Analyzing the effectiveness of graph metrics for anomaly detection in online social networks

Online social networks can be modelled as graphs; in this paper, we analyze the use of graph metrics for identifying users with anomalous relationships to other users. A framework is proposed for analyzing the effectiveness of various graph theoretic properties such as the number of neighbouring nodes and edges, betweenness centrality, and community cohesiveness in detecting anomalous users. Experimental results on real-world data collected from online social networks show that the majority of users typically have friends who are friends themselves, whereas anomalous users’ graphs typically do not follow this common rule. Empirical analysis also shows that the relationship between average betweenness centrality and edges identifies anomalies more accurately than other approaches.

Data requirements and graph data structures for a multi-modal, multi-objective trip planner

Traffic congestion has a significant impact on the economy and environment. Encouraging the use of multimodal transport (public transport, bicycle, park’n’ride, etc.) has been identified by traffic operators as a good strategy to tackle congestion issues and its detrimental environmental impacts. A multi-modal and multi-objective trip planner provides users with various multi-modal options optimised on objectives that they prefer (cheapest, fastest, safest, etc) and has a potential to reduce congestion on both a temporal and spatial scale. The computation of multi-modal and multi-objective trips is a complicated mathematical problem, as it must integrate and utilize a diverse range of large data sets, including both road network information and public transport schedules, as well as optimising for a number of competing objectives, where fully optimising for one objective, such as travel time, can adversely affect other objectives, such as cost. The relationship between these objectives can also be quite subjective, as their priorities will vary from user to user. This paper will first outline the various data requirements and formats that are needed for the multi-modal multi-objective trip planner to operate, including static information about the physical infrastructure within Brisbane as well as real-time and historical data to predict traffic flow on the road network and the status of public transport. It will then present information on the graph data structures representing the road and public transport networks within Brisbane that are used in the trip planner to calculate optimal routes. This will allow for an investigation into the various shortest path algorithms that have been researched over the last few decades, and provide a foundation for the construction of the Multi-modal Multi-objective Trip Planner by the development of innovative new algorithms that can operate the large diverse data sets and competing objectives.

Attitudes of future special education teachers toward gifted students and their education

Saudi Arabian education is undergoing substantial reform in the context of a nation transitioning from a resource-rich economy to a knowledge economy. Gifted students are important human resources for such developing countries. However, there are some concerns emanating from the international literature that gifted students have been neglected in many schools due to teachers’ attitudes toward them. The literature shows that future teachers also hold similar negative attitudes, especially those in Special Education courses who, as practicing teachers, are often responsible for supporting the gifted education process. The purpose of this study was to explore whether these attitudes are held by future special education teachers in Saudi Arabia, and how the standard gifted education course, delivered as part of their program, impacts on their attitudes toward gifted students. The study was strongly influenced by the Theory of Reasoned Action (Ajzen, 1980, 2012) and the Theory of Personal Knowledge (Polanyi, 1966), which both suggest that attitudes are related to people’s (i.e. teachers’) beliefs. A mixed methods design was used to collect quantitative and qualitative data from a cohort of students enrolled in a teacher education program at a Saudi Arabian university. The program was designed for students majoring in special education. The quantitative component of the study involved an investigation of a cohort of future special education teachers taking a semester-long course in gifted education. The data were primarily sourced from a standard questionnaire instrument modified in the Arabic language, and supplemented with questions that probed the future teachers’ attitudes toward gifted children. The participants, 90 special education future teachers, were enrolled in an introductory course about gifted education. The questionnaire contained 34 items from the "Opinions about the Gifted and Their Education" (Gagné, 1991) questionnaire, utilising a five-point Likert scale. The quantitative data were analysed through the use of descriptive statistics, Spearman correlation Coefficients, Paired Samples t-test, and Multiple Linear Regression. The qualitative component focussed on eight participants enrolled in the gifted education course. The primary source of the qualitative data was informed by individual semi-structured interviews with each of these participants. The findings, based on both the quantitative and qualitative data, indicated that the majority of future special education teachers held, overall, slightly positive attitudes toward gifted students and their education. However, the participants were resistant to offering special services for the gifted within the regular classroom, even when a comparison was made on equity grounds with disabled students. While the participants held ambivalent attitudes toward ability grouping, their attitudes were positive toward grade acceleration. Further, the majority agreed that gifted students are likely to be rejected by their teachers. Despite such judgments, they considered the gifted to be a valuable resource for Saudi society. Differences within the cohort were found when two variables emerged as potential predictors of attitude: age, experience, and participants’ hometown. The younger (under 25 years old) future special education teachers, with no internship or school practice experience, held more positive attitudes toward the gifted students, with respect to their general needs, than did the older participants with previous school experiences. Additionally, participants from a rural region were more resistant toward gifted education than future teachers from urban areas. The findings also indicated that the attitudes of most of the participants were significantly improved, as a result of the course, toward ability grouping such as special classes and schools, but remained highly concerned about differentiation within regular classrooms with either elitism or time pressure. From the findings, it can be confirmed that a lectured-based course can serve as a starting point from which to focus future teachers’ attention on the varied needs of the gifted, and as a conduit for learning about special services for the gifted. However, by itself, the course appears to have minimal influence on attitudes toward differentiation. As a consequence, there is merit in its redevelopment, and the incorporation of more practical opportunities for future teachers to experience the teaching of the gifted.

