999 resultados para membrane computing
Resumo:
The behaviour of ion channels within cardiac and neuronal cells is intrinsically stochastic in nature. When the number of channels is small this stochastic noise is large and can have an impact on the dynamics of the system which is potentially an issue when modelling small neurons and drug block in cardiac cells. While exact methods correctly capture the stochastic dynamics of a system they are computationally expensive, restricting their inclusion into tissue level models and so approximations to exact methods are often used instead. The other issue in modelling ion channel dynamics is that the transition rates are voltage dependent, adding a level of complexity as the channel dynamics are coupled to the membrane potential. By assuming that such transition rates are constant over each time step, it is possible to derive a stochastic differential equation (SDE), in the same manner as for biochemical reaction networks, that describes the stochastic dynamics of ion channels. While such a model is more computationally efficient than exact methods we show that there are analytical problems with the resulting SDE as well as issues in using current numerical schemes to solve such an equation. We therefore make two contributions: develop a different model to describe the stochastic ion channel dynamics that analytically behaves in the correct manner and also discuss numerical methods that preserve the analytical properties of the model.
Resumo:
We describe a model of computation of the parallel type, which we call 'computing with bio-agents', based on the concept that motions of biological objects such as bacteria or protein molecular motors in confined spaces can be regarded as computations. We begin with the observation that the geometric nature of the physical structures in which model biological objects move modulates the motions of the latter. Consequently, by changing the geometry, one can control the characteristic trajectories of the objects; on the basis of this, we argue that such systems are computing devices. We investigate the computing power of mobile bio-agent systems and show that they are computationally universal in the sense that they are capable of computing any Boolean function in parallel. We argue also that using appropriate conditions, bio-agent systems can solve NP-complete problems in probabilistic polynomial time.
Resumo:
Video games have shown great potential as tools that both engage and motivate players to achieve tasks and build communities in fantasy worlds. We propose that the application of game elements to real world activities can aid in delivering contextual information in interesting ways and help young people to engage in everyday events. Our research will explore how we can unite utility and fun to enhance information delivery, encourage participation, build communities and engage users with utilitarian events situated in the real world. This research aims to identify key game elements that work effectively to engage young digital natives, and provide guidelines to influence the design of interactions and interfaces for event applications in the future. This research will primarily contribute to areas of user experience and pervasive gaming.
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The increasing capability of mobile devices and social networks to gather contextual and social data has led to increased interest in context-aware computing for mobile applications. This paper explores ways of reconciling two different viewpoints of context, representational and interactional, that have arisen respectively from technical and social science perspectives on context-aware computing. Through a case study in agile ridesharing, the importance of dynamic context control, historical context and broader context is discussed. We build upon earlier work that has sought to address the divide by further explicating the problem in the mobile context and expanding on the design approaches.
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The final shape of the "Internet of Things" ubiquitous computing promises relies on a cybernetic system of inputs (in the form of sensory information), computation or decision making (based on the prefiguration of rules, contexts, and user-generated or defined metadata), and outputs (associated action from ubiquitous computing devices). My interest in this paper lies in the computational intelligences that suture these positions together, and how positioning these intelligences as autonomous agents extends the dialogue between human-users and ubiquitous computing technology. Drawing specifically on the scenarios surrounding the employment of ubiquitous computing within aged care, I argue that agency is something that cannot be traded without serious consideration of the associated ethics.
Resumo:
On obstacle-cluttered construction sites where heavy equipment is in use, safety issues are of major concern. The main objective of this paper is to develop a framework with algorithms for obstacle avoidance and path planning based on real-time three-dimensional job site models to improve safety during equipment operation. These algorithms have the potential to prevent collisions between heavy equipment vehicles and other on-site objects. In this study, algorithms were developed for image data acquisition, real-time 3D spatial modeling, obstacle avoidance, and shortest path finding and were all integrated to construct a comprehensive collision-free path. Preliminary research results show that the proposed approach is feasible and has the potential to be used as an active safety feature for heavy equipment.
