ppxscal/embedding_network huggingface dataset:
Latency-Optimized Parallelization of the FMM Near-Field Computations
Authors: Ivo Kabadshow, Bruno Lang
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

In this paper we present a new parallelization scheme for the FMM near-field. The parallelization is based on the Global Arrays Toolkit and uses one-sided communication with overlapping. It employs a purely static load-balancing approach to minimize the number of communication steps and benefits from a maximum utilization of data locality. In contrast to other implementations the communication is initiated by the process owning the data via a put call, not the process receiving the data (via a get call).
Installation of the First Production 701
Authors: D. E. Rosenheim
Venue: IEEE Annals of the History of Computing (1983)

Editor's Note: Donald E. Rosenheim, now director of the IBM San Jose Research Laboratory, was an instructor of the first 701 Customer Engineering Class. In his paper he refers to cathode-ray-tube memory, and the accompanying picture shows him with F. C. Williams and others. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Circuit Complexity of Regular Languages
Authors: Michal Koucký
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

We survey our current knowledge of circuit complexity of regular languages. We show that regular languages are of interest as languages providing understanding of different circuit classes. We also prove that regular languages that are in AC0 and ACC0 are all computable by almost linear size circuits, extending the result of Chandra et al.[5].
The Design of Software Architecture for E-Learning Platforms
Authors: Dongdai Zhou, Zhuo Zhang, Shaochun Zhong, Pan Xie
Venue: Proceedings of the 3rd international conference on Technologies for E-Learning and Digital Entertainment (2008)

Although e-learning have been widely used at schools, universities and other institutes, some obvious shortcomings have been recognized. Current e-learning platforms are developed using existing technologies and compensate for the disadvantages of traditional education methods. However, most of them are not flexible and efficient enough to support real world teaching and learning. In this paper, we present flexible and hierarchical reusable dynamical software architecture for e-learning platforms and an approach of software components integration based web services. We also analyze how this architecture can facilitate a web-based e-learning system development.
An efficient compression scheme for data communication which uses a new family of self-organizing binary search trees
Authors: Luis Rueda, B. John Oommen
Venue: International Journal of Communication Systems (2008)

In this paper, we demonstrate that we can effectively use the results from the field of adaptive self-organizing data structures in enhancing compression schemes. Unlike adaptive lists, which have already been used in compression, to the best of our knowledge, adaptive self-organizing trees have not been used in this regard. To achieve this, we introduce a new data structure, the partitioning binary search tree (PBST) which, although based on the well-known binary search tree (BST), also appropriately partitions the data elements into mutually exclusive sets. When used in conjunction with Fano encoding, the PBST leads to the so-called Fano binary search tree (FBST), which, indeed, incorporates the required Fano coding (nearly equal probability) property into the BST. We demonstrate how both the PBST and the FBST can be maintained adaptively and in a self-organizing manner. The updating procedure that converts a PBST into an FBST, and the corresponding new tree-based operators, namely the shift-to-left and the shift-to-right operators, are explicitly presented. The encoding and decoding procedures that also update the FBST have been implemented and rigorously tested. Our empirical results on the files of the well-known benchmarks, the Calgary and Canterbury Corpora, show that the adaptive Fano coding using FBSTs, the Huffman, and the greedy adaptive Fano coding achieve similar compression ratios. However, in terms of encoding-decoding speed, the new scheme is much faster than the latter two in the encoding phase, and they achieve approximately the same speed in the decoding phase. We believe that the same philosophy, namely that of using an adaptive self-organizing BST to maintain the frequencies, can also be utilized for other data encoding mechanisms, even as the Fenwick scheme has been used in arithmetic coding. Copyright &copy; 2008 John Wiley & Sons, Ltd.
Truncation Error Estimate on Random Signals by Local Average
Authors: Gaiyun He, Zhanjie Song, Deyun Yang, Jianhua Zhu
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

Since signals are often of random characters, random signals play an important role in signal processing. We show that the bandlimited wide sense stationary stochastic process can be approximated by Shannon sampling theorem on local averages. Explicit truncation error bounds are given.
Incorporating Domain Knowledge into a Min-Max Modular Support Vector Machine for Protein Subcellular Localization
Authors: Yang Yang, Bao-Liang Lu
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

