Multiple Data Model Research Articles

Heterogeneous programming with Single Operation Multiple Data

Heterogeneity is omnipresent in today's commodity computational systems, which comprise at least one Central Processing Unit (CPU) and one Graphics Processing Unit (GPU). Nonetheless, all this computing power is not being harnessed in mainstream computing, as the programming of these systems entails many details of the underlying architecture and execution models. Current research on parallel programming is addressing these issues but, still, the system's heterogeneity is exposed at language level. This paper proposes a uniform framework, grounded on the Single Operation Multiple Data model, for the programming of such heterogeneous systems. We designed a simple extension of the Java programming language that embodies the model, and developed a compiler that generates code for both multi-core CPUs and GPUs. A performance evaluation attests that, despite being based on a simple programming model, the approach is able to deliver performance gains on par with hand-tuned data-parallel multi-threaded Java applications.

Geographic Video 3d Data Model And Retrieval

Abstract. Geographic video includes both spatial and temporal geographic features acquired through ground-based or non-ground-based cameras. With the popularity of video capture devices such as smartphones, the volume of user-generated geographic video clips has grown significantly and the trend of this growth is quickly accelerating. Such a massive and increasing volume poses a major challenge to efficient video management and query. Most of the today’s video management and query techniques are based on signal level content extraction. They are not able to fully utilize the geographic information of the videos. This paper aimed to introduce a geographic video 3D data model based on spatial information. The main idea of the model is to utilize the location, trajectory and azimuth information acquired by sensors such as GPS receivers and 3D electronic compasses in conjunction with video contents. The raw spatial information is synthesized to point, line, polygon and solid according to the camcorder parameters such as focal length and angle of view. With the video segment and video frame, we defined the three categories geometry object using the geometry model of OGC Simple Features Specification for SQL. We can query video through computing the spatial relation between query objects and three categories geometry object such as VFLocation, VSTrajectory, VSFOView and VFFovCone etc. We designed the query methods using the structured query language (SQL) in detail. The experiment indicate that the model is a multiple objective, integration, loosely coupled, flexible and extensible data model for the management of geographic stereo video.

Identifying gene-environment and gene-gene interactions using a progressive penalization approach.

In genomic studies, identifying important gene-environment and gene-gene interactions is a challenging problem. In this study, we adopt the statistical modeling approach, where interactions are represented by product terms in regression models. For the identification of important interactions, we adopt penalization, which has been used in many genomic studies. Straightforward application of penalization does not respect the "main effect, interaction" hierarchical structure. A few recently proposed methods respect this structure by applying constrained penalization. However, they demand very complicated computational algorithms and can only accommodate a small number of genomic measurements. We propose a computationally fast penalization method that can identify important gene-environment and gene-gene interactions and respect a strong hierarchical structure. The method takes a stagewise approach and progressively expands its optimization domain to account for possible hierarchical interactions. It is applicable to multiple data types and models. A coordinate descent method is utilized to produce the entire regularized solution path. Simulation study demonstrates the superior performance of the proposed method. We analyze a lung cancer prognosis study with gene expression measurements and identify important gene-environment interactions.

Evaluating Gene Set Enrichment Analysis via a Hybrid Data Model

Gene set enrichment analysis (GSA) methods have been widely adopted by biological labs to analyze data and generate hypotheses for validation. Most of the existing comparison studies focus on whether the existing GSA methods can produce accurate P-values; however, practitioners are often more concerned with the correct gene-set ranking generated by the methods. The ranking performance is closely related to two critical goals associated with GSA methods: the ability to reveal biological themes and ensuring reproducibility, especially for small-sample studies. We have conducted a comprehensive simulation study focusing on the ranking performance of seven representative GSA methods. We overcome the limitation on the availability of real data sets by creating hybrid data models from existing large data sets. To build the data model, we pick a master gene from the data set to form the ground truth and artificially generate the phenotype labels. Multiple hybrid data models can be constructed from one data set and multiple data sets of smaller sizes can be generated by resampling the original data set. This approach enables us to generate a large batch of data sets to check the ranking performance of GSA methods. Our simulation study reveals that for the proposed data model, the Q2 type GSA methods have in general better performance than other GSA methods and the global test has the most robust results. The properties of a data set play a critical role in the performance. For the data sets with highly connected genes, all GSA methods suffer significantly in performance.

