SFGA-CPA: A Novel Screening Correlation Power Analysis Framework Based on Genetic Algorithm

Correlation power analysis(CPA)combined with genetic algorithms(GA)now achieves greater attack efficiency and can recover all subkeys simultaneously.However,two issues in GA-based CPA still need to be addressed:key degeneration and slow evolution within populations.These challenges significantly hinder key recovery efforts.This paper proposes a screening correlation power analysis framework combined with a genetic algorithm,named SFGA-CPA,to address these issues.SFGA-CPA introduces three operations designed to exploit CPA characteris-tics:propagative operation,constrained crossover,and constrained mutation.Firstly,the propagative operation accelerates population evolution by maximizing the number of correct bytes in each individual.Secondly,the constrained crossover and mutation operations effectively address key degeneration by preventing the compromise of correct bytes.Finally,an intelligent search method is proposed to identify optimal parameters,further improving attack efficiency.Experiments were conducted on both simulated environments and real power traces collected from the SAKURA-G platform.In the case of simulation,SFGA-CPA reduces the number of traces by 27.3%and 60%compared to CPA based on multiple screening methods(MS-CPA)and CPA based on simple GA method(SGA-CPA)when the success rate reaches 90%.Moreover,real experimental results on the SAKURA-G platform demonstrate that our approach outperforms other methods.

Research on the Work-for-Relief Policy within the Scope of Comprehensive Rural Revitalization:Quantitative Analysis of Policy Texts Based on 71 Policy Documents

Work-for-relief plays a unique role in China’s journey toward modernization.From the perspectives of policy tools and interest analysis,this paper uses quantitative analysis of policy texts and integrates grounded theory to build a policy expression analysis model to discuss the current work-for-relief policy system.The study found that China’s use of the work-for-relief policy is unbalanced,and it is necessary to enhance the involvement of non-governmental sectors,as well as to fully consider the policy’s target groups and the social issues that need addressing.

Short-Term Prediction of Photovoltaic Power Generation Based on LMD Permutation Entropy and Singular Spectrum Analysis

The power output state of photovoltaic power generation is affected by the earth’s rotation and solar radiation intensity.On the one hand,its output sequence has daily periodicity;on the other hand,it has discrete randomness.With the development of new energy economy,the proportion of photovoltaic energy increased accordingly.In order to solve the problem of improving the energy conversion efficiency in the grid-connected optical network and ensure the stability of photovoltaic power generation,this paper proposes the short-termprediction of photovoltaic power generation based on the improvedmulti-scale permutation entropy,localmean decomposition and singular spectrum analysis algorithm.Firstly,taking the power output per unit day as the research object,the multi-scale permutation entropy is used to calculate the eigenvectors under different weather conditions,and the cluster analysis is used to reconstruct the historical power generation under typical weather rainy and snowy,sunny,abrupt,cloudy.Then,local mean decomposition(LMD)is used to decompose the output sequence,so as to extract more detail components of the reconstructed output sequence.Finally,combined with the weather forecast of the Meteorological Bureau for the next day,the singular spectrumanalysis algorithm is used to predict the photovoltaic classification of the recombination decomposition sequence under typical weather.Through the verification and analysis of examples,the hierarchical prediction experiments of reconstructed and non-reconstructed output sequences are compared.The results show that the algorithm proposed in this paper is effective in realizing the short-term prediction of photovoltaic generator,and has the advantages of simple structure and high prediction accuracy.

A Single Feasibility Study of System Multi-feature Analysis and Evaluation Tool Based on AADL Model

The tool for analyzing and evaluating system characteristics based on the AADL model can achieve real-time,reliability,security,and schedulability analysis and evaluation for software-intensive systems.It provides a complete solution for quality analysis of real-time,reliability,safety,and schedulability in the design and demonstration stages of software-intensive systems.By using the system′s multi-characteristic(real-time capability,reliability,safety,schedulability)analysis and evaluation tool based on AADL models,it can meet the software non-functional requirements stipulated by the existing model development standards and specifications.This effectively enhances the efficiency of demonstrating the compliance of the system′s non-functional quality attributes in the design work of our unit′s software-intensive system.It can also improve the performance of our unit′s software-intensive system in engineering inspections and requirement reviews conducted by various organizations.The improvement in the quality level of software-intensive systems can enhance the market competitiveness of our unit′s electronic products.

