Constructing a Triangular Linkage Model of Government Audit,Social Audit,and Internal Audit to Promote High-Quality Development of Audit Services

It is a complex and important topic to study the linkage mechanism of government audit,social audit,and internal audit in the context of China’s high-quality economic development.The implementation of measures,such as establishing a sound and perfect organizational safeguard mechanism,strengthening project collaborative audit mechanism,enhancing the mechanism for utilizing audit results,and establishing an audit and rectification joint mechanism can promote the efficient operation of the audit supervision system and the high-quality development of audit services.

Impact of Government Environmental Audit of the Environmental Performance

Although the deterioration of high pollution and high energy consumption has brought about the economic development,the problem of environmental pollution has also emerged.Therefore,a pow erful means is needed to solve the environmental problems.In this case,the environmental audit as a means of supervision is widely put on the agenda.At present,in terms of environmental audit,the government audit makes up the largest proportion among different kinds of audit like private audit and third-party audit.To carry out the government’s environmental audit work,China’s Audit Commission has proposed a series of environmental remediation and environmental management projects with the special investigation.This paper mainly discussed the effectiveness of the government environmental audit,with the sample of the water pollution control audit of the Yellow River basin.According to the relevant data analysis,the impact of the government environmental audit on environmental quality improvement was explored.

A Research on University Postgraduates＇ Innovation Practice Ability Promotion Strategy

There is no doubt that college postgraduates should improve their ability of innovation practice, keep pace with the times, and strive for realism the innovation, in order to keep up with the development pace of the times. So far, our country postgraduates＇ innovation practice ability is not desirable, which are not completely get rid of the dependence on teachers. For this reason, how to improve postgraduates＇ innovation practice ability become a realistic problem in front of educators in colleges and universities. This paper fries to put forward several strategies of enhancing university postgraduates＇ innovation practice ability.

A Cross Language Code Security Audit Framework Based on Normalized Representation

With the rapid development of information technology,audit objects and audit itself are more and more inseparable from software.As an important means of software security audit,code security audit will become an important aspect of future audit that cannot be ignored.However,the existing code security audit ismainly based on source code,which is difficult to meet the audit needs of more and more programming languages and binary commercial software.Based on the idea of normalized transformation,this paper constructs a cross language code security audit framework(CLCSA).CLCSA first uses compile/decompile technology to convert different highlevel programming languages and binary codes into normalized representation,and then usesmachine learning technology to build a cross language code security audit model based on normalized representation to evaluate code security and find out possible code security vulnerabilities.Finally,for the discovered vulnerabilities,the heuristic search strategy will be used to find the best repair scheme from the existing normalized representation sample library for automatic repair,which can improve the effectiveness of code security audit.CLCSA realizes the normalized code security audit of different types and levels of code,which provides a strong support for improving the breadth and depth of code security audit.

Big Data Analysis of Policy Coordination Paths Based on Latent Dirichlet Allocation Model and Fuzzy-Set Qualitative Comparative Analysis Method

The selection and coordinated application of government innovation policies are crucial for guiding the direction of enterprise innovation and unleashing their innovation potential.However,due to the lengthy,voluminous,complex,and unstructured nature of regional innovation policy texts,traditional policy classification methods often overlook the reality that these texts cover multiple policy topics,leading to lack of objectivity.In contrast,topic mining technology can handle large-scale textual data,overcoming challenges such as the abundance of policy content and difficulty in classification.Although topic models can partition numerous policy texts into topics,they cannot analyze the interplay among policy topics and the impact of policy topic coordination on enterprise innovation in detail.Therefore,we propose a big data analysis scheme for policy coordination paths based on the latent Dirichlet allocation(LDA)model and the fuzzyset qualitative comparative analysis(fsQCA)method by combining topic models with qualitative comparative analysis.The LDA model was employed to derive the topic distribution of each document and the word distribution of each topic and enable automatic classi-fication through algorithms,providing reliable and objective textual classification results.Subsequently,the fsQCA method was used to analyze the coordination paths and dynamic characteristics.Finally,experimental analysis was conducted using innovation policy text data from 31 provincial-level administrative regions in China from 2012 to 2021 as research samples.The results suggest that the proposed method effectively partitions innovation policy topics and analyzes the policy configuration,driving enterprise innovation in different regions.

Machine learning and human‐machine trust in healthcare:A systematic survey

As human‐machine interaction(HMI)in healthcare continues to evolve,the issue of trust in HMI in healthcare has been raised and explored.It is critical for the development and safety of healthcare that humans have proper trust in medical machines.Intelligent machines that have applied machine learning(ML)technologies continue to penetrate deeper into the medical environment,which also places higher demands on intelligent healthcare.In order to make machines play a role in HMI in healthcare more effectively and make human‐machine cooperation more harmonious,the authors need to build good humanmachine trust(HMT)in healthcare.This article provides a systematic overview of the prominent research on ML and HMT in healthcare.In addition,this study explores and analyses ML and three important factors that influence HMT in healthcare,and then proposes a HMT model in healthcare.Finally,general trends are summarised and issues to consider addressing in future research on HMT in healthcare are identified.

