Configuration Synthesis and Grasping Performance Analysis of Multi-Loop Coupling Capture Mechanism for Launch and Recovery of Torpedo-Shaped Autonomous Underwater Vehicle

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.

Performance Analysis and Optimization of Energy Harvesting Modulation for Multi-User Integrated Data and Energy Transfer

Integrated data and energy transfer(IDET)enables the electromagnetic waves to transmit wireless energy at the same time of data delivery for lowpower devices.In this paper,an energy harvesting modulation(EHM)assisted multi-user IDET system is studied,where all the received signals at the users are exploited for energy harvesting without the degradation of wireless data transfer(WDT)performance.The joint IDET performance is then analysed theoretically by conceiving a practical time-dependent wireless channel.With the aid of the AO based algorithm,the average effective data rate among users are maximized by ensuring the BER and the wireless energy transfer(WET)performance.Simulation results validate and evaluate the IDET performance of the EHM assisted system,which also demonstrates that the optimal number of user clusters and IDET time slots should be allocated,in order to improve the WET and WDT performance.

Python Server Page Performance Analysis and Modeling

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.

Optimization and Performance Analysis of Intelligent Video AI Dynamic

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.

Performance Analysis of the Packet-Based PNT Service in NGSO Broadband Satellite Communication Systems

Providing alternative PNT service to GNSS-challenged users will be an important function of next-generation NGSO broadband satellite communication systems.Herein,a packet-based PNT service architecture in NGSO broadband systems is proposed in which a primary satellite and selected assistant satellites work together to provide PNT service to requesting users.Its positioning performance bounds are mathematically formulated by rigorously analyzing the bounds constrained by different waveforms.Simulations are conducted on different configurations of Walker Delta MEO constellations and Walker Star LEO constellations for corroboration,revealing the following:(1)Both MEO and LEO constellations achieve sub-meter-level positioning precision given enough satellites.(2)Compared to the GNSS Doppler-based velocity estimation method,the position advance based velocity estimation algorithm is more precise and applicable to the PNT service in NGSO broadband systems.(3)To provide PNT service to users in GNSS-challenged environments,the primary and each assistant satellite need only∼0.1‰of the time of one downlink beam.

Performance analysis of quantum key distribution using polarized coherent-states in free-space channel

In free space channel,continuous-variable quantum key distribution(CV-QKD)using polarized coherent-states can not only make the signal state more stable and less susceptible to interference based on the polarization non-sensitive of the free-space channel,but also reduce the noise introduced by phase interference.However,arbitrary continuous modulation can not be carried out in the past polarization coding,resulting in that the signal state can not obtain arbitrary continuous value in Poincare space,and the security analysis of CV-QKD using polarized coherent-states in free space is not complete.Here we propose a new modulation method to extend the modulation range of signal states with an optical-fiber-based polarization controller.In particular,in terms of the main influence factors in the free-space channel,we utilize the beam extinction and elliptical model when considering the transmittance and adopt the formulation of secret key rate.In addition,the performance of the proposed scheme under foggy weather is also taken into consideration to reveal the influence of severe weather.Numerical simulation shows that the proposed scheme is seriously affected by attenuation under foggy weather.The protocol fails when visibility is less than 1 km.At the same time,the wavelength can affect the performance of the proposed scheme.Specifically,under foggy weather,the longer the wavelength,the smaller the attenuation coefficient,and the better the transmission performance.Our proposed scheme can expand the modulation range of signal state,and supplement the security research of the scheme in the free-space channel,thus can provide theoretical support for subsequent experiments.

Evolutionary Algorithm Based Feature Subset Selection for Students Academic Performance Analysis

Educational Data Mining(EDM)is an emergent discipline that concen-trates on the design of self-learning and adaptive approaches.Higher education institutions have started to utilize analytical tools to improve students’grades and retention.Prediction of students’performance is a difficult process owing to the massive quantity of educational data.Therefore,Artificial Intelligence(AI)techniques can be used for educational data mining in a big data environ-ment.At the same time,in EDM,the feature selection process becomes necessary in creation of feature subsets.Since the feature selection performance affects the predictive performance of any model,it is important to elaborately investigate the outcome of students’performance model related to the feature selection techni-ques.With this motivation,this paper presents a new Metaheuristic Optimiza-tion-based Feature Subset Selection with an Optimal Deep Learning model(MOFSS-ODL)for predicting students’performance.In addition,the proposed model uses an isolation forest-based outlier detection approach to eliminate the existence of outliers.Besides,the Chaotic Monarch Butterfly Optimization Algo-rithm(CBOA)is used for the selection of highly related features with low com-plexity and high performance.Then,a sailfish optimizer with stacked sparse autoencoder(SFO-SSAE)approach is utilized for the classification of educational data.The MOFSS-ODL model is tested against a benchmark student’s perfor-mance data set from the UCI repository.A wide-ranging simulation analysis por-trayed the improved predictive performance of the MOFSS-ODL technique over recent approaches in terms of different measures.Compared to other methods,experimental results prove that the proposed(MOFSS-ODL)classification model does a great job of predicting students’academic progress,with an accuracy of 96.49%.

