Robust Deadlock Avoidance Policy for Automated Manufacturing System With Multiple Unreliable Resources

This work studies the robust deadlock control of automated manufacturing systems with multiple unreliable resources. Our goal is to ensure the continuous production of the jobs that only require reliable resources. To reach this goal, we propose a new modified Banker's algorithm(MBA) to ensure that all resources required by these jobs can be freed. Moreover,a Petri net based deadlock avoidance policy(DAP) is introduced to ensure that all jobs remaining in the system after executing the new MBA can complete their processing smoothly when their required unreliable resources are operational. The new MBA together with the DAP forms a new DAP that is robust to the failures of unreliable resources. Owing to the high permissiveness of the new MBA and the optimality of the DAP, it is tested to be more permissive than state-of-the-art control policies.

Multi-Layer Reconstruction Errors Autoencoding and Density Estimate for Network Anomaly Detection

Anomaly detection is an important method for intrusion detection.In recent years,unsupervised methods have been widely researched because they do not require labeling.For example,a nonlinear autoencoder can use reconstruction errors to attain the discrimination threshold.This method is not effective when the model complexity is high or the data contains noise.The method for detecting the density of compressed features in a hidden layer can be used to reduce the influence of noise on the selection of the threshold because the density of abnormal data in hidden layers is smaller than normal data.However,compressed features may lose some of the high-dimensional distribution information of the original data.In this paper,we present an efficient anomaly detection framework for unsupervised anomaly detection,which includes network data capturing,processing,feature extraction,and anomaly detection.We employ a deep autoencoder to obtain compressed features and multi-layer reconstruction errors,and feeds them the same to the Gaussian mixture model to estimate the density.The proposed approach is trained and tested on multiple current intrusion detection datasets and real network scenes,and performance indicators,namely accuracy,recall,and F1-score,are better than other autoencoder models.

Mortgage of Land Management Right in the Rural Area Under the Policy Context

The aim of this study is to explore the necessity to consider the specialty of policy context in ethnic minority area during the policymaking process.Case analysis is applied to study the policy context in microscopic aspect.The information came from two sources:questionnaires or phone calls,and related documents.Study suggested that the mortgage of land management lies in the negligence of temporal dynamic balance when it comes to the mastering of policy context.Optimal plan of method design was given in the end of this paper.

＂Cold Shoulder＂ Experience of Farmland Property Right Mortgage--Based on the questionnaire of 1250 households in Jiangxi Province

Rural households field questionnaire survey found that current promotion pilot of agricultural property mortgage loan policy suffered the "cold shoulder" experience, and the analysis on the survey found that agricultural property mortgage loan pilot policy had significant effect on the economy in Jiangxi, which still had improvement space. Loan institutions obviously lack enough trust on the policy, leading in general reluctance to lending, and farmers suffered "loan embarrassing", trust loss, more loan difficulty and loan disdain. Therefore, it suggested that the mortgage policy for rural land property rights should be implemented according to different local conditions, so as to enhance the useful decisions of CPC Central Committee on financial benefits of farmland consolidation results.