Management Of Complex Systems Research Articles

Not just a dollhouse: whatThe Sims2can teach us about women's IT learning

PurposeThe purpose of this paper is to describe how a popular computer game, The Sims2, engages players in computing practices that are foundational to information technology (IT) fluency, and to draw implications for engaging young people, particularly girls and women, in computer‐related learning.Design/methodology/approachThe analysis is framed within a conceptual perspective on learning as a process of acquiring situated understandings through participation in meaningful activity. The paper draws on two years of work with girls developing IT fluency through playing and modding The Sims. It also draws on interviews with adult women who are highly engaged in creating Sims content.FindingsThe paper identifies a set of practices inherent in Sims game play that are foundational to IT fluency: managing complex systems; cheating and glitching; tinkering with tools; and making, manipulating, and reasoning with spatial representations.Practical implicationsThe paper suggests how existing practices associated with games might be leveraged for the development of IT fluencies.Originality/valueThis study contributes to efforts aimed at rethinking how educators might conceptualize and support the development of IT fluencies. The paper offers new perspectives on the nature of IT fluency in the context of participatory culture and productive uses of new media.

Adaptive management for water quality planning - from theory to practice

Adaptive management has been promoted as a structured approach to learning in response to the uncertainty associated with managing complex systems. We developed and tested a protocol to guide an adaptive approach to water quality management in north-eastern Australia. The protocol articulates a framework for documenting uncertainties and performance expectations, negotiating feedback and anticipating iterative and transformative responses to future scenarios. A Water Quality Improvement Plan developed for the Tully–Murray catchment in the Great Barrier Reef region was used to test the protocol and three benefits of its use were identified. First, developing rigorous and timely monitoring and evaluation ensures that opportunities for iterative planning are realised. Second, anticipating future endogenous or exogenous changes to the plan enables the early initiation of actions to inform transformative planning responses. Finally, the protocol exposed the need to coordinate multi-scalar responses to tackle environmental knowledge and management uncertainties and assumptions. The protocol seeks to provide a practical translation of adaptive planning theory that will enable the benefits of adaptive management to be realised on the ground.

A Data Driven Prognostic Methodology without a Priori Knowledge

Nowadays systems are more and more complex, there is intense pressure to continuously reduce and eliminate costly, unscheduled maintenance of these systems. In such case, using physics-based damage model is not adequate in term cost/benefit analysis. While, recent technological advances of new sensors, coupled with robust processing algorithms offer an elegant and theoretically sound approach to Condition-Based Maintenance (CBM)/Prognostic Health Management of such complex systems. A new strategy based on forecasting of system degradation through a prognostic data-driven method is required. This paper introduces the development of a data-driven methodology to predict remaining useful life (RUL) of an unspecified complex system. Remaining useful life prediction is performed by recent machine learning techniques without including any system or domain specific informations. The solution is efficient and easy to implement and has the potential to be applicable to a variety of complex systems (automobiles, aerospace systems).

Dynamic Equilibrium Model for Spatial Auction Markets

Spatial equilibrium models are utilized for description of behavior and for management of complex systems containing many interacting elements, with taking into account their spatial distribution. We consider such a system of auction markets joined by transmission lines subject to joint balance and capacity flows constraints for a certain time period propose a primal-dual system of variational inequalities whose solutions yield an equilibrium trajectory of this system. A splitting type method is proposed to find a solution.

An overview of rolling stock and track monitoring systems and guidelines to provide safety of heavy and long train operation in the Russian Railways

An analysis of statistics on derailment of freight trains in the Russian Railways is carried out. Some results of simulation of vehicle—track interaction and experimental studies on moving of empty cars along track sections with diverse combination of horizontal and vertical irregularities are presented. An overview of guidelines to provide safety of heavy and long train operation is also presented. Technical means of rolling stock and track condition monitoring that is used and developing in the Russian Railways is described. Existing and developing wayside and on-board automated monitoring systems enabling continuous control over moving rolling stock and track are discussed. To provide safety of heavy haul operation, a general concept of a complex system of safety management based on monitoring of rolling stock and track is suggested.

