ppxscal/embedding_network huggingface dataset:
Characterization of particle swarm optimization with diversive curiosity
Authors: Hong Zhang, Masumi Ishikawa
Venue: Neural Computing and Applications (2009)

For obtaining superior search performance in particle swarm optimization (PSO), we proposed particle swarm optimization with diversive curiosity (PSO/DC). The mechanism of diversive curiosity in PSO can prevent premature convergence and ensure exploration. To clarify the characteristics of PSO/DC, we estimated the range for appropriate parameter values, and investigated the trade-off between exploration and exploitation. Applications of the proposed method to a two-dimensional multimodal optimization problem and a suite of five-dimensional benchmark problems well demonstrate its effectiveness. Our experimental results basically accord with the findings in psychology, i.e., diversive curiosity being prone to exploration and anxiety.
Anti-periodic solutions for a class of Cohen-Grossberg neural networks
Authors: Shuhua Gong
Venue: Computers Mathematics with Applications (2009)

In this paper, Cohen-Grossberg neural networks (CGNNs) with delays are considered. Some new sufficient conditions for the existence and exponential stability of anti-periodic solutions are established.
A simulation of the sport small arms trigger mechanisms
Authors: Martin Macko
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

This article deals with the simulation of the sport small arms trigger mechanisms. A right function of the trigger mechanism is an important factor, which influences a shooting accuracy. It is needful to simulate a trigger mechanism function to achieve a right design parameter values. From point of view a physic analysis: the trigger mechanisms are the specific part of the solid figures, which don't allow to use neither dynamical method nor only statical method for their computing.
A New Approach to Improving ICA-Based Models for the Classification of Microarray Data
Authors: Kun-Hong Liu, Bo Li, Jun Zhang, Ji-Xiang Du
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Inspired by the idea of ensemble feature selection, we design an ICA based ensemble learning system to fully utilize the difference among different IC sets. Firstly, some IC sets are generated by different ICA transformations. A multi-objective genetic algorithm (MOGA) is then designed to select different biologically significant IC subsets from these IC sets, which are applied to build base classifiers. In addition, a global-recording technique is designed to record the best IC subsets of each IC set discovered by the MOGA into a global-recording list. When MOGA stops, all individuals in the list are deployed to train base classifiers. The base classifiers generated by these schemes are fused by the majority vote rule. Three microarray datasets are used to test the ensemble systems, and the corresponding results demonstrate that two ensemble schemes can improve the performance of the ICA based classification model.
A new algorithm for multiple key interpolation search in uniform list of numbers
Authors: Ahmed Tarek
Venue: Proceedings of the international conference on Computational and information science 2009 (2009)

In this paper, a new algorithm for multiple key interpolation search is proposed. The idea pertaining to the multiple key Interpolation search in a given list of elements is based on the concept that the algorithm searches for each key from a sorted list of m different keys starting with the first key by predicting the next possible position of the key currently under consideration in a relatively larger list, which is based on a linear interpolation of the current key, and the values at the end of the current search interval in that larger list. Once a key is identified at a particular index position, the next key search interval starts at the index position following it, and the elementary interval considered is the next index through the last of the original list. However, in performing the interpolation search with a particular key, the index values at the end of the elementary interval considered are subsequently adjusted in narrowing down the search efforts depending upon the projected value of the current key index position, which is computed using a linear interpolation. Basically, it is narrowing down the interval of the straight line in linear interpolation applied to a key search at each iteration, such that eventually the straight line segment converges to a single point index value, which is the index of the search key currently under consideration. The convergence of the straight line segments depends on the uniformity in the distribution of elements within the list, where the multiple key interpolation search technique is being applied. This concept is analogous to searching for multiple words in lexicographical sequence inside a dictionary, where one does not just blindly select the middle page of each search area, but rather decides where it is most likely to be judging by the current page range limits. As linear interpolation is being considered with the multiple key interpolation search, therefore, the search is largely dependent on the slopes of the straight lines during the entire search process. The slopes of the straight lines vary from range-to-range during the search process for non-uniformly distributed list elements where the algorithm is being applied.
Spatio-Featural Scale-Space
Authors: Michael Felsberg
Venue: Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision (2009)

