Integrating network analysis, sensor tags, and observation to understand shark ecology and behavior

Group living in animals is a well-studied phenomenon, having been documented extensively in a wide range of terrestrial, freshwater, and marine species. Although social dynamics are complex across space and time, recent technological and analytical advances enable deeper understanding of their nature and ecological implications. While for some taxa, a great deal of information is known regarding the mechanistic underpinnings of these social processes, knowledge of these mechanisms in elasmobranchs is lacking. Here, we used an integrative and novel combination of direct observation, accelerometer biologgers, and recent advances in network analysis to better understand the mechanistic bases of individual-level differences in sociality (leadership, network attributes) and diel patterns of locomotor activity in a widespread marine predator, the lemon shark (Negaprion brevirostris). We found that dynamic models of interaction based on Markov chains can accurately predict juvenile lemon shark social behavior and that lemon sharks did not occupy consistent positions within their network. Lemon sharks did however preferentially associate with specific group members, by sex as well as by similarity or nonsimilarity for a number of behavioral (nonsimilarity: leadership) and locomotor traits (similarity: proportion of time swimming "fast," mean swim duration; nonsimilarity: proportion of swimming bursts/transitions between activity states). Our study provides some of the first information on the mechanistic bases of group living and personality in sharks and further, a potential experimental approach for studying fine-scale differences in behavior and locomotor patterns in difficult-to-study organisms.

Social network analysis resolves temporal dynamics of male dominance relationships

Social organization is often studied through point estimates of individual association or interaction patterns, which does not account for temporal changes in the course of familiarization processes and the establishment of social dominance. Here, we present new insights on short-term temporal dynamics in social organization of mixed-sex groups that have the potential to affect sexual selection patterns. Using the live-bearing Atlantic molly (Poecilia mexicana), a species with pronounced male size polymorphism, we investigated social network dynamics of mixed sex experimental groups consisting of eight females and three different-sized males over a period of 5 days. Analyzing association-based social networks as well as direct measures of spatial proximity, we found that large males tended to monopolize most females, while excluding small- and medium-bodied males from access to females. This effect, however, emerged only gradually over time, and different-sized males had equal access to females on day 1 as well as day 2, though to a lesser extent. In this highly aggressive species with strong social dominance stratifications, the observed temporal dynamics in male-female association patterns may balance the presumed reproductive skew among differentially competitive male phenotypes when social structures are unstable (i.e., when individual turnover rates are moderate to high). Ultimately, our results point toward context-dependent sexual selection arising from temporal shifts in social organization.

Artificial neural network modeling for surface roughness prediction in cylindrical grinding of Al‐SiCp metal matrix composites and ANOVA analysis

Metal matrix composites (MMC) having aluminium (Al) in the matrix phase and silicon carbide particles (SiCp) in reinforcement phase, ie Al‐SiCp type MMC, have gained popularity in the re‐cent past. In this competitive age, manufacturing industries strive to produce superior quality products at reasonable price. This is possible by achieving higher productivity while performing machining at optimum combinations of process variables. The low weight and high strength MMC are found suitable for variety of components

Temporal analysis of tourism research collaboration network

Network analysis is an effective tool for the study of collaboration relationships among researchers. Collaboration networks constructed from previous studies, and their changes over time have been studied. However, the impact of individual researchers in collaboration networks has not been investigated systematically. We introduce a new method of measuring the contribution of researchers to the connectivity of collaboration networks and evaluate the importance of researchers by considering both contribution and productivity. Betweenness centrality is found to be better than degree centrality in terms of reflecting the changes of importance of researchers. Accordingly, a method is further proposed to identify key researchers at certain periods. The performance of the identified researchers demonstrates the effectiveness of the proposed method.

Scientific collaboration network among Brazilian universities: an analysis in Dentistry area

This paper analyses the scientific collaboration network formed by the Brazilian universities that investigate in dentistry area. The constructed network is based on the published documents in the Scopus (Elsevier) database covering a period of 10 (ten) years. It is used social network analysis as the best methodological approach to visualize the capacity for collaboration, dissemination and transmission of new knowledge among universities. Cohesion and density of the collaboration network is analyzed, as well as the centrality of the universities as key-actors and the occurrence of subgroups within the network. Data were analyzed using the software UCINET and NetDraw. The number of documents published by each university was used as an indicator of its scientific production.

