Indirect ties in knowledge networks:a social network analysis with ordered weighted averaging operators

This PhD thesis analyses networks of knowledge flows, focusing on the role of indirect ties in the knowledge transfer, knowledge accumulation and knowledge creation process. It extends and improves existing methods for mapping networks of knowledge flows in two different applications and contributes to two stream of research. To support the underlying idea of this thesis, which is finding an alternative method to rank indirect network ties to shed a new light on the dynamics of knowledge transfer, we apply Ordered Weighted Averaging (OWA) to two different network contexts. Knowledge flows in patent citation networks and a company supply chain network are analysed using Social Network Analysis (SNA) and the OWA operator. The OWA is used here for the first time (i) to rank indirect citations in patent networks, providing new insight into their role in transferring knowledge among network nodes; and to analyse a long chain of patent generations along 13 years; (ii) to rank indirect relations in a company supply chain network, to shed light on the role of indirectly connected individuals involved in the knowledge transfer and creation processes and to contribute to the literature on knowledge management in a supply chain. In doing so, indirect ties are measured and their role as means of knowledge transfer is shown. Thus, this thesis represents a first attempt to bridge the OWA and SNA fields and to show that the two methods can be used together to enrich the understanding of the role of indirectly connected nodes in a network. More specifically, the OWA scores enrich our understanding of knowledge evolution over time within complex networks. Future research can show the usefulness of OWA operator in different complex networks, such as the on-line social networks that consists of thousand of nodes.

The value of indirect ties in citation networks:SNA analysis with OWA operator weights

This paper seeks to advance the theory and practice of the dynamics of complex networks in relation to direct and indirect citations. It applies social network analysis (SNA) and the ordered weighted averaging operator (OWA) to study a patent citations network. So far the SNA studies investigating long chains of patents citations have rarely been undertaken and the importance of a node in a network has been associated mostly with its number of direct ties. In this research OWA is used to analyse complex networks, assess the role of indirect ties, and provide guidance to reduce complexity for decision makers and analysts. An empirical example of a set of European patents published in 2000 in the renewable energy industry is provided to show the usefulness of the proposed approach for the preference ranking of patent citations.

Data Protection and Packet Mode in the Distributed Information Measurement and Control System for Research in Physics

The present paper is devoted to creation of cryptographic data security and realization of the packet mode in the distributed information measurement and control system that implements methods of optical spectroscopy for plasma physics research and atomic collisions. This system gives a remote access to information and instrument resources within the Intranet/Internet networks. The system provides remote access to information and hardware resources for the natural sciences within the Intranet/Internet networks. The access to physical equipment is realized through the standard interface servers (PXI, CАМАC, and GPIB), the server providing access to Ethernet devices, and the communication server, which integrates the equipment servers into a uniform information system. The system is used to make research task in optical spectroscopy, as well as to support the process of education at the Department of Physics and Engineering of Petrozavodsk State University.

Node centrality for continuous-time quantum walks

The study of complex networks has recently attracted increasing interest because of the large variety of systems that can be modeled using graphs. A fundamental operation in the analysis of complex networks is that of measuring the centrality of a vertex. In this paper, we propose to measure vertex centrality using a continuous-time quantum walk. More specifically, we relate the importance of a vertex to the influence that its initial phase has on the interference patterns that emerge during the quantum walk evolution. To this end, we make use of the quantum Jensen-Shannon divergence between two suitably defined quantum states. We investigate how the importance varies as we change the initial state of the walk and the Hamiltonian of the system. We find that, for a suitable combination of the two, the importance of a vertex is almost linearly correlated with its degree. Finally, we evaluate the proposed measure on two commonly used networks. © 2014 Springer-Verlag Berlin Heidelberg.

Capillary siphons and their application in the fuel delivery system of direct methanol fuel cells

