21349955
A unified optimization framework for microelectronics industry
In this paper, an object-oriented unified optimization framework (UOF) for general problem optimization is proposed. Based on evolutionary algorithms, numerical deterministic methods, and C++ objective design, the UOF possesses real-world applications for various optimization problems. The UOF is with interface between defining a general problem and generic solver; hence the two areas are bridged. The UOF's components are categorized into problem and solver parts, and they work independently. Therefore, the reusable high level code allows the adaptation to new problem and solver quickly. Practical applications in microelectronics industry confirm the functionality of the developed unified optimization framework.
18159266
A Distributed Simulation-Based Computational Intelligence Algorithm for Nanoscale Semiconductor Device Inverse Problem
In this paper, a distributed simulation-based computational intelligence algorithm for inverse problem of nanoscale semiconductor device is presented. This approach features a simulation-based optimization strategy, and mainly integrates the semiconductor process simulation, semiconductor device simulation, evolutionary strategy, and empirical knowledge on a distributed computing environment. For a set of given target current-voltage (I-V) curves of metal-oxide-semiconductor field effect transistors (MOSFETs) devices, the developed prototype executes evolutionary tasks to solve an inverse doping profile problem, and therefore optimize fabrication recipes. In the evolutionary loop, the established management server allocates the jobs of process simulation and device simulation on a PC-based Linux cluster with message passing interface (MPI) libraries. Good benchmark results including the speed-up, the load balancing, and the parallel efficiency are presented. Computed results, compared with the realistic measured data of 65 nm n-type MOSFET, show the accuracy and robustness of the method.
12948988
Parallelization of Multiple Genome Alignment
In this work, we implement a genome alignment system which applies parallelization schemes to the ClustalW algorithm and the interface of database querying. Parallel construction of the distance matrices and parallelization of progressive alignment in the ClustalW algorithm are performed on PC-based Linux cluster with message-passing interface libraries. Achieved experiments show good speedup and significant parallel performance.
6671949
Identification of critical genes in microarray experiments by a Neuro-Fuzzy approach
Gene expression profiling by microarray technology is usually difficult to interpret into a simpler pattern. One approach to resolve the complexity of gene expression profiles is the application of artificial neural networks (ANNs). A potential difficulty in this strategy, however, is that the non-linear nature of ANN makes it essentially a 'black-box' computation process. Addition of a fuzzy logic approach is useful because it can complement ANN by explicitly specifying membership function during computation. We employed a hybrid approach of neural network and fuzzy logic to further analyze a published microarray study of gene responses to eight bacteria in human macrophages. The original analysis by hierarchical clustering found common gene responses to all bacteria but did not address individual responses. Our method allowed exploration of the gene response of the host to individual bacterium. We implemented a two-layer, feed-forward neural network containing the principle of 'competitive learning' (i.e. 'winner-take-all'). The weights of the trained neural network were fed into a fuzzy logic inference system. A new measurement, called the impact rating (IR) was also introduced to explore the degree of importance of each gene. To assess the reliability of the IR value, a bootstrap re-sampling method was applied to the dataset and a confidence level for each IR was obtained. Our approach has successfully uncovered the unique features of host response to individual bacterium. Further, application of gene ontology (GO) annotation to the genes of high IR values in each response has suggested new biological pathways for individual host-pathogen interactions.
14759214
Real-coded ECGA for economic dispatch
In this paper, we propose a new approach that consists of the extended compact genetic algorithm (ECGA) and split-on-demand (SoD), an adaptive discretization technique, to economic dispatch (ED) problems with nonsmooth cost functions. ECGA is designed for handling problems with decision variables of the discrete type, while the decision variables of ED problems are oftentimes real numbers. Thus, in order to employ ECGA to tackle ED problems, SoD is utilized for discretizing the continuous decision variables and works as the interface between ECGA and the ED problem. Furthermore, ED problems in practice are usually hard for traditional mathematical programming methodologies because of the equality and inequality constraints. Hence, in addition to integrating ECGA and SoD, in this study, we devise a repair operator specifically for making the infeasible solutions to satisfy the equality constraint. To examine the performance and effectiveness, we apply the proposed framework to two different-sized ED problems with nonsmooth cost function considering the valve-point effects. The experimental results are compared to those obtained by various evolutionary algorithms and demonstrate that handling ED problems with the proposed framework is a promising research direction.
