论当代大学生的公民意识教育

党的十七大报告明确指出：＂加强公民意识教育,树立社会主义民主法治、自由平等、公平正义理念。＂这里的公民意识是一种现代社会意识,是公民对自己在国家中的社会地位、社会权利和社会责任的一种自觉认识。没有具有现代意识的高素质的公民,中国的现代化就很难实现。大学生做为未来社会发展的中坚力量,是祖国的栋梁之材,他们将站在中国与世界交流的最前列,所以当代中国大学生的公民意识决定了祖国的未来。     

大学生体质健康状况及干预对策的研究

以鞍山师范学院大学生为研究对象,运用文献资料法、访谈法、测量法和数理统计等方法,结合国民体质监测标准分析了在校学生的体质健康状况.根据分析结果,提出了提升鞍山师范学院大学生健康体质状况的干预措施及相关建议.     

基于“人本主义课程理论”的教材评价研究——评新版《新视野大学英语读写教程》教材

＂人本主义课程理论＂强调＂以人为本,全人教育＂。本文研究了国内外相关教材评价理论,并基于＂人本主义课程理论＂,对新版《新视野大学英语读写教程》教材进行分析与评价,旨在今后的大学英语教学中充分发挥此教材的特长,改进教学方法和提高教学效果。     

Examining the relationship between higher educational attainment,trauma symptoms,and internalizing behaviors in child sexual abuse survivors

The trauma symptoms of child sexual abuse (CSA) survivors don’t end with the abuse, or even with the advent of adulthood. Instead, these symptoms can persist into all the realms of a survivor’s life, including education, which sets the foundation for career advancement. This retrospective study of adult survivors of childhood sexual abuse (n = 260) examined the relationships between trauma symptoms, dissociation, dissociative amnesia, anxiety, depression, sleep problems and higher education attainment. The purpose of this study was to determine if these factors are associated with higher education completion for childhood sexual abuse (CSA) survivors. Linear regressions and ANOVAs suggest that many of these variables are significantly associated with survivors’ educational trajectory, and multiple linear regressions show that trauma symptoms (as measured by the Trauma Symptom Checklist-40), caregivers’ education levels, and age at onset of abuse are significant predictors of decreased education levels. This information can provide insight into additional risk and protective factors for CSA survivors in order to enhance acute and long-term management of trauma symptoms to increase levels ofattainment of higher education.     

Event-triggered non-fragile H∞ fault detection for discrete time-delayed nonlinear systems with channel fadings

In this paper, the event-triggered non-fragile H_∞ fault detection filter is designed for a class of discrete-time nonlinear systems subject to time-varying delays and channel fadings. The Lth Rice fading model is utilized to reflect the actual received measurement signals, and its channel coefficients own arbitrary probability density functions on interval [0,1]. The event-based filter is constructed to reduce unnecessary data transmissions in the communication channel, which only updates the measurement signal to the filter when the prespecified “event” is triggered. Multiplicative gain variations are utilized to describe the phenomenon of parameter variations in actual implementation of the filter. Based on Lyapunov stability theory, stochastic analysis technology along with linear matrix inequalities (LMIs) skills, sufficient conditions for the existence of the non-fragile fault detection filter are obtained which make the filtering error system stochastically stable and satisfy the H_∞ constraint. The gains of the filter can be calculated out by solving the feasible solution to a certain LMI. A simulation example is given to show the effectiveness of the proposed method.     

Event-based weighted residual generator design via non-PDC scheme for fault diagnosis in T–S fuzzy systems

This paper is concerned with the event-based weighted residual generator design via non-parallel distribution compensation (PDC) scheme for fault diagnosis in discrete-time T–S fuzzy systems, under consideration of the imperfect premise matching membership functions. An event-triggered mechanism is firstly introduced to save communication resources, which leads to the premise variables of the system and observer to be asynchronous. Then, a fuzzy diagnostic observer with mismatched premise variables is designed to estimate the unmeasurable states of the system. Moreover, by using non-PDC method, a diagnostic observer-based weighted residual generator is established to improve the fault detection (FD) performance by using the information provided by each local system, in which the membership functions structure of the diagnostic observer and residual generator need not to be the same as the systems, and the L_∞/L₂ and L_∞ FD scheme is used to optimize the FD performance. Finally, two simulation results are provided to show the efficiency of the proposed non-PDC method.     

