Provable secure identity based generalized signcryption scheme

According to actual needs, a generalized signcryption scheme can flexibly work as an encryption scheme, a signature scheme or a signcryption scheme. In this paper, firstly, we give a security model for identity based generalized signcryption which is more complete than the existing model. Secondly, we propose an identity based generalized signcryption scheme. Thirdly, we give the security proof of the new scheme in this complete model. Compared with existing identity based generalized signcryption, the new scheme has less implementation complexity. Moreover, the new scheme has comparable computation complexity with the existing normal signcryption schemes.     

Active time scheduling for rechargeable sensor networks

Recent progress in energy harvesting technologies made it possible to build sensor networks with rechargeable nodes which target an indefinitely long operation. In these networks, the goal of energy management is to allocate the available energy such that the important performance metrics, such as the number of detected threats, are maximized. As the harvested energy is not sufficient for continuous operation, the scheduling of the active and inactive time is one of the main components of energy management. The active time scheduling protocols need to maintain the energy equilibrium of the nodes, while considering the uncertainties of the energy income, which is strongly influenced by the weather, and the energy expenditures, which are dependent on the behavior of the targets. In this paper, we describe and experimentally compare three active time scheduling protocols: (a) static active time, (b) dynamic active time based on a multi-parameter heuristic and (c) utility-based uniform sensing. We show that protocols which take into consideration the probabilistic models of the energy income and expenditure and can dynamically adapt to changes in the environment, can provide a significant performance advantage.     

Innovative product design based on customer requirement weight calculation model

In the processes of product innovation and design, it is important for the designers to find and capture customer's focus through customer requirement weight calculation and ranking. Based on the fuzzy set theory and Euclidean space distance, this paper puts forward a method for customer requirement weight calculation called Euclidean space distances weighting ranking method. This method is used in the fuzzy analytic hierarchy process that satisfies the additive consistent fuzzy matrix. A model for the weight calculation steps is constructed; meanwhile, a product innovation design module on the basis of the customer requirement weight calculation model is developed. Finally, combined with the instance of titanium sponge production, the customer requirement weight calculation model is validated. By the innovation design module, the structure of the titanium sponge reactor has been improved and made innovative.     

基于改进惯性权重的粒子群优化算法

惯性权重是粒子群算法中平衡全局搜索和局部搜索能力的重要参数,提出了一种基于改进惯性权重的粒子群优化算法。该算法在进化初期采用基于不同粒子不同维的动态自适应惯性权重策略,加快收敛速度,在进化后期采用线性递减权重策略,同时为防止陷入局优,适时引入混沌变异增加种群多样性。对5个典型测试函数的测试结果表明,NPSO在收敛速度、收敛精度、稳定性和全局搜索能力等方面比线性权重PSO(LDIWPSO)均有很大程度上的提高。     

The adaptive fuzzy time series model with an application to Taiwan’s tourism demand

In this study, an adaptive fuzzy time series model for forecasting Taiwan’s tourism demand is proposed to further enhance the predicted accuracy. We first transfer fuzzy time series data to the fuzzy logic group, assign weights to each period, and then use the proposed adaptive fuzzy time series model for forecasting in which an enrollment forecasting values is applied to obtain the smallest forecasting error. Finally, an illustrated example for forecasting Taiwan’s tourism demand is used to verify the effectiveness of proposed model and confirmed the potential benefits of the proposed approach with a very small forecasting error MAPE and RMSE.     

Designing of MIP-based QCM sensor for the determination of Cu(II) ions in solution

A novel quartz crystal microbalance (QCM) sensor with a high selectivity and sensitivity has been developed for the determination of Cu(II) ions, based on the modification of Cu(II) ion-imprinted polymer (Cu(II)-IIP) film onto a quartz crystal. The performance of the developed MIP-QCM sensor was evaluated and the results indicated that a sensitive MIP-QCM sensor could be fabricated. The obtained MIP-QCM sensor presents high-selectivity monitoring of Cu(II) ions, better reproducibility, shorter response time (6 min), wider linear range (0.001–50 μM) and lower detection limit (8 × 10⁻⁴ μM). The practical analysis of the MIP-QCM sensor confirms the feasibility of Cu(II) determination in wastewater.     

System identification-based control of an unmanned autonomous wind-propelled catamaran

An autonomous catamaran, based on a modified Prindle-19 day-sailing catamaran and fitted with several sensors and actuators was built to test the viability of GPS-based system identification for precision control. Using an electric trolling motor for propulsion, and lead ballast to match all-up weight, several system identification passes were performed to excite system modes and model the dynamic response. The identification process used the Observer Kalman IDentification (OKID) method for identifying a linear time invariant plant model and associated pseudo-Kalman filter. System identification input was generated using a human pilot driving the catamaran on roughly straight line passes. A fourth order discrete time model was generated from the data, and showed excellent prediction results. Using these models, linear quadratic Gaussian (LQG) controllers were designed and tested with the electric trolling motor. These controllers demonstrated excellent line-tracking performance, with error standard deviations of less than 0.15 m. The wing-sail propulsion system was fitted, and these same controllers re-tested with the wing providing all propulsive thrust. Line-following performance and disturbance rejection were excellent, with the cross-track error standard deviations of approximately 0.30 m, in spite of wind speed variations of over 50% of nominal value.     

数据丢失情况下的最小二乘参数辨识算法

现有系统参数辨识方法大多是建立在输入输出数据可以完全测量和完全获取的基础上,而在实际系统中,由于传感器故障或网络传输机构故障,使得数据丢失现象经常发生。研究一类线性系统在输入或输出数据丢失情况下的系统辨识问题,并将数据丢失现象描述为随机伯努利序列,在此基础上提出新的辨识算法来估计数据丢失情况下系统的参数。最后,通过仿真示例验证所提算法对数据丢失的影响。结果表明,所提出的算法相较于递推最小二乘法有更好的收敛性。     

Multiple-mode adaptive state estimator for nonlinear switched systems

This paper deals with the issue of state estimator design for nonlinear switched systems. A multiplemode adaptive estimator is proposed under mode-dependent average dwell time (MDADT) switching, and the switching signal with MDADT constraint is also obtained to guarantee the exponential stability of estimation error dynamics, where the Lipschitz constant may be unknown since it is adaptively adjusted by designing an adaptation law. Based on both Lyapunov stable theory and the feasible solution of an optimization problem with linear matrix inequality constraint, the gain matrices and switching signals are provided, respectively. The sufficient conditions of the existence of multiple-mode adaptive switched estimator are also derived. Meanwhile, the above methods are also extended to the case of the average dwell time (ADT) switching, and an algorithm is given to summarize the implementation of the proposed estimators. Finally, the effectiveness of the designed methods is illustrated by simulation examples.     

Quantized H∞ control for a class of 2-D systems with missing measurements

In this paper, the problem of quantized H∞ control is investigated for a class of 2-D systems described by Roesser model with missing measurements. The measurement missing of system state is described by a sequence of random variables obeying the Bernoulli distribution. Meanwhile, the state measurements are quantized by logarithmic quantizer before being communicated. By introducing a new 2-D Lyapunov-like function, a sufficient condition is derived to guarantee stochastically stable and H∞ performance of the closed-loop 2-D system, where the method of sector-bounded uncertainties is utilized to deal with quantization error. Based on the condition, the quantized H∞ control can be designed by using linear matrix inequality technique. A simulation example is also given to illustrate the proposed method.