薛福成的人才观

薛福成是近代早期改良派重要人物，他的人才观是他改良思想的重要内容。他对科举制度的选拔人才进行彻底批判，认为它选拔不出人才。主张人才选拔要有时务性，主张征辟、搜访幽隐，并设特科在大政事、大谋议等关键时刻选拔人才．同要在平时多设学堂，多选学生，并出洋留学，加强对人才的培养．这种人才观，布新除旧，在中国近代史上具有重要的历史价值．

DIV： Dynamic Integrity Validation Framework for Detecting Compromises on Virtual Machine Based Cloud Services in Real Time

with the increasing popularity of cloud services,attacks on the cloud infrastructure also increase dramatically.Especially,how to monitor the integrity of cloud execution environments is still a difficult task.In this paper,a real-time dynamic integrity validation(DIV) framework is proposed to monitor the integrity of virtual machine based execution environments in the cloud.DIV can detect the integrity of the whole architecture stack from the cloud servers up to the VM OS by extending the current trusted chain into virtual machine's architecture stack.DIV introduces a trusted third party(TTP) to collect the integrity information and detect remotely the integrity violations on VMs periodically to avoid the heavy involvement of cloud tenants and unnecessary information leakage of the cloud providers.To evaluate the effectiveness and efficiency of DIV framework,a prototype on KVM/QEMU is implemented,and extensive analysis and experimental evaluation are performed.Experimental results show that the DIV can efficiently validate the integrity of files and loaded programs in real-time,with minor performance overhead.

Application of predictive control scheduling method to real-time periodic control tasks overrun

Based on the abort strategy of fixed periods, a novel predictive control scheduling methodology was proposed to efficiently solve overrun problems. By applying the latest control value in the prediction sequences to the control objective, the new strategy was expected to optimize the control system for better performance and yet guarantee the schedulability of all tasks under overrun. The schedulability of the real-time systems with p-period overruns was analyzed, and the corresponding stability criteria was given as well. The simulation results show that the new approach can improve the performance of control system compared to that of conventional abort strategy, it can reduce the overshoot and adjust time as well as ensure the schedulability and stability.

Self-Organizing Mechanism for Cloud Services and Performance Analysis

To improve the performance and robustness in service discovery, a self-organizing mechanism for service alliances of Service Providers (SPs) is proposed in this paper. According to the similarity of service content, an SP publishes its services in a partition of SPs to construct connections between highly similar SPs. These SPs constitute a self-organized distributed environment. A self-organizing protocol is designed to ensure the correctness of the construction of the alliances. The protocol consists of four stages - initiating stage, developing stage, developed stage and degradation stage. The experimental results demonstrate that this protocol ensures the self-property. The visualization of alliance developing stages illustrates that sub-alliances are sp lit in balance and self-connected. Compared with the Random Walker algorithm, the time cost and the number of forwarded messages in alliance-based mechanism is lower in service discovery. On three typical topologies (Grid, Random-Graph, Power-Law), the success rate of service discovery is much higher, which shows that self-organized alliances are helpful to enhance the discovery performance.

Network Reliability Analysis of Digital Instrument and Control System with GO-FLOW Methodology

In this paper,the network reliability of an actual digital instrument and control system (DICS) network is analyzed by using GO-FLOW methodology (GFM).The evaluations of common-cause failure (CCF) and uncertainty are incorporated.Three significant CCF groups (real time servers,gateways,reactor protection system) and three typical time intervals (10 min,1 h,and 24 h) are selected in the analysis.It is concluded that the network contribution of CCF accounts for over 68% of the system failure probability.The result indicates that GFM is suitable for the network reliability analysis.

Research on the High Robustness JavaEE Enterprise Development Mode based on Hadoop and Cloud Servers

In this paper, we conduct research on the high robustness JavaEE enterprise development mode based on Hadoop and cloud servers. The current virtual machine real-time migration can only achieve manual migration, and cannot achieve full-automatic migration. In other words, when the server overload requires the administrator to artificially select a low-load host, and then hit migration command to implement the migration. In recent years, the Hadoop is becoming popular, and the read performance of the data is measured in terms of the time overhead for reading the required data. The key to reducing read time is to optimize that Hadoop cloud data read time and the RDBMS data query time. This paper integrates the mentioned techniques to construct the novel JavaEE enterprise development pattern that will promote the further development of the related techniques.

Temporal consistency maintenance on multiprocessor platforms with instance skipping

Maintaining temporal consistency of real-time data is important for cyber-physical systems.Most of the previous studies focus on uniprocessor systems.In this paper,the problem of temporal consistency maintenance on multiprocessor platforms with instance skipping was formulated based on the(m,k)-constrained model.A partitioned scheduling method SC-AD was proposed to solve the problem.SC-AD uses a derived sufficient schedulability condition to calculate the initial value of m for each sensor transaction.It then partitions the transactions among the processors in a balanced way.To further reduce the average relative invalid time of real-time data,SC-AD judiciously increases the values of m for transactions assigned to each processor.Experiment results show that SC-AD outperforms the baseline methods in terms of the average relative invalid time and the average valid ratio under different system workloads.