Linear scale-space theory is the fundamental building block for many approaches to image processing like pyramids or scale-selection. However, linear smoothing does not preserve image structures very well and thus non-linear techniques are mostly applied for image enhancement. A different perspective is given in the framework of channel-smoothing, where the feature domain is not considered as a linear space, but it is decomposed into local basis functions. One major drawback is the larger memory requirement for this type of representation, which is avoided if the channel representation is subsampled in the spatial domain. This general type of feature representation is called channel-coded feature map (CCFM) in the literature and a special case using linear channels is the SIFT descriptor. For computing CCFMs the spatial resolution and the feature resolution need to be selected.In this paper, we focus on the spatio-featural scale-space from a scale-selection perspective. We propose a coupled scheme for selecting the spatial and the featural scales. The scheme is based on an analysis of lower bounds for the product of uncertainties, which is summarized in a theorem about a spatio-featural uncertainty relation. As a practical application of the derived theory, we reconstruct images from CCFMs with resolutions according to our theory. The results are very similar to the results of non-linear evolution schemes, but our algorithm has the fundamental advantage of being non-iterative. Any level of smoothing can be achieved with about the same computational effort.
Technical Section: A new construction of smooth surfaces from triangle meshes using parametric pseudo-manifolds
Authors: Marcelo Siqueira, Dianna Xu, Jean Gallier, Luis Gustavo Nonato, Dimas Martínez Morera, Luiz Velho
Venue: Computers and Graphics (2009)

We introduce a new manifold-based construction for fitting a smooth surface to a triangle mesh of arbitrary topology. Our construction combines in novel ways most of the best features of previous constructions and, thus, it fills the gap left by them. We also introduce a theoretical framework that provides a sound justification for the correctness of our construction. Finally, we demonstrate the effectiveness of our manifold-based construction with a few concrete examples.
Design of robust fuzzy logic controllers for complex non-linear processes with time delay
Authors: Snejana Yordanova
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

The progress of industrial applications of fuzzy logic controllers (FLCs) for high performance control of complex, non-linear, time-varying processes, sets demands for their design - to be laid on theoretical grounds, to be general and simple, to bind together system robustness, stability and performance in the design objective as a guarantee for practical feasibility. The aim of this investigation is to develop and implement PI-like FLCs for robust control of complex industrial plants with time delay. The suggested simple and objective FLC design and parameter tuning procedures are based on the derived in previous work robust stability and robust performance criteria as modification of Popov stability criterion for the case of a fuzzy control system accounting also for system robustness. The data required is a simple approximate nominal plant model and a plant uncertainty model, both estimated by experts. First, a Mamdani incremental or a position PI single input fuzzy controller (SI FC) is designed with a fuzzy unit (FU) - sector bounded static non-linearity, and a LTI dynamic part. Next, a two input incremental PI FLC is developed on the basis of the du-e projection of the FLC control curve. Further a Sugeno neural-fuzzy plant predictor is designed and embedded in the control system feedback in order to reduce the effect of the plant time delay. The design procedures are applied to various industrial plants. Results from simulation and real time control using MATLABk™ allow to assess control system performance and to compare it with the performance of systems with ordinary PI controller.
Deployment and management of large planar reflectarray antennas simulation on grid
Authors: Rémi Sharrock, Fadi Khalil, Thierry Monteil, Hervé Aubert, Fabio Cocccetti, Patricia Stolf, Laurent Broto, Robert Plana
Venue: Proceedings of the 7th international workshop on Challenges of large applications in distributed environments (2009)

Nowadays, scientists are interested in using computer grids to run their specific domain applications. Nevertheless the difficulty for non expert in computer science to run those applications on a high number of nodes discourages them. This paper deals with the deployment and the management of an electromagnetic simulator on a computer grid, by using the TUNe autonomic middleware. First, we describe the simulator and how to make it work with TUNe. Then, we measure TUNe's performance during specific phases: deployment, starting and undeployment. Moreover, some capabilities like automatic repair of applications in case of failure are shown.
High speed and secure optical CDMA-based passive optical networks
Authors: Chao-Chin Yang
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2009)

One bi-directional passive optical network (PON) based on optical code-division multiple access with interference elimination is proposed. By combining with wavelength division multiplexing (WDM) technique, the proposed scheme alleviates the noise arising during photo-detecting process in the PON. Therefore, the bit error rate performance is improved, which is demonstrated by the results of performance analysis. In addition, simple and low cost encoding/decoding structures with small sizes in the optical line terminal are proposed, and they can cooperate with the dynamic codeword assignment scheme to provide a more secure signal transmission in the PONs.
A Fast Algorithm for 2-D ARMA Parameters Estimation
Authors: Zhipo Deng, Youshen Xia
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

