ppxscal/embedding_network huggingface dataset:
SOCs Drive New Product Development
Venue: Computer (1999)

To dispel a potential misperception that system-on-chip designs are a long way off, the authors describe several examples of new products that derive benefits from using SOCs. These designs, like those for embedded processors, emphasize the combination of a complementary set of functions into an economically viable package. SOCs are fueling new products that wouldn't have been possible--either economically or technologically--a few years ago.Gary Silcott, the author of "SOC Challenges for Wireless Handsets," describes the features of Motorola's chip that answers the call for smaller handsets and longer battery life by integrating the separate DSP and microcontroller onto one piece of silicon. He also makes some predictions about what's next in this design area . In "Thin Clients Benefit from SOC," Janet Wilson describes how SOCs offer original equipment manufacturers an economical package on which to base new products. She reports that thin-client vendors like Wyse are using this model to make serious inroads into corporate computing, a domain long dominated by the desktop PC. Neil Peterson and William Peisel, the authors of "Networking the Office with SOCs," explain how OEMs can save time and money by buying a product that integrates several networking functions--copier, facsimile, and laser-quality printer--into a single chip. In "MEMS Technology Emerges," Kirk L. Kroeker presents a sampling of emerging commercial products that use microelectromechanical systems--semiconductor chips that integrate mechanical elements, sensors, actuators, and electronics on a silicon substrate. He describes some advantages of MEMS over current devices that perform the same functions and explains why MEMS is sure to be the technology of the future for many applications.
Multi-wavelets from B-spline super-functions with approximation order
Authors: Hüseyin Özkaramanli, Asim Bhatti, Bulent Bilgehan
Venue: Signal Processing (2002)

Approximation order is an important feature of all wavelets. It implies that polynomials up to degree p - 1 are in the space spanned by the scaling function(s). In the scalar case, the scalar sum rules determine the approximation order or the left eigenvectors of the infinite down-sampled convolution matrix H determine the combinations of scaling functions required to produce the desired polynomial. For multi-wavelets the condition for approximation order is similar to the conditions in the scalar case. Generalized left eigenvectors of the matrix Hf; a finite portion of H determines the combinations of scaling functions that produce the desired superfunction from which polynomials of desired degree can be reproduced. The superfunctions in this work are taken to be B-splines. However, any refinable function can serve as the superfunction. The condition of approximation order is derived and new, symmetric, compactly supported and orthogonal multi-wavelets with approximation orders one, two, three and four are constructed.
Discontinuity-Preserving and Viewpoint Invariant Reconstruction of Visible Surfaces Using a First Order Regularization
Authors: June H. Yi, David M. Chelberg
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (1995)

This paper describes the application of a first order regularization technique to the problem of reconstruction of visible surfaces. Our approach is a computationally efficient first order method that simultaneously achieves approximate invariance and preservation of discontinuities. Our reconstruction method is also robust with respect to the smoothing parameter ¿. The robustness property to ¿ allows a free choice of the smoothing parameter ¿ without struggling to determine an optimal ¿ that provides the best reconstruction. A new approximately invariant first order stabilizing function for surface reconstruction is obtained by employing a first order Taylor expansion of a nonconvex invariant stabilizing function that is expanded at the estimated value of the squared gradient instead of at zero. The data compatibility measure used is the squared perpendicular distance between the reconstructed surface and the constraint surface. This combination of stabilizing function and data compatibility measure is necessary to achieve invariance with respect to rotations and translations of the surfaces being reconstructed. Sharp preservation of discontinuities is achieved by a weighted sum of adjacent pixels such that the adjacent pixels that are more likely to be in different regions are less weighted. The results indicate that the proposed methods for surface reconstruction perform well on sparse noisy range data. In addition, the volume between two surfaces normalized by the surface area (interpreted as average distance between two surfaces) is proposed as an invariant measure for the comparison of reconstruction results.
Inverting the Hodrick&ndash;Prescott Filter
Authors: John Landon-Lane
Venue: Computational Economics (2002)

