A rule-based hybrid method for anomaly detection in online-social-network graphs

Detecting anomalies in the online social network is a significant task as it assists in revealing the useful and interesting information about the user behavior on the network. This paper proposes a rule-based hybrid method using graph theory, Fuzzy clustering and Fuzzy rules for modeling user relationships inherent in online-social-network and for identifying anomalies. Fuzzy C-Means clustering is used to cluster the data and Fuzzy inference engine is used to generate rules based on the cluster behavior. The proposed method is able to achieve improved accuracy for identifying anomalies in comparison to existing methods.

A novel process of group-oriented question reduction for rule-based recommendation websites

Several websites utilise a rule-base recommendation system, which generates choices based on a series of questionnaires, for recommending products to users. This approach has a high risk of customer attrition and the bottleneck is the questionnaire set. If the questioning process is too long, complex or tedious; users are most likely to quit the questionnaire before a product is recommended to them. If the questioning process is short; the user intensions cannot be gathered. The commonly used feature selection methods do not provide a satisfactory solution. We propose a novel process combining clustering, decisions tree and association rule mining for a group-oriented question reduction process. The question set is reduced according to common properties that are shared by a specific group of users. When applied on a real-world website, the proposed combined method outperforms the methods where the reduction of question is done only by using association rule mining or only by observing distribution within the group.

Using the quantum probability ranking principle to rank interdependent documents

A known limitation of the Probability Ranking Principle (PRP) is that it does not cater for dependence between documents. Recently, the Quantum Probability Ranking Principle (QPRP) has been proposed, which implicitly captures dependencies between documents through “quantum interference”. This paper explores whether this new ranking principle leads to improved performance for subtopic retrieval, where novelty and diversity is required. In a thorough empirical investigation, models based on the PRP, as well as other recently proposed ranking strategies for subtopic retrieval (i.e. Maximal Marginal Relevance (MMR) and Portfolio Theory(PT)), are compared against the QPRP. On the given task, it is shown that the QPRP outperforms these other ranking strategies. And unlike MMR and PT, one of the main advantages of the QPRP is that no parameter estimation/tuning is required; making the QPRP both simple and effective. This research demonstrates that the application of quantum theory to problems within information retrieval can lead to significant improvements.

Is intent-aware expected reciprocal rank sufficient to evaluate diversity?

In this paper we define two models of users that require diversity in search results; these models are theoretically grounded in the notion of intrinsic and extrinsic diversity. We then examine Intent-Aware Expected Reciprocal Rank (ERR-IA), one of the official measures used to assess diversity in TREC 2011-12, with respect to the proposed user models. By analyzing ranking preferences as expressed by the user models and those estimated by ERR-IA, we investigate whether ERR-IA assesses document rankings according to the requirements of the diversity retrieval task expressed by the two models. Empirical results demonstrate that ERR-IA neglects query-intents coverage by attributing excessive importance to redundant relevant documents. ERR-IA behavior is contrary to the user models that require measures to first assess diversity through the coverage of intents, and then assess the redundancy of relevant intents. Furthermore, diversity should be considered separately from document relevance and the documents positions in the ranking.

Characteristics of spatial variation, size distribution, formation and growth of particles in urban environments

This thesis is the first comprehensive study of important parameters relating to aerosols' impact on climate and human health, namely spatial variation, particle size distribution and new particle formation. We determined the importance of spatial variation of particle number concentration in microscale environments, developed a method for particle size parameterisation and provided knowledge about the chemistry of new particle formation. This is a significant contribution to our understanding of processes behind the transformation and dynamics of urban aerosols. This PhD project included extensive measurements of air quality parameters using state of the art instrumentation at each of the 25 sites within the Brisbane metropolitan area and advanced statistical analysis.

Beyond rule based reasoning - the meaning and use of cases

Commercial legal expert systems are invariably rule based. Such systems are poor at dealing with open texture and the argumentation inherent in law. To overcome these problems we suggest supplementing rule based legal expert systems with case based reasoning or neural networks. Both case based reasoners and neural networks use cases-but in very different ways. We discuss these differences at length. In particular we examine the role of explanation in existing expert systems methodologies. Because neural networks provide poor explanation facilities, we consider the use of Toulmin argument structures to support explanation (S. Toulmin, 1958). We illustrate our ideas with regard to a number of systems built by the authors

Facilitating query decomposition in query language modeling by association rule mining using multiple sliding windows

This paper presents a novel framework to further advance the recent trend of using query decomposition and high-order term relationships in query language modeling, which takes into account terms implicitly associated with different subsets of query terms. Existing approaches, most remarkably the language model based on the Information Flow method are however unable to capture multiple levels of associations and also suffer from a high computational overhead. In this paper, we propose to compute association rules from pseudo feedback documents that are segmented into variable length chunks via multiple sliding windows of different sizes. Extensive experiments have been conducted on various TREC collections and our approach significantly outperforms a baseline Query Likelihood language model, the Relevance Model and the Information Flow model.

