云南省高校计算机等级考试的网络收分技术

云南省高校计算机等级考试是由省教育厅主办的全省高校计算机水平考试。该考试只有上机考试,上机考试中考生交卷后要当场评分并收集成绩,传统的单机收分方法效率低、成本高,网络收分存在着不安全和不可靠等问题。本文设计了基于网络的收分技术,改善了网络收分的可靠性和安全性,详细介绍了该技术的实现。

基于网络环境的计算机技能考试系统的设计与实现

介绍了河北省对口招生计算机技能测试考试系统的设计。该系统是一个基于网络环境的无纸化自动评分并实现网络收分的考试系统,采用C/S模式,对系统硬件要求低,软件容易安装,易于考试管理人员使用和管理。该系统在河北省对口招生计能考试中连续使用了2年,考试结果分析表明,考生的成绩分布曲线正常。

Lazy loading algorithm for traffic assignment of road networks under fixed charge condition

The measures of path charge are important considerations in traffic assignment of road networks. Factors, such as travel time, fixed charge and traffic congestion which affect road users＇ choices of trip paths, are analyzed. Travelers usually decide their trip paths based on their personal habits, preferences and the information at hand. By considering both deterministic and stochastic factors which affect the value of time （VOT） during the process of path choosing, a variational inequality model is proposed to describe the problem of traffic assignment. A lazy loading algorithm for traffic assignment is designed to solve the proposed model, and the calculation steps are given. Numerical experiment results show that compared with the all-or-nothing assignment, the proposed model and the algorithm can provide more optimal traffic assignments for road networks. The results of this study can be used to optimize traffic planning and management.

Game theoretic analysis for pricing-based incentive mechanism in non-dedicated cooperative relay networks

In non-dedicated cooperative relay networks, each node is autonomous and selfish in nature, and thus spontaneous cooperation among nodes is challenged. To stimulate the selfish node to participate in cooperation, a pricing-based cooperation engine using game theory was designed. Firstly, the feasible regions of the charge price and reimbursement price were deduced. Then, the non-cooperative and cooperative games were adopted to analyze the amount of bandwidth that initiating cooperation node(ICN) forwards data through participating cooperation node(PCN) and the amount of bandwidth that PCN helps ICN to relay data. Meanwhile, the Nash equilibrium solutions of cooperation bandwidth allocations(CBAs) were obtained through geometrical interpretation. Secondly, a pricing-based cooperation engine was proposed and a cooperative communication system model with cooperation engines was depicted. Finally, an algorithm based on game theory was proposed to realize the cooperation engine. The simulation results demonstrate that, compared with the system without pricing-based incentive, the proposed system can significantly improve the ICN's metric measured by bit-per-Joule and increase the PCN's revenue.

Distribution of primary school based on spatial network comprehensive model in low-income mountainous cities： a case study in Wanyuan, China

Focusing on the peculiarities of urban construction resulting from specific mountain terrains, the purpose of this study is to find out a suitable method based on a Spatial Network Comprehensive Model(SNCM) to reasonably plan and distribute primary schools in low-income mountain cities. The construction principles and advantages of the SNCM method are proposed and the method tested in Wanyuan city of Qinba Mountain area(Southwest China) to verify its feasibility and optimization. Taking account of the mountain terrain and its influence on user behavior, we used the SNCM method to build a comprehensive model which integrates the road slope and the walking speed of pupils into the basic spatial model. The model is used to calculate a reasonable layout of the primary schools and to validate the rationale. The results show that the SNCM method can be effectively applied in low-income mountainous cities. It can not only improve the accessibility and service efficiency of primary schools using as little capital-investment as possible, but also help the city grow in an intensive and efficient way.

A Robust Energy Efficiency Power AllocationAlgorithm in Cognitive Radio Networks

In order to solve the problem that traditional energy efficiency power allocation algorithms usually require the assumption of constant or perfect channel state information in cognitive radio networks(CRNs),which may lead to performance degradation in real systems with disturbances or uncertainties,we propose a robust energy efficiency power allocation algorithm for underlay cognitive radio(CR)systems with channel uncertainty in consideration of interference power threshold constraint and minimum target SINR requirement constraint.The ellipsoid sets are used to describe the channel uncertainty,and a constrained fractional programming for the allocation is transformed to a convex optimization problem by worst-case optimization approach.A simplified version of robust energy efficiency scheme by a substitutional constraint having lower complexity is presented.Simulation results show that our proposed scheme can provide higher energy efficiency compared with capacity maximization algorithm and guarantee the signal to interference plus noise ratio(SINR)requirement of each cognitive user under channel uncertainty.

