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    ABSTRACT: In order to fully exploit the concept of Smart Home, challenges associated with multiple device management in consumer facing applications have to be addressed. Specific to this is the management of resource usage in the home via the improved utilization of devices, this is achieved by integration with the wider environment they operate in. The traditional model of the isolated device no longer applies, the future home will be connected with services provided by third parties ranging from supermarkets to domestic appliance manufacturers. In order to achieve this risk based integrated device management and contextualization is explored in this paper based on the cloud computing model. We produce an architecture and evaluate risk models to assist in this management of devices from a security, privacy and resource management perspective. We later propose an expansion on the risk based approach to wider data sharing between the home and external services using the key indicators of TREC (Trust, Risk, Eco-efficiency and Cost). The paper contributes to Smart Home research by defining how Cloud service management principles of risk and contextualization for virtual machines can produce solutions to emerging challenges facing a new generation of Smart Home devices.
    Future Generation Computer Systems 09/2014; 38:13–22. DOI:10.1016/j.future.2013.08.006
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    ABSTRACT: This paper studies a multi-criteria optimization problem which appears in the context of booking chemotherapy appointments. The main feature of the model under study is the requirement to book for each patient multiple appointments which should follow a pre-specified multi-day pattern. Each appointment involves several nurse activities which should also follow a pre-specified intra-day pattern. The main objectives are to minimize patients’ waiting times and peaks of nurses’ workload for an outpatient clinic. Our solution approach is based on the concept of a multi-level template schedule which is generated for a set of artificial patients with typical treatment patterns. There are two stages in template generation: the multi-day stage, which fixes appointment dates for all artificial patients, and the intra-day stage, which fixes for each day appointment starting times and patient allocation to nurses. The running schedule is created by considering actual patients one by one as they arrive to the clinic. Booking appointments for each new patient is performed by assigning appropriate dates and times of the template schedule following the prescribed multi-day and intra-day patterns. Additional rescheduling procedure is used to re-optimize intra-day schedules on a treatment day or shortly beforehand. The key stages of the scheduling process are modeled as integer linear programs and solved using CPLEX solver. We demonstrate the effectiveness of our approach through case-based scenarios derived from a real clinic and discuss the advantages that the multi-level template can bring.
    09/2014; 3(3). DOI:10.1016/j.orhc.2014.02.002
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    ABSTRACT: With a fully reconstructed and extensively characterized neural circuit, the nematode Caenorhabditis elegans is a promising model system for integrating our understanding of neuronal, circuit and whole-animal dynamics. Fundamental to addressing this challenge is the need to consider the tight neuronal-environmental coupling that allows the animal to survive and adapt to changing conditions. Locomotion behaviors are affected by environmental variables both at the biomechanical level and via adaptive sensory responses that drive and modulate premotor and motor circuits. Here we review significant advances in our understanding of proprioceptive control of locomotion, and more abstract models of spatial orientation and navigation. The growing evidence of the complexity of the underlying circuits suggests that the intuition gained is but the first step in elucidating the secrets of neural computation in this relatively simple system.
    Current opinion in neurobiology 04/2014; 25C:99-106. DOI:10.1016/j.conb.2013.12.003
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    ABSTRACT: The sessile microbial communities known as biofilms exhibit varying architectures as environmental factors are varied, which for immersed biofilms includes the shear rate of the surrounding flow. Here we modify an established agent-based biofilm model to include affine flow and employ it to analyze the growth of surface roughness of single-species, three-dimensional biofilms. We find linear growth laws for surface geometry in both horizontal and vertical directions and measure the thickness of the active surface layer, which is shown to anticorrelate with roughness. Flow is shown to monotonically reduce surface roughness without affecting the thickness of the active layer. We argue that the rapid roughening is due to nonlocal surface interactions mediated by the nutrient field, which are curtailed when advection competes with diffusion. We further argue the need for simplified models to elucidate the underlying mechanisms coupling flow to growth.
    Physical Review E 09/2013; 88(3-1):032702. DOI:10.1103/PhysRevE.88.032702
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    ABSTRACT: Analytical and numerical calculations are presented for the mechanical response of fiber networks in a state of axisymmetric prestress, in the limit where geometric nonlinearities such as fiber rotation are negligible. This allows us to focus on the anisotropy deriving purely from the nonlinear force-extension curves of individual fibers. The number of independent elastic coefficients for isotropic, axisymmetric, and fully anisotropic networks are enumerated before deriving expressions for the response to a locally applied force that can be tested against, e.g., microrheology experiments. Localized forces can generate anisotropy away from the point of application, so numerical integration of nonlinear continuum equations is employed to determine the stress field, and induced mechanical anisotropy, at points located directly behind and in front of a force monopole. Results are presented for the wormlike chain model in normalized forms, allowing them to be easily mapped to a range of systems. Finally, the relevance of these findings to naturally occurring systems and directions for future investigation are discussed.
