A small country in a world of big science a preliminary bibliometric study of science in Singapore

An analysis of 258 papers published from Singapore and covered inScience Citation Index (SCI) 1979 and 1980 indicates that (1) much of R&D in Singapore pertains to medical research, (2) almost all the papers are published in English language periodicals published from the western world, (3) nearly two-thirds of Singapore's publication output is accounted for by the University of Singapore, and (4) by and large papers from Singapore are rarely cited, even if many of them have appeared in journals having impact factor greater than one.     

RAPID ONLINE MONITORING OF A HETEROGENEOUS CATALYST BY A PULSED REACTOR COUPLED TO GC-MS

A rapid screening system for heterogeneous catalyst discovery has been developed by coupling an in-house designed and fabricated high temperature vapor phase pulse reactor on-line to a GC-MS. The incorporation of gas chromatography for separation of the products with the mass spectrometry system allowed simultaneous identification and determination of reaction products and substrate conversion. This system was employed to study the vapor phase catalytic hydride transfer reduction (CHTR) of nitrobenzene with methanol as hydrogen donor on an MgO catalyst as a model reaction. Structural information of all the by-products that were formed was useful to understand the reaction mechanism. The products obtained with the new screening technique were in good agreement with conventional bench scale experiments. The rapid online screening provided an efficient methodology for optimization of reaction conditions such as catalyst loading, reaction temperature, and mole ratios. Response Surface Methodology (RSM) was used to optimize the conversion of reactants and selectivity of products.     

Quality aspects for component‐based systems: A metrics based approach

In component‐based development, software systems are built by assembling components already developed and prepared for integration. To estimate the quality of components, complexity, reusability, dependability, and maintainability are the key aspects. The quality of an individual component influences the quality of the overall system. Therefore, there is a strong need to select the best quality component, both from functional and nonfunctional aspects. The present paper produces a critical analysis of metrics for various quality aspects for components and component‐based systems. These aspects include four main quality factors: complexity, dependency, reusability, and maintainability. A systematic study is applied to find as much literature as possible. A total of 49 papers were found suitable after a defined search criteria. The analysis provided in this paper has a different objective as we focused on efficiency and practical ability of the proposed approach in the selected papers. The various key attributes from these two are defined. Each paper is evaluated based on the various key parameters viz. metrics definition, implementation technique, validation, usability, data source, comparative analysis, practicability, and extendibility. The paper critically examines various quality aspects and their metrics for component‐based systems. In some papers, authors have also compared the results with other techniques. For characteristics like complexity and dependency, most of the proposed metrics are analytical. Soft computing and evolutionary approaches are either not being used or much less explored so far for these aspects, which may be the future concern for the researchers. In addition, hybrid approaches like neuro‐fuzzy, neuro‐genetic, etc., may also be examined for evaluation of these aspects. However, to conclude that one particular technique is better than others may not be appropriate. It may be true for one characteristic by considering different set of inputs and dataset but may not be true for the same with different inputs. The intension in the proposed work is to give a score for each metric proposed by the researchers based on the selected parameters, but certainly not to criticize any research contribution by authors. Copyright © 2012 John Wiley & Sons, Ltd.     

A Parallel Interval Computation Model for Global Optimization with Automatic Load Balancing

In this paper,we propose a decentralized parallel computation model for global optimization using interval analysis.The model is adaptive to any number of processors and the workload is automatically and evenly distributed among all processors by alternative message passing.The problems received by each processor are processed based on their local dominance properties,which avoids unnecessary interval evaluations.Further,the problem is treated as a whole at the beginning of computation so that no initial decomposition scheme is required.Numerical experiments indicate that the model works well and is stable with different number of parallel processors,distributes the load evenly among the processors,and provides an impressive speedup,especially when the problem is time-consuming to solve.     

