ppxscal/embedding_network huggingface dataset:
A diversity maintaining population-based incremental learning algorithm
Authors: Mario Ventresca, Hamid R. Tizhoosh
Venue: Information Sciences: an International Journal (2008)

In this paper we propose a new probability update rule and sampling procedure for population-based incremental learning. These proposed methods are based on the concept of opposition as a means for controlling the amount of diversity within a given sample population. We prove that under this scheme we are able to asymptotically guarantee a higher diversity, which allows for a greater exploration of the search space. The presented probabilistic algorithm is specifically for applications in the binary domain. The benchmark data used for the experiments are commonly used deceptive and attractor basin functions as well as 10 common travelling salesman problem instances. Our experimental results focus on the effect of parameters and problem size on the accuracy of the algorithm as well as on a comparison to traditional population-based incremental learning. We show that the new algorithm is able to effectively utilize the increased diversity of opposition which leads to significantly improved results over traditional population-based incremental learning.
Concepts of Switching in the Time-Triggered Network-on-Chip
Authors: Christian Paukovits, Hermann Kopetz
Venue: Proceedings of the 2008 14th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2008)

This paper presents the concepts of switching in the Time-Triggered Network-on-Chip (TTNoC), which is the communication subsystem of the Time-Triggered System on-Chip (TTSoC) architecture. This includes the design of the switching components that make up the network-on-chip (NoC), as well as the switching algorithm applied in those components. Furthermore, we focus on the implications for the operation of the TTNoC entailed by these design choices, and deal with frequently used scenarios in a NoC, particularly multi-casting. Finally, we present results of a prototype implementation based on FPGA technology.
A novel hardware-oriented Kohonen SOM image compression algorithm and its FPGA implementation
Authors: W. Kurdthongmee
Venue: Journal of Systems Architecture: the EUROMICRO Journal (2008)

Kohonen self-organizing map (K-SOM) has proved to be suitable for lossy compression of digital images. The major drawback of the software implementation of this technique is its very computational intensive task. Fortunately, the structure is fairly easy to convert into hardware processing units executing in parallel. The resulting hardware system, however, consumes much of a microchip's internal resources, i.e. slice registers and look-up table units. This results in utilising more than a single microchip to realize the structure in pure hardware implementation. Previously proposed K-SOM realizations were mainly targetted on implementing on an application specific integrated circuit (ASIC) with low restriction on resource utilization. In this paper, we propose an alternative architecture of K-SOM suitable for moderate density FPGAs with acceptable image quality and frame rate. In addition, its hardware architecture and synthesis results are presented. The proposed K-SOM algorithm compromises between the image quality, the frame rate throughput, the FPGA's resource utilization and, additionally, the topological relationship among neural cells within the network. The architecture has been proved to be successfully synthesized on a single moderate resource FPGA with acceptable image quality and frame rate.
A Methodology for Analyzing Case Retrieval from a Clustered Case Memory
Authors: Albert Fornells, Elisabet Golobardes, Josep Maria Martorell, Josep Maria Garrell, Núria Macià, Ester Bernadó
Venue: Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2007)

Case retrieval from a clustered case memory consists in finding out the clusters most similar to the new input case, and then retrieving the cases from them. Although the computational time is improved, the accuracy rate may be degraded if the clusters are not representative enough due to data geometry. This paper proposes a methodology for allowing the expert to analyze the case retrieval strategies from a clustered case memory according to the required computational time improvement and the maximum accuracy reduction accepted. The mechanisms used to assess the data geometry are the complexity measures. This methodology is successfully tested on a case memory organized by a Self-Organization Map.
Power-efficient integrated cognitive and software radio system: architecture, algorithms, and protocols
Authors: Wayne Wolf
Venue:  (2008)

Software radio and cognitive radio have become very active research areas. Challenges of cognitive radio and software radio are their complexity and power consumption. Main stream research, unfortunately, focuses on individual components and only very few designs consider the entire system. Especially, the interaction between cognitive radio functions and software radio platform is usually ignored and the benefit of an integrated architecture is unaware. In this dissertation, we propose a power-efficient integrated cognitive and software radio architecture. This architecture is composed of four parts: software radio platform, software radio controls, cognitive radio functions, and communication protocols. Function-wise, this architecture includes spectrum sensing, signal reception, cognitive networks, and control algorithms. In each component of this architecture, we propose power-efficient and low-complexity algorithms. This new architecture is shown to be a complete and promising software/cognitive radio system.
Security, Cryptography and Directed Bigraphs
Authors: Davide Grohmann
Venue: Proceedings of the 4th international conference on Graph Transformations (2008)