Robust Principal Component Analysis Integrating Sparse and Low-Rank Priors

Principal Component Analysis (PCA) is a widely used technique for data analysis and dimensionality reduction, but its sensitivity to feature scale and outliers limits its applicability. Robust Principal Component Analysis (RPCA) addresses these limitations by decomposing data into a low-rank matrix capturing the underlying structure and a sparse matrix identifying outliers, enhancing robustness against noise and outliers. This paper introduces a novel RPCA variant, Robust PCA Integrating Sparse and Low-rank Priors (RPCA-SL). Each prior targets a specific aspect of the data’s underlying structure and their combination allows for a more nuanced and accurate separation of the main data components from outliers and noise. Then RPCA-SL is solved by employing a proximal gradient algorithm for improved anomaly detection and data decomposition. Experimental results on simulation and real data demonstrate significant advancements.

Low-Rank Multi-View Subspace Clustering Based on Sparse Regularization

Multi-view Subspace Clustering (MVSC) emerges as an advanced clustering method, designed to integrate diverse views to uncover a common subspace, enhancing the accuracy and robustness of clustering results. The significance of low-rank prior in MVSC is emphasized, highlighting its role in capturing the global data structure across views for improved performance. However, it faces challenges with outlier sensitivity due to its reliance on the Frobenius norm for error measurement. Addressing this, our paper proposes a Low-Rank Multi-view Subspace Clustering Based on Sparse Regularization (LMVSC- Sparse) approach. Sparse regularization helps in selecting the most relevant features or views for clustering while ignoring irrelevant or noisy ones. This leads to a more efficient and effective representation of the data, improving the clustering accuracy and robustness, especially in the presence of outliers or noisy data. By incorporating sparse regularization, LMVSC-Sparse can effectively handle outlier sensitivity, which is a common challenge in traditional MVSC methods relying solely on low-rank priors. Then Alternating Direction Method of Multipliers (ADMM) algorithm is employed to solve the proposed optimization problems. Our comprehensive experiments demonstrate the efficiency and effectiveness of LMVSC-Sparse, offering a robust alternative to traditional MVSC methods.

Global Value Chain Restructuring:Challenges,Opportunities and Strategies for China

Global value chains(GVCs)have entered a new stage of restructuring characterized by trends towards localization,regionalization and diversification.These trends can be attributed to the evolution of the international division,irrational responses to crisis shocks,and trade protectionism.In this context,China’s industrial and supply chain upgrades face both opportunities and challenges which require navigating the adverse effects of industrial re-shoring,unfair technology competition,and changes in the global industrial layout.Yet,such challenges may create pressures for China to accelerate innovation,overcome the low-end lock-up effect by creating regional value chains,and broaden international cooperation.China needs to explore an effective strategy to defuse risks and seize opportunities.On one hand,China should influence the restructuring of GVCs evolution and strengthen its supply chains by playing an active role in economic globalization and the international division.On the other hand,China should proactively respond to GVCs restructuring amid rising trade protectionism,defuse risks from trade protectionism by opening wider to the outside world,and strive to upgrade industrial and supply chains while enhancing the security and stability of their nation.

Covert Communication with a Spectrum Sharing Relay in the Finite Blocklength Regime

In this paper,we investigate the feasibility and performance of the covert communication with a spectrum sharing relay in the finite blocklength regime.Specifically,the relay opportunistically forwards the source's messages to the primary receiver or conveys the covert messages to its own receiver via the sharing spectrum,while the warden attempts to detect the transmission.First,we derive a lower bound on the covertness constraint,and the analytical expressions of both the primary average effective covert throughput(AECT)and sum AECT are presented by considering the overall decoding error performance.Then,we formulate two optimization problems to maximize the primary and sum AECT respectively by optimizing the blocklength and the transmit power at the source and the relay.Our examinations show that there exists an optimal blocklength to maximize the primary and sum AECT.Besides,it is revealed that,to maximize the primary AECT,the optimal transmit power of each hop increases as its channel quality deteriorates.Furthermore,in the optimization for maximizing the sum AECT,the optimal transmit power at the source equals to zero when the channel quality from relay to the secondary receiver is not weaker than that from relay to the primary receiver.

POWER VARIATION OF SUBFRACTIONAL BROWNIAN MOTION AND APPLICATION

In this paper, we consider the power variation of subfractional Brownian mo- tion. As an application, we introduce a class of estimators for the index of a subfractional Brownian motion and show that they are strongly consistent.

The Postdoctoral System Research from the Perspective of Innovation

2015 is the 30th anniversary of the establishment of China’s postdoctoral system and the first year of the'deep implementation of innovation-driving development strategy'proposed by the Central Committee of the Communist Party of China,and the necessity and urgency of focusing on the postdoctoral work has been studied in the view point of innovation in order to better carry out the innovation-driving development strategy and analyze the role and function of the postdoctoral system in the innovative talent training and scientific&technological development.In combination with the research and practice of postdoctoral management,the thinking and advice are given at the policy level of improving the postdoctoral work.

