ppxscal/embedding_network huggingface dataset:
Determining contact energy function for continuous state models of globular protein conformations
Authors: Y. Zenmei Ohkubo, Gordon M. Crippen
Venue: Proceedings of the fourth annual international conference on Computational molecular biology (2000)

One of the approaches to protein structure prediction is to obtain energy functions which can recognize the native conformation of a given sequence among a zoo of conformations. The discriminations can be done by assigning the lowest energy to the native conformation, with the guarantee that the native is in the zoo. Well-adjusted functions, then, can be used in the search for other (near-) natives. Here the aim is the discrimination at relatively high resolution (RMSD difference between the native and the closest nonnative is around 1 &Aring;) by pairwise energy potentials. The results show that the potential can be trained to discriminate between the native conformation of one protein as the (near-) global minimum, and other nonnatives, including energy-minimized ones (or local minima). This potential function is able to identify the native conformation of another protein, too.
The onion technique: indexing for linear optimization queries
Authors: Yuan-Chi Chang, Lawrence Bergman, Vittorio Castelli, Chung-Sheng Li, Ming-Ling Lo, John R. Smith
Venue: ACM SIGMOD Record (2000)

This paper describes the Onion technique, a special indexing structure for linear optimization queries. Linear optimization queries ask for top-N records subject to the maximization or minimization of linearly weighted sum of record attribute values. Such query appears in many applications employing linear models and is an effective way to summarize representative cases, such as the top-50 ranked colleges. The Onion indexing is based on a geometric property of convex hull, which guarantees that the optimal value can always be found at one or more of its vertices. The Onion indexing makes use of this property to construct convex hulls in layers with outer layers enclosing inner layers geometrically. A data record is indexed by its layer number or equivalently its depth in the layered convex hull. Queries with linear weightings issued at run time are evaluated from the outmost layer inwards. We show experimentally that the Onion indexing achieves orders of magnitude speedup against sequential linear scan when N is small compared to the cardinality of the set. The Onion technique also enables progressive retrieval, which processes and returns ranked results in a progressive manner. Furthermore, the proposed indexing can be extended into a hierarchical organization of data to accommodate both global and local queries.
Energy efficient design of portable wireless systems
Authors: Tajana Simunic, Haris Vikalo, Peter Glynn, Giovanni De Micheli
Venue: Proceedings of the 2000 international symposium on Low power electronics and design (2000)

Portable wireless systems require long battery lifetime while still delivering high performance. The major contribution of this work is combining new it power management(PM) and it power control (PC) algorithms to trade off performance for power consumption at the system level in portable devices. First we present the formulation for the solution of the PM policy optimization based on renewaltheory. Next we present the formulation for power control (PC) of the wireless link that enables us to obtain further energy savings when thesystem is active. Finally, we discuss the measurements obtained for a set of PM and PC algorithms implemented for the WLAN card on a laptop. The PM policy we developed based on our renewal model consumes three times less power as compared to the default PM policy for the WLAN card with still high performance. Power control saves additional 53% in energy at same bit error rate. With both power control and power management algorithms in place, we observe on average a factor of six in power savings.
A Preconditioned Semi-Implicit Method for Magnetohydrodynamics Equations
Authors: T. Amari, J. F. Luciani, P. Joly
Venue: SIAM Journal on Scientific Computing (1999)

The paper describes the development of a semi-implicit solver designed for the need to follow slow evolution flows encountered in nonlinear resistive computational plasma dynamics (CPD). Spatial discretization uses a second order finite difference approximation while temporal advance is achieved by a second order semi-implicit predictor-corrector scheme that reduces the severe time step constraints imposed by the fast magnetosonic and Alfven waves on standard explicit schemes. An efficient preconditioner adapted to magnetohydrodynamics (MHD) problems and associated with conjugate gradient--like linear solvers considerably increases the CPU saving when compared with an explicit advance. This scheme enables the use of a large time step as well as the necessary high spatial resolution. An application of this scheme to a class of astrophysical nonlinear MHD problems allows one to perform numerical experiments relevant to the slow MHD evolution of the magnetic field, dominating the outer atmosphere of the sun, that leads to small scales formation.
Optimal Zero-Aliasing Space Compaction of Test Responses
Authors: Krishnendu Chakrabarty, Brian T. Murray, John P. Hayes
Venue: IEEE Transactions on Computers (1998)