The Hodrick&ndash;Prescott (HP) filter is the most popular method of transforming data in the Real Business Cycle (RBC) literature. An algorithm to invert the Hodrick&ndash;Prescott (HP) filter is described. This algorithm is applied, using Markov chain Monte Carlo methods, to the problem of evaluating a simple RBC model. The problem of determining the optimal smoothing parameter for the HP filter is also studied.
Yet Another Optimization Article
Authors: Martin Fowler
Venue: IEEE Software (2002)

For many programmers, performance is something you pay continuous attention to as you program. Every time you write fragment of code, you consider the performance implications and code the program to maximize performance. This is an obvious technique--pity it works so badly.
An intelligent sales forecasting system through integration of artificial neural networks and fuzzy neural networks with fuzzy weight elimination
Authors: R. J. Kuo, P. Wu, C. P. Wang
Venue: Neural Networks (2002)

Sales forecasting plays a very prominent role in business strategy. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average (ARMA). However, sales forecasting is very complicated owing to influence by internal and external environments. Recently, artificial neural networks (ANNs) have also been applied in sales forecasting since their promising performances in the areas of control and pattern recognition. However, further improvement is still necessary since unique circumstances, e.g. promotion, cause a sudden change in the sales pattern. Thus, this study utilizes a proposed fuzzy neural network (FNN), which is able to eliminate the unimportant weights, for the sake of learning fuzzy IF-THEN rules obtained from the marketing experts with respect to promotion. The result from FNN is further integrated with the time series data through an ANN. Both the simulated and real-world problem results show that FNN with weight elimination can have lower training error compared with the regular FNN. Besides, real-world problem results also indicate that the proposed estimation system outperforms the conventional statistical method and single ANN in accuracy.
A Modified Fourier&ndash;Galerkin Method for the Poisson and Helmholtz Equations
Authors: Ole F. Næss, Knut S. Eckhoff
Venue: Journal of Scientific Computing (2002)

In this paper we present a modified Fourier&ndash;Galerkin method for the numerical solution of the Poisson and Helmholtz equations in a d-dimensional box. The inversion of the differential operators requires O(Nd) operations, where Nd is the number of unknowns. The total cost of the presented algorithms is O(Nd&emsp14;log2&emsp14;N), due to the application of the Fast Fourier Transform (FFT) at the preprocessing stage. The method is based on an extension of the Fourier spaces by adding appropriate functions. Utilizing suitable bilinear forms, approximate projections onto these extended spaces give rapidly converging and highly accurate series expansions.
Simultaneous Bidirectional Transceiver Logic
Authors: Kenichi Ishibashi, Tsutomu Goto, Takehisa Hayashi, Tetsuhiko Okada, Akira Yamagiwa, Masabumi Shibata, Kazuhiro Akimoto, Naoki Hamanaka, Toshiro Takahashi, Akio Koyama, Tatsuhiro Aida
Venue: IEEE Micro (1999)

A 26.8-GB/s crossbar switch for the HITACHI high-end SMP server VT800 using Simultaneous Bi-directional Transceiver Logic (SBTL) is described. The 16-way PA-8000 SMP server, the VT800, has 14 crossbar switch ports for processor/memory/I/O boards. Each port transmits 8-byte data bidirectionally (to/from a crossbar switch) at 120-MHz. SBTL circuits are implemented in the LSIs composing the crossbar switch and the control logic in the processor/memory/I/O boards. This reduced the total number of LSIs and signal nets in the backplane required for implementing the crossbar switch. The number of backplane signal nets, which is logically more than tow thousands, has been halved physically by using SBTL. This technology is effective to simplify the implementation and to reduce cost of crossbar switch based SMP servers.
Comments on parallel algorithms for the knapsack problem
Authors: Carlos Alberto Alonso Sanches, Nei Yoshihiro Soma, Horacio Hideki Yanasse
Venue: Parallel Computing (2002)

