ppxscal/embedding_network huggingface dataset:
Experience with Tcl/Tk for scientific and engineering visualization
Authors: Brian W. Kernighan
Venue: Proceedings of the 3rd Annual USENIX Workshop on Tcl/Tk - Volume 3 (1995)

This paper relates experience gained while building a graphical user interface for a system that helps design and implement indoor wireless communications facilities. In this paper, I will describe this interface briefly, and draw some conclusions about what works well and what does not. I will also compare Tcl/Tk with Visual Basic for the same application.
The ARTEMIS cross-domain architecture for embedded systems
Authors: Hermann Kopetz
Venue: Proceedings of the conference on Design, automation and test in Europe (2007)

Today the embedded system market is a highly fragmented market, where custom-designed solutions dominate, resulting in a significant duplication of development effort for hardware, software and services. The ever-increasing complexity level of embedded systems, the technology trends of the semiconductor industry to large production series of chips, and the increased competition in the world market entail the need for a European-wide coherent and integrated development strategy for embedded systems. The ARTEMIS technology platform has been created to fill this need by joining the forces of many of the European players in the embedded system market in order to create the critical mass that is necessary to tackle the formidable challenges of the field.
Study of a group project model in computer science
Authors: C. E. Willis
Venue: Proceedings of the Frontiers in Education Conference,1997. on 27th Annual Conference. Teaching and Learning in an Era of Change. - Volume 01 (1997)

We have explored the use of peer learning in a large, introductory data structures course within our computer science curriculum. The principal peer learning activities are group programming projects where each student group is assisted by a trained upper-class undergraduate peer learning assistant (PLA). The PLAs are consultants to the group to help facilitate group interaction and support group and individual questions. This paper describes the use of group programming projects in the course and studies their use in three instances of the course over a four year period. Each of these courses was taught by the same professor during the same time in each academic year. Each course was taught with the same group programming project model, but with variations in the number of students, how the groups were organized and the number of PLAs that were used. Overall, we feel the introduction of group programming projects in this large introductory course has been beneficial to students, PLAs, TAs and faculty. The students are able to legitimately work with peers to solve problems and learn the material. Peers are more able to provide a student perspective in answering questions. The results shown, in the paper indicate the long-term viability of such an approach. The approach has continued to rate well with students through variations in how it is used.
Automatic generation of algorithm animations in a programming environment
Authors: F. Naharro-Berrocal
Venue: Proceedings of the 30th Annual Frontiers in Education - Volume 02 (2000)

The design and analysis of algorithms is one of the core fields of computer science, and their study is an intellectually demanding task. Animations are promising educational aids for the study of algorithms, but the main obstacle for an extensive educational use is the technical difficulty of producing them. This fact dissuades many teachers and most students from building animations. We report the facilities for algorithm animation we have integrated in a functional programming environment. One of our main concerns was to simplify the generation of animations to the extent of being as simple as handling an office application. In addition, the integration of animation generation with the programming environment produces synergy benefits. From the point of view of user interaction, our programming environment allow one to produce automatically, graphical, customizable visualizations of different instants of the algorithm execution. In a second step, an animation is built by arranging sequentially such visualizations, as a cartoons.
Effectiveness of Rotation Forest in Meta-learning Based Gene Expression Classification
Authors: Gregor Stiglic, Peter Kokol
Venue: Proceedings of the Twentieth IEEE International Symposium on Computer-Based Medical Systems (2007)

A lot of research has been done in the field of assembling classifiers in ensembles and on the other hand selecting the most appropriate single classifiers for a given problem which was solved by meta-learning techniques. This paper presents application of recently proposed ensemble of classifiers called Rotation Forest to Grading meta-learning scheme, where it is used as one of the base classifiers and meta-level classifier at the same time. Our proposed Grading variation is compared to four widely used classifiers on 14 datasets from the domain of gene expression classification problems. Experimental evaluations show that using Rotation Forest at meta-level most significantly impacts the accuracy of Grading scheme and confirms that it can be used for estimation of classifiers regions of strong and weak classification.
A new hybrid system based on MMI-neural networks for the RM speech recognition task
Authors: G. Rigoll
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02 (1996)

