ppxscal/embedding_network huggingface dataset:
Adapting to the user's internet search strategy on small devices
Authors: Jean-David Ruvini
Venue: Proceedings of the 8th international conference on Intelligent user interfaces (2003)

World Wide Web search engines typically return thousands of results to the users. To avoid users browsing through the whole list of results, search engines use ranking algorithms to order the list according to predefined criteria. In this paper, we present Toogle, a front-end to the Google search engine for mobile phones offering web browsing. For a given search query, Toogle first ranks results using Googles algorithm and, as the user browses through the result list, uses machine learning techniques to infer a model of her search goal and to adapt accordingly the order in which yet-unseen results are presented. We report preliminary experimental results that show the effectiveness of this approach
Federated Search of Scientific Literature
Authors: Bruce Schatz, William Mischo, Timothy Cole, Ann Bishop, Susan Harum, Eric Johnson, Laura Neumann, Hsinchun Chen, Dorbin Ng
Venue: Computer (1999)

The Internet of the 21st century will radically transform how we interact with knowledge. The rise of the World Wide Web and the information infrastructure have rapidly developed the technologies of collections for independent communities. In the future, online information will be dominated by small collections. The information infrastructure must similarly be radically different to support indexing of community collections and searching across such small collections. Users will consider themselves to be navigating in the Interspace, across logical spaces of semantic indexes, rather than in the Internet, across physical networks of computer servers. The Digital Libraries Initiative (DLI) project at the University of Illinois at Urbana-Champaign (UIUC) was one of six sponsored by the NSF, DARPA, and NASA from 1994 through 1998. The goal: develop widely usable Web technology to effectively search technical documents on the Internet. This article details their efforts.
Performances of novel Pd/Sn and Pd/Sn/Au ohmic metallizations to n-GaAs
Authors: M. S. Islam, M. Q. Huda, A. H. M. Zahirul Alam, Patrick J. McNally
Venue: Microelectronic Engineering (2002)

Performance of novel Pd/Sn and Pd/Sn/Au Ohmic metallizations to n-GaAs have been investigated. Metallizations were deposited using a resistance heating evaporator and annealings were performed utilizing a conventional graphite strip annealer (cGSA). Metallization samples were characterized using scanning tunneling microscopy (STM), secondary ion mass spectrometry (SIMS) and current-voltage (I-V) measurements. Contact resistivities, ρc, of the metallizations were measured utilizing conventional transmission line model (cTLM) method. Novel Pd/Sn and Pd/Sn/Au Ohmic contacts exhibit better thermal stability compared to nonalloyed Pd/Ge metallization. In order to investigate the effectiveness of novel Pd/Sn and Pd/Sn/Au Ohmic metallizations in device applications, gallium arsenide metal-semiconductor field-effect transistors (GaAs MESFETs) have been fabricated. MESFETs fabricated with Pd/Sn/Au Ohmic contacts show a extrinsic transconductance, gme, of more than 133 mS/mm for a gate length, LG, of 2 µm.
The Morphological Structure of Images: The Differential Equations of Morphological Scale-Space
Authors: R. van den Boomgaard, A. Smeulders
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (1994)

We introduce a class of nonlinear differential equations that are solved using morphological operations. The erosion and dilation act as morphological propagators propagating the initial condition into the "scale-space", much like the Gaussian convolution is the propagator for the linear diffusion equation. The analysis starts in the set domain, resulting in the description of erosions and dilations in terms of contour propagation. We show that the structuring elements to be used must have the property that at each point of the contour there is a well-defined and unique normal vector. Then given the normal at a point of the dilated contour we can find the corresponding point (point-of-contact) on the original contour. In some situations we can even link the normal of the dilated contour with the normal in the point-of-contact of the original contour. The results of the set domain are then generalized to grey value images. The role of the normal is replaced with the function gradient. The same analysis also holds for the erosion. Using a family of increasingly larger structuring functions we are then able to link infinitesimal changes in grey value with the gradient in the image.
HubLocator: an exact solution method for the multiple allocation hub location problem
Authors: Gabriela Mayer, Bernd Wagner
Venue: Computers and Operations Research (2002)

