Standard Test Bed Research Articles

Wide-area power oscillation damping with a fuzzy controller compensating the continuous communication delays

Recent technological developments in the wide-area measurement system (WAMS) are realizing centralized controls for improving the power systems stability. The most challenging barrier against these advances relates to communication delays, which are not constant and depend on information system loading. Neglecting this latency could deteriorate the damping performance of closed loop control or even degrade the system stability. This paper designs a fuzzy logic wide-area damping controller (FLWADC) to damp the inter-area oscillations compensating for the continuous latency. The controller is based on the fuzzy logic due to its proven robustness against input signal variations. The proposed controller has three input signals consisting of angular difference, its derivative, and the time latency, which is precisely determined through measured data time tags and the accurate time signal at the controller location. Rule bases of FLWADC are developed such that membership functions of the output variable are accordingly shifted to compensate for the time delay. A standard test bed for dynamic simulations and its expanded version are examined, and numerical evidences are discussed. To generalize the conclusions drawn in the case study, various sets of sensitivity studies are conducted, covering controller parameter changes, power system reconfigurations, and shifting the system operating point.

Any-Angle Path Planning for Computer Games

Path planning is a critical part of modern computer games; rare is the game where nothing moves and path planning is unneeded. A* is the workhorse for most path planning applications. Block A* is a state-of-the-art algorithm that is always faster than A* in experiments using game maps. Unlike other methods that improve upon A*'s performance, Block A* is never worse than A* nor require any knowledge of the map. In our experiments, Block A* is ideal for games with randomly generated maps, large maps, or games with a highly dynamic multi-agent environment. Furthermore, in the domain of grid-based any-angle path planning, we show that Block A* is an order of magnitude faster than the previous best any-angle path planning algorithm, Theta*. We empirically show our results using maps from Dragon Age: Origins and Starcraft. Finally, we introduce ``populated game maps'' as a new test bed that is a better approximation of real game conditions than the standard test beds of this field. The main contributions of this paper is a more rigorous set of experiments for Block A*, and introducing a new test bed (populated game maps) that is a more accurate representation of actual game conditions than the standard test beds.

A Decade of Data Mining and Still Counting

The introduction of database-wide disproportionality screening for signal detection in spontaneous reporting systems (SRS) sparked a renaissance in pharmacovigilance research notable for numerous peer reviewed research articles, three expert working groups/white papers, countless meetings, symposia, workshops, graduate school theses and aggressive promotion of proprietary software. In addition to expanding the pharmacovigilance toolkit, this research has yielded ancillary benefits beyond patient safety, including an increased awareness of data quality issues such as case report duplication, the importance of adverse event coding terminology, the proper definition of signal in drug safety, the logic of signal detection and an admonition that conflicts of interest, both intellectual and financial, may not only involve the ‘usual suspects’ such as software vendors, but also other stakeholders that may not normally come tomind, such as regulatory authorities. The absence of standard test beds for systematic evaluation of signal detection methodologies is an impediment to progress. A fundamental question is what steps of a comprehensive screening strategy to test and what to compare performance against. Herein, we discuss the value of data mining evaluation studies that continue to appear, and related issues, in the hope of facilitating pharmacovigilance system benchmarking and optimization. As a basis for discussion we focus on three recent performance evaluations published in Drug Safety (see table I).

Software Testing Practices

In the simplest terms, Software Testing is a process to ensure the accuracy, completeness and quality of any developed software. Rather than limiting this to a formally technical process used to investigate and measure quality of the developed computer software in terms of correctness, completeness and security, it is imperative to test the software components and the software as a whole for integrity, capability, reliability, efficiency, portability, maintainability, compatibility and usability of the software. This is particularly important in an operating environment where it is planned to be implemented, and testing will need to adhere to the technical requirements as described under ISO standard ISO 9126. Effective testing requires the presence of adequate and suitable test data. Where test results are specified, it is presumed that the inputs will be consistent from text execution to execution. In situations where automated testing methodologies are employed, a standardized test bed of data may be required to facilitate the automated assessment of passed. The best approach is to conduct end to end testing. Testing methodology is applied in two major phases: Functional Testing and Non-Functional Testing. One of the purposes of automated testing is to ease regression testing. Once the system is stable, then automated testing can be started. Preferably, automated tests can be run overnight on software builds, rather than the live version. This will help give a clearer indication to the stability of the build the following morning. Hopefully leading to more time being available for the rest of the testing and development. Software Testing Practices

Applications of Screened Hybrid Density Functionals with Empirical Dispersion Corrections to Rare Gas Dimers and Solids.

