#539 PRESENTING A MODEL OF KNOWLEDGE MANAGEMENT COMPONENTS WITH ISM APPROACH
Authors: Houshang Taghizadeh and Mostafa Ziyaei H Ajipirlu
The present research has been carried out with the aim of presenting the model of systemic relationships among knowledge management components through interpretive structural modeling (ISM) technique. This paper is also helpful to understand the mutual influences of Knowledge Management Components (KMCs) and to identify them as supports of other KMC factors (by means of their driving power) and also those KMCs which are most influenced by other KMCs (by their dependence power). The interpretive structural modeling (ISM) methodology has been used to evolve the mutual relationships among these KMCs. The final results were obtained in the form of a classified model on 3 different levels based on the KMCs driving and dependence power with respect to the ISM methodology. The objective behind this classification is to analyze the driving power and dependence power of these KMCs for better understanding the relations among them.
#540 Endogenous Market Hub Sizes and Locations in a Virtual Economy
Authors: Milan van den Heuvel, Aaron Bramson and Koen Schoors
We are interested in the combined forces of resource distribution, market sizes, infrastructure, and transport costs on the existence and locations of trade hubs. To do this we analyze empirical data collected from a massively multiplayer game called EVE Online in which players engage in activities such as mining, industry, trade, shipping, exploration, politics, and conflict in an open-ended sandbox environment. The location and size/popularity of market hubs are determined endogenously by the players’ activity, and the game imposes many constraints on the players’ activities such as distance and the risk of piracy. We use this game as a testbed for competing theories on the optimal locations of regional hubs and their expected popularity.
The game includes regions of space with distinct safety levels and ownership rules. The high security space is monitored by non-player police but other economic activities are also regulated there and nobody can claim ownership of the systems. The “null security” space allows players to own and control the systems and their resources, but there is no non-player regulation or support making it much riskier to transport goods. We reveal how differences in land ownership, transportation time, and risk of loss effect the movement of goods and the establishment of markets.
The dataset is especially useful because the ownership of the available properties changes over time (through battles) and we can track changes in the traffic of goods (in total and specific to particular activities) and in the volumes/prices of market activities in response to specific perturbations. Because all these changes are generated through the behaviors of thousands of partially informed and independently motivated players we can effectively test the robustness of the explanatory theories.
#544 Fractal dynamics invariant to resolution scale transformations
Authors: Maricel Agop and Gabriel Ciobanu
Several models of complex systems taking into account both their functionality and structure are based on the assumption of the differentiability of the physical parameters describing them (such as density, momentum, energy). However, the differential method fails when facing the physical reality, namely with non- differentiable or non-integrable physical dynamics such as instabilities in the case of a complex fluid flow, instabilities that can generate both chaos and patterns.
It is necessary to introduce explicitly the resolution scale in the expressions of the physical variables describing these systems. This means that any dynamic variable dependent on both spatial coordinates and time (in a classical approach) becomes dependent also on the resolution scale. In other words, instead of working with parameters described through strictly non-differentiable functions, we work with approximations of these functions derived from different resolution scales. Therefore, any dynamic variable appears as limit of functions defined for a non-zero value of the scale resolution (the functions being non-differentiable for a null resolution scale, and differentiable for a non-zero resolution scale). Several applications from physics in which real determination is conducted at a finite resolution scale require the development of a new theory for which the motion laws invariant to spatio-temporal transformations are completed with resolution scale laws invariant at scale transformations. This kind of theory was developed in the frame of Scale Relativity Theory with an arbitrary constant fractal dimension in which the complexity of interactions is reflected by non-differentiability, and the motion constrained on continuous and differentiable curves are replaced with free motion without any constrains on continuous and non-differentiable curves in a fractal space. This happens over a new mathematical framework based on sets invariant to permutations (bijective transformations) working with infinite structures in terms of finitely supported objects (and so, named Finitely Supported Mathematics).
