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In this work, we model speech samples with a two-sided generalized Gamma distribution and evaluate its efficiency for voice activity detection. Using a computationally inexpensive maximum likelihood approach, we employ the Bayesian Information Criterion for identifying the phoneme boundaries in noisy speech.
As the field of Intelligent Virtual Agents evolves and advances, an ever increasing number of functional and useful applications are presented. Intelligent Virtual Agents have become more realistic, intelligent and sociable, with apparent and substantial benefits to domains such as training, tutoring, simulation and entertainment. However, even though many end-users can enjoy these benefits today,...
In this paper a new maximum a posteriori (MAP) approach based on mixtures of multinomials is proposed for discovering probabilistic patterns in sequences. The main advantage of the method is the ability to bypass the problem of overlapping patterns in neighboring positions of sequences by using a Markov random field (MRF) prior. This model consists of two components, the first models the pattern and...
A hardware architecture is presented, which accelerates the per- formance of intelligent applications that are based on logic programming. The logic programs are mapped on hardware and more precisely on FPGAs (Field Programmable Gate Array). Since logic programs may easily be transformed into an equivalent Attribute Grammar (AG), the underlying model of implementing an embedded system for the aforementioned...
Decision making is widely considered as a fundamental organizational activity that comprises a series of knowledge representation and processing tasks. Admitting that the quality of a decision depends on the quality of the knowledge used to make it, it is argued that the enhancement of the decision making efficiency and effectiveness is strongly related to the appropriate exploitation of all possible...
The market clearing prices in deregulated electricity markets are volatile. Good market clearing price forecasting will help producers and consumers to prepare their corresponding bidding strategies so as to maximize their profits. Market clearing price prediction is a difficult task since bidding strategies used by market participants are complicated and various uncertainties interact in an intricate...
A random signal-based learning merged with simulated annealing (SARSL), which is serial algorithm, has been considered by the authors. But the serial nature of SARSL degrades its performance as the complexity of the search space is increasing. To solve this problem, this paper proposes a population structure of SARSL (PSARSL) which enables multi-point search. Moreover, adaptive partitioning method...
This paper is concerned with cascade fuzzy neural networks and its optimization. These networks come with sound and transparent logic characteristics by being developed with the aid of AND and OR fuzzy neurons and subsequently logic processors (LPs). We discuss main functional properties of the model and relate them to its form of cascade type of systems formed as a stack of LPs. The structure of...
Video broadcast series like news or magazine broadcasts usually expose a strong temporal structure, along with a characteristic audio-visual appearance. This results in frequent patterns occurring in the video signal. We propose an algorithm for the automatic detection of such patterns that exploits the video’s self-similarity induced by the patterns. The approach is applied to the problem of anchor...
This paper presents a content-based approach to spam detection based on low-level information. Instead of the traditional ’bag of words’ representation, we use a ’bag of character n-grams’ representation which avoids the sparse data problem that arises in n-grams on the word-level. Moreover, it is language-independent and does not require any lemmatizer or ’deep’ text preprocessing. Based on experiments...
The intermittent nature of the wind creates significant uncertainty in the operation of power systems with increased wind power penetration. Con- siderable efforts have been made for the accurate prediction of the wind power using either statistical or physical models. In this paper, a method based on Artificial Neural Network (ANN) is proposed in order to improve the predictions of an existing neuro-fuzzy...
This paper presents a new bidding strategy for continuous double auctions (CDA) designed for Mertacor, a successful trading agent, which won the first price in the “travel game” of Trading Agent Competition (TAC) for 2005. TAC provides a realistic benchmarking environment in which various travel commodities are offered in simultaneous online auctions. Among these, entertainment tickets are traded...
The leap from decision support to autonomous systems has often raised a number of issues, namely system safety, soundness and security. Depending on the field of application, these issues can either be easily overcome or even hinder progress. In the case of Supply Chain Management (SCM), where system performance implies loss or profit, these issues are of high importance. SCM environments are often...
Probabilistic Latent Semantic Indexing (PLSI) is a statistical technique for automatic document indexing. A novel method is proposed for updating PLSI when new documents arrive. The proposed method adds incrementally the words of any new document in the term-document matrix and derives the updating equations for the probability of terms given the class (i.e. latent) variables and the probability of...
Parametric models such as linear regression can provide useful, interpretable descriptions of simple structure in data. However, sometimes such simple structure does not extend across an entire data set and may instead be confined more locally within subsets of the data. Nonparametric regression typically involves local averaging. In this study, local averaging estimator is coupled with a machine...
We present, Mine Time, a tool that supports discovery over time series data. Mine Time is realized by the introduction of novel algorithmic processes, which support assessment of coherence and similarity across timeseries data. The innovation comes from the inclusion of specific ‘control’ operations in the elaborated time-series matching metric. The final outcome is the clustering of time-series into...
Several agent frameworks have been proposed for developing intelligent software agents and multi-agent systems that are able to perform in dynamic environments. These frameworks and architectures exploit specific reasoning tasks (such as option selection, desire filtering, plan elaboration and means-end reasoning) that support agents to react, deliberate and/or interact/cooperate with other agents...
This paper describes the application of Decision Tress (DTs) in order to specify the most critical location and the rate of series compensation in order to increase power system loading margin. The proposed methodology is applied to a projected model of the Hellenic interconnected system in several system configurations. Investigation of the best system operating point to create the DTs, the effect...
In this paper, a new genetic clustering algorithm called IHGA-clustering is proposed to deal with the clustering problem under the criterion of minimum sum of squares clustering. In IHGA-clustering, DHB operation is developed to improve the individual and accelerate the convergence speed, and partition-mergence mutation operation is designed to reassign objects among different clusters. Equipped with...
We present a named-entity recognizer for Greek person names and temporal expressions. For temporal expressions, it relies on semi- automatically produced patterns. For person names, it employs two Support Vector Machines, that scan the input text in two passes, and active learning, which reduces the human annotation effort during training.
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