Making a shallow network deep: Conversion of a boosting classifier into a decision tree by boolean optimisation

This paper presents a novel way to speed up the evaluation time of a boosting classifier. We make a shallow (flat) network deep (hierarchical) by growing a tree from decision regions of a given boosting classifier. The tree provides many short paths for speeding up while preserving the reasonably smooth decision regions of the boosting classifier for good generalisation. For converting a boosting classifier into a decision tree, we formulate a Boolean optimization problem, which has been previously studied for circuit design but limited to a small number of binary variables. In this work, a novel optimisation method is proposed for, firstly, several tens of variables i.e. weak-learners of a boosting classifier, and then any larger number of weak-learners by using a two-stage cascade. Experiments on the synthetic and face image data sets show that the obtained tree achieves a significant speed up both over a standard boosting classifier and the Fast-exit-a previously described method for speeding-up boosting classification, at the same accuracy. The proposed method as a general meta-algorithm is also useful for a boosting cascade, where it speeds up individual stage classifiers by different gains. The proposed method is further demonstrated for fast-moving object tracking and segmentation problems. © 2011 Springer Science+Business Media, LLC.

HTGR fuel element depletion benchmark: Stage three results

Recently, a new numerical benchmark exercise for High Temperature Gas Cooled Reactor (HTGR) fuel depletion was defined. The purpose of this benchmark is to provide a comparison basis for different codes and methods applied to the burnup analysis of HTGRs. The benchmark specifications include three different models: (1) an infinite lattice of tristructural isotropic (TRISO) fuel particles, (2) an infinite lattice of fuel pebbles, and (3) a prismatic fuel including fuel and coolant channels. In this paper, we present the results of the third stage of the benchmark obtained with MCNP based depletion code BGCore and deterministic lattice code HELIOS 1.9. The depletion calculations were performed for three-dimensional model of prismatic fuel with explicitly described TRISO particles as well as for two-dimensional model, in which double heterogeneity of the TRISO particles was eliminated using reactivity equivalent physical transformation (RPT). Generally, good agreement in the results of the calculations obtained using different methods and codes was observed.

HTGR fuel element depletion benchmark: Stage one results

In this paper, we reported the results of the first stage of HTGR fuel element depletion benchmark obtained with BGCore and HELIOS depletion codes. The results of the k-inf are generally in good agreement. However, significant deviation in concentrations of several nuclides between MCNP based and HELIOS codes was observed.

Evolution of InAs branches in InAsGaAs nanowire heterostructures

Branched nanowire heterostructures of InAsGaAs were observed during Au-assisted growth of InAs on GaAs nanowires. The evolution of these branches has been determined through detailed electron microscopy characterization with the following sequence: (1) in the initial stage of InAs growth, the Au droplet is observed to slide down the side of the GaAs nanowire, (2) the downward movement of Au nanoparticle later terminates when the nanoparticle encounters InAs growing radially on the GaAs nanowire sidewalls, and (3) with further supply of In and As vapor reactants, the Au nanoparticles assist the formation of InAs branches with a well-defined orientation relationship with GaAsInAs core/shell stems. We anticipate that these observations advance the understanding of the kink formation in axial nanowire heterostructures. © 2007 American Institute of Physics.

Stakeholder engagement in early stage product-service system development for healthcare informatics

This paper presents the findings from four case studies on stakeholder engagement in new health information and communication technology (ICT) product-service system (PSS) development. The degree of connectivity between the new health ICT PSS and its intended operating environment has emerged to be an important contextual factor that may impact the decision of stakeholder engagement in the early stage development process. Along with the proposition of a four-level framework to guide stakeholder identification for new PSS development, three stakeholder engagement propositions that are based on the degree of connectivity are developed. Analysis has shown that there can be two types of connectivity: data and process. Moreover, each connectivity type can be characterized by how much the new PSS is connected with its environment: independent if there is no linkage, linked if it interfaces with, or incorporated if it is embedded into. Furthermore, depending upon whether and to what extent the PSS has data and process connectivity with its intended operating environment, the stakeholder engagement needs in early stage development vary. The propositions presented in this paper provide important directions for future work exploring PSS characterization and stakeholder engagement decision in early stage new PSS development in the healthcare industry. © 2013 PICMET.

Cecum lymph node dendritic cells harbor slow-growing bacteria phenotypically tolerant to antibiotic treatment.