Many built-in self-testing (BIST) schemes compress the test responses from a k-output circuit to q signature streams, where q 1.
Optimized unrolling of nested loops
Authors: Vivek Sarkar
Venue: Proceedings of the 14th international conference on Supercomputing (2000)

In this paper, we address the problems of automatically selecting unroll factors for perfectly nested loops, and generating compact code for the selected unroll factors. Compared to past work, the contributions of our work include a) a more detailed cost model that includes ILP and 1-cache considerations, b) a new code generation algorithm for unrolling nested loops that generates more compact code (with fewer remainder loops) than the unroll-and-jam transformation, and c) a new algorithm for efficiently enumerating feasible unroll vectors.Our experimental results confirm the wide applicability of our approach by showing a 2.2X speedup on matrix multiply, and an average 1.08X speedup on seven of the SPEC95fp benchmarks (with a 1.2X speedup for two benchmarks). These speedups are significant because the baseline compiler used for comparison is the IBM XL Fortran product compiler which generates high quality code with unrolling and software pipelining of innermost loops enabled. Larger performance improvements due to unrolling of nested loops can be expected on processors that have larger numbers of registers and larger degrees of instruction-level parallelism than the processor used for our measurements (PowerPC 604).
GENOA&mdash;a customizable, front-end-retargetable source code analysis framework
Authors: Premkumar T. Devanbu
Venue: ACM Transactions on Software Engineering and Methodology (TOSEM) (1999)

Code analysis tools provide support for such software engineering tasks as program understanding, software metrics, testing, and reengineering. In this article we describe GENOA, the framework underlying application generators such as Aria and GEN++ which have been used to generate a wide range of practical code analysis tools. This experience illustrates front-end retargetability of GENOA; we describe the features of the GENOA framework that allow it to be used with different front ends. While permitting arbitrary parse tree computations, the GENOA specification language has special, compact iteration operators that are tuned for expressing simple, polynomial-time analysis programs; in fact, there is a useful sublanguage of the GENOA language that can express precisely all (and only) polynomial-time (PTIME) analysis programs on parse trees. Thus, we argue that the GENOA language is a simple and convenient vehicle for implementing a range of analysis tools. We also argue that the &ldquo;front-and reuse&rdquo; approach of GENOA offers an important advantage for tools aimed at large software projects: the reuse of complex, expensive build procedures to run generated tools over large source bases. In this article, we describe the GENOA framework and our experiences with it.
An approximate search engine for structural databases
Authors: Jason T. L. Wang, Xiong Wang Dennis Shasha, Bruce A. Shapiro, Kaizhong Zhang, Qicheng Ma, Zasha Weinberg
Venue: ACM SIGMOD Record (2000)

When a person interested in a topic enters a keyword into a Web search engine, the response is nearly instantaneous (and sometimes overwhelming). The impressive speed is due to clever inverted index structures, caching, and a domain-independent knowledge of strings. Our project seeks to construct algorithms, data structures, and software that approach the speed of keyword-based search engines for queries on structural databases.A structural database is one whose data objects include trees, graphs, or a set of interrelated labeled points in two, three, or higher dimensional space. Examples include databases holding (i) protein secondary and tertiary structure, (ii) phylogenetic trees, (iii) neuroanatomical networks, (iv) parse trees, (v) molecular diagrams, and (vi) XML documents. Comparison queries on such databases require solving variants of the graph isomorphism or subisomorphism problems (for which all known algorithms are exponential), so we have explored a large heuristic space.
Reliability growth modeling from fault failure rates
Authors: Steven J. Zeil
Venue: ACM SIGSOFT Software Engineering Notes (2000)