HubLocator is a new branch-and-bound procedure for the uncapacitated multiple allocation hub location problem. An existing optimal method developed by Klincewicz (Location Sci. 4 (1996) 173) is based on dual ascent and dual adjustment techniques applied to a disaggregated model formulation. These techniques have already successfully been used to solve the closely related simple plant location problem. However, due to the specific structure of the problem at hand, the success of these techniques in reducing the computational effort is rather restricted. Therefore, HubLocator additionally considers an aggregated model formulation enabling us to significantly tighten the lower bounds. Upper bounds which satisfy complementary slackness conditions for some constraints are constructed and improved by means of a simple heuristic procedure. Computational experiments demonstrate that optimal solutions for problems with up to 40 nodes can be found in a reasonable amount of time.
On Hardware for Computing Exponential and Trigonometric Functions
Authors: Vitit Kantabutra
Venue: IEEE Transactions on Computers (1996)

This paper presents new, fast hardware for computing the exponential function, sine, and cosine. The main new idea is to use low-precision arithmetic components to approximate high precision computations, and then to correct very quickly the approximation error periodically so that the effect is to get high precision computation at near low-precision speed. The algorithm used in the paper is a nontrivial modification of the well-known CORDIC algorithm, and might be applicable to the computation of other functions than the ones presented.
Scheduling for Reactive Real-Time Systems
Authors: Pai Chou, Elizabeth A. Walkup, Gaetano Borriello
Venue: IEEE Micro (1994)

In designing Chinook, a hardware-software cosynthesis system for reactive real-time controllers, the impact of timing constraints on software scheduling has been a central concern. By dividing constraints into two levels, corresponding to low-level interactions with device interfaces and high-level real-time response and rate requirements, we have developed solutions tailored to each aspect. These scheduling techniques enable Chinook to map a high-level specification onto a specified collection of processors and peripheral devices while respecting performance requirements.
Reconstructing infinite objects
Authors: Dieter Rautenbach
Venue: Discrete Mathematics (2002)

We generalize an algebraic tool due to Alon et al. (J. Combin. Theory B 47 (1989) 153-161) for the reconstruction of finite objects to infinite objects. We apply our result to the reconstruction of infinite sets of points in the space Rn with respect to two different groups of automorphisms of Rn.
Virtual temporal bone dissection: a case study
Authors: Jason Bryan, Don Stredney, Greg Wiet, Dennis Sessanna
Venue: Proceedings of the conference on Visualization '01 (2001)

The Temporal Bone Dissection Simulator is an ongoing research project for the construction of a synthetic environment suitable for virtual dissection of human temporal bone and related anatomy. Funded by the National Institute on Deafness and Other Communication Disorders (NIDCD), the primary goal of this project is to provide a safe, robust, and cost-effective virtual environment for learning the anatomy and surgical procedures associated with the temporal bone. Direct volume visualization has been indispensable for the necessary level of realism and interactivity that is vital to the success of this project. This work is being conducted by the Ohio Supercomputer Center in conjunction with the Department of Otolaryngology at the Ohio State University, and NIDCD.
Generalized Multiprocessor Scheduling and Applications to Matrix Computations
Authors: G. N. Srinivasa Prasanna, B. R. Musicus
Venue: IEEE Transactions on Parallel and Distributed Systems (1996)