#547 Building Distributed Applications for Stressful Environments using Reversibility and Phase-Awareness
Authors: Ruma Paul and Peter Van Roy
Large-scale applications for mobile devices and Internet of Things live in stressful real-world environments: they have both continuous faults and bursts of high faults. Typical faults are node crashes, network partitions, and communication delays. We give a principled way to build applications that survive in such environments by using the concepts of Reversibility and Phase [1]. A system is Reversible if the set of operations it provides depends on its current fault rate and not on the history of the fault rate. Reversibility generalizes standard fault tolerance with nested fault models. When the fault rate goes outside one model then it is still inside the next model. Phase is a per-node property that gives a qualitative indication of what system operations are available at each node, given the current fault rate. Phase can be determined with no additional distributed computation. We present two case studies. First, we present a transactional key-value store built on a structured overlay network and we explain how to make it Reversible [2]. Second, we present a distributed collaborative graphic editor built on top of the key-value store, and we explain how to make it Phase-Aware, i.e., it optimizes its behavior according to a real-time observation of phase at each node using a Phase API. This shows the usefulness of Reversibility and Phase-Awareness for building large-scale Internet applications.
[1] Ruma R. Paul, Peter Van Roy, and Vladimir Vlassov. Reversible Phase Transitions in a Structured Overlay Network with Churn. NETYS 2016, Marrakech, Morocco, May 18-20, 2016.
[2] Ruma R. Paul, Peter Van Roy, and Vladimir Vlassov. Interaction Between Network Partitioning and Churn in a Self-Healing Structured Overlay Network. ICPADS 2015, Melbourne, Australia, Dec. 14-17, 2015.
#548 Complex network approach to explore the science subject synthesis examination
Authors: Lin Zhang, Tao Ren, Shijie Lu and Jinghua Xiao
Totally more than 40 thousand students' scores of the science subject synthesis in the college entrance examinations of Beijing are used to describe the relations between the three subjects of the test, which are Physics, Chemistry, and Biology. Moreover, the relations between 31 questions of the test are also investigated by the minimum spanning tree (MST) approach, and the dynamical threshold network approach. Our results show a clear relation between the three subjects, that is, Chemistry possesses the central role among the three, while Physics and Biology are at the marginal positions of the MST. Finally, the dynamical approach of the question-network reveals rich relations between knowledge of different subjects. Our method and results will shed light on the reform of examination evaluation.
Authors: Houshang Taghizadeh and Mostafa Ziyaei H Ajipirlu
The present research has been carried out with the aim of presenting the model of systemic relationships among knowledge management components through interpretive structural modeling (ISM) technique. This paper is also helpful to understand the mutual influences of Knowledge Management Components (KMCs) and to identify them as supports of other KMC factors (by means of their driving power) and also those KMCs which are most influenced by other KMCs (by their dependence power). The interpretive structural modeling (ISM) methodology has been used to evolve the mutual relationships among these KMCs. The final results were obtained in the form of a classified model on 3 different levels based on the KMCs driving and dependence power with respect to the ISM methodology. The objective behind this classification is to analyze the driving power and dependence power of these KMCs for better understanding the relations among them.
#540 Endogenous Market Hub Sizes and Locations in a Virtual Economy
Authors: Milan van den Heuvel, Aaron Bramson and Koen Schoors
We are interested in the combined forces of resource distribution, market sizes, infrastructure, and transport costs on the existence and locations of trade hubs. To do this we analyze empirical data collected from a massively multiplayer game called EVE Online in which players engage in activities such as mining, industry, trade, shipping, exploration, politics, and conflict in an open-ended sandbox environment. The location and size/popularity of market hubs are determined endogenously by the players’ activity, and the game imposes many constraints on the players’ activities such as distance and the risk of piracy. We use this game as a testbed for competing theories on the optimal locations of regional hubs and their expected popularity.
The game includes regions of space with distinct safety levels and ownership rules. The high security space is monitored by non-player police but other economic activities are also regulated there and nobody can claim ownership of the systems. The “null security” space allows players to own and control the systems and their resources, but there is no non-player regulation or support making it much riskier to transport goods. We reveal how differences in land ownership, transportation time, and risk of loss effect the movement of goods and the establishment of markets.
The dataset is especially useful because the ownership of the available properties changes over time (through battles) and we can track changes in the traffic of goods (in total and specific to particular activities) and in the volumes/prices of market activities in response to specific perturbations. Because all these changes are generated through the behaviors of thousands of partially informed and independently motivated players we can effectively test the robustness of the explanatory theories.
