Complex System

We discuss the close link between intermittent events ('quakes') and extremal noise fluctuations which has been advocated in recent numerical and theoretical work. From the idea that record-breaking noise fluctuations trigger the quakes, an approximate analytical description of non-equilibrium aging as a Poisson process with logarithmic time arguments can be derived. Theoretical predictions for measurable statistical properties of mesoscopic fluctuations are emphasized, and supporting numerical evidence is included from simulations of short-ranged Ising spin-glass models, of the ROM model of vortex dynamics in type II superconductors, and of the Tangled Nature model of biological evolution.

This position paper illustrates the use of a natural framework for the modelling, analysis, and design of engineering systems that involve two or more controllers, each of which has an associated objective function. Such systems arise when ordinary single controller systems are networked through communication links so that the information available to each controller may contain aspects of the other systems' states and the optimization of each objective function is no longer decoupled from each other. Single controller optimization is no longer directly applicable. Appropriate to the study of such systems is the theory of games that has been developing in mathematics, economics, and engineering for the past 60 years. There are extensive applications in economics, but in engineering the applications are scarce. In recent years, there has been great attention to global problems such as the negative environmental impact of energy use, and global warming. These problems arise from complex systems with multiple controllers. Among the approaches for dealing with the problems, there should be one on a total systems approach with a game theory base. A natural framework for this is the subject of this policy paper.

Command Control, Communication Computer and Intelligence (C4I) systems enables modern military forces to achieve information superiority in the battlefield. C4I are complex System of systems (SOS) where individual systems interact locally to achieve global SOS behaviors. To build software for C4I systems conventional software engineering SwE process and practices have shortcomings and are not capable to support certain aspect of these systems. If C4I systems fail to operate as required due to the fact that SwE process was unable to fulfill its requirements, the consequences may not be tolerated because of the criticality of the mission of these systems in information warfare (IW). This paper highlights the distinguished characteristics and operational requirements of C4I systems which poses challenges to SwE process and practices. This paper also discuss the possible future research areas in order to enhance SwE process so that better software could drive these complex systems as required.

In this paper, concept mapping is suggested as a methodological catalyst for organizational learning. Concept mapping, by virtue of its psychological and sociological foundations, offers a way to simultaneously understand complex systems in terms of both intra- and inter-personal relationships. We posit that key stakeholders, when taken together, represent the organization as a bounded unit and set the stage for

Public enterprises have been an integral part of the involvement of the state in the economy for most of the 20th century. After 1980, privatization has been the dominant trend until the 2008-2010 economic crisis when new nationalizations happened.

Recent discovery of ADDL protein (Amyloid β-Derived Diffusible Ligand) allows the trigger mechanism causing Alzheimer's Disease (AD) to be described by principles of complex systems theory. This entails a teleological cosmology with inherent self-organized / anticipatory parameters introducing a life principle (élan vital) providing the action driving self-organization in autopoietic living systems. Interaction between this Noetic Field (élan vital) and brain is defined in terms of a Hamiltonian-Lagrange operator called the Noetic Effect. If mind/body interactions mediating this Noetic Effect drive the system away from equilibrium catastrophes causing protein misfolds may trigger the onset of AD. The discovery of ADDL also promises an AD vaccine.

This paper presents a model-based approach that combines the data-flow and object-oriented computing paradigms to model embedded systems. The rationale behind the approach is that both views are important for modelling purposes in embedded systems environments, and thus a combined and integrated usage is not only useful, but also fundamental for developing complex systems. We also show that by using models we were able to implement automated transformations between different views of the system under design. We exemplify the approach with an IPv6 router case study.