Chang et al. [Parallel Comput. (1994) 233] introduced a parallel algorithm based on a shared memory SIMD architecture for the generation phase of the classic Horowitz and Sahni [J. ACM 21(2) (1974) 277] two-list serial algorithm for the knapsack problem. They claimed that their parallel generation phase could be accomplished in time O((n/8)2) and in space O(2n/4) with O(2n/8) processors.We prove that their results are not correct, i.e., that the suggested scheme time and space complexity should be bounded, instead, by O(n2n/2) and O(2n/2), respectively. These results also invalidate the performance analysis of the more recent Lou and Chang [Parallel Comput. (1997) 1985] algorithm.
Pattern Recognition Properties of Various Feature Spaces for Higher Order Neural Networks
Authors: W. A. C. Schmidt, J. P. Davis
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (1993)

The authors explore alternatives that reduce the number of network weights while maintaining geometric invariant properties for recognizing patterns in real-time processing applications. This study is limited to translation and rotation invariance. The primary interest is in examining the properties of various feature spaces for higher-order neural networks (HONNs), in correlated and uncorrelated noise, such as the effect of various types of input features, feature size and number of feature pixels, and effect of scene size. The robustness of HONN training is considered in terms of target detectability. The experimental setup consists of a 15*20 pixel scene possibly containing a 3*10 target. Each trial used 500 training scenes plus 500 testing scenes. Results indicate that HONNs yield similar geometric invariant target recognition properties to classical template matching. However, the HONNs require an order of magnitude less computer processing time compared with template matching. Results also indicate that HONNs could be considered for real-time target recognition applications.
Knowledge Representation Using Fuzzy Petri Nets
Authors: S. -M. Chen, J. -S. Ke, J. -F. Chang
Venue: IEEE Transactions on Knowledge and Data Engineering (1990)

A fuzzy Petri net model (FPN) is presented to represent the fuzzy production rule of a rule-based system in which a fuzzy production rule describes the fuzzy relation between two propositions. Based on the fuzzy Petri net model, an efficient algorithm is proposed to perform fuzzy reasoning automatically. It can determine whether an antecedent-consequence relationship exists from proposition d/sub s/ to proposition d/sub j/, where d/sub s/ not=d/sub j/. If the degree of truth of proposition d/sub s/ is given, then the degrees of truth of proposition d/sub j/ can be evaluated. The formal description of the model and the fuzzy reasoning algorithm are shown in detail. The upper bound of the time complexity of the fuzzy reasoning algorithm is O(nm), where n is the number of places and m is the number of transitions. Its execution time is proportional to the number of nodes in a sprouting tree generated by the algorithm only generates necessary reasoning paths from a starting place to a goal place, it can be executed very efficiently.
Analysis of large data logs: an application of Poisson sampling on excite web queries
Authors: H. Cenk Ozmutlu, Amanda Spink, Seda Ozmutlu
Venue: Information Processing and Management: an International Journal (2002)

Search engines are the gateway for users to retrieve information from the Web. There is a crucial need for tools that allow effective analysis of search engine queries to provide a greater understanding of Web users' information seeking behavior. The objective of the study is to develop an effective strategy for the selection of samples from large-scale data sets. Millions of queries are submitted to Web search engines daily and new sampling techniques are required to bring these databases to a manageable size, while preserving the statistically representative characteristics of the entire data set. This paper reports results from a study using data logs from the Excite Web search engine. We use Poisson sampling to develop a sampling strategy, and show how sample sets selected by Poisson sampling statistically effectively represent the characteristics of the entire dataset. In addition, this paper discusses the use of Poisson sampling in continuous monitoring of stochastic processes, such as Web site dynamics.
On the Discriminatory Power of Adaptive Feed-Forward Layered Networks
Authors: H. Osman, M. M. Fahmy
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (1994)