This paper considerably extends the multiprocessor scheduling techniques in [1], [2], and applies it to matrix arithmetic compilation. In [1], [2] we presented several new results in the theory of homogeneous multiprocessor scheduling. A directed acyclic graph (DAG) of tasks is to be scheduled. Tasks are assumed to be parallelizable¿as more processors are applied to a task, the time taken to compute it decreases, yielding some speedup. Because of communication, synchronization, and task scheduling overhead, this speedup increases less than linearly with the number of processors applied. The optimal scheduling problem is to determine the number of processors assigned to each task, and task sequencing, to minimize the finishing time.Using optimal control theory, in the special case where the speedup function of each task is p¿, where p is the amount of processing power applied to the task, a closed form solution for task graphs formed from parallel and series connections was derived [1], [2]. This paper extends these results for arbitrary DAGS. The optimality conditions impose nonlinear constraints on the flow of processing power from predecessors to successors, and on the finishing times of siblings. This paper presents a fast algorithm for determining and solving these nonlinear equations. The algorithm utilizes the structure of the finishing time equations to efficiently run a conjugate gradient minimization, leading to the optimal solution.The algorithm has been tested on a variety of DAGs commonly encountered in matrix arithmetic. The results show that if the p¿ speedup assumption holds, the schedules produced are superior to heuristic approaches. The algorithm has been applied to compiling matrix arithmetic [9], for the MIT Alewife machine, a distributed-shared memory multiprocessor. While matrix arithmetic tasks do not exactly satisfy the p¿ speedup assumptions, the algorithm can be applied as a good heuristic. The results show that the schedules produced by our algorithm are faster than alternative heuristic techniques.
Will Physical Scalability Sabotage Performance Gains?
Authors: Doug Matzke
Venue: Computer (1997)

The most important physical trend facing chip architects is the fact that on-chip wires are becoming much slower relative to logic as the on-chip devices shrink. The author points out that it will soon be impossible to maintain one global clock over the entire chip, and sending signals across a billion-transistor processor may require as many as 20 cycles.
On Two Applications of H-Differentiability to Optimization and Complementarity Problems
Authors: M. A. Tawhid, M. Seetharama Gowda
Venue: Computational Optimization and Applications (2000)

In a recent paper, Gowda and Ravindran (Algebraic univalence theorems for nonsmooth functions, Research Report, Department of Mathematics and Statistics, University of Maryland, Baltimore, MD 21250, March 15, 1998) introduced the concepts of H-differentiability and H-differential for a function f : Rn &rarr; Rn and showed that the Fr&eacute;chet derivative of a Fr&eacute;chet differentiable function, the Clarke generalized Jacobian of a locally Lipschitzian function, the Bouligand subdifferential of a semismooth function, and the C-differential of a C-differentiable function are particular instances of H-differentials.In this paper, we consider two applications of H-differentiability. In the first application, we derive a necessary optimality condition for a local minimum of an H-differentiable function. In the second application, we consider a nonlinear complementarity problem corresponding to an H-differentiable function f and show how, under appropriate conditions on an H-differential of f, minimizing a merit function corresponding to f leads to a solution of the nonlinear complementarity problem. These two applications were motivated by numerous studies carried out for C1, convex, locally Lipschitzian, and semismooth function by various researchers.
Debiasing Training Data for Inductive Expert System Construction
Authors: Vijay S. Mookerjee
Venue: IEEE Transactions on Knowledge and Data Engineering (2001)

We study the presence of economic bias in the training data used to develop inductive expert systems. Such bias arises when an expert considers economic factors in decision making. We find that the presence of economic bias is particularly harmful when there is an economic misalignment between the expert and the user of the induced expert system. Such misalignment is referred to as differential bias. The most significant contribution of this study is a training data debiasing procedure that uses a genetic algorithm to reconstruct training data that is relatively free of economic bias. We conduct a series of simulation experiments that show: 1) the economic performance of accuracy and value seeking algorithms is statistically the same when the training data has economic bias, 2) both accuracy and value seeking algorithms suffer in the presence of differential bias, 3) the proposed debiasing procedure significantly combats differential bias, and 4) the debiasing procedure is quite robust with respect to estimation errors in its input parameters.
Generation of Electrically Induced Stimuli for MEMS Self-Test
Authors: Benoît Charlot, Salvador Mir, Fabien Parrain, Bernard Courtois
Venue: Journal of Electronic Testing: Theory and Applications (2001)

