When images are customized to identify changes that have occurred using techniques such as spectral signature, which can be used to extract features, they can be of great value. In this paper, it was proposed to use the spectral signature to extract information from satellite images and then classify them into four categories. Here it is based on a set of data from the Kaggle satellite imagery website that represents different categories such as clouds, deserts, water, and green areas. After preprocessing these images, the data is transformed into a spectral signature using the Fast Fourier Transform (FFT) algorithm. Then the data of each image is reduced by selecting the top 20 features and transforming them from a two-dimensional matrix to a one-dimensional vector matrix using the Vector Quantization (VQ) algorithm. The data is divided into training and testing. Then it is fed into 23 layers of deep neural networks (DNN) that classify satellite images. The result is 2,145,020 parameters, and the evaluation of performance measures was accuracy = 100%, loopback = 100%, and the result F1 = 100 %.
Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de
... Show MoreInternal control system is a safety valve that preserves economic units assets and ensure the accuracy of financial data, as well as to obligation in the laws, regulations, administrative policies ,and improve the efficiency, effectiveness and economic of operation, so it has become imperative for these units attention to internal and developed control system The research problem in exposure the economic units when the exercise of their business to many of the risks to growth or hinder the achievement of its objectives and the risks (financial, operational, strategy, risk) and not it rely on risk Assessment according to modern scientific methods, as in Brown's risk Classification, Which led to the weakness of the internal control identif
... Show MoreThe aim of this research is to identify the availability of quality standards for the websites of the Palestinian TV channels and to provide an assessment of the quality standards used by the websites of TV Channels web sites in general and Palestinian TV channels in particular. Through the use of the method of media survey method descriptive methods, and the research has reached the difference in the application of quality standards for TV Channels sites in the web sites of Palestinian TV Channels, and the development of language of visual communication for the design of those sites in exchange for the lack of access to those sites of the technical possibilities that is Provided by the Internet.
The current research dealt with the study and analysis of the documentary
program on RT satellite channel dealt with research in a problem identified
by the researcher in a major question, which is the methods of technical
processing of documentary programs in satellite channels? The goal of
identifying the channel's handling of its documentary programs.
The research is considered descriptive research in which the researcher
used the survey method, the content analysis method to analyze (12)
documentary programs, It was determined by the comprehensive inventory
method within the temporal field of research extending from 1/10/2019 to
29/12/2019.
The researcher has obtained several results, the most important
In this paper, a new modification was proposed to enhance the security level in the Blowfish algorithm by increasing the difficulty of cracking the original message which will lead to be safe against unauthorized attack. This algorithm is a symmetric variable-length key, 64-bit block cipher and it is implemented using gray scale images of different sizes. Instead of using a single key in cipher operation, another key (KEY2) of one byte length was used in the proposed algorithm which has taken place in the Feistel function in the first round both in encryption and decryption processes. In addition, the proposed modified Blowfish algorithm uses five Sboxes instead of four; the additional key (KEY2) is selected randomly from additional Sbox
... Show MoreIn this paper, we have employed a computation of three technique to reduce the computational complexity and bit rate for compressed image. These techniques are bit plane coding based on two absolute values, vector quantization VQ technique using Cache codebook and Weber's low condition. The experimental results show that the proposed techniques achieve reduce the storage size of bit plane and low computational complexity.
It is commonly known that Euler-Bernoulli’s thin beam theorem is not applicable whenever a nonlinear distribution of strain/stress occurs, such as in deep beams, or the stress distribution is discontinuous. In order to design the members experiencing such distorted stress regions, the Strut-and-Tie Model (STM) could be utilized. In this paper, experimental investigation of STM technique for three identical small-scale deep beams was conducted. The beams were simply supported and loaded statically with a concentrated load at the mid span of the beams. These deep beams had two symmetrical openings near the application point of loading. Both the deep beam, where the stress distribution cannot be assumed linear, and the ex
... Show MoreAmputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte
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