Modularity concepts for the automotive industry: A critical review

Modularization has been used mostly in order for the management of complex systems to be simplified. In the present paper, the major evolutions of modularity concepts are reviewed in the case of the automotive industry. The current trend indicates that the next generation of vehicles will change from the integrated “unibody” with high production volume and low flexibility, to the modular ones of middle to high production volume and flexibility. Typical examples of different modular design approaches are presented and discussed. The paper includes the vehicle's body design requirements that have to be met in order for such a modular approach to be effective.

Tipping Points: Managing Complex Systems for Economic Development Success

In the paper, I argue that different management approaches in International Financial Institutions (IFIs) are receptive to different economic and theoretical paradigms, which in turn lead decision makers to different design of investment, and such differences in design and investment lead to significant differences in development success. Successful development efforts lead an economy to the point where it achieves a critical mass of structural transformation and tips to the side of a sustained growth process. The paper characterizes International Financial Institutions (IFIs, also known as MFIs or Multilateral development Finance Institutions) as planning oriented and politically dominated by their governance set-up. Developing economies are complex systems. The paper outlines the complex systems development paradigm. Designing investment interventions for complex systems requires decentralized, flexible and networked institutions equipped to explore a variety of development outcomes. Experimentation, trial and error, quick replication of successful prototype investment projects, exploration of alternatives when rapid feedback shows unsatisfactory results in the field, are the hallmarks of managing a complex system. The traditional approach by IFIs to managing development is likely to lead to inferior development outcomes, as the paper demonstrates with investment examples. One path to better development investment design is the institutional establishment of management tools in the form of evolutionary, complex systems models of economies that can inform realistic and rigorous decision making, and flanked by human resource incentives that stimulate competition for ideas and success.

Toward a Revolution in Transportation Operations: AI for Complex Systems

This article presents an parallel traffic management system for integrated control and management of urban transportation systems. This system's construction and operation are based on the ACP (artificial, computational, parallel) approach, which consists of modeling with artificial systems, analysis with computational experiments, and operation through parallel execution for control and management of complex systems with social and behavioral dimensions.

Factors determining soil nutrient distribution in a small-scaled watershed in the purple soil region of Sichuan Province, China

Determining soil nutrient distribution is critical to identify sites which are at risk of N and P loading. Equally important are determining factors that influence such distribution (e.g. land use, land management, topography, etc.). In this research, soil nutrient distribution and its influencing factors were studied in a small-scaled watershed in the purple soil region of Sichuan Province, China. The watershed is 1.3 km 2 with a complex land management system including agriculture and forestry. Surface soil samples (0–20 cm) from 48 sites within the watershed were collected in the spring of 1999 and analysed for chemical properties. When spatial distribution patterns of soil organic matter and soil nutrients were considered, several patterns were evident. Soil organic matter and total nitrogen coincided with high soil nutrients in the center of the watershed. Total phosphorus was linked to low soil nutrient contents on hilltops, while total potassium was characterized by low variability and high soil nutrient content throughout the watershed. Water-soluble nutrients in soils were highly variable throughout the watershed. Results of this study indicate that land use, topography and other variables play important roles in controlling the spatial distribution of most soil nutrients. However, the relative roles of these indices were nutrient specific. The relationship was therefore complex. Land use, silt, and sand content contributed to a high level of heterogeneity for soil organic matter and total nitrogen with the former being the dominant factor. Land use, particle size distribution (silt and sand) and topographic factors (slope and elevation) contributed to the variability of total phosphorus. However, particle size distribution and topographic factors were the dominant factors affecting total phosphorus. Elevation influenced the concentration of total potassium and land use controlled the concentration of dissolved phosphorous. No significant relationship was found between the studied characteristics and nitrate nitrogen.