A semi-supervised graph-based algorithm for detecting outliers in online-social-networks

In this paper, we propose a semi-supervised approach of anomaly detection in Online Social Networks. The social network is modeled as a graph and its features are extracted to detect anomaly. A clustering algorithm is then used to group users based on these features and fuzzy logic is applied to assign degree of anomalous behavior to the users of these clusters. Empirical analysis shows effectiveness of this method.

Mechanical properties of bioinspired bicontinuous nanocomposites

Inspired by the wonderful properties of some biological composites in nature, we performed molecular dynamics simulations to investigate the mechanical behavior of bicontinuous nanocomposites. Three representative types of bicontinuous composites, which have regular network, random network, and nacre inspired microstructures respectively, were studied and the results were compared with those of a honeycomb nanocomposite with only one continuous phase. It was found that the mechanical strength of nanocomposites in a given direction strongly depends on the connectivity of microstructure in that direction. Directional isotropy in mechanical strength and easy manufacturability favor the random network nanocomposites as a potentially great bioinspired composite with balanced performances. In addition, the tensile strength of random network nanocomposites is less sensitive to the interfacial failure, owing to its super high interface-to-volume ratio and random distribution of internal interfaces. The results provide a useful guideline for design and optimization of advanced nanocomposites with superior mechanical properties.

A people-to-people matching system using graph mining techniques

A people-to-people matching system (or a match-making system) refers to a system in which users join with the objective of meeting other users with the common need. Some real-world examples of these systems are employer-employee (in job search networks), mentor-student (in university social networks), consume-to-consumer (in marketplaces) and male-female (in an online dating network). The network underlying in these systems consists of two groups of users, and the relationships between users need to be captured for developing an efficient match-making system. Most of the existing studies utilize information either about each of the users in isolation or their interaction separately, and develop recommender systems using the one form of information only. It is imperative to understand the linkages among the users in the network and use them in developing a match-making system. This study utilizes several social network analysis methods such as graph theory, small world phenomenon, centrality analysis, density analysis to gain insight into the entities and their relationships present in this network. This paper also proposes a new type of graph called “attributed bipartite graph”. By using these analyses and the proposed type of graph, an efficient hybrid recommender system is developed which generates recommendation for new users as well as shows improvement in accuracy over the baseline methods.

Flexible design of decoupling and matching networks for two strongly coupled antennas

The flexible design of decoupling and matching networks for coupled antennas is introduced. The network includes three parts: circuits for impedance transformation, an element for odd-mode decoupling and conventional matching networks. It is found that all three parts are determined by one parameter of the ABCD matrix of the impedance transformation circuit. Thus a large variety of circuits with different element values can be used for decoupling which relaxes the practical design constraints.

Graph coloring applied to secure computation in non-Abelian groups

We study the natural problem of secure n-party computation (in the computationally unbounded attack model) of circuits over an arbitrary finite non-Abelian group (G,⋅), which we call G-circuits. Besides its intrinsic interest, this problem is also motivating by a completeness result of Barrington, stating that such protocols can be applied for general secure computation of arbitrary functions. For flexibility, we are interested in protocols which only require black-box access to the group G (i.e. the only computations performed by players in the protocol are a group operation, a group inverse, or sampling a uniformly random group element). Our investigations focus on the passive adversarial model, where up to t of the n participating parties are corrupted.

Decomposition construction for secret sharing schemes with graph access structures in polynomial time

The purpose of this paper is to describe a new decomposition construction for perfect secret sharing schemes with graph access structures. The previous decomposition construction proposed by Stinson is a recursive method that uses small secret sharing schemes as building blocks in the construction of larger schemes. When the Stinson method is applied to the graph access structures, the number of such “small” schemes is typically exponential in the number of the participants, resulting in an exponential algorithm. Our method has the same flavor as the Stinson decomposition construction; however, the linear programming problem involved in the construction is formulated in such a way that the number of “small” schemes is polynomial in the size of the participants, which in turn gives rise to a polynomial time construction. We also show that if we apply the Stinson construction to the “small” schemes arising from our new construction, both have the same information rate.

Flexible process graph : a prologue

Businesses document their operational processes as process models. The common practice is to represent process models as directed graphs. The nodes of a process graph represent activities and directed edges constitute activity ordering constraints. A flexible process graph modeling approach proposes to generalize process graph structure to a hypergraph. Obtained process structure aims at formalization of ad-hoc process control flow. In this paper we discuss aspects relevant to concurrent execution of process activities in a collaborative manner organized as a flexible process graph. We provide a real world flexible process scenario to illustrate the approach.