As biological sequences and various annotation data grow rapidly in public databases, the classification problems become larger and more complicated. New classifier designs are necessitated. Besides, how to incorporate some explicit domain knowledge into learning methods is also a big issue. In this paper, we adopt a modular classifier, min-max modular support vector machine (M3-SVM) to solve protein subcellular localization problem, and use the domain knowledge of taxonomy information to guide the task decomposition. Experimental results show that M3-SVM can maintain the overall accuracy and improve location average accuracy compared with traditional SVMs. The taxonomy decomposition is superior to other decomposition methods on a majority of the classes. The results also demonstrate a speedup on training time of M3-SVM compared with traditional SVMs.
Ensemble Approaches to Facial Action Unit Classification
Authors: Terry Windeatt, Kaushala Dias
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

Facial action unit (au) classification is an approach to face expression recognition that decouples the recognition of expression from individual actions. In this paper, upper face aus are classified using an ensemble of MLP (Multi-layer perceptron) base classifiers with feature ranking based on PCA components. This approach is compared experimentally with other popular feature-ranking methods applied to Gabor features. Experimental results on Cohn-Kanade database demonstrate that the MLP ensemble is relatively insensitive to the feature-ranking method but optimized PCA features achieve lowest error rate. When posed as a multi-class problem using Error-Correcting-Output-Coding (ECOC), error rates are comparable to two-class problems (one-versus-rest) when the number of features and base classifier are optimized.
Mathematical models of phase syncronization systems with quadrature and phase-quadrature units
Authors: G. A. Leonov
Venue: Automation and Remote Control (2008)

Integro-differential and differential equations are derived for PLL systems with squarer and for the Costas loop. The equations are based on special asymptotic methods of high-frequency harmonic and pulse oscillations analysis. Methods to compute phase detector characteristics are proposed. New classes of such characteristics are introduced for highfrequency pulse clocks.
An Enhanced Theory of Infinite Time Register Machines
Authors: Peter Koepke, Russell Miller
Venue: Proceedings of the 4th conference on Computability in Europe: Logic and Theory of Algorithms (2008)

Infinite time register machines (ITRMs) are register machines which act on natural numbers and which are allowed to run for arbitrarily many ordinal steps. Successor steps are determined by standard register machine commands. At limit times a register content is defined as a $\liminf$ of previous register contents, if that limit is finite; otherwise the register is reset to 0. (A previous weaker version of infinitary register machines, in [6], would halt without a result in case of such an overflow.) The theory of infinite time register machines has similarities to the infinite time Turing machines (ITTMs) of Hamkins and Lewis. Indeed ITRMs can decide all $\Pi^1_1$ sets, yet they are strictly weaker than ITTMs.
Semantically Configurable Code Generation
Authors: Adam Prout, Joanne M. Atlee, Nancy A. Day, Pourya Shaker
Venue: Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems (2008)

In model-driven engineering (MDE), software development is centred around a formal description (model) of the proposed software system, and other software artifacts are derived directly from the model. We are investigating semantically configurable MDE, in which specifiers are able to configure the semantics of their models. The goal of this work is to provide a modelling environment that offers flexible, configurable modelling notations, so that specifiers are better able to represent their ideas, and yet still provides the types of analysis tools and code generators normally associated with model-driven engineering. In this paper, we present a semantically configurable code-generator generator, which creates a Java-code generator for a modelling notation given the notation's semantics expressed as a set of parameter values. We are able to simulate multiple different model-based code generators, though at present the performance of our generated code is about an order of magnitude slower than that produced by commercial-grade generators.
Linguistic Summarization of Time Series Under Different Granulation of Describing Features
Authors: Janusz Kacprzyk, Anna Wilbik, Sławomir Zadrożny
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

We consider an extension to a new approach to the linguistic summarization of time series data proposed in our previous papers. We summarize trends identified here with straight segments of a piecewise linear approximation of time series. Then we employ, as a set of features, the duration, dynamics of change and variability, and assume different, human consistent granulations of their values. The problem boils down to a linguistic quantifier driven aggregation of partial trends that is done via the classic Zadeh's calculus of linguistically quantified propositions but with different t-norms. We show an application to linguistic summarization of time series data on daily quotations of an investment fund over an eight year period.
Understanding the Environment Through Wireless Sensor Networks
Authors: Salvatore Gaglio, Luca Gatani, Giuseppe Lo Re, Marco Ortolani
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