This paper proposed a fast algorithm for 2-D ARMA parameter estimation under noise environments. The proposed algorithm is based on a kind of inverse filter technique for the approximation of random excitation. The proposed algorithm only solves a low order 2-D AR system for the 2-D ARMA parameter. In contrast with Zhang and Cheng 's and Kizilkaya and Kayran's algorithms for 2-D ARMA parameter estimation, the proposed algorithm considers the noisy observation and is more suitable for practical applications. Moreover, the proposed algorithm has a fast speed due to a low computational cost. Simulation results show that the proposed algorithm can obtain more accurate estimates with a faster speed than the two algorithms.
Comparative study of clustering algorithms on textual databases - Clustering of curricula vitae into comptency-based groups to support knowledge management
Authors: Sebastian R. Spiegler
Venue:  (2007)

The large collection of Brazilian researcher`s curricula vitae held on the Lattes Platform provides a formidable base for the discovery of information about people`s skills, abilities and knowledge which is referred to as competencies. Results from the analysis of competencies can be applied in human resources, project management and the planning of on-the-job training in terms of how to enforce collaboration, how to build or modify teams and how to direct resources. The study builds on Knowledge Discovery in Textual Database (KDT) in order to analyze each step from data selection, term extraction and weighting to clustering and the interpretation toward knowledge management. For the division of an input dataset into a priori unknown competency-based groups two clustering algorithms have been implemented, namely the k-means algorithm and Kohonen Self-Organizing Maps (Kohonen-SOM). Two illustration techniques for competency-based groups as well as decision rules for the application of both algorithms will be presented. 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
Chaotic and higher harmonic oscillations in a nonlinear on-off circuit with a synchronous switch
Authors: Nizar Jabli, Hedi Khammari, M. Faouzi Mimouni
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

In this paper we consider a modified model of an Alpazur oscillator with a periodically switching operation. Complex oscillatory phenomena are observed due to both switching operation and the appearance of an additional nonlinear component in circuit model. Indeed, subharmonic oscillations and chaotic behavior are illustrated. In addition, time series, phase trajectories and power spectrum was examined in the analysis of the dynamic of system. The transition through doubling period bifurcation cascade to chaos and two other ways of transition to chaotic states are discussed in the state space. For the numerical simulations, techniques for deriving time and composite Poincaré method are applied.
Automated dynamic detection of busy&ndash;wait synchronizations
Authors: Chen Tian, Vijay Nagarajan, Rajiv Gupta, Sriraman Tallam
Venue: Software&mdash;Practice Experience (2009)

With the advent of multicores, multithreaded programming has acquired increased importance. In order to obtain good performance, the synchronization constructs in multithreaded programs need to be carefully implemented. These implementations can be broadly classified into two categories: busy&ndash;wait and schedule-based. For shared memory architectures, busy&ndash;wait synchronizations are preferred over schedule-based synchronizations because they can achieve lower wakeup latency, especially when the expected wait time is much shorter than the scheduling time. While busy&ndash;wait synchronizations can improve the performance of multithreaded programs running on multicore machines, they create a challenge in program debugging, especially in detecting and identifying the causes of data races. Although significant research has been done on data race detection, prior works rely on one important assumption&mdash;the debuggers are aware of all the synchronization operations performed during a program run. This assumption is a significant limitation as multithreaded programs, including the popular SPLASH-2 benchmark have busy&ndash;wait synchronizations such as barriers and flag synchronizations implemented in the user code. We show that the lack of knowledge of these synchronization operations leads to unnecessary reporting of numerous races. To tackle this problem, we propose a dynamic technique for identifying user-defined synchronizations that are performed during a program run. Both software and hardware implementations are presented. Furthermore, our technique can be easily exploited by a record-replay system to significantly speedup the replay. It can also be leveraged by a transactional memory system to effectively resolve a livelock situation. Our evaluation confirms that our synchronization detector is highly accurate with no false negatives and very few false positives. We further observe that the knowledge of synchronization operations results in 23&percnt; reduction in replay time. Finally, we show that using synchronization knowledge livelocks can be efficiently avoided during runtime monitoring of programs. Copyright &copy; 2009 John Wiley & Sons, Ltd.
Exploiting temporal statistics for events analysis and understanding
Authors: Christian Micheloni, Lauro Snidaro, Gian Luca Foresti
Venue: Image and Vision Computing (2009)

In this paper, we propose a technique for detecting anomalous events in outdoor areas monitored by a video surveillance system. In particular, the focus is on the time spent by an object to carry out simple events. To have a statistical representation of the time commonly required to perform certain activities, mixtures of Gaussians are maintained for each event type. Such statistics are then exploited both for the analysis of simple activities and for discovering anomalous situations, eventually alerting the operator. To this end, a novel way of visualizing results is also discussed. Experiments have been performed on a multi-camera system for parking lot security.
Rule learning with monotonicity constraints
Authors: Wojciech Kotłowski, Roman Słowiński
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