The objective of the work is to develop a fuel delivery system for potable direct methanol fuel cell. Currently, one of the most fundamental limitations of direct methanol fuel cells is that the fuel supplied to the anode of the DMFC must be a very dilute aqueous methanol solution (usually 0.5∼1.5 M). If a DMFC is filled with a dilute aqueous methanol solution, the fuel cell operation time per refuel would be very short, which would considerably diminish the advantage of a DMFC over a conventional battery. To overcome this difficulty, a complex fuel delivery system based on the modern micro system technology was proposed by the author. The proposed fuel delivery system would include micro-pumps, a methanol sensor, and a control unit. The fuel delivery system adds considerable costs to the fuel cell system and consume considerable amount of electricity from the fuel cell, which in turn significantly reduces the net power output of the fuel cell. As a result, the DMFC would have tremendous difficulty to compete with the conventional battery technology in terms of costs and power output. ^ This work presents a novel passive fuel delivery system for direct methanol fuel cells. In this particular system, a methanol fuel and an aqueous methanol solution are stored separately in two containers and a wick is disposed between the two containers in a siphon fashion, with the container of the aqueous methanol solution communicating with the anode of the DMFC. Methanol is siphoned from the methanol container to the aqueous solution container in-situ when the methanol in the aqueous methanol solution is consumed during the operation of the fuel cell. Through a proper selection of the wick and the containers, the methanol concentration near the anode of the DMFC could be maintained within a preferable range. ^

Changing use and hydromorphological adjustment in a coastal lagoon–estuarine system, the Ria de Aveiro, Portugal

Today the Ria de Aveiro of northern Portugal has a hydromorphological regime in which river influence is limited to periods of flood. For most of the annual cycle, tidal currents and wind waves are the major forcing agents in this complex coastal lagoon–estuarine system. The system has evolved over two centuries from one that was naturally fluvially dominant to one that is today tidally dominant. Human influence was a trigger for these changes, starting in 1808 when its natural evolution was halted by the construction of a new inlet/outlet channel through the mobile sand spit that isolates it from the Atlantic Ocean. In consequence, tidal ranges in the lagoon increased rapidly from ~0.1 m to >1 m and continued to increase, as a result of continued engineering works and dredging, today reaching ~3 m on spring tides. Hydromorphological adjustments that have taken place include the deepening of channels, an increase in the area of inter-tidal flats, regression of salt marsh, increased tidal propagation and increased saline intrusion. Loss of once abundant submerged aquatic vegetation (SAV), due to increased tidal flows, exacerbated by increased recreational activities, has been accompanied by a change from fine cohesive sediments to coarser, mobile sediments with reduced biological activity.

Development and pharmacological evaluation of ropivacaine-2-hydroxypropyl-beta-cyclodextrin inclusion complex

Ropivacaine (RVC) is an enantiomerically pure local anesthetic (LA) largely used in surgical procedures, which presents physico-chemical and therapeutic properties similar to those of bupivacaine (BPV), but associated to less systemic toxicity This study focuses on the development and pharmacological evaluation of a RVC in 2-hydroxypropyl-beta-cyclodextrin (HP-P-CD) inclusion complex. Phase-solubility diagrams allowed the determination of the association constant between RVC and HP-beta-CD (9.46 M-1) and showed an increase on RVC solubility upon complexation. Release kinetics revealed a decrease on RVC release rate and reduced hemolytic effects after complexation. (onset at 3.7 mM and 11.2 mM for RVC and RVCHP-beta-CD, respectively) were observed. Differential scanning calorimetry (DSC), scanning electron microscopy (SEM) and X-ray analysis (X-ray) showed the formation and the morphology of the complex. Nuclear magnetic resonance (NMR) and job-plot experiments afforded data regarding inclusion complex stoichiometry (1:1) and topology. Sciatic nerve blockade studies showed that RVCHP-beta-CD was able to reduce the latency without increasing the duration of motor blockade, but prolonging the duration and intensity of the sensory blockade (p < 0.001) induced by the LA in mice. These results identify the RVCHP-beta-CD complex as an effective novel approach to enhance the pharmacological effects of RVC, presenting it as a promising new anesthetic formulation. (c) 2007 Elsevier B.V All rights reserved.

Método de análise de vulnerabilidade utilizando redes complexas : aplicação na rede de transporte aéreo brasileira

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, 2016.

