Recovering Social Networks from Individual Attributes

One of the most important challenges of network analysis remains the scarcity of reliable information on existing connection structures. This work explores theoretical and empirical methods of inferring directed networks from nodes attributes and from functions of these attributes that are computed for connected nodes. We discuss the conditions, under which an underlying connection structure can be (probabilistically) recovered, and propose a Bayesian recovery algorithm. In an empirical application, we test the algorithm on the data from the European School Survey Project on Alcohol and Other Drugs.

Identifying Critical Financial Networks of the DJIA: Toward a Network-Based Index

The purpose of this article is twofold. First, we introduce a novel definition of financial networks obtained from time series data from the stock market. Second, we demonstrate that these networks can be used as an index with the property to reflect critical states of the market, respectively, crashes sufficiently. Our work aims to advocate a network-based analysis in the context of the stock market, because such a collective phenomenon can not only be economically described by networks but also analyzed as demonstrated in this article. (C) 2010 Wiley Periodicals, Inc. Complexity 16: 24-33, 2010

Phylogeographic analysis of North American populations of the parasitic herbaceous plant Monotropa hypopitys reveals a complex history of range expansion from multiple late glacial refugia

Aim We carried out a phylogeographic study across the range of the herbaceous plant species Monotropa hypopitys L. in North America to determine whether its current disjunct distribution is due to recolonization from separate eastern and western refugia after the Last Glacial Maximum (LGM). Location North America: Pacific Northwest and north-eastern USA/south-eastern Canada. Methods Palaeodistribution modelling was carried out to determine suitable climatic regions for M. hypopitys at the LGM. We analysed between 155 and 176 individuals from 39 locations spanning the species' entire range in North America. Sequence data were obtained for the chloroplast rps2 gene (n=168) and for the nuclear ITS region (n=158). Individuals were also genotyped for eight microsatellite loci (n=176). Interpolation of diversity values was used to visualize the range-wide distribution of genetic diversity for each of the three marker classes. Minimum spanning networks were constructed showing the relationships between the rps2 and ITS haplotypes, and the geographical distributions of these haplotypes were plotted. The numbers of genetic clusters based on the microsatellite data were estimated using Bayesian clustering approaches. Results The palaeodistribution modelling indicated suitable climate envelopes for M. hypopitys at the LGM in both the Pacific Northwest and south-eastern USA. High levels of genetic diversity and endemic haplotypes were found in Oregon, the Alexander Archipelago, Wisconsin, and in the south-eastern part of the species' distribution range. Main conclusions Our results suggest a complex recolonization history for M. hypopitys in North America, involving persistence in separate eastern and western refugia. A generally high degree of congruence between the different marker classes analysed indicated the presence of multiple refugia, with at least two refugia in each area. In the west, putative refugia were identified in Oregon and the Alexander Archipelago, whereas eastern refugia may have been located in the southern part of the species' current distribution, as well as in the 'Driftless Area'. These findings are in contrast to a previous study on the related species Orthilia secunda, which has a similar disjunct distribution to M. hypopitys, but which appears to have recolonized solely from western refugia. © 2011 Blackwell Publishing Ltd.

Analysis and Design of Class-E3F and Transmission-Line Class-E3F2 Power Amplifiers

In this paper, analysis and synthesis approach for two new variants within the Class-EF power amplifier (PA) family is elaborated. These amplifiers are classified here as Class-E3 F2 and transmission-line (TL) Class-E3 F 2. The proposed circuits offer means to alleviate some of the major issues faced by existing topologies such as substantial power losses due to the parasitic resistance of the large inductor in the Class-EF load network and deviation from ideal Class-EF operation due to the effect of device output inductance at high frequencies. Both lumped-element and transmission-line load networks for the Class-E 3 F PA are described. The load networks of the Class-E3 F and TL Class-E 3 F2amplifier topologies developed in this paper simultaneously satisfy the Class-EF optimum impedance requirements at fundamental frequency, second, and third harmonics as well as simultaneously providing matching to the circuit optimum load resistance for any prescribed system load resistance. Optimum circuit component values are analytically derived and validated by harmonic balance simulations. Trade-offs between circuit figures of merit and component values with some practical limitations being considered are discussed. © 2010 IEEE.

