ppxscal/embedding_network huggingface dataset:
Embedded Java (embedded tutorial) (abstract only): techniques and applications
Authors: Brian Barry, John Duimovich
Venue: Proceedings of the 1999 IEEE/ACM international conference on Computer-aided design (1999)

Java is an ideal language for developing embedded applications. However, most Java implementations and tools were designed for workstations and have limitations due to that heritage. Special tools are required to support deployment and effect better integration with target hardware. This talk will be in two parts. The first part will provide an overview of pervasive computing with a special focus on embedded Java, and described typical applications drawn from several different market segments. The second half will delve more deeply into the architecture of an embedded Java runtime and discuss technical issues relating to dynamic compilation, optimization, and deployment.
A Matroid-Theoretic Solution to an Assignment Problem in the Conformance Testing of Communication Protocols
Authors: T. Ramalingom, Krishnaiyan Thulasiraman, Anindya Das
Venue: IEEE Transactions on Computers (2000)

The minimum length test sequence generation method proposed in [2] for conformance testing of a protocol uses Unique Input Sequences (UIS) for state identification. This method, called the U-method, requires that the test graph, a graph derived from the protocol, be connected. This requirement also needs to be satisfied in the case of the MU-method [31], [30], which assumes that the multiple UISs are available for each state. Thus, the U-method and the MU-method may not provide minimum length test sequences in cases where the test graph is not connected. Nevertheless, these methods generate minimum length test sequences with high fault coverage whenever the test graph is connected. This raises an important problem: Does there exist an assignment of UISs to the transitions such that the resulting test graph is connected? In this paper, we formulate this problem as a maximum cardinality two matroid intersection problem and discuss an efficient algorithmic solution. We also point out the role of the work in the minimum length test sequence generation problem.
Partial Reset Methodology and Experiments for Improving Random-Pattern Testability and BIST of Sequential Circuits
Authors: Huy Nguyen, Rabindra Roy, Abhijit Chatterjee
Venue: Journal of Electronic Testing: Theory and Applications (1999)

Partial reset has been shown to have significant impact on test generation for sequential circuits in a stored-pattern test application environment. In this paper, we explore the use of partial reset in fault-independent testing and built-in self-test (BIST) of non-scan sequential circuits. We select a subset of flip-flops in the circuit to be resetable to logic one or zero during the application of the test vectors. The resetting is performed with random frequency. The selection of the flip-flops and the reset polarity is based on fault-propagation analysis, which determines the impact of a selected flip-flop on fault propagation from the circuits structure. Application of partial reset as described above yields an average improvement of 15% in fault-coverage for sequential circuits resistant to random pattern testing. To further enhance testability, we also present a methodology for selecting observable test points based on propagation of switching activity. Overall, high fault coverages (about 97%) are obtained for many of the ISCAS89 benchmark circuits. Thus, partial reset BIST provides a low cost alternative for testing sequential circuits when scan design is unacceptable due to area and/or delay constraints. The routing overhead for implementing BIST is seen to be about 6%.
Stochastic Linear Quadratic Regulators with Indefinite Control Weight Costs
Authors: Shuping Chen, Xunjing Li, Xun Yu Zhou
Venue: SIAM Journal on Control and Optimization (1998)

This paper considers optimal (minimizing) control of stochastic linear quadratic regulators (LQRs). The assumption that the control weight costs must be positive definite, inherited from the deterministic case, has been taken for granted in the literature. It is, however, shown in this paper that some stochastic LQR problems with indefinite (in particular, negative) control weight costs may still be sensible and well-posed due to the deep nature of stochastic systems. New stochastic Riccati equations, which are backward stochastic differential equations involving complicated nonlinear terms, are presented and their solvability is proved to be sufficient for the well-posedness and the solutions of the optimal LQR problems. Existence and uniqueness of solutions to the Riccati equation for a special case are obtained. Finally, it is argued that, quite contrary to the deterministic systems, the stochastic maximum principle cannot fully characterize the optimality of the stochastic LQR problems.
Examining workgroup influence on technology usage: a community of practice perspective
Authors: Michael J. Gallivan
Venue: Proceedings of the 2000 ACM SIGCPR conference on Computer personnel research (2000)