#544 Fractal dynamics invariant to resolution scale transformations
Authors: Maricel Agop and Gabriel Ciobanu
Several models of complex systems taking into account both their functionality and structure are based on the assumption of the differentiability of the physical parameters describing them (such as density, momentum, energy). However, the differential method fails when facing the physical reality, namely with non- differentiable or non-integrable physical dynamics such as instabilities in the case of a complex fluid flow, instabilities that can generate both chaos and patterns.
It is necessary to introduce explicitly the resolution scale in the expressions of the physical variables describing these systems. This means that any dynamic variable dependent on both spatial coordinates and time (in a classical approach) becomes dependent also on the resolution scale. In other words, instead of working with parameters described through strictly non-differentiable functions, we work with approximations of these functions derived from different resolution scales. Therefore, any dynamic variable appears as limit of functions defined for a non-zero value of the scale resolution (the functions being non-differentiable for a null resolution scale, and differentiable for a non-zero resolution scale). Several applications from physics in which real determination is conducted at a finite resolution scale require the development of a new theory for which the motion laws invariant to spatio-temporal transformations are completed with resolution scale laws invariant at scale transformations. This kind of theory was developed in the frame of Scale Relativity Theory with an arbitrary constant fractal dimension in which the complexity of interactions is reflected by non-differentiability, and the motion constrained on continuous and differentiable curves are replaced with free motion without any constrains on continuous and non-differentiable curves in a fractal space. This happens over a new mathematical framework based on sets invariant to permutations (bijective transformations) working with infinite structures in terms of finitely supported objects (and so, named Finitely Supported Mathematics).
#547 Building Distributed Applications for Stressful Environments using Reversibility and Phase-Awareness
Authors: Ruma Paul and Peter Van Roy
Large-scale applications for mobile devices and Internet of Things live in stressful real-world environments: they have both continuous faults and bursts of high faults. Typical faults are node crashes, network partitions, and communication delays. We give a principled way to build applications that survive in such environments by using the concepts of Reversibility and Phase [1]. A system is Reversible if the set of operations it provides depends on its current fault rate and not on the history of the fault rate. Reversibility generalizes standard fault tolerance with nested fault models. When the fault rate goes outside one model then it is still inside the next model. Phase is a per-node property that gives a qualitative indication of what system operations are available at each node, given the current fault rate. Phase can be determined with no additional distributed computation. We present two case studies. First, we present a transactional key-value store built on a structured overlay network and we explain how to make it Reversible [2]. Second, we present a distributed collaborative graphic editor built on top of the key-value store, and we explain how to make it Phase-Aware, i.e., it optimizes its behavior according to a real-time observation of phase at each node using a Phase API. This shows the usefulness of Reversibility and Phase-Awareness for building large-scale Internet applications.
[1] Ruma R. Paul, Peter Van Roy, and Vladimir Vlassov. Reversible Phase Transitions in a Structured Overlay Network with Churn. NETYS 2016, Marrakech, Morocco, May 18-20, 2016.
[2] Ruma R. Paul, Peter Van Roy, and Vladimir Vlassov. Interaction Between Network Partitioning and Churn in a Self-Healing Structured Overlay Network. ICPADS 2015, Melbourne, Australia, Dec. 14-17, 2015.
#548 Complex network approach to explore the science subject synthesis examination
Authors: Lin Zhang, Tao Ren, Shijie Lu and Jinghua Xiao
Totally more than 40 thousand students' scores of the science subject synthesis in the college entrance examinations of Beijing are used to describe the relations between the three subjects of the test, which are Physics, Chemistry, and Biology. Moreover, the relations between 31 questions of the test are also investigated by the minimum spanning tree (MST) approach, and the dynamical threshold network approach. Our results show a clear relation between the three subjects, that is, Chemistry possesses the central role among the three, while Physics and Biology are at the marginal positions of the MST. Finally, the dynamical approach of the question-network reveals rich relations between knowledge of different subjects. Our method and results will shed light on the reform of examination evaluation.
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