Stimuler la creativite demeure un enjeu majeur pour soutenir l’innovation. Depuis les travaux theoriques fondateurs des annees 1950-1960, il existe aujourd’hui un grand nombre d’outils, de methodes, et de guides d’aide au choix diffuses parmi les praticiens. Cependant, les entreprises font aujourd’hui face a une telle complexite, a la fois technique et organisationnelle, que les outils et methodes traditionnellement utilises arrivent a leurs limites et manquent d’efficacite. Non seulement nous manquons encore d’une theorie fondamentale de la creativite qui fasse consensus, mais la recherche dans ce domaine manque souvent de pertinence en termes de transfert dans la pratique et d’adequation avec les besoins pragmatiques industriels. Cette these explore comment l'approche systemique permet d’etudier la creativite afin de mettre en evidence de nouveaux moyens de la stimuler dans des contextes industriels complexes. Cette approche nous a permis de synthetiser les mecanismes de la cr...

Resource allocation in complex real-time computer systems (RTCSs) cannot be adequately handled by straightforward extensions of the CPU and peripheral device scheduling techniques used in non-RTCSs. Rather, all the resources including CPUs, ...

We develop a geometric approach to complexity based on the principle that complexity requires interactions at different scales of description. Complex systems are more than the sum of their parts of any size, and not just more than the sum of their elements. Using information geometry, we therefore analyze the decomposition of a system in terms of an interaction hierarchy. In mathematical terms, we present a theory of complexity measures for finite random fields using the geometric framework of hierarchies of exponential families. Within our framework, previously proposed complexity measures find their natural place and gain a new interpretation.

Nanotechnology, taken to its full three-dimensional potential, will place within the volume of a cube of sugar systems of vast complexity that far exceed the quantitative and qualitative capabilities of today's largest supercomputers. Currently, the uncertainty and imprecision of the real world is tamed, rigidly fixed, by addressable, digital techniques and the careful orchestration of digital patterns within our machines. How to handle the interaction between our digitally implemented systems and continuous, disorganized nature is a key question. NASA is currently researching ways to move beyond autonomy implemented as bruteforce control over every degree of freedom we can discover in our systems. Our systems operate in natural environments: inhumanly harsh, unfamiliar, unknown, and uncontrolled environments. Nature often surprises us, and so we turn to natural systems for clues about how to make massively complex systems more robust, reliable, and truly autonomous. Turning to Computer Science we draw on what we've learned about multi-agent systems running continuously and autonomously to understand information flow at the highest semantic levels. From physics we recall that the behaviors of systems may often be enumerated in a basis of fundamental behaviors. Non-linear physics contains clues about how to connect the physical world with the patterns of electric signals that make up the soft, information component of the systems. Genetics and control theory instruct how to handle long and short-term feedbacks throughout the system. Chemistry and biology provide important guiding principles governing system functions. We touch on our first experiments with Neural Basis Functions (NBF), a hybrid hardware/software construct that is a key component in Super Micro Autonomous Reconfigurable Technology (SMART) enabled systems architectures.

Each complex network (or class of networks) presents specific topological features which characterize its connectivity and highly influence the dynamics of processes executed on the network. The analysis, discrimination, and synthesis of complex networks therefore rely on the use of measurements capable of expressing the most relevant topological features. This article presents a survey of such measurements. It includes general considerations about complex network characterization, a brief review of the principal models, and the ...

The Nature Conservancy (TNC) and its partners are attempting to restore the riparian ecosystem of the Sacramento River over ~100 river miles, from Red Bluff to Colusa. To evaluate baseline ecosystem conditions, determine how the system is responding to current management practices (including restoration efforts) and better define current threats, TNC is collaborating with scientists from academic institutions, state and federal agencies, and other non-profit organizations. Our scientific investigations combine broad-based monitoring and focused research. Monitoring a wide range of biological, physical and chemical parameters helps us track system dynamics, and conducting focused research allows us to resolve key uncertainties concerning ecosystem function. In this paper we introduce important studies that are currently underway and identify future research needs. Only through comprehensive scientific investigation and coordinated effort will we achieve our goal of restoring ecosyste...