This paper develops a new theoretical model with which to examine the factors that determine employees' technology usage within organizational settings. Much of the prior IS training literature has assumed an underlying relationship between necessary conditions for technology adoption &mdash; such as user training and support resources &mdash; and actual technology use. Whereas these &ldquo;facilitating conditions&rdquo; for technology usage [38, 80, 81] have been taken for granted as factors that influence system adoption and usage, the reality of learning and working in organizational settings suggests an entirely different mode of influence on employees' technology-related behavior. Drawing from research in cognitive anthropology [35], and acknowledging the role of communities of practice that shape learning, behavior, and memory [5, 65, 87, 88], we develop an alternative theoretical framework to explain employees' adoption of technology and their degree of system usage. Contrasting this novel theoretical framework with traditional notions that presume technology usage to be directly related to the amount or perceived quality of user training and support, we evaluate both frameworks with empirical data obtained from a technology implementation initiative across five sites of one nonprofit organization. While both theories receive some support from our data, we argue for the recognition that social influences exert an effect not just on whether employees adopt IT [77], but more importantly on how and how much employees use technology for their jobs. Implications for research and practice related to IT training are provided, as well as to more general lessons for managing technology implementation.
A Distributed Deadlock Resolution Algorithm for the AND Model
Authors: José Ramón González de Mendívil, Federico Fariña, José Ramó Garitagoitia, Carlos F. Alastruey, J. M. Bernabeu-Auban
Venue: IEEE Transactions on Parallel and Distributed Systems (1999)

Previous proposals for Distributed Deadlock Detection/Resolution algorithms for the AND model have the main disadvantage of resolving false deadlocks, that is, nonexisting or currently being resolved deadlocks. This paper provides an algorithm free of false deadlock resolutions. A simple specification for a safe deadlock resolution algorithm is introduced, and the new distributed solution is developed in a hierarchical fashion from its abstract specification. The algorithm is probe-based, uses node priorities, and coordinates the actions of resolvers so that false deadlocks are not resolved. The solution is formally proven correct by using the Input-Output Automata Model. Finally, a study about the liveness of the algorithm is provided.
On the Sample Complexity for Nonoverlapping Neural Networks
Authors: Michael Schmitt
Venue: Machine Learning (1999)

A neural network is said to be nonoverlapping if there is at most one edge outgoing from each node. We investigate the number of examples that a learning algorithm needs when using nonoverlapping neural networks as hypotheses. We derive bounds for this sample complexity in terms of the Vapnik-Chervonenkis dimension. In particular, we consider networks consisting of threshold, sigmoidal and linear gates. We show that the class of nonoverlapping threshold networks and the class of nonoverlapping sigmoidal networks on n inputs both have Vapnik-Chervonenkis dimension &Omega;(nlog n). This bound is asymptotically tight for the class of nonoverlapping threshold networks. We also present an upper bound for this class where the constants involved are considerably smaller than in a previous calculation. Finally, we argue that the Vapnik-Chervonenkis dimension of nonoverlapping threshold or sigmoidal networks cannot become larger by allowing the nodes to compute linear functions. This sheds some light on a recent result that exhibited neural networks with quadratic Vapnik-Chervonenkis dimension.
Rankings of Directed Graphs
Authors: Jan Kratochvíl, Zsolt Tuza
Venue: SIAM Journal on Discrete Mathematics (1999)

A ranking of a graph is a coloring of the vertex set with positive integers in such a way that on every path connecting two vertices of the same color there is a vertex of larger color. We consider the directed variant of this problem, where the above condition is imposed only on those paths in which all edges are oriented consecutively. We show that the ranking number of an orientation of a tree is bounded by that of its longest directed path plus one, and that it can be computed in polynomial time. Unlike the undirected case, however, deciding whether the ranking number of a directed (and even of an acyclic directed) graph is bounded by a constant is NP-complete. In fact, the 3-ranking of planar bipartite acyclic digraphs is already hard.
Iterative Solution of the Helmholtz Equation by a Second-Order Method
Authors: Kurt Otto, Elisabeth Larsson
Venue: SIAM Journal on Matrix Analysis and Applications (1999)