In classification with monotonicity constraints, it is assumed that the class label should increase with increasing values on the attributes. In this paper we aim at formalizing the approach to learning with monotonicity constraints from statistical point of view. Motivated by the statistical analysis, we present an algorithm for learning rule ensembles. The algorithm first "monotonizes" the data using a nonparametric classification procedure and then generates a rule ensemble consistent with the training set. The procedure is justified by a theoretical analysis and verified in a computational experiment.
Verification Techniques for System-Level Design
Authors: Masahiro Fujita, Indradeep Ghosh, Mukul Prasad
Venue: Systems On Silicon (2007)

This book will explain how to verify SoC logic designs using "formal" and "semi-formal" verification techniques. The critical issue to be addressed is whether the functionality of the design is the one that the designers intended. Simulation has been used for checking the correctness of SoC designs (as in "functional" verification), but many subtle design errors cannot be caught by simulation. Recently, formal verification, giving mathematical proof of the correctness of designs, has been getting much more attention. So far, most of the books on formal verification target the register transfer level (RTL) or lower levels of design. For higher design productivity, it is essential to debug designs as early as possible. That is, designs should be completely verified at very abstracted design levels (higher than RTL). This book covers all aspects of high-level formal and semi-formal verification techniques for system level designs. . First book that covers all aspects of formal and semi-formal, high-level (higher than RTL) design verification targeting SoC designs.. Formal verification of high-level designs (RTL or higher).. Verification techniques are discussed with associated system-level design methodology.
Compaction of Schedules and a Two-Stage Approach for Duplication-Based DAG Scheduling
Authors: Doruk Bozdağ, Füsun Özgüner, Umit V. Catalyurek
Venue: IEEE Transactions on Parallel and Distributed Systems (2009)

Many DAG scheduling algorithms generate schedules that require prohibitively large number of processors. To address this problem, we propose a generic algorithm, SC, to minimize the processor requirement of any given valid schedule. SC preserves the schedule length of the original schedule and reduces processor count by merging processor schedules and removing redundant duplicate tasks. To the best of our knowledge, this is the first algorithm to address this highly unexplored aspect of DAG scheduling. Onaverage, SC reduced the processor requirement 91, 82, and 72 percent for schedules generated by PLW, TCSD, and CPFD algorithms, respectively. SC algorithm has a low complexity (O(\vert {\cal N}\vert^3)) compared to most duplication-based algorithms. Moreover, it decouples processor economization from schedule length minimization problem. To take advantage of these features of SC, we also propose a scheduling algorithm SDS, having the same time complexity as SC. Our experiments demonstrate that schedules generated by SDS are only 3 percent longer than CPFD (O(\vert {\cal N}\vert^4)), one of the best algorithms in that respect. SDS and SC together form a two-stage scheduling algorithm that produces schedules with high quality and low processor requirement, and has lower complexity than the comparable algorithms that produce similar high-quality results.
Intelligent Tutoring and Human Tutoring in Small Groups: An Empirical Comparison
Authors: Carole R. Beal, Erin Shaw, Mike Birch
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

The efficacy of a tutoring system for pre-algebra instruction plus human tutoring was compared to instruction provided to small groups of middle school students by experienced human math tutors, with instructional time held constant. Students completed pre-and post-tests of computation, fractions, algebra and rational numbers skills. Results indicated that students showed significant improvement from pre-to post-test, but there was no difference as a function of type of tutoring. The findings help to establish the efficacy of ITS instruction relative to skilled human tutoring of students in small groups.
A Direct Test of Risk Aversion and Regret in First Price Sealed-Bid Auctions
Authors: Richard Engelbrecht-Wiggans, Elena Katok
Venue: Decision Analysis (2009)

Why do bidders tend to bid higher than the risk-neutral Nash equilibrium in sealed-bid first price auction experiments? The effect of risk aversion has long been offered as a possible explanation. More recently, several studies proposed regret as another explanation, citing strong experimental evidence. But which effect is more important? We design an experiment to separate the effects of risk aversion from those of regret. We find overwhelming evidence in support of the regret model, and virtually no support for the constant relative risk aversion model.
Approximation Properties of Planning Benchmarks
Authors: Malte Helmert, Robert Mattmüller, Gabi Röger
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

For many classical planning domains, the computational complexity of non-optimal and optimal planning is known. However, little is known about the area in between the two extremes of finding some plan and finding optimal plans. In this contribution, we provide a complete classification of the propositional domains from the first four International Planning Competitions with respect to the approximation classes PO, PTAS, APX, poly-APX, and NPO.