Comparative analysis of different meat traceability systems using multiple criteria and a social network approach

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Validation of network communicability metrics for the analysis of brain structural networks.

Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

Analysis of constructivist, network-based discourses:concepts, prospects, and illustrations

The authors propose a new approach to discourse analysis which is based on meta data from social networking behavior of learners who are submerged in a socially constructivist e-learning environment. It is shown that traditional data modeling techniques can be combined with social network analysis - an approach that promises to yield new insights into the largely uncharted domain of network-based discourse analysis. The chapter is treated as a non-technical introduction and is illustrated with real examples, visual representations, and empirical findings. Within the setting of a constructivist statistics course, the chapter provides an illustration of what network-based discourse analysis is about (mainly from a methodological point of view), how it is implemented in practice, and why it is relevant for researchers and educators.

Against small arms: An analysis of an international network

Small Arms and Light Weapons (SALW) proliferation was undertaken by the Non-Governmental Organizations (NGOs) as the next important issue in international relations after the success of the International Campaign to Ban Landmines (ICBL). This dissertation focuses on the reasons why the issue of SALW resulted in an Action Program rather than an international convention. Thus, this result was considered as unsuccessful by the advocates of regulating the illicit trade in SALW. The study provides a social movement theoretical approach, using framing, political opportunity and network analysis to explain why the advocates of regulating the illicit trade in SALW did no succeed in their goals. The UN is taken as the arena in which NGOs, States and International Governmental Organizations (IGOs) discussed the illicit trade in SALW. ^ The findings of the study indicate that the political opportunity for the issue of SALW was not ideal. The network of NGOs, States and IGOs was not strong. The NGOs advocating regulation of SALW were divided over the approach of the issue and were part of different coalitions with differing objectives. Despite initial widespread interest among States, only a couple of States were fully committed to the issue till the end. The regional IGOs approached the issue based on their regional priorities and were less interested in an international covenant. The advocates of regulating illicit trade in SALW attempted to frame SALW as a humanitarian issue rather than as a security issue. Thus they were not able to use frame alignment to convince states to treat SALW as a humanitarian issue. In conclusion it can be said that all three items, framing, political opportunity and the network, play a role in the lack of success of advocates for regulating the illicit trade in SALW. ^

Do board contacts matter? : an analysis of the relationship between boards of directors’ ties and the performance of Australia’s largest companies.

Boards of directors are thought to provide access to a wealth of knowledge and resources for the companies they serve, and are considered important to corporate governance. Under the Resource Based View (RBV) of the firm (Wernerfelt, 1984) boards are viewed as a strategic resource available to firms. As a consequence there has been a significant research effort aimed at establishing a link between board attributes and company performance. In this thesis I explore and extend the study of interlocking directorships (Mizruchi, 1996; Scott 1991a) by examining the links between directors’ opportunity networks and firm performance. Specifically, I use resource dependence theory (Pfeffer & Salancik, 1978) and social capital theory (Burt, 1980b; Coleman, 1988) as the basis for a new measure of a board’s opportunity network. I contend that both directors’ formal company ties and their social ties determine a director’s opportunity network through which they are able to access and mobilise resources for their firms. This approach is based on recent studies that suggest the measurement of interlocks at the director level, rather than at the firm level, may be a more reliable indicator of this phenomenon. This research uses publicly available data drawn from Australia’s top-105 listed companies and their directors in 1999. I employ Social Network Analysis (SNA) (Scott, 1991b) using the UCINET software to analyse the individual director’s formal and social networks. SNA is used to measure a the number of ties a director has to other directors in the top-105 company director network at both one and two degrees of separation, that is, direct ties and indirect (or ‘friend of a friend’) ties. These individual measures of director connectedness are aggregated to produce a board-level network metric for comparison with measures of a firm’s performance using multiple regression analysis. Performance is measured with accounting-based and market-based measures. Findings indicate that better-connected boards are associated with higher market-based company performance (measured by Tobin’s q). However, weaker and mostly unreliable associations were found for accounting-based performance measure ROA. Furthermore, formal (or corporate) network ties are a stronger predictor of market performance than total network ties (comprising social and corporate ties). Similarly, strong ties (connectedness at degree-1) are better predictors of performance than weak ties (connectedness at degree-2). My research makes four contributions to the literature on director interlocks. First, it extends a new way of measuring a board’s opportunity network based on the director rather than the company as the unit of interlock. Second, it establishes evidence of a relationship between market-based measures of firm performance and the connectedness of that firm’s board. Third, it establishes that director’s formal corporate ties matter more to market-based firm performance than their social ties. Fourth, it establishes that director’s strong direct ties are more important to market-based performance than weak ties. The thesis concludes with implications for research and practice, including a more speculative interpretation of these results. In particular, I raise the possibility of reverse causality – that is networked directors seek to join high-performing companies. Thus, the relationship may be a result of symbolic action by companies seeking to increase the legitimacy of their firms rather than a reflection of the social capital available to the companies. This is an important consideration worthy of future investigation.