A variety of reliability growth models provide quantified measures of test effectiveness in terms that are directly relevant to project management [Lyu96], but at the cost of restricting testing to representative selection, in which test data is chosen to reflect the operational distribution of the program's inputs. During testing, data is collected on the observed times between program failures (or, similarly, numbers of failures within a time interval). These observations are fitted to one of various models, which can then be used to estimate the current reliability of the program.
Relaxation of Control Systems Under State Constraints
Authors: Hélène Frankowska, Franco Rampazzo
Venue: SIAM Journal on Control and Optimization (1999)

In this paper we provide a relaxation result for control systems under both equality and inequality constraints involving the state and the control. In particular, we show that the Mangasarian--Fromowitz constraint qualification allows us to rewrite constrained systems as differential inclusions with locally Lipschitz right-hand side. Then the Filippov--Wazewski relaxation theorem may be applied to show that ordinary solutions are dense in the set of relaxed solutions. If, besides agreeing with the above constraints, the state has to remain in a control-independent set K, then the Mangasarian--Fromowitz condition cannot hold. This case is investigated as well by means of a condition on the feasible velocities on the boundary of K.
Exploiting Behavioral Information in Gate-Level ATPG
Authors: Silvia Chiusano, Fulvio Corno, Paolo Prinetto
Venue: Journal of Electronic Testing: Theory and Applications (1999)

This paper aims at broadening the scope of hierarchical ATPG to the behavioral-level. The main problem is identified, namely the mismatch of timing models between the behavioral- and gate-levels. As a main contribution of this paper, a theoretical analysis of this problem led to the definition of a novel concept, that of dominated patterns, that captures the needed link between the levels. Some metrics are defined, taken from the software realm, that allow generation of test patterns at the behavioral-level. To validate the concept correctness, different ATPG systems are presented, and experimental results show an improvement in the test quality, thanks to the exploitation of behavioral-level information.
Levelwise Search and Pruning Strategies for First-Order HypothesisSpaces
Authors: Irene Weber
Venue: Journal of Intelligent Information Systems (2000)

The discovery of interesting patterns in relational databases is an important data mining task. This paper is concerned with the development of a search algorithm for first-order hypothesis spaces adopting an important pruning technique (termed subset pruning here) from association rule mining in a first-order setting. The basic search algorithm is extended by so-called requires and excludes constraints allowing to declare prior knowledge about the data, such as mutual exclusion or generalization relationships among attributes, so that it can be exploited for further structuring and restricting the search space. Furthermore, it is illustrated how to process taxonomies and numerical attributes in the search algorithm.Several task settings using different interestingness criteria and search modes with corresponding pruning criteria are described. Three settings serve as test beds for evaluation of the proposed approach. The experimental evaluation shows that the impact of subset pruning is significant, since it reduces the number of hypothesis evaluations in many cases by about 50%. The impact of generalization relationships is shown to be less effective in our experimental set-up.
Learning Team Strategies: Soccer Case Studies
Authors: Rafał P. Sałustowicz, Marco A. Wiering, Jürgen Schmidhuber
Venue: Machine Learning (1998)