Resumo:
This special issue of the Journal of Urban Technology brings together five articles that are based on presentations given at the Street Computing workshop held on 24 November 2009 in Melbourne in conjunction with the Australian Computer-Human Interaction conference (OZCHI 2009). Our own article introduces the Street Computing vision and explores the potential, challenges and foundations of this research vision. In order to do so, we first look at the currently available sources of information and discuss their link to existing research efforts. Section 2 then introduces the notion of Street Computing and our research approach in more detail. Section 3 looks beyond the core concept itself and summarises related work in this field of interest.
Resumo:
From location-aware computing to mining the social web, representations of context have promised to make better software applications. The opportunities and challenges of context-aware computing from representational, situated and interactional perspectives have been well documented, but arguments from the perspective of design are somewhat disparate. This paper draws on both theoretical perspectives and a design framing, using the problem of designing a social mobile agile ridesharing system, in order to reflect upon and call for broader design approaches for context-aware computing and human-computer Interaction research in general.
Resumo:
Filtration membrane technology has already been employed to remove various organic effluents produced from the textile, paper, plastic, leather, food and mineral processing industries. To improve membrane efficiency and alleviate membrane fouling, an integrated approach is adopted that combines membrane filtration and photocatalysis technology. In this study, alumina nanofiber (AF) membranes with pore size of about 10 nm (determined by the liquid-liquid displacement method) have been synthesized through an in situ hydrothermal reaction, which permitted a large flux and achieved high selectivity. Silver nanoparticles (Ag NPs) are subsequently doped on the nanofibers of the membranes. Silver nanoparticles can strongly absorb visible light due to the surface plasmon resonance (SPR) effect, and thus induce photocatalytic degradation of organic dyes, including anionic, cationic and neutral dyes, under visible light irradiation. In this integrated system, the dyes are retained on the membrane surface, their concentration in the vicinity of the Ag NPs are high and thus can be efficiently decomposed. Meanwhile, the usual flux deterioration caused by the accumulation of the filtered dyes in the passage pores can be avoided. For example, when an aqueous solution containing methylene blue is processed using an integrated membrane, a large flux of 200 L m-2 h-1 and a stable permeating selectivity of 85% were achieved. The combined photocatalysis and filtration function leads to superior performance of the integrated membranes, which have a potential to be used for the removal of organic pollutants in drinking water.
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In comparison to our knowledge of the recycling of adhesion receptors and actin assembly, exactly how the cell controls its surface membrane to form a lamellipodium during migration is poorly understood. Here, we show the recycling endosome membrane is incorporated into the leading edge of a migrating cell to expand lamellipodia membrane. We have identified the SNARE complex that is necessary for fusion of the recycling endosome with the cell surface, as consisting of the R-SNARE VAMP3 on the recycling endosome partnering with the surface Q-SNARE Stx4/SNAP23, which was found to translocate and accumulate on the leading edge of migrating cells. Increasing VAMP3-mediated fusion of the recycling endosome with the surface increased membrane ruffling, while inhibition of VAMP3-mediated fusion showed that incorporation of the recycling endosome is necessary for efficient lamellipodia formation. At the same time, insertion of this recycling endosome membrane also delivers its cargo integrin α5β1 to the cell surface. The loss of this extra membrane for lamellipodia expansion and delivery of cargo in cells resulted in macrophages with a diminished capacity to effectively migrate. Thus, the recycling endosome membrane is incorporated into the leading edge and this aids expansion of the lamellipodia and simultaneously delivers integrins necessary for efficient cell migration.
