Search results for "Location"

Solving Graph Coloring Problems Using Learning Automata

2008

The graph coloring problem (GCP) is a widely studied combinatorial optimization problem with numerous applications, including time tabling, frequency assignment, and register allocation. The growing need for more efficient algorithms has led to the development of several GCP solvers. In this paper, we introduce the first GCP solver that is based on Learning Automata (LA). We enhance traditional Random Walk with LA-based learning capability, encoding the GCP as a Boolean satisfiability problem (SAT). Extensive experiments demonstrate that the LA significantly improve the performance of RW, thus laying the foundation for novel LA-based solutions to the GCP.

Optimal Resource Discovery Paths of Gnutella2

2008

This paper shows that the performance of peer-to-peer resource discovery algorithms is upper bounded by a k-Steiner minimum tree and proposes an algorithm locating near-optimal query paths for the peer-to-peer resource discovery problem. Global knowledge of the topology and the resources from the peer-to-peer network are required as an input to the algorithm. The algorithm provides an objective measure for defining how good local search algorithms are. The performance is evaluated in simulated peer-to-peer scenarios and in the measured Gnutella2 P2P network topology with four local search algorithms: breadth-first search, self-avoiding random walker, highest degree search and Dynamic Query …

E-learning approach of the graph coloring problem applied to register allocation in embedded systems

2016

The main aim of this paper consists in developing an effective e-learning tool, focused on evolutionary algorithms, in order to solve the graph coloring problem. Subsidiary, we apply graph coloring for register allocation in embedded systems. From didactic viewpoint, our tool has benefits in the learning process because it helps students to observe the relationship between the graph coloring problem and CPU registers allocation with the help of four developed modules: the genetic algorithm, the graphical viewer, the interference graph for a C program and a web application which collects the simulation results. All these applications are combined by a graphical interface which allows the use…

Non-cross-linked collagen type I/III materials enhance cell proliferation: in vitro and in vivo evidence

2014

Objective: To analyze Mucograft®(MG), a recently introduced collagen matrix, in vitro and in vivo, and compare it with BioGide®(BG), a well-established collagen membrane, as control. Material and Methods: A detailed analysis of the materials surface and ultra-structure was performed. Cellular growth patterns and proliferation rates of human fibroblasts on MG and BG were analyzed in vitro. In addition, the early tissue reaction of CD-1 mouse to these materials was analyzed by means of histological and histomorphometrical analysis. Results: MG showed a three-fold higher thickness both in dry and wet conditions, when compared to BG. The spongy surface of BG significantly differed from that of …

A central nervous system-focused treatment approach for people with frozen shoulder: protocol for a randomized clinical trial

2019

Background: Frozen shoulder (FS) is a musculoskeletal condition of poorly understood etiology that results in shoulder pain and large mobility deficits. Despite some physical therapy interventions, such as joint mobilization and exercise, having shown therapeutic benefit, a definitive treatment does not currently exist. The aim of this study will be to compare the effectiveness of a central nervous system (CNS)-directed treatment program versus a standard medical and physical therapy care program on outcomes in participants with FS. Methods/design: The study is a two-group, randomized clinical trial with blinding of participants and assessors. Participants will be recruited via referrals fr…

Influence of respiratory rate and end-expiratory pressure variation on cyclic alveolar recruitment in an experimental lung injury model

2012

Introduction Cyclic alveolar recruitment/derecruitment (R/D) is an important mechanism of ventilator-associated lung injury. In experimental models this process can be measured with high temporal resolution by detection of respiratory-dependent oscillations of the paO2 (ΔpaO2). A previous study showed that end-expiratory collapse can be prevented by an increased respiratory rate in saline-lavaged rabbits. The current study compares the effects of increased positive end-expiratory pressure (PEEP) versus an individually titrated respiratory rate (RRind) on intra-tidal amplitude of Δ paO2 and on average paO2 in saline-lavaged pigs. Methods Acute lung injury was induced by bronchoalveolar lavag…

A note on the calibration of the tourists mobility in Sicily and Sardinia

2011

Chloroplast signal length requirement reflects the outer membrane and TOC complex dimension

2015

Background and Purpose: The evolution of an efficient preprotein targeting and translocation system was a central prerequisite for the endosymbiotic integration of a -proteobacteria and cyanobacteria as cellular organelles. Today, it is widely accepted that during evolution most (pre-)proteins destined for these two organelles were equipped with an N-terminal targeting signal for localization. While multiple modes of evolution of these extensions are currently discussed, all evolved signals serve the same function – forming a signal for targeting to the correct organelle and translocation across both membranes. We aimed to generalize the current idea for the length requirement of the N-term…

Multi-label Classification Using Stacked Hierarchical Dirichlet Processes with Reduced Sampling Complexity

2018

Nonparametric topic models based on hierarchical Dirichlet processes (HDPs) allow for the number of topics to be automatically discovered from the data. The computational complexity of standard Gibbs sampling techniques for model training is linear in the number of topics. Recently, it was reduced to be linear in the number of topics per word using a technique called alias sampling combined with Metropolis Hastings (MH) sampling. We propose a different proposal distribution for the MH step based on the observation that distributions on the upper hierarchy level change slower than the document-specific distributions at the lower level. This reduces the sampling complexity, making it linear i…

Online Sparse Collapsed Hybrid Variational-Gibbs Algorithm for Hierarchical Dirichlet Process Topic Models

2017

Topic models for text analysis are most commonly trained using either Gibbs sampling or variational Bayes. Recently, hybrid variational-Gibbs algorithms have been found to combine the best of both worlds. Variational algorithms are fast to converge and more efficient for inference on new documents. Gibbs sampling enables sparse updates since each token is only associated with one topic instead of a distribution over all topics. Additionally, Gibbs sampling is unbiased. Although Gibbs sampling takes longer to converge, it is guaranteed to arrive at the true posterior after infinitely many iterations. By combining the two methods it is possible to reduce the bias of variational methods while …