In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN), Convolutional Neural Network-Slanlet Transform (CNN-SLT) model uses Slanlet Transform (SLT). The CBIR system was therefore inspected and the outcomes benchmarked. The results clearly illustrate that generally, the recommended technique outdid the rest with accuracy of 89 percent out of the three datasets that were applied in our experiments. This remarkable performance clearly illustrated that the CNN-SLT method worked well for all three datasets, where the previous phase (CNN) and the successive phase (CNN-SLT) harmoniously worked together.
Media plays an important role in shaping the mental image of their audiences for individuals, groups and organizations, States and peoples. It is the window through which overlooks the masses on events and issues, and in the light of their exposure to these means are their opinions and impressions.
Despite the importance of direct experiences in shaping opinions, drawing pictures and impressions, it is inevitable to rely on these means as individuals can not engage in direct experiences with thousands of events, issues and topics that concern their community and other societies.
There is no doubt that media is of great importance at the present time, because of its significant impact in the management of the course of pol
... Show MoreThe 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
... Show MoreInfrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was
... Show MoreThe study discusses the marketing profile of electoral candidates and politicians especially the image that takes root in the minds of voters has become more important than the ideologies in the technological era or their party affiliations and voters are no longer paying attention to the concepts of a liberal, conservative, right-wing or secular, etc. while their interests have increased towards candidates. The consultants and image experts are able to make a dramatic shift in their electoral roles. They, as specialists in the electoral arena, dominate the roles of political parties.
The importance of the study comes from the fact that the image exceeds its normal framework in our contemporary world to become political and cultural
Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use
... Show MoreBackground: Obesity tends to appear in modern societies and constitutes a significant public health problem with an increased risk of cardiovascular diseases.
Objective: This study aims to determine the agreement between actual and perceived body image in the general population.
Methods: A descriptive cross-sectional study design was conducted with a sample size of 300. The data were collected from eight major populated areas of Northern district of Karachi Sindh with a period of six months (10th January 2020 to 21st June 2020). The Figure rating questionnaire scale (FRS) was applied to collect the demographic data and perception about body weight. Body mass index (BMI) used for ass
... Show MoreThis work discusses the beginning of fractional calculus and how the Sumudu and Elzaki transforms are applied to fractional derivatives. This approach combines a double Sumudu-Elzaki transform strategy to discover analytic solutions to space-time fractional partial differential equations in Mittag-Leffler functions subject to initial and boundary conditions. Where this method gets closer and closer to the correct answer, and the technique's efficacy is demonstrated using numerical examples performed with Matlab R2015a.
Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect
... Show MoreIn this paper, we discuss physical layer security techniques in downlink networks, including eavesdroppers. The main objective of using physical layer security is delivering a perfectly secure message from a transmitter to an intended receiver in the presence of passive or active eavesdroppers who are trying to wiretap the information or disturb the network stability. In downlink networks, based on the random feature of channels to terminals, opportunistic user scheduling can be exploited as an additional tool for enhancing physical layer security. We introduce user scheduling strategies and discuss the corresponding performances according to different levels of channel state information (CSI) at the base station (BS). We show that the avai
... Show More