On spectral line profiles in Type Ia supernova spectra

We present a detailed analysis of spectral line profiles in Type Ia supernova (SN Ia) spectra. We focus on the feature at ~3500 - 4000 A, which is commonly thought to be caused by blueshifted absorption of Ca H&K. Unlike some other spectral features in SN Ia spectra, this feature often has two overlapping (blue and red) components. It is accepted that the red component comes from photospheric calcium. However, it has been proposed that the blue component is caused by either high-velocity calcium (from either abundance or density enhancements above the photosphere of the SN) or Si II 3858. By looking at multiple data sets and model spectra, we conclude that the blue component of the Ca H&K feature is caused by Si II 3858 for most SNe Ia. The strength of the Si II 3858 feature varies strongly with the light-curve shape of a SN. As a result, the velocity measured from a single-Gaussian fit to the full line profile correlates with light-curve shape. The velocity of the Ca H&K component of the profile does not correlate with light-curve shape, contrary to previous claims. We detail the pitfalls of assuming that the blue component of the Ca H&K feature is caused by calcium, with implications for our understanding of SN Ia progenitors, explosions, and cosmology.

Constraints on Carbon Monoxide Emissions Based on Tall Tower Measurements in the U.S. Upper Midwest

We interpret a full year of high-frequency CO measurements from a tall tower in the U.S. Upper Midwest with a time-reversed Lagrangian Particle Dispersion Model (STILT LPDM) and an Eulerian chemical transport model (GEOS-Chem CTM) to develop top-down constraints on U.S. CO sources in 2009. Our best estimate is that anthropogenic CO emissions in the U.S. Upper Midwest in 2009 were 2.9 Tg, 61% lower (a posteriori scale factor of 0.39) than our a priori prediction based on the U.S. EPA's National Emission Inventory for 2005 (NEI 2005). If the same bias applies across the contiguous U.S., the inferred CO emissions are 26 Tg/y, compared to the a priori estimate of 66 Tg/y. This discrepancy is significantly greater than would be expected based solely on emission decreases between 2005 and 2009 (EPA estimate: 23% decrease). Model transport error is an important source of uncertainty in the analysis, and we employ an ensemble of sensitivity runs using multiple meteorological data sets and model configurations to assess its impact on our results. A posteriori scale factors for the U.S. anthropogenic CO source from these sensitivity runs range from 0.22 to 0.64, corresponding to emissions of 1.6-4.8 Tg/y for the U.S. Upper Midwest and 15-42 Tg/y for the contiguous U.S. The data have limited sensitivity for constraining biomass + biofuel burning emissions and photochemical CO production from precursor organic compounds. Our finding of a NEI 2005 overestimate of CO emissions is consistent with recent assessments for individual cities and with earlier analyses based on the NEI 1999, implying the need for a better mechanism for refining such bottom-up emission estimates in response to top-down constraints.

Solving finite-difference equations for diffractive optics problems using graphics processing units

This article presents a vector algorithm of the solution of the Helmholtz equation by beam propagation method (BPM), based on rep- resentation of calculations in the single instruction, multiple data model. Use of this algorithm on the graphic NVIDIA GeForce GTX 660Ti proces- sor on the compute unified device architecture technology results in 30- times acceleration of calculations in comparison with calculations on the Intel Core2 Duo CPU E8500. © 2013 Society of Photo-Optical Instrumentation