The numerical solution of the Helmholtz equation subject to nonlocal radiation boundary conditions is studied. The specific problem is the propagation of hydroacoustic waves in a two-dimensional curvilinear duct. The problem is discretized with a second-order accurate finite difference method, resulting in a linear system of equations. To solve the system of equations, a preconditioned Krylov subspace method is employed. We construct a preconditioner that is based on fast transforms and yields a direct fast Helmholtz solver for rectangular domains. Numerical experiments for curved ducts demonstrate that the rate of convergence is high. The fast transform preconditioner is compared with a symmetric successive over-relaxation (SSOR) preconditioner, and also with band Gaussian elimination. For the preconditioned iterative methods, the gains in storage requirement are large compared with band Gaussian elimination. Regarding the arithmetic complexity, the fast transform preconditioner yields a significant gain, whereas the SSOR preconditioner performs worse than band Gaussian elimination.
SAT based ATPG using fast justification and propagation in the implication graph
Authors: Paul Tafertshofer, Andreas Ganz
Venue: Proceedings of the 1999 IEEE/ACM international conference on Computer-aided design (1999)

In this paper we present new methods for fast justification and propagation in the implication graph (IG) which is the core data structure of our SAT based implication engine. As the IG model represents all information on the implemented logic function as well as the topology of a circuit, the proposed techniques inherit all advantages of both general SAT based and structure based approaches to justification, propagation, and implication. These three fundamental Boolean problems are the main tasks to be performed during Automatic Test Pattern Generation (ATPG) such that the proposed algorithms are incorporated into our ATPG tool TIP which is built on top of the implication engine.Working exclusively in the IG, the complex functional operations of justification, propagation, and implication reduce to significantly simpler graph algorithms. They are easily extended to exploit bit-parallel techniques. As the IG is automatically generated for arbitrary logics the algorithms remain applicable independent of the required logic. This allows processing of various fault models using the same engine. That is, the presented IG based methods offer a complete and versatile framework for rapid development of new ATPG tools that target emerging fault models such as cross-talk, delay or bridging faults. TIP currently handles stuck-at as well as various delay fault models. Furthermore, the proposed methods are used within tools for Boolean equivalence checking, optimization of netlists, timing analysis or retiming (reset state computation).In order to demonstrate the performance of IG based ATPG, i.e. justification and propagation in the IG, we provide experimental results for stuck-at and path delay fault models. They show that TIP outperforms the state-of-the-art in SAT based and structure based ATPG.
Class prediction and discovery using gene expression data
Authors: Donna K. Slonim, Pablo Tamayo, Jill P. Mesirov, Todd R. Golub, Eric S. Lander
Venue: Proceedings of the fourth annual international conference on Computational molecular biology (2000)

Classification of patient samples is a crucial aspect of cancer diagnosis and treatment. We present a method for classifying samples by computational analysis of gene expression data. We consider the classification problem in two parts: class discovery and class prediction. Class discovery refers to the process of dividing samples into reproducible classes that have similar behavior or properties, while class prediction places new samples into already known classes. We describe a method for performing class prediction and illustrate its strength by correctly classifying bone marrow and blood samples from acute leukemia patients. We also describe how to use our predictor to validate newly discovered classes, and we demonstrate how this technique could have discovered the key distinctions among leukemias if they were not already known. This proof-of-concept experiment paves the way for a wealth of future work on the molecular classification and understanding of disease.
On a theory of computing symposia
Authors: Avrim Blum, Prabhakar Raghavan
Venue: ACM SIGACT News (1998)