Staurosporine augments EGF-mediated EMT in PMC42-LA cells through actin depolymerisation, focal contact size reduction and Snail1 induction : a model for cross-modulation

Background A feature of epithelial to mesenchymal transition (EMT) relevant to tumour dissemination is the reorganization of actin cytoskeleton/focal contacts, influencing cellular ECM adherence and motility. This is coupled with the transcriptional repression of E-cadherin, often mediated by Snail1, Snail2 and Zeb1/δEF1. These genes, overexpressed in breast carcinomas, are known targets of growth factor-initiated pathways, however it is less clear how alterations in ECM attachment cross-modulate to regulate these pathways. EGF induces EMT in the breast cancer cell line PMC42-LA and the kinase inhibitor staurosporine (ST) induces EMT in embryonic neural epithelial cells, with F-actin de-bundling and disruption of cell-cell adhesion, via inhibition of aPKC. Methods PMC42-LA cells were treated for 72 h with 10 ng/ml EGF, 40 nM ST, or both, and assessed for expression of E-cadherin repressor genes (Snail1, Snail2, Zeb1/δEF1) and EMT-related genes by QRT-PCR, multiplex tandem PCR (MT-PCR) and immunofluorescence +/- cycloheximide. Actin and focal contacts (paxillin) were visualized by confocal microscopy. A public database of human breast cancers was assessed for expression of Snail1 and Snail2 in relation to outcome. Results When PMC42-LA were treated with EGF, Snail2 was the principal E-cadherin repressor induced. With ST or ST+EGF this shifted to Snail1, with more extreme EMT and Zeb1/δEF1 induction seen with ST+EGF. ST reduced stress fibres and focal contact size rapidly and independently of gene transcription. Gene expression analysis by MT-PCR indicated that ST repressed many genes which were induced by EGF (EGFR, CAV1, CTGF, CYR61, CD44, S100A4) and induced genes which alter the actin cytoskeleton (NLF1, NLF2, EPHB4). Examination of the public database of breast cancers revealed tumours exhibiting higher Snail1 expression have an increased risk of disease-recurrence. This was not seen for Snail2, and Zeb1/δEF1 showed a reverse correlation with lower expression values being predictive of increased risk. Conclusion ST in combination with EGF directed a greater EMT via actin depolymerisation and focal contact size reduction, resulting in a loosening of cell-ECM attachment along with Snail1-Zeb1/δEF1 induction. This appeared fundamentally different to the EGF-induced EMT, highlighting the multiple pathways which can regulate EMT. Our findings add support for a functional role for Snail1 in invasive breast cancer.

An endogenously deposited fibrin scaffold determines construct size in the surgically created arteriovenous loop chamber model of tissue engineering

Background: An arteriovenous loop (AVL) enclosed in a polycarbonate chamber in vivo, produces a fibrin exudate which acts as a provisional matrix for the development of a tissue engineered microcirculatory network. Objectives: By administering enoxaparin sodium - an inhibitor of fibrin polymerization, the significance of fibrin scaffold formation on AVL construct size (including the AVL, fibrin scaffold, and new tissue growth into the fibrin), growth, and vascularization were assessed and compared to controls. Methods: In Sprague Dawley rats, an AVL was created on femoral vessels and inserted into a polycarbonate chamber in the groin in 3 control groups (Series I) and 3 experimental groups (Series II). Two hours before surgery and 6 hours post-surgery, saline (Series I) or enoxaparin sodium (0.6 mg/kg, Series II) was administered intra-peritoneally. Thereafter, the rats were injected daily with saline (Series I) or enoxaparin sodium (1.5 mg/kg, Series II) until construct retrieval at 3, 10, or 21 days. The retrieved constructs underwent weight and volume measurements, and morphologic/morphometric analysis of new tissue components. Results: Enoxaparin sodium treatment resulted in the development of smaller AVL constructs at 3, 10, and 21 days. Construct weight and volume were significantly reduced at 10 days (control weight 0.337 ± 0.016 g [Mean ± SEM] vs treated 0.228 ± 0.048, [P < .001]: control volume 0.317 ± 0.015 mL vs treated 0.184 ± 0.039 mL [P < .01]) and 21 days (control weight 0.306 ± 0.053 g vs treated 0.198 ± 0.043 g [P < .01]: control volume 0.285 ± 0.047 mL vs treated 0.148 ± 0.041 mL, [P < .01]). Angiogenesis was delayed in the enoxaparin sodium-treated constructs with the absolute vascular volume significantly decreased at 10 days (control vascular volume 0.029 ± 0.03 mL vs treated 0.012 ± 0.002 mL [P < .05]). Conclusion: In this in vivo tissue engineering model, endogenous, extra-vascularly deposited fibrin volume determines construct size and vascular growth in the first 3 weeks and is, therefore, critical to full construct development.

