6,934 research outputs found
From fracture to fragmentation: discrete element modeling -- Complexity of crackling noise and fragmentation phenomena revealed by discrete element simulations
Discrete element modelling (DEM) is one of the most efficient computational
approaches to the fracture processes of heterogeneous materials on mesoscopic
scales. From the dynamics of single crack propagation through the statistics of
crack ensembles to the rapid fragmentation of materials DEM had a substantial
contribution to our understanding over the past decades. Recently, the
combination of DEM with other simulation techniques like Finite Element
Modelling further extended the field of applicability. In this paper we briefly
review the motivations and basic idea behind the DEM approach to cohesive
particulate matter and then we give an overview of on-going developments and
applications of the method focusing on two fields where recent success has been
achieved. We discuss current challenges of this rapidly evolving field and
outline possible future perspectives and debates
A Comparison of Clustering Techniques for Malware Analysis
In this research, we apply clustering techniques to the malware detection problem. Our goal is to classify malware as part of a fully automated detection strategy. We compute clusters using the well-known �-means and EM clustering algorithms, with scores obtained from Hidden Markov Models (HMM). The previous work in this area consists of using HMM and �-means clustering technique to achieve the same. The current effort aims to extend it to use EM clustering technique for detection and also compare this technique with the �-means clustering
Geo-located Twitter as the proxy for global mobility patterns
In the advent of a pervasive presence of location sharing services
researchers gained an unprecedented access to the direct records of human
activity in space and time. This paper analyses geo-located Twitter messages in
order to uncover global patterns of human mobility. Based on a dataset of
almost a billion tweets recorded in 2012 we estimate volumes of international
travelers in respect to their country of residence. We examine mobility
profiles of different nations looking at the characteristics such as mobility
rate, radius of gyration, diversity of destinations and a balance of the
inflows and outflows. The temporal patterns disclose the universal seasons of
increased international mobility and the peculiar national nature of overseen
travels. Our analysis of the community structure of the Twitter mobility
network, obtained with the iterative network partitioning, reveals spatially
cohesive regions that follow the regional division of the world. Finally, we
validate our result with the global tourism statistics and mobility models
provided by other authors, and argue that Twitter is a viable source to
understand and quantify global mobility patterns.Comment: 17 pages, 13 figure
Assessing and augmenting SCADA cyber security: a survey of techniques
SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability
Vectors to ore in replacive volcanogenic massive sulfide (VMS) deposits of the northern Iberian Pyrite Belt: Mineral zoning, whole rock geochemistry, and application of portable X-ray fluorescence
In this work we have performed a detailed study of vectors to ore to a representative volcanic-rock-hosted replacive volcanogenic massive sulfide (VMS) deposit located in the northern Iberian Pyrite Belt (Spain), the Aguas Teñidas deposit. The investigated vectors include the following: (1) mineralogical zoning, (2) host sequence characterization and mineralized unit identification based on whole rock geochemistry discrimination diagrams, (3) study of the characteristics and behaviour of whole rock geochemical anomalies around the ore (e.g. alteration-related compositional changes, characteristics and extent of geochemical halos of indicative elements such as Cu, Zn, Pb, Sb, Tl, and Ba around the deposit), and (4) application of portable X-ray fluorescence (p-XRF) analysis to the detection of the previous vectors
Quick survey of graph-based fraud detection methods
In general, anomaly detection is the problem of distinguishing between normal
data samples with well defined patterns or signatures and those that do not
conform to the expected profiles. Financial transactions, customer reviews,
social media posts are all characterized by relational information. In these
networks, fraudulent behaviour may appear as a distinctive graph edge, such as
spam message, a node or a larger subgraph structure, such as when a group of
clients engage in money laundering schemes. Most commonly, these networks are
represented as attributed graphs, with numerical features complementing
relational information. We present a survey on anomaly detection techniques
used for fraud detection that exploit both the graph structure underlying the
data and the contextual information contained in the attributes
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