Analysis of Potential Causes of Safety Failure of New Energy Vehicle Power Batteries

The aim of this paper is to analyze the potential reasons for the safety failure of batteries for new-energy vehicles.Firstly,the importance and popularization of new energy batteries are introduced,and the importance of safety failure issues is drawn out.Then,the composition and working principle of the battery is explained in detail,which provides the basis for the subsequent analysis.Then,the potential impacts of factors such as overcharge and over-discharge,high and low temperature environments,internal faults,and external shocks and vibrations on the safety of the batteries are analyzed.Finally,some common safety measures and solutions are proposed to improve the safety of new energy batteries,in hopes of improving the safety of batteries for new-energy vehicle.

DYNAMICS ANALYSIS OF SPECIAL STRUCTURE OF MILLING-HEAD MACHINE TOOL

The milling-head machine tool is a sophisticated and high-quality machine tool of which the spindle system is made up of special multi-element structure. Two special mechanical configurations make the cutting performance of the machine tool decline. One is the milling head spindle supported on two sets of complex bearings. The mechanical dynamic rigidity of milling head structure is researched on designed digital prototype with finite element analysis（FEA） and modal synthesis analysis （ MSA ） for identifying the weak structures. The other is the ram structure hanging on milling head. The structure is researched to get dynamic performance on cutting at different ram extending positions. The analysis results on spindle and ram are used to improve the mechanical configurations and structure in design. The machine tool is built up with modified structure and gets better dynamic rigidity than it was before.

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.

Rural Power System Load Forecast Based on Principal Component Analysis

Power load forecasting accuracy related to the development of the power system. There were so many factors influencing the power load, but their effects were not the same and what factors played a leading role could not be determined empirically. Based on the analysis of the principal component, the paper forecasted the demands of power load with the method of the multivariate linear regression model prediction. Took the rural power grid load for example, the paper analyzed the impacts of different factors on power load, selected the forecast methods which were appropriate for using in this area, forecasted its 2014-2018 electricity load, and provided a reliable basis for grid planning.

Application of Statistical Tools for Data Analysis and Interpretation in Rice Plant Pathology

There has been a significant advancement in the application of statistical tools in plant pathology during the past four decades. These tools include multivariate analysis of disease dynamics involving principal component analysis, cluster analysis, factor analysis, pattern analysis, discriminant analysis, multivariate analysis of variance, correspondence analysis, canonical correlation analysis, redundancy analysis, genetic diversity analysis, and stability analysis, which involve in joint regression, additive main effects and multiplicative interactions, and genotype-by-environment interaction biplot analysis. The advanced statistical tools, such as non-parametric analysis of disease association, meta-analysis, Bayesian analysis, and decision theory, take an important place in analysis of disease dynamics. Disease forecasting methods by simulation models for plant diseases have a great potentiality in practical disease control strategies. Common mathematical tools such as monomolecular, exponential, logistic, Gompertz and linked differential equations take an important place in growth curve analysis of disease epidemics. The highly informative means of displaying a range of numerical data through construction of box and whisker plots has been suggested. The probable applications of recent advanced tools of linear and non-linear mixed models like the linear mixed model, generalized linear model, and generalized linear mixed models have been presented. The most recent technologies such as micro-array analysis, though cost effective, provide estimates of gene expressions for thousands of genes simultaneously and need attention by the molecular biologists. Some of these advanced tools can be well applied in different branches of rice research, including crop improvement, crop production, crop protection, social sciences as well as agricultural engineering. The rice research scientists should take advantage of these new opportunities adequately in adoption of the new highly potential advanced technologies while planning experimental designs, data collection, analysis and interpretation of their research data sets.

POWER FLOW ANALYSIS AND APPLICATION SIMULATION OF ELECTROMAGNETIC CONTINUOUSLY VARIABLE TRANSMISSION

With the structure of two air gaps and two rotors, the electromagnetic continuously variable transmission（EMCVT） is a novel power-split continuously variable transmission（CVT）. There are two kinds of power flowing through the EMCVT, one is mechanical power and the other is electric power. In the mean time, there are three power ports in the EMCVT, one is the outer rotor named mechanical power port and the other two are the inner rotor and the stator named electric power ports. The mechanical power port is connected to the driving wheels through the final gear and the electric ports are connected to the batteries through the transducers. The two kinds of power are coupled on the outer rotor of the EMCVT. The EMCVT can be equipped on the conventional vehicle being regarded as the CVT and it also can be equipped on the hybrid electric vehicle（HEV） as the multi-energy sources assembly. The power flows of these two kinds of applications are analysed. The back electromotive force（EMF） equations are illatively studied and so the dynamic mathematic model is theorized. In order to certify the feasibility of the above theories, three simulations are carried out in allusion to the above two kinds of mentioned applications of the EMCVT and a five speed automatic transmission（AT） vehicle. The simulation results illustrate that the efficiency of the EMCVT vehicles is higher than that of the AT vehicle owed to the optimized operation area of the engine. Hence the fuel consumption of the EMCVT vehicles is knock-down.

