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EEG signal is used to establish a communication channel between brain and control device. A common scenario of machine learning based brain computer interface (BCI) is class wise accuracy is different from overall accuracy. Accuracy for one class is worse than overall accuracy. Because, error rates of all classes are not converging in same rate during training of learner. Active class selection (ACS)...
In this paper, we formed prediction intervals using historical similarities, found through the direct correlation. At first, a string of 5 to 20 recent samples is correlated with a long training string of samples. Then, the highest normalized correlation values and corresponding indexes are picked. After that, the amplitudes of the matched samples are adjusted by multiplying the value with the amplitude...
Classification of lung cancer using a low population, high dimensional dataset is challenging due to insufficient samples to learn an accurate mapping among features and class labels. Current literature usually handles this task through hand-crafted feature creation and selection. In recent years, deep learning is found to be able to identify the underlying structure of data through the use of autoencoders...
Weber's law has been widely used by researchers for perceptual analysis in data reduction algorithms proposed for haptic applications. The law in its basic definition suggests a constant coefficient к or Just Noticeable Difference (JND). This constant is the percentage of actual stimulus around which the human sensory system cannot notice a change. Moreover, research studies have been conducted to...
A motion simulator is an effective tool for training a driver in a safe environment by mimicking motion similar to the real world. To give a realistic feeling of driving and avoid motion sickness, an accurate motion cueing algorithm is required to restrict the platform within the allowed workspace range while regenerating an appropriate motion feeling for the simulator driver. Recently, employing...
Driving behaviour prediction is a challenging problem due to the nonlinearity of human behaviour. Linear and nonlinear techniques have been used to solve this problem, and they provide good results presented in the performance of the current autonomous cars. However, they lack the ability to adapt to abruptness that happens because of the human factor. In this paper, we introduce a method to extract...
Recent efforts in the evolutionary multi-objective optimization (EMO) community focus on addressing shortcomings of current solution techniques adopted for solving many-objective optimization problems (MaOPs). One such challenge faced by classical multi-objective evolutionary algorithms is diversity preservation in optimization problems with more than three objectives, namely MaOPs. In this vein,...
Developing a watermarking method that is robust to cropping attack is a challenging task in image watermarking. The moment-based watermarking schemes show good robustness to common signal processing attacks and some geometric attacks but are sensitive to cropping attack. In this paper, we modify the moment-based approach to deal with cropping attack. Firstly, we find the probability density function...
Optimising energy consumption in wireless sensor networks is of dominant importance. Sink mobility is introduced to deal with this problem by approaching the sensor nodes and collecting their data buffers using the less energy demanding single-hop communication. The sink route is very crucial for the data collection operation performed in the network especially when the collection requests generated...
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