Fractional-order follower observer design for tracking consensus in second-order leader multi-agent systems: Periodic sampled-based event-triggered control

This paper investigates the tracking consensus problem for the second-order leader systems by designing fractional-order observer, where a periodic sampled-based data event-triggered control is employed. In order to track the position information of leader, observers for followers are designed by fractional-order system, where only the relative position information is available. Furthermore, in the process of observers design, a sampled-based event-triggered strategy is proposed so that observers use the event-triggered sampled-data, to reduce the overall load of the network. In our proposed event-triggered strategy, the event detection only works at every sampling time instant which determines whether the sampled-data should be discarded or used. Under this control strategy, the Zeno-behavior is absolutely excluded since the minimum of inter-event times is inherently lower bounded by one sampling period. It is found that the followers can track state of the leader if fractional-order observers are appropriately designed and relevant parameters are properly selected. By using the generalized Nyquist stability criterion, a necessary and sufficient condition for the observer tracking consensus of the second-order leader systems is derived. The results show that the real and imaginary parts of the eigenvalues of the augmented Laplacian matrix, and fractional-order α of observer play a vital role in reaching consensus.     

A new sensor selection scheme for Bayesian learning based sparse signal recovery in WSNs

In this paper, we address the issue of sparse signal recovery in wireless sensor networks (WSNs) based on Bayesian learning. We first formulate a compressed sensing (CS)-based signal recovery problem for the detection of sparse event in WSNs. Then, from the perspective of energy saving and communication overhead reduction of the WSNs, we develop an optimal sensor selection algorithm by employing a lower-bound of the mean square error (MSE) for the MMSE estimator. To tackle the nonconvex difficulty of the optimum sensor selection problem, a convex relaxation is introduced to achieve a suboptimal solution. Both uncorrelated and correlated noises are considered and a low-complexity realization of the sensor selection algorithm is also suggested. Based on the selected subset of sensors, the sparse Bayesian learning (SBL) is utilized to reconstruct the sparse signal. Simulation results illustrate that our proposed approaches lead to a superior performance over the reference methods in comparison.     

Teaching for developmental growth: learning partnerships and student development in graduate education in China

Teaching and learning in higher education can integrate and accomplish student developmental goals in addition to promoting student learning of subject matter knowledge and transferrable skills. Drawn from the theoretical concept of self-authorship, the Learning Partnerships Model was implemented in teaching a graduate-level course on social research methodology. This paper describes the conceptualization and implementation of the developmentally attuned course, and reports a qualitative study that examined student development as its result. Qualitative data were collected from five cohorts of course participants, in the forms of reflective essays, student interviews, and the instructor’s teaching journal. Seven themes were identified that reflected student development throughout the course. The seven themes fall into three dimensions of epistemological, intrapersonal, and interpersonal development that are interconnected, and the epistemological dimension stands out as a strong partner among the three. These findings may help university faculty understand and integrate student development into their teaching practices.     

Negotiating Voice Construction Between Writers and Readers in College Writing: A Case Study of an L2 Writer

Voice is co-constructed, a result of the “text-mediated interaction between the writer and the reader.” The present study, using the context of U.S. college writing, explores the complicated process by which an L2 novice writer—one who has a growing awareness of, yet peripheral access to, discourse practices—constructs a voice. Through interviews and a close analysis of a text, a comparison is made between the voice the L2 writer wished to project in an assigned paper and the voice constructed by two readers in the course of their anonymous readings of the paper. The significant gap between the L2 writer’s aims and the readers’ responses suggests that a writer’s view of her voice stems from the ways in which she conceptualizes discourse conventions, in association with her particular linguistic, social, and cultural background. The pedagogical implications of the L2 writer’s process of negotiating identity, and her struggles to learn discourse expectations, are discussed.