Tool Health Condition Recognition Method for High Speed Milling of Titanium Alloy Based on Principal Component Analysis (PCA) and Long Short Term Memory (LSTM)

The healthy condition of the milling tool has a very high impact on the machining quality of the titanium components.Therefore,it is important to recognize the healthy condition of the tool and replace the damaged cutter at the right time.In order to recognize the health condition of the milling cutter,a method based on the long short term memory(LSTM)was proposed to recognize tool health state in this paper.The various signals collected in the tool wear experiments were analyzed by time-domain statistics,and then the extracted data were generated by principal component analysis(PCA)method.The preprocessed data extracted by PCA is transmitted to the LSTM model for recognition.Compared with back propagation neural network(BPNN)and support vector machine(SVM),the proposed method can effectively utilize the time-domain regulation in the data to achieve higher recognition speed and accuracy.

Review on failure analysis of interconnections in power devices

Interconnections in microelectronic packaging are not only the physical carrier to realize the function of electronic circuits,but also the weak spots in reliability tests.Most of failures in power devices are caused by the malfunction of interconnections,including failure of bonding wire as well as cracks of solder layer.In fact,the interconnection failure of power devices is the result of a combination of factors such as electricity,temperature,and force.It is significant to investigate the failure mechanisms of various factors for the failure analysis of interconnections in power devices.This paper reviews the main failure modes of bonding wire and solder layer in the interconnection structure of power devices,and its failure mechanism.Then the reliability test method and failure analysis techniques of interconnection in power device are introduced.These methods are of great significance to the reliability analysis and life prediction of power devices.

Benchmarking Approach to Compare Web Applications Static Analysis Tools Detecting OWASP Top Ten Security Vulnerabilities

To detect security vulnerabilities in a web application,the security analyst must choose the best performance Security Analysis Static Tool(SAST)in terms of discovering the greatest number of security vulnerabilities as possible.To compare static analysis tools for web applications,an adapted benchmark to the vulnerability categories included in the known standard Open Web Application Security Project(OWASP)Top Ten project is required.The information of the security effectiveness of a commercial static analysis tool is not usually a publicly accessible research and the state of the art on static security tool analyzers shows that the different design and implementation of those tools has different effectiveness rates in terms of security performance.Given the significant cost of commercial tools,this paper studies the performance of seven static tools using a new methodology proposal and a new benchmark designed for vulnerability categories included in the known standard OWASP Top Ten project.Thus,the practitioners will have more precise information to select the best tool using a benchmark adapted to the last versions of OWASP Top Ten project.The results of this work have been obtaining using widely acceptable metrics to classify them according to three different degree of web application criticality.

Data network traffic analysis and optimization strategy of real-time power grid dynamic monitoring system for wide-frequency measurements

The application and development of a wide-area measurement system(WAMS)has enabled many applications and led to several requirements based on dynamic measurement data.Such data are transmitted as big data information flow.To ensure effective transmission of wide-frequency electrical information by the communication protocol of a WAMS,this study performs real-time traffic monitoring and analysis of the data network of a power information system,and establishes corresponding network optimization strategies to solve existing transmission problems.This study utilizes the traffic analysis results obtained using the current real-time dynamic monitoring system to design an optimization strategy,covering the optimization in three progressive levels:the underlying communication protocol,source data,and transmission process.Optimization of the system structure and scheduling optimization of data information are validated to be feasible and practical via tests.

Dynamic character analysis for the arc welding power source based on fuzzy logic

A lot of experimental methods have been brought forth to assess the dynamic character of the arc welding power source, but up to now, this issue has not been solved very well. In this paper, based on the fuzzy logic reasoning method, a dynamic character assessing model for the arc welding power source was established and used to analyze the dynamic character of the welding power source. Three different types of welding machine have been tested, and the characteristic information of the electrical signals such as re-striking arc voltage, low welding current and so on of the welding process were extracted accurately by using a self-developed welding dynamic arc wavelet analyzer. The experimental results indicate that this model can be used as a new assessing method for the dynamic character of the arc welding power source.

