系统科学研究对象、任务与学科性质探究

以国内外系统科学前沿研究为基础,深入分析系统科学的研究对象、任务和学科性质。研究对象是存在和演化的具体系统中一般意义的关系性特征;研究任务是从发现问题、总结"同型性"、探究"规律性"、解决问题再到发现问题的反馈回路;系统科学具有超越科学性、中立科学性、建构论、弱经验性和问题指向性等特征。     

系统论视野下的动物福利立法——兼谈传统法哲学的演进

本文依据系统哲学的原理进行考察,动物福利立法模式蕴含了清晰而稳妥的理论路径,因而最具现实可行性。在系统哲学、生态文明与和法治建设相互融摄的背景下,加速动物福利立法,同时将弥合传统法哲学的割裂。     

云计算环境中SBS应用动态资源分配方法

建立了一个SBS（基于服务的系统,service based system）应用端到端性能评价模型,并在该模型的基础上提出了SBS应用动态资源分配方法,该方法通过将静态的初始资源分配和动态的资源分配方案调整相结合,能够适应用户访问行为的动态变化,保证SBS应用端到端性能. 在SBS应用动态资源分配问题求解中,提出了服务吞吐量约束确定算法并在此基础上 给出了SBS应用动态资源分配算法,该算法根据SBS应用吞吐量约束确定服务资源需求量并在此基础上通过起始服务 到服务间的转移时间计算服务的资源分配时刻,从而能够在保证SBS应用端到端性能约束的同时提高资源利用率. 实验验证了所提出的基于SBS应用端到端性能评价模型的动态资源分配方法的有效性.     

Self-alignment of full skewed RSINS：observability analysis and full-observable Kalman filter

Traditional orthogonal strapdown inertial navigation sys-tem （SINS） cannot achieve satisfactory self-alignment accuracy in the stationary base： taking more than 5 minutes and al the iner-tial sensors biases cannot get ful observability except the up-axis accelerometer. However, the ful skewed redundant SINS （RSINS） can not only enhance the reliability of the system, but also improve the accuracy of the system, such as the initial alignment. Firstly, the observability of the system state includes attitude errors and al the inertial sensors biases are analyzed with the global perspective method： any three gyroscopes and three accelerometers can be assembled into an independent subordinate SINS （sub-SINS）;the system state can be uniquely confirmed by the coupling connec-tions of al the sub-SINSs;the attitude errors and random constant biases of al the inertial sensors are observable. However, the ran-dom noises of the inertial sensors are not taken into account in the above analyzing process. Secondly, the ful-observable Kalman filter which can be applied to the actual RSINS containing random noises is established; the system state includes the position, ve-locity, attitude errors of al the sub-SINSs and the random constant biases of the redundant inertial sensors. At last, the initial self-alignment process of a typical four-redundancy ful skewed RSINS is simulated： the horizontal attitudes （pitch, rol ） errors and yaw error can be exactly evaluated within 80 s and 100 s respectively, while the random constant biases of gyroscopes and accelero-meters can be precisely evaluated within 120 s. For the ful skewed RSINS, the self-alignment accuracy is greatly improved, mean-while the self-alignment time is widely shortened.     

Spiking neural P systems with anti-spikes and without annihilating priority as number acceptors

Spiking neural P systems with anti-spikes （ASN P systems） are variant forms of spiking neural P systems, which are inspired by inhibitory impulses/spikes or inhibitory synapses. The typical feature of ASN P systems is when a neuron contains both spikes and anti-spikes, spikes and anti-spikes wil immediately annihilate each other in a maximal way. In this paper, a restricted variant of ASN P systems, cal ed ASN P systems without anni-hilating priority, is considered, where the annihilating rule is used as the standard rule, i.e., it is not obligatory to use in the neuron associated with both spikes and anti-spikes. If the annihilating rule is used in a neuron, the annihilation wil consume one time unit. As a result, such systems using two categories of spiking rules （identified by （a, a） and （a,a^-）） can achieve Turing completeness as number accepting devices.     

Codebook design for uplink of densely small cells

The shrinking of cell-size brings significant changes to the wireless uplink of densely small cells （DSCs）. A codebook design is proposed that utilizes the strong line of sight （LOS） chan- nel component existing in a DSC system for uplink of the DSC system. To further improve the uplink performance, the high-rank codebook is designed based on singular value decomposition （SVD） due to the unnecessary preservation of strict constant modulus in the DSC system. And according to the simulation result, the proposed codebook leads to significant sum-rate gain and appreciable block error rate （BLER） performance improvement in the DSC system.     

基于泛函网络的组合推荐算法

在研究组合算法的基础上,提出一种基于泛函网络实现前融合推荐算法. 探讨Vague集条件下推荐算法的前融合问题,给出了基于泛函网络构架实现前融合组合推荐算法的一般过程. 通过推荐系统泛函拓朴结构的建立,利用泛函神经元的自学习、自组织和自适应能力,进一步优化推荐结果,较大地提高了系统的推荐准确度. 最后,将算法应用于Movielens推荐系统中,计算机仿真实验结果表明,本文提出的基于泛函网络实现前融合推荐算法是有效的、可靠的.     

中国高技术产业创新系统协同度

基于复杂系统论的视角,将我国高技术产业创新系统分为创新环境、技术研发、技术吸收、创新产出四个子系统,采用我国高技术产业17个子行业的数据,运用复合系统协同度模型对各行业创新系统的协同度及子系统有序度进行测度。研究发现:我国高技术产业创新系统的协同度整体偏低,其根源在于技术研发、技术吸收两子系统有序度欠佳,各行业间的差距较为显著,同类产业之间相互匹配和支撑性较差。最后,针对性地提出政策建议,以期不断推进我国各产业创新系统的协同发展。     

DDoS主动防御建模仿真研究

建模仿真是研究网络攻防的一种行之有效的手段。在研究DDo S主动防御理论模型的基础上,基于多Agent建模思想建立了DDo S主动防御多Agent模型;基于网络仿真软件OMNe T++建立了DDo S主动防御仿真模型;针对网络仿真软件操作复杂等问题,采用MFC开发工具对OMNe T++进行二次开发,构建了具有友好界面的DDo S主动防御仿真验证演示系统。进行了DDo S攻击与主动防御仿真实验。实验结果证明了所建模型的正确性和仿真验证演示系统的可用性。为进一步研究网络安全仿真提供了模型和平台支持。