The multi-focus image fusion method can fuse more than one focused image to generate a single image with more accurate description. The purpose of image fusion is to generate one image by combining information from many source images of the same scene. In this paper, a multi-focus image fusion method is proposed with a hybrid pixel level obtained in the spatial and transform domains. The proposed method is implemented on multi-focus source images in YCbCr color space. As the first step two-level stationary wavelet transform was applied on the Y channel of two source images. The fused Y channel is implemented by using many fusion rule techniques. The Cb and Cr channels of the source images are fused using principal component analysis (PCA).

The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. The measurement results demonstrate a highly efficient capability for target detection in terms of frequency response and peak forming that was isola

Corona Virus Disease-2019 (COVID-19) is a novel virus belongs to the corona virus's family. It spreads very quickly and causes many deaths around the world. The early diagnosis of the disease can help in providing the proper therapy and saving the humans' life. However, it founded that the diagnosis of chest radiography can give an indicator of coronavirus. Thus, a Corner-based Weber Local Descriptor (CWLD) for COVID-19 diagnostics based on chest X-Ray image analysis is presented in this article. The histogram of Weber differential excitation and gradient orientation of the local regions surrounding points of interest are proposed to represent the patterns of the chest X-Ray image. Support Vector Machine (SVM) and Deep Belief Network (DBN)

Aerial manipulation of objects has a number of advantages as it is not limited by the morphology of the terrain. One of the main problems of the aerial payload process is the lack of real-time prediction of the interaction between the gripper of the aerial robot and the payload. This paper introduces a digital twin (DT) approach based on impedance control of the aerial payload transmission process. The impedance control technique is implemented to develop the target impedance based on emerging the mass of the payload and the model of the gripper fingers. Tracking the position of the interactional point between the fingers of gripper and payload, inside the impedance control, is achieved using model predictive control (MPD) approach.

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In this study, optical fibers were designed and implemented as a chemical sensor based on surface plasmon resonance (SPR) to estimate the age of the oil used in electrical transformers. The study depends on the refractive indices of the oil. The sensor was created by embedding the center portion of the optical fiber in a resin block, followed by polishing, and tapering to create the optical fiber sensor. The tapering time was 50 min. The multi-mode optical fiber was coated with 60 nm thickness gold metal. The deposition length was 4 cm. The sensor's resonance wavelength was 415 nm. The primary sensor parameters were calculated, including sensitivity (6.25), signal-to-noise ratio (2.38), figure of merit (4.88), and accuracy (3.2)

As cities across the world grow and the mobility of populations increases, there has also been a corresponding increase in the number of vehicles on roads. The result of this has been a proliferation of challenges for authorities with regard to road traffic management. A consequence of this has been congestion of traffic, more accidents, and pollution. Accidents are a still major cause of death, despite the development of sophisticated systems for traffic management and other technologies linked with vehicles. Hence, it is necessary that a common system for accident management is developed. For instance, traffic congestion in most urban areas can be alleviated by the real-time planning of routes. However, the designing of an efficie

      Detecting and subtracting the Motion objects from backgrounds is one of the most important areas. The development of cameras and their widespread use in most areas of security, surveillance, and others made face this problem. The difficulty of this area is unstable in the classification of the pixels (foreground or background). This paper proposed a suggested background subtraction algorithm based on the histogram. The classification threshold is adaptively calculated according to many tests. The performance of the proposed algorithms was compared with state-of-the-art methods in complex dynamic scenes.

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

The exponential growth of audio data shared over the internet and communication channels has raised significant concerns about the security and privacy of transmitted information. Due to high processing requirements, traditional encryption algorithms demand considerable computational effort for real-time audio encryption. To address these challenges, this paper presents a permutation for secure audio encryption using a combination of Tent and 1D logistic maps. The audio data is first shuffled using Tent map for the random permutation. The high random secret key with a length equal to the size of the audio data is then generated using a 1D logistic map. Finally, the Exclusive OR (XOR) operation is applied between the generated key and the sh

User confidentiality protection is concerning a topic in control and monitoring spaces. In image, user's faces security in concerning with compound information, abused situations, participation on global transmission media and real-world experiences are extremely significant. For minifying the counting needs for vast size of image info and for minifying the size of time needful for the image to be address computationally. consequently, partial encryption user-face is picked. This study focuses on a large technique that is designed to encrypt the user's face slightly. Primarily, dlib is utilizing for user-face detection. Susan is one of the top edge detectors with valuable localization characteristics marked edges, is used to extract