ppxscal/embedding_network huggingface dataset:
Probabilistic neural network versus cubic least-squares minimum-distance in classifying EEG signals
Authors: I. Kalatzis, N. Piliouras, E. Ventouras, I. Kandarakis, C. C. Papageorgiou, A. D. Rabavilas, D. Cavouras
Venue: Proceedings of the international conference on Computational methods in sciences and engineering (2003)

The purpose of the present study is the implementation of a classification system for differentiating healthy subjects from patients with depression. Twenty-five depressive patients and an equal number of gender and aged-matched normal controls were evaluated using a computerized version of the digit span Wechsler test. Morphological waveform features were extracted from the digitized Event-Related Potential (ERP) signals, recorded from 15 scalp electrodes. The feature extraction process focused on the P600 component of the ERPs. The designed system comprised two classifiers, the probabilistic neural network (PNN) and the cubic least-squares (CLS) minimum-distance, two routines for feature reduction and feature selection, and an overall system evaluation routine, consisting of the exhaustive search and the leave-one-out methods. Highest classification accuracies achieved were 96% for the PNN and 94% for the CLS, using the 'latency/amplitude ratio' and 'peak-to-peak slope' two-feature combination. In conclusion, employing computer-based pattern recognition techniques with features not easily evaluated by the clinician, patients with depression could be distinguished from healthy subjects with high accuracy.
An empirical evaluation of the G/Q/M method
Authors: Khaled El Emam, Nadir Moukheiber, Nazim H. Madhavji
Venue: Proceedings of the 1993 conference of the Centre for Advanced Studies on Collaborative research: software engineering - Volume 1 (1993)

Improvement of the software process is a major concern for many organizations. A critical part of such an endeavor is the definition of metrics. Despite the importance of metric definition, there have been no evaluations of existing methods for achieving this. It is generally taken for granted that a method with wide acceptance is suitable. A review of metric definition methods identities Basili's G/Q/M as one of the most widely used. This paper reports on an evaluation of the G/Q/M method. The evaluation is based on an actual application of the method in a process improvement effort. The resultant metrics (and instrument) are evaluated with respect to the following criteria: interpretability, validity, reliability, effectiveness, and transportability. The causes of problems found are identified. These causes are problems with the G/Q/M method itself. The evaluation indicates that the metrics resultant from the application of the G/Q/M method do not appropriately meet the above criteria, and research on evolving G/Q/M or developing alternative methods is emphasized.
Studies on Rule-Learning in Gaming Simulation
Authors: Yuji Shinoda, Yoshiteru Nakamori
Venue: Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 3 - Volume 3 (2004)

Gaming is one of the good tools to deal with complex phenomena. Now, computer agents arebeginning to join gaming as substitutes for human players. To help designing of a gaming, this paper proposes a model for gaming-simulation. In this model, each agent has its own neural-networks for predicting behavior of other agents, including itself. In addition, each agent has a classifier model for tactical decision-making, and to achieve tactical target, the agent uses neural-networks to get an optimal answer. These agents try to find tactical rules with playing the game that aims at the second phase. It is shown that this three-model structure enables us to monitor behavior of agents easily.
Memory allocation and mapping in high-level synthesis: an integrated approach
Authors: Jaewon Seo, Taewhan Kim, Preeti Ranjan Panda
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2003)

With the increasing design complexity and performance requirement, data arrays in behavioral specification are usually mapped to memories in behavioral synthesis. This paper describes a new algorithm that overcomes two limitations of the previous works on the problem of memory-allocation and array-mapping to memories. Specifically, its key features are a tight link to the scheduling effect, which was totally or partially ignored by the existing memory synthesis systems, and supporting nonuniform access speeds among the ports of memories, which greatly diversify the possible (practical) memory configurations. Experimental data on a set of benchmark filter designs are provided to show the effectiveness of the proposed exploration strategy in finding globally best memory configurations.
Complex-valued wavelet network
Authors: Chunguang Li, Xiaofeng Liao, Juebang Yu
Venue: Journal of Computer and System Sciences (2003)

In this paper, a complex-valued wavelet network (CWN) is proposed. The network has complex inputs, outputs, connection weights, dilation and translation parameters, but the nonlinearity of the hidden nodes remains a real-valued function (real-valued wavelet function). This kind of network is able to approximate an arbitrary nonlinear function in complex multi-dimensional space, and it provides a powerful tool for nonlinear signal processing involving complex signals. A complex algorithm is derived for the training of the proposed CWN. A numerical example on nonlinear communication channel identification is presented for illustration.
Load and QoS-Adaptive Scheduling in Bluetooth Piconets
Authors: Vojislav B. Mi"i", Eric W. S. Ko, Jelena Mi"i"
Venue: Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 9 - Volume 9 (2004)