Post hoc power analysis:is it an informative and meaningful analysis?

Power analysis is a key component for planning prospective studies such as clinical trials. However, some journals in biomedical and psychosocial sciences ask for power analysis for data already collected and analysed before accepting manuscripts for publication. In this report, post hoc power analysis for retrospective studies is examined and the informativeness of understanding the power for detecting significant effects of the results analysed, using the same data on which the power analysis is based, is scrutinised. Monte Carlo simulation is used to investigate the performance of posthoc power analysis.

Architecture design and demand analysis on application layer of standard system for ubiquitous power Internet of Things

The ubiquitous power Internet of Things(UPIoT)is an intelligent service system with comprehensive state perception,efficient processing,and flexible application of information.It focuses on each link of the power system and makes full use of the mobile internet,artificial intelligence,and other advanced information and communication technologies in order to realize the inter-human interaction of all things in all links of the power system.This article systematically presents to the national and international organizations and agencies in charge of UPIoT layer standardization the status quo of the research on the Internet of Things(IoT)-related industry standards system.It briefly describes the generic standard classification methods,layered architecture,conceptual model,and system tables in the UPIoT application layer.Based on the principles of inheritance,innovation,and practicability,this study divides the application layer into customer service,power grid operation,integrated energy,and enterprise operation,emerging business and analyzes the standard requirements of these five fields.This study also proposes a standard plan.Finally,it summarizes the research report and provides suggestions for a follow-up work.

Structural optimization strategy of pipe isolation tool by dynamic plugging process analysis

During the pipeline plugging process,both the pipeline and the pipe isolation tool(PIT)will be greatly damaged,due to the violent vibration of the flow field.In this study,it was proposed for the first time to reduce the vibration of the flow field during the plugging process by optimizing the surface structure of the PIT.Firstly,the central composite design(CCD)was used to obtain the optimization schemes,and the drag coefficient and pressure coefficient were proposed to evaluate the degree of flow field changes.Secondly,a series of computational fluid dynamics(CFD)simulations were performed to obtain the drag coefficient and pressure coefficient during dynamic plugging.And the mathematical model of drag coefficient and pressure coefficient with the surface structure of the PIT were established respectively.Then,a modified particle swarm optimization(PSO)was applied to predict the optimal value of the surface structure of the PIT.Finally,an experimental rig was built to verify the effectiveness of the optimization.The results showed that the improved method could reduce the flow field vibration by 49.56%.This study provides a reference for the design of the PIT surface structure for flow field vibration technology.

Test Analysis of Traction Battery Peak Power

The test process of electric vehicles (EVs) traction battery peak power is analyzed in detail. Aimed at a special “traction” design of versatile battery—HORIZON~ C~2M Battery, the features are introduced. According to the peak power test schedule, the test parameters of HORIZON~ C~2M Battery are calculated and the charging and discharging experiments are carried out. The sustained (30 s) discharge power capability of battery at 2/3 of its open circuit voltage at each of various depths of discharge is determined. The dynamic internal resistance under peak power test is established. Considering the temperature impact during discharging, the peak power capability at each of various depths of discharge is corrected. The correctness of peak power test is validated by combining theory analysis with test results.

Research on energy storage capacity configuration for PV power plants using uncertainty analysis and its applications

Compensating for photovoltaic(PV)power forecast errors is an important function of energy storage systems.As PV power outputs have strong random fluctuations and uncertainty,it is difficult to satisfy the grid-connection requirements using fixed energy storage capacity configuration methods.In this paper,a method of configuring energy storage capacity is proposed based on the uncertainty of PV power generation.A k-means clustering algorithm is used to classify weather types based on differences in solar irradiance.The power forecast errors in different weather types are analyzed,and an energy storage system is used to compensate for the errors.The kernel density estimation is used to fit the distributions of the daily maximum power and maximum capacity requirements of the energy storage system;the power and capacity of the energy storage unit are calculated at different confidence levels.The optimized energy storage configuration of a PV plant is presented according to the calculated degrees of power and capacity satisfaction.The proposed method was validated using actual operating data from a PV power station.The results indicated that the required energy storage can be significantly reduced while compensating for power forecast errors.