This paper presents a new cognitive architecture for extracting meaningful, high-level information from the environment, starting from the raw data collected by a Wireless Sensor Network. The proposed framework is capable of building rich internal representation of the sensed environment by means of intelligent data processing and correlation. Furthermore, our approach aims at integrating the connectionist, data-driven model with the symbolic one, that uses a high-level knowledge about the domain to drive the environment interpretation. To this aim, the framework exploits the notion of conceptual spaces, adopting a conceptual layer between the subsymbolic one, that processes sensory data, and the symbolic one, that describes the environment by means of a high level language; this intermediate layer plays the key role of anchoring the upper layer symbols. In order to highlight the characteristics of the proposed framework, we also describe a sample application, aiming at monitoring a forest through a Wireless Sensor Network, in order to timely detect the presence of fire.
Impact of memory size on graph exploration capability
Authors: Pierre Fraigniaud, David Ilcinkas, Andrzej Pelc
Venue: Discrete Applied Mathematics (2008)

A mobile agent (robot), modeled as a finite automaton, has to visit all nodes of a regular graph. How does the memory size of the agent (the number of states of the automaton) influence its exploration capability? In particular, does every increase of the memory size enable an agent to explore more graphs? We give a partial answer to this problem by showing that a strict gain of the exploration power can be obtained by a polynomial increase of the number of states. We also show that, for automata with few states, the increase of memory by even one state results in the capability of exploring more graphs.
European Developments in the Design and Implementation of Training for eInclusion
Authors: Gill Whitney, Suzette Keith
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

Information and communication technologies offer an important opportunity for social, political and economic engagement of older and disabled people. The successful implementation of a policy on eInclusion is dependent on understanding the principles, practicalities and processes of a 'design for all' programme. The aim of this paper is to describe those activities of the European Sixth Framework Programme IST Coordination Action "Design for All @ eInclusion" which focus on training and education. The paper will focus on the need for students of ICT to learn more about the requirements of older and disabled users, the training needs with respect to higher and vocational education and the diverse ways in which those needs are being meet around Europe. The paper will describe a selection of case studies of best practice teaching in this area.
Perturbation based privacy preserving data mining techniques for real-world data
Authors: B. Thuraisingham, M. Kantarcioglu
Venue:  (2008)

The Perturbation method has been extensively studied for privacy preserving data mining. In this method, random noise from a known distribution is added to the privacy sensitive data before the data is sent to the data miner. Subsequently, the data miner reconstructs an approximation to the original data distribution from the perturbed data and uses the reconstructed distribution for data mining purposes. Due to the addition of noise, loss of information versus preservation of privacy is always a trade off in the perturbation-based approaches. The question is, to what extent are the users willing to compromise their privacy? This is a choice that changes from individual to individual. Different individuals may have different attitudes towards privacy based on customs and cultures. Unfortunately, current perturbation based privacy preserving data mining techniques do not allow the individuals to choose their desired privacy levels. This is a drawback as privacy is a personal choice. In this dissertation, we propose an individually adaptable perturbation model, which enables the individuals to choose their own privacy levels. The effectiveness of our new approach is demonstrated by various experiments conducted on both synthetic and real-world data sets. Reconstruction of original distribution has be questioned for potential privacy breaches. After investigating the reconstruction step in detail, we also question the applicability of this approach deal with the real-word data. In this dissertation, we propose a new perturbation based technique. In our solution, instead of rebuilding the original data distribution, we modify the data mining algorithms so that they can be directly used on the perturbed data. In other words, we directly build a classifier for the original data set from the perturbed training data set. Our approach is especially suitable for the scenarios where the reconstruction of the original data distribution may not be successful, due to the limited amount of training data.
Improving Routing Reliability on Wireless Sensors Network with Emergency Paths
Authors: Bastien Mainaud, Mariem Zekri, Hossam Afifi
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

One of the most important issues in Wireless Sensor Networks is reliable communication. In this article, we present MAODV-SIM, a routing protocol that increases the reliability in a sensor network and which is based on AODV. Our protocol introduces multipath and signal intensity metric.We need to define what reliability is? How can we say that a protocol is more reliable than another? Which benchmark can be used?Multipath is needed to determine emergency routes that are required to find a new path to the destination if the first one fails. Then,to choose more reliable routes we use a different metric, the signal intensity metric which is based on 802.15.4 standard that defines two physical measurements : The Link Quality Indication(LQI) and the Energy Detection (ED). Simulations show that MAODV-SIM increases reliability in sensor network.
Knowledge support and automation for performance analysis with PerfExplorer 2.0
Authors: Kevin A. Huck, Allen D. Malony Sameer Shende Alan Morris
Venue: Scientific Programming (2008)

