The purpose of this pilot study was to explore the feasibility of using hand drawn images to identify symbol components for incorporation into warning symbol design software. This software will use an interactive evol...
The purpose of this pilot study was to explore the feasibility of using hand drawn images to identify symbol components for incorporation into warning symbol design software. This software will use an interactive evolutionary computation (IEC) algorithm to generate and evolve symbols mathematically described by a set of numerical parameters. Therefore, participants (N = 100) ages 19–43 (x = 23.2) were recruited to determine these symbol design parameters. Participants were invited to hand draw warning symbols for three referents: fall from elevation, hearing protection, and hazardous atmosphere. A panel of design engineers determined 27 attributes were present in the fall from elevation, 19 in the hearing protection, and 25 in the hazardous atmosphere images. A direct clustering algorithm was used to determine which attributes, or symbol parameters, were most commonly present or conspicuously absent among the clustered image families. For the fall from elevation, hearing protection and hazardous atmosphere referents, the clustering algorithm identified six, four and four symbol parameters, respectively, primarily responsible for distinguishing one drawn symbol from another. Thus, these parameters will be included as evolvable genes in the IEC software.
This paper investigates the applicability of Gaussian processes (GP) classification for recognition of articulated and deformable human motions from image sequences. Using tensor subspace analysis (TSA), space-time hu...
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ISBN:
(纸本)9781424421749
This paper investigates the applicability of Gaussian processes (GP) classification for recognition of articulated and deformable human motions from image sequences. Using tensor subspace analysis (TSA), space-time human silhouettes (extracted from motion videos) are transformed to low-dimensional multivariate time series, based on which structure-based statistical features are calculated to summarize the motion properties. GP classification is then used to learn and predict motion categories. Experimental results on two real-world state-of-the-art datasets show that the proposed approach is effective, and outperforms support vector machine (SVM).
The Modeling in softwareengineering (MiSE) workshops are a collaboration between the ICSE and MoDELS research communities, with a focus on using models to facilitate software development.
ISBN:
(纸本)9781605580791
The Modeling in softwareengineering (MiSE) workshops are a collaboration between the ICSE and MoDELS research communities, with a focus on using models to facilitate software development.
Large-scale computing environments, such as TeraGrid, Distributed ASCI Supercomputer (DAS), and Gridpsila5000, have been using resource co-allocation to execute applications on multiple sites. Their schedulers work wi...
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Large-scale computing environments, such as TeraGrid, Distributed ASCI Supercomputer (DAS), and Gridpsila5000, have been using resource co-allocation to execute applications on multiple sites. Their schedulers work with requests that contain imprecise estimations provided by users. This lack of accuracy generates fragments inside the scheduling queues that can be filled by rescheduling both local and multi-site requests. Current resource co-allocation solutions rely on advance reservations to ensure that users can access all the resources at the same time. These coallocation requests cannot be rescheduled if they are based on rigid advance reservations. In this work, we investigate the impact of rescheduling co-allocation requests based on flexible advance reservations and processor remapping. The metascheduler can modify the start time of each job component and remap the number of processors they use in each site. The experimental results show that local jobs may not fill all the fragments in the scheduling queues and hence rescheduling co-allocation requests reduces response time of both local and multi-site jobs. Moreover, we have observed in some scenarios that processor remapping increases the chances of placing the tasks of multi-site jobs into a single cluster, thus eliminating the inter-cluster network overhead.
Since many organizations recently decide to implement and publish their applications over Internet, the number of Web services has dramatically increased. In many cases, a single service is not sufficient to respond t...
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Since many organizations recently decide to implement and publish their applications over Internet, the number of Web services has dramatically increased. In many cases, a single service is not sufficient to respond to the user’s request. In order to tackle this problem, services have to be combined together. Therefore, composition of Web services is one of the recent critical issues. Several approaches have been presented, to tackle this problem. In this paper, we classify these approaches into four categories namely Workflow-based, AI-planning based, Syntactic-based, and Ontology-based. Then, we describe and compare these approaches using some criteria (like QoS, scalability, and correctness). The overall results indicate that some AI-planning and Ontology based approaches like HTN-DL and WSMO satisfy most of the criteria.
