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Intelligent Education Physics Platform (IEPP) based on visualized knowledge elements can better meet actual needs of teachers and students in the process of curriculum teaching for the acquisition, learning and exploration of subject knowledge. Visualized knowledge element expressions of subject domain knowledge and readable problem's automatic and dynamic generation for given scenario are cornerstone problems of ICAI intelligent education subject platform research. On the background of junior middle school IEPP, combined with structural characteristics of unit knowledge, the theory of automatic and dynamic readable physical problem generation with visualized knowledge element expression under given scenario has been expanded to (junior middle school) electricity unit. A solid foundation has been laid for ICAI electricity problem's readable solution and application with knowledge expression, reasoning, and automatic and dynamic readable problem generation method proposed in this paper. It will play an exemplary role when expanding research works of other unit of knowledge.

The Cyber-physical system (CPS) will soon become the basic technology of contemporary industry, which consists of two interacting networks where the cyber network overlays the physical network. Due to the high interdependence, the CPS are more fragile in general when facing attacks. In order to avoid the occurrence of catastrophic accidents while taking into account the cost of construction, it is critical to find and protect key nodes whose failure will lead to serious cascading failures. In this paper, we present a way to evaluate the node importance in CPS based on information theory, where node states are treated as discrete random variables, and their importance is interpreted as the information gain. After research, we find that self-information of a node state can reflect its ability to influence the whole system. In particular, the result of this method is affected by the probability of attacking nodes, which helps to assess the node importance in different scenarios and environments.

To obtain a better performance of trajectory tracking for hypersonic glide vehicles (HGVs), this paper focuses on enhancing the accuracy of tracking model, an effective method with a modified tracking model is proposed. Firstly, according to the skip glide trajectory of HTV-2, a simplified trajectory model is established to describe the periodical characteristic of the trajectory. Secondly, a modified tracking model based on Sine model for HGVs is designed. Thirdly, for better model matching performance, an adaptive method is proposed to update the probability transition matrix of IMM. Finally, numerical simulation results are given to demonstrate that: interacting multiple model (IMM) algorithm based on the proposed Sine model is more accurate than that of Singer model, moreover, the adaptive IMM (AIMM) algorithm improves both the precision and the convergence rate of tracking for HGV.

One of the 21st core competences is the ability of international communication, which refers to English. It has been included in the compulsory education in Taiwan. However, students often feel bored while memorizing the vocabulary because they think it is irrelevant to their lives. Besides, the most used items in the exams are usually multiple choices, which can only test students' passive knowledge. Passive knowledge is hard for students to apply in the real context. Therefore, in this study, contextual digital games combining passive or active knowledge question items were proposed to promote students' learning achievement as well as motivation and to increase the application in their daily lives. Two classes of students in an elementary school were assigned to learn with the game with passive knowledge question items or the game with active knowledge question items. The results show that the learning achievement of those students learning with the game with active question items is better. No significance was found in students' learning motivation but the ratings still increase. The cognitive load of students learning with active knowledge is heavier. Those findings imply that an approach with certain degree of cognitive load might still have positive impacts on students.

The fast growth of Internet web documents has posed new challenges on how to efficiently and accurately manage and retrieve the textual collections, text clustering plays a significant role. Traditional document clustering is an unsupervised categorization of a given document collection based on vector space model, which is a high sparse vector. In this paper, we propose a means to fight the existing shortcomings with a word vector in distributed representation which is obtained from a neural probabilistic language model. To improve the representation of document vector and enhance the accuracy of text clustering, we first computing semantic similarities between words using word embedded vector, and then expanding the keywords of each document. The experiment results show the method can improve the accuracy of clustering.

This study mainly focuses on the community structure analysis of micro-blog user networks. With deep analysis on the micro-blog user network, we proposed the concept of user's core degree and user's attractiveness according to the characteristics of the micro-blog users, and then based on these concepts we propose two algorithms. An algorithm is designed to make some breakthrough on the time complexity of Internet community detection algorithm, another is the corresponding overlapping community detection algorithm. The research is for large social networks, and the another advantage is that the method does not require to specify the number of clusters. We test our algorithms under the real user data of Sina micro-blog, and the results verify the effectiveness and reliability of our algorithms.

Parameters setting in numerical simulation of Fluid-Structure Interaction (FSI) is important to get accurate results. A variable without units was defined to describe the mesh density. Effects of that variable and coupling control parameter in numerical simulation of FSI were studied. As an example, the underwater contact explosion on circular plate was simulated using the FEM programe LS-DYNA. The results of numerical simulation were compared with experimental data. The results showed that calculation errors were reduced at first and then increased according to the mesh density increased. Optimum range of mesh density was 2¨C3 and ratio of fluid mesh density to structure mesh density was 2¨C1. The optimum aspect ratio of structure mesh does not exceed 2. Penetration could be modified through adjusted coupling control parameters. The modifying way had no effect on structural deformation and fracture.

