Examining the Burden Reduction Policy for Primary and Secondary School Teachers in China:A Framework Analysis Centered on the Rational Selection of Institutional Doctrine

The“burden reduction”policy aims to reduce the workload of primary and secondary school teachers to alleviate their burdens.While it has improved the quality of teachers,implementation challenges still exist.This study utilizes rational choice institutionalism and Ostrom’s institutional analysis and development framework to examine the policy.By considering the preferences of the Ministry of Education,local governments,schools,and teachers,it explores interactions and outcomes,identifies challenges,and provides policy suggestions.

System Reliability Analysis for Truss Structures Based on Automatic Updated Model

Multiple failure modes tend to be identified in the reliability analysis of a redundant truss structure.This identification process involves updating the model for identifying the next potential failure members.Herein we intend to update the finite element model automatically in the identification process of failure modes and further perform the system reliability analysis efficiently.This study presents a framework that is implemented through the joint simulation of MATLAB and APDL and consists of three parts:reliability index of a single member,identification of dominant failure modes,and system-level reliability analysis for system reliability analysis of truss structures.Firstly,RSM(response surface method)combines with a constrained optimization model to calculate the reliability indices ofmembers.Then theβ-unzipping method is adopted to identify the dominant failuremodes,and the system function in MATLAB,as well as the EKILL command in APDL,is used to facilitate the automatic update of the finite element model and realize load-redistribution.Besides,the differential equivalence recursion algorithmis performed to approximate the reliability indices of failuremodes efficiently and accurately.Eventually,the PNET(probabilistic network evaluation technique)is used to calculate the joint failure probability as well as the system reliability index.Two illustrative examples demonstrate the accuracy and efficiency of the proposed system reliability analysis framework through comparison with corresponding references.

A New Framework of Convergence Analysis for Solving the General Nonlinear Schrodinger Equation using the Fourier Pseudo-Spectral Method in Two Dimensions

This paper aims to build a new framework of convergence analysis of conservative Fourier pseudo-spectral method for the general nonlinear Schr¨odinger equation in two dimensions,which is not restricted that the nonlinear term is mere cubic.The new framework of convergence analysis consists of two steps.In the first step,by truncating the nonlinear term into a global Lipschitz function,an alternative numerical method is proposed and proved in a rigorous way to be convergent in the discrete L2 norm;followed in the second step,the maximum bound of the numerical solution of the alternative numerical method is obtained by using a lifting technique,as implies that the two numerical methods are the same one.Under our framework of convergence analysis,with neither any restriction on the grid ratio nor any requirement of the small initial value,we establish the error estimate of the proposed conservative Fourier pseudo-spectral method,while previous work requires the certain restriction for the focusing case.The error bound is proved to be of O(h^(r)+t^(2))with grid size h and time step t.In fact,the framework can be used to prove the unconditional convergence of many other Fourier pseudo-spectral methods for solving the nonlinear Schr¨odinger-type equations.Numerical results are conducted to indicate the accuracy and efficiency of the proposed method,and investigate the effect of the nonlinear term and initial data on the blow-up solution.

Analysing Delay Impact from Potential Risk Factors on Project Delivery of Oil and Gas Pipeline:A Case Study in IRAQ

The aim of this paper is to present the design and specifications of an integrated Delay Analysis Framework(DAF),which could be used to quantify the delay caused by the Risk Factors(RFs)in Oil and Gas Pipelines(OGPs)projects in a simple and systematic way.The main inputs of the DAF are(i)the potential list of RFs in the projects and their impact levels on the projects and the estimated maximum and minimum duration of each task.Monte Carlo Simulation integrated within@Risk simulator was the key process algorithm that used to quantify the impact of delay caused by the associated RFs.The key output of the DAF is the amount of potential delay caused by RFs in the OGP project.The functionalities of the developed DAF were evaluated using a case study of newly developed OGP project,in the south of Iraq.It is found that the case study project might have delayed by 45 days if neglected the consideration of the RFs associated with the project at the construction stage.The paper concludes that identifying the associated RFs and analysing the potential delay in advance will help in reducing the construction delay and improving the effectiveness of the project delivery by taking suitable risk mitigation measures.

Research on Self-Supervised Comparative Learning for Computer Vision

In recent years,self-supervised learning which does not require a large number of manual labels generate supervised signals through the data itself to attain the characterization learning of samples.Self-supervised learning solves the problem of learning semantic features from unlabeled data,and realizes pre-training of models in large data sets.Its significant advantages have been extensively studied by scholars in recent years.There are usually three types of self-supervised learning:"Generative,Contrastive,and GeneTative-Contrastive."The model of the comparative learning method is relatively simple,and the performance of the current downstream task is comparable to that of the supervised learning method.Therefore,we propose a conceptual analysis framework:data augmentation pipeline,architectures,pretext tasks,comparison methods,semisupervised fine-tuning.Based on this conceptual framework,we qualitatively analyze the existing comparative self-supervised learning methods for computer vision,and then further analyze its performance at different stages,and finally summarize the research status of sei supervised comparative learning methods in other fields.

CSRF protection in JavaScript frameworks and the security of JavaScript applications

With JavaScript being the most popular programming language on the web,several new JavaScript frameworks are released every year.A well designed framework may help developers create secure applications.The goal of our study is to understand how framework developers can best protect applications developed using their framework.In this work we studied how cross-site request forgery vulnerability is mitigated in several server-side JavaScript frameworks:Express.js,Koa.js,Hapi.js,Sails.js,and Meteor.js.We then analyzed open source applications developed with these frameworks using open source and custom written tools for automated static analysis and identified the percentage of protected applications for each framework.We correlated our analysis results to the implementation levels of mitigating controls in each framework and performed statistical analysis of our results to ensure no other confounding factors were involved.Based on the received outcomes we provide recommendations for framework developers on how to create frameworks that produce secure applications.

Electrolint and security of electron applications

JavaScript applications today are not limited to just client-side web applications and server-side code powered by Node.js.They became the standard for desktop application development with the emergence and popularity of the Electron framework.Combining the features of client-side and server-side applications,the Electron applications possess a completely different security posture.The attacks typical for front-end applications can now be escalated to the back-end attacks,for example,making a cross-site scripting result in a remote code execution on the user’s machine.The goal of our study is to analyze the typical security vulnerabilities of an Electron application,study common mitigation controls,and propose new remediation solutions that are easy to implement for developers.In this study we analyze security vulnerabilities in over a hundred open source Electron applications using automated and manual static analysis.We explore the mitigation controls existing in the Electron framework,and propose changes to the framework that will prevent many of the common vulnerabilities.Based on these results,we develop an IDE plugin for Electron applications that automatically suggests remediations to common security defects within a developer’s work environment,thus shifting the fixing of a vulnerability to earlier in the software development life cycle.We show the effectiveness of the IDE plugin by applying the plugin’s suggestions to the analyzed open source applications and demonstrating that they stop being exploitable after the applied fix.