A major task for the implementation of Built-In-Self-Test (BIST) strategies for MEMS is the generation of the test stimuli. These devices can work in different energy domains and are thus designed to sense signals which are generally not electrical. In this work, we describe, for different types of MEMS, how the required non-electrical test stimuli can be induced on-chip by means of electrical signals. This provides the basis for adding BIST strategies for MEMS parts embedded in the coming generation of integrated systems. The on-chip test signal generation is illustrated for the case of MEMS transducers which exploit such physical principles as time-varying electrostatic capacitance, piezo-resistivity effect and Seebeck effect. These principles are used in devices such as accelerometers, infrared imagers, pressure sensors or tactile sensors. For implementation, we have used two major MEMS technologies including CMOS-compatible bulk micromachining and surface micromachining. We illustrate the ability to generate on-chip test stimuli and to implement a self-test strategy for the case of a complete application. This corresponds to an infrared imager that can be used in multiple applications such as overheating detection, night vision, and earth tracking for satellite positioning. The imager consists of an array of thermal pixels that sense an infrared radiation. Each pixel is implemented as a suspended membrane that contains several thermopiles along the different support arms. The on-chip test signal generation proposed requires only slight modifications and allows a production test of the imager with a standard test equipment, without the need of special infrared sources and the associated optical equipment. The test function can also be activated off-line in the field for validation and maintenance purposes.
Inductive Learning for Risk Classification
Authors: Michael J. Shaw, James A. Gentry
Venue: IEEE Expert: Intelligent Systems and Their Applications (1990)

The authors discuss the application of inductive learning to credit risk analysis. Three risk classification problems are addressed: business loan evaluation, bond rating, and bankruptcy prediction. The use of a system called Marble, a knowledge-based decision-support system that uses approximately 80 decision rules to evaluate commercial loans, is discussed. In particular, an aspect of Marble that uses inductive learning to classify financial risks is described, and the effectiveness of the technique is discussed.
Chain-Split Evaluation in Deductive Databases
Authors: Jiawei Han
Venue: IEEE Transactions on Knowledge and Data Engineering (1995)

Many popularly studied recursions in deductive databases can be compiled into one or a set of highly regular chain generating paths, each of which consists of one or a set of connected predicates. Previous studies on chain-based query evaluation in deductive databases take a chain generating path as an inseparable unit in the evaluation. However, some recursions, especially many functional recursions whose compiled chain consists of infinitely evaluable function(s), should be evaluated by chain-split evaluation, which splits a chain generating path into two portions in the evaluation: an immediately evaluable portion and a delayed-evaluation portion. In this paper, the necessity of chain-split evaluation is examined from the points of view of both efficiency and finite evaluation, and three chain-split evaluation techniques: magic sets, buffered evaluation, and partial evaluation are developed. Our study shows that chain-split evaluation is a primitive recursive query evaluation technique for different kinds of recursions, and it can be implemented efficiently in deductive databases by extensions to the existing recursive query evaluation methods.
Biorthogonal vector sequence transformations and Pad&#x00E9; approximation of vector series
Authors: C. Brezinski
Venue: Applied Numerical Mathematics (2002)

The aim of this paper is to provide a quite general framework for vector sequence transformations. The methodology presented covers other strategies for deriving such transformations. When applied to the partial sums of a formal power series with vector coefficients, these transformations lead to rational approximations in the Padé style.
Deferred Correction Methods for Initial Boundary Value Problems
Authors: Wendy Kress, Bertil Gustafsson
Venue: Journal of Scientific Computing (2002)