Resumo:
Software as a Service (SaaS) is gaining more and more attention from software users and providers recently. This has raised many new challenges to SaaS providers in providing better SaaSes that suit everyone needs at minimum costs. One of the emerging approaches in tackling this challenge is by delivering the SaaS as a composite SaaS. Delivering it in such an approach has a number of benefits, including flexible offering of the SaaS functions and decreased cost of subscription for users. However, this approach also introduces new problems for SaaS resource management in a Cloud data centre. We present the problem of composite SaaS resource management in Cloud data centre, specifically on its initial placement and resource optimization problems aiming at improving the SaaS performance based on its execution time as well as minimizing the resource usage. Our approach differs from existing literature because it addresses the problems resulting from composite SaaS characteristics, where we focus on the SaaS requirements, constraints and interdependencies. The problems are tackled using evolutionary algorithms. Experimental results demonstrate the efficiency and the scalability of the proposed algorithms.
Resumo:
Recently, Software as a Service (SaaS) in Cloud computing, has become more and more significant among software users and providers. To offer a SaaS with flexible functions at a low cost, SaaS providers have focused on the decomposition of the SaaS functionalities, or known as composite SaaS. This approach has introduced new challenges in SaaS resource management in data centres. One of the challenges is managing the resources allocated to the composite SaaS. Due to the dynamic environment of a Cloud data centre, resources that have been initially allocated to SaaS components may be overloaded or wasted. As such, reconfiguration for the components’ placement is triggered to maintain the performance of the composite SaaS. However, existing approaches often ignore the communication or dependencies between SaaS components in their implementation. In a composite SaaS, it is important to include these elements, as they will directly affect the performance of the SaaS. This paper will propose a Grouping Genetic Algorithm (GGA) for multiple composite SaaS application component clustering in Cloud computing that will address this gap. To the best of our knowledge, this is the first attempt to handle multiple composite SaaS reconfiguration placement in a dynamic Cloud environment. The experimental results demonstrate the feasibility and the scalability of the GGA.
In the pursuit of effective affective computing : the relationship between features and registration
Resumo:
For facial expression recognition systems to be applicable in the real world, they need to be able to detect and track a previously unseen person's face and its facial movements accurately in realistic environments. A highly plausible solution involves performing a "dense" form of alignment, where 60-70 fiducial facial points are tracked with high accuracy. The problem is that, in practice, this type of dense alignment had so far been impossible to achieve in a generic sense, mainly due to poor reliability and robustness. Instead, many expression detection methods have opted for a "coarse" form of face alignment, followed by an application of a biologically inspired appearance descriptor such as the histogram of oriented gradients or Gabor magnitudes. Encouragingly, recent advances to a number of dense alignment algorithms have demonstrated both high reliability and accuracy for unseen subjects [e.g., constrained local models (CLMs)]. This begs the question: Aside from countering against illumination variation, what do these appearance descriptors do that standard pixel representations do not? In this paper, we show that, when close to perfect alignment is obtained, there is no real benefit in employing these different appearance-based representations (under consistent illumination conditions). In fact, when misalignment does occur, we show that these appearance descriptors do work well by encoding robustness to alignment error. For this work, we compared two popular methods for dense alignment-subject-dependent active appearance models versus subject-independent CLMs-on the task of action-unit detection. These comparisons were conducted through a battery of experiments across various publicly available data sets (i.e., CK+, Pain, M3, and GEMEP-FERA). We also report our performance in the recent 2011 Facial Expression Recognition and Analysis Challenge for the subject-independent task.
Resumo:
A composite SaaS (Software as a Service) is a software that is comprised of several software components and data components. The composite SaaS placement problem is to determine where each of the components should be deployed in a cloud computing environment such that the performance of the composite SaaS is optimal. From the computational point of view, the composite SaaS placement problem is a large-scale combinatorial optimization problem. Thus, an Iterative Cooperative Co-evolutionary Genetic Algorithm (ICCGA) was proposed. The ICCGA can find reasonable quality of solutions. However, its computation time is noticeably slow. Aiming at improving the computation time, we propose an unsynchronized Parallel Cooperative Co-evolutionary Genetic Algorithm (PCCGA) in this paper. Experimental results have shown that the PCCGA not only has quicker computation time, but also generates better quality of solutions than the ICCGA.