A novel polling scheme for intra-piconet scheduling in Bluetooth piconets, dubbed Adaptive Cycle-Limited Scheduling, is described. The scheme allocates the time to each slave according to its current traffic, whilst trying to limit the maximum piconet cycle time. This approach makes scheduling of mixed asynchronous and CBR traffic much easier than with other known schemes. In this manner, the scheme is able to provide near-optimum performance for asynchronous data traffic, guaranteed QoS for CBR traffic, and inherent fairness among slaves with asymmetric traffic. Simulations confirm that the new scheme performs as good as, or in some cases even better than, other common polling schemes.
The Zero-Free Intervals for Chromatic Polynomials of Graphs
Authors: Carsten Thomassen
Venue: Combinatorics, Probability and Computing (1997)

The maximal zero-free intervals for chromatic polynomials of graphs are precisely (&minus;&infin;, 0), (0, 1), (1, 32&#x002F;27]. We also investigate the distribution of zeros of chromatic polynomials in various classes of graphs closed under minors. For example, the zeros of chromatic polynomials of graphs of tree-width at most k consist of 0, 1 and a dense subset of the interval (32&#x002F;27, k].
Multitiered nonlinear morphology using multitape finite automata: a case study on Syriac and Arabic
Authors: George Anton Kiraz
Venue: Computational Linguistics (2000)

This paper presents a computational model for nonlinear morphology with illustrations from Syriac and Arabic. The model is a multitiered one in that it allows for multiple lexical representations corresponding to the multiple tiers of autosegmental phonology. The model consists of three main components: (i) a lexicon, which is made of sublexica, with each sublexicon representing lexical material from a specific tier, (ii) a rewrite rules component that maps multiple lexical representations into one surface form and vice versa, and (iii) a morphotactic component that employs regular grammars. The system is finite-state in that lexica and rules can be represented by multitape finite-state machines.
Inventing new media: what we can learn from new media art and media history
Authors: Lev Manovich
Venue: Proceedings of the eleventh ACM international conference on Multimedia (2003)

Throughout the human history, the design of different cultural techniques and media forms for representing human knowledge, collective and personal experience, and what we now call "data" have not been confined to single individuals or disciplines. To mention just a few examples, natural languages, printed books, a linear perspective, landscape photography, and documentary cinema have all been developed and refined over time by whole societies and multiple individuals.Today with the computer acting as the interface for all past, present, and emergent forms of media, the situation is quite different. Computer scientists working on media computing play the key role in how our societies will remember their histories, how we will represent ourselves and others, what we will imagine and what metaphors we use to understand reality. In short, to work on media computing today is to assume big cultural responsibility - and also have tremendous power to define new forms of media.Unfortunately, more often than not, computer scientists do not take advantage of their powers. Too often, they simply translate existing media forms and cultural techniques into software interfaces. For instance, the controls of software media players are modeled after VCR; Acrobat software tries to recreate the conventions of a printed page; etc. This made sense twenty years ago when people were coming to computers after having first experienced other media technologies --- but not today.While I do not want to position the whole field of digital art as more innovative in this respect, one can point at a number of artists who have dedicated their careers to use computers to invent substantially new forms of media, often with very exiting results. In my talk I will show and discuss a number of works by these artists. I will also talk about the selected historical moments than a new media form emerged to see what we can learn from these histories.
Raindrop: a uniform and layered algebraic framework for XQueries on XML streams
Authors: Hong Su, Jinhui Jian, Elke A. Rundensteiner
Venue: Proceedings of the twelfth international conference on Information and knowledge management (2003)

XML stream applications bring the challenge of efficiently processing queries on sequentially accessible token-based data. While the automata model is naturally suited for pattern matching on tokenized XML streams, the algebraic model in contrast is a well-established technique for set-oriented processing of self-contained tuples. However, neither automata nor algebraic models are well-equipped to handle both computation paradigms. The goal of the Raindrop project is to accommodate these two paradigms within one algebraic framework to take advantage of both. In our query model, both tokenized data and self-contained tuples are supported in a uniform manner. Query plans can be flexibly rewritten using equivalence rules to change what computation is done using tokenized data versus tuples. This paper highlights the four abstraction levels in Raindrop, namely, semantics-focused plan, stream logical plan, stream physical plan and execution plan. Various optimization techniques are provided at each level. The necessity of such a uniform and layered plan is shown by experimental study
The role of computer systems in the nuclear power debate
Authors: Kevin W. Bowyer
Venue: ACM SIGCAS Computers and Society (1980)

One of the primary reasons for the current "decline" of nuclear power is that reactors have not operated reliably. This unreliability has raised questions of both safety and economics. Computer systems have been a part of this failure of technology. If nuclear power is to be revived as an energy option for our country, both the quantity and quality of computer applications must increase.
Cyber Security Exercises: Testing an Organization's Ability to Prevent, Detect, and Respond to Cyber Security Events
Authors: Gregory B. White, Glenn Dietrich, Tim Goles
Venue: Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 7 - Volume 7 (2004)

