Modeling of vehicular traffic system

The behavior of traffic systems controlled by traffic lights on a single lane is presented using the optimal velocity model. The effect of different traffic light control strategies on the traffic flow is discussed using three different strategies, i.e. the synchronized, green wave, and random offset. Some simulation results on the model using cellular automata are presented. The flow-density diagrams are analyzed using these strategies. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

城市主干道交通信号灯模糊线控制的探讨

本文首先提出城市交通系统线控制的两级递阶结构：第一级，用模糊逻辑控制器确定单路口交通信号灯的周期和绿信比；第二级，用模糊相位控制器确定相邻两路口的相位差；两级间用模糊转换开关协调；然后，提出具体的实现方法。     

The impact of integrated STEM modeling on elementary preservice teachers’ self‐efficacy for integrated STEM instruction: A co‐teaching approach

The purpose of the current study was to evaluate the impact of co‐taught integrated STEM methods instruction on preservice elementary teachers’ self‐efficacy for teaching science and mathematics within an integrated STEM framework. Two instructional methods courses (Elementary Mathematics Methods and Elementary Science Methods) were redesigned to include STEM integration components, including STEM model lessons co‐taught by a mathematics and science educator, as well as a special education colleague. Quantitative data were gathered at three time points in the semester (beginning, middle, and end) from 55 preservice teachers examining teacher self‐efficacy for integrated STEM teaching. Qualitative data were gathered from a purposeful sample of seven preservice teachers to further understand preservice teachers’ perceptions on delivering integrated STEM instruction in an elementary setting. Quantitative results showed a significant increase in teacher self‐efficacy across all three time points. Item‐level analysis revealed that self‐efficacy for tasks involving engineering and assessment (both formative and summative) were low across time points, while self‐efficacy for tasks involving technology and flexibility were consistently high. Qualitative results revealed that the preservice teachers did not feel adequately prepared by university‐level science and mathematics courses, in terms of content knowledge and integration of science and mathematics for elementary students.     

Nonextensive model of self‐organizing systems

The article concerns the new nonextensive model of self‐organizing systems and consists of two interrelated parts. The first one presents a new nonextensive model of interaction between elements of systems. The second one concerns the relationship between microscopic and macroscopic processes in complex systems. It is shown that nonextensivity and self‐organization of systems is a result of mismatch between its elements. © 2013 Wiley Periodicals, Inc. Complexity 18: 28–36, 2013     

A conductivity‐dependent phase transition from closed‐loop to open‐loop dendritic networks

Motivated by a principle of minimum dissipation per channel length, we introduce a model for branching, hierarchical networks in an open, dissipative system. Global properties of the resulting structures are observed to scale with the ratio of conductivity in the dendrite material to conductivity in the lattice material. Beyond a critical conductivity ratio, the resulting structures are naturally self‐avoiding and possess scale‐independent branching ratios. Our findings suggest that the conductivity ratio determines the geometric properties of naturally arising dendritic structures. We discuss empirical verification in the context of a system of self‐organizing agglomerates of metal particles in castor oil. © 2004 Wiley Periodicals, Inc. Complexity 9: 56–60, 2004     

Community‐Based Service‐Learning as a Source of Personal Self‐Efficacy: Preparing Preservice Elementary Teachers to Teach Science for Diversity

Bandura (1997) contends that when compared to other sources of efficacy, mastery experiences, when presented appropriately, have the most powerful influence on self‐efficacy. The purpose of this study was to investigate the effects of community‐based service learning (CBSL) experiences on preservice elementary teachers' personal self‐efficacy beliefs about equitable science teaching and learning. Data were collected using pretests‐posttests and post‐questionnaires with the study sample. Findings from this study support Bandura's assertion. CBSL experiences were an important source of personal self‐efficacy and significantly influenced preservice elementary teachers' personal self‐efficacy beliefs about equitable science teaching and learning.     

Maximal small extensions of o‐minimal structures

A proper elementary extension of a model is called small if it realizes no new types over any finite set in the base model. We answer a question of Marker, and show that it is possible to have an o‐minimal structure with a maximal small extension. Our construction yields such a structure for any cardinality. We show that in some cases, notably when the base structure is countable, the maximal small extension has maximal possible cardinality (© 2010 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

交通灯数学模型

主要讨论在假定车流均匀的前提下如何安排路口的交通灯时间才能使路口的交通达到最大限度的畅通.这里交通最大限度通畅的定义是一个交通周期内积存车辆的最大可能长度达到最小.文章首先以最大限度通畅为目标,道路条件、行人通过马路等条件为约束,建立优化模型解决孤立丁字路口的交通灯安排问题,这个模型也适用于孤立十字路口的分析.随后文章建立了多个路口相连时路口交通灯的安排模型.最后,文章讨论了上述几个模型的稳定性以及改进方向.     

