Free Information Flow Benefits Truth Seeking

How can we approach the truth in a society? It may depend on various factors. In this paper, using a well-established truth seeking model, the authors show that the persistent free information flow will bring us to the truth. Here the free information flow is modeled as the environmental random noise that could alter one's cognition. Without the random noise, the model predicts that the truth can only be captured by the truth seekers who own actively perceptive ability of the truth and their believers, while the other individuals may stick to falsehood. But under the influence of the random noise, the authors strictly prove that even there is only one truth seeker in the group, all individuals will finally approach the truth.     

Fuzzy Views on Black-Litterman Portfolio Selection Model

In this paper, views of investor are described in fuzzy sets, and two fuzzy Black-Litterman models are constructed with fuzzy views and fuzzy random views respectively. In the models, expected returns and uncertainty matrix of views are redefined and the views are formulated by fuzzy approaches suitably. Then the models are tested with data from Chinese financial markets. Empirical results show that the fuzzy random views model performs the best, and both the fuzzy models are better than the traditional ones, demonstrating that the fuzzy approaches can contain more information in the views and measure the uncertainty more correctly.     

Optimal Multimodel Representation by Laguerre Filters Applied to a Communicating Two Tank System

This paper presents the development of a new nonlinear representation by exploiting the multimodel approach and the new linear representation ARX-Laguerre for each operating region. The resulting multimodel, entitled ARX-Laguerre multimodel, is characterized by the parameter number reduction with a recursive representation. However, a significant reduction of this multimodel is subject to an optimal choice of Laguerre poles characterizing each local linear model ARX-Laguerre. Therefore, the authors propose an optimization algorithm to estimate, from input/output measurements, the optimal values of Laguerre poles. The ARX-Laguerre multimodel as well as the proposed optimization algorithm are tested on a continuous stirred tank reactor system (CSTR). Moreover, the authors take into account a practical validation on an experimental communicating two tank system (CTTS).     

Existence and Uniqueness Results for Quaternion-Valued Nonlinear Impulsive Differential Systems

This paper studies the existence and uniqueness conditions for the quaternion-valued nonlinear impulsive system. Firstly, a space of quaternion-valued piecewise functions is constructed and completeness of the space is also proved. Then by taking advantage of the Bielecki norm and fixed point theorem, existence and uniqueness criteria of quaternion-valued nonlinear impulsive system are obtained. At last, an example is given to illustrate our theoretical results.     

Data-Driven Leader-Follower Output Synchronization for Networked Non-Linear Multi-Agent Systems with Switching Topology and Time-Varying Delays

This paper studies the output synchronization problem for a class of networked non-linear multi-agent systems with switching topology and time-varying delays. To synchronize the outputs, a leader is introduced whose connectivity to the followers varies with time, and a novel data-driven consensus protocol based on model free adaptive control is proposed, where the reference input of each follower is designed to be the time-varying average of the neighboring agents’ outputs. Both the case when the leader is with a prescribed reference input and the case otherwise are considered. The proposed protocol allows for time-varying delays, switching topology, and does not use the agent structure or the dynamics information implicitly or explicitly. Sufficient conditions are derived to guarantee the closed-loop stability, and conditions for consensus convergence are obtained, where only a joint spanning tree is required. Numerical simulations and practical experiments are conducted to demonstrate the effectiveness of the proposed protocol.     

Chaos and Nonlinear Feedback Control of the Arch Micro-Electro-Mechanical System

This paper addresses a nonlinear feedback control problem for the chaotic arch microelectro- mechanical system with unknown parameters, immeasurable states and partial state-constraint subjected to the distributed electrostatic actuation. To reflect inherent properties and design controller, the phase diagrams, bifurcation diagram and Poincare section are presented to investigate the nonlinear dynamics. The authors employ a symmetric barrier Lyapunov function to prevent violation of constraint when the arch micro-electro-mechanical system faces some limits. An RBF neural network system integrating with an update law is adopted to estimate unknown function with arbitrarily small error. To eliminate chaotic oscillation, a neuro-adaptive backstepping control scheme fused with an extended state tracking differentiator and an observer is constructed to lower requirements on measured states and precise system model. Besides, introducing an extended state tracking differentiator avoids repeated derivative for the virtual control signal associated with conventional backstepping. Finally, simulation results are presented to illustrate feasibility of the proposed scheme.     

Systemic Thinking and Practice Toward Facilitating Inclusive Education: Reflections on a Case of Co-Generated Knowledge and Action in South Africa

This article offers our reflections around a case of facilitating systemic thinking and practice in which the first author of the article (Tlale) interacted with research participants/participant researchers with the intention of strengthening systemic thought and action toward fostering inclusive education in the setting (a rural school in the Eastern Cape in South Africa). We reflect upon the process and also how our engagement was perceived by participants, as expressed in feedback received from them. We point to how Tlale introduced the idea of systemic thinking (to teachers, school management team, school governing body, and a district officer for the district) as tied to the possibility of acting to generate transformation toward a more inclusive educational context for the benefit of the learners at the school in question, thus acting as a systemic mediator on their behalf.     

Human Development in Saudi Education: a Critical Systemic Approach

This paper is drawn from PhD research funded by the Saudi government on the policy and governance of Saudi schools (Algraini 2017. A critical systemic approach to human development in education: a case study of the Ministry of Education in Saudi Arabia). The aim of this article is to address human development challenges using the Critical Systems Heuristics approach. The results show that the central policy framework limits the opportunity for teachers and learners to contribute to shaping the curriculum and the process for human development. The Saudi Ministry of Education needs to: a) develop policy that takes into account the structure and the processes that shape education outcomes and b) to represent the voices of service users and service providers who have different and overlapping views.     

Community Work Research through Co-Operative Inquiry in Timor-Leste,Australia and Peru: Insights into Process

Co-operative inquiry is an under-explored method in community-based research. Its democratic approach involves a group of “co-researchers” collaboratively inquiring into a mutually-agreed research topic through systematic cycles of reflection and action. This article shares the process, outcomes, and methodological reflections of three co-operative inquiries that were conducted as part of an international study regarding love in community work. Groups of up to 10 community workers in rural villages in Timor-Leste, Australia, and Peru engaged in co-operative inquiry to collaboratively develop new knowledge to inform practice. The article analyses data regarding co-inquirer experiences of the methodology, and identifies the strengths and challenges of the co-operative inquiry method to support the collective generation of new knowledge. The article concludes that co-operative inquiry involves shared power, participation, action, and contextual reflexivity, and is a useful method for community workers to collaboratively develop innovative approaches to community work practice through cycles of reflection and action.     

The Convergence of Least-Squares Progressive Iterative Approximation for Singular Least-Squares Fitting System

Data fitting is an extensively employed modeling tool in geometric design. With the advent of the big data era, the data sets to be fitted are made larger and larger, leading to more and more leastsquares fitting systems with singular coefficient matrices. LSPIA (least-squares progressive iterative approximation) is an efficient iterative method for the least-squares fitting. However, the convergence of LSPIA for the singular least-squares fitting systems remains as an open problem. In this paper, the authors showed that LSPIA for the singular least-squares fitting systems is convergent. Moreover, in a special case, LSPIA converges to the Moore-Penrose (M-P) pseudo-inverse solution to the leastsquares fitting result of the data set. This property makes LSPIA, an iterative method with clear geometric meanings, robust in geometric modeling applications. In addition, the authors discussed some implementation detail of LSPIA, and presented an example to validate the convergence of LSPIA for the singular least-squares fitting systems.