Bigraphical reactive systems are an emerging graphical framework proposed by Milner and others [4,5,2,3] as a unifying theory of process models for distributed, concurrent and ubiquitous computing. A bigraphical reactive system consists of a category of bigraphs (usually generated over a given signature of controls) and a set of reaction rules. Bigraphs can be seen as representations of the possible configurations of the system, and the reaction rules specify how these configuration can evolve. The advantage of using bigraphical reactive systems is that they provide general results for deriving a labelled transition system automatically from the reaction rules, via the so-called IPO construction. Notably, the bisimulation on this transition system is always a congruence.
A Correction of Misstated Equations in Hespeler (2008)
Authors: Frank Hespeler
Venue: Computational Economics (2008)

This note presents corrections to some misstated equations in Hespeler (Comput Econ, 31, 207---223pp).
Protocol Modeling with Model Program Composition
Authors: Margus Veanes, Wolfram Schulte
Venue: Proceedings of the 28th IFIP WG 6.1 international conference on Formal Techniques for Networked and Distributed Systems (2008)

Designing and interoperability testing of distributed, application-level network protocols is complex. Windows, for example, supports currently more than 200 protocols, ranging from simple protocols for email exchange to complex ones for distributed file replication or real time communication. To fight this increasing complexity problem, we introduce a methodology and formal framework that uses model program composition to specify behavior of such protocols. A model program can be used to specify an increment of protocol functionality with a coherent purpose, which can be understood and analyzed separately. The overall behavior of a protocol can be defined by a composite model program, which defines how the individual parts interoperate.
Non-interleaving Semantics with Causality for Nondeterministic Dataflow
Authors: Oana Agrigoroaiei, Gabriel Ciobanu
Venue: Proceedings of the 5th international colloquium on Theoretical Aspects of Computing (2008)

We present a denotational model of nondeterministic dataflow in which an explicit notion of causality is introduced. We define a set of labelled flows over a set of fixed channels and two orders which induce cpo structures. Labelled flows are based on a conflict relation which allows to express several behaviours (configurations) at once. A netflow is a continuous function over configurations used to represent a dataflow network. We use a form of Galois connection in which such a function is the upper adjoint to correlate the possible outputs with their causes. The feedback operation is defined using a fixed point construction. Russell's example is used to show how this formal approach solves causal anomalies of nondeterministic dataflow.
Rao-Blackwellized Particle Filter for Human Appearance and Position Tracking
Authors: Jesús Martínez-Del-Rincón, Carlos Orrite-Uruñuela, Grégory Rogez
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I (2007)

In human motion analysis, the joint estimation of appearance, body pose and location parameters is not always tractable due to its huge computational cost. In this paper, we propose a Rao-Blackwellized Particle Filter for addressing the problem of human pose estimation and tracking. The advantage of the proposed approach is that Rao-Blackwellization allows the state variables to be splitted into two sets, being one of them analytically calculated from the posterior probability of the remaining ones. This procedure reduces the dimensionality of the Particle Filter, thus requiring fewer particles to achieve a similar tracking performance. In this manner, location and size over the image are obtained stochastically using colour and motion clues, whereas body pose is solved analytically applying learned human Point Distribution Models.
A Study of Recovering from Communication Failure Caused by Route Hijacking
Authors: Toshimitsu Ooshima, Mitsuho Tahara, Ritsu Kusaba, Souhei Majima, Satoshi Tajima, Yoshinori Kawamura, Ryousuke Narita
Venue: Proceedings of the 10th Asia-Pacific Network Operations and Management Symposium on Managing Next Generation Networks and Services (2007)

In this paper, we discussed methods for recovering from communication failures due to route hijacking. Looking ahead we intend to pursue further work on systemization, authentication, and evaluation.
New algorithm to enable 400+ TFlop/s sustained performance in simulations of disorder effects in high-Tc superconductors
Authors: G. Alvarez, M. S. Summers, D. E. Maxwell, M. Eisenbach, J. S. Meredith, J. M. Larkin, J. Levesque, T. A. Maier, P. R. C. Kent, E. F. D'Azevedo, T. C. Schulthess
Venue: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (2008)