This correspondence expands the available theoretical framework that establishes a link between discriminant analysis and adaptive feed-forward layered linear-output networks used as mean-square classifiers. This has the advantages of providing more theoretical justification for the use of these nets in pattern classification and gaining a better insight into their behavior and about their use. The authors prove that, under reasonable assumptions, minimizing the mean-square error at the network output is equivalent to minimizing the following: 1) the difference between the optimum value of a familiar discriminant criterion and the value of this criterion evaluated in the space spanned 2) the outputs of the final hidden layer, and 3) the difference between the values of the same discriminant criterion evaluated in desired-output and actual-output subspaces. The authors also illustrate, under specific constraints, how to solve the following problem: given a feature extraction criterion, how the target coding scheme can be selected such that this criterion is maximized at the output of the network final hidden layer. Other properties for these networks are explored.
MicroUnity's MediaProcessor Architecture
Authors: Craig Hansen
Venue: IEEE Micro (1996)

A broadband mediaprocessor extends and streamlines a general-purpose computer system to attain the goal of communicating and processing digital video, audio, data and RF signals at broadband rates using compiled, downloadable, software rather than special-purpose hardware. The instruction set, system facilities, and initial implementations of an architectural family of broadband mediaprocessors are introduced, and compiled software development is illustrated with an example and description of the development environment.
Solving the Group Priority Inversion Problem in a Timed Asynchronous System
Authors: Yun Wang, Emmanuelle Anceaume, Francisco Brasileiro, Fabíola Greve, Michel Hurfin
Venue: IEEE Transactions on Computers (2002)

We consider the priority inversion problem in an actively replicated system. Priority inversion was originally defined in the context of nonreplicated systems. Therefore, we first introduce the concept of group priority inversion, which extends the concept of (local) priority inversion to the context of a group of processors that perform an actively replicated processing. We then present the properties of a request scheduling protocol to enforce a total ordering for the processing of requests while avoiding group priority inversions. These properties have been implemented in a protocol that relies on a timed asynchronous system model equipped with a failure detector of the class diamond S. The proposed solution allows us to replicate a critical server while ensuring that the processing of all the incoming requests is consistent (mechanisms for solving the atomic broadcast problem) and predictable (mechanisms for solving the group priority inversion problem). Thus, the described request scheduling protocol is a key component which can be used to develop fault-tolerant real-time applications in a timed asynchronous system.
Now You See It, Now You Don't
Authors: Christine Rigden
Venue: Computer (2002)

Everyone has an opinion about color. Although we tend to assume that people see the same colors, who hasn't disagreed about an object's particular shade? Whether something is blue or indigo usually isn't a major issue, but when it comes to creating an interface that uses color to code information, serious problems can arise for some users if designers are unaware of certainprinciples that govern how people perceive their work. For example,among the one in 12 men who havecolor-deficient vision, perhaps two thirds or more experience problems significant enough to impact their ability to carry out everyday tasks.By following a few basic guidelines, it's possible to ensure that Web browsers and other interfaces do not put such users at a disadvantage. Developers can accomplish this for little cost and without compromising the designs' wider qualities.
The TigerSHARC DSP Architecture
Authors: Jose Fridman, Zvi Greenfield
Venue: IEEE Micro (2000)

This highly parallel DSP architecture based on a short-vector memory system incorporates techniques found in general-purpose computing. It promises sustained performance close to its peak computational rates of 900 Mflops (32-bit floating-point) or 3.6 BOPS (16-bit fixed-point).
Reorganizing Knowledge to Improve Performance
Authors: A. Lopez-Suarez, M. Kamel
Venue: IEEE Transactions on Knowledge and Data Engineering (1998)

This paper presents a method to reorganize rules in knowledge bases with the objective of improving their performance. Knowledge reorganization is achieved through the combination of rule compression and abstraction techniques. The effectiveness of this methodology is evaluated in terms of pattern matching activity and execution times using knowledge bases from several application areas.
Validating and Improving Test-Case Effectiveness
Authors: Yuri Chernak
Venue: IEEE Software (2001)