A CSMA/CA based MAC protocol for hybrid Power-line/Visible-light communication networks:Design and analysis

Hybrid Power-line/Visible-light Communication(HPVC)network has been one of the most promising Cooperative Communication(CC)technologies for constructing Smart Home due to its superior communication reliability and hardware efficiency.Current research on HPVC networks focuses on the performance analysis and optimization of the Physical(PHY)layer,where the Power Line Communication(PLC)component only serves as the backbone to provide power to light Emitting Diode(LED)devices.So designing a Media Access Control(MAC)protocol remains a great challenge because it allows both PLC and Visible Light Communication(VLC)components to operate data transmission,i.e.,to achieve a true HPVC network CC.To solve this problem,we propose a new HPC network MAC protocol(HPVC MAC)based on Carrier Sense Multiple Access/Collision Avoidance(CSMA/CA)by combining IEEE 802.15.7 and IEEE 1901 standards.Firstly,we add an Additional Assistance(AA)layer to provide the channel selection strategies for sensor stations,so that they can complete data transmission on the selected channel via the specified CSMA/CA mechanism,respectively.Based on this,we give a detailed working principle of the HPVC MAC,followed by the construction of a joint analytical model for mathematicalmathematical validation of the HPVC MAC.In the modeling process,the impacts of PHY layer settings(including channel fading types and additive noise feature),CSMA/CA mechanisms of 802.15.7 and 1901,and practical configurations(such as traffic rate,transit buffer size)are comprehensively taken into consideration.Moreover,we prove the proposed analytical model has the solvability.Finally,through extensive simulations,we characterize the HPVC MAC performance under different system parameters and verify the correctness of the corresponding analytical model with an average error rate of 4.62%between the simulation and analytical results.

PERFORMANCE ANALYSIS AND KINEMATIC DESIGN OF PURE TRANSLATIONAL PARALLEL MECHANISM WITH VERTICAL GUIDE-WAYS

Performance analysis and kinematic design of the 3-PUU pure translational parallel mechanism with vertical guide-ways are investigated. Two novel performance indices, the critical slider stroke and the main section area of workspace, are defined; The expressions of two other indices, i.e. the global dexterity and global force transfer ratio are revised based on the main section of workspace. Using these indices, performance changes versus the varieties of dimensional parameters of mechanism are investigated in detail and the graphic descriptions of change tendencies of the performance indices are illustrated. By means of these obtained graphic descriptions, kinematic parameters for the 3-PUU pure translational parallel mechanism with better characteristics can be directly acquired.

Power Allocation and Performance Analysis of the Collaborative NOMA Assisted Relaying Systems in 5G

Serving multiple cell-edge mobile terminals poses multifaceted challenges due to the increased transmission power and interferences, which could be overcome by relay communications. With the recent advancement of 5G technologies, non-orthogonal multiple access(NOMA) has been used at relay node to transmit multiple messages simultaneously to multiple cell-edge users. In this paper, a Collaborative NOMA Assisted Relaying(CNAR) system for 5G is proposed by enabling the collaboration of source-relay(S-R) and relay-destination(R-D) NOMA links. The relay node of the CNAR decodes the message for itself from S-R NOMA signal and transmits the remaining messages to the multiple cell-edge users in R-D link. A simplified-CNAR(S-CNAR) system is then developed to reduce the relay complexity. The outage probabilities for both systems are analyzed by considering outage behaviors in S-R and R-D links separately. To guarantee the data rate, the optimal power allocation among NOMA users is achieved by minimizing the outage probability. The ergodic sum capacity in high SNR regime is also approximated. Our mathematical analysis and simulation results show that CNAR system outperforms existing transmission strategies and S-CNAR reaches similar performance with much lower complexity.

Performance analysis and optimal design for well patterns in anisotropic formations

The mechanism of the effects of anisotropic permeability on well patterns and reservoir development are investigated by coordinate transformation, fluid flow analysis, and reservoir development concepts. Anisotropy of permeability has reconstructive effects on well patterns. The originally designed flooding units are broken up, and new pattern units are made up of the wells that belong to different original units. The behavior possesses strong randomness, and leads to a complicated relationship among the injection and production wells, and unpredictable productivity of the formations. To prevent the break-up of well patterns, well lines should be either parallel or perpendicular to the maximum principal direction of the anisotropic permeability （i.e. the fracture direction）. To optimize the development effects ofanisotropic formations, the latitudinal and longitudinal well spacing of the well network are calculated from the principal values of the anisotropic permeability.

Performance analysis of active schedules in identical parallel machine

Active schedule is one of the most basic and popular concepts in production scheduling research. For identical parallel machine scheduling with jobs＇ dynamic arrivals, the tight performance bounds of active schedules under the measurement of four popular objectives are respectively given in this paper. Similar analysis method and conclusions can be generalized to static identical parallel machine and single machine scheduling problem.

