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Epidemiological Complex Networks: A Survey
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     In this review paper, several research studies were surveyed to assist future researchers to identify available techniques in the field of infectious disease modeling across complex networks. Infectious disease modelling is becoming increasingly important because of the microbes and viruses that threaten people’s lives and societies in all respects. It has long been a focus of research in many domains, including mathematical biology, physics, computer science, engineering, economics, and the social sciences, to properly represent and analyze spreading processes. This survey first presents a brief overview of previous literature and some graphs and equations to clarify the modeling in complex networks, the detection of societies and their medical information, the identification of nodes, the method of communication with individuals and their spread, the analysis of their transmission through complex networks, and the detection of mathematical methods over the past century. Secondly, the types of epidemiological models and complex networks and the extent of their impact on humans are presented.

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Publication Date
Tue Mar 25 2014
Journal Name
Sensors
Minimal Camera Networks for 3D Image Based Modeling of Cultural Heritage Objects
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Publication Date
Fri May 01 2020
Journal Name
International Journal Of Advanced Science And Technology
Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval
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Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CN

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Fri Apr 01 2022
Journal Name
Journal Of Engineering
Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks
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The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

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Publication Date
Mon Jul 06 2026
Journal Name
Iraqi Journal For Computer Science And Mathematics
Enhanced Intrusion Detection Using Recurrent Neural Networks with Amino Acid Codon Features
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Intrusion Detection Systems (IDS) is the main defense mechanism deployed by the current networks to prevent cyber threats. Recurrent Neural Network (RNN) are also a novel IDS structure that replaces the conventional training and testing mechanism. The strategy encodes network traffic data as biological sequences using amino acid codons in such a fashion that the RNN is capable of effectively analyzing temporal and sequence data patterns. RNN architecture design adopts embedding layers to handle codon representations and Long Short-Term Memory (LSTM) layers to perform sequential data learning, which is followed by a fully connected network to perform classification functions, which preserve high feature extraction and classification

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Publication Date
Mon Dec 31 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
ELEMENTS OF MARKETING MIX AND THEIR ROLE IN CONSUMER PERCEPTION OF BRAND IMAGE: A SURVEY OF SAMPLE OPINIONS FROM CONSUMERS OF ENIEM BRAND IN THE ALGERIAN MARKET.: ELEMENTS OF MARKETING MIX AND THEIR ROLE IN CONSUMER PERCEPTION OF BRAND IMAGE: A SURVEY OF SAMPLE OPINIONS FROM CONSUMERS OF ENIEM BRAND IN THE ALGERIAN MARKET.
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The current research aimed to analyze the importance, correlation and the effect of independent variables represented by marketing variables on the dependent variable represented by local brand, through taking ENIEM as a model for this study, which represents a sensitive sector for the Algerian consumer. The results of the study evinced that the Algerian consumer has a positive image toward the brand ENIEM given marketing variables which has acquired considerable importance to this consumer. Also, the results of this study showed a statistically significant correlation between marketing variables and good perception toward the brand ENIEM, at the same time, the existence of a statistically significant effect for each of these variables o

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Publication Date
Mon Jun 20 2022
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
ALLIANCE BETWEEN BARN SWALLOW HIRUNDO RUSTICA LINNAEUS, 1758 AND INDIAN MUSTARD BRASSICA JUNCEA (L.) CZERNAJEW, 1859: A NEW INTUITION IN BIRD-PLANT ECOLOGICAL NETWORKS
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The habitat type and food availability always influence the population size of many
organisms. Bird’s feeding pattern should be abstracted to complete avian community structure
data. The agronomy main research farm of Orissa University of Agriculture and Technology
is a well-managed multi-crop agro-ecosystem which provides a suitable ground for ecological
research. In a multi-crop farmland, the association of Barn Swallow Hirundo rustica Linnaeus,
1758, with the Indian mustard Brassica juncea (L.) Czernajew, 1859 crops have been
recorded for the first time while hovering only on this field. A flock of Barn swallows was
recorded in 32 field visits while flying continuously over the Indian mustard field after
flow

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Publication Date
Mon Mar 30 2020
Journal Name
Plant Archives
Survey of the insect pests from some orchards in the middle of Iraq
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Publication Date
Mon Feb 28 2022
Journal Name
Gsc Biological And Pharmaceutical Sciences
Survey of some plant for the Razzaza Lake and adjacent areas in Iraq
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The study showed that there are (28) plant families present in Al-Razzaza Lake. The families are (Amaranthaceae, Amaryllidaceae, Aizoaceae, Apiaceae, Apocynