ppxscal/embedding_network huggingface dataset:
Novel Extension of k - TSP Algorithm for Microarray Classification
Authors: Marcin Czajkowski, Marek Krętowski
Venue: Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence (2008)

This paper presents a new method, referred as Weight k ¿ TSP, which generates simple and accurate decision rules that can be widely used for classifying gene expression data. The proposed method extends previous approaches: TSP and k ¿ TSP algorithms by considering weight pairwise mRNA comparisons and percentage changes of gene expressions in different classes. Both rankings have been modified as well as decision rules, however the concept of "relative expression reversals" is retained. New solutions to match analyzed datasets more accurately were also included. Experimental validation was performed on several human microarray datasets and obtained results are promising.
The Anticipatory Approach: Definitions and Taxonomies
Authors: Giovanni Pezzulo, Martin V. Butz, Cristiano Castelfranchi
Venue: The Challenge of Anticipation: A Unifying Framework for the Analysis and Design of Artificial Cognitive Systems (2008)

The anticipatory approach that we propose consists in understanding and conceptualizing anticipation and anticipatory behavior in natural cognition and implementing them in artificial systems. We propose that anticipatory systems have capabilities that go far beyond those of purely reactive ones and that anticipation is a prerequisite for several cognitive functions, and in general for goal-oriented behavior.Consequently, in this chapter we first provide definitions for anticipation and anticipatory behavior (Section 2.1). We then classify and distinguish different types and aspects of predictive and anticipatory mechanisms (Section 2.2). Next, we classify anticipatory mechanisms in goal-oriented behavior (Section 2.3) and finally distinguish anticipatory mechanisms in learning structures (Section 2.4).The classifications put forward in this chapter are meant to clarify what anticipatory mechanisms are and how they can influence cognitive systems' behavior and learning. Chapter 3 then reviews the potential benefits of anticipatory mechanism and also discusses potential drawbacks. In the subsequent chapters, we then take the artificial systems perspective and put forward the requirements and the capabilities of currently available anticipatory cognitive systems.
Sample Selection Bias Correction Theory
Authors: Corinna Cortes, Mehryar Mohri, Michael Riley, Afshin Rostamizadeh
Venue: Proceedings of the 19th international conference on Algorithmic Learning Theory (2008)

This paper presents a theoretical analysis of sample selection bias correction. The sample bias correction technique commonly used in machine learning consists of reweighting the cost of an error on each training point of a biased sample to more closely reflect the unbiased distribution. This relies on weights derived by various estimation techniques based on finite samples. We analyze the effect of an error in that estimation on the accuracy of the hypothesis returned by the learning algorithm for two estimation techniques: a cluster-based estimation technique and kernel mean matching. We also report the results of sample bias correction experiments with several data sets using these techniques. Our analysis is based on the novel concept of distributional stability which generalizes the existing concept of point-based stability. Much of our work and proof techniques can be used to analyze other importance weighting techniques and their effect on accuracy when using a distributionally stable algorithm.
Adaptive identification in graphs
Authors: Yael Ben-Haim, Sylvain Gravier, Antoine Lobstein, Julien Moncel
Venue: Journal of Combinatorial Theory Series A (2008)

An adaptive version of identifying codes is introduced. These codes are motivated by various engineering applications. Bounds on adaptive identifying codes are given for regular graphs and torii in the square grid. The new codes are compared to the classical non-adaptive case.
An Intelligent Differential Evolution Algorithm for Designing Trading-Ratio System of Water Market
Authors: Ying Liu, Bo Liu, Jikun Huang, Yunhua Wu, Ling Wang, Yihui Jin
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

As a novel optimization technique, neural network based optimization has gained much attention and some applications during the past decade. To enhance the performance of Differential Evolution Algorithm (DEA), which is an evolutionary computation technique through individual improvement plus population cooperation and competition, an intelligent Differential Evolution Algorithm (IDEA) is proposed by incorporating neural network based search behaviors into classic DEA. Firstly, DEA operators are used for exploration by updating individuals so as to maintain the diversity of population and speedup the search process. Secondly, a multi-layer feed-forward neural network is employed for local exploitation to avoid being trapped in local optima and improve the convergence of the IDEA. Simulation results and comparisons based on well-known benchmarks and optimal designing of trading-ratio system for water market demonstrate that the IDEA can effectively enhance the searching efficiency and greatly improve the searching quality.
Shockwave Detection for Electronic Vehicle Detectors
Authors: Hsung-Jung Cho, Ming-Te Tseng
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

Although shockwaves have been extensively adopted in traditional traffic flow theory, how to detect shockwaves using an electronic vehicle detector has not been explored. Therefore, this study illustrates, for the first time, not only how to detect shockwaves, but also how to obtain shockwaves from three new traffic parameters: Stopped, Moving, and Empty. The Stopped parameter attempts to identify a newly arrived shockwave equation when a traffic queue approaches the electronic vehicle detector. The Moving and Empty parameters derive another new arrival shockwave equation when the electronic vehicle detector fails to identify any queue. An algorithm is also created to demonstrate how to use these parameters and equations to detect shockwaves. Additionally, numerous simulations are conducted to identify the behaviors of new traffic parameters and the effectiveness of the proposed algorithm. Results of this study demonstrate that the computing algorithm for electronic vehicle detectors can accurately detect shockwaves.
A System for Automatic Chord Transcription from Audio Using Genre-Specific Hidden Markov Models
Authors: Kyogu Lee
Venue: Adaptive Multimedial Retrieval: Retrieval, User, and Semantics: 5th International Workshop, AMR 2007, Paris, France, July 5-6, 2007 Revised Selected Papers (2007)

We describe a system for automatic chord transcription from the raw audio using genre-specific hidden Markov models trained on audio-from-symbolic data. In order to avoid enormous amount of human labor required to manually annotate the chord labels for ground-truth, we use symbolic data such as MIDI files to automate the labeling process. In parallel, we synthesize the same symbolic files to provide the models with the sufficient amount of observation feature vectors along with the automatically generated annotations for training. In doing so, we build different models for various musical genres, whose model parameters reveal characteristics specific to their corresponding genre. The experimental results show that the HMMs trained on synthesized data perform very well on real acoustic recordings. It is also shown that when the correct genre is chosen, simpler, genre-specific model yields performance better than or comparable to that of more complex model that is genre-independent. Furthermore, we also demonstrate the potential application of the proposed model to the genre classification task. 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
An Efficient Implementation Method of Arbiter for the ML-AHB Busmatrix
Authors: Soo Yun Hwang, Hyeong Jun Park, Kyoung Son Jhang
Venue: Proceedings of the 3rd international conference on Embedded Software and Systems (2007)

The multi-layer AHB busmatrix (ML-AHB busmatrix) proposed by ARM is a highly efficient on chip bus that allows parallel access paths between multiple masters and slaves in a system. In this paper, we present one way to improve the arbiter implementation of the ML-AHB busmatrix. We employ the masking mechanism which does not impose any restrictions on arbitration scheme. Therefore, the proposed scheme is applied to the implementation of busmatrixes to support the transaction based arbitrations as well as the transfer based arbitrations. In addition, we could not only enhance the throughput of bus system but also reduce the total area, clock period and power consumption. Experimental results show that the throughput of our busmatrix based on the transfer based fixed priority (round robin) arbitration scheme is increased by 41% (18%) compared with that of the equivalent busmatrix of ARM. Moreover, we could reduce the total area, clock period and power consumption by 22%, 28% and 19% (12%, 15% and 13%) respectively, compared with the busmatrix employing the transfer based fixed priority (round robin) arbitration scheme of ARM.
Complexity of Data Tree Patterns over XML Documents
Authors: Claire David
Venue: Proceedings of the 33rd international symposium on Mathematical Foundations of Computer Science (2008)

We consider Boolean combinations of data tree patterns as a specification and query language for XML documents. Data tree patterns are tree patterns plus variable (in)equalities which express joins between attribute values. Data tree patterns are a simple and natural formalism for expressing properties of XML documents. We consider first the model checking problem (query evaluation), we show that it is DP-complete in general and already NP-complete when we consider a single pattern. We then consider the satisfiability problem in the presence of a DTD. We show that it is in general undecidable and we identify several decidable fragments.
Identity Transposon Networks in D. melanogaster
Authors: Alcides Castro-E-Silva, Gerald Weber, Romuel F. Machado, Elizabeth F. Wanner, Renata Guerra-Sá
Venue: Proceedings of the 3rd Brazilian symposium on Bioinformatics: Advances in Bioinformatics and Computational Biology (2008)

Transposable elements, or transposons, are DNA segments that are repeated within the same genome and are an important component of the genomes of most species. It is generally believed that they play an important role in evolution and genome restructuring. In this work we built a network based on a score which represents the transposon identity. This score is calculated by comparing all currently known D. melanogaster transposons to each other using a Neddleman-Wunsch alignment algorithm. We then use this score to build networks with transposons having a minimal value of identity. We start with networks of transposons with total identity (all have score one) to networks where they may have any identity score (all have non-negative score). The number of successful comparisons as a function of the minimal score shows an abrupt transition for minimal scores at 0.25 which can be associated to general properties of repetitions usually found in genomes. We also show that this score leads to a transition in the topology of transposon networks from scale-free to almost fully-connected.
Data Services in Distributed Real-Time Embedded Systems
Authors: Woochul Kang, Sang H. Son
Venue: Proceedings of the 6th IFIP WG 10.2 international workshop on Software Technologies for Embedded and Ubiquitous Systems (2008)

The computing systems are becoming deeply embedded into ordinary life and interact with physical processes and events. They monitor the physical world with sensors and provide appropriate reaction and control over it. This cyber-physical interaction, which occurs through ubiquitous embedded systems, has the potential to transform how humans interact with and control the physical world. Applications of such systems include infrastructure management and environmental monitoring. For these applications, the demand for real-time data services is increasing since they are inherently data-intensive. However, providing real-time data services in such large-scale and geographically distributed environment is a challenging task. In particular, both unpredictable communicational delays and computational workloads of large-scale distributed systems can lead to large number of deadline misses. In this paper, we propose a real-time data service architecture called DRACON (Decentralized data Replication And CONtrol), which is designed to support large-scale distributed real-time applications. DRACON uses cluster-based replica-sharing and a decentralized control structure to address communication and computational unpredictability.
Particle swarm approaches using Lozi map chaotic sequences to fuzzy modelling of an experimental thermal-vacuum system
Authors: Ernesto Araujo, Leandro dos S. Coelho
Venue: Applied Soft Computing (2008)

Particle Swarm Optimization (PSO) approach intertwined with Lozi map chaotic sequences to obtain Takagi-Sugeno (TS) fuzzy model for representing dynamical behaviours are proposed in this paper. The proposed method is an alternative for nonlinear identification approaches especially when dealing with complex systems that cannot always be modelled using first principles to determine their dynamical behaviour. Since modelling nonlinear systems is normally a difficult task, fuzzy models have been employed in many identification problems due its inherent nonlinear characteristics and simple structure, as well. This proposed chaotic PSO (CPSO) approach is employed here for optimizing the premise part of the IF-THEN rules of TS fuzzy model; for the consequent part, least mean squares technique is used. The proposed method is utilized in an experimental application; a thermal-vacuum system which is employed for space environmental emulation and satellite qualification. Results obtained with a variety of CPSO's are compared with traditional PSO approach. Numerical results indicate that the chaotic PSO approach succeeded in eliciting a TS fuzzy model for this nonlinear and time-delay application.
Multi-agent control and operation of electric power distribution systems
Authors: Ali Feliachi
Venue:  (2005)

This dissertation presents operation and control strategies for electric power distribution systems containing distributed generators. First, models of microturbines and fuel cells are developed. These dynamic models are incorporated in a power system analysis package. Second, operation of these generators in a distribution system is addressed and load following schemes are designed. The penetration of distributed generators (DGs) into the power distribution system stability becomes an issue and so the control of those DGs becomes necessary. A decentralized control structure based on conventional controllers is designed for distributed generators using a new developed optimization technique called Guided Particle Swarm Optimization. However, the limitations of the conventional controllers do not satisfy the stability requirement of a power distribution system that has a high DG penetration level, which imposes the necessity of developing a new control structure able to overcome the limitations imposed by the fixed structure conventional controllers and limit the penetration of DGs in the overall transient stability of the distribution system. Third, a novel multi-agent based control architecture is proposed for transient stability enhancement for distribution systems with microturbines. The proposed control architecture is hierarchical with one supervisory global control agent and a distributed number of local control agents in the lower layer. Specifically, a central control center supervises and optimizes the overall process, while each microturbine is equipped with its own local control agent. The control of naval shipboard electric power system is another application of distributed control with multi-agent based structure. In this proposal, the focus is to introduce the concept of multi-agent based control architecture to improve the stability of the shipboard power system during faulty conditions. The effectiveness of the proposed methods is illustrated using a 37-bus IEEE benchmark system and an all-electric naval ship.
DWT-Based Audio Watermarking Using Support Vector Regression and Subsampling
Authors: Xiaojuan Xu, Hong Peng, Chengyuan He
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

How to protect the copyright of digital media over the Internet is a problem for the creator/owner. A novel support vector regression (SVR) based digital audio watermarking scheme in the wavelet domain which using subsampling is proposed in this paper. The audio signal is subsampled and all the sub-audios are decomposed into the wavelet domain respectively. Then the watermark information is embedded into the low-frequency region of random one sub-audio. With the high correlation among the sub-audios, accordingly, the distributing rule of different sub-audios in the wavelet domain is similar to each other, SVR can be used to learn the characteristics of them. Using the information of unmodified template positions in the low-frequency region of the wavelet domain, the SVR can be trained well. Thanks to the good learning ability of SVR, the watermark can be correctly extracted under several different attacks. The proposed watermarking method which doesn't require the use of the original audio signal for watermark extraction can provide a good copyright protection scheme. The experimental results show the algorithm is robust to signal processing, such as lossy compression (MP3), filtering, resampling and requantizing, etc.
Influence of Character Type of Japanese Hiragana on Writer Recognition
Authors: Yoshinori Adachi, Masahiro Ozaki, Yuji Iwahori
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

The character used for the writer recognition was limited to 46 types of hiragana with a lot of curve parts, and the difference of the similarity values by the kind of character was examined. As a result, it has been understood that the similarity values were quite dependent on the type of character. Moreover, it turned out that the similarity value was greatly different according to the type of character. Moreover, it was confirmed that the recognition ratio was improved by using the steady character which writer could write similarly each time. In addition, it was confirmed that there exist the character that was appropriate for recognition even the similarity value was low (e.g. "¿","¿","¿"), and the improper character even the similarity value was high (e.g. "¿","¿","¿").
Exploiting Interactions among Query Rewrite Rules in the Teradata DBMS
Authors: Ahmad Ghazal, Dawit Seid, Alain Crolotte, Bill Mckenna
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

Query rewrite (QRW) optimizations apply algebraic transformations to a SQL query Q producing a SQL query Q'. Both Q and Q' are semantically equivalent (i.e. they produce the same result) but the execution of Q' is generally faster than that of Q. Folding views/derived tables, applying transitive closure on predicates, and converting outer joins to inner joins are some examples of QRW optimizations. In this paper, we carefully analyze the interactions among a number of rewrite rules and show how this knowledge is used to devise a triggering mechanism in the new Teradata extensible QRW subsystem thereby enabling efficient application of the rewrite rules. We also present results from experimental studies that show that, as compared to a conventional recognize-act cycle strategy, exploiting these interactions yields significant reduction in the time and space cost of query optimization while producing the same re-written queries.
Finding Identity Group "Fingerprints" in Documents
Authors: Lashon B. Booker
Venue: Proceedings of the 2nd international workshop on Computational Forensics (2008)

This paper describes how social identity group "fingerprints" can be extracted from a document collection by applying topic analysis methods in a novel way. The results of document classification experiments suggest that these group-level attributes provide better predictions of group affiliation than document-level attributes. Applications of this method for forensic authorship analysis are also discussed.
Fredholm integral equation method for the integro-differential Schrödinger equation
Authors: Ick-Soon Chang, Sheon-Young Kang
Venue: Computers Mathematics with Applications (2008)

A new method based on the Clenshaw-Curtis quadrature for the numerical solution of the integro-differential Schrodinger equation is investigated. The method shows that it converges quickly and the truncation errors decrease faster than any power of the inverse number of the Chebyshev support points. Discretization technique is presented in detail. Accompanying C^+^+ code for the Fredholm type method is available upon request.
Existence and stability of periodic solution for BAM neural networks with discontinuous neuron activations
Authors: Huaiqin Wu, Yingwei Li
Venue: Computers Mathematics with Applications (2008)

In this paper, by using the fixed point theorem of differential inclusion theory and constructing suitable Lyapunov functions, the existence, uniqueness and global exponential stability of the periodic solution for BAM neural networks with discontinuous neuron activations are investigated. Moreover, the global convergence in finite time of the networks is discussed. The conditions that ensure the existence and stability of periodic solution are given. The obtained results extend previous work on global stability of BAM neural networks with Lipschitz continuous neuron activations but without delays, and show that Forti's conjecture is true for BAM neural networks without delays.
Fast communication: Blind SIMO channel identification using FFT/IFFT
Authors: Song Wang, Jonathan H. Manton
Venue: Signal Processing (2008)

This paper presents an FFT/IFFT-based deterministic blind identification method for estimating the finite impulse response of single-input multiple-output (SIMO) communication channels. The new method delivers a frequency-domain realization of the cross-relation between each channel output pair. With no assumption of the precise knowledge of channel order, the proposed algorithm is capable of estimating channel parameters as well as detecting channel order. In small sample size situations, our method exhibits consistent or better performance compared to the existing methods, e.g., the subspace, cross-relation and shifted correlation algorithms.