We present a hybrid speech recognition system for speaker independent continuous speech recognition. The system combines a novel information theory based neural network (NN) paradigm and discrete Hidden Markov models (HMMs) including state-of-the-art techniques like state clustered triphones. The novel NN type is trained by an algorithm based on principles of self-organization that achieves maximum mutual information between the generated output labels and the basic phonetic classes. The structure of the hybrid system is quite similar to a classical VQ-HMM system but the vector quantizer (VQ) is replaced by the NN. To evaluate the system we use the speaker independent part of the resource management (RM) database. We obtained an important improvement by introducing a novel kind of context dependent basic classes used by the acoustic processor. The average RM recognition result with a word-pair grammar is now 95.2% what is significantly better than a classical VQ-system, slightly better than a different hybrid system with a recurrent network as probability estimator, and very close to the best continuous probability density function (PDF) HMM speech recognizers.
Indexing and Search of Correlated Business Events
Authors: Roland Vecera, Szabolcs Rozsnyai, Heinz Roth
Venue: Proceedings of the The Second International Conference on Availability, Reliability and Security (2007)

Complex Event Processing (CEP) is an emerging technology gaining a lot of momentum in research as well as in commercial products. CEP is a technique that utilizes event-driven IT-systems to monitor, optimize and steer todays business situations in real-time. Lots of contributions have been published on how to handle large amounts of event streams and how to extract meaningful knowledge out of often fine-grained events. From our experience we learned that complex use cases implemented with CEP need appropriate tool support to validate, understand and analyze the event processing done by the CEP software. We introduce the EventCloud system which is a generic event search and analysis tool integrating with CEP solutions in almost every domain. EventCloud is an end user application that allows complex search and analysis of correlated events. As CEP requires a highly specialized system architecture, the characteristics of events also have impacts on the infrastructure for indexing, searching and analyzing events. In this paper we present two approaches describing how to properly represent correlated events in persistent storages to allow performant event indexing and searching. Further we describe the "document-oriented" approach, where correlated events are managed in a full-text index and discuss the problems and pitfalls with its implementation in Apache Lucene. Finally we compare different full-text engines, namely Apache Lucene[7] and Microsoft SQL Server 2005, to analyze their performance and features for event indexing and search.
NameIt: Extraction of product names
Authors: Gerhard Friedrich, Kostyantyn Shchekotykhin
Venue: Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops (2006)

An important precondition for the Semantic Web is to identify and annotate entities, their names, and their descriptions in the Web. In particular, the Web contains numerous Web pages describing various entities. In this paper we present a method for unsupervised generation of identities (i.e. product names) based on a set of concept instance describing Web pages. We exploit the redundancy of descriptions by statistical classification methods. We conducted an elaborated evaluation in order to identify the appropriate classification criteria and validated our system on two popular example domains. The result is a system for generating names which shows an F-Measure of 0.9 in our experiments.
Time-varying characteristics of postural sway differ between balance impaired and unimpaired populations
Authors: P. J. Loughlin
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 03 (1996)

To study potential time-varying dynamics of postural sway as measured via center-of-pressure (COP), the authors applied time-frequency analysis to COP data from ten vestibularly impaired subjects and thirteen unimpaired controls, during quiet stance and in response to visual perturbation. This analysis revealed that: (1) the spectral characteristics of the COP change over time; (2) there are time-dependent and frequency-dependent differences in the COP between impaired and unimpaired populations during visual perturbation; and (3) there is no difference in the COP during quiet stance (eyes open) between impaired and unimpaired populations for the parameters investigated. A novel finding of this research is that controls appear to adapt to constant frequency visual perturbation, while vestibularly impaired subjects do not.
Lightweight Dependency Models to Manage Software Architecture
Authors: Neeraj Sangal
Venue: Proceedings of the Sixth Working IEEE/IFIP Conference on Software Architecture (2007)

This tutorial will present a practical technique for managing the architecture of large software systems using Dependency Models. We will demonstrate that the matrix representation used by these models provides a unique view of the architecture and is highly scalable compared to the directed graph approaches that are common today. We will also show a variety of matrix algorithms that can be applied to analyze and organize the system into a form that reflects key architectural patterns and highlights problematic dependencies.
Methods of Sensors Localization in Wireless Sensor Networks
Authors: Zenon Chaczko, Ryszard Klempous, Jan Nikodem, Michal Nikodem
Venue: Proceedings of the 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (2007)

In recent years there has been a growing interest in wireless sensor networks (WSN) applications. Such sensor networks can be used to control temperature, humidity, contamination, pollution etc. Self-organization and routing algorithms dedicated to wireless sensor networks usually assume that sensors absolute positions are unknown and all decisions are based on sensor's own local information. This assumption makes wireless sensor networks more flexible and energy conserve because making decisions locally is faster and energy efficient. But sooner or later sensors positions have to be found (when sensor sends a message about some event we of course would like to know where this event takes place). In this paper we describe different solutions of finding transceivers positions in wireless networks and we discuss localization in wireless sensor networks. We propose to transfer localization function from base stations to every sensor. We evaluate presented method using simulations.
Domain and type enforcement for linux
Authors: Serge E. Hallyn, Phil Kearns
Venue: Proceedings of the 4th annual Linux Showcase & Conference - Volume 4 (2000)