We consider the problem of scheduling a conference to achieve the benefits in time-compression of parallel sessions, but without the associated high degree of conflict between talks. We describe a randomized construction meeting these goals that we analyze based on an expansion property of an associated graph. We also give algorithms for attendees scheduling their time within such a conference, and algorithms for verifying a proposed conference schedule. Finally, we present simulation results for typical conference sizes.
Multiresolution Based on Weighted Averages of the Hat Function II: Nonlinear Reconstruction Techniques
Authors: Francesc Aràndiga, Rosa Donat, Ami Harten
Venue: SIAM Journal on Scientific Computing (1999)

In this paper we describe and analyze a class of nonlinear \mr schemes for the multiresolution setting which corresponds to discretization by local averages with respect to the hat function. These schemes are based on the essentially-non-oscillatory (ENO) interpolatory procedure described in [A. Harten, B. Engquist, S. Osher, and S. Chakravarthy, J. Comput. Phys., 71 (1987), pp. 231--302]. We show that by allowing the approximation to fit the local nature of the data, one can improve the compression capabilities of the multiresolution algorithms. The question of stability for nonlinear (data-dependent) reconstruction techniques is also addressed.
Overview of clinical trials with MIT-MANUS: a robot-aided neuro-rehabilitation facility
Authors: H. I. Krebs, N. Hogan, B. T. Volpe, M. L. Aisen, C. Diels
Venue: Technology and Health Care (1999)

We are applying robotics and information technology to assist, enhance, and quantify neuro-rehabilitation. Our goal is a new class of interactive, user-affectionate clinical devices designed not only for evaluating patients, but also for delivering meaningful therapy via engaging "video games". Notably, the novel robot MIT-MANUS has been designed and programmed for clinical neurological applications, and has undergone extensive clinical trials for more than four years at Burke Rehabilitation Hospital - White Plains, NY. This paper will review results of the first clinical trial of 20 patients, which showed that: Stroke patients treated daily with additional robot-aided therapy during acute rehabilitation had improved outcome in motor activity at hospital discharge, when compared to a control group that received only standard acute rehabilitation treatment. This improved outcome was sustained after three years. The neuro-recovery process continued far beyond the commonly accepted 3 months post-stroke interval.
Algorithm 792: accuracy test of ACM algorithms for interpolation of scattered data in the plane
Authors: Robert J. Renka, Ron Brown
Venue: ACM Transactions on Mathematical Software (TOMS) (1999)

We present results of accuracy tests on scattered-data fitting methods that have been published as ACM algorithms. The algorithms include seven triangulation-based methods and three modified Shepard methods, two of which are new algorithms. Our purpose is twofold: to guide potential users in the selection of an appropriate algorithm and to provide a test suite for assessing the accuracy of new methods (or existing methods that are not included in this survey). Our test suite consists of five sets of nodes, with nodes counts ranging from 25 to 100, and 10 test functions. These are made available in the form of three Fortran subroutines: TESTDT returns one of the node sets; TSTFN1 returns a value and, optionally, a gradient value, of one of the test funciton; and TSTFN2 returns a value, first partials, and second partial derivatives of one of the test functions.
Determining Generative Models of Objects Under Varying Illumination: Shape and Albedo from Multiple Images Using SVDand Integrability
Authors: A. L. Yuille, D. Snow, R. Epstein, P. N. Belhumeur
Venue: International Journal of Computer Vision (1999)