    Physical Review E 08/2013; 88(2):022717. DOI:10.1103/PhysRevE.88.022717
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    Proceedings of the 2nd Workshop of Arabic Corpus Linguistics WACL-2; 07/2013
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    ABSTRACT: An integer fixed-charge multicommodity flow (FCMF) model is used as the first part of a two-phase approach for train unit scheduling, and solved by an exact branch- and-price method. To strengthen knapsack constraints and deal with complicated scenarios arisen in the integer linear program (ILP) from the integer FCMF model, preprocessing is used by computing convex hulls of sets of points representing all possible train formations utilizing multiple unit types.
    Electronic Notes in Discrete Mathematics 06/2013; 41:165–172. DOI:10.1016/j.endm.2013.05.089
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    ABSTRACT: Three dimensional (3D) tissue reconstructions from the histology images with different stains allows the spatial alignment of structural and functional elements highlighted by different stains for quantitative study of many physiological and pathological phenomena. This has significant potential to improve the understanding of the growth patterns and the spatial arrangement of diseased cells, and enhance the study of biomechanical behavior of the tissue structures towards better treatments (e.g. tissue-engineering applications). This paper evaluates three strategies for 3D reconstruction from sets of two dimensional (2D) histological sections with different stains, by combining methods of 2D multi-stain registration and 3D volumetric reconstruction from same stain sections. The different strategies have been evaluated on two liver specimens (80 sections in total) stained with Hematoxylin and Eosin (H and E), Sirius Red, and Cytokeratin (CK) 7. A strategy of using multi-stain registration to align images of a second stain to a volume reconstructed by same-stain registration results in the lowest overall error, although an interlaced image registration approach may be more robust to poor section quality.
    03/2013; 4(Suppl):S7. DOI:10.4103/2153-3539.109864
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    ABSTRACT: As a critical technique in a digital pathology laboratory, automatic nuclear detection has been investigated for more than one decade. Conventional methods work on the raw images directly whose color/intensity homogeneity within tissue/cell areas are undermined due to artefacts such as uneven staining, making the subsequent binarization process prone to error. This paper concerns detecting cell nuclei automatically from digital pathology images by enhancing the color homogeneity as a pre-processing step. Unlike previous watershed based algorithms relying on post-processing of the watershed, we present a new method that incorporates the staining information of pathological slides in the analysis. This pre-processing step strengthens the color homogeneity within the nuclear areas as well as the background areas, while keeping the nuclear edges sharp. Proof of convergence for the proposed algorithm is also provided. After pre-processing, Otsu's threshold is applied to binarize the image, which is further segmented via watershed. To keep a proper compromise between removing overlapping and avoiding over-segmentation, a naive Bayes classifier is designed to refine the splits suggested by the watershed segmentation. The method is validated with 10 sets of 1000 × 1000 pathology images of lymphoma from one digital slide. The mean precision and recall rates are 87% and 91%, corresponding to a mean F-score equal to 89%. Standard deviations for these performance indicators are 5.1%, 1.6% and 3.2% respectively. The precision/recall performance obtained indicates that the proposed method outperforms several other alternatives. In particular, for nuclear detection, stain guided mean-shift (SGMS) is more effective than the direct application of mean-shift in pre-processing. Our experiments also show that pre-processing the digital pathology images with SGMS gives better results than conventional watershed algorithms. Nevertheless, as only one type of tissue is tested in this paper, a further study is planned to enhance the robustness of the algorithm so that other types of tissues/stains can also be processed reliably.
    03/2013; 4(Suppl):S6. DOI:10.4103/2153-3539.109863
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    ABSTRACT: In this paper I consider the much mulled over question of whether vagueness is an exclusively linguistic phenomenon, or whether there are actually things in the world that are intrinsically vague. I argue that vagueness affects our descriptions of real world objects in several different ways. It not only affects the identification of objects as being examples of some class, but also the individuation and demarcation criteria of objects. I present a formal semantics that models indeterminacy in both predicates and objects. A vague object is taken to be a referent of a singular term or variable, whose identity is fixed, but whose exact demarcation and constituents are indeterminate.
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Proceedings of NITS 3rd National Information Technology Symposium; 01/2011
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Future Generation Computer Systems 01/2012; DOI:10.1016/j.future.2011.05.022
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