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Mental stress assessment remains riddled with biases caused by subjective reports and individual differences across societal backgrounds. To objectively determine the presence or absence of mental stress, there is a need to move away from the traditional subjective methods of self-report questionnaires and interviews. Previously, it has been evidence that EEG Oscillations can discriminate mental…

Modulation type classification is a part of waveform estimation required to employ spectrum sharing scenarios like dynamic spectrum access that allow more efficient spectrum utilization. In this work multiple classification features, feature extraction, and classification algorithms for modulation type classification have been studied and compared in terms of classification speed and accuracy to suggest the…

In the present article, we introduce a foveation-based optimized embedded and its optimized version image coders thereafter called VOEFIC/MOEFIC and its related foveation wavelet visible difference predictor FWVDP coding quality metric. It advances a visually advanced foveal weighting mask that regulates the wavelet-based image spectrum before its encoding by the SPIHT encoder. It intends to…

Neurological signals are generally very weak in amplitude and strongly noisy. As a result, one of the major challenges in neuroscience is to be able to eliminate noise and thus exploit the maximum amount of information contained in neurological signals (EEG…). In this paper, we aimed at studying the N400 wave of the Event-Related Potentials…

This work presents new pipeline-parallel, generic and configurable parallel hardware architectures for the Direct/Inverse Wavelet Packet Transform (DWPT/IDWPT) independent of any specific family of wavelets, implemented in FPGA technology using a parallel architecture of direct FIR filter. We propose in the following paper, new P-parallel structures for the DWPT and IDWPT transforms based on the…

The objective of this paper is to investigate the use of the 1-D wavelet analysis to extract several patterns from signals data sets collected from healthy and faulty input-output signals of control systems as a preliminary step in real-time implementation of fault detection diagnosis and isolation strategies. The 1-D wavelet analysis proved that is an…

This work is dedicated to present a new pipeline-parallel architecture of Discrete Wavelet Packet Transform (DWPT) for all wavelet family implemented in FPGA technology. The main target of our architecture is to provide an effective performance trade-off, where it significantly increases the throughput with a restricted amount of hardware. In this article, we propose two…

Video shot boundary detection is important step for the research in the content analysis and retrieval fields. In this paper, firstly we presented an efficient method for Video-frame quality improvement to suppress flash occurred within video frame using logarithm, wavelet and contourlet transform. In addition, wavelet and contourlet transform also performed denoising. Secondly, for shot…

For systems using rotating machinery, diagnosing the faults of the rotating machinery is critical for system maintenance. Recently, a machine learning algorithm has been employed as one of the methods for diagnosing the faults of rotating machinery. This algorithm has an advantage of automatically classifying faults without an expert knowledge. However, despite a good training…

A new method of analysis and classification of rock acoustic emission signals is proposed. It is based on symbol description of signals and involves the following processing. First, signal segments containing pulses are detected. Second, noise of the detected pulses is reduced by the wavelet filtration method. Fourth-order symlets and adaptive threshold scheme based on…

The integration of renewable energy distributed generation (REDG) into the energized distribution power grid has become more popular in recent years. This has been escalated by the general global energy shortages. The REDG has proven to be effective for energy sustainability and reliability. However, there are technical challenges which arise from integrating REDG into the…

Person recognition using thermal imaging, multi-biometric traits, with groups of feature filters and classifiers, is the subject of this paper. These were used to tackle the problems of biometric systems, such as a change in illumination and spoof attacks. Using a combination of, hard and soft-biometric, attributes in thermal facial images. The hard-biometric trait, of…

In this paper, we propose a new Perceptually Optimized Embedded Zero Tree Image Coder EVIC and its improved version MEVIC. The coder presents a new perceptual model to weight wavelet coefficients to enhance SPIHT embedded coding. The new visual coder aims to improve the visual quality obtained by the reference SPIHT coder for a given…

Early detection and treatment of cervical cancer is crucial to patients’ recovery with a reported success rate of nearly 100%. Presently, Pap smear test which is a visual inspection of cells collected from the ectocervix is the screening tool mainly used in cancer prevention programs. The Pap smear is relatively easy to handle however, it…

Feature extraction is taking a very vital and essential part of bio-signal processing. We need to choose one of two paths to identify and select features in any system. The most popular track is engineering handcrafted, which mainly depends on the user experience and the field of application. While the other path is feature learning,…

Listening to auditory stimuli during study can give positive and negative influence on human cognitive processing. Thus, it has attracted researchers to conduct studies using various types of auditory stimuli. Some researchers believe that Mozart music and white noise are able to give positive influence on cognitive performance. However, most of the past studies gave…

Epilepsy is a neurological disorder which is most widespread in human beings after stroke. Approximately 70% of epilepsy cases can be cured if diagnosed and medicated properly. Electro-encephalogram (EEG) signals are recording of brain electrical activity that provides insight information and understanding of the mechanisms inside the brain. Since epileptic seizures occur erratically, it is…

A functional near-infrared spectroscopy (fNIRS) can be employed to investigate brain activation by measuring the absorption of near-infrared light through the intact skull. The general linear model (GLM) as a standard model for fMRI analysis has been applied to functional near-infrared spectroscopic (fNIRS) imaging analysis as well. The GLM has drawback of failure in fNIRS…

The research in Neuro-Prosthetics is gaining more significance and popularity as the advancement in prosthetics control allows amputees to perform even more tasks. Indeed, the improvement of classification accuracy is a challenge in prosthetics control. In this research, a system is developed in order to improve the multiclass classification rate. Two classifiers namely Artificial Neural…

Feature extraction is playing a significant role in bio-signal processing. Feature identification and selection has two approaches. The standard method is engineering handcraft which is based on user experience and application area. While the other approach is feature learning that based on making the system identify and select the best features suit the application. The…

A thrombus or a blood clot is the result of blood coagulation which is a natural process to prevent bleeding. An inappropriate formation of a thrombus in a deep vein is known as Deep Venous Thrombosis (DVT). The main complication of a DVT is a Pulmonary Embolism (PE) which occurs when a thrombus breaks loose…

This paper presents a comparative study of using different color systems on watermarking algorithms. This comparison aim is to determining the robustness and the stability of the color systems used in the watermarking scheme. The watermarking algorithm that is used in this paper is a hybrid scheme using the Discrete Wavelet Transform (DWT) in the…