MultiAspect Graphs: Algebraic representation and algorithms

We present the algebraic representation and basic algorithms for MultiAspect Graphs (MAGs). A MAG is a structure capable of representing multilayer and time-varying networks, as well as higher-order networks, while also having the property of being isomorphic to a directed graph. In particular, we show that, as a consequence of the properties associated with the MAG structure, a MAG can be represented in matrix form. Moreover, we also show that any possible MAG function (algorithm) can be obtained from this matrix-based representation. This is an important theoretical result since it paves the way for adapting well-known graph algorithms for application in MAGs. We present a set of basic MAG algorithms, constructed from well-known graph algorithms, such as degree computing, Breadth First Search (BFS), and Depth First Search (DFS). These algorithms adapted to the MAG context can be used as primitives for building other more sophisticated MAG algorithms. Therefore, such examples can be seen as guidelines on how to properly derive MAG algorithms from basic algorithms on directed graph. We also make available Python implementations of all the algorithms presented in this paper.Comment: 59 pages, 6 figure

Algorithmic Networks: central time to trigger expected emergent open-endedness

This article investigates emergence and complexity in complex systems that can share information on a network. To this end, we use a theoretical approach from information theory, computability theory, and complex networks. One key studied question is how much emergent complexity (or information) arises when a population of computable systems is networked compared with when this population is isolated. First, we define a general model for networked theoretical machines, which we call algorithmic networks. Then, we narrow our scope to investigate algorithmic networks that optimize the average fitnesses of nodes in a scenario in which each node imitates the fittest neighbor and the randomly generated population is networked by a time-varying graph. We show that there are graph-topological conditions that cause these algorithmic networks to have the property of expected emergent open-endedness for large enough populations. In other words, the expected emergent algorithmic complexity of a node tends to infinity as the population size tends to infinity. Given a dynamic network, we show that these conditions imply the existence of a central time to trigger expected emergent open-endedness. Moreover, we show that networks with small diameter compared to the network size meet these conditions. We also discuss future research based on how our results are related to some problems in network science, information theory, computability theory, distributed computing, game theory, evolutionary biology, and synergy in complex systems.Comment: This is a revised version of the research report no. 4/2018 at the National Laboratory for Scientific Computing (LNCC), Brazi

Model predictive control of a free piston compressor/expander with an integrated linear motor/alternator

Linear positive displacement machines are becoming increasingly more attractive for applications that are normally known as unconquerable niches of rotary and scroll machines. Free-piston machines are characterized by the absence of a crank mechanism, since there is a direct transformation of electrical energy into the piston movement. From the point of view of manufacturing, these machines benefit from a higher robustness and reliability because of less mechanical components involved and reduced frictional losses associate with a conventional crank mechanism. However, the major challenge in replacing the rotary machines by linear ones is a lower efficiency at lower speeds which is unavoidable because of the nature of linear motion: continuous operation means a reciprocating movement within a stroke length with significantly long periods of acceleration and deceleration when the speed is far from its optimal value. However, the advantage of free-piston machines is the fact that the motion profile is freely configurable within physical constraints, which provides a possibility to optimize the speed given the efficiency map of particular linear motor. While the methods and results of the efficiency assessment for rotary machines are widely available, there is a lack of these analyses for linear machines. The current study provides in-depth analyses of a double-coil iron core linear motor also acting as a generator

Solar heat driven water circulation and aeration system for aquaculture

The proposed design concept of water aeration and updraft circulation in aquaculture is based on the Organic Rankine Cycle (ORC) technology and uses a solar energy absorbed by a floating collector. The pressure required for the aerator is created by evaporating a working fluid and optimized for an average depth of a pond. The working pressure is defined by the maximum achievable temperature of the working fluid. The condensing heat is rejected at a certain depth with the lowest temperature and drives the convective circulation. A prototype is designed by using common materials and off-the-shelf components to ensure maintenance-free and proper capacity to fulfil the needs of an average or a small aquaculture farm: the working fluid in the working chamber evaporates increasing in volume and pumping air out of the vessel as well as the expanded working fluid in the second working chamber. The working fluid is cooled down in the condenser which is submerged into the pond and it is condensed while decreasing in volume. The new design can perform multiple cycles per day increasing the volume of pumped air. In order to make the operation of this unit possible during the night, a heat buffer with a phase changing material (PCM) is used. A parametric study of suitable working fluids and PCMs has been performed in order to select the most appropriate combination for the target applications

A Unifying Model for Representing Time-Varying Graphs

Graph-based models form a fundamental aspect of data representation in Data Sciences and play a key role in modeling complex networked systems. In particular, recently there is an ever-increasing interest in modeling dynamic complex networks, i.e. networks in which the topological structure (nodes and edges) may vary over time. In this context, we propose a novel model for representing finite discrete Time-Varying Graphs (TVGs), which are typically used to model dynamic complex networked systems. We analyze the data structures built from our proposed model and demonstrate that, for most practical cases, the asymptotic memory complexity of our model is in the order of the cardinality of the set of edges. Further, we show that our proposal is an unifying model that can represent several previous (classes of) models for dynamic networks found in the recent literature, which in general are unable to represent each other. In contrast to previous models, our proposal is also able to intrinsically model cyclic (i.e. periodic) behavior in dynamic networks. These representation capabilities attest the expressive power of our proposed unifying model for TVGs. We thus believe our unifying model for TVGs is a step forward in the theoretical foundations for data analysis of complex networked systems.Comment: Also appears in the Proc. of the IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA'2015

Algorithmic information and incompressibility of families of multidimensional networks

This article presents a theoretical investigation of string-based generalized representations of families of finite networks in a multidimensional space. First, we study the recursive labeling of networks with (finite) arbitrary node dimensions (or aspects), such as time instants or layers. In particular, we study these networks that are formalized in the form of multiaspect graphs. We show that, unlike classical graphs, the algorithmic information of a multidimensional network is not in general dominated by the algorithmic information of the binary sequence that determines the presence or absence of edges. This universal algorithmic approach sets limitations and conditions for irreducible information content analysis in comparing networks with a large number of dimensions, such as multilayer networks. Nevertheless, we show that there are particular cases of infinite nesting families of finite multidimensional networks with a unified recursive labeling such that each member of these families is incompressible. From these results, we study network topological properties and equivalences in irreducible information content of multidimensional networks in comparison to their isomorphic classical graph.Comment: Extended preprint version of the pape

Insights from Industry Leaders: A Maturity Model for Strengthening Communication Measurement and Evaluation

Much scholarship has been devoted to identifying barriers that prevent the advancement of communication measurement and evaluation. This research focuses on the characteristics, objectives, and practices of chief communication officers (CCOs) with successful measurement and evaluation programs. Three key dimensions of practice emerged from in-depth interviews: communication executives’ measurement practices and evaluation programs were used to adjust communication strategies; were aligned with other business units; and were integrated with business priority plans. Interviewees also focused on the ability of communication measurement practices and evaluation programs to provide insights for executives, to align communication with the work of other business units, and to connect the organization with the outside environment and stakeholders. This study extends strategic communication scholarship by discussing how overcoming barriers and advancing measurement and evaluation work relates to roles adopted by organizational leaders. This article also offers a preliminary, scalable maturity model that aids in the development, formalization, and optimization of strategic communication measurement and evaluation. This study demonstrates the capacity for communication evaluation to overcome perceived barriers, realize appropriate stature with organizations, and grow communication functions accordingly