in terms of user satisfaction. Furthermore, we identified performance characteristics such as throughput, resource utilization, and response time of a system through measurement and modeling by simulation. Finally, we present a simple queue model of an Apache web server, which reasonably represents the behavior of a saturated web server using the Simulink model in Matlab (Matrix Laboratory) and also incorporates sporadic incoming traffic. We obtain server performance metrics such as average response time and throughput through simulations. Compared to other models, our model is conceptually straightforward. The model has been validated through measurements and simulations during the tests that we conducted.
文摘The diagnosis and prognosis of cardiovascular diseases are critical medical responsibilities that assist cardiologists in correctly classifying patients and treating them accordingly.The utilization of machine learning in the medical domain has witnessed a notable surge due to its ability to discern patterns from vast amounts of data.Machine learning algorithms that can categorize cases of cardiovascular illness may help doctors reduce the number of wrong diagnoses.This research investigates the efficacy of different machine learning algorithms in predicting cardiovascular disease in accordance with risk factors.This study utilizes a variety of machine learning models,including Logistic Regression,Random Forest,Decision Tree,Extra Trees classifier,Support Vector Machine(SVM),XGBoost(XGB),Light Gradient Boosting Machine(LGBM),GaussianNB,and Multilayer Perceptron(MLP).The machine learning models are applied to a concrete dataset acquired from Kaggle.The models underwent training using a dataset that was partitioned into an 80:20 ratio.Machine learning model evaluation involves the utilization of performance measurements such as Accuracy,Precision,Recall,and ROC curves.An exhaustive evaluation is carried out to gauge the efficacy of the models.
文摘In today’s information age,video data,as an important carrier of information,is growing explosively in terms of production volume.The quick and accurate extraction of useful information from massive video data has become a focus of research in the field of computer vision.AI dynamic recognition technology has become one of the key technologies to address this issue due to its powerful data processing capabilities and intelligent recognition functions.Based on this,this paper first elaborates on the development of intelligent video AI dynamic recognition technology,then proposes several optimization strategies for intelligent video AI dynamic recognition technology,and finally analyzes the performance of intelligent video AI dynamic recognition technology for reference.
基金Project(61563032)supported by the National Natural Science Foundation of ChinaProject(18JR3RA133)supported by Gansu Basic Research Innovation Group,China
文摘Microbial fuel cell(MFC)is a kind of promising clean power supply energy equipment,but serious nonlinearities and disturbances exist when the MFC runs,and it is an important topic to guarantee that the output voltage reaches the setting value quickly and smoothly.Regulating the feeding flow is an effective way to achieve this goal,and especially,the satisfactory results can be achieved by regulating anode feeding flow.In this work,a feedforward fuzzy logic PID algorithm is proposed.The fuzzy logic system is introduced to deal with the non-linear dynamics of MFC,and corresponding PID parameters are calculated according to defuzzification.The magnitude value of the current density is used to simulate the value of the external load.The simulation results indicate that the MFC output voltage can track the setting value quickly and smoothly with the proposed feedforward fuzzy logic PID algorithm.The proposed algorithm is more efficient and robust with respect to anti-disturbance performance and tracking accuracy than other three control methods.
基金Supported by the Natural Science Foundation of China(61076019)the China Postdoctoral Science Foundation(20100481134)+1 种基金the Natural Science Foundation of Jiangsu Province(BK2008387)the Graduate Student Innovation Foundation of Jiangsu Province(CX07B-105z)~~
文摘The network on chip（NoC）is used as a solution for the communication problems in a complex system on chip（SoC）design.To further enhance performances,the NoC architectures,a high level modeling and an evaluation method based on OPNET are proposed to analyze their performances on different injection rates and traffic patterns.Simulation results for general NoC in terms of the average latency and the throughput are analyzed and used as a guideline to make appropriate choices for a given application.Finally,a MPEG4 decoder is mapped on different NoC architectures.Results prove the effectiveness of the evaluation method.
文摘This paper presents RTSS simulation software with the capability for graphical model building and animation display. The RTSS simulation software consists of three separated parts: the simulation kernel, the model building program and the result post processing program. The RTSS may run in the client/server mode. The main features of the RTSS software are more modular, more flexible and easier to upgrade. RTSS is built on object oriented technology, so it has more flexibility. The RTSS model of a system is an open queueing network. For modeling various data acquisition systems, communication networks and flexible manufacturing systems at different abstraction levels, RTSS has proven to be an extremely useful tool for performance analysis.
基金the National Natural Science Foundation of China(No.61605223)the Strategic Priority Research Program of Chinese Academy of Sciences(No.614A010717)the Director Fund of Advanced Laser Technology Laboratory of Anhui Province(No.AHL2021ZR06)。
文摘A numerical simulation model of plenoptic sensor aberration wavefront detection is established to simulate and analyze the detection performance of plenoptic sensor aberration wavefront for different turbulence intensities.The results show that the plenoptic sensor can achieve better distortion wavefront detection,and its wavefront detection accuracy improves with turbulence intensity.The unique optical structure design of the plenoptic sensor makes it more suitable for aberration wavefront detection in strong turbulent conditions.The wavefront detection performance of the plenoptic sensor is not only related to its wavefront reconstruction algorithm but also closely related to its structural parameter settings.The influence of structural parameters on the wavefront detection accuracy of plenoptic sensors under different turbulence intensities is simulated and analyzed.The variation law of wavefront detection accuracy and structural parameters under different turbulence intensities is summarized to provide a reference for the structural design and parameter optimization of plenoptic sensors.