Access control in Linux is currently very limited. This paper details the implementation of Domain and Type Enforcement (DTE) in Linux, which gives the system administrator a significant advantage in securing his systems. We control access from domains to types, domain transitions, and signal access between domains, based on a policy which is read at boot time.
Task Decomposition for Communication Computation Overlap to Reengineer a Web-Based System
Authors: Jian Kang, Hong Zhou, Hongji Yang
Venue: Proceedings of the 11th IEEE International Workshop on Future Trends of Distributed Computing Systems (2007)

Overcoming web code defects, such as nested loops, large multimedia packages, and mixed programming languages by decomposing and then composing program into a set of reusable segments can benefit web-based system reengineering. However, existing methods seldom meet the needs for correct, reliable, and economical program reengineering process. In this paper, program slicing and program transformations within Maintainer's Assistant software evolution environment are depicted to decompose and transform web page source code of a web-based system, with the purpose for communication and computation overlap. The result presents kinds of overlapped code after decomposition and reengineering achieves a relatively speedy quality when being explored.
Geometry of interpolation sets in derivative free optimization
Authors: A. R. Conn, K. Scheinberg, Lu&#x00ed;s N. Vicente
Venue: Mathematical Programming: Series A and B (2007)

We consider derivative free methods based on sampling approaches for nonlinear optimization problems where derivatives of the objective function are not available and cannot be directly approximated. We show how the bounds on the error between an interpolating polynomial and the true function can be used in the convergence theory of derivative free sampling methods. These bounds involve a constant that reflects the quality of the interpolation set. The main task of such a derivative free algorithm is to maintain an interpolation sampling set so that this constant remains small, and at least uniformly bounded. This constant is often described through the basis of Lagrange polynomials associated with the interpolation set. We provide an alternative, more intuitive, definition for this concept and show how this constant is related to the condition number of a certain matrix. This relation enables us to provide a range of algorithms whilst maintaining the interpolation set so that this condition number or the geometry constant remain uniformly bounded. We also derive bounds on the error between the model and the function and between their derivatives, directly in terms of this condition number and of this geometry constant.
IT Governance in the Light of Paradox--A Social Systems Theory Perspective
Authors: U. Ask, H. Bjornsson, M. Johansson, J. Magnusson, A. Nilsson
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

This paper uses Niclas Luhmann's concepts of paradox and deparadoxization as a starting point for looking at IT governance within large, Swedish organizations. All in all a total of 25 organizations within both the public and private sector have been investigated through interviews with the companies Chief Information Officers. The results are presented in relation to a number of areas within the study that could be identified as dichotomies, or areas where the respondents had to deal with conflicting logics. The results are discussed in general terms in relation to IT Governance practice as well as the potential value of applying Luhmann's theory of Social Systems to the study of IT Governance.
Computational Physics Education with Python
Authors: Arnd Backer
Venue: Computing in Science and Engineering (2007)

Educators at an institution in Germany have started using Python to teach computational physics. The author describes how graphical visualizations also play an important role, which he illustrates here with a few simple examples.
Instrumenting where it hurts: an automatic concurrent debugging technique
Authors: Rachel Tzoref, Shmuel Ur, Elad Yom-Tov
Venue: Proceedings of the 2007 international symposium on Software testing and analysis (2007)

As concurrent and distributive applications are becoming more common and debugging such applications is very difficult, practical tools for automatic debugging of concurrent applications are in demand. In previous work, we applied automatic debugging to noise-based testing of concurrent programs. The idea of noise-based testing is to increase the probability of observing the bugs by adding, using instrumentation, timing "noise" to the execution of the program. The technique of finding a small subset of points that causes the bug to manifest can be used as an automatic debugging technique. Previously, we showed that Delta Debugging can be used to pinpoint the bug location on some small programs. In the work reported in this paper, we create and evaluate two algorithms for automatically pinpointing program locations that are in the vicinity of the bugs on a number of industrial programs. We discovered that the Delta Debugging algorithms do not scale due to the non-monotonic nature of the concurrent debugging problem. Instead we decided to try a machine learning feature selection algorithm. The idea is to consider each instrumentation point as a feature, execute the program many times with different instrumentations, and correlate the features (instrumentation points) with the executions in which the bug was revealed. This idea works very well when the bug is very hard to reveal using instrumentation, correlating to the case when a very specific timing window is needed to reveal the bug. However, in the more common case, when the bugs are easy to find using instrumentation points ranked high by the feature selection algorithm is not high enough. We show that for these cases, the important value is not the absolute value of the evaluation of the feature but the derivative of that value along the program execution path. As a number of groups expressed interest in this research, we built an open infrastructure for automatic debugging algorithms for concurrent applications, based on noise injection based concurrent testing using instrumentation. The infrastructure is described in this paper.
Low-cost unified architectures for the computation of discrete trigonometric transforms
Authors: Shen-Fu Hsiao
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06 (2000)

