Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA) has been proposed.
Via using the MCA associative memory as a new trend, the proposed module goes through two phases: the
first is the training phase (which is executed once during the module installation process) and the second is
the analysis phase. Both phases will be developed through the use of MCA, each according to its process.
The training phase will take place through the learning phase of MCA, while the analysis phase will take
place through the convergence phase of MCA. The use of MCA increases the efficiency of the training
process for the proposed system by using a minimum number of training images that do not exceed 10
training images of the total number of frames in JPG format. The proposed module has been evaluated using
11,825 images that have been extracted from 11 tested videos. As a result, the module can detect the intruder
with an accuracy ratio in the range of 97%–100%. The average training process time for the training videos
was in the range of 10.2 s to 23.2 s.
Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network
... Show MoreData steganography is a technique used to hide data, secret message, within another data, cover carrier. It is considered as a part of information security. Audio steganography is a type of data steganography, where the secret message is hidden in audio carrier. This paper proposes an efficient audio steganography method that uses LSB technique. The proposed method enhances steganography performance by exploiting all carrier samples and balancing between hiding capacity and distortion ratio. It suggests an adaptive number of hiding bits for each audio sample depending on the secret message size, the cover carrier size, and the signal to noise ratio (SNR). Comparison results show that the proposed method outperforms state of the art methods
... Show MoreDigital Elevation Model (DEM) is one of the developed techniques for relief representation. The definition of a DEM construction is the modeling technique of earth surface from existing data. DEM plays a role as one of the fundamental information requirement that has been generally utilized in GIS data structures. The main aim of this research is to present a methodology for assessing DEMs generation methods. The DEMs data will be extracted from open source data e.g. Google Earth. The tested data will be compared with data produced from formal institutions such as General Directorate of Surveying. The study area has been chosen in south of Iraq (Al-Gharraf / Dhi Qar governorate. The methods of DEMs creation are kri
... Show MoreIn this paper, the behavior of structural concrete linear bar members was studied using numerical model implemented in a computer program written in MATLAB. The numerical model is based on the modified version of the procedure developed by Oukaili. The model is based on real stress-strain diagrams of concrete and steel and their secant modulus of elasticity at different loading stages. The behavior presented by normal force-axial strain and bending moment-curvature relationships is studied by calculating the secant sectional stiffness of the member. Based on secant methods, this methodology can be easily implemented using an iterative procedure to solve non-linear equations. A compari
Photonic crystal fiber interferometers are used in many sensing applications. In this work, an in-reflection photonic crystal fiber (PCF) based on Mach-Zehnder (micro-holes collapsing) (MZ) interferometer, which exhibits high sensitivity to different volatile organic compounds (VOCs), without the needing of any permeable material. The interferometer is robust, compact, and consists of a stub photonic crystal fiber of large-mode area, photonic crystal fiber spliced to standard single mode fiber (SMF) (corning-28), this splicing occurs with optimized splice loss 0.19 dB In the splice regions the voids of the holey fiber are completely collapsed, which allows the excitation and recombination of core and cladding modes. The device reflection
... Show MoreIn this paper, a national grid-connected photovoltaic (PV) system is proposed. It extracts the maximum power point (MPP) using three-incremental-steps perturb and observe (TISP&O) maximum power point tracking (MPPT) method. It improves the classic P&O by using three incremental duty ratio (ΔD) instead of a single one in the conventional P and O MPPT method. Therefore, the system's performance is improved to a higher speed and less power fluctuation around the MPP. The Boost converter controls the MPPT and then is connected to a three-phase voltage source inverter (VSI). This type of inverter needs a high and constant input voltage. A second-order low pass (LC) filter is connected to the output of VSI to reduce t
... Show MoreIn this work we present a detailed study on anisotype nGe-pSi heterojunction (HJ) used as photodetector in the wavelength range (500-1100 nm). I-V characteristics in the dark and under illumination, C-V characteristics, minority carriers lifetime (MCLT), spectral responsivity, field of view, and linearity were investigated at 300K. The results showed that the detector has maximum spectral responsivity at λ=950 nm. The photo-induced open circuit voltage decay results revealed that the MCLT of HJ was around 14.4 μs
Iron–phthalocyanine (FePc) organic photoconductive detector was fabricated using pulsed laser deposition (PLD) technique to work in ultraviolet (UV) and visible regions. The organic semiconductor material (iron phthalocyanine) was deposited on n-type silicon wafer (Si) substrates at different thicknesses (100, 200 and 300) nm. FePc organic photoconductive detector has been improved by two methods: the first is to manufacture the detector on PSi substrates, and the second is by coating the detector with polyamide–nylon polymer to enhance the photoconductivity of the FePc detector. The current–voltage (I–V) characteristics, responsivity, photocurrent gain, response time and the quantum efficiency of the fabricated photoconduc
... Show MoreAn intelligent software defined network (ISDN) based on an intelligent controller can manage and control the network in a remarkable way. In this article, a methodology is proposed to estimate the packet flow at the sensing plane in the software defined network-Internet of Things based on a partial recurrent spike neural network (PRSNN) congestion controller, to predict the next step ahead of packet flow and thus, reduce the congestion that may occur. That is, the proposed model (spike ISDN-IoT) is enhanced with a congestion controller. This controller works as a proactive controller in the proposed model. In addition, we propose another intelligent clustering controller based on an artificial neural network, which operates as a reactive co
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