개별관리 대통령기록물의 연계관리를 위한 통합 메타데이터 설계 방안 연구

국내 대통령기록물의 연구 및 활용, 서비스를 위해서는 다양한 대통령기록물의 유형과 포맷에 대한 통합 메타데이터 설계 및 운영이 필요하며, 상이한 메타데이터 구조를 가지고 있는 대통령기록관과 민간 대통령도서관 기념관의 메타데이터 표준화가 요구된다. 이에 이 연구에서는 국내 대통령기록물의 메타데이터 통합 운영을 위하여 통합 메타데이터 설계 원칙과 메타데이터 속성 및 관계를 제안하였다. 메타데이터 설계 원칙은 '대통령기록물 간의 관계 설정 및 설계', '다중 개체 모형을 적용한 대통령기록물 각 개체별 설계', '다양한 유형의 대통령기록물을 기술할 수 있도록 설계', '소장기관의 업무 전주기를 반영한 메타데이터 설계', '하이브리드형 장기보존 메타데이터 설계'이다. 메타데이터 요소는 모든 유형의 대통령기록물들이 공통적으로 지니고 있는 공통속성 요소, 특정 대통령기록물만이 갖는 고유속성 요소, 대통령기록물 생산에 관련된 타 기록물간의 연관 및 참조정보 요소이다. Metadata standardization of resources, having a heterogeneous metadata structure for each presidential archive and presidential library and museum is preferentially required for utilizing and sharing presidential records. An integrated operation model of metadata to manage various types of presidential records is then needed. The purpose of this study is to create a design principle of integrated metadata, and to suggest relationships and attributes of metadata, needed for developing integrated metadata operation system on presidential records. The design principle includes "creation of relationship among presidential records", "design of each entity, applicable multiple entity data model", "design to describe various types of presidential records", "design to reflect lifelong management on records of holding institutes", and "designing hybrid metadata for long term preservation". Metadata element set consists of elements for common attributes with all types of presidential records for a unique attribute for a specific presidential record and for reference information among different records related to the production of presidential records.

Application of neuro-fuzzy modeling technique for operational problem solving in a CO2 capture process system

A good understanding about relationships among key process parameters is important in optimizing operation and enhancing efficiency of the CO2 capture process system. This understanding would enable the operator to better analyze process conditions and become aware of ongoing trends or events so that timely and effective control actions can be taken for adjusting the relevant process parameters and efficiency of plant operations can be enhanced. The studies that focused on exploring the key parameters of the amine-based post-combustion CO2 capture process system implemented at the International Test Center of CO2 Capture (ITC) have revealed that among multiple data modeling techniques adopted, the adaptive-network-based fuzzy inference system (ANFIS) modeling approach generated satisfactory models for adequately describing the process system. This paper presents development and application of the four ANFIS models for solving four real-life problems encountered in operation of the CO2 capture process system. The testing results of the four developed models show that they can be applied for satisfactory solution of these problems. Some lessons and observations made during the application process are also discussed.

Parallelization of 2-D IADE-DY Scheme on Geranium Cadcam Cluster for Heat Equation

A parallel implementation of the Iterative Alternating Direction Explicit method by D’Yakonov (IADE-DY) for solving 2-D heat equation on a distributed system of Geranium Cadcam cluster (GCC) using the Message Passing Interface (MPI) is presented. The implementation of the scheduling of n tri-diagonal system of equations with the above method was used to show improvement on speedup, effectiveness, and efficiency. The Master/Worker paradigm and Single Program Multiple Data (SPMD) model is employed to manage the whole computation based on the use of domain decomposition. The completion of the execution can need task recovery and favorable configuration. The above mentioned details consist of a main report about the numerical validation of the parallelization through simulation to demonstrate the proposed method effectiveness on the cluster system. It was found that the rate of convergence decreases as the number of processors increases. The result of this paper suggests that the 2-D IADE-DY scheme is a good approach to solving problems, particularly when it is simulation with more processors.

