The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models

We propose a probabilistic model to infer supervised latent variables in the Hamming space from observed data. Our model allows simultaneous inference of the number of binary latent variables, and their values. The latent variables preserve neighbourhood structure of the data in a sense that objects in the same semantic concept have similar latent values, and objects in different concepts have dissimilar latent values. We formulate the supervised infinite latent variable problem based on an intuitive principle of pulling objects together if they are of the same type, and pushing them apart if they are not. We then combine this principle with a flexible Indian Buffet Process prior on the latent variables. We show that the inferred supervised latent variables can be directly used to perform a nearest neighbour search for the purpose of retrieval. We introduce a new application of dynamically extending hash codes, and show how to effectively couple the structure of the hash codes with continuously growing structure of the neighbourhood preserving infinite latent feature space.

Exploring an effective model of new product development in medical devices: A knowledge cluster approach

This study proposes a new product development (NPD) model that aims to improve the effectiveness of innovative NPD in the medical devices. By adopting open innovation theory and applying an in-depth investigation methodology, this paper proposes a knowledge cluster that improves the integration of interdisciplinary human resources and enhances the acquirement of innovative technologies. A knowledge cluster approach helps gather, organise, synthesise, and accumulate knowledge in order to become the impetus for innovation. Although enterprises are no longer the principals of research and development, they should still be capable of integrating professional physicians, external groups, and individuals through the knowledge cluster platform. However, in order to support an effective NPD model, enterprises should provide adequate incentives and trust to external individuals or groups willing to contribute their expertise and knowledge to this knowledge cluster platform. Copyright © 2013 Inderscience Enterprises Ltd.

A simplified mathematical approach for modelling stack ventilation in multi-compartment buildings

A simple mathematical model of stack ventilation flows in multi-compartment buildings is developed with a view to providing an intuitive understanding of the physical processes governing the movement of air and heat through naturally ventilated buildings. Rules of thumb for preliminary design can be ascertained from a qualitative examination of the governing equations of flow, which elucidate the relationships between 'core' variables - flow rates, air temperatures, heat inputs and building geometry. The model is applied to an example three-storey office building with an inlet plenum and atrium. An examination of the governing equations of flow is used to predict the behaviour of steady flows and to provide a number of preliminary design suggestions. It is shown that control of ventilation flows must be shared between all ventilation openings within the building in order to minimise the disparity in flow rates between storeys, and ensure adequate fresh air supply rates for all occupants. © 2013 Elsevier Ltd.

Digital elevation models and GIS for watershed modelling and flood prediction-A case study of Accra Ghana

Geographical Information Systems (GIS) and Digital Elevation Models (DEM) can be used to perform many geospatial and hydrological modelling including drainage and watershed delineation, flood prediction and physical development studies of urban and rural settlements. This paper explores the use of contour data and planimetric features extracted from topographic maps to derive digital elevation models (DEMs) for watershed delineation and flood impact analysis (for emergency preparedness) of part of Accra, Ghana in a GIS environment. In the study two categories of DEMs were developed with 5 m contour and planimetric topographic data; bare earth DEM and built environment DEM. These derived DEMs were used as terrain inputs for performing spatial analysis and obtaining derivative products. The generated DEMs were used to delineate drainage patterns and watershed of the study area using ArcGIS desktop and its ArcHydro extension tool from Environmental Systems Research Institute (ESRI). A vector-based approach was used to derive inundation areas at various flood levels. The DEM of built-up areas was used as inputs for determining properties which will be inundated in a flood event and subsequently generating flood inundation maps. The resulting inundation maps show that about 80% areas which have perennially experienced extensive flooding in the city falls within the predicted flood extent. This approach can therefore provide a simplified means of predicting the extent of inundation during flood events for emergency action especially in less developed economies where sophisticated technologies and expertise are hard to come by. © 2009 Springer Netherlands.

Unified form language: A domain-specific language for weak formulations of partial differential equations

We present the Unified Form Language (UFL), which is a domain-specific language for representing weak formulations of partial differential equations with a view to numerical approximation. Features of UFL include support for variational forms and functionals, automatic differentiation of forms and expressions, arbitrary function space hierarchies formultifield problems, general differential operators and flexible tensor algebra. With these features, UFL has been used to effortlessly express finite element methods for complex systems of partial differential equations in near-mathematical notation, resulting in compact, intuitive and readable programs. We present in this work the language and its construction. An implementation of UFL is freely available as an open-source software library. The library generates abstract syntax tree representations of variational problems, which are used by other software libraries to generate concrete low-level implementations. Some application examples are presented and libraries that support UFL are highlighted. © 2014 ACM.