As plant nutrition issues are redefined by society, new applications emerge for a basic understanding of nutrient use efficiency in soil-plant processes to avoid excess on rich soils as commonly found in the temperate zone and make the best of it under access-limited conditions common in the tropics. The main challenge of plant nutrition may be to increase the width of the domain between the access and excess frontiers, rather than to define a single' economic optimum' point. Two approaches are discussed to widen this domain: the technical paradigm of precision farming and the ecological analogue approach based on filter functions and complementarity of components in mixed plant systems. Current understanding of plant nutrition, largely focused on monocultural situations, needs to be augmented by the interactions that occur in more complex systems, including agroforestry and intercropping as these may form part of the answer in both the excess and shortage type of situation. Simulations with the WaNuLCAS model to explore the concepts of a 'safety-net' for mobile nutrients by deep rooted plants suggested a limited but real opportunity to intercept nutrients on their way out of the system and thus increase nutrient use-efficiency at the system level. The impacts of rhizosphere modification to mobilize nutrients in mixed-species systems were shown to depend on the degree of synlocation of roots of the various plant components, as well as on the long-term replenishment of the nutrient resources accessed. In conclusion, the concepts and tools to help farmers navigate between the scylla of access and the charibdis of excess problems in plant nutrition certainly exist, but their use requires an appreciation of the site-specific interactions and various levels of internal regulation, rather than areliance alone on genetic modification of plants aimed at transferring specific mechanisms out of context.

Consanguinity or inter-cousin marriage is a phenomenon quite prevalent in certain regions around the globe. Consanguineous parents have a higher risk of having offspring with congenital disorders. It is difficult to model large scale consanguineous parental populations because of disparate cultural issues unique to regions and cultures across the globe. Although consanguinity has previously been studied as a social problem, it has not been modeled from a biological perspective. Discrete Event System Specification (DEVS) is a powerful modeling formalism for the study of intricate details of real-world complex systems. In this paper, we have developed a DEVS model to get an insight into the role of consanguineous marriages in the evolution of congenital disorders in a population. As proof-of-concept, we further developed a consanguinity simulation model in Simio simulation software. Simulation results validated using population growth data show the effectiveness of this approach in the modeling of consanguinity in populations.

When prototyping the requirement specifications of a large and complex system, it is very dificult to express them in a single model containing all the features. It is often disastrous i f the requirement specifications are prototyped in a single level or single window of a single model. Hence multimodel-based hiemrchical requirement specifications are desirable in order to fully specify large and complex systems. But multimodel-based hierarchical requirement specifications tools are then confronted with verification problems for inter-model consistency and syntactic correctness. W e introduce a predefined graphical structural syntax checker called Model Hierarchy Definition (MHD) which provides interactive hierarchy syntax checking during modeling the structured requirement specijications and predefined lowest level graphical formalisms called Model Hierarchy Model (MHM), defining the meta rules, the graphical diagramming entity and the hierarchical relationship for MHD embedding in the prototyping models. Having MHD and the MHM in the prototyping environment, one obtains higher quality structured requirement specifications when building hierarchical multimodel-based prototypes for complex system analysis, and greatly reduces the prototyping time and costs.

Electronic noses are complex systems built around an array of chemical sensors and designed to mimic the human olfactory system in a wide area of applications. Such systems , and in particular those designed for research applications, utilize a large number of sub-systems for chemical sampling control, for signal generation and acquisition, and for data manipulation. The activity of each sub-system must be strictly synchronized with the activity of the other systems, and a repetitive set-up is often required. This paper describes a toolbox of virtual instruments developed for research purposes and based on a laboratory electronic nose including commercial instrumentation and custom electronics. The toolbox consists of several virtual instruments, allowing the implementution of the different measurement techniques that are commonly used in this research field. What follows describes an integrated system that automatically controls the composition of the mixture under analysis, provides set-up for both the instrumentation and the custom electronics, and performs the selected class of algorithms for feature extraction, datu dimensionality reduction and classification. Assigning repetitive tasks to virtual instruments controlling the entire system gives the possibility to avoid the presence of errors due to the human control. Moreover, thanks to this approach it is possible to hide, at the user level, the data flow between measurement system and data analysis algorithms, giving the possibility to focus the attention only on the results of the analysis and on the optimizution of the analysis method.