Identifying the spatial scale of land use that most strongly influences overall river ecosystem health score

Catchment and riparian degradation has resulted in declining ecosystem health of streams worldwide. With restoration a priority in many regions, there is an increasing interest in the scale at which land use influences stream ecosystem health. Our goal was to use a substantial data set collected as part of a monitoring program (the Southeast Queensland, Australia, Ecological Health Monitoring Program data set, collected at 116 sites over six years) to identify the spatial scale of land use, or the combination of spatial scales, that most strongly influences overall ecosystem health. In addition, we aimed to determine whether the most influential scale differed for different aspects of ecosystem health. We used linear-mixed models and a Bayesian model-averaging approach to generate models for the overall aggregated ecosystem health score and for each of the five component indicators (fish, macroinvertebrates, water quality, nutrients, and ecosystem processes) that make up the score. Dense forest close to the survey site, mid-dense forest in the hydrologically active nearstream areas of the catchment, urbanization in the riparian buffer, and tree cover at the reach scale were all significant in explaining ecosystem health, suggesting an overriding influence of forest cover, particularly close to the stream. Season and antecedent rainfall were also important explanatory variables, with some land-use variables showing significant seasonal interactions. There were also differential influences of land use for each of the component indicators. Our approach is useful given that restoring general ecosystem health is the focus of many stream restoration projects; it allowed us to predict the scale and catchment position of restoration that would result in the greatest improvement of ecosystem health in the regions streams and rivers. The models we generated suggested that good ecosystem health can be maintained in catchments where 80% of hydrologically active areas in close proximity to the stream have mid-dense forest cover and moderate health can be obtained with 60% cover.

How to strengthen any weakly unforgeable signature into a strongly unforgeable signature

Standard signature schemes are usually designed only to achieve weak unforgeability – i.e. preventing forgery of signatures on new messages not previously signed. However, most signature schemes are randomised and allow many possible signatures for a single message. In this case, it may be possible to produce a new signature on a previously signed message. Some applications require that this type of forgery also be prevented – this requirement is called strong unforgeability. At PKC2006, Boneh Shen and Waters presented an efficient transform based on any randomised trapdoor hash function which converts a weakly unforgeable signature into a strongly unforgeable signature and applied it to construct a strongly unforgeable signature based on the CDH problem. However, the transform of Boneh et al only applies to a class of so-called partitioned signatures. Although many schemes fall in this class, some do not, for example the DSA signature. Hence it is natural to ask whether one can obtain a truly generic efficient transform based on any randomised trapdoor hash function which converts any weakly unforgeable signature into a strongly unforgeable one. We answer this question in the positive by presenting a simple modification of the Boneh-Shen-Waters transform. Our modified transform uses two randomised trapdoor hash functions.

Effect of Coulomb blockade, gold resistance, and thermal expansion on the electrical resistance of ultrathin gold films

Controlling the electrical resistance of granular thin films is of great importance for many applications, yet a full understanding of electron transport in such films remains a major challenge. We have studied experimentally and by model calculations the temperature dependence of the electrical resistance of ultrathin gold films at temperatures between 2 K and 300 K. Using sputter deposition, the film morphology was varied from a discontinuous film of weakly coupled meandering islands to a continuous film of strongly coupled coalesced islands. In the weak-coupling regime, we compare the regular island array model, the cotunneling model, and the conduction percolation model with our experimental data. We show that the tunnel barriers and the Coulomb blockade energies are important at low temperatures and that the thermal expansion of the substrate and the island resistance affect the resistance at high temperatures. At low temperatures our experimental data show evidence for a transition from electron cotunneling to sequential tunneling but the data can also be interpreted in terms of conduction percolation. The resistivity and temperature coefficient of resistance of the meandering gold islands are found to resemble those of gold nanowires. We derive a simple expression for the temperature at which the resistance changes from non-metal-like behavior into metal-like behavior. In the case of strong island coupling, the total resistance is solely determined by the Ohmic island resistance.

Self-organized nanoarrays : plasma-related controls

The paper presents an investigation of self-organizational and -assembly processes of nanostructure growth on surfaces exposed to low-temperature plasmas. We have considered three main growth stages-initial, or sub-monolayer growth stage, separate nanostructure growth stage, and array growth stages with the characteristic sizes of several nm, several tens of nm, and several hundreds of nm, respectively, and have demonstrated, by the experimental data and hybrid multiscale numerical simulations, that the plasma parameters can strongly influence the surface processes and hence the kinetics of self-organization and -assembly. Our results show that plasma-controlled self-organization is a promising way to assemble large regular arrays of nanostructures. © 2008 IUPAC.

Surface waves in strongly irradiated dusty plasmas

High-frequency surface waves at the interface between two dusty plasmas subject to radiation are considered. Ultraviolet radiation with energy flux larger than the photoelectric work function of the dust surface causes photoemission of electrons. The dust charge and the overall charge balance of the plasma are thus modified. The dispersion properties of the surface waves are investigated for three parameter regimes distinguished by the charging mechanisms in the two plasmas. It is shown that photoemission can significantly affect the plasma and the surface waves.