Detecting evolving patterns of self‐organizing networks by flow hierarchy measurement

Hierarchies occur widely in evolving self‐organizing ecological, biological, technological, and social networks, but detecting and comparing hierarchies is difficult. Here we present a metric and technique to quantitatively assess the extent to which self‐organizing directed networks exhibit a flow hierarchy. Flow hierarchy is a commonly observed but theoretically overlooked form of hierarchy in networks. We show that the ecological, neurobiological, economic, and information processing networks are generally more hierarchical than their comparable random networks. We further discovered that hierarchy degree has increased over the course of the evolution of Linux kernels. Taken together, our results suggest that hierarchy is a central organizing feature of real‐world evolving networks, and the measurement of hierarchy opens the way to understand the structural regimes and evolutionary patterns of self‐organizing networks. Our measurement technique makes it possible to objectively compare hierarchies of different networks and of different evolutionary stages of a single network, and compare evolving patterns of different networks. It can be applied to various complex systems, which can be represented as directed networks. © 2011 Wiley Periodicals, Inc. Complexity, 2011     

Equilibrium configurations of a thin elastic rod with self‐contacts

Spatial equilibria of a closed thin isotropic elastic rod are considered. The thin elastic rod is a classical model for the large‐scale structure of relatively long DNA molecules. Particular attention is paid to the shapes with self‐contacts which are assembled from the elementary loops.     

Using self‐dissimilarity to quantify complexity

For many systems characterized as “complex” the patterns exhibited on different scales differ markedly from one another. For example, the biomass distribution in a human body “looks very different” depending on the scale at which one examines it. Conversely, the patterns at different scales in “simple” systems (e.g., gases, mountains, crystals) vary little from one scale to another. Accordingly, the degrees of self‐dissimilarity between the patterns of a system at various scales constitute a complexity “signature” of that system. Here we present a novel quantification of self‐dissimilarity. This signature can, if desired, incorporate a novel information‐theoretic measure of the distance between probability distributions that we derive here. Whatever distance measure is chosen, our quantification of self‐dissimilarity can be measured for many kinds of real‐world data. This allows comparisons of the complexity signatures of wholly different kinds of systems (e.g., systems involving information density in a digital computer vs. species densities in a rain forest vs. capital density in an economy, etc.). Moreover, in contrast to many other suggested complexity measures, evaluating the self‐dissimilarity of a system does not require one to already have a model of the system. These facts may allow self‐dissimilarity signatures to be used as the underlying observational variables of an eventual overarching theory relating all complex systems. To illustrate self‐dissimilarity, we present several numerical experiments. In particular, we show that the underlying structure of the logistic map is picked out by the self‐dissimilarity signature of time series produced by that map. © 2007 Wiley Periodicals, Inc. Complexity 12: 77–85, 2007     

On self‐organising traffic lights technology

Self‐organising traffic lights (SOTL) are considered a promising instrument for the development of more efficient adaptive traffic control systems. In this paper, we explain why this technology should be scrutinised and carefully reviewed. Research projects based on SOTL currently under way should be reviewed too. © 2015 Wiley Periodicals, Inc. Complexity 21: 328–330, 2016     

Contextual regularity and complexity of neuronal activity: From stand‐alone cultures to task‐performing animals

Precursors of the superior information processing capabilities of our cortex can most probably be traced back to simple invertebrate systems. Using a unique set of newly developed neuronal preparations and state‐of‐the‐art analysis tools, we show that insect neurons have the ability to self‐regulate the information capacity of their electrical activity. We characterize the activity of a distinct population of neurons under progressive levels of structural and functional constraints: self‐formed networks of neuron clusters in vitro; isolated ex vivo ganglions; in vivo task‐free, and in vivotask‐forced neuronal activity in the intact animal. We show common motifs and identify trends of increasing self‐regulated complexity. This important principle may have played a key role in the gradual transition from simple neuronal motor control to complex information processing. © 2004 Wiley Periodicals, Inc. Complexity 9: 25–32, 2004     

Wave simulations of Gray‐Scott reaction‐diffusion system

In this work, we study the numerical simulation of the one‐dimensional reaction‐diffusion system known as the Gray‐Scott model. This model is responsible for the spatial pattern formation, which we often meet in nature as the result of some chemical reactions. We have used the trigonometric quartic B‐spline (T4B) functions for space discretization with the Crank‐Nicolson method for time integration to integrate the nonlinear reaction‐diffusion equation into a system of algebraic equations. The solutions of the Gray‐Scott model are presented with different wave simulations. Test problems are chosen from the literature to illustrate the stationary waves, pulse‐splitting waves, and self‐replicating waves.     