Analysis of information leakage from encrypted Skype conversations

Voice over IP (VoIP) has experienced a tremendous growth over the last few years and is now widely used among the population and for business purposes. The security of such VoIP systems is often assumed, creating a false sense of privacy. This paper investigates in detail the leakage of information from Skype, a widely used and protected VoIP application. Experiments have shown that isolated phonemes can be classified and given sentences identified. By using the dynamic time warping (DTW) algorithm, frequently used in speech processing, an accuracy of 60% can be reached. The results can be further improved by choosing specific training data and reach an accuracy of 83% under specific conditions. The initial results being speaker dependent, an approach involving the Kalman filter is proposed to extract the kernel of all training signals.

Automated nonlinear system modelling with multiple neural networks

This article discusses the identification of nonlinear dynamic systems using multi-layer perceptrons (MLPs). It focuses on both structure uncertainty and parameter uncertainty, which have been widely explored in the literature of nonlinear system identification. The main contribution is that an integrated analytic framework is proposed for automated neural network structure selection, parameter identification and hysteresis network switching with guaranteed neural identification performance. First, an automated network structure selection procedure is proposed within a fixed time interval for a given network construction criterion. Then, the network parameter updating algorithm is proposed with guaranteed bounded identification error. To cope with structure uncertainty, a hysteresis strategy is proposed to enable neural identifier switching with guaranteed network performance along the switching process. Both theoretic analysis and a simulation example show the efficacy of the proposed method.

Networks for systems biology: conceptual connection of data and function

The purpose of this study is to survey the use of networks and network-based methods in systems biology. This study starts with an introduction to graph theory and basic measures allowing to quantify structural properties of networks. Then, the authors present important network classes and gene networks as well as methods for their analysis. In the last part of this study, the authors review approaches that aim at analysing the functional organisation of gene networks and the use of networks in medicine. In addition to this, the authors advocate networks as a systematic approach to general problems in systems biology, because networks are capable of assuming multiple roles that are very beneficial connecting experimental data with a functional interpretation in biological terms.

Determining propeller induced erosion alongside quay walls in harbours using Artificial Neural Networks

In shallow waters, such as those found close to berth structures, the wash from a manoeuvring ship’s propeller can cause erosion of the seabed. This erosion can be increased if the wash intersects a berth structure. A number of researchers have undertaken model studies and used regression analysis to develop predictive relationships for the scouring action. This paper presents an experimental investigation with Artificial Neural Networks (ANN’s), used to analyse the results. The purpose of using ANN’s was to examine the prediction accuracy of the Networks in comparison with previous regression analysis methods. ANN’s were found to provide a more accurate method of predicting propeller wash scour than the equations presented by previous investigators.

A Bayesian analysis of the chromosome architecture of human disorders by integrating reductionist data

In this paper, we present a Bayesian approach to estimate a chromosome and a disorder network from the Online Mendelian Inheritance in Man (OMIM) database. In contrast to other approaches, we obtain statistic rather than deterministic networks enabling a parametric control in the uncertainty of the underlying disorder-disease gene associations contained in the OMIM, on which the networks are based. From a structural investigation of the chromosome network, we identify three chromosome subgroups that reflect architectural differences in chromosome-disorder associations that are predictively exploitable for a functional analysis of diseases.

Design and Analysis of an Independent, Layer 2, Open-Access WiFi Monitoring Infrastructure in the Wild

While WiFi monitoring networks have been deployed in previous research, to date none have assessed live network data from an open access, public environment. In this paper we describe the construction of a replicable, independent WLAN monitoring system and address some of the challenges in analysing the resultant traffic. Analysis of traffic from the system demonstrates that basic traffic information from open-access networks varies over time (temporal inconsistency). The results also show that arbitrary selection of Request-Reply intervals can have a significant effect on Probe and Association frame exchange calculations, which can impact on the ability to detect flooding attacks.

Evaluating the effectiveness of community-based dementia care networks:The Dementia Care Networks' Study

Purpose: The Dementia Care Networks' Study examined the effectiveness of four community-based, not-for-profit dementia networks. The study involved assessing the relationship between the types of administrative and service-delivery exchanges that occurred among the networked agencies and the network members' perception of the effectiveness of these exchanges. Design and Methods: With the use of a case-study method, the evolution, structure, and processes of each network were documented. Social network analysis using a standardized questionnaire completed by member agencies identified patterns of administrative and clinical exchanges among networked agencies. Results: Differences were found between the four networks in terms of their perceptions of service-delivery effectiveness; perceptions of administrative effectiveness did not factor significantly. Exchanges between groups of agencies (cliques) within each of the four networks were found to be more critical than those between individual agencies within each network. Implications: Integration-measured by the types of exchanges within as opposed to across networks-differentiated the four networks studied. This research contributes to our understanding of the use of multiple measures to evaluate the inner workings of service delivery and their impact on elder health and elder health care. Copyright 2005 by The Gerontological Society of America.

