Swarm scheduling approaches for work-flow applications with security constraints in distributed data-intensive computing environments

The scheduling problem in distributed data-intensive computing environments has become an active research topic due to the tremendous growth in grid and cloud computing environments. As an innovative distributed intelligent paradigm, swarm intelligence provides a novel approach to solving these potentially intractable problems. In this paper, we formulate the scheduling problem for work-flow applications with security constraints in distributed data-intensive computing environments and present a novel security constraint model. Several meta-heuristic adaptations to the particle swarm optimization algorithm are introduced to deal with the formulation of efficient schedules. A variable neighborhood particle swarm optimization algorithm is compared with a multi-start particle swarm optimization and multi-start genetic algorithm. Experimental results illustrate that population based meta-heuristics approaches usually provide a good balance between global exploration and local exploitation and their feasibility and effectiveness for scheduling work-flow applications. © 2010 Elsevier Inc. All rights reserved.

Bystander Signalling: Exploring Clinical Relevance Through New Approaches and New Models

Classical radiation biology research has centred on nuclear DNA as the main target of radiation-induced damage. Over the past two decades, this has been challenged by a significant amount of scientific evidence clearly showing radiation-induced cell signalling effects to have important roles in mediating overall radiobiological response. These effects, generally termed radiation-induced bystander effects (RIBEs) have challenged the traditional DNA targeted theory in radiation biology and highlighted an important role for cells not directly traversed by radiation. The multiplicity of experimental systems and exposure conditions in which RIBEs have been observed has hindered precise definitions of these effects. However, RIBEs have recently been classified for different relevant human radiation exposure scenarios in an attempt to clarify their role in vivo. Despite significant research efforts in this area, there is little direct evidence for their role in clinically relevant exposure scenarios. In this review, we explore the clinical relevance of RIBEs from classical experimental approaches through to novel models that have been used to further determine their potential implications in the clinic. 

Treatment approaches for diabetes and dyslipidemia

Dyslipidemia is an important risk factor for cardiovascular complications in persons with diabetes. Low-density lipoprotein-cholesterol (LDL-C) is the 'cornerstone' for assessment of lipoprotein-associated risk. However, LDL-C levels do not reflect the classic 'diabetic dyslipidemia' of hypertriglyceridemia and low high-density lipoprotein-cholesterol (HDL-C). Measurements of plasma apolipoprotein B100 concentrations and non-HDL-C may improve the definition of dyslipidemia. Statins, nicotinic acid and fibrates have roles in treating dyslipidemia in diabetes. Residual risk (i.e. risk that persists after correction of 'conventional' plasma lipoprotein abnormalities) is a new concept in the role of dyslipidemia in the pathogenesis of diabetic vascular complications. For example, regardless of plasma levels, lipoprotein extravasation through a leaking retinal blood barrier and subsequent modification may be crucial in the development of diabetic retinopathy. The current approach to the management of dyslipidemia in diabetes is briefly summarized, followed by a discussion of new concepts of residual risk and emerging lipoprotein-related mechanisms for vascular disease in diabetes.

Identifying optimal feeding habitat and proposed Marine Protected Areas (pMPAs) for the black-legged kittiwake (Rissa tridactyla) suggests a need for complementary management approaches

Marine Protected Areas (MPAs) are an important conservation tool. For marine predators, recent research has focused on the use of Species Distribution Models (SDMs) to identify proposed sites. We used a maximum entropy modelling approach based on static and dynamic oceanographic parameters to determine optimal feeding habitat for black-legged kittiwakes (Rissa tridactyla) at two colonies during two consecutive breeding seasons (2009 and 2010). A combination of Geographic Positioning System (GPS) loggers and Time-Depth Recorders (TDRs) attributed feeding activity to specific locations. Feeding areas were <30 km from the colony, <40 km from land, in productive waters, 25–175m deep. The predicted extent of optimal habitat declined at both colonies between 2009 and 2010 coincident with declines in reproductive success. Whilst the area of predicted optimal habitat changed, its location was spatially stable between years. There was a close match between observed feeding locations and habitat predicted as optimal at one colony (Lambay Island, Republic of Ireland), but a notable mismatch at the other (Rathlin Island, Northern Ireland). Designation of an MPA at Rathlin may, therefore, be less effective than a similar designation at Lambay perhaps due to the inherent variability in currents and sea state in the North Channel compared to the comparatively stable conditions in the central Irish Sea. Current strategies for designating MPAs do not accommodate likely future redistribution of resources due to climate change. We advocate the development of new approaches including dynamic MPAs that track changes in optimal habitat and non-colony specific ecosystem management.

Analysis of Bayesian classification-based approaches for Android malware detection

Mobile malware has been growing in scale and complexity spurred by the unabated uptake of smartphones worldwide. Android is fast becoming the most popular mobile platform resulting in sharp increase in malware targeting the platform. Additionally, Android malware is evolving rapidly to evade detection by traditional signature-based scanning. Despite current detection measures in place, timely discovery of new malware is still a critical issue. This calls for novel approaches to mitigate the growing threat of zero-day Android malware. Hence, the authors develop and analyse proactive machine-learning approaches based on Bayesian classification aimed at uncovering unknown Android malware via static analysis. The study, which is based on a large malware sample set of majority of the existing families, demonstrates detection capabilities with high accuracy. Empirical results and comparative analysis are presented offering useful insight towards development of effective static-analytic Bayesian classification-based solutions for detecting unknown Android malware.