We use simulated soccer to study multiagent learning. Each team&lsquo;s players (agents) share action set and policy, but may behave differently due to position-dependent inputs. All agents making up a team are rewarded or punished collectively in case of goals. We conduct simulations with varying team sizes, and compare several learning algorithms: TD-Q learning with linear neural networks (TD-Q), Probabilistic Incremental Program Evolution (PIPE), and a PIPE version that learns by coevolution (CO-PIPE). TD-Q is based on learning evaluation functions (EFs) mapping input/action pairs to expected reward. PIPE and CO-PIPE search policy space directly. They use adaptive probability distributions to synthesize programs that calculate action probabilities from current inputs. Our results show that linear TD-Q encounters several difficulties in learning appropriate shared EFs. PIPE and CO-PIPE, however, do not depend on EFs and find good policies faster and more reliably. This suggests that in some multiagent learning scenarios direct search in policy space can offer advantages over EF-based approaches.
Generic Universal Switch Blocks
Authors: Michael Shyu, Guang-Ming Wu, Yu-Dong Chang, Yao-Wen Chang
Venue: IEEE Transactions on Computers (2000)

A switch block $M$ with $W$ terminals on each side is said to be universal if every set of nets satisfying the dimension constraint (i.e., the number of nets on each side of $M$ is at most $W$) is simultaneously routable through $M$ [2]. In this paper, we present an algorithm to construct N-sided universal switch blocks with $W$ terminals on each side. Each of our universal switch blocks has ${{N}\choose{2}}W$ switches and switch-block flexibility$N-1$ (i.e., $F_S = N-1$). We prove that no switch block with less than ${{N}\choose{2}}W$ switches can be universal. We also compare our universal switch blocks with others of the topology associated with Xilinx XC4000-type FPGAs. To explore the area performance of the universal switch blocks, we develop a detailed router for hierarchical FPGAs (HFPGAs) with 5-sided switch blocks. Experimental results demonstrate that our universal switch blocks improve routability at the chip level. Based on extensive experiments, we also provide key insights into the interactions between switch-block architectures and routing.
Designing special-purpose input devices
Authors: W. Bradford Paley
Venue: ACM SIGGRAPH Computer Graphics (1998)

For an increasing number of applications, we may be reaching the point of diminishing returns with general purpose computer input devices, such as the keyboard and mouse. At Digital Image Design Incorporated (DID) we've created special purpose input devices to perform tasks that are commonly addressed with software and general purpose devices alone. These more specific devices have led to significant advantages in accomplishing the tasks, and we've developed an approach to designing these devices that I hope will help others in doing similar work.When someone says "Build us a system to speed up computer character animation," the typical solution is purely software. This is not necessarily optimal or even cost effective, and the only way to determine that is to consider developing a hardware device during the initial project exploration. Let's go through the process of designing a special purpose device together. Real-world details are critical to this process, so we'll do it in the problem domain of animation, where DID and others have previously developed special purpose input devices. I'll generalize where appropriate.
Handwritten Digit Recognition by a Mixture of Local PrincipalComponent Analysis
Authors: Bailing Zhang, Minyue Fu, Hong Yan
Venue: Neural Processing Letters (1998)

Mixture of local principal component analysis (PCA) has attracted attention due to a number of benefits over global PCA. The performance of a mixture model usually depends on the data partition and local linear fitting. In this paper, we propose a mixture model which has the properties of optimal data partition and robust local fitting. Data partition is realized by a soft competition algorithm called neural &rsquo;gas&lsquo; and robust local linear fitting is approached by a nonlinear extension of PCA learning algorithm. Based on this mixture model, we describe a modular classification scheme for handwritten digit recognition, in which each module or network models the manifold of one of ten digit classes. Experiments demonstrate a very high recognition rate.
Filtering for Texture Classification: A Comparative Study
Authors: Trygve Randen, John Hå Husøy
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (1999)

In this paper, we review most major filtering approaches to texture feature extraction and perform a comparative study. Filtering approaches included are Laws masks, ring/wedge filters, dyadic Gabor filter banks, wavelet transforms, wavelet packets and wavelet frames, quadrature mirror filters, discrete cosine transform, eigenfilters, optimized Gabor filters, linear predictors, and optimized finite impulse response filters. The features are computed as the local energy of the filter responses. The effect of the filtering is highlighted, keeping the local energy function and the classification algorithm identical for most approaches. For reference, comparisons with two classical nonfiltering approaches, co-occurrence (statistical) and autoregressive (model based) features, are given. We present a ranking of the tested approaches based on extensive experiments.
A speech interface for building musical score collections
Authors: Lloyd A. Smith, Eline F. Chiu, Brian L. Scott
Venue: Proceedings of the fifth ACM conference on Digital libraries (2000)