Size- and orientation-selective Si nanowire growth : thermokinetic effects of naeoscale plasma chemistry

A multiscale, multiphase thermokinetic model is used to show the effective control of the growth orientation of thin Si NWs for nanoelectronic devices enabled by nanoscale plasma chemistry. It is shown that very thin Si NWs with [110] growth direction can nucleate at much lower process temperatures and pressures compared to thermal chemical vapor deposition where [111]-directed Si NWs are predominantly grown. These findings explain a host of experimental results and offer the possibility of energy- and matter-efficient, size- and orientation-controlled growth of [110] Si NWs for next-generation nanodevices.

Nanoscale plasma chemistry enables fast, size-selective nanotube nucleation

The possibility of fast, narrow-size/chirality nucleation of thin single-walled carbon nanotubes (SWCNTs) at low, device-tolerant process temperatures in a plasma-enhanced chemical vapor deposition (CVD) is demonstrated using multiphase, multiscale numerical experiments. These effects are due to the unique nanoscale reactive plasma chemistry (NRPC) on the surfaces and within Au catalyst nanoparticles. The computed three-dimensional process parameter maps link the nanotube incubation times and the relative differences between the incubation times of SWCNTs of different sizes/chiralities to the main plasma- and precursor gas-specific parameters and explain recent experimental observations. It is shown that the unique NRPC leads not only to much faster nucleation of thin nanotubes at much lower process temperatures, but also to better selectivity between the incubation times of SWCNTs with different sizes and chiralities, compared to thermal CVD. These results are used to propose a time-programmed kinetic approach based on fast-responding plasmas which control the size-selective, narrow-chirality nucleation and growth of thin SWCNTs. This approach is generic and can be used for other nanostructure and materials systems.

Energy and matter-efficient size-selective growth of thin quantum wires in a plasma

It is shown that plasmas can minimize the adverse Gibbs-Thompson effect in thin quantum wire growth. The model of Si nanowirenucleation includes the unprecedented combination of the plasma sheath, ion- and radical-induced species creation and heating effects on the surface and within an Au catalyst nanoparticle. Compared to neutral gas thermal processes, much thinner, size-selective wires can nucleate at the same temperature and pressure while much lower energy and matter budget is needed to grow same-size wires. This explains the experimental observations and may lead to energy- and matter-efficient synthesis of a broader range of one-dimensional quantum structures.

Increased size selectivity of Si quantum dots on SiC at low substrate temperatures : an ion-assisted self-organization approach

A simple, effective, and innovative approach based on ion-assisted self-organization is proposed to synthesize size-selected Si quantum dots (QDs) on SiC substrates at low substrate temperatures. Using hybrid numerical simulations, the formation of Si QDs through a self-organization approach is investigated by taking into account two distinct cases of Si QD formation using the ionization energy approximation theory, which considers ionized in-fluxes containing Si3+ and Si1+ ions in the presence of a microscopic nonuniform electric field induced by a variable surface bias. The results show that the highest percentage of the surface coverage by 1 and 2 nm size-selected QDs was achieved using a bias of -20 V and ions in the lowest charge state, namely, Si1+ ions in a low substrate temperature range (227-327 °C). As low substrate temperatures (≤500 °C) are desirable from a technological point of view, because (i) low-temperature deposition techniques are compatible with current thin-film Si-based solar cell fabrication and (ii) high processing temperatures can frequently cause damage to other components in electronic devices and destroy the tandem structure of Si QD-based third-generation solar cells, our results are highly relevant to the development of the third-generation all-Si tandem photovoltaic solar cells.