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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.
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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.
    Operations Research for Health Care. 09/2014;
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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.
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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.
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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.
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    Proceedings of the 2nd Workshop of Arabic Corpus Linguistics WACL-2; 07/2013
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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.
    03/2013;
  • Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences 01/2013; 371(1983):20120082.
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    ABSTRACT: Cloud computing technologies have reached a high level of development, yet a number of obstacles still exist that must be overcome before widespread commercial adoption can become a reality. In a cloud environment, end users requesting services and cloud providers negotiate service-level agreements (SLAs) that provide explicit statements of all expectations and obligations of the participants. If cloud computing is to experience widespread commercial adoption, then incorporating risk assessment techniques is essential during SLA negotiation and service operation. This article focuses on the legal issues surrounding risk assessment in cloud computing. Specifically, it analyses risk regarding data protection and security, and presents the requirements of an inherent risk inventory. The usefulness of such a risk inventory is described in the context of the OPTIMIS project.
    Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences 01/2013; 371(1983):20120075.
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    ABSTRACT: As one of the emerging algorithms in the field of Artificial Immune Systems (AIS), the Dendritic Cell Algorithm (DCA) has been successfully applied to a number of challenging real-world problems. However, one criticism is the lack of a formal definition, which could result in ambiguity for understanding the algorithm. Moreover, previous investigations have mainly focused on its empirical aspects. Therefore, it is necessary to provide a formal definition of the algorithm, as well as to perform runtime analyses to reveal its theoretical aspects. In this paper, we define the deterministic version of the DCA, named the dDCA, using set theory and mathematical functions. Runtime analyses of the standard algorithm and the one with additional segmentation are performed. Our analysis suggests that the standard dDCA has a runtime complexity of O(n(2)) for the worst-case scenario, where n is the number of input data instances. The introduction of segmentation changes the algorithm's worst case runtime complexity to O(max(nN,nz)), for DC population size N with size of each segment z. Finally, two runtime variables of the algorithm are formulated based on the input data, to understand its runtime behaviour as guidelines for further development.
    Bio Systems 01/2013;
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KI-97: Advances in Artificial Intelligence, 21st Annual German Conference on Artificial Intelligence, Freiburg, Germany, September 9-12, 1997, Proceedings; 01/1997
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