Tipping Points: Managing Complex Systems for Economic Development Success

In the paper, I argue that different management approaches in International Financial Institutions (IFIs) are receptive to different economic and theoretical paradigms, which in turn lead decision makers to different design of investment, and such differences in design and investment lead to significant differences in development success. Successful development efforts lead an economy to the point where it achieves a critical mass of structural transformation and tips to the side of a sustained growth process. The paper characterizes International Financial Institutions (IFIs, also known as MFIs or Multilateral development Finance Institutions) as planning oriented and politically dominated by their governance set-up. Developing economies are complex systems. The paper outlines the complex systems development paradigm. Designing investment interventions for complex systems requires decentralized, flexible and networked institutions equipped to explore a variety of development outcomes. Experimentation, trial and error, quick replication of successful prototype investment projects, exploration of alternatives when rapid feedback shows unsatisfactory results in the field, are the hallmarks of managing a complex system. The traditional approach by IFIs to managing development is likely to lead to inferior development outcomes, as the paper demonstrates with investment examples. One path to better development investment design is the institutional establishment of management tools in the form of evolutionary, complex systems models of economies that can inform realistic and rigorous decision making, and flanked by human resource incentives that stimulate competition for ideas and success.

Special issue on computational intelligence agents

The intersection between Computational Intelligence and Agent technology opens new significant scenarios in many fields where the representation and management of complex systems play a fundamental role. In the formulation of Agent-based systems, the role of uncertainty is crucial for an efficient and coherent resolution of complex problems. Agents overcome classical programs thanks to their inner capabilities to be autonomous and to adapt their behavior with the changing of the environment where agents live and interact. This means that inevitably they meet uncertainty during their work, or in many cases, for the high complexity of the problem, the information they handle is (or needs to be) approximate. In recent years there has been a growing awareness that Computational Intelligence handling of uncertainty in agents is equally important as other features of agent paradigm. The objective of the proposed special issue is to highlight an ongoing research on computational intelligence agents and their applications on various domains. This special issue on computational intelligence agents receives thirteen papers, of which four papers have been accepted. This volume contains four papers that consider different aspects of perception based on the computational intelligent agents. The first paper HealthAgents: Distributed Multi-Agent Brain Tumour Diagnosis and Prognosis by Horacio Gonzalez-Velez, Mariola Mier, Margarida

Feedback Design for the Control of a Dynamic Multitasking System: Dissociating Outcome Feedback From Control Feedback

We distinguish outcome feedback from control feedback to show that suboptimal performance in a dynamic multitasking system may be caused by limits inherent to the information provided rather than human resource limits. Tardast is a paradigm for investigating human multitasking behavior, complex system management, and supervisory control. Prior research attributed the suboptimal performance of Tardast operators to poor strategic task management. We varied the nature of performance feedback in the Tardast paradigm to compare continuous, cumulative feedback (global feedback) on performance outcome with feedback limited to the most recent system state (local feedback). Participants in both conditions improved with practice, but those with local feedback performed better than those with global feedback. An eye gaze analysis showed increased visual attention directed toward the feedback display in the local feedback condition. Predicting performance in the control of a dynamic multitasking system requires understanding the interactions between embodied cognition, the task being performed, and characteristics of performance feedback. In the current case, at least part of what had been diagnosed as a deficit caused by limited cognitive resources has been shown to be data limited. Perfect outcome feedback can provide inadequate control feedback. Instances of suboptimal performance can be alleviated by better feedback design that takes into account the temporal dynamics of the human-system interaction.