An empirical dispersion correction is added to the range-separated hybrid density functionals HSE and HISS via parametrization versus a standard test bed of weakly bound complexes. The performance of the resulting HSE-D and HISS-D functionals is evaluated by calculating the equilibrium bond length, harmonic frequency, and dissociation energy for a number of rare gas dimers, and the lattice constants, band gaps, and sublimation energies of the rare gas solids. Both HSE-D and HISS-D are shown to provide accurate results for both molecules and extended systems, suggesting that the combination of a screened hybrid functional with an empirical dispersion correction provides an accurate, widely applicable method for use in solid-state and gas-phase electronic structure theory.

An artificial life approach to dense stereo disparity

This article presents an adaptive approach to improving the infection algorithm that we have used to solve the dense stereo matching problem. The algorithm presented here incorporates two different epidemic automata along a single execution of the infection algorithm. The new algorithm attempts to provide a general behavior of guessing the best correspondence between a pair of images. Our aim is to provide a new strategy inspired by evolutionary computation, which combines the behaviors of both automata into a single correspondence problem. The new algorithm will decide which automata will be used based on the transmission of information and mutation, as well as the attributes, texture, and geometry, of the input images. This article gives details about how the rules used in the infection algorithm are coded. Finally, we show experiments with a real stereo pair, as well as with a standard test bed, to show how the infection algorithm works.

Transient Mode Calibration — Mixture Quality Evaluation

AVL List GmbH presents a measurement technique which enables evaluation of mixture formation quality in order to support calibration of emissions relevant SI engine operation. The method is especially suited to identify individual cycles’ particulate emissions contributions at engine start and in transient operation. Sensors, signal recorders and signal evaluation are part of standard test bed and on-board analysis systems.

Cost Aggregation and Occlusion Handling With WLS in Stereo Matching

This paper presents a novel method for cost aggregation and occlusion handling for stereo matching. In order to estimate optimal cost, given a per-pixel difference image as observed data, we define an energy function and solve the minimization problem by solving the iterative equation with the numerical method. We improve performance and increase the convergence rate by using several acceleration techniques such as the Gauss-Seidel method, the multiscale approach, and adaptive interpolation. The proposed method is computationally efficient since it does not use color segmentation or any global optimization techniques. For occlusion handling, which has not been performed effectively by any conventional cost aggregation approaches, we combine the occlusion problem with the proposed minimization scheme. Asymmetric information is used so that few additional computational loads are necessary. Experimental results show that performance is comparable to that of many state-of-the-art methods. The proposed method is in fact the most successful among all cost aggregation methods based on standard stereo test beds.

Implementation of standard testbeds for numerical relativity

We discuss results that have been obtained from the implementation of the initial round of testbeds for numerical relativity which was proposed in the first paper of the Apples with Apples Alliance. We present benchmark results for various codes which provide templates for analyzing the testbeds and to draw conclusions about various features of the codes. This allows us to sharpen the initial test specifications, design a new test and add theoretical insight.

In this issue

In this issue

Knowledge-based query expansion to support scenario-specific retrieval of medical free text

In retrieving medical free text, users are often interested in answers pertinent to certain scenarios that correspond to common tasks performed in medical practice, e.g., treatment or diagnosis of a disease. A major challenge in handling such queries is that scenario terms in the query (e.g., treatment) are often too general to match specialized terms in relevant documents (e.g., chemotherapy). In this paper, we propose a knowledge-based query expansion method that exploits the UMLS knowledge source to append the original query with additional terms that are specifically relevant to the query's scenario(s). We compared the proposed method with traditional statistical expansion that expands terms which are statistically correlated but not necessarily scenario specific. Our study on two standard testbeds shows that the knowledge-based method, by providing scenario-specific expansion, yields notable improvements over the statistical method in terms of average precision-recall. On the OHSUMED testbed, for example, the improvement is more than 5% averaging over all scenario-specific queries studied and about 10% for queries that mention certain scenarios, such as treatment of a disease and differential diagnosis of a symptom/disease.