Web services are the preferred standards-based way to realize service oriented architecture (SOA) computing. A problem that has become one of the recent critical issues is automated composition of Web services. A numb...
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Web services are the preferred standards-based way to realize service oriented architecture (SOA) computing. A problem that has become one of the recent critical issues is automated composition of Web services. A number of approaches have been proposed to resolve the problem. However, discovery and composition of Web services have been neglected by majority of those approaches. In this paper, we propose an approach called AIMO, based on AI-planning and Web service modeling ontology (WSMO), which are adapted and extended to tackle the mentioned problem. Moreover, we propose a translator to provide interaction between WSMO and AI-planning. We start with presenting the AIMO architecture which shows all components of the proposed approach. Finally, a simple case study is designed to test some components of AIMO. The preliminary results of the test demonstrate that our approach provides an applicable solution.
In this paper we focus on the notion of robust matrix root-clustering analysis in a union of regions that are possibly disjoint and non symmetric. Indeed this work aims at computing a bound on the size of the uncertai...
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In this paper we focus on the notion of robust matrix root-clustering analysis in a union of regions that are possibly disjoint and non symmetric. Indeed this work aims at computing a bound on the size of the uncertainty domain preserving matrix D u -stability. A Linear Fractional Transform (LFT) uncertainty is considered. To reduce conservatism, a new approach, based on some generalized S-procedure, is addressed. In the case where the studied matrices depend afflnely on the uncertain parameters or when the studied matrices are subject to polytopic uncertainty, it is known that recently developed L.M.J conditions are effective to assess the robust performance in a less conservative fashion. This paper further extends the preceding results and propose a unified way to obtain new L.M.J conditions even in the case of rational parameter dependence. Some conservatism induced by some techniques encountered in the literature is here reduced .
As users increasingly require better quality of service from grids, resource management and scheduling mechanisms have to evolve in order to satisfy competing demands on limited resources. Traditional schedulers for g...
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As users increasingly require better quality of service from grids, resource management and scheduling mechanisms have to evolve in order to satisfy competing demands on limited resources. Traditional schedulers for grids are system centric and favour system performance over increasing userpsilas utility. On the other hand market oriented schedulers are price-based systems that favour users but are based solely on user valuations. This paper proposes a novel meta-scheduler that unifies the advantages of both the systems for benefiting both users and resources. In order to do that, we design a valuation metric for userpsilas applications and computational resources based on multi-criteria requirements of users and resource load. The meta-scheduler maps user applications to suitable distributed resources using a continuous double auction (CDA). Through simulation, we compare our scheduling mechanism against other common mechanisms used by current meta-schedulers. The results show that our meta-scheduler mechanism can satisfy more users than the others while still meeting traditional system-centric performance criteria such as average load and deadline of applications.
This paper introduces a novel particle swarm optimization algorithm based on the concept of black holes in physics, called random black hole particle swarm optimization (RBH-PSO) for the first time. In each dimension ...
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ISBN:
(纸本)9781424423101
This paper introduces a novel particle swarm optimization algorithm based on the concept of black holes in physics, called random black hole particle swarm optimization (RBH-PSO) for the first time. In each dimension of a particle, we randomly generate a black hole located nearest to the best particle of the swarm in current generation and then randomly pull particles of the swarm into the black hole with a probability p. By this mechanism of random black hole, we can give all the particles another interesting direction to converge as well as another chance to fly out of local minima when a premature convergence happens. Several experiments on fifteen benchmark test functions are conducted to demonstrate that the proposed RBH-PSO algorithm is able to speedup the evolution process distinctly and improve the performance of global optimizer greatly. Finally, an actual application of the proposed algorithm to spam detection is conducted then compared to other three current methods.
We model the Sum and Product Riddle inpublic announcement logic, which is interpreted on an epistemic Kripke model. The model is symbolically represented as a finite state program with n agents. A model checking metho...
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