The integration of scalable performance analysis in parallel development tools is difficult. The potential size of data sets and the need to compare results from multiple experiments presents a challenge to manage and process the information. Simply to characterize the performance of parallel applications running on potentially hundreds of thousands of processor cores requires new scalable analysis techniques. Furthermore, many exploratory analysis processes are repeatable and could be automated, but are now implemented as manual procedures. In this paper, we will discuss the current version of PerfExplorer, a performance analysis framework which provides dimension reduction, clustering and correlation analysis of individual trails of large dimensions, and can perform relative performance analysis between multiple application executions. PerfExplorer analysis processes can be captured in the form of Python scripts, automating what would otherwise be time-consuming tasks. We will give examples of large-scale analysis results, and discuss the future development of the framework, including the encoding and processing of expert performance rules, and the increasing use of performance metadata.
Incremental Evolution of Animats' Behaviors as a Multi-objective Optimization
Authors: Jean-Baptiste Mouret, Stéphane Doncieux
Venue: Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats (2008)

Evolutionary algorithms have been successfully used to create controllers for many animats. However, intuitive fitness functions like the survival time of the animat, often do not lead to interesting results because of the bootstrap problem, arguably one of the main challenges in evolutionary robotics: if all the individuals perform equally poorly, the evolutionary process cannot start. To overcome this problem, many authors defined ordered sub-tasks to bootstrap the process, leading to an incremental evolution scheme. Published methods require a deep knowledge of the underlying structure of the analyzed task, which is often not available to the experimenter. In this paper, we propose a new incremental scheme based on multi-objective evolution. This process is able to automatically switch between each sub-task resolution and does not require to order them. The proposed method has been successfully tested on the evolution of a neuro-controller for a complex-light seeking simulated robot, involving 8 sub-tasks.
Crawling Bug Tracker for Semantic Bug Search
Authors: Ha Manh Tran, Georgi Chulkov, Jürgen Schönwälder
Venue: Proceedings of the 19th IFIP/IEEE international workshop on Distributed Systems: Operations and Management: Managing Large-Scale Service Deployment (2008)

The Web has become an important knowledge source for resolving system installation problems and for working around software bugs. In particular, web-based bug tracking systems offer large archives of useful troubleshooting advice. However, searching bug tracking systems can be time consuming since generic search engines do not take advantage of the semi-structured knowledge recorded in bug tracking systems. We present work towards a semantics-based bug search system which tries to take advantage of the semi-structured data found in many widely used bug tracking systems. We present a study of bug tracking systems and we describe how to crawl them in order to extract semi-structured data. We describe a unified data model to store bug tracking data. The model has been derived from the analysis of the most popular systems. Finally, we describe how the crawled data can be fed into a semantic search engine to facilitate semantic search.
Using Gavish-Grave LP to Formulate the Directed Black and White Traveling Salesman Problem
Authors: He Jiang, Xianchao Zhang, Mingchu Li, Haoyang Che
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

The black and white traveling salesman problem (BWTSP) is a new class of NP-hard problem arising from work on airline scheduling and telecommunication fiber networks. The existing Ghiani LP for the undirected BWTSP contains an exponential number of constraints. For a special case of the directed BWTSP whose L = + ¿, the LP with polynomial number of constraints could be obtained by transforming it to an asymmetric traveling salesman problem with replenishment arcs (RATSP), whereas there exists no LP for the directed BWTSP in its general form. This paper proposes a LP with 3n 2 + 2n constraints only for the directed BWTSP in such a way that, by reducing the problem to an asymmetric traveling salesman problem (ATSP), we add n 2 cardinality constraints and n 2 length constraints to the existing Gavish-Grave LP for the ATSP. The new LP is also valid for the undirected BWTSP when viewed as a special case of the directed BWTSP.
The complexity of the algorithms for the image recognition and classification (IRC)
Authors: Ioan Ispas, Eduard Franti, Florin Lazo
Venue: Proceedings of the WSEAS International Conference on Applied Computing Conference (2008)

The problem of the image recognition and classification (IRC) based on the pattern recognition is of a strategic importance in lots of domains. Our contribution consists in the foundation of the complexity of the algorithms for image recognition and classification. This will help us issue some precise statements on the computational difficulty of the problem of the image recognition and classification (IRC).
Quaternary Unequal Error Protection Codes
Authors: Ludo Tolhuizen
Venue: Proceedings of the 2nd international Castle meeting on Coding Theory and Applications (2008)

We consider codes that offer unequal error protection to different information symbols, as measured by the so-called separation vector (a generalisation of the minimum Hamming distance).We determine the parameters of all optimal linear quaternary codes of length at most eleven.