The stochastic joint replenishment problem: A new policy, analysis, and insights

AbstractIn this study, we propose a new parsimonious policy for the stochastic joint replenishment problem in a single‐location, N‐item setting. The replenishment decisions are based on both group reorder point‐group order quantity and the time since the last decision epoch. We derive the expressions for the key operating characteristics of the inventory system for both unit and compound Poisson demands. In a comprehensive numerical study, we compare the performance of the proposed policy with that of existing ones over a standard test bed. Our numerical results indicate that the proposed policy dominates the existing ones in 100 of 139 instances with comparably significant savings for unit demands. With batch demands, the savings increase as the stochasticity of demand size gets larger. We also observe that it performs well in environments with low demand diversity across items. The inventory system herein also models a two‐echelon setting with a single item, multiple retailers, and cross docking at the upper echelon. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006

A computational method for the calculation of the feasibility boundary and clustering in differential-algebraic systems

A clustering approach is presented to calculate the limits of parametric stability for a stable equilibrium of the power systems modeled by differential algebraic equations (DAEs) , the so-called feasibility boundary. The underlying algorithm for calculation is based on the sensitivities of the eigenvalues of the DA system. The procedure is illustrated with several examples based on the standard nine-bus system and test beds formed by connecting sets of two and four nine-bus systems together.

Towards standard testbeds for numerical relativity

In recent years, many different numerical evolution schemes for Einstein's equations have been proposed to address stability and accuracy problems that have plagued the numerical relativity community for decades. Some of these approaches have been tested on different spacetimes, and conclusions have been drawn based on these tests. However, differences in results originate from many sources, including not only formulations of the equations, but also gauges, boundary conditions, numerical methods and so on. We propose to build up a suite of standardized testbeds for comparing approaches to the numerical evolution of Einstein's equations that are designed to both probe their strengths and weaknesses and to separate out different effects, and their causes, seen in the results. We discuss general design principles of suitable testbeds, and we present an initial round of simple tests with periodic boundary conditions. This is a pivotal first step towards building a suite of testbeds to serve the numerical relativists and researchers from related fields who wish to assess the capabilities of numerical relativity codes. We present some examples of how these tests can be quite effective in revealing various limitations of different approaches, and illustrating their differences. The tests are presently limited to vacuum spacetimes, can be run on modest computational resources and can be used with many different approaches used in the relativity community.

Local Extremes, Runs, Strings and Multiresolution

The paper considers the problem of nonparametric regression with emphasis on controlling the number of local extremes. Two methods, the run method and the taut-string multiresolution method, are introduced and analyzed on standard test beds. It is shown that the number and locations of local extreme values are consistently estimated. Rates of convergence are proved for both methods. The run method converges slowly but can withstand blocks as well as a high proportion of isolated outliers. The rate of convergence of the taut-string multiresolution method is almost optimal. The method is extremely sensitive and can detect very low power peaks. Section 1 contains an introduction with special reference to the number of local extreme values. The run method is described in Section 2 and the taut-string-multiresolution method in Section 3. Low power peaks are considered in Section 4. Section contains a comparison with other methods and Section 6 a short conclusion. The proofs are given in Section 7 and the taut-string algorithm is described in the Appendix.