Nitrogen fertilization and winter pruning are commonly used to control crop production in peach [Prunus persica (L.) Batsch] orchards. They are also known to affect the dynamics of Myzus persicae (Sulzer) (Homoptera: Aphididae) aphid populations via bottom-up regulation processes. Interactions between crops and pests can cause complex system behaviour in response to management practices. An integrated approach will therefore improve the understanding of the effects of these two cultural practices on aphid and peach performances.

This paper describes the development of a generalized agent -based simulation tool for studying manpower and personnel management behaviors. The subject matter of the simulation are complex organizational behaviors found within Uni ted States Navy Manpower and Personnel processes. Behavior of such a complex system is typically associated with a hierarchi- cal structure in which the lowest level agents are

In this paper, we present a summary of our work on highly photostable supramolecular ruthenium complexes, which may be incorporated into more complex systems for artificial solar energy conversion. We have used supramolecular chemistry and photochemistry to synthesize highly photostable ruthenium bipyridine cnronates and a bipyridazine podate complex and to enhance photoelectron-transfer reactions in physical model systems for artificial photosynthesis.

We survey and extend the work on the paradigm called "computing by observing". Its central feature is that one considers the behavior of an evolving system as the result of a computation. To this purpose an external observer records this behavior. In this way, several computational trade-offs between the observer and the observed system can be determined. It has turned out that the observed behavior of computationally simple systems can be very complex, when an appropriate observer is used. For example, a restricted version of context-free grammars with regular observers suffices to obtain computational completeness. As a second instantiation presented here, we apply an observer to sticker systems, an abstract model of DNA computing. Finally, we introduce and investigate the case where the observers can read only one measure of the observed system (e.g., mass or temperature) modeling in this way, limitations in the observation of real physical systems. Finally a research perspective on the topic is presented.

What can enhance the resilience of communities, and can collaborative forms of planning play any role in such an effort? To identify the potential contributions to resilience of collaborative planning approaches and tools, it is important to understand the mechanisms underlying various threats to community integrity, and how individuals and communities react to such threats. These mechanisms can be examined from three perspectives, all related to the individual decisions of community members as well as to the ways in which they come together to make joint decisions regarding their complex physical and societal environments: individual decisions, individuals' and communities' ability to anticipate at least some of the consequences of others' actions or of natural disasters, and the effect on our ability to make resilience-related decisions in a context of increasing complexity. This article examines resilience as rooted in these three aspects -how individuals make decisions, obstacles to effective anticipation, and organizational complexity. It derives recommendations for how communicative planning and collaborative tools might compensate for individual and joint decision deficiencies to enhance resilience.

The model of inclined seam excavation is established acc ording to the deformation characteristics of inclined seam and the principles of FEA. It carried out numerical s imulation method to research rock mass movement, surface subsidence and distribution of stress, which simulated excavat ion with the ANSYS software, at the same time the basi c characteristics of rock movement and the correlative par ameters of surface subsidence are obtained. The ANSYS software can not only compute the deformation mechanism of surface subsidence, but also draw up the distribution contours of stress, the distribution contours of horizontal displace and vertical subsidence. The computing model visuall y displays the deformation and stress distribution of the o verburden rock board, coal strata and lower rock board. The deformation mechanism of surface subsidence provides a refe rence for inclined seam excavation under the building. The underground excavation of mine is the huge and complex system eng...

Landscape classification is a demanding task,mainly because of andscape's holistic nature. Landscape experts are able to intuitively recognize landscape units which, regarding the morphological and physical factors, prove unified and homogeneous. But with such »gestalt « perception only those landscape units can be recognized that differ from the wider area and are evidently distinguishable. The classification of usually smooth and fuzzy passages between them often presents a problem. Another frequent approach to landscape classification is a clear and repeatable parametric approach. Landscape units are defined by simple combination of physical factors. But landscape is too complex system for such simplification. In search of new methods of landscape classification the usability of artificial neural networks was tested. Their application was based on landscape samples that experts identified in the area of »Karst landscape of the interior of Slovenia « and classified into 7 land...