Models as web services using the Open Geospatial Consortium (OGC) Web Processing Service (WPS) standard

Environmental modeling often requires the use of multiple data sources, models, and analysis routines coupled into a workflow to answer a research question. Coupling these computational resources can be accomplished using various tools, each requiring the developer to follow a specific protocol to ensure that components are linkable. Despite these coupling tools, it is not always straight forward to create a modeling workflow due to platform dependencies, computer architecture requirements, and programming language incompatibilities. A service-oriented approach that enables individual models to operate and interact with others using web services is one method for overcoming these challenges. This work advances the idea of service-oriented modeling by presenting a design for a modeling service that builds from the Open Geospatial Consortium (OGC) Web Processing Service (WPS) protocol. We demonstrate how the WPS protocol can be used to create modeling services, and then demonstrate how these modeling services can be brought into workflow environments using generic client-side code. We implemented this approach within the HydroModeler environment, a model coupling tool built on the Open Modeling Interface standard (version 1.4), and show how a hydrology model can be hosted as a WPS web service and used within a client-side workflow. The primary advantage of this approach is that the server-side software follows an established standard that can be leveraged and reused within multiple workflow environments and decision support systems.

Reducing thread divergence in a GPU‐accelerated branch‐and‐bound algorithm

SUMMARYIn this paper, we address the design and implementation of graphical processing unit (GPU)‐accelerated branch‐and‐bound algorithms (B&B) for solving flow‐shop scheduling optimization problems (FSP). Such applications are CPU‐time consuming and highly irregular. On the other hand, GPUs are massively multithreaded accelerators using the single instruction multiple data model at execution. A major issue that arises when executing on GPU, a B&B applied to FSP is thread or branch divergence. Such divergence is caused by the lower bound function of FSP that contains many irregular loops and conditional instructions. Our challenge is therefore to revisit the design and implementation of B&B applied to FSP dealing with thread divergence. Extensive experiments of the proposed approach have been carried out on well‐known FSP benchmarks using an Nvidia Tesla (C2050 GPU card (http://www.nvidia.com/docs/IO/43395/NV_DS_Tesla_C2050_C2070_jul10_lores.pdf)). Compared with a CPU‐based execution, accelerations up to × 77.46 are achieved for large problem instances. Copyright © 2012 John Wiley & Sons, Ltd.

A comparison of data sources and models to project HRH needs in India: lessons from the universal health coverage planning process

Description of the problem The path to universal health care in India requires concurrently addressing several human resource issues and is thus an opportunity to bring about much needed reforms in the health workforce. A key component of these reforms is systemic knowledge generation around what Human Resources for Health (HRH) capacity currently exists in the country and what future needs may be projected to achieve universal health coverage. A lack of uniform sources of data has resulted in the use of diverse sources, which presents its own challenges in the planning process. Methods Based on a qualitative comparative framework, we examine the implications of multiple data sources and models to estimate HR needs for India over the next 30 years. One set of comparisons projects estimates from Census and other sample survey data to adjusted figures from professional health councils to actually determine what the population coverage of various HRH cadres is (doctors, nurses and ANMS). Here we compare the data sources, assumptions and methodologies of HRH estimation approaches. Another set of comparisons is of models that propose to achieve international norms of doctor-population coverage and nurse/midwife to doctor ratios, as compared to models that operate on more general health worker densities incorporating the role and contribution of community health workers and mid-level health practitioners. Here we compare theoretical bases, historical contexts and international evidence supporting that justify various model and assess their relevance to the Indian case. Main findings The use of different data sources results in estimation exercises with varying baselines and ultimately projects widely divergent HR numbers and requirements. Major reliability and validity concerns may be raised with regard to typical sources of HRH data in India (the Census, the Medical Council of India, Indian Nursing Council, Sample Registration System). This is also related to a lack of inter-operability across these sources in terms of definitions and frequency in generation of health information. Profound epistemological questions regarding India’s vision for health emerge in comparing doctor-driven models to community health worker-driven models or models that seek a middle path of mid-level practitioners. India’s successes with producing doctors has to be reconciled with the lack of a supportive eco-system for practice, its world renowned record of community health worker programmes has to be reconciled with the scale of coverage and resultant quality and training implications; finally, operationalizing mid-level practitioners across the country will require overcoming legal and normative barriers that privilege medical dominance and circumscribe what a legitimacy of HRH cadres. Discussion including recommendations HR Projection exercises and sensitivity analyses raise key questions around the level of clinical competency across cadres, the functional implications of proposed new cadres, the paucity of “live” data, and epistemic considerations related to India’s vision for how to (human) resource universal health coverage. Recommendations include the use of human resources information management systems as part of management reform.There is an urgent need for systematic data generation related to HRH at appropriate levels in the country, supplemented by routinized cadre review. The country also needs to evolve uniform standards for regulation and accreditation, with appropriate (legal) attention to the scope and integration of practice across cadres at various levels of care. These structural changes require a careful balance between central guidance and strategic planning at the state level – in striking that balance, knowledge generation and management around HRH could improve in the country and by extension, enhance HRH planning. Conflict of Interest Statement The author was a member of the technical secretariat of the High Level Expert Group on Universal Health Coverage.

