适用于无线体域网的动态口令认证协议

无线体域网中传输的是与生命高度相关的敏感数据，身份认证是信息安全保护的第一道防线。现有的基于人体生物信息的身份认证方案存在信息难提取、偶然性大和误差性大的问题，基于传统密码学的认证方案需较大计算资源和能量消耗，并不适用于无线体域网环境。为此，在动态口令和非对称加密机制基础上，提出一种适用于无线体域网的动态口令双向认证轻量协议，并对其进行形式化分析。通过理论证明、SVO逻辑推理及SPIN模型检测得出：该协议满足双向认证，且能够抵御重放攻击、伪装攻击、拒绝服务器攻击和口令离线攻击，具有较高安全性。     

Co-creation of value and the project context: Towards application on the case of Hinkley Point C Nuclear Power Station

The research analyses decisions as evaluative outcomes regarding project value. The UK-French Hinkley Point C Nuclear Power Station provides the case study. Value is traditionally assessed as inputs and outputs. Here, value is conceptualized as a co-created value proposition at the front-end with implications for realization post-completion. Service-dominant logic (SDL) provides the theoretical lens and contributes to a methodological approach for examining projects. Decision-making outcomes provide the evidence from a range of data sources, including reports and commentaries. The methods are interpretative. The findings show that decision-making extends beyond the time-cost-quality/scope dimensions. The long-term issues regarding value realized are often overlooked. Stakeholders and individual actors have mainly focused upon managing political and financial risks, especially time and cost. The research poses challenges to project management analysis, SDL and research design in assessing evidence. Addressing these issues facilitates a knowledge contribution to SDL theorization and the field of project management.     

All two-input logic gates by a single-stage single electron box

In this paper, the design of all two-input logic gates is presented by only a single-stage single electron box (SEB) for the first time. All gates are constructed based on a same circuit. We have used unique periodic characteristics of SEB to design these gates and present all two-input logic gates (monotonic/non-monotonic, symmetric/non-symmetric) by a single-stage design. In conventional monotonic devices, such as MOSFETs, implementing non-monotonic logic gates such as XOR and XNOR is impossible by only a single-stage design, and a multistage design is required which leads to more complexity, higher power consumption and less speed of the gates. We present qualitative design at first and then detailed designs are investigated and optimised by using our previous works. All designs are verified by a single electron simulator which shows correct operation of the gates.     

准噶尔盆地南缘四棵树地区中浅层砾岩层识别刻画

准噶尔盆地南缘中、下组合构造普遍位于中浅层砾岩层之下,砾岩层具有横向展布范围广且不规则、纵横向速度变化大等特点,严重制约中、下组合目标的精细落实。因此,搞清砾岩层结构及分布特征,对下伏构造形态和高点位置的准确落实尤为重要。结合微测井、钻井、测井资料以及地震剖面对准噶尔盆地南缘四棵树地区中浅层砾岩层结构特征进行分析,对低速和高速砾岩层的顶底界面进行识别刻画,并分区、分段建立了砾岩层时深关系曲线,用于指导深度域下组合构造成图和叠前深度偏移中浅层速度模型的建立。实例应用证明,南缘四棵树地区中浅层砾岩层识别刻画对准确落实构造目标,提高地震剖面成像品质至关重要,同样也可以在准噶尔盆地南缘其他类似地区进行推广应用。     

基于Stateflow电力机车变流器控制设计与实现

某出口型号交流电力机车牵引控制系统要求变流器控制逻辑具备接触器控制、牵引系统数据交互、变流器故障保护、变流器启动自检等功能。针对以上功能,基于MATLAB中的Simulink/Stateflow可视化编程工具进行牵引控制模型的搭建,遵循模块化编程理念,采用较少的程序代码编写实现复杂的逻辑控制模型,生成逻辑清晰的控制功能流程图,进行半实物仿真测试,增强控制模型的可靠性。通过该变流器产品型式试验检验,验证变流器控制逻辑的功能可以满足控制系统的需求。     

Actuator fault tolerant control using adaptive RBFNN fuzzy sliding mode controller for coaxial octorotor UAV

In this paper, a robust controller for a Six Degrees of Freedom (6 DOF) coaxial octorotor helicopter control is proposed in presence of actuator faults. Radial Base Function Neural Network (RBFNN), Fuzzy Logic Control approach (FLC) and Sliding Mode Control (SMC) technique are used to design a controller, named Fault Tolerant Control (FTC), for each subsystem of the octorotor helicopter. The proposed FTC scheme allows avoiding difficult modeling, attenuating the chattering effect of the SMC, reducing the rules number of the fuzzy controller, and guaranteeing the stability and the robustness of the system. The simulation results show that the proposed FTC can greatly alleviate the chattering effect, good tracking in presence of actuator faults.     

重新找回人工智能的可解释性

针对深度神经网络AI研究的可解释性瓶颈，指出刚性逻辑（数理形式逻辑）和二值神经元等价，二值神经网络可转换成逻辑表达式，有强可解释性。深度神经网络一味增加中间层数来拟合大数据，没有适时通过抽象把最小粒度的数据（原子）变成粒度较大的知识（分子），再把较小粒度的知识变成较大粒度的知识，把原有的强可解释性淹没在中间层次的汪洋大海中。要支持多粒度的知识处理，需把刚性逻辑扩张为柔性命题逻辑（命题级数理辩证逻辑），把二值神经元扩张为柔性神经元，才能保持强可解释性。本文详细介绍了从刚性逻辑到柔性逻辑的扩张过程和成果，最后介绍了它们在AI研究中的应用，这是重新找回AI研究强可解释性的最佳途径。