A well-known problem in complex cognition is the so-called dynamic stocks and flows task (DSF). The challenge in this task is to control different flows, e.g. the inflows and outflows of water to a tank, towards a specified goal configuration, i.e. a certain amount of water in the tank. The problem is that some flows are exogenously controlled with a hidden dynamic. These flows need to be counterbalanced by setting endogenous flows. Since the dynamic underlying the hidden flows can be any computable function, this task can be classified as computationally complex. Psychological findings show that humans have difficulties in dealing with such dynamic systems. In this article, we present a formal generalization of this task and present a computational approach for solving such tasks as a first step towards an assistance system for complex system control.

Small-world networks are the focus of recent interest because they appear to circumvent many of the limitations of either random networks or regular lattices as frameworks for the study of interaction networks of complex systems. Here, we report an empirical study of the statistical properties of a variety of diverse real-world networks. We present evidence of the occurrence of three classes of small-world networks: (a) scale-free networks, characterized by a vertex connectivity distribution that decays as a power law; (b) broad-scale networks, characterized by a connectivity distribution that has a power-law regime followed by a sharp cut-off; (c) single-scale networks, characterized by a connectivity distribution with a fast decaying tail. Moreover, we note for the classes of broad-scale and single-scale networks that there are constraints limiting the addition of new links. Our results suggest that the nature of such constraints may be the controlling factor for the emergence of different classes of networks.

The waveform data, which is gathered during digital simulation of large and complex systems easily fill up huge amounts of disk space on the simulation computer. This is specially true for many deep-submicron designs. Hence, we developed a set of algorithms and techniques which can be used to efficiently compress digital waveforms without losing any significant information from the original data. Experimental results show that compression ratios of up to 300 compared to a original VCD formatted file can be achieved.

The current trends in video surveillance systems aim to incorporate mechanisms that understand and remember the activity in a scene to make decisions. These decision modules have as input the object trajectories in a scene resulting from the treatment of the images captured by a video camera. In this paper we propose a novel industrial supervision system for complex multivariable processes that incorporates this decision module. The scenario in this case does not come from the treatment of a video image sequences but from the projection of process variables on a 2D plane using dimension reduction techniques.

For a long time, one of the major research goals in the computer science research community has been to raise the level of abstraction power of specification languages/programming languages. Many specification languages and formalisms have been invented, but unfortunately very few of those are practically useful, due to limited computer support of these languages and/or inefficient implementations. Thus, one important goal is executable specification languages of high abstraction power and with high performance, good enough for practical usage and comparable in execution speed to hand implementations of applications in low-level languages such as C or C++. In this paper we briefly describe our work in creating efficient executable specification languages for two application domains. The first area is formal specification of programming language semantics, whereas the second is formal specification of complex systems for which we have developed an object-oriented mathematical modeling language called Modelica, including architectural support for components and connectors. Based on these efforts, we are currently working on a unified equation-based mathematical modeling language that can handle modeling of items as diverse as programming languages, computer algebra, event-driven systems, and continuous-time physical systems. The key unifying feature is the notion of equation. In this paper we describe the design and implementation of the unified language. A compiler implementation is already up and running, and used for substantial applications.

Fractal measurements using the Cantor's dust method in a linear one-dimensional analysis mode were made on the fracture patterns revealed on two-dimensional, planar surfaces in four granites. This method allows one to conclude that: (1) The fracture systems seen on two-dimensional surfaces in granites are consistent with the part of fractal theory that predicts a repetition of patterns on different scales of observation, self similarity. Fractal analysis gives essentially the same values of D on the scale of kilometres, metres and centimetres (five orders of magnitude) using mapped, surface fracture patterns in a Sierra Nevada granite batholith (Mt. Abbot quadrangle, Calif.). (2) Fractures show the same fractal values at different depths in a given batholith. Mapped fractures (main stage ore veins) at three mining levels (over a 700 m depth interval) of the Boulder batholith, Butte, Mont. show the same fractal values although the fracture disposition appears to be different at different levels. (3) Different sets of fracture planes in a granite batholith, Central France, and in experimental deformation can have different fractal values. In these examples shear and tension modes have the same fractal values while compressional fractures follow a different fractal mode of failure. The composite fracture patterns are also fractal but with a different, median, fractal value compared to the individual values for the fracture plane sets. These observations indicate that the fractal method can possibly be used to distinguish fractures of different origins in a complex system. It is concluded that granites fracture in a fractal manner which can be followed at many scales. It appears that fracture planes of different origins can be characterized using linear fractal analysis.