The digital age has transformed how today's organizations operate. The production and delivery of essential goods and services takes place through complex and interconnected business processes that in turn rely on a set of interdependent infrastructures. These infrastructures and their supporting information systems transcend individual organizations. However, information systems security research is largely under the purview of computer science and engineering departments, and consequently often focuses on technological issues while overlooking the pervasive nature of information systems in today's society. This has generated calls for a new approach to information systems security; one that employs a socio-organizational perspective that includes not only individual organizations but entire industry sectors and government agencies as well.This paper presents one such approach, the use of scenario-based exercises in addressing security issues common to large organizations, industry sectors, and various levels of government. Lessons learned from illustrative examples of such exercises, as well assuggestions to help organizations conduct their own exercise, are discussed.
Performance of the Optimal Causal Multicast Algorithm: A Statistical Analysis
Authors: Punit Chandra, Pranav Gambhire, Ajay D. Kshemkalyani
Venue: IEEE Transactions on Parallel and Distributed Systems (2004)

Abstract--An optimal causal message ordering algorithm for asynchronous distributed systems was proposed by Kshemkalyani and Singhal and its optimality was proven theoretically. For a system of n processes, although the space complexity of this algorithm was shown to be O(n^2) integers, it was expected that the actual space overhead would be much less than n^2. It is difficult to determine the behavior of this algorithm by a theoretical analysis. In this paper, we measure the overheads of two different implementations of the optimal causal message ordering algorithm via simulation under a wide range of system conditions. The optimal algorithm is seen to display significantly less message space overhead and log space overhead than the canonical Raynal-Schiper-Toueg algorithm.
Efficient Undeniable Signature Schemes Based on Ideal Arithmetic in Quadratic Orders
Authors: Ingrid Biehl, Sacher Paulus, Tsuyoshi Takagi
Venue: Designs, Codes and Cryptography (2004)

In undeniable signature schemes the correctness or incorrectness of a signature of some message cannot be checked without the agreement of and the interaction with the signer. This is a favorable property for some applications. Well-known undeniable signature schemes presented in the literature will cause operations for the signer which take cubic running time. For a real world implementation, e.g., on a chip card or a web server this might be too inefficient. &emsp;In this paper, we present new efficient undeniable signature schemes which are constructed over an imaginary quadratic field. We compare our schemes to the only really competitive scheme so far, which is based on RSA. In all signature protocols presented here the signer&rsquo;s part involving the secret key is always of quadratic complexity, which is much faster in practice than the signer&rsquo;s part in the RSA-based undeniable signature protocol.
MEDAL: A CASE Tool Extension for Model-Driven Software Engineering
Authors: Nicolas Guelfi, Benoît Ries, Paul Sterges
Venue: Proceedings of the IEEE International Conference on Software-Science, Technology & Engineering (2003)

The complexity of today's software systems leads to thecreation of many related diagrams, representing differentviewpoints, different levels of abstraction, and differentimplementation alternatives. Model-driven softwareengineering places these models in the center of thedevelopment process. Tool support is an essential aspectof model-driven engineering. Of particular interest aremodel transformation tools: they can facilitate thecreation and the evolution of models; they provide a levelof traceability between them and they help keeping themsynchronized. Unfortunately, currently there are few suchtools for UML-based models. This paper presentsMEDAL, our model transformation tool. First, we presentour viewpoint on model-driven software engineering.Then we describe MEDAL and how we implementedMEDAL on top of Rational XDE. Finally, in the lastsection we show how a web application development thatis based on an architectural framework can be supportedby the MEDAL tool.
Comparing sequential visualisation methods for the Mandelbrot set
Authors: V. Drakopoulos
Venue: Proceedings of the international conference on Computational methods in sciences and engineering (2003)

sequential visualisation methods for the most widely used methods for the graphical representation of the Mandelbrot set are compared. Two groups of methods are presented. In the first, the Mandelbrot set (or its border) is rendered and, in the second, its complement is rendered. Examples of two-dimensional images obtained using these methods are also given.
Zero-Sum Average Semi-Markov Games: Fixed-Point Solutions of the Shapley Equation
Authors: Oscar Vega-Amaya
Venue: SIAM Journal on Control and Optimization (2003)

This paper deals with zero-sum average semi-Markov games with Borel state and action spaces, unbounded payoffs, and mean holding times. A solution to the Shapley equation is obtained via the Banach fixed-point theorem assuming that the model satisfies a Lyapunov-like condition, a growth hypothesis on the payoff function, and the mean holding times, besides standard continuity and compactness requirements.
Programming Models for Hybrid CPU/FPGA Chips
Authors: David Andrews, Douglas Niehaus, Peter Ashenden
Venue: Computer (2004)