Emergy analysis of a silvo-pastoral system, a case study in southern Portugal

The Mediterranean silvo-pastoral system known as Montado, in Portugal, is a complex land use system composed of an open tree stratum in various densities and an herbaceous layer, used for livestock grazing. Livestock also profit from the acorns, and the grazing contributes to avoid shrub encroachment. In the last 20 years, subsidies from the European Union have greatly promoted cattle rearing in this system and the introduction of heavy breeds, at the expense of sheep, goats or the native cattle breeds. The balance of the traditional system is thus threatened, and a precise assessment of the balance between the different components of the system, therefore is highly needed. The goal of this study was to gain a better under- standing of a Montado farm system with cattle rearing as the major economic activity by applying the emergy evaluation method to calculate indices of yield, investment, environmental loading and sustainability. By integrating different ecosystem components, the emergy evaluation method allows a comprehensive evaluation of this complex and multifunctional system at the scale of an individual farm. This method provides a set of indices that can help us understand the system and design management strategies that maximize emergy flow in the farm. In this paper, we apply the emergy evaluation method to a Montado farm with cattle rearing, as a way to gain a better understanding of this system at the farm scale. The value for the transformity of veal (2.66E?06 sej J-1) is slightly higher, when compared to other systems producing protein. That means that the investment of nature and man in this product was higher and it requires a premium price on the market. The renewa- bility for Holm Oaks Farm (49 %), lower than for other similar systems, supports the assumption that this is a farm in which, comparing with others, the number of purchased inputs in relation to renewable inputs provided by nature, is higher. The Emergy Investment Ratio is 0.91 for cattle rearing compared to a value of 0.49 for cork and 0.43 for firewood harvesting, making it clear that cattle rearing is a more labor demanding activity comparing with extractive activities as cork and firewood harvesting.

Modeling and Model Predictive Control of an Industrial Hydraulic System

This thesis aims to illustrate the construction of a mathematical model of a hydraulic system, oriented to the design of a model predictive control (MPC) algorithm. The modeling procedure starts with the basic formulation of a piston-servovalve system. The latter is a complex non linear system with some unknown and not measurable effects that constitute a challenging problem for the modeling procedure. The first level of approximation for system parameters is obtained basing on datasheet informations, provided workbench tests and other data from the company. Then, to validate and refine the model, open-loop simulations have been made for data matching with the characteristics obtained from real acquisitions. The final developed set of ODEs captures all the main peculiarities of the system despite some characteristics due to highly varying and unknown hydraulic effects, like the unmodeled resistive elements of the pipes. After an accurate analysis, since the model presents many internal complexities, a simplified version is presented. The latter is used to linearize and discretize correctly the non linear model. Basing on that, a MPC algorithm for reference tracking with linear constraints is implemented. The results obtained show the potential of MPC in this kind of industrial applications, thus a high quality tracking performances while satisfying state and input constraints. The increased robustness and flexibility are evident with respect to the standard control techniques, such as PID controllers, adopted for these systems. The simulations for model validation and the controlled system have been carried out in a Python code environment.

The non-equilibrium nature of culinary evolution

Food is an essential part of civilization, with a scope that ranges from the biological to the economic and cultural levels. Here, we study the statistics of ingredients and recipes taken from Brazilian, British, French and Medieval cookery books. We find universal distributions with scale invariant behaviour. We propose a copy-mutate process to model culinary evolution that fits our empirical data very well. We find a cultural 'founder effect' produced by the non-equilibrium dynamics of the model. Both the invariant and idiosyncratic aspects of culture are accounted for by our model, which may have applications in other kinds of evolutionary processes.

Network of recurrent events for the Olami-Feder-Christensen model

We numerically study the dynamics of a discrete spring-block model introduced by Olami, Feder, and Christensen (OFC) to mimic earthquakes and investigate to what extent this simple model is able to reproduce the observed spatiotemporal clustering of seismicity. Following a recently proposed method to characterize such clustering by networks of recurrent events [J. Davidsen, P. Grassberger, and M. Paczuski, Geophys. Res. Lett. 33, L11304 (2006)], we find that for synthetic catalogs generated by the OFC model these networks have many nontrivial statistical properties. This includes characteristic degree distributions, very similar to what has been observed for real seismicity. There are, however, also significant differences between the OFC model and earthquake catalogs, indicating that this simple model is insufficient to account for certain aspects of the spatiotemporal clustering of seismicity.

Automatic Network Fingerprinting through Single-Node Motifs

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.

Musical genres: beating to the rhythms of different drums

Online music databases have increased significantly as a consequence of the rapid growth of the Internet and digital audio, requiring the development of faster and more efficient tools for music content analysis. Musical genres are widely used to organize music collections. In this paper, the problem of automatic single and multi-label music genre classification is addressed by exploring rhythm-based features obtained from a respective complex network representation. A Markov model is built in order to analyse the temporal sequence of rhythmic notation events. Feature analysis is performed by using two multi-variate statistical approaches: principal components analysis (unsupervised) and linear discriminant analysis (supervised). Similarly, two classifiers are applied in order to identify the category of rhythms: parametric Bayesian classifier under the Gaussian hypothesis (supervised) and agglomerative hierarchical clustering (unsupervised). Qualitative results obtained by using the kappa coefficient and the obtained clusters corroborated the effectiveness of the proposed method.