Effective software testing before release is crucial for product success. Based on a new metric and an associated methodology for in-process validation of test-case effectiveness, the author presents an approach to improving the software testing process.
A study on tone statistics in Chinese names
Authors: Yaxin Zhang, Anton Medievski, James Lawrence, Jianming Song
Venue: Speech Communication (2002)

This paper describes a study on tone statistics of peoples' names in Mandarin Chinese. The problem was brought out when we tried to apply an English version of a speech recognizer to a Chinese voice tag dialing task. The questions were: (1) How serious is the tone-confusable problem in a Chinese voice tag dialing system? (2) Do we need to enhance the recognizer to properly recognize tonal languages? To gain more information, we studied a Chinese name database consisting of 1.6 million names. The statistical analysis shows the potential for a problem with tone-confusable names in a Mandarin voice tag dialing system. We developed a tone enhancement approach to turn an English speech recognizer to a tonal language speech recognizer. We performed benchmark testing to compare recognition performance of an English version speech recognizer and a tone-enhanced version, both working on a small database of Chinese names. Then we did a pseudo-recognition analysis for the large Chinese voice tag database. From this analysis we conclude that enhancing an English version speech recognizer to add tonal recognition capabilities would improve recognition of Chinese names, reducing the recognition error rate by 10-20%.
Methodical Analysis of Adaptive Load Sharing Algorithms
Authors: O. Kremien, J. Kramer
Venue: IEEE Transactions on Parallel and Distributed Systems (1992)

A method for qualitative and quantitative analysis of load sharing algorithms is presented, using a number of well known examples as illustration. Algorithm design choice are considered with respect to the main activities of information dissemination and allocation decision making. It is argued that nodes must be capable of making local decisions, and for this efficient state, dissemination techniques are necessary. Activities related to remote execution should be bounded and restricted to a small proportion of the activity of the system. The quantitative analysis provides both performance and efficiency measures, including consideration of the load and delay characteristics of the environment. To assess stability, which is also a precondition for scalability, the authors introduce and measure the load-sharing hit-ratio, the ratio of remote execution requests concluded successfully. Using their analysis method, they are able to suggest improvements to some published algorithms.
Stochastic Models for Performance Analysis of Database Recovery Control
Authors: Ushio Sumita, Paulo B. Goes
Venue: IEEE Transactions on Computers (1995)

In this paper we develop three analytical models for a comprehensive analysis of database recovery. These models, based on semi-Markov stochastic analysis and queueing networks, not only capture the details of modern recovery mechanisms, but take the complex stochastic behavior of the system into account. Furthermore, we use multiple performance measures to analyze different recovery mechanisms, the impact of environment characteristics and the effect of tunable system parameters, thus offering database designers and administrators a better understanding of the recovery system to be designed or managed. A special case of database recovery that has been studied by previous researchers is analyzed in detail; numerical experiments offer evidence of the effectiveness of our approach. The models developed in this paper, however, are applicable to much more general systems and environments.
Deferring Real-Time Traffic for Improved Non-Real-Time Communication in FDDI Networks
Authors: Parameswaran Ramanathan, Moncef Hamdaoui
Venue: IEEE Transactions on Computers (1995)

The fiber distributed data interface (FDDI) is suitable for real-time communication because of the high speed and the performance guarantees it provides. However, these guarantees are achieved at the expense of non-real-time traffic because the real-time messages are given higher priority over non-real-time messages, resulting in excessive delays for non-real-time messages. In this paper, we propose a scheme for reducing the response time of non-real-time messages while still providing the same guarantees to real-time messages. In particular, the proposed approach gives higher priority to real-time messages only when it is absolutely necessary in order for them to meet their deadlines. Non-real-time messages are thus transmitted ahead of real-time messages whenever possible. We present an algorithm for determining when and by how much the transmission of a real-time message can be deferred without jeopardizing its deadline. The proposed approach is evaluated through simulation. The simulation results show that a substantial reduction in the mean response time of non-real-time messages is achieved when using the proposed approach.