Local assortativity has been recently proposed as a measure to analyse complex networks. It has been noted that the Internet Autonomous System level networks show a markedly different local assortativity profile to most biological and social networks. In this paper we show that, even though several Internet growth models exist, none of them produce the local assortativity profile that can be observed in the real AS networks. We introduce a new generic growth model which can produce a linear local assortativity profile similar to that of the Internet. We verify that this model accurately depicts the local assortativity profile criteria of Internet, while also satisfactorily modelling other attributes of AS networks already explained by existing models.

Software understanding (for documentation, maintenance or evolution) is one of the longest-standing problems in Computer Science. The use of "high-level" programming paradigms and object-oriented languages helps, but fundamentally remains far from solving the problem. Most programming languages and systems have fallen prey to the assumption that they are supposed to capture idealized models of computation inspired by deceptively simple metaphors such as objects and mathematical functions. Aspect-oriented programming languages have made a significant break through by noticing that, in many situations, humans think and describe in crosscutting terms. In this paper we suggest that the next break through would require looking even closer to the way humans have been thinking and describing complex systems for thousand of years using natural languages. While natural languages themselves are not appropriate for programming, they contain a number of elements that make descriptions concise, effective and understandable. In particular, natural languages referentiality is a key factor in supporting powerful program organizations that can be easier understood by humans.

... for that taking selected ordering parameters as input is much efficient for modeling. ... Taleb-Bendiab, “Performance Evaluation for Self-Healing Distributed Services and Fault Detection Mechanisms,” Journal ... 4].M. Steinder and AS Sethi, “A Survey of Fault Localization Techniques ...

We have revised our analysis of the SPIRE observations of 2MASSW J1207334-393254 (2M1207). Recent PACS observations show a bright source located ∼25 ′′ east of 2M1207. There are issues in terms of the detection/non-detection of the bright source when comparing the Spitzer, WISE, and PACS observations. It is apparently inconsistent, perhaps due to variability or low signal-to-noise of the data. We have looked into the possible misidentification of the target, and have revised the measured SPIRE fluxes and the disc parameters for 2M1207. We have also reviewed which among the various formation mechanisms of this system would still be valid.

We investigate the properties of correlation based networks originating from economic complex systems, such as the network of stocks traded at the New York Stock Exchange (NYSE). The weaker links (low correlation) of the system are found to contribute to the overall connectivity of the network significantly more than the strong links (high correlation). We find that nodes connected through strong links form well defined communities. These communities are clustered together in more complex ways compared to the widely used classification according to the economic activity. We find that some companies, such as General Electric (GE), Coca Cola (KO), and others, can be involved in different communities. The communities are found to be quite stable over time. Similar results were obtained by investigating markets completely different in size and properties, such as the Athens Stock Exchange (ASE). The present method may be also useful for other networks generated through correlations.

This article presents a constrained review of human factors issues relevant to adaptive automation (AA), including designing complex system interfaces to support AA, facilitating human-computer interaction and crew interactions in adaptive system operations, and considering workload associated with AA management in the design of human roles in adaptive systems. Unfortunately, these issues have received limited attention in earlier reviews of AA. This work is aimed at supporting a general theory of human-centered automation advocating humans as active information processors in complex system control loops to support situation awareness and effective performance. The review demonstrates the need for research into user-centered design of dynamic displays in adaptive systems. It also points to the need for discretion in designing transparent interfaces to facilitate human awareness of modes of automated systems. Finally, the review identifies the need to consider critical human-human interactions in designing adaptive systems. This work describes important branches of a developing framework of AA research and contributes to the general theory of human-centered automation.