Information Flow Security Models for Cloud Computing

Cloud computing provides services to users through Internet.This open mode not only facilitates the access by users,but also brings potential security risks.In cloud computing,the risk of data leakage exists between users and virtual machines.Whether direct or indirect data leakage,it can be regarded as illegal information flow.Methods,such as access control models can control the information flow,but not the covert information flow.Therefore,it needs to use the noninterference models to detect the existence of illegal information flow in cloud computing architecture.Typical noninterference models are not suitable to certificate information flow in cloud computing architecture.In this paper,we propose several information flow models for cloud architecture.One model is for transitive cloud computing architecture.The others are for intransitive cloud computing architecture.When concurrent access actions execute in the cloud architecture,we want that security domain and security domain do not affect each other,that there is no information flow between security domains.But in fact,there will be more or less indirect information flow between security domains.Our models are concerned with how much information is allowed to flow.For example,in the CIP model,the other domain can learn the sequence of actions.But in the CTA model,the other domain can’t learn the information.Which security model will be used in an architecture depends on the security requirements for that architecture.

The impact of carbon emission trading policy on firms’green innovation in China

This study aims to examine the green innovation effect of the carbon emissions pilot policy in China.First,using the difference-in-differences method and regressions of instrumental variables using the data from Chinese listed firms,we verify that the policy promotes green innovation among regulated firms and is more pronounced among state-owned enterprises,firms in the eastern region,and those with lower financing constraints.Furthermore,this positive effect spreads downstream relative to the regulated firms through input–output linkages,but reduces green innovation to upstream firms.Accordingly,such diffusion of innovation is achieved through the price mechanism.The results necessitate the introduction of various derivatives to mobilize the market to reduce the speculative volatility of carbon prices.In addition,relevant supporting policies must be established to encourage corporate innovation to reduce the crowding-out effect owing to emission reduction and the nonmarket factors.

Further Results of Meromorphic Functions that Share a Polynomial

In this paper,we use the theory of value distribution and study the uniqueness of meromorphic functions.We will prove the following result:Let f(z)and g(z)be two transcendental meromorphic functions,p(z)a polynomial of degree k,n≥max{11,k+1}a positive integer.If fn(z)f(z)and gn(z)g(z)share p(z)CM,then either f(z)=c1ec p(z)dz, g(z)=c2e ?c p(z)dz ,where c1,c2 and c are three constants satisfying(c1c2) n+1 c2=-1 or f(z)≡tg(z)for a constant t such that tn+1=1.

Numericals for total variation-based reconstruction of motion blurred images

In this paper image with horizontal motion blur, vertical motion blur and angled motion blur are considered. We construct several difference schemes to the highly nonlinear term △↓.（△↓u/√｜△↓｜^2＋β） of the total variation-based image motion deblurring problem. The large nonlinear system is linearized by fixed point iteration method. An algebraic multigrid method with Krylov subspace acceleration is used to solve the corresponding linear equations as in [7]. The algorithms can restore the image very well. We give some numerical experiments to demonstrate that our difference schemes are efficient and robust.

STOCHASTIC HEAT EQUATION WITH FRACTIONAL LAPLACIAN AND FRACTIONAL NOISE:EXISTENCE OF THE SOLUTION AND ANALYSIS OF ITS DENSITY

In this paper we study a fractional stochastic heat equation on Rd （d 〉 1） with additive noise /t u（t, x） = Dα/δ u（t, x）＋ b（u（t, x） ） ＋ WH （t, x） where D α/δ is a nonlocal fractional differential operator and W H is a Gaussian-colored noise. We show the existence and the uniqueness of the mild solution for this equation. In addition, in the case of space dimension d = 1, we prove the existence of the density for this solution and we establish lower and upper Gaussian bounds for the density by Malliavin calculus.

Global behavior of dynamical agents in directed network

This paper investigates the global behavior of controlled dynamical agents in directed networks. The agents are Lyapunov stable, are distributed in a line, and communicate through a directed network. The communication topology of the network is characterized by a directed graph and the control protocol is designed in simple linear decentralized feedback law. We study the different conditions under which agents will achieve aggregation, and critical and divergent trajectories, respectively. Our investigation on the dynamical agent system under network is extended to the time-delay network case. Furthermore, we study the case with two pre-specified virtual leaders in the system. Numerical simulations are given and demonstrate that our theoretical results are effective.

On the generalized risk measures

In this paper, new risk measures are introduced, tation results are also given. These newly introduced risk introduced by Song and Yan （2009） and Karoui （2009）. and the corresponding represen- measures are extensions of those

α-times Integrated Cosine Operator Functions with Growth ω

For a continuous,increasing functionω:[0,∞)→C of finite exponential type,we establish a Hille-Yosida type theorem for strongly continuous α-times(α>0)integrated cosine operator functions with O(ω).It includes the corresponding results for n-times integrated cosine operator functions that are polynomially bounded and exponentially bounded.