Staggering computational and algorithmic advances in recent years now make possible systematic Quantum Monte Carlo (QMC) simulations of high temperature (high-Tc) superconductivity in a microscopic model, the two dimensional (2D) Hubbard model, with parameters relevant to the cuprate materials. Here we report the algorithmic and computational advances that enable us to study the effect of disorder and nano-scale inhomogeneities on the pair-formation and the superconducting transition temperature necessary to understand real materials. The simulation code is written with a generic and extensible approach and is tuned to perform well at scale. Significant algorithmic improvements have been made to make effective use of current supercomputing architectures. By implementing delayed Monte Carlo updates and a mixed single-/double precision mode, we are able to dramatically increase the efficiency of the code. On the Cray XT4 systems of the Oak Ridge National Laboratory (ORNL), for example, we currently run production jobs on 31 thousand processors and thereby routinely achieve a sustained performance that exceeds 200 TFIop/s. On a system with 49 thousand processors we achieved a sustained performance of 409 TFIop/s. We present a study of how random disorder in the effective Coulomb interaction strength affects the superconducting transition temperature in the Hubbard model.
Apprentice-Based Learning Via Integrated Lectures and Assignments
Authors: Michael Kölling, David J. Barnes
Venue: Reflections on the Teaching of Programming: Methods and Implementations (2008)

Various methods have been proposed in the past to improve student learning by introducing new styles of working with assignments. These include problem-based learning, the use of case studies and apprenticeship. In most courses, however, these proposals have not resulted in a widespread, significant change of teaching methods. Most institutions still use a traditional lecture/lab class approach with a strong separation of tasks between them.In this chapter, we propose an approach to teaching introductory programming in Java that integrates assignments and lectures, using elements of all three approaches mentioned above. In addition, we show how the BlueJ interactive programming environment can be used to provide the type of support that has hitherto hindered the widespread take-up of these approaches. We arrive at a teaching method that is motivating, effective and relatively easy to put into practice.
MPIBlib: Benchmarking MPI Communications for Parallel Computing on Homogeneous and Heterogeneous Clusters
Authors: Alexey Lastovetsky, Vladimir Rychkov, Maureen O'Flynn
Venue: Proceedings of the 15th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2008)

In this paper, we analyze existing MPI benchmarking suites, focusing on two restrictions that prevent them from a wider use in applications and programming systems. The first is a single method of measurement of the execution time of MPI communications implemented by each of the suites. The second one is the design of the suites in the form of a standalone executable program that cannot be easily integrated into applications or programming systems. We present a more flexible benchmarking package, MPIBlib, that provides multiple methods of measurement, both operation-independent and operation-specific. This package can be used not only for benchmarking but also as a library in applications and programming systems for communication performance modeling and optimization of MPI operations.
MIRACLE at ImageCLEFmed 2007: Merging Textual and Visual Strategies to Improve Medical Image Retrieval
Authors: Julio Villena-Román, Sara Lana-Serrano, José Carlos González-Cristóbal
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

This paper describes the participation of MIRACLE research consortium at the ImageCLEF Medical Image Retrieval task of ImageCLEF 2007. For this campaign, our challenge was to research on different merging strategies, i.e. methods of combination of textual and visual retrieval techniques. We have focused on the idea of performing all possible combinations of well-known textual and visual techniques in order to find which ones offer the best results in terms of MAP and analyze if the combined results may improve the individual ones.
A Constrained Non-rigid Registration Algorithm for Use in Prostate Image-Guided Radiotherapy
Authors: William H. Greene, Sudhakar Chelikani, Kailas Purushothaman, Zhe Chen, Jonathan P. Knisely, Lawrence H. Staib, Xenophon Papademetris, Jim Duncan
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

A constrained non-rigid registration (CNRR) algorithm for use in updating prostate external beam image-guided radiotherapy treatment plans is presented in this paper. The developed algorithm is based on a multi-resolution cubic B-spline FFD transformation and has been tested and verified using 3D CT images from 10 sets of real patient data acquired from 4 different patients on different treatment days. The registration can be constrained to any combination of the prostate, rectum, bladder, pelvis, left femur, and right femur. The CNRR was tested with 5 different combinations of constraints and each test significantly outperformed both rigid and non-rigid registration at aligning constrained bones and critical organs. The CNRR was then used to update the treatment plans to account for articulated, rigid bone motion and non-rigid organ deformation. Each updated treatment plan outperformed the original treatment plan by increasing radiation dosage to the prostate and lowering radiation dosage to the rectum and bladder.
Event Detection by HMM, SVM and ANN: A Comparative Study
Authors: Carla Lopes, Fernando Perdigão
Venue: Proceedings of the 8th international conference on Computational Processing of the Portuguese Language (2008)