An Approximate Determinization Algorithm for Weighted Finite-State Automata

Nondeterministic weighted finite-state automata are a key abstraction in automatic speech recognition systems. The efficiency of automatic speech recognition depends directly on the sizes of these automata and the degree of nondeterminism present, so recent research has studied ways to determinize and minimize them, using analogues of classical automata determinization and minimization. Although, as we describe here, determinization can in the worst case cause poly-exponential blowup in the number of states of a weighted finite-state automaton, in practice it is remarkably successful. In extensive experiments in automatic speech recognition systems, deterministic weighted finite-state automata tend to be smaller than the corresponding nondeterministic inputs. Our observations show that these size reductions depend critically on the interplay between weights and topology in nondeterministic weighted finite-state automata. We exploit these observations to design a new approximate determinization algorithm, which produces a deterministic weighted finite-state automaton that preserves the strings of a weighted language but not necessarily their weights. We apply our algorithm to two different types of weighted finite-state automata that occur in automatic speech recognition systems and in each case provide extensive experimental results showing that, compared with current techniques, we achieve significant size reductions without affecting performance. In particular, for a standard test bed, we can reduce automatic speech recognition memory requirements by 25—35\percent with negligible effects on recognition time and accuracy.

Application of bacteriorhodopsin for optical limiting eye protection filters

The optical limiting properties of wildtype bacteriorhodopsin and D96N variant, solutions and films are described. Nanosecond pulse and continuous-wave visible regimes were used to evaluate samples in standard test-beds, for the application of eye protection laser filters. Molecular switching at low enough energies and powers for eye protection was possible, but only a low level of limiting was found. The refractive index change in films was found to reduce the laser energy present on a simulated retina. However the transmission spectrum of the unexposed films had poor characteristics for this application.

Genetic algorithms (GAs) to evolve multiple-agent cooperative systems

In this paper, a microrobot soccer-playing game, such as that of MIROSOT (Microrobot World Cup Soccer Tournament), is adopted as a standard test bed for research on multiple-agent cooperative systems. It is considerably complex and requires expertise in several difficult research topics, such as mobile microrobot design, motor control, sensor technology, intelligent strategy planning, etc., to build up a complete system to play the game. In addition, because it is an antagonistic game, it appears ideal to test whether one method is better than other. To date there have been two different kinds of architecture for building such system. One is called vision-based or centralized architecture, and the other is known as robot-based or decentralized architecture. The main difference between them lies in whether there exists a host computer system which responds to data processing and strategy planning, and a global vision system which can view the whole playground and transfer the environment information to the host computer in real time. We believe that the decentralized approach is more advanced, but in the preliminary step of our study, we used the centralized approach because it can lighten any overload of the microrobot design. In this paper, a simplified layer model of the multiple-agent cooperative system is first proposed. Based on such a model, a system for a microrobot soccer-playing game is organized. At the same time a simple genetic algorithm (SGA) is used for the autonomous evolution of cooperative behavior among microrobots. Finally, a computer simulation system is introduced and some simulated results are explained.

TESSA—an image testbed for evaluating 2-D spatial similarity algorithms

In multimedia database applications, a major class of users' requests require retrieving those images in the database that are spatially similar to the query image. To process such queries, a spatial similarity algorithm is required. A spatial similarity algorithm assesses the degree to which the spatial relationships among the domain objects in a database image conform to those specified in the query image. The recent ubiquitous interest in multimedia information systems has spurred a great interest in spatial similarity algorithms. A standard testbed of images is required not only to systematically evaluate these algorithms but also to compare and contrast them. However, there is no such testbed of images available for this purpose.In this paper, we describe a collection of images, referred to as TESSA, as a testbed for investigating the robustness of spatial similarity algorithms and their further use in evaluating the retrieval effectiveness of these algorithms. The TESSA collection comprises 160 images and are produced by generating 15 variants of each of the 10 original images. Image variants are produced by scale, rotation, and translation, and by an arbitrary composition of these three transformations. The variants are designed to inquire into the robustness of spatial similarity algorithms. To facilitate their further use in evaluating the retrieval effectiveness, each image in TESSA is considered as a query in turn, and an expert is asked to provide a rank ordering of the TESSA images with respect to the query image vis-a-vis expert provided rank ordering. System provided rank ordering for a query image is the rank ordering of TESSA images induced by a spatial similarity algorithm with respect to the query. Retrieval effectiveness of spatial similarity algorithms is then characterized by using R norm measure. This measure is based on both the expert and system provided rank orderings.