Dynamic analysis of stochastic delayed cellular neural networks

The stability of stochastic delayed cellular neural networks(DCNNs) is investigated in this paper. Under the help of Lyapunov functional and the semimartingale convergence theorem, some sufficient criteria were obtained to check the almost sure exponential stability of the DCNNs.

Synthesis of flowerlike nickel particles and their microwave absorbing properties

Two kinds of nickel particles with flower-like struc~＇es assembled with a number of nano-flakes were synthesized and the relationship of their morphology and microwave absorbing properties was studied. The electromagnetic parameters of these flower-like Ni were measured with vector network analyzer at 2-18 GHz frequency and the reflection losses （RL） with different sample thicknesses were calculated. The results indicate that the flower-like nickel-wax composites with the sample thickness less than 2 mm show excellent absorbing ability. This result is expected to play a guiding role in the preparation of the highly efficient absorber.

Full Diversity Reception Based on Dempster-Shafer Theory for Network Coding with Multiple-Antennas Relay

In this paper,a two-way relay system which achieves bi-directional communication via a multiple-antenna relay in two time slots is studied.In the multiple access(MA) phase,the novel receive schemes based on Dempster-Shafer(D-S) evidence theory are proposed at the relay node.Instead of traditional linear detection,the first proposed MIMO-DS NC scheme adopts D-S evidence theory to detect the signals of each source node before mapping them into network-coded signal.Moreover,different from traditional physical-layer network coding(PNC) based on virtual MIMO model,the further proposed MIMO-DS PNC comes from the vector space perspective and combines PNC mapping with D-S theory to obtain network-coded signal without estimating each source node signal.D-S theory can appropriately characterize uncertainty and make full use of multiple evidence source information by Dempster's combination rule to obtain reliable decisions.In the broadcast(BC) phase,the space-time coding(STC) and antenna selection(AS) schemes are adopted to achieve transmit diversity.Simulation results reveal that the STC and AS schemes both achieve full transmit diversity in the BC phase and the proposed MIMO-DS NC/PNC schemes obtain better end-to-end BER performance and throughputs compared with traditional schemes with a little complexity increasing and no matter which scheme is adopted in the BC phase,MIMO-DS PNC always achieves full end-to-end diversity gain as MIMO-ML NC but with a lower complexity and its throughput approaches the throughput of MIMO-ML NC in high SNR regime.

Convergence Analysis and Its Application in the Fixed Point Formulation of Medium Access in Wireless Network

In the Internet of things, it is of critical importance to fully utilize the potential capacity of the network with efficient medium access control （MAC） mechanisms. In this paper, we study the convergence property of the fixed point formulation of distributed coordination function （DCF）, which is widely used for medium access control in wireless networks. We first Kind that the fixed point could be repelling, which means that it is impossible for an MAC system to converge at its fixed point. Next, we show the existence of periodic points to prove that the fixed point function will oscillate between two periodic points when the fixed point is repelling. We also find that the average of the two periodic points is a close approximation of the fixed point. Based on the findings, we propose an algorithm to compute the fixed point efficiently. Simulation results verify the accuracy and efficiency of our algorithm compared with the previous fixed point computing method.

A NEW NEURAL NETWORK-BASED ADAPTIVE ILC FOR NONLINEAR DISCRETE-TIME SYSTEMS WITH DEAD ZONE SCHEME

By introducing a deadwzone scheme, a new neural network based adaptive iterative learning control （ILC） （NN-AILC） scheme is presented for nonlinear discrete-time systems, where the NN weights are time-varying. The most distinct contribution of the proposed NN-AILC is the relaxation of the identical conditions of initial state and reference trajectory, which are common requirements in traditional ILC problems. Convergence analysis indicates that the tracking error converges to a bounded ball, whose size is determined by the dead-zone nonlinearity. Computer simulations verify the theoretical results.