基金supported by the Joint Civil Aviation Fund of National Natural Science Foundation of China(Nos.U1533108 and U1233112)
文摘The theoretical positioning accuracy of multilateration(MLAT) with the time difference of arrival(TDOA) algorithm is very high. However, there are some problems in practical applications. Here we analyze the location performance of the time sum of arrival(TSOA) algorithm from the root mean square error(RMSE) and geometric dilution of precision(GDOP) in additive white Gaussian noise(AWGN) environment. The TSOA localization model is constructed. Using it, the distribution of location ambiguity region is presented with 4-base stations. And then, the location performance analysis is started from the 4-base stations with calculating the RMSE and GDOP variation. Subsequently, when the location parameters are changed in number of base stations, base station layout and so on, the performance changing patterns of the TSOA location algorithm are shown. So, the TSOA location characteristics and performance are revealed. From the RMSE and GDOP state changing trend, the anti-noise performance and robustness of the TSOA localization algorithm are proved. The TSOA anti-noise performance will be used for reducing the blind-zone and the false location rate of MLAT systems.
基金Project supported by the Young Scientists Fund of the National Natural Science Foundation of China(Grant No.61403395)the Natural Science Foundation of Tianjin,China(Grant No.13JCYBJC39000)+2 种基金the Scientific Research Foundation for the Returned Overseas Chinese Scholars,State Education Ministry,Chinathe Tianjin Key Laboratory of Civil Aircraft Airworthiness and Maintenance in Civil Aviation of China(Grant No.104003020106)the Fund for Scholars of Civil Aviation University of China(Grant No.2012QD21x)
文摘This paper focuses on the methodology analysis for the stability and the corresponding tracking performance of a closed-loop digital jump linear control system with a stochastic switching signal. The method is applied to a flight control system. A distributed recoverable platform is implemented on the flight control system and subject to independent digital upsets. The upset processes are used to stimulate electromagnetic environments. Specifically, the paper presents the scenarios that the upset process is directly injected into the distributed flight control system, which is modeled by independent Markov upset processes and independent and identically distributed （IID） processes. A theoretical performance analysis and simulation modelling are both presented in detail for a more complete independent digital upset injection. The specific examples are proposed to verify the methodology of tracking performance analysis. The general analyses for different configurations are also proposed. Comparisons among different configurations are conducted to demonstrate the availability and the characteristics of the design.
基金the National 863 High-Tech Project (863 -3 0 0 -0 2 -0 9-99) and Key Research Project of Hubei Province(991P110 )
文摘A system designed for supporting the network performance analysis and forecast effort is presented, based on the combination of offline network analysis and online real-time performance forecast. The off-line analysis will perform analysis of specific network node performance, correlation analysis of relative network nodes performance and evolutionary mathematical modeling of long-term network performance measurements. The online real-time network performance forecast will be based on one so-called hybrid prediction modeling approach for short-term network, performance prediction and trend analysis. Based on the module design, the system proposed has good intelligence, scalability and self-adaptability, which will offer highly effective network performance analysis and forecast tools for network managers, and is one ideal support platform for network performance analysis and forecast effort.
基金supported by the National Natural Science Foundation of China under Grant 62131012the Fundamental Research Funds for the Central Universities under Grant 021014380187。
文摘Emulation platforms are critical for evaluation and verification in the research of networking technologies and protocols for space networks(SN).High fidelity emulating technologies have been extensively studied for SN in earlier work,while little emphasis has been placed on the performance evaluation part.In this paper,the design of a network performance analysis architecture is presented,with which high-speed network traffic can be captured and indexed,and the performance of the emulated SN can be well analyzed and evaluated.This architecture comprises three components,namely capture layer,storage layer and analysis layer.Analytic Hierarchy Process(AHP)and several analysis methods are adopted to evaluate the network performance comprehensively.In the implementation of the proposed architecture,configuration optimization and parallel processing are applied to handle large amount of high-speed network traffic.Finally,experiment results through the analysis system exhibits the effectiveness of the proposed architecture.
文摘Electrodynamic tethered deorbit technology is a novel way to remove abandoned spacecrafts like upper stages or unusable satellites. This paper investigates and analyses the deorbit performance and mission applicability of the electrodynamic tethered system. To do so, the electrodynamic tethered deorbit dynamics with multi-perturbation is firstly formulated, where the Earth magnetic field, the atmospheric drag, and the Earth oblateness effect are considered. Then, the key system parameters, including payload mass, tether length and tether type, are analyzed by numerical simulations to investigate their influences on the deorbit performance and to give the setting principles for choosing system parameters. Based on this and given an appropriate group of system parameters, numerical simulations are undertaken to study the impact of the mission parameters, including orbit height and orbit inclination, and thus to investigate the mission applicability of the electrodynamic tethered deorbit technology.
基金Supported by the National Natural Science Foundation of China under Grant No 11365015
文摘The model of a three-terminal thermoelectric refrigerator with ideal tunneling quantum dots is established. It consists of a cavity connected to two quantum dots embedded between two electron reservoirs at different temperatures and chemical potentials. According to the Landauer formula the expressions for the heat current, the cooling rate and the coefficient of performance （COP） are derived analytically. The performance characteristic curves of the cooling rate versus the coefficient of performance are plotted with numerical calculation. The optimal regions of the cooling rate and the COP are determined. Moreover, we optimize the cooling rate and the COP with respect to the position of energy level of the right quantum dot, respectively. The influence of the width of energy level and the temperature ratio on performance of the three-terminal thermoelectric refrigerator is analyzed. Lastly, when the width of energy level is small enough, the optimal performance of the refrigerator is discussed in detail.