In vivo, antibiotics are often much less efficient than ex vivo and relapses can occur. The reasons for poor in vivo activity are still not completely understood. We have studied the fluoroquinolone antibiotic ciprofloxacin in an animal model for complicated Salmonellosis. High-dose ciprofloxacin treatment efficiently reduced pathogen loads in feces and most organs. However, the cecum draining lymph node (cLN), the gut tissue, and the spleen retained surviving bacteria. In cLN, approximately 10%-20% of the bacteria remained viable. These phenotypically tolerant bacteria lodged mostly within CD103⁺CX₃CR1⁻CD11c⁺ dendritic cells, remained genetically susceptible to ciprofloxacin, were sufficient to reinitiate infection after the end of the therapy, and displayed an extremely slow growth rate, as shown by mathematical analysis of infections with mixed inocula and segregative plasmid experiments. The slow growth was sufficient to explain recalcitrance to antibiotics treatment. Therefore, slow-growing antibiotic-tolerant bacteria lodged within dendritic cells can explain poor in vivo antibiotic activity and relapse. Administration of LPS or CpG, known elicitors of innate immune defense, reduced the loads of tolerant bacteria. Thus, manipulating innate immunity may augment the in vivo activity of antibiotics.

Production planning of multi-stage multi-option seru production systems with sustainable measures

With the concerns over climate change and the escalation in worldwide population, sustainable development attracts more and more attention of academia, policy makers, and businesses in countries. Sustainable manufacturing is an inextricable measure to achieve sustainable development since manufacturing is one of the main energy consumers and greenhouse gas contributors. In the previous researches on production planning of manufacturing systems, environmental factor was rarely considered. This paper investigates the production planning problem under the performance measures of economy and environment with respect to seru production systems, a new manufacturing system praised as Double E (ecology and economy) in Japanese manufacturing industries. We propose a mathematical model with two objectives minimizing carbon dioxide emission and makespan for processing all product types by a seru production system. To solve this mathematical model, we develop an algorithm based on the non-dominated sorting genetic algorithm II. The computation results and analysis of three numeral examples confirm the effectiveness of our proposed algorithm. © 2014 Elsevier Ltd. All rights reserved.

Modelling of settlement induced building damage

This thesis focuses on the modelling of settlement induced damage to masonry buildings. In densely populated areas, the need for new space is nowadays producing a rapid increment of underground excavations. Due to the construction of new metro lines, tunnelling activity in urban areas is growing. One of the consequences is a greater attention to the risk of damage on existing structures. Thus, the assessment of potential damage of surface buildings has become an essential stage in the excavation projects in urban areas (Chapter 1). The current damage risk assessment procedure is based on strong simplifications, which not always lead to conservative results. Object of this thesis is the development of an improved damage classification system, which takes into account the parameters influencing the structural response to settlement, like the non-linear behaviour of masonry and the soil-structure interaction. The methodology used in this research is based on experimental and numerical modelling. The design and execution of an experimental benchmark test representative of the problem allows to identify the principal factors and mechanisms involved. The numerical simulations enable to generalize the results to a broader range of physical scenarios. The methodological choice is based on a critical review of the currently available procedures for the assessment of settlement-induced building damage (Chapter 2). A new experimental test on a 1/10th masonry façade with a rubber base interface is specifically designed to investigate the effect of soil-structure interaction on the tunnelling-induced damage (Chapter 3). The experimental results are used to validate a 2D semi-coupled finite element model for the simulation of the structural response (Chapter 4). The numerical approach, which includes a continuum cracking model for the masonry and a non-linear interface to simulate the soil-structure interaction, is then used to perform a sensitivity study on the effect of openings, material properties, initial damage, initial conditions, normal and shear behaviour of the base interface and applied settlement profile (Chapter 5). The results assess quantitatively the major role played by the normal stiffness of the soil-structure interaction and by the material parameters defining the quasi-brittle masonry behaviour. The limitation of the 2D modelling approach in simulating the progressive 3D displacement field induced by the excavation and the consequent torsional response of the building are overcome by the development of a 3D coupled model of building, foundation, soil and tunnel (Chapter 6). Following the same method applied to the 2D semi-coupled approach, the 3D model is validated through comparison with the monitoring data of a literature case study. The model is then used to carry out a series of parametric analyses on geometrical factors: the aspect ratio of horizontal building dimensions with respect to the tunnel axis direction, the presence of adjacent structures and the position and alignment of the building with respect to the excavation (Chapter 7). The results show the governing effect of the 3D building response, proving the relevance of 3D modelling. Finally, the results from the 2D and 3D parametric analyses are used to set the framework of an overall damage model which correlates the analysed structural features with the risk for the building of being damaged by a certain settlement (Chapter 8). This research therefore provides an increased experimental and numerical understanding of the building response to excavation-induced settlements, and sets the basis for an operational tool for the risk assessment of structural damage (Chapter 9).