Improving Patient Safety Through Formal and Informal Learning Networks

This paper explores a novel perspective on patient safety improvements, which draws on
contemporary social network and learning theories. A case study was conducted at a Portuguese
acute university hospital. Data collection followed a staged approach, whereby 46 interviews
were conducted involving 49 respondents from a broad array of departments and professional
backgrounds. This case study highlights the importance of two major interlinked factors in
contributing to patient safety improvements. The first of these is the crucial role of formal and
informal, internal and external social networks. The second is the importance and the possible
advantage of combining formal and informal learning. The analysis suggests that initiatives
rooted in formal learning approaches alone do not necessarily lead to the creation of long-term
grounded internal safety networks, and that patient safety improvements can crucially depend on
bottom-up initiatives of communities of practice and informal learning. Traditional research on
patient safety places a strong emphasis on top-down and managerialist approaches and is often
based on the assumption that „safety? learning is primarily formal and context-independent. This
paper suggests that bottom-up initiatives and a combination of formal and informal learning can
make a major contribute to patient safety improvements.

Maximum Outage Capacity in Dense Indoor Femtocell Networks with Joint Energy and Spectrum Utilization

We consider a multiple femtocell deployment in a small area which shares spectrum with the underlaid macrocell. We design a joint energy and radio spectrum scheme which aims not only for co-existence with the macrocell, but also for an energy-efficient implementation of the multi-femtocells. Particularly, aggregate energy usage on dense femtocell channels is formulated taking into account the cost of both the spectrum and energy usage. We investigate an energy-and-spectral efficient approach to balance between the two costs by varying the number of active sub-channels and their energy. The proposed scheme is addressed by deriving closed-form expressions for the interference towards the macrocell and the outage capacity. Analytically, discrete regions under which the most promising outage capacity is achieved by the same size of active sub-channels are introduced. Through a joint optimization of the sub-channels and their energy, properties can be found for the maximum outage capacity under realistic constraints. Using asymptotic and numerical analysis, it can be noticed that in a dense femtocell deployment, the optimum utilization of the energy and the spectrum to maximize the outage capacity converges towards a round-robin scheduling approach for a very small outage threshold. This is the inverse of the traditional greedy approach. © 2012 IEEE.

Export Cartels: Is it Legal to Target your Neighbour? Analysis in Light of Recent Case Law

Despite the growing sophistication of antitrust regimes around the world, export cartels benefit from special treatment: they are almost universally tolerated, if not encouraged in the countries of origin. Economists do not offer an unambiguous policy recommendation on how to deal with them in part due to the lack of empirical data. This article discusses arguments for and against export cartels and it identifies the existing gaps in the present regulatory framework. The theoretical part is followed by an analysis of the recent case law: a US cartel challenged with different outcomes in India and South Africa, as well as Chinese export cartels pursued in the USA. The Chinese cases are particularly topical as the conduct at stake, apart from being subject to private antitrust actions before US courts, was also challenged within the WTO dispute settlement framework, pointing out to the existing interface between trade and competition. While the recent developments prove that unaddressed issues tend not to vanish, the new South-North dimension has the potential of placing export cartels again on the international agenda. Pragmatic thinking suggests looking for the solution within the WTO framework.

Implementation and Evaluation of Measurement-Based Admission Control Schemes Within a Converged Networks QoS Management Framework

Policy-based network management (PBNM) paradigms provide an effective tool for end-to-end resource
management in converged next generation networks by enabling unified, adaptive and scalable solutions
that integrate and co-ordinate diverse resource management mechanisms associated with heterogeneous
access technologies. In our project, a PBNM framework for end-to-end QoS management in converged
networks is being developed. The framework consists of distributed functional entities managed within a
policy-based infrastructure to provide QoS and resource management in converged networks. Within any
QoS control framework, an effective admission control scheme is essential for maintaining the QoS of
flows present in the network. Measurement based admission control (MBAC) and parameter basedadmission control (PBAC) are two commonly used approaches. This paper presents the implementationand analysis of various measurement-based admission control schemes developed within a Java-based
prototype of our policy-based framework. The evaluation is made with real traffic flows on a Linux-based experimental testbed where the current prototype is deployed. Our results show that unlike with classic MBAC or PBAC only schemes, a hybrid approach that combines both methods can simultaneously result in improved admission control and network utilization efficiency