XFormsDB

Most Web applications are based on a conventional three-tier architecture, in which the presentation, application logic, and data management are developed and maintained in separate tiers. The main disadvantage of this architecture is that it requires expertise in multiple programming languages, programming paradigms, and data models used in each tier. A single expert rarely masters all the technologies and concepts involved. In this paper, we introduce a tier-expanding architectural approach that unifies the client-side (presentation tier) and server-side (logic and data tiers) programming under a single model. We base our approach on a W3C-standardized client-side markup language, XForms, and its server-side extension proposed in this paper. We derive the extension requirements from the literature and use cases, and demonstrate their functionality on the example of a blog Web application. We also show how the extension can be implemented as part of a comprehensive Web application framework called XFormsDB . The XFormsDB framework is an extensible Web application framework built upon declarative W3C standards. It has four major advantages: (1) one programming language, (2) one data model, (3) based on W3C-standardized declarative markup, and (4) extensibility in all tiers. Our conclusion is that expanding the presentation tier to cover both application logic and data management functionality makes both the development and maintenance of small- and medium-sized Web applications easier.

The Relationship between Governance and Sustainable Development

This paper presents a methodological approach to evaluating the relationship between governance and several variables commonly related to the concept of sustainable development and, also, related to financial indicators from various countries. We explore the theoretical framework linking the level of governance of the countries with their economic performance. Our sample incorporates data from developed and emergent countries, collected by the World Bank and Transparency International, in order to assess the significance of governance impact among countries with distinct degrees of development. Multiple regression analysis and panel data modeling were used to explore statistical relations amongst variables. Results show a positive relation between levels of governance and economic development, besides illustrating other significant issues.

Armadillo generation distributed system with geranium Cadcam cluster for solving 2D telegraphic problem

In this paper, the parallel implementation of the iterative alternating direction explicit method by D'Yakonov (IADE-DY) and the Mitchell and Fairweather double sweep method (DS-MF) compared with the alternative direction implicit (ADI) method for solving the 2D telegraphic problem on a distributed system of Armadillo cluster and geranium Cadcam cluster using the parallel virtual machine and message passing interface is presented. We implement the scheduling of n tridiagonal system of equations with the above methods to show improvement on speedup and efficiency with parallel strategies across the two platforms. The single program multiple data model was employed for the implementation. The IADE-DY, DS-MF and ADI are developed by the splitting of the implicit equation using the finite difference discretization on the 2D telegraphic problem. The implementation is discussed in relation to means of the performance parallel strategies and analysis. The model enhances overlap communication and computation to avoid unnecessary synchronization, hence, the method yields significant speedup by the use of the non-blocking communication. We present some analyses that are helpful for speedup and efficiency.