12536250
Generalised similarity analysis and pathfinder network scaling
Abstract This paper introduces a generic approach to the development of hypermedia information systems. This approach emphasises the role of intrinsic inter-document relationships in structuring and visualising a large hypermedia information space. In this paper, we illustrate the use of this approach based on three types of similarity measurements: hypertext linkage, content similarity and usage patterns. Salient patterns in these relationships are extracted and visualised in a simple and intuitive associated network. The spatial layout of a visualisation is optimised such that closely related documents are placed near to each other and only those intrinsic connections among them are shown to users as automatically generated virtual links. This approach supports self-organised information space transformation based on usage patterns and other feedback such that the visual structure of the information space is incrementally tailored to users' search and browsing styles.
42451139
Visualizing scientific paradigms: An introduction
This special topic issue includes a collection of seven articles on visualizing scientific paradigms. All articles in this special issue reflect the influence of Thomas Kuhn’s structure of scientific revolutions on our understanding of the growth of scientific knowledge. On the other hand, each article represents a unique perspective of how one may pursue the quest for transforming something as intangible and empirically evasive as invisible colleges and competing paradigms into something that is more accessible and traceable to scholars and professions of various disciplines, ranging from historians, philosophers, and educators to scientists and engineers. The opening article is Henry Small’s personal account of the endeavor in probing scientific paradigms using science mapping. His article, entitled “Paradigms, Citations and Maps of Science: A Personal History,” provides a valuable introduction to the key issues involved in this area and reveals an overview of promising avenues as well as challenging routes. He identifies an emerging trend that reflects and redefines Kuhn’s paradigms and emphasizes the empirical viability of research methodologies in understanding the growth of scientific knowledge. He suggests that revolutionary and normal science should be seen as extremes on a continuum of rates of change rather than, as Kuhn originally asserted, as an all-or-none proposition. The second and third articles take a prominent historical perspective in depicting the evolution of scientific citations. Eugene Garfield and his collaborators’ article is entitled “Why Do We Need Algorithmic Historiography?” They explain the rationale for creating HistCite, their new program that produces historiographs of scholarly topics. These historiographs help analysts and historians identify key events, people, and journals in a particular field. Scholars can evaluate the evolution of a scientific paradigm by studying the genealogic profile of such evolution. The third article is entitled “Timeline Visualization of Research Fronts.” Steven Morris and his colleagues focus on temporal changes in research fronts and explain the power of timeline visualizations. They first cluster documents into research fronts based on bibliographic coupling and then visualize research fronts using horizontal timeline tracks. Documents from research fronts are plotted along corresponding timeline tracks. Because time line visualizations can reveal temporal relations among research fronts and their member documents, time lines are potentially useful tools in identifying new research fronts as well as existing research expertise and research excellence. Although both the fourth and fifth articles have connections to Pathfinder networks, they address different topics. Howard White’s article, entitled “Pathfinder Networks and Author Cocitation Analysis: A Remapping of Paradigmatic Information Scientists,” clarifies an important methodological issue, whereas Chen and Kuljis focus on a general framework for visualizing scientific paradigms in their article. Author Cocitation Analysis (ACA) is a long established methodology for studying intellectual structures. Researchers have routinely used Pearson correlation coefficients rather than raw cocitation counts as the measure of similarity between author pairs. Howard White compellingly demonstrates the advantages of using raw cocitation counts in Pathfinder network visualizations of author cocitation structures. He compares Pathfinder networks of the information scientists derived from raw cocitation counts and Pearson correlation coefficients, respectively. In the fifth article “The Rising Landscape: A Visual Exploration of Superstring Revolutions in Physics,” Chen and Kuljis introduce a general framework for visualizing the growth of scientific paradigms based on Kuhn’s theory on scientific revolutions. They illustrate the use of this framework in a case study of superstring revolutions in physics. The evolution of cocitation networks is depicted and explained through animated visualizations of citations and cocitation links. Visual-spatial properties as well as structural patterns associated with superstring revolutions are identified. The sixth and seventh articles deal with heterogeneous data sources. In their article entitled “Indicator-Assisted Evaluation and Funding of Research: Visualizing the Influ© 2003 Wiley Periodicals, Inc.
704070
Model-Guided Empirical Optimization for Multimedia Extension Architectures: A Case Study
Compiler technology for multimedia extensions must effectively utilize not only the SIMD compute engines but also the various levels of the memory hierarchy: superword registers, multi-level caches and TLB. In this paper, we describe a compiler that combines optimization across all levels of the memory hierarchy with automatic generation of SIMD code for multimedia extensions. At the high-level, model-guided empirical optimization is used to transform code to optimize for all levels of the memory hierarchy. This compiler interacts with a backend compiler exploiting superword-level parallelism that takes sequential code as input and produces SIMD code. This paper discusses how we have combined these technologies into a single framework. Through a case study with matrix multiply, we observe performance results that outperform the hand-tuned Intel MKL library, and achieve performance that is within 4% of the ATLAS self-tuning library with architectural defaults and more than 4X faster than the native Intel compiler.