Building machine readable collections of musical scores is a tedious and time consuming task. The most common interface for performing music data entry is a mouse and toolbar system; using the mouse, the user selects a rhythm (note shape) from a toolbar, then drags the note to the correct position on the staff. We compare the usability of a hybrid speech and mouse-driven interface to a traditional mouse-driven one. The speech-enhanced interface allows users to enter note rhythms by voice, while still using the mouse to indicate pitches. While task completion time is nearly the same, users (N=13) significantly preferred the speech-augmented interface. A second study using the first two authors of this paper (N=2) indicates that experienced users can enter music 11% faster with the speech interface. Many users expressed a desire to enter pitches, as well as rhythms, by speech. A third study, however, shows that the recognizer is unable to reliably distinguish among A, B, C, D, E, F and G (N=10).
Building quality into a digital library
Authors: Hussein Suleman, Edward A. Fox, Marc Abrams
Venue: Proceedings of the fifth ACM conference on Digital libraries (2000)

The Web Characterization Repository contains a collection of internet log files used by researchers to analyze and improve on the architecture of the Web. This repository improves on prior collections by thoroughly testing the log files for format to assure a degree of data quality. Instituting quality control into the digital library addressed many complex issues including technical support for quality assessment, the definition of a workflow to achieve quality control, the assignment of tasks to different people and the definition and automation of quality assessment for log files. By reaching realistic compromises on these issues it was possible to build quality control as an integral part of the digital library.
The Parametrized Complexity of Some Fundamental Problems in Coding Theory
Authors: Rod G. Downey, Michael R. Fellows, Alexander Vardy, Geoff Whittle
Venue: SIAM Journal on Computing (1999)

The parametrized complexity of a number of fundamental problems in the theory of linear codes and integer lattices is explored. Concerning codes, the main results are that MAXIMUM-LIKELIHOOD DECODING and WEIGHT DISTRUBUTION are hard for the parametrized complexity class W[1]. The NP-completeness of these two problems was established by Berlekamp, McEliece, and van Tilborg in 1978 using by means of a reduction from THREE-DIMENSIONAL MATCHING. On the other hand, our proof of hardness for W[1] is based on a parametric polynomial-time transformation from PERFECT CODE in graphs. An immediate consequence of our results is that bounded-distance decoding is likely to be hard for binary linear codes. Concerning lattices, we address the THETA SERIES problem of determining for an integer lattice $\L$ %given by a set of generators, and a positive integer k whether there is a vector $x \in \L$ of Euclidean norm k. We prove here for the first time that THETA SERIES is NP-complete and show that it is also hard for W[1]. Furthermore, we prove that the NEAREST VECTOR problem for integer lattices is hard for W[1]. These problems are the counterparts of WEIGHT DISTRUBUTION and MAXIMUM-LIKELIHOOD DECODING for lattices. Relations between all these problems and combinatorial problems in graphs are discussed.
Removing Noise and Preserving Details with Relaxed Median Filters
Authors: Abdessamad Ben Hamza, Pedro L. Luque-Escamilla, José Martínez-Aroza, Ramón Román-Roldán
Venue: Journal of Mathematical Imaging and Vision (1999)

In this paper, a median based filter called relaxed median filter is proposed. The filter is obtained by relaxing the order statistic for pixel substitution. Noise attenuation properties as well as edge and line preservation are analyzed statistically. The trade-off between noise elimination and detail preservation is widely analyzed. It is shown that relaxed median filters preserve details better than the standard median filter, and remove noise better than other median type filters.