Components that combine a CPU and reconfigurable logic gates need a programming model that abstracts the computational hardware.
Reducing the Number of Sequential Diagnosis Iterations in Hypercubes
Authors: Paolo Santi, Stefano Chessa
Venue: IEEE Transactions on Computers (2004)

Abstract--In this note, we use a vertex-isoperimetric inequality to show that the number of test and repair iterations needed to perform sequential diagnosis of d-dimensional hypercubes is upper bounded by d-r, where r\in\Theta(d). This result improves the best bound of d test and repair iterations previously known. Numerical evaluation has shown that the actual value of r ranges from 0.16d to 0.31d.
Topologically Faithful Fitting of Simple Closed Curves
Authors: Daniel Keren
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2004)

Abstract--Implicit representations of curves have certain advantages over explicit representation, one of them being the ability to determine with ease whether a point is inside or outside the curve (inside-outside functions). However, save for some special cases, it is not known how to construct implicit representations which are guaranteed to preserve the curve's topology. As a result, points may be erroneously classified with respect to the curve. The paper offers to overcome this problem by using a representation which is guaranteed to yield the correct topology of a simple closed curve by using homeomorphic mappings of the plane to itself. If such a map carries the curve onto the unit circle, then a point is inside the curve if and only if its image is inside the unit circle.
Honeypots: Catching the Insider Threat
Authors: Lance Spitzner
Venue: Proceedings of the 19th Annual Computer Security Applications Conference (2003)

In the past several years there has been extensiveresearch into honeypot technologies, primarily fordetection and information gathering against externalthreats. However, little research has been done for one ofthe most dangerous threats, the advance insider, thetrusted individual who knows your internal organization.These individuals are not after your systems, they areafter your information. This presentation discusses howhoneypot technologies can be used to detect, identify, andgather information on these specific threats.
Techniques for timing closure on high-speed field programmable gate arrays
Authors: Stephen Brown
Venue:  (2003)

The Field Programmable Gate Array (FPGA) has become a popular implementation medium for digital circuits due to its ability to be configured to realize a variety of different circuits. Although the configurable nature of FPGAs is very attractive, circuits implemented in FPGAs are almost an order of magnitude slower than their ASIC counterparts. Thus it has become increasingly difficult for users to realize realistic timing constraints for FPGA implementations. This is usually referred to as the &ldquo;timing closure&rdquo; problem. This thesis investigates methods for achieving timing closure for FPGA based designs. Two main techniques are studied in this dissertation. The first studies the effects of creating arbitrary mappings between the logical and physical hierarchy of a design. This method has shown an average of 12% speed improvement when used to map critical sections of logic to fast physical regions on the target device. The second technique tightly integrates netlist optimizations with the placement and routing steps of the FPGA CAD flow. The circuit is restructured with a suite of timing-driven optimizations to better cope with the routing delays inherent in FPGAs. The suite of optimizations includes sequential retiming, Shannon's decomposition theorem, and clock skew optimization. Each technique is applicable, depending on circuit characteristics, or they may all be used in concert. These restructuring techniques have shown an average speedup of up to 25%.
Applying associative retrieval techniques to alleviate the sparsity problem in collaborative filtering
Authors: Zan Huang, Hsinchun Chen, Daniel Zeng
Venue: ACM Transactions on Information Systems (TOIS) (2004)

Recommender systems are being widely applied in many application settings to suggest products, services, and information items to potential consumers. Collaborative filtering, the most successful recommendation approach, makes recommendations based on past transactions and feedback from consumers sharing similar interests. A major problem limiting the usefulness of collaborative filtering is the sparsity problem, which refers to a situation in which transactional or feedback data is sparse and insufficient to identify similarities in consumer interests. In this article, we propose to deal with this sparsity problem by applying an associative retrieval framework and related spreading activation algorithms to explore transitive associations among consumers through their past transactions and feedback. Such transitive associations are a valuable source of information to help infer consumer interests and can be explored to deal with the sparsity problem. To evaluate the effectiveness of our approach, we have conducted an experimental study using a data set from an online bookstore. We experimented with three spreading activation algorithms including a constrained Leaky Capacitor algorithm, a branch-and-bound serial symbolic search algorithm, and a Hopfield net parallel relaxation search algorithm. These algorithms were compared with several collaborative filtering approaches that do not consider the transitive associations: a simple graph search approach, two variations of the user-based approach, and an item-based approach. Our experimental results indicate that spreading activation-based approaches significantly outperformed the other collaborative filtering methods as measured by recommendation precision, recall, the F-measure, and the rank score. We also observed the over-activation effect of the spreading activation approach, that is, incorporating transitive associations with past transactional data that is not sparse may "dilute" the data used to infer user preferences and lead to degradation in recommendation performance.