The goal of speech event detection (SED) is to reveal the presence of important elements in the speech signal for different sound classes. In a speech recognition system, events can be combined to detect phones, words or sentences, or to identify landmarks with which a decoder could be synchronized. In this paper, we introduce three popular classification techniques, HMM, SVM, ANN and Non-Negative Matrix Deconvolution (NMD) for SED. The main purpose of this paper is to compare the performance of (1) HMM, (2) hybrid SVM/NMD (3) hybrid SVM/HMM and (4) hybrid MLP /HMM approaches to SED and emphasize approaches to reaching lower Event Error Rates (EER). It was found that the hybrid SVM/HMM approach outperformed the HMM system. Regarding EER, an improvement of 6% was achieved. The hybrid MLP/HMM got the best EER rate. Improvements of 11% and 8% were found in comparison with the HMM and hybrid SVM/HMM event detector, respectively.
Teaching the Importance of Communication in IT
Authors: Jay Liebowitz
Venue: IT Professional (2004)

A new course focuses on managing the IT enterprise in a modern organization, paying particular attention to effective communication.
Haptic Pottery Modeling Using Circular Sector Element Method
Authors: Jaebong Lee, Gabjong Han, Seungmoon Choi
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

This paper presents an efficient modeling system of virtual pottery in which the user can deform a body of virtual clay with a haptic tool. The clay body is represented with a set of circular sector elements based on the cylindrical symmetry of pottery. The circular sector element method allows much finer spatial resolution for modeling than previous techniques. Also described are efficient algorithms for collision detection and response where the viscosity of virtual clay is simulated along with the friction due to the rotating potter's wheel. Empirical evaluation showed that the modeling system is computationally efficient, is intuitive to use, and provides convincing model deformation and force feedback.
Profiling a multicast video stream: An evaluation and implementation platform
Authors: Michael Hempel, Hamid Sharif
Venue: Journal of Computational Methods in Sciences and Engineering (2005)

In this article, we present a quantitative approach to develop an application suite to evaluate and develop a streaming video network protocol for multicast video streams. This study is based on our project of streaming the three educational channels of SCOLA TV signals over Internet2. As a part of this project, a multicast reflector tool was developed to collect and analyze the network parameters for the end-to-end quality of service. The collected data from the reflector is an integral part of the test bed development for streaming protocols. Throughout the course of analyzing the stream's characteristics, we observed that the underlying network topology plays a significant role in successfully delivering streaming content. It also became apparent that there are shortcomings in streaming content solution such as Windows Media Encoder that will be addressed in this paper.
A Fuzzy Neural-Network-Driven Weighting System for Electric Shovel
Authors: Yingkui Gu, Luheng Wu, Shuyun Tang
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

In order to improve the weighting precision and optimize the loading of trucks and the production efficiency of electric shovel, an online weighting model is developed by using fuzzy logic and improved T-S neural network in this paper. The weighting model is established based on the mechanics analysis of the electric shovel firstly. Then, a T-S fuzzy neural network model is established to obtain the influence coefficient through training large numbers of samples. Applications show that by using the presented weighting model, it not only can decrease the fuzzy and uncertain factors in the weighting process, but also can improve the production and management efficiency.
UAIC Participation at AVE 2007
Authors: Adrian Iftene, Alexandra Balahur-Dobrescu
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

Textual Entailment Recognition (RTE) is a recently proposed task, aiming at capturing the means through which textual inferences can be made. Moreover, using such a module is meant to contribute to the increase in performance of many NLP applications, such as Summarization, Information Retrieval or Question Answering, both for answer ranking as well as for answer validation. This article presents the manner in which we used the TE system built for the RTE3 competition this year for the AVE exercise. We describe the steps followed in building the patterns for question transformation, the generation of the corresponding hypotheses and finally for answer ranking. We conclude by presenting an overview of the performance obtained by this approach and a critical analysis of the errors obtained.
State Isomorphism in Model Programs with Abstract Data Structures
Authors: Margus Veanes, Juhan Ernits, Colin Campbell
Venue: Proceedings of the 27th IFIP WG 6.1 international conference on Formal Techniques for Networked and Distributed Systems (2007)

Modeling software features with model programs in C# is a way of formalizing software requirements that lends itself to automated analysis such as model-based testing. Unordered structures like sets and maps provide a useful abstract view of system state within a model program and greatly reduce the number of states that must be considered during analysis. Similarly, a technique called linearization reduces the number of states that must be considered by identifying isomorphic states, or states that are identical except for reserve element choice (such as the choice of object IDs for instances of classes). Unfortunately, linearization does not work on unordered structures such as sets. The problem turns into graph isomorphism, for which no polynomial time solution is known. In this paper we discuss the issue of state isomorphism in the presence of unordered structures and give a practical approach that overcomes some of the algorithmic limitations.