New hardware-oriented matrix formulations and their corresponding VLSI architectures are proposed for both radix-2 and radix-4 fast algorithms of a variety of discrete trigonometric transforms (DXTs), including the discrete Fourier transform (DFT), discrete cosine transform (DCT), discrete sine transform (DST), and discrete Hartley transform (DHT). All the DXTs have the same complex kernel operation consisting of products of diagonal matrices and band matrices with equally spaced nonzero diagonals. New linear arrays based on the systolic mapping of the common kernel operation are designed which lead to hardware-efficient architectures requiring much fewer processing elements compared to other previously proposed unified DXT architectures of the same throughput rate.
Using machine-learning to assign function labels to parser output for Spanish
Authors: Grzegorz Chrupała, Josef van Genabith
Venue: Proceedings of the COLING/ACL on Main conference poster sessions (2006)

Data-driven grammatical function tag assignment has been studied for English using the Penn-II Treebank data. In this paper we address the question of whether such methods can be applied successfully to other languages and treebank resources. In addition to tag assignment accuracy and f-scores we also present results of a task-based evaluation. We use three machine-learning methods to assign Cast3LB function tags to sentences parsed with Bikel's parser trained on the Cast3LB treebank. The best performing method, SVM, achieves an f-score of 86.87% on gold-standard trees and 66.67% on parser output - a statistically significant improvement of 6.74% over the baseline. In a task-based evaluation we generate LFG functional-structures from the function-tag-enriched trees. On this task we achive an f-score of 75.67%, a statistically significant 3.4% improvement over the baseline.
Mixed-signal vlsi robust time-frequency feature extraction
Authors: Gert Cauwenberghs
Venue:  (2007)

Robust feature extraction is critical to pattern recognition and intelligent systems. The problem of extracting reliable features from real-world signals is challenging because these signals are embedded in non-stationary noise; real-time operation requires fast adaptation; and mobile operation requires miniature hardware with low-power consumption. The need for robust real-time, and low-power feature extraction solutions calls for an integrative approach that combines adaptive signal processing, machine learning, and micropower VLSI design. This dissertation presents time-frequency feature extraction algorithms, inspired by biological models of auditory processing, for robust feature extraction. The algorithms map efficiently onto massive parallel VLSI hardware to provide real-time operation. Analog models of computation are combined with digital programmability and adaptation, leading to significant savings in silicon area and power compared to purely analog or digital approaches. A digitally programmable operational transconductance amplifier (OTA) offers more than three decades transconductance gain and wide linear range. Fully differential continuous-time OTA-C filters provide high dynamic range, high power supply noise rejection, and programmable filter parameters. Fabrication-induced mismatch in the analog implementation is compensated through calibration using a generalized linear modeling and optimization scheme. My research has resulted in a reconfigurable biomimetic mixed-signal VLSI feature extraction frontend for sonar and acoustic classification. The reconfigurable system is integrated on a single 3mm &times; 3mm chip in 0.5um CMOS technology. It features a 32-channel filter bank, with reconfigurable filter topology and programmable filter parameters. The chip consumes 9mW power for a total of 96 integrated biquad filters.My work further led to application of the frontend architecture to robust speech and speaker recognition, sonar signal processing for under water target detection, and statistical analysis of speckle field for adaptive laser communication and adaptive optics. Experiments with robust speech and speaker recognition demonstrated the noise robustness of the extracted features under the auditory perception model, outperforming MFCC feature extraction algorithms. Combining ultrasonic time-frequency features with support machine learning algorithms, we showed detection of buried underwater targets from sonar backscatter of single-ping sonar signals. In adaptive optics experiments, time-frequency analysis of speckle field signals indicated to be an effective laser beam quality metric for adaptive target-in-the-loop control.