Parallel Implementation of 2-D Telegraphic Equation on MPI/PVM Cluster

In this paper, a parallel implementation of the Iterative Alternating Direction Explicit method by D’Yakonov (IADE-DY) to solve 2-D telegraphic problem on a distributed system using Message Passing Interface (MPI) and Parallel Virtue Machine (PVM) are presented. The parallelization of the program is implemented by a domain decomposition strategy. A Single Program Multiple Data (SPMD) model is employed for the implementation. The implementation is discussed in relation to means of the parallel performance strategies and analysis. The model enhances overlap communication and computation to avoid unnecessary synchronization, hence, the method yields significant speedup. The level of speedup observed from tables as the mesh increases are in the range of 5–10%. Improvement has been achieved by numbers of tables and figures in our experiment. We present some analyses that are helpful for speedup and efficiency. It is concluded that the efficiency is strongly dependent on the grid size, block numbers and the number of processors for both MPI and PVM. Different strategies to improve the computational efficiency are proposed.

A Case Study on Recordkeeping Metadata Standard Applying Multiple Entities

The multiple entity data model which contains metadata that associate two or more entities is applied recordkeeping metadata standard in recent years. This paper described and analyzed the recordkeeping metadata standard applying multiple entities such as ISO 23081, Australia recordkeeping metadata Standard, New Zealand recordkeeping metadata Standard, New South Wales recordkeeping metadata Standard, Queensland recordkeeping metadata Standard recordkeeping metadata Standard, South Australia recordkeeping metadata Standard, focusing on scope, the number of entities, category in entity, metadata elements. And shows some examples of relationship entity which is the key of multiple entity. As a result of the analysis, this paper suggests some consideration when recordkeeping metadata standard applying multiple entities is revised.

History of The CA IDMS Database Management System

The origins of IDMS can be traced from Charles Bachman's work on IDS at GE in the 1960s, through its formative years at B.F. Goodrich in the 1970s and its introduction into the commercial market by Cullinane/Cullinet Software into the 1980s. The modern CA IDMS evolved from a network model DBMS to one that supports multiple data models and an entire line of database administration and application development products.

CaBIG™ VISDA: Modeling, visualization, and discovery for cluster analysis of genomic data

BackgroundThe main limitations of most existing clustering methods used in genomic data analysis include heuristic or random algorithm initialization, the potential of finding poor local optima, the lack of cluster number detection, an inability to incorporate prior/expert knowledge, black-box and non-adaptive designs, in addition to the curse of dimensionality and the discernment of uninformative, uninteresting cluster structure associated with confounding variables.ResultsIn an effort to partially address these limitations, we develop the VIsual Statistical Data Analyzer (VISDA) for cluster modeling, visualization, and discovery in genomic data. VISDA performs progressive, coarse-to-fine (divisive) hierarchical clustering and visualization, supported by hierarchical mixture modeling, supervised/unsupervised informative gene selection, supervised/unsupervised data visualization, and user/prior knowledge guidance, to discover hidden clusters within complex, high-dimensional genomic data. The hierarchical visualization and clustering scheme of VISDA uses multiple local visualization subspaces (one at each node of the hierarchy) and consequent subspace data modeling to reveal both global and local cluster structures in a "divide and conquer" scenario. Multiple projection methods, each sensitive to a distinct type of clustering tendency, are used for data visualization, which increases the likelihood that cluster structures of interest are revealed. Initialization of the full dimensional model is based on first learning models with user/prior knowledge guidance on data projected into the low-dimensional visualization spaces. Model order selection for the high dimensional data is accomplished by Bayesian theoretic criteria and user justification applied via the hierarchy of low-dimensional visualization subspaces. Based on its complementary building blocks and flexible functionality, VISDA is generally applicable for gene clustering, sample clustering, and phenotype clustering (wherein phenotype labels for samples are known), albeit with minor algorithm modifications customized to each of these tasks.ConclusionVISDA achieved robust and superior clustering accuracy, compared with several benchmark clustering schemes. The model order selection scheme in VISDA was shown to be effective for high dimensional genomic data clustering. On muscular dystrophy data and muscle regeneration data, VISDA identified biologically relevant co-expressed gene clusters. VISDA also captured the pathological relationships among different phenotypes revealed at the molecular level, through phenotype clustering on muscular dystrophy data and multi-category cancer data.