A social matching system for an online dating network : a preliminary study

Due to the change in attitudes and lifestyles, people expect to find new partners and friends via various ways now-a-days. Online dating networks create a network for people to meet each other and allow making contact with different objectives of developing a personal, romantic or sexual relationship. Due to the higher expectation of users, online matching companies are trying to adopt recommender systems. However, the existing recommendation techniques such as content-based, collaborative filtering or hybrid techniques focus on users explicit contact behaviors but ignore the implicit relationship among users in the network. This paper proposes a social matching system that uses past relations and user similarities in finding potential matches. The proposed system is evaluated on the dataset collected from an online dating network. Empirical analysis shows that the recommendation success rate has increased to 31% as compared to the baseline success rate of 19%.

Resilience of a corrupt police network : the first and second jokes in Queensland

Resilient organised crime groups survive and prosper despite law enforcement activity, criminal competition and market forces. Corrupt police networks, like any other crime network, must contain resiliency characteristics if they are to continue operation and avoid being closed down through detection and arrest of their members. This paper examines the resilience of a large corrupt police network, namely The Joke which operated in the Australian state of Queensland for a number of decades. The paper uses social network analysis tools to determine the resilient characteristics of the network. This paper also assumes that these characteristics will be different to those of mainstream organised crime groups because the police network operates within an established policing agency rather than as an independent entity hiding within the broader community.

Leveraging the network information for evaluating answer quality in a collaborative question answering portal

Collaborative question answering (cQA) portals such as Yahoo! Answers allow users as askers or answer authors to communicate, and exchange information through the asking and answering of questions in the network. In their current set-up, answers to a question are arranged in chronological order. For effective information retrieval, it will be advantageous to have the users’ answers ranked according to their quality. This paper proposes a novel approach of evaluating and ranking the users’answers and recommending the top-n quality answers to information seekers. The proposed approach is based on a user-reputation method which assigns a score to an answer reflecting its answer author’s reputation level in the network. The proposed approach is evaluated on a dataset collected from a live cQA, namely, Yahoo! Answers. To compare the results obtained by the non-content-based user-reputation method, experiments were also conducted with several content-based methods that assign a score to an answer reflecting its content quality. Various combinations of non-content and content-based scores were also used in comparing results. Empirical analysis shows that the proposed method is able to rank the users’ answers and recommend the top-n answers with good accuracy. Results of the proposed method outperform the content-based methods, various combinations, and the results obtained by the popular link analysis method, HITS.

Reputation modelling in Citizen Science for environmental acoustic data analysis

Citizen Science projects are initiatives in which members of the general public participate in scientific research projects and perform or manage research-related tasks such as data collection and/or data annotation. Citizen Science is technologically possible and scientifically significant. However, although research teams can save time and money by recruiting general citizens to volunteer their time and skills to help data analysis, the reliability of contributed data varies a lot. Data reliability issues are significant to the domain of Citizen Science due to the quantity and diversity of people and devices involved. Participants may submit low quality, misleading, inaccurate, or even malicious data. Therefore, finding a way to improve the data reliability has become an urgent demand. This study aims to investigate techniques to enhance the reliability of data contributed by general citizens in scientific research projects especially for acoustic sensing projects. In particular, we propose to design a reputation framework to enhance data reliability and also investigate some critical elements that should be aware of during developing and designing new reputation systems.