Key-frame selection plays an important role in facial expression recognition systems. It helps in selecting the most representative frames that capture the different poses of the face. The effect of the number of selected keyframes has been studied in this paper to find its impact on the final accuracy of the emotion recognition system. Dynamic and static information is employed to select the most effective key-frames of the facial video with a short response time. Firstly, the absolute difference between the successive frames is used to reduce the number of frames and select the candidate ones which then contribute to the clustering process. The static-based information of the reduced sets of frames is then given to the fuzzy C-Means algorithm to select the best C-frames. The selected keyframes are then fed to a graph mining-based facial emotion recognition system to select the most effective sub-graphs in the given set of keyframes. Different experiments have been conducted using Surrey Audio-Visual Expressed Emotion (SAVEE) database and the results show that the proposed method can effectively capture the keyframes that give the best accuracy with a mean response time equals to 2.89.
Cobalt substituted nickel copper ferrite samples with general formula Ni0.95-xCoxCu0.05Fe2O4, where (x= 0.00, 0.01, 0.02, 0.03, 0.04 and 0.05) were prepared by solid-state reactions method at 1373 K for 4h. The samples prepared were examined by X-ray diffraction (XRD(, atomic force microscope (AFM), Fourier transform infra-red spectroscopy (FTIR) and Vickers hardness. X-ray diffraction patterns confirm the formation of a single phase of cubic spinel structure in all the prepared samples . XRD analysis showed that the increase in the cobalt concentration causes an increase in the lattice constant, bulk density (ρm) and the x-ray density (ρx), whereas porosity (p) and crystallite size (D) decrease. The Topography of the surface observed
... Show MoreFinancial inclusion refers to the access of financial services at low cost and high-quality from the formal financial sector to all segments of society, especially marginalized groups, and then use and benefit from them. Financial inclusion is also associated with banking stability, as well as with financial integrity and financial protection for the consumer, therefore, it achieves a number of objectives, the most important of which is to support and enhance banking stability. This is what made it attract the attention of many countries and central banks recently.
The study aims to show the impact of financial inclusion indicators on ban
... Show MoreKombucha(Khubdat Humza) is composed of yeast and acetic acid bacteria especially, Acetobacter xylinum which forms a cellulose pellicle on tea broth. Kombucha(Khubdat Humza) produces bacterial cellulose pellicles, with unique purity and fine structure. It can be used in many forms, such as an emulsifier, stabilizer, dispersing agent, thickener and gelling agent but these are generally subsidiary to its most important use of holding on to water. Recently, bacterial cellulose is used in many special applications such as a scaffold for tissue engineering of cartilages and blood vessels, also for artificial skin for temporary covering of wounds, as well as its used in the clothing industry. The yield of cellulose produced were investiga
... Show MoreRecently, interest in the use of projectiles in research on recycling waste materials for construction applications has grown. Using recycled materials for the construction of asphalt concrete pavement, in the meantime, has become a topic of research due to its significant benefits, such as cost savings and reduced environmental impacts. This study reports on comprehensive experimental research conducted using a typical mechanical milling waste, iron filing waste (IFW), as an alternative fine aggregate for warm mix asphalt (WMA) for pavement wearing surface applications. A type of IFW from a local machine workshop was used to replace the conventional fine aggregate, fine natural sand (FNS), at percentages of 25%, 50% 75%, and 100% b
... Show MoreRecently, interest in the use of projectiles in research on recycling waste materials for construction applications has grown. Using recycled materials for the construction of asphalt concrete pavement, in the meantime, has become a topic of research due to its significant benefits, such as cost savings and reduced environmental impacts. This study reports on comprehensive experimental research conducted using a typical mechanical milling waste, iron filing waste (IFW), as an alternative fine aggregate for warm mix asphalt (WMA) for pavement wearing surface applications. A type of IFW from a local machine workshop was used to replace the conventional fine aggregate, fine natural sand (FNS), at percentages of 25%, 50% 75%, and 100% b
... Show MoreFace recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security
... Show MoreA hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m
... Show MoreElectromyogram (EMG)-based Pattern Recognition (PR) systems for upper-limb prosthesis control provide promising ways to enable an intuitive control of the prostheses with multiple degrees of freedom and fast reaction times. However, the lack of robustness of the PR systems may limit their usability. In this paper, a novel adaptive time windowing framework is proposed to enhance the performance of the PR systems by focusing on their windowing and classification steps. The proposed framework estimates the output probabilities of each class and outputs a movement only if a decision with a probability above a certain threshold is achieved. Otherwise (i.e., all probability values are below the threshold), the window size of the EMG signa
... Show MoreThis work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.
The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20
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