Auto-Discovering Configurations for Service Management

Determining service configurations is essential for effective service management. In this paper we describe a model-driven approach for service configuration auto-discovery. We develop metrics for performance and scalability analysis of such auto-discovery mechanisms. Our approach addresses several problems in auto-discovery: specification of what services to discover, how to efficiently distribute service discovery, and how to match instances of services into related groups. We use object-oriented models for discovery specifications, a flexible bus-based architecture for distribution and communication, and a novel multi-phased, instance matching approach. We have applied our approach to typical e-commerce services, Enterprise Resource Planning applications, like SAP, and Microsoft Exchange services running on a mixture of Windows and Unix platforms. The main contribution of this work is the flexibility of our models, architecture and algorithms to address discovery of a multitude of services.     

Time and Space Optimal Data Parallel Volume Rendering Using Permutation Warping

In this paper we present a data parallel volume rendering algorithm that possesses numerous advantages over prior published solutions. Volume rendering is a three-dimensional graphics rendering algorithm that computes views of sampled medical and simulation data, but has been much slower than other graphics algorithms because of the data set sizes and the computational complexity. Our algorithm usespermutation warpingto achieve linear speedup (run time is O(S/P) forPprocessors whenP\= O(S/logS) forS\=n³samples), linear storage (O(S)) for large data sets, arbitrary view directions, and high-quality filters. We derived a new processor permutation assignment of five passes (our prior known solution was eight passes), and a new parallel compositing technique that is essential for scaling linearly on machines that have more processors than view rays to process (P>n²). We show a speedup of 15.7 for a 16k processor over a 1k processor MasPar MP-1 (16 is linear) and two frames/second with a 128³volume and trilinear view reconstruction. In addition, we demonstrate volume sizes of 256³, constant run time over angles 5 to 75°, filter quality comparisons, and communication congestion of just 19 to 29\%.     

On fuzzy sobriety

This paper mainly shows that sober fuzzy topological spaces form the epireflective hull of the fuzzy Sierpinski space in the category of T₀-fuzzy topological spaces.     

Distributed diagnosis in dynamic fault environments

The problem of distributed diagnosis in the presence of dynamic failures and repairs is considered. To address this problem, the notion of bounded correctness is defined. Bounded correctness is made up of three properties: bounded diagnostic latency, which ensures that information about state changes of nodes in the system reaches working nodes with a bounded delay, bounded start-up time, which guarantees that working nodes determine valid states for every other node in the system within bounded time after their recovery, and accuracy, which ensures that no spurious events are recorded by working nodes. It is shown that, in order to achieve bounded correctness, the rate at which nodes fail and are repaired must be limited. This requirement is quantified by defining a minimum state holding time in the system. Algorithm heartbeatcomplete is presented and it is proven that this algorithm achieves bounded correctness in fully-connected systems while simultaneously minimizing diagnostic latency, start-up time, and state holding time. A diagnosis algorithm for arbitrary topologies, known as algorithm forwardheartbeat, is also presented. Forwardheartbeat is shown to produce significantly shorter latency and state holding time than prior algorithms, which focused primarily on minimizing the number of tests at the expense of latency.     

Estimation of composite damage model parameters using spectral finite element and neural network

A multi-layer perceptron (MLP) network using error back propagation algorithm is employed in this paper to estimate the damage parameters from broad-band spectral data as diagnostic signal. Various existing models of damage in laminated composite and the resulting stiffness degradation are discussed from comparative view-point. Degradation of ply properties can be considered to be one of the damage model parameters while monitoring transverse matrix cracks in cross-ply, splitting in longitudinal ply, and evolution of consecutive stages of damage, such as delaminations and fiber fracture. The stiffness degradation factor, the location and size of the damaged zone in laminated composite beam are considered as damage model parameters in the present paper. Fourier spectral data, which is typical to most of the diagnostic wave measurements, are used as input to the neural network. Since, training the neural network in such case involves many data sets and all of these data are difficult to generate using experiments, a spectral finite element model (SFEM) with embedded degraded zone in laminated composite beam is developed. Numerical simulation using this element is carried out, which shows the nature of temporal signal that are likely to be measured. Analytical studies on the performance of the neural network are presented based on numerically simulated data. Effect of measurement noise on the network performance is also reported.