Digital Elevation Models and GIS for watershed modelling and flood prediction - A case study of Accra Ghana

Geographical Information Systems (GIS) and Digital Elevation Models (DEM) can be used to perform many geospatial and hydrological modelling including drainage and watershed delineation, flood prediction and physical development studies of urban and rural settlements. This paper explores the use of contour data and planimetric features extracted from topographic maps to derive digital elevation models (DEMs) for watershed delineation and flood impact analysis (for emergency preparedness) of part of Accra, Ghana in a GIS environment. In the study two categories of DEMs were developed with 5 m contour and planimetric topographic data; bare earth DEM and built environment DEM. These derived DEMs were used as terrain inputs for performing spatial analysis and obtaining derivative products. The generated DEMs were used to delineate drainage patterns and watershed of the study area using ArcGIS desktop and its ArcHydro extension tool from Environmental Systems Research Institute (ESRI). A vector-based approach was used to derive inundation areas at various flood levels. The DEM of built-up areas was used as inputs for determining properties which will be inundated in a flood event and subsequently generating flood inundation maps. The resulting inundation maps show that about 80% areas which have perennially experienced extensive flooding in the city falls within the predicted flood extent. This approach can therefore provide a simplified means of predicting the extent of inundation during flood events for emergency action especially in less developed economies where sophisticated technologies and expertise are hard to come by. © Springer Science + Business Media B.V. 2009.

Magnetic quantum oscillations for the surface states of topological insulator Bi2Se3

We study quantum oscillations of the magnetization in Bi2Se3 (111) surface system in the presence of a perpendicular magnetic field. The combined spin-chiral Dirac cone and Landau quantization produce profound effects on the magnetization properties that are fundamentally different from those in the conventional semiconductor two-dimensional electron gas. In particular, we show that the oscillating center in the magnetization chooses to pick up positive or negative values depending on whether the zero-mode Landau level is occupied or empty. An intuitive analysis of these features is given and the subsequent effects on the magnetic susceptibility and Hall conductance are also discussed.

The fabrication and properties of InAs/GaAs columnal islands

A columnal islands system, which was composed of three layers of self-assembled InAs/GaAs quantum dots (QDs), has been fabricated by solid-source molecular beam epitaxy (MBE) through S-K mode on a (100) semi-insulating GaAs substrate. The effects of the thickness of GaAs space layer, the growth interruption time and the amount of InAs deposition on the emission wavelength of columnal islands were presented. The image of atomic force microscopy (AFM) indicated the columnal islands with high uniformity in size and shape. At room temperature, the emission wavelength of columnal islands with different effective heights was achieved 1.32 and 1.4 mum; however, the emission wavelength of single-layer QDs with normal height was just 1. l mum. It provides a useful and intuitive approach to artificially control the emission wavelength of a QD material system.

Processing network models of energy/environment systems

Processing networks are a variant of the standard linear programming network model which are especially useful for optimizing industrial energy/environment systems. Modelling advantages include an intuitive diagrammatic representation and the ability to incorporate all forms of energy and pollutants in a single integrated linear network model. Added advantages include increased speed of solution and algorithms supporting formulation. The paper explores their use in modelling the energy and pollution control systems in large industrial plants. The pollution control options in an ethylene production plant are analyzed as an example. PROFLOW, a computer tool for the formulation, analysis, and solution of processing network models, is introduced.

Study on tapered crossed subwavelength gratings by Fourier modal method

Fourier modal method incorporating staircase approximation is used to study tapered crossed subwavelength gratings in this paper. Three intuitive formulations of eigenvalue functions originating from the prototype are presented, and their convergences are compared through numerical calculation. One of them is found to be suitable in modeling the diffraction efficiency of the circular tapered crossed subwavelength gratings without high absorption, and staircase approximation is further proven valid for non-highly-absorption tapered gratings. This approach is used to simulate the "moth-eye" antireflection surface on silicon, and the numerical result agrees well with the experimental one.