Autoecological Approaches to Resolve Subjective Taxonomic Divisions within Arcellacea

Arcellacea (testate lobose amoebae) are important lacustrine environmental indicators that have been used in paleoclimatic reconstructions, assessing the effectiveness of mine tailings pond reclamation projects and for studying the effects of land use change in rural, industrial and urban settings. Recognition of ecophenotypically significant infra-specific ‘strains’ within arcellacean assemblages has the potential to enhance the utility of the group in characterizing contemporary and paleoenvironments. We present a novel approach which employs statistical tools to investigate the environmental and taxonomic significance of proposed strains. We test this approach on two identified strains: Difflugia protaeiformis Lamarck strain ‘acuminata’ (DPA), characterized by fine grained agglutination, and Difflugia protaeiformis Lamarck strain ‘claviformis’ (DPC), characterized by coarse grained agglutination. Redundancy analysis indicated that both organisms are associated with similar environmental variables. No relationship was observed between substrate particle size and abundance of DPC, indicating that DPC has a size preference for xenosomes during test construction. Thus DPC should not be designated as a distinct strain but rather form a species complex with DPA. This study elucidates the need to justify the designation of strains based on their autecology in addition to morphological stability.

Adaptive Fusion Of Particle Filtering And Spatio-Temporal Motion Energy For Human Tracking

Object tracking is an active research area nowadays due to its importance in human computer interface, teleconferencing and video surveillance. However, reliable tracking of objects in the presence of occlusions, pose and illumination changes is still a challenging topic. In this paper, we introduce a novel tracking approach that fuses two cues namely colour and spatio-temporal motion energy within a particle filter based framework. We conduct a measure of coherent motion over two image frames, which reveals the spatio-temporal dynamics of the target. At the same time, the importance of both colour and motion energy cues is determined in the stage of reliability evaluation. This determination helps maintain the performance of the tracking system against abrupt appearance changes. Experimental results demonstrate that the proposed method outperforms the other state of the art techniques in the used test datasets.

Drive-by bridge inspection from three different approaches

This study presents a vibration-based health monitoring strategy for short span bridges utilizing an inspection vehicle. How to screen the health condition of short span bridges in terms of a drive-by bridge inspection is described. Feasibility of the drive-by bridge inspection is investigated through a scaled laboratory moving vehicle experiment. The feasibility of using an instrumented vehicle to detect the natural frequency and changes in structural damping of a model bridge was observed. Observations also demonstrated the possibility of diagnosis of bridges by comparing patterns of identified bridge dynamic parameters through periodical monitoring. It was confirmed that the moving vehicle method identifies the damage location and severity well.

Co-Creating Knowledge Online: Approaches for Community Artists

Forming peer alliances to share and build knowledge is an important aspect of community arts practice, and these co-creation processes are increasingly being mediated by the internet. This paper offers guidance for practitioners who are interested in better utilising the internet to connect, share, and make new knowledge. It argues that new approaches are required to foster the organising activities that underpin online co-creation, building from the premise that people have become increasingly networked as individuals rather than in groups (Rainie and Wellman 2012: 6), and that these new ways of connecting enable new modes of peer-to-peer production and exchange. This position advocates that practitioners move beyond situating the internet as a platform for dissemination and a tool for co-creating media, to embrace its knowledge collaboration potential.

Drawing on a design experiment I developed to promote online knowledge co-creation, this paper suggests three development phases – developing connections, developing ideas, and developing agility – to ground six methods. They are: switching and routing, engaging in small trades of ideas with networked individuals; organising, co-ordinating networked individuals and their data; beta-release, offering ‘beta’ artifacts as knowledge trades; beta-testing, trialing and modifying other peoples ‘beta’ ideas; adapting, responding to technological disruption; and, reconfiguring, embracing opportunities offered by technological disruption. These approaches position knowledge co-creation as another capability of the community artist, along with co-creating art and media.

Dry computational approaches for wet medical problems

This is a report on the 4th international conference in 'Quantitative Biology and Bioinformatics in Modern Medicine' held in Belfast (UK), 19-20 September 2013. The aim of the conference was to bring together leading experts from a variety of different areas that are key for Systems Medicine to exchange novel findings and promote interdisciplinary ideas and collaborations.

ARTICLE: Anarchy and International Law: The Approaches of Hedley Bull and Noam Chomsky

Are anarchy and the law antithetical? Not so, as for more than 350 years international law has governed a legal order based on anarchy; wherein no central authority exists and law functions not on the basis of coercion but on cooperation whereby States must agree to each specific laws before it is bound by its obligations. This article contemplates two manners in which an anarchist might consider international law interesting: first, as a legal system which governs an anarchical society as described by Hedley Bull in line with the English School of International Relations; and second, as a manifestation of a State system which, though illegitimate can be utilized, as Noam Chomsky does, for tactical reasons to demonstrate its inconsistencies and thus weakening the system with the ultimate aim being its implosion