Recognizing facial expressions and emotions is a basic skill that is learned at an early age and it is important for human social interaction. Facial expressions are one of the most powerful natural and immediate means that humans use to express their feelings and intentions. Therefore, automatic emotion recognition based on facial expressions become an interesting area in research, which had been introduced and applied in many areas such as security, safety health, and human machine interface (HMI). Facial expression recognition transition from controlled environmental conditions and their improvement and succession of recent deep learning approaches from different areas made facial expression representation mostly based on using a deep neural network that is generally divided into two critical issues. These are a variation of expression and overfitting. Expression variations such as identity bias, head pose, illumination, and overfitting formed as a result of a lack of training data. This paper firstly discussed the general background and terminology utilized in facial expression recognition in field of computer vision and image processing. Secondly, we discussed general pipeline of deep learning. After that, for facial expression recognition to classify emotion there should be datasets in order to compare the image with the datasets for classifying the emotion. Besides that we summarized, discussed, and compared illustrated various recent approaches of researchers that have used deep techniques as a base for facial expression recognition, then we briefly presented and highlighted the classification of the deep feature. Finally, we summarized the most critical challenges and issues that are widely present for overcoming, improving, and designing an efficient deep facial expression recognition system.
The automatic liquid filling system is used in different applications such as production of detergents, liquid soaps, fruit juices, milk products, bottled water, etc. The automatic bottle filling system is highly expensive. Where, the common filling systems required to complex changes in hardware and software in order to modify volume of liquid. There are many important variables in the filling process such as volume of liquid, the filling time, etc. This paper presents a new approach to develop an automatic liquid filling system. The new proposed system consists of a conveyor subsystem, filling stations, and camera to detect the level of the liquid at any instant during the filling process. The camera can detect accurately the leve
... Show MoreSo far, APT (Advanced Persistent Threats) is a constant concern for information security. Despite that, many approaches have been used in order to detect APT attacks, such as change controlling, sandboxing and network traffic analysis. However, success of 100% couldn’t be achieved. Current studies have illustrated that APTs adopt many complex techniques to evade all detection types. This paper describes and analyzes APT problems by analyzing the most common techniques, tools and pathways used by attackers. In addition, it highlights the weaknesses and strengths of the existing security solutions that have been used since the threat was identified in 2006 until 2019. Furthermore, this research proposes a new framework that can be u
... Show MorePhotonic Crystal Fiber (PCF) based on the Surface Plasmon Resonance (SPR) effect has been proposed to detect polluted water samples. The sensing characteristics are illustrated using the finite element method. The right hole of the right side of PCF core has been coated with chemically stable gold material to achieve the practical sensing approach. The performance parameter of the proposed sensor is investigated in terms of wavelength sensitivity, amplitude sensitivity, sensor resolution, and linearity of the resonant wavelength with the variation of refractive index of analyte. In the sensing range of 1.33 to 1.3624, maximum sensitivities of 1360.2 nm ∕ RIU and 184 RIU−1 are achieved with the high sensor resolutions of 7
... Show MoreThe Digital Elevation Model (DEM) has been known as a quantitative description of the surface of the Earth, which provides essential information about the terrain. DEMs are significant information sources for a number of practical applications that need surface elevation data. The open-source DEM datasets, such as the Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER), the Shuttle Radar Topography Mission (SRTM), and the Advanced Land Observing Satellite (ALOS) usually have approximately low accuracy and coarser resolution. The errors in many datasets of DEMs have already been generally examined for their importance, where their quality could be affected within different aspects, including the types of sensors, algor
... Show MoreModern ciphers are one of the more difficult to break cipher systems because these ciphers high security, high speed, non - propagation error and difficulty in breaking it. One of the most important weaknesses of stream cipher is a matching or correlation between the output key-stream and the output of shift registers.
This work considers new investigation methods for cryptanalysis stream cipher using ciphertext only attack depending on Particle Swarm Optimization (PSO) for the automatic extraction for the key. It also introduces a cryptanalysis system based on PSO with suggestion for enhancement of the performance of PSO, by using Simulated Annealing (SA). Additionally, it presents a comparison for the cryptanal
... Show MoreCipher security is becoming an important step when transmitting important information through networks. The algorithms of cryptography play major roles in providing security and avoiding hacker attacks. In this work two hybrid cryptosystems have been proposed, that combine a modification of the symmetric cryptosystem Playfair cipher called the modified Playfair cipher and two modifications of the asymmetric cryptosystem RSA called the square of RSA technique and the square RSA with Chinese remainder theorem technique. The proposed hybrid cryptosystems have two layers of encryption and decryption. In the first layer the plaintext is encrypted using modified Playfair to get the cipher text, this cipher text will be encrypted using squared
... Show MoreThe economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s
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