We describe a method of learning generative models of objects from a set of images of the object under different, and unknown, illumination. Such a model allows us to approximate the objects&lsquo; appearance under a range of lighting conditions. This work is closely related to photometric stereo with unknown light sources and, in particular, to the use of Singular Value Decomposition (SVD) to estimate shape and albedo from multiple images up to a linear transformation (Hayakawa, 1994). Firstly we analyze and extend the SVD approach to this problem. We demonstrate that it applies to objects for which the dominant imaging effects are Lambertian reflectance with a distant light source and a background ambient term. To determine that this is a reasonable approximation we calculate the eigenvectors of the SVD on a set of real objects, under varying lighting conditions, and demonstrate that the first few eigenvectors account for most of the data in agreement with our predictions. We then analyze the linear ambiguities in the SVD approach and demonstrate that previous methods proposed to resolve them (Hayakawa, 1994) are only valid under certain conditions. We discuss alternative possibilities and, in particular, demonstrate that knowledge of the object class is sufficient to resolve this problem. Secondly, we describe the use of surface consistency for putting constraints on the possible solutions. We prove that this constraint reduces the ambiguities to a subspace called the generalized bas relief ambiguity (GBR) which is inherent in the Lambertian reflectance function (and which can be shown to exist even if attached and cast shadows are present (Belhumeur et al., 1997)). We demonstrate the use of surface consistency to solve for the shape and albedo up to a GBR and describe, and implement, a variety of additional assumptions to resolve the GBR. Thirdly, we demonstrate an iterative algorithm that can detect and remove some attached shadows from the objects thereby increasing the accuracy of the reconstructed shape and albedo.
The Cornell Jaguar project: adding mobility to PREDATOR
Authors: Phillippe Bonnet, Kyle Buza, Zhiyuan Chan, Victor Cheng, Randolph Chung, Takako Hickey, Ryan Kennedy, Daniel Mahashin, Tobias Mayr, Ivan Oprencak, Praveen Seshadri, Hubert Siu
Venue: ACM SIGMOD Record (1999)

The Cornell Jaguar Project is exploring a variety of issues related to mobility and query processing. One broad theme is to break down the traditional client and server boundaries, leading to ubiquitous query processing. Another theme is to extend database and query processing techniques to small-scale and mobile devices. The project builds on and extends the Cornell PREDATOR database engine.
Growth and server availability of the NCSTRL digital library
Authors: Allison L. Powell, James C. French
Venue: Proceedings of the fifth ACM conference on Digital libraries (2000)

This paper reports on measurements of the NCSTRL digital library taken over a two-year period. We report the growth of the system along two dimensions: number of participating institutions and number of documents indexed by the system. We also report an aspect of reliability for this distributed digital library system.
Declarative peephole optimization using string pattern matching
Authors: Diomidis Spinellis
Venue: ACM SIGPLAN Notices (1999)

Peephole optimisation as a last step of a compilation sequence capitalises on significant opportunities for removing low level code slackness left over by the code generation process. We have designed a peephole optimiser that operates using a declarative specification of the optimisations to be performed. The optimiser's implementation is based on string pattern matching using regular expressions. We used this approach to prototype an optimiser to convert target machine instruction sequences containing conditional execution of instructions inside loop bodies into code that adaptively executes the optimum branch instructions according to the program's branch behaviour.
Report on a workshop on software change and evolution
Authors: V. T. Rajlich, S. Rank, N. Wilde, K. H. Bennett
Venue: ACM SIGSOFT Software Engineering Notes (2000)

This paper provides a brief overview and report on the main out-comes of the software change and evolution (SCE99) workshop held in Los Angeles on May 17, 1999, as part of the International Conference on Software Engineering 1999.The purpose of the workshop was to gather the most active of researchers and practitioners in the field of software evolution and change. The overall conclusion of the workshop was that this is a topic of enormous importance to industry, and there is a growing community of both practitioners and researchers who are working in the field. It would therefore make sense to arrange further workshops to support this expanding community.
Low-power digital filtering using multiple voltage distribution and adaptive voltage scaling (poster session)
Authors: Sandeep Dhar, Dragan Maksimović
Venue: Proceedings of the 2000 international symposium on Low power electronics and design (2000)

This paper describes an adaptive power management architecture to reduce power consumption in digital filters. The proposed approach combines two low-power techniques which utilize supply voltage reduction. The first technique, multiple voltage distribution (MVD), attempts to reduce power consumption by assigning reduced supply voltages to circuit modules while satisfying timing constraints. The second technique, adaptive voltage scaling (AVS), dynamically adjusts these multiple voltages to meet throughput requirements resulting in further power reduction. An FIR filter application using the combined MVD-AVS power management scheme for two adaptively scaled supply voltages is shown to consume one-third the power of a fixed supply voltage scheme, and half the power consumed with a single supply AVS.