Signal‐regulated systems and networks

The article presents the use of signal regulatory networks (SRNs), a biologically inspired model based on gene regulatory networks. SRNs are a way of understanding a class of self‐organizing IT systems, signal‐regulated systems (SRSs). This article builds on the theory of SRSs and introduces some formalisms to clarify the discussion. An exemplar SRS that can be evaluated using SRNs is presented. Finally, an implementation of an adaptive and robust solution, built on a theory of SRSs and analyzed as a SRN, is shown to be plausible. © 2010 Wiley Periodicals, Inc. Complexity, 2010     

Science Self‐Efficacy of Preservice Teachers in Face‐to‐Face versus Blended Environments

Using a quasi‐experimental mixed methods concurrent design, this study measured the science self‐efficacy of pre‐service elementary teachers before and after a survey of science content course. Further, this course was delivered in two different formats: face‐to‐face and hybrid (approximately 50% online), and compared pre‐and post‐science self‐efficacy of students in the two different course formats. Our quantitative results showed increases in personal efficacy, but not outcome expectancy for both formats, and no significant differences between the increases for either format. Our qualitative data showed that participants attributed their increased levels of personal efficacy to the hands‐on components of the course, as well as perceived teacher attitudes toward science, both of which would be challenging to replicate in a purely online format, as opposed to the hybrid format included in this study.     

The small‐is‐very‐small principle

The central result of this paper is the small‐is‐very‐small principle for restricted sequential theories. The principle says roughly that whenever the given theory shows that a definable property has a small witness, i.e., a witness in a sufficiently small definable cut, then it shows that the property has a very small witness: i.e., a witness below a given standard number. Which cuts are sufficiently small will depend on the complexity of the formula defining the property. We draw various consequences from the central result. E.g., roughly speaking, (i) every restricted, recursively enumerable sequential theory has a finitely axiomatized extension that is conservative with respect to formulas of complexity $\le n$; (ii) every sequential model has, for any n, an extension that is elementary for formulas of complexity $\le n$, in which the intersection of all definable cuts is the natural numbers; (iii) we have reflection for ${\mathrm{\Sigma }}_2^0$‐sentences with sufficiently small witness in any consistent restricted theory U; (iv) suppose U is recursively enumerable and sequential. Suppose further that every recursively enumerable and sequential V that locally inteprets U, globally interprets U. Then, U is mutually globally interpretable with a finitely axiomatized sequential theory. The paper contains some careful groundwork developing partial satisfaction predicates in sequential theories for the complexity measure depth of quantifier alternations.     

An information‐theoretic primer on complexity,self‐organization,and emergence

Complex Systems Science aims to understand concepts like complexity, self‐organization, emergence and adaptation, among others. The inherent fuzziness in complex systems definitions is complicated by the unclear relation among these central processes: does self‐organisation emerge or does it set the preconditions for emergence? Does complexity arise by adaptation or is complexity necessary for adaptation to arise? The inevitable consequence of the current impasse is miscommunication among scientists within and across disciplines. We propose a set of concepts, together with their possible information‐theoretic interpretations, which can be used to facilitate the Complex Systems Science discourse. Our hope is that the suggested information‐theoretic baseline may promote consistent communications among practitioners, and provide new insights into the field. Published 2008 Wiley Periodicals, Inc. Complexity, 2009     

Knowledge‐based scenario tree generation methods and application in multiperiod portfolio selection problem

A scenario tree is an efficient way to represent a stochastic data process in decision problems under uncertainty. This paper addresses how to efficiently generate appropriate scenario trees. A knowledge‐based scenario tree generation method is proposed; the new method is further improved by accounting for subjective judgements or expectations about the random future. Compared with existing approaches, complicated mathematical models and time‐consuming estimation, simulation and optimization problem solution are avoided in our knowledge‐based algorithms, and large‐scale scenario trees can be quickly generated. To show the advantages of the new algorithms, a multiperiod portfolio selection problem is considered, and a dynamic risk measure is adopted to control the intermediate risk, which is superior to the single‐period risk measure used in the existing literature. A series of numerical experiments are carried out by using real trading data from the Shanghai stock market. The results show that the scenarios generated by our algorithms can properly represent the underlying distribution; our algorithms have high performance, say, a scenario tree with up to 10,000 scenarios can be generated in less than a half minute. The applications in the multiperiod portfolio management problem demonstrate that our scenario tree generation methods are stable, and the optimal trading strategies obtained with the generated scenario tree are reasonable, efficient and robust. Copyright © 2013 John Wiley & Sons, Ltd.     

Advances in the study of elementary cellular automata regular language complexity

Cellular automata (CA) are discrete dynamical systems that, out of the fully local action of its state transition rule, are capable of generating a multitude of global patterns, from the trivial to the arbitrarily complex ones. The set of global configurations that can be obtained by iterating a one‐dimensional cellular automaton for a finite number of times can always be described by a regular language. The size of the minimum finite automaton corresponding to such a language at a given time step provides a complexity measure of the underlying rule. Here, we study the time evolution of elementary CA, in terms of such a regular language complexity. We review and expand the original results on the topic, describe an alternative method for generating the subsequent finite automata in time, and provide a method to analyze and detect patterns in the complexity growth of the rules. © 2015 Wiley Periodicals, Inc. Complexity 21: 267–279, 2016