In this paper, we consider the deferred correction principle for initial boundary value problems. The method will here be applied to the discretization in time. We obtain a method of even order p by applying the implicit midpoint rule p/2 times in each time step. For the space discretization we will use a compact implicit difference scheme. We derive error estimates for the case of time dependent coefficients and present numerical experiments confirming the theoretical analysis.
A New Approach for the Performance Analysis of a Single-Bus Multiprocessor System with General Service Times
Authors: A. van de Liefvoort, N. Subramanian
Venue: IEEE Transactions on Computers (1993)

The linear algebraic approach to queuing theory is applied to analyze the performance of a typical single-bus multiprocessor system. This system can be modeled as an M/G/1/N queuing system with load-dependent arrivals. The method presented requires only that the nonexponential service time distribution for the system be a matrix-exponential, that is, one with a rational Laplace transform. Using linear algebraic techniques, expressions are obtained for the performance characteristics of interest, such as the processing power for the multiprocessor system. The algorithm does not rely on root finding and can be implemented using symbolic programming techniques. The explicit closed-form expression for the processing power is presented for some special cases.
The Scalable Coherent Interface and Related Standards Projects
Authors: Davib B. Gustavson
Venue: IEEE Micro (1992)

The Scalable Coherent Interface (SCI) (IEEE P1596), which provides bus services by transmitting packets on a collection of point-to-point unidirectional links, is described. Its protocols support cache coherence in a distributed shared-memory multiprocessor model, with message passing, I/O, and LAN communication taking place over fiber optic or wire links. Several ongoing SCI-related projects that apply the SCI technology to new areas or extend it to more difficult problems are also described. Future plans are sketched.
Application Performance on the MIT Alewife Machine
Authors: Frederic T. Chong, Beng-Hong Lim, Ricardo Bianchini, John Kubiatowicz, Anant Agarwal
Venue: Computer (1996)

The architecture of parallel machines influences the structure of parallel programs, and vice versa. This symbiotic cycle has been in motion for at least a decade. An important result of research on shared memory applications is the two sets of benchmarks, Splash and NAS, that have driven much research into shared memory architectures and cache-coherence protocols. At the same time, succeeding generations of shared memory multiprocessors (Stanford Dash, MIT Alewife, and Wisconsin Typhoon) have been used to characterize the behavior of shared memory applications. New applications and architectural mechanisms are now emerging. In particular, fine-grain applications are an important emerging class that warrants further study. These applications have long been thought to favor message-passing over shared memory architectures because of their frequent communications and sensitivity to memory latency. The authors present the performance of 14 applications on the Alewife machine, including both coarse- and fine-grain applications. Not surprisingly, Alewife's mechanisms support the good performance of traditional coarse-grain applications from the Splash and NAS benchmark suites. But the authors also show that Alewife provides an excellent communication mechanism for fine-grain applications. The results confirm that hardware support for limited sharing is adequate for a broad range of applications, even on large numbers of processors. Local cache-miss behavior turns out to be important on multiprocessors with low remote miss latencies. The results show that low-latency miss-handling mechanisms for both local and remote accesses in Alewife make fine-grain applications viable candidates for shared memory parallel processing.
Enhancing Functional and Irregular Parallelism: Stateful Functions and their Semantics
Authors: Isabelle Attali, Denis Caromel, Yung-Syau Chen, Jean-Luc Gaudiot, Andrew L. Wendelborn
Venue: International Journal of Parallel Programming (2001)

We describe an approach in which stateful computations can be expressed within the framework of a functional language. We consider algorithms with nondeterministic intermediate results and a deterministic final result which is obtained for any series of intermediate values of some variable shared among parallel tasks or, in other words, the ordering of updates to the variable does not matter. Functional languages normally abstract away from explicit synchronization and exploit parallelism between separate uses of a variable. But in some cases we can relax that requirement with both parallelism and determinate computation. To increase its expressiveness and efficiency for this important class of problems, we propose to extend the Sisal language with state variables encapsulated within stateful functions. We have used Centaur to specify and construct a semantic-based environment. We illustrate the proposed language extension with analysis of several examples, and comparison with other languages.