Performance Modeling and Approximate Analysis of Multiserver Multiqueue Systems with Poisson and Self-similar Arrivals

The problem of state space explosion is still ran outstanding challenge in Markovian performance analysis for multiserver multiqueue (MSMQ) systems. The system behavior of a MSMQ system is described using stochastic high-level Petri net (SHLPN) models, and an approximate performance analysis technique is proposed based on decomposition and refinement methods as well as iteration technique. A real MSMQ system, Web-server cluster, is investigated. The performance of an integrated scheme of request dispatching and scheduling is analyzed with both Poisson and self-similar request arrivals. The study shows that the approximate analysis technique significantly reduces the complexity of the model solution and is also efficient for accuracy of numerical results.

Performance analysis of empirical models for predicting rock mass deformation modulus using regression and Bayesian methods

Deformation modulus of rock mass is one of the input parameters to most rock engineering designs and constructions.The field tests for determination of deformation modulus are cumbersome,expensive and time-consuming.This has prompted the development of various regression equations to estimate deformation modulus from results of rock mass classifications,with rock mass rating(RMR)being one of the frequently used classifications.The regression equations are of different types ranging from linear to nonlinear functions like power and exponential.Bayesian method has recently been developed to incorporate regression equations into a Bayesian framework to provide better estimates of geotechnical properties.The question of whether Bayesian method improves the estimation of geotechnical properties in all circumstances remains open.Therefore,a comparative study was conducted to assess the performances of regression and Bayesian methods when they are used to characterize deformation modulus from the same set of RMR data obtained from two project sites.The study also investigated the performance of different types of regression equations in estimation of the deformation modulus.Statistics,probability distributions and prediction indicators were used to assess the performances of regression and Bayesian methods and different types of regression equations.It was found that power and exponential types of regression equations provide a better estimate than linear regression equations.In addition,it was discovered that the ability of the Bayesian method to provide better estimates of deformation modulus than regression method depends on the quality and quantity of input data as well as the type of the regression equation.

Sensitivity and Distance Based Performance Analysis for Batteryless Tags with Transmit Beamforming and Ambient Backscattering

Ambient backscatter is a new green technology for Internet of Things(IoT)that utilizes surrounding wireless signals to enable batteryless devices to communicate with other devices.The battery-free devices first harvest energy from ambient wireless signals and then backscatter the signals for communications.Clearly,sensitivity and distance are two important parameters for system performance.However,most existing studies on ambient backscatter communication systems do not consider the impact of the sensitivity of the energy-harvesting nodes and the distances between these devices.In this paper,we first provide a literature review for ambient communication technology and then take sensitivity and distance as two key parameters and investigate the sensitivity and distance based performance for ambient backscatter communication systems.Specifically,we establish the mathematical model based on distances between transceivers and backscattering nodes,extract a parameter that can differentiate the direct path and the backscattering path,evaluate the effects of transmit beamforming,design an energy detector for the reader,and analyze the outage probability of energy harvesting at the tag and the bit error rate(BER)at the reader.Simulations are then provided to corroborate the proposed studies.

IMPLEMENTATION AND PERFORMANCE ANALYSIS OF ACCURATE LOCALIZATION OF SHORT-RANGE TARGETS BASED ON MULTISENSOR SYSTEMS

In this paper, the optimal estimate method is systematically investigated for estimating the position and velocity vectors of a short range target in space with a multisensor system TR n (one transmitting sensor and n receiving sensors). A suboptimal and realizable signal processing scheme is provided. The performance of the suboptimal procedure is analyzed theoretically in detail, and analytical expressions are obtained for the covariance matrix of the estimator error. Simulation results verify the theoretical prediction, which demonstrates the system is able to accurately locate a short range target.

Stability and performance analysis of a jump linear control system subject to digital upsets

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.

Design of Intelligent Network Performance Analysis & Forecast Support System

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.

Comparative Analysis of the Measured and Simulated Performances of a Grid-Connected Photovoltaic Power Plant

The present study comparing actual data and simulated parameters was carried out using the PVsyst software for a 5.94 KWp grid-connected photovoltaic system,consisting of three types of mono-Si(2.04 KWp),poly-Si(2.04 KWp)and amorphous-Si(1.86 KWp)photovoltaic panels and a weather station.The research is based on data collected for one year(2020)of energy production Simulations were performed using long-term meteorological data generated by NASA and on-site measurement.A comparison of evaluated monthly and annually performance elements has also been considered:Eac,PR,FC.As shown by the results,each photovoltaic technology has certain advantages in different weather conditions.The uncertainties of the PVSyst software used to estimate the output of the photovoltaic installation have also been critically examined.

Design and Implementation of a Network Performance Analysis System for Space Network Emulation Platforms

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.