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In BCI research community, EEG based self-paced brain-computer interfaces (SBCI) have been widely researched in the past several years. SBCI systems allow individuals to control outside device using EEG signals at their own pace. But the performance of current SBCI technology is not suitable for most applications due to the difficult in detection of the non-periodic intentionally brain state changing...
In this study, we present the Big Bang-Big Crunch (BB-BC) method to solve the post-enrolment course timetabling problem. This method is derived from one of the evolution of the universe theories in physics and astronomy. The BB-BC theory involves two phases (Big Bang and Big Crunch). The Big Bang phase feeds the Big Crunch phase with many inputs and the Big Crunch phase is the shrinking destiny of...
In this paper we propose a music Query by Humming System made of two main functional blocks; the first implements a voice-to-midi transcription algorithm to process the query, the second implements a search engine based on a novel template matching technique for Dynamic Time Warping. The voice-to-midi algorithm transforms the sung or hummed query in a MIDI file by segmenting and identifying the notes'...
In this paper we perform the analysis of Dempster-Shafer temporalized structure for the construction of more precise decisions based on the expert knowledge valuations. The relation of information precision is defined on the bodies of evidence. Negative inaccuracy is defined as the stream of rational expert knowledge in Dempster-Shafer temporalized structure. The principle of negative inaccuracy is...
This paper presents an optimizing methodology for implementing a multi-layer perceptron (MLP) neural network in a Field Programmable Gate Array (FPGA) device. In order to obtain an efficient implementation, a compromise of time and area is needed. Starting from simulation in the learning phase with fixed point operators, we have developed a methodology which allows the automatic generation of a VHDL...
Optimizing the virtual reality model is a necessity to cope with the nature of the World Wide Web. Virtual reality scenes should load within an acceptable time for the user's experience and the sense of being immersed in the virtual environment is not to be affected. In this study, we propose to optimize web-based virtual reality models by removing redundant objects within the scenes, while keeping...
This paper proposes a new feature-selection strategy by integrating the Rough Set Theory (RST) and Particle Swarm Optimisation (PSO) algorithms to generate a set of discriminatory features for the classification problem. The proposed method is seen as a marriage between filter and wrapper approaches in which the RST is used to pre-reduce the feature set before optimisation by PSO, a meta-heuristic...
In business analysis, models are sometimes oversimplified. We pragmatically approach many problems with a single financial objective and include monetary values for non-monetary variables. We enforce constraints which may not be as strict in reality. Based on a case in distributed energy production, we illustrate how we can avoid simplification by modeling multiple objectives, solving it with an NSGA-II...
Combining pattern recognition is the promising direction in designing an effective classifier systems. There are several approaches of collective decision-making, among them voting methods, where the decision is a combination of individual classifiers' outputs are quite popular. This article focuses on the problem of fuser design which uses continuous outputs of individual classifiers to make a decision...
Studies on content-based music retrieval (CBMR) which search music by analyzing their acoustic features and defining their similarity, have been conducted actively. However, it is desirable that the similarity evaluation be adaptive to each user's demand, because the search criteria differs user by user. In this paper, we propose a framework of CBMR that tries to satisfy the various demands of different...
The necessity of lowering the execution of system tests' cost is a consensual point in the software development community. The present study presents an optimization of the regression tests' activity, by adapting a test cases prioritization technique called Failure Pursuit Sampling-previously used and validated for the prioritization of tests in general-improving its efficiency for the exclusive execution...
Attribute reduction is a basic issue in knowledge representation and data mining. It simplifies an information system by discarding some redundant attributes. In this paper, we present a hybrid approach that combines the nature of variable neighbourhood search in the first phase with an iterated local search in the second phase that always accepts best solutions. The approach is tested over 13 well-known...
In this paper a new criterion is introduced for the discrete covering problem. Using the representation of a possibility measure through associated probabilities, a new criterion for discrete covering problem is constructed based on aggregation by the Monotone Expectation (ME) (or Choquet integral). In this criterion the a priori information represented by a possibility measure and a misbelief distribution...
Considering recent developments in the field of carry-save representation in synthesis of arithmetic circuits, it was considered imperative to develop an automated system to optimize an arithmetic circuit design to handle cases of practical interest, including scattered logic, and generate an optimized solution in Verilog; so that it could reduce both design and debugging costs drastically. We, therefore,...
The generalized assignment problem is a well-known NP-complete problem whose objective is to find a minimum cost assignment of a set of jobs to a set of agents by considering the resource constraints. Dynamic instances of the generalized assignment problem can be created by changing the resource consumptions, capacity constraints and costs of jobs. Memory-based approaches are among a set of evolutionary...
This paper presents a methodology to find optimal solutions for linear programming problems on imprecise conditions. By using α-cuts, the cumulative membership function and the classic fuzzy linear programming model, a fuzzy joint parameters where its left hand side is defined by any kind of fuzzy set and its right hand side is defined by linear fuzzy sets, is solved and its crisp output is found...
Worker differences are fundamental consideration in personnel assignment which is one of the key decisions that influence the productivity and quality of assembly production. The personnel station fitness is proposed to describe the suitability of the worker for the assembly activity they assume. A personnel assignment model for assembly production is constructed, and the objectives are maximizing...
The optimal product line design problem consists of predicting the acceptance of new products in the market, prior of the actual production phase. It requires a unique blend of techniques and resources as it deals with multiple parameters and hard optimization problems. This paper proposes a service oriented architecture which outlines the basic features that a marketing decision support system should...
Unequal Area Facility Layout Problem (UA-FLP) has been addressed by several methods. However, UA-FLP has only been solved regarding quantitative criteria. Our approach includes subjective features to UA-FLP, which are difficult to take into account with a classical heuristic optimization. For that, an Interactive Genetic Algorithm (IGA) is proposed that allows an interaction between the algorithm...
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