There are many different disturbances for hypersonic air vehicles due to complex flight environment and flight conditions of the high altitudes and Mach numbers. This paper analyses many kinds of disturbances such as aerodynamic interference, measurement noise, elevator disturbance and parametric uncertainty based on the fuzzy adaptive controller. Simulation results show that these disturbances obviously impact the flight tracking of height and velocity. However, the fuzzy adaptive controller is also able to effectively overcome these problems, and it has fine tracking performance and robustness.

Centralized control can improve the consistence of the network and reduce the load of routers. Trustworthy and Controllable Network takes centralized control as one of the basic control mechanisms and requires to build reliable centralized intra-domain routing. In this paper, we solved the problem of building reliable centralized intra-domain routing by finding the routing configuration which maximizes the disjoint paths of each ingress to all egresses. The problem is transformed to finding K paths for each ingress to the egresses. It is proved to be NP- hard to find the optimal solution when K≥2 if ingresses do not cross each other and when K≥3 if the ingresses cross each other. To solve the problem efficiently, a heuristic algorithm based on network flow theory called HANE is proposed and evaluated on different types of topologies. The experimental results show that HANE can achieve good performance.

Considering with interaction arising from Joint compensation of two kinds of flexible AC transmission systems(FACTS) devices which are the static var compensator ?SVC?and thyristor controlled series compensator (TCSC), this paper give point to quantitative analysis on the interaction strength of both devices by Singular Value Decomposition ?SVD?and then simulate it by using MATLAB software. SVD analysis and simulation result has shown that: the electrical distance between two devices and load both had a certain influence on the interaction. Shorter the distance is, more serious the interaction will be, and increase load also lead to stronger interaction between two compensation devices.

Traditional wireless sensor networks (WSNs) working in the license-free spectrum suffer from uncontrolled interference as the license-free spectrum becomes increasingly crowded. A WSN based on cognitive radios can potentially provide data transmissions with quality of service, while avoiding the high cost for accessing the licensed spectrum and uncontrolled interference in the license-free spectrum. Our previous works have studied delay performance of constant bit rate traffic in a cognitive radio sensor network (CRSN). In this paper we study the delay performance of random traffic with burst arrivals in the network. We derive the average delay for transmitting the random traffic using different channel sensing mechanisms, and verify the results using computer simulation. Our results show that satisfactory latency performance can be provided in the CRSN.

This paper deals with the extracellular polymeric substance (EPS) of Rhizobium radiobacter F2 used as a novel biosorbent to remove Cu (II) and Mn (II) ions from aqueous solutions. The Cu (II) and Mn (II) ions biosorption characteristics of the EPS were examined as a function of initial pH, contact time and EPS concentration. The proper pH of the aqueous solution was found to be 6.0 for both the biosorption of Cu (II) and Mn (II). Biosorption equilibrium times of Cu (II) and Mn (II) were achieved in 1.0 h. The maximum biosorption capacities under optimum conditions of Cu (II) and Mn (II) on the EPS were determined to be 45.30 ±± 1.62 mg/g and 28.86 ±± 1.28 mg/g, respectively. The fitness of the biosorption data for Langmuir and Freundlich isotherm models was investigated. It was found that biosorption of Cu (II) and Mn (II) ions onto the EPS were better suitable to Langmuir than Freundlich isotherm model. Competitive biosorption of Mn (II) and Cu (II) ions was also investigated to determine the selectivity of the bioflocculant.

In this paper we consider supporting real-time traffic in a cognitive radio sensor network (CRSN). A lot of traffic in wireless sensor networks (WSNs) requires strict quality of service (QoS) requirements, while most existing WSNs working in the license-free spectrum cannot provide guaranteed QoS. A cognitive radio network (CRN) can possibly support traffic with strict QoS requirements while avoiding high cost for accessing the licensed spectrum. The CRSN studied in this paper is cluster-based and supports both real-time traffic and best effort traffic. We consider two resource allocation policies in order to provide a higher priority to the real-time traffic. Mathematical models are developed to analyze the performance of the real-time traffic, and the analytical results are verified by computer simulations. Our results indicate that satisfactory real-time performance can be achieved in the CRSN.

How to effectively measure the adaptation complexity is an open issue in nature-inspired computation. In this paper, some essential characteristics of adaptation in evolution and the importance/complexity of constructing multi-objective fitness functions in evolutionary computation are analyzed. Based on the authorpsilas former work on the single-objective normalization, a general method is brought forward for multi-objective decision making and optimization whose key point is to divide the process of constructing fitness functions into there basic cases. Then the issues on the determination of the corresponding mathematical models and their parameters, the integration of all the fitness functions into a multi-objective fitness function are discussed. A paradigm in multi-input-multi-output control systems is illustrated to show the technical route of our method.

Due to disagreement with the proof of convergence theorems of diagonal recurrent neural networks (DRNN) for MISO systems given by Ku and Lee (1995), modified proofs are presented in this paper. Meanwhile, since the output error(s) are the function(s) of all the weights in DRNNs, it is irrational to update part of the weights while the others are kept invariable. Therefore convergence theorems for MISO systems should be modified in the way of putting all the weights into one variable vector. In addition, a convergence theorem of DRNNs for MIMO systems is developed.