BPEL流程监视的可视化实现

When a BPEL process is executed,it is necessary to dynamically monitor the process.BPEL is a executable language,which is not suitable for visual monitoring.On the other hand,BPMN is designed to visually describe business process and is more intuitive for monitoring.To visually monitor a BPEL process, transformation from BPEL to BPMN is necessary.However,current study of transformation from BPEL to BPMN does not support the transformation of"link"activity.Besides,no work has been done to add supplementary information into BPMN during transformation.In this paper,we transform nested BPEL process into a flat BPMN process graph without hierarchy through applying a flattening strategy.Especially, we analyze various scenarios of the transformation of link activity,and provide a method to deal with it. Besides,we analyze the mapping between BPEL activities and BPMN graph,through which we found out that some supplementary information cannot automatically obtained from BPEL process.These supplementary information need to be added during transformation.At the end of this paper,we present the structure of our monitoring tool which is based on our transformation algorithm.

Asymmetric heat conduction in nonlinear lattices

In this Letter, we conduct an extensive study of the two-segment Frenkel-Kontorova model. We show that the rectification effect of the heat flux reported in recent literature is possible only in the weak interfacial coupling limit. The rectification effect will be reversed when the properties of the interface and the system size change. These two types of asymmetric heat conduction are governed by different mechanisms though both are induced by nonlinearity. An intuitive physical picture is proposed to interpret the reversal of the rectification effect. Since asymmetric heat conduction depends critically on the properties of the interface and the system size, it is probably not an easy task to fabricate a thermal rectifier or thermal diode in practice.

Building capacity for integrated coastal management in developing countries

The need for building human and institutional capacity has been identified in Agenda 21 of the UNCED conference as well as by a number of international environmental institutions as essential for integrated coastal management (ICM) and sustainable development in developing coastal states. There is a growing need for coastal management practitioners and organizations with expertise in planning and implementation for ICM. The application of strategies for institutional development and building human capacity in coastal management and other fields shows that short-term intensive training efforts and long-term institutional strengthening programs are appropriate to address the issues and needs of ICM. An overview of the experience of the URI/USAID International Coastal Resources Management Program in Sri Lanka, Thailand and Ecuador presents lessons learned for strengthening ICM efforts in developing countries.

Introduction to Molecular Analysis of Ectomycorrhizal Communities

A number of methods are available for those researchers considering the addition of molecular analyses of ectomycorrhizal (EcM) fungi to their research projects and weighing the various approaches they might take. Analyzing natural EcM fungal communities has traditionally been a highly skilled, time-consuming process relying heavily on exacting morphological characterization of EcM root tips. Increasingly powerful molecular methods for analyzing EcM communities make this area of research available to a much wider range of researchers. Ecologists can gain from the body of work characterizing EcM while avoiding the requirement for exceptional expertise by carefully combining elements of traditional methods with the more recent molecular approaches. A cursory morphological analysis can yield a traditional quantification of EcM fungi based on tip numbers, a unit with functional and historical significance. Ectomycorrhizal root DNA extracts may then be analyzed with molecular methods widely used for characterizing microbiota. These range from methods applicable only to the simple mixes resulting from careful morphotyping, to community-oriented methods that identify many types in mixed samples as well as provide an estimate of their relative abundances. Extramatrical hyphae in bulk soil can also be more effectively studied, extending characterization of EcM fungal communities beyond the rhizoplane. The trend toward techniques permitting larger sample sets without prohibitive labor and time requirements will also permit us to more frequently address the issues of spatial and temporal variability and better characterize the roles of EcM fungi at multiple scales.

Decision tree classification of land cover from remotely sensed data

Decision tree classification algorithms have significant potential for land cover mapping problems and have not been tested in detail by the remote sensing community relative to more conventional pattern recognition techniques such as maximum likelihood classification. In this paper, we present several types of decision tree classification algorithms arid evaluate them on three different remote sensing data sets. The decision tree classification algorithms tested include an univariate decision tree, a multivariate decision tree, and a hybrid decision tree capable of including several different types of classification algorithms within a single decision tree structure. Classification accuracies produced by each of these decision tree algorithms are compared with both maximum likelihood and linear discriminant function classifiers. Results from this analysis show that the decision tree algorithms consistently outperform the maximum likelihood and linear discriminant function classifiers in regard to classf — cation accuracy. In particular, the hybrid tree consistently produced the highest classification accuracies for the data sets tested. More generally, the results from this work show that decision trees have several advantages for remote sensing applications by virtue of their relatively simple, explicit, and intuitive classification structure. Further, decision tree algorithms are strictly nonparametric and, therefore, make no assumptions regarding the distribution of input data, and are flexible and robust with respect to nonlinear and noisy relations among input features and class labels.