Analysis on traffic characteristics and transmission efficiency of instant messager services

Traffic characteristics of several typical instant messager services under certain scenarios are firstly analyzed,based on real-time data collected in the commercial mobile network.Then criteria for the evaluation of the efficiency of the mobile network for the transmission of packet services are proposed in both transport layer and physical layer over air interface.The transmission efficiency of IM services is evaluated and compared under the proposed criteria.Furthermore,a so-called smart resource adaptation algorithm is verified in the effectiveness of improving the wireless transmission efficiency.Finally,improvements to the smart resource adaptation are proposed to further improve the wireless transmission efficiency,and its effectiveness is verified by the calculations.

Fortified Financial Forecasting Models Based on Non-Linear Searching Approaches

The paper＇s aim is how to forecast data with variations involving at times series data to get the best forecasting model. When researchers are going to forecast data with variations involving at times series data （i.e., secular trends, cyclical variations, seasonal effects, and stochastic variations）, they believe the best forecasting model is the one which realistically considers the underlying causal factors in a situational relationship and therefore has the best ＂track records＂ in generating data. Paper＇s models can be adjusted for variations in related a time series which processes a great deal of randomness, to improve the accuracy of the financial forecasts. Because of Na＇fve forecasting models are based on an extrapolation of past values for future. These models may be adjusted for seasonal, secular, and cyclical trends in related data. When a data series processes a great deal of randomness, smoothing techniques, such as moving averages and exponential smoothing, may improve the accuracy of the financial forecasts. But neither Na＇fve models nor smoothing techniques are capable of identifying major future changes in the direction of a situational data series. Hereby, nonlinear techniques, like direct and sequential search approaches, overcome those shortcomings can be used. The methodology which we have used is based on inferential analysis. To build the models to identify the major future changes in the direction of a situational data series, a comparative model building is applied. Hereby, the paper suggests using some of the nonlinear techniques, like direct and sequential search approaches, to reduce the technical shortcomings. The final result of the paper is to manipulate, to prepare, and to integrate heuristic non-linear searching methods to serve calculating adjusted factors to produce the best forecast data.

RELIABILITY INDICES OF DISCRETE-TIME Geo^X/G/1 QUEUEING SYSTEM WITH UNRELIABLE SERVICE STATION AND MULTIPLE ADAPTIVE DELAYED VACATIONS

This paper considers the discrete-time GeoX/G/1 queueing model with unreliable service station and multiple adaptive delayed vacations from the perspective of reliability research. Following problems will be discussed： 1） The probability that the server is in a ＂generalized busy period＂ at time n; 2） The probability that the service station is in failure at time n, i.e., the transient unavailability of the service station, and the steady state unavailability of the service station; 3） The expected number of service station failures during the time interval （0, hi, and the steady state failure frequency of the service station; 4） The expected number of service station breakdowns in a server＇s ＂generalized busy period＂. Finally, the authors demonstrate that some common discrete-time queueing models with unreliable service station are special cases of the model discussed in this paper.

Delimiting Ecological Space and Simulating Spatial-temporal Changes in Its Ecosystem Service Functions based on a Dynamic Perspective: A Case Study on Qionglai City of Sichuan Province, China

Delimiting ecological space scientifically and making reasonable predictions of the spatial-temporal trend of changes in the dominant ecosystem service functions(ESFs) are the basis of constructing an ecological protection pattern of territorial space, which has important theoretical significance and application value. At present, most research on the identification, functional partitioning and pattern reconstruction of ecological space refers to the current ESFs and their structural information, which ignores the spatial-temporal dynamic nature of the comprehensive and dominant ESFs, and does not seriously consider the change simulation in the dominant ESFs of the future ecological space. This affects the rationality of constructing an ecological space protection pattern to some extent. In this study, we propose an ecological space delimitation method based on the dynamic change characteristics of the ESFs, realize the identification of the ecological space range in Qionglai City and solve the problem of ignoring the spatial-temporal changes of ESFs in current research. On this basis, we also apply the Markov-CA model to integrate the spatial-temporal change characteristics of the dominant ESFs, successfully realize the simulation of the spatial-temporal changes in the dominant ESFs in Qionglai City’s ecological space in 2025, find a suitable method for simulating ecological spatial-temporal changes and also provide a basis for constructing a reasonable ecological space protection pattern. This study finds that the comprehensive quantity of ESF and its annual rate of change in Qionglai City show obvious dynamics, which confirms the necessity of considering the dynamic characteristics of ESFs when identifying ecological space. The areas of ecological space in Qionglai city represent 98307 ha by using the ecological space identification method proposed in this study, which is consistent with the ecological spatial distribution in the local ecological civilization construction plan. This confirms the reliability of the ecological space identification method based on the dynamic characteristics of the ESFs. The results also show that the dominant ESFs in Qionglai City represented strong non-stationary characteristics during 2003–2019,which showed that we should fully consider the influence of the dynamics in the dominant ESFs on the future ESF pattern during the process of constructing the ecological spatial protection pattern. The Markov-CA model realized the simulation of spatial-temporal changes in the dominant ESFs with a high precision Kappa coefficient of above 0.95, which illustrated the feasibility of using this model to simulate the future dominant ESF spatial pattern. The simulation results showed that the dominant ESFs in Qionglai will still undergo mutual conversions during 2019–2025 due to the effect of the their non-stationary nature. The ecological space will still maintain the three dominant ESFs of primary product production, climate regulation and hydrological regulation in 2025, but their areas will change to 32793 ha, 52490 ha and 13024 ha, respectively. This study can serve as a scientific reference for the delimitation of the ecological conservation redline, ecological function regionalization and the construction of an ecological spatial protection pattern.