改进和声搜索算法的英语考试智能组卷策略

为提升英语考试智能组卷成功率和组卷质量,提出基于改进和声搜索算法的英语考试智能组卷策略.首先建立英语考试智能组卷的目标优化函数,然后采用和声搜索算法对英语考试智能组卷的目标优化函数进行求解,并针对采用声搜索算法的不足进行相应的改进,最后进行了与英语考试智能组卷的应用实例分析.结果表明,改进和声搜索算法的英语考试智能组卷成功率高,而且组卷质量好,同时获得比其它英语考试智能组卷策略更优的结果,具有明显的优越性.     

IMPULP: A Hardware Approach for In-Process Memory Protection via User-Level Partitioning

In recent years many security attacks occur when malicious codes abuse in-process memory resources.Due to the increasing complexity,an application program may call third-party code which cannot be controlled by programmers but may contain security vulnerabilities.As a result,the users have the risk of suffering information leakage and control flow hijacking.However,current solutions like Intel memory protection extensions(MPX)severely degrade performance,while other approaches like Intel memory protection keys(MPK)lack flexibility in dividing security domains.In this paper,we propose IMPULP,an effective and efficient hardware approach for in-process memory protection.The rationale of IMPULP is user-level partitioning that user code segments are divided into different security domains according to their instruction addresses,and accessible memory spaces are specified dynamically for each domain via a set of boundary registers.Each instruction related to memory access will be checked according to its security domain and the corresponding boundaries,and illegal in-process memory access of untrusted code segments will be prevented.IMPULP can be leveraged to prevent a wide range of in-process memory abuse attacks,such as buffer overflows and memory leakages.For verification,an FPGA prototype based on RISC-V instruction set architecture has been developed.We present eight tests to verify the effectiveness of IMPULP,including five memory protection function tests,a test to defense typical buffer overflow,a test to defense famous memory leakage attack named Heartbleed,and a test for security benchmark.We execute the SPEC CPU2006 benchmark programs to evaluate the efficiency of IMPULP.The performance overhead of IMPULP is less than 0.2%runtime on average,which is negligible.Moreover,the resource overhead is less than 5.5%for hardware modification of IMPULP.     

Blaming the client: on data refinement in the presence of pointers

Data refinement is a common approach to reasoning about programs, based on establishing that a concrete program indeed satisfies all the required properties imposed by an intended abstract pattern. Reasoning about programs in this setting becomes complex when use of pointers is assumed and, moreover, a well-known method for proving data refinement, namely the forward simulation method, becomes unsound in presence of pointers. The reason for unsoundness is the failure of the “lifting theorem” for simulations: that a simulation between abstract and concrete modules can be lifted to all client programs. The result is that simulation does not imply that a concrete can replace an abstract module in all contexts. Our diagnosis of this problem is that unsoundness is due to interference from the client programs. Rather than blame a module for the unsoundness of lifting simulations, our analysis places the blame on the client programs which cause the interference: when interference is not present, soundness is recovered. Technically, we present a novel instrumented semantics which is capable of detecting interference between a module and its client. With use of special simulation relations, namely growing relations, and interpreting the simulation method using the instrumented semantics, we obtain a lifting theorem. We then show situations under which simulation does indeed imply refinement.     

Design of observer-based adaptive controller for nonlinear systems with unmodeled dynamics and actuator dead-zone

This paper presents an up-to-date study on the observer-based control problem for nonlinear systems in the presence of unmodeled dynamics and actuator dead-zone. By introducing a dynamic signal to dominate the unmodeled dynamics and using an adaptive nonlinear damping to counter the effects of the nonlinearities and dead-zone input, the proposed observer and controller can ensure that the closed-loop system is asymptotically stable in the sense of uniform ultimate boundedness. Only one adaptive parameter is needed no matter how many unknown parameters there are. The system investigated is more general and there is no need to solve Linear matrix inequality (LMI). Moreover, with our method, some assumptions imposed on nonlinear terms and dead-zone input are relaxed. Finally, simulations illustrate the effectiveness of the proposed adaptive control scheme.     

Goguen命题逻辑系统公理化扩张的Γ-k真度理论及性质

本文首先对n值Goguen命题逻辑进行公理化扩张,Goguen_~,△,记为Π_~,△.利用公式的诱导函数给出公式在k（k任取~或△）连接词下相对于局部有限理论Γ的Γ-k真度的定义;讨论了Π_~,△中Γ-k真度的MP规则、HS规则等相关性质;最后,在Π_~,△中定义了两公式间的Γ-k相似度与Γ-k伪距离,得到了公式在连接词下相对于局部有限理论Γ的Γ-k相似度与Γ-k伪距离所具有的一些良好性质.     

一种递归定义的可扩展片上网络拓扑结构

晶体管工艺的持续发展导致片上处理器数的逐渐增多,片上系统的核间通信要求吞吐量高、延时低、可扩展性好,传统的片上总线和crossbar互连结构已无法满足片上系统的通信需求,为此研究者提出新的片上互连结构,称为片上网络.为满足片上网络的特有通信需求,提出了一种可扩展的拓扑结构Rgrid及其路由算法DR,它缩短了片上处理器间...     

基于动态概率路径事件模型的RFID数据填补算法

RFID 数据采集过程中漏读现象频频发生,降低了RFID(radio frequency identification)应用中查询结果的准确性.目前解决漏读问题的算法主要是以RFID 原始读数为粒度,并基于标签自身历史读数进行窗口平滑,这种作法会填补许多与查询无关的冗余数据,并且在多逻辑区域参与的复杂应用中,填补准确率较差.为解决上述问题,首次将RFID数据从数据层抽象到逻辑区域层作为处理的粒度,提出3 种基于动态概率路径事件模型的数据填补算法,通过挖掘已知的区域事件的顺序相关性来对后续发生的事件进行判断     

Adaptive neural network dynamic surface control for a class of nonlinear systems with uncertain time delays

This paper presents a solution to tracking control problem for a class of nonlinear systems with unknown parameters and uncertain time-varying delays. A new adaptive neural network(NN) dynamic surface controller(DSC) is developed. Some assumptions on uncertain time delays, which were required to be satisfied in previous works, are removed by introducing a novel indirect neural network algorithm into dynamic surface control framework. Also, the designed controller is independent of the time delays. Moreover,the dynamic compensation terms are introduced to facilitate the controller design. It is shown that the closed-loop tracking error converges to a small neighborhood of zero. Finally, a chaotic circuit system is initially bench tested to show the effectiveness of the proposed method.     

基于灰色神经网络的Web社区主题舆情传播模型

Web舆情传播的动态性,不确定性等特征给精确预测舆情传播带来困难．在分析了灰色理论系统的基础上,提出了灰色理论微分方程型模型（GM）和扩展BP神经网络的组合模型,该组合模型综合考虑了网络的结构和传播特性,首先建立灰色理论微分方程型模型,然后映射到扩展的BP神经网络中,通过训练数据来训练该神经网络,使网络具有传播预测能力．仿真实验表明,该组合模型在Web社区主题舆情传播预测精确性方面高于单一的GM模型．     

回收金属破碎机机理的仿真研究

对回收金属破碎机及预压进料系统进行了虚拟设计,利用非线性有限元法,以ANSYS/LS-DYNA为工具,对回收金属破碎过程进行了计算机数值仿真;探讨了非线性问题计算机仿真研究中的沙漏模态(Hourglassmode)控制方法。为回收金属破碎机的设计制造提供了一定的理论依据,文中所述方法具有一定意义。