Coordinated management of hardware and software self-adaptivity

Self-adaptivity is the capability of a system to adapt itself dynamically to achieve its goals. Self-adaptive systems will be widely used in the future both to efficiently use system resources and to ease the management of complex systems. The frameworks for self-adaptivity developed so far usually concentrate either on self-adaptive software or on self-adaptive hardware, but not both. In this paper, we propose a model of self-adaptive systems and we describe how to manage self-adaptivity at all levels (both hardware and software) by means of a decentralized control algorithm. The key advantage of decentralized control is in the simplicity of the local controllers. Simulation results are provided to show the main characteristics of the model and to discuss it.

Conceptual Model and Realization Methods of Autonomic Computing

自主计算是一个新兴的热点研究领域,旨在通过"技术管理技术"的手段隐藏系统管理复杂性,建立用户可指导的、状态觉察的和自适应的计算机系统.目前,自主计算的研究仍处于起步阶段,尚缺乏系统而成熟的理论体系.在阐明自主计算概念的基础上,提出一个自主计算概念模型.该模型刻画了自主元素和自主计算系统的基本工作机制和原理.以该模型为依据,概括性地提出了两类分别基于知识模型和数学模型的自主计算系统,分析它们的优点和不足.最后,给出了自主计算研究展望.;Autonomic computing is an emerging research hotspot, which aims at hiding system management complexity from human users by means of technologies managing technologies, to establish guidable, state-aware, and self-adaptive computer systems. Currently, the research of autonomic computing is still in its infancy, without systematic and mature theories. After clarifying the definition of autonomic computing, this paper proposes a conceptual model, which describes the basic working mechanisms and principles of autonomic elements and autonomic computing systems. On the basis of this model, two categories of autonomic computing systems based on knowledge model and mathematical model respectively are summarized and analyzed, with their advantages and disadvantages. Finally, the future research directions of autonomic computing are proposed.

Risk in Real TimeShouldering Risks: The Culture of Control in the Nuclear Power Industry. By Constance Perin. Princeton: Princeton University Press, 2005.

Previous articleNext article No AccessBooksRisk in Real Time Shouldering Risks: The Culture of Control in the Nuclear Power Industry. By Constance Perin. Princeton: Princeton University Press, 2005.Joseph MascoJoseph MascoDepartment of Anthropology, University of Chicago, 1126 E. 59th St., Chicago, IL 60637, U.S.A. ([email protected]). 5 XI 07 Search for more articles by this author Department of Anthropology, University of Chicago, 1126 E. 59th St., Chicago, IL 60637, U.S.A. ([email protected]). 5 XI 07PDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by Current Anthropology Volume 49, Number 3June 2008 Sponsored by the Wenner-Gren Foundation for Anthropological Research Article DOIhttps://doi.org/10.1086/528748 Views: 30Total views on this site PDF download Crossref reports no articles citing this article.

Findings from an Organizational Network Analysis to Support Local Public Health Management

We assessed the feasibility of using organizational network analysis in a local public health organization. The research setting was an urban/suburban county health department with 156 employees. The goal of the research was to study communication and information flow in the department and to assess the technique for public health management. Network data were derived from survey questionnaires. Computational analysis was performed with the Organizational Risk Analyzer. Analysis revealed centralized communication, limited interdependencies, potential knowledge loss through retirement, and possible informational silos. The findings suggested opportunities for more cross program coordination but also suggested the presences of potentially efficient communication paths and potentially beneficial social connectedness. Managers found the findings useful to support decision making. Public health organizations must be effective in an increasingly complex environment. Network analysis can help build public health capacity for complex system management.

Aide à la décision pour la conception de systèmes complexes. Une approche SMA

Management of complex systems (such as hospitals, cities, transportation systems) is concerned with many problems, among which the impact evaluation of a decision is. To do so, we propose that the decision maker interacts with a model of the organization. This action is similar with a player's one and makes possible immersion of the decision maker in a virtual environment rather close to the real environment. Thus environment objects must be able to react as realistically as possible. Within an Urban Traffic Systems that leads to produce a modeling and simulation environment with SimCity©-like graphics but with some advanced functionalities added for the design of networks and the management of the traffic. The graphic aspect has a huge importance within this domain. We propose to solve this problem using an approach that combines the facility of object oriented modeling with the power of behaviors description of the multiagent approach. This methodological framework includes the use of formal specifications enabling a model checking before its implementation.

Spatial equilibrium problems for auction type systems

At the present time rather a lot of spatial equilibrium models exist which are utilized for description of behavior and for management of complex systems containing many interacting elements, with taking into account their spatial distribution. Such models are greatly developed in economics where they usually describe systems of markets joined by transport communications within either perfect (in the sense of Walras) or imperfect (in the sense on Cournot–Bertrand) competition conditions (see, e.g., [1–3]). However, these kinds of competition are not sufficient for an adequate description of modern management mechanisms in economic systems. In particular, this is the case for systems related to natural monopolies in energy sectors where a state permits their privatization, but keeps certain tools for influence in this field, for instance, via the price policy (see, e.g., [4–6]). Since the optimal control of such a system requires consideration of both separate markets (participants) reactions and capacity and topology restrictions, the hierarchic (multilevel) optimization and game theory problems are usually utilized as suitable mathematical models. As a result, one must solve either very complicated global optimization problems having equilibrium constraints, or mixed integer programming problems. It is very difficult to find then efficient computational solution methods, especially for high-dimensional problems, which arise typically in applications.

Knowledge Management Systems Usage

Humans often seek input from others when solving complex problems and knowledge management systems (KMSs) support this activity by providing a computer-mediated approach to information sharing. However, if the content provided by the KMS is obsolete or incomplete, end-users may need to exert greater effort to detect these problems or they risk relying on poor inputs leading to less accurate decisions. As a result, most KMSs include rating schemes as part of the user interface designed to help users identify high-quality content. Rating schemes depend on current users rating the quality of the existing content, guiding subsequent users in their future content searches. However, specific ratings may be low in validity and not reflect the true content quality (unintentionally or intentionally). This study examines how rating scheme validity influences how users trade-off search and evaluation effort for decision-making accuracy. Results demonstrate that rating validity differentially influences how KMS search and evaluation effort relates to decision accuracy. The research findings provide insight into KMS user interface design and how end-users efficiently and effectively use the knowledge in KMSs to make decisions.

Lagomizing, Organic Integration, and Systems Emergency Wards: Innovative Practices in Managing Complex Systems Development Projects

In complex systems development, project management is a key factor for innovation, for bringing together system capabilities to actually working systems and taking them to the customer. The critical question then is: How can successful project management in this field be conceptualized, practiced, and understood? In the extant literature, there is a plethora of suggested tools for advanced planning and scheduling, for system decomposition and modularization, and for reducing interdependencies and avoiding errors. There is also a growing criticism of these “planning approaches,” suggesting various contingency and flexibility approaches, to reflect and adapt to complexity and change. This critique, however, tends to lack grounded suggestions for effective managerial practices and does not distinguish between general flexibility needs and specific project structures required to make complex systems development at all possible. This article centers on the development of large, complex systems with an empirical focus on the telecom industry. Key challenges here, it is argued, are to understand complexity, reduce complexity, and rapidly act on the consequences of complexity to ensure timely delivery of reliable and predictable systems to highly demanding customers. To cope with these challenges, a set of innovative practices has been developed within Ericsson, a world leader in mobile network systems. We focus on three such practices, which together represent examples of a “neo-realistic” approach to project management: (1) lagomizing, a top-down redefinition of project goals to reduce complexity and transform expectations; (2) organic integration, an articulation and visualization of a shared understanding of system capabilities; and (3) Systemakut, the Systems Emergency Ward, a real-time, high-visibility agora for managing integration, handling errors, and making swift decisions and in public. The study is based on a research methodology involving knowledge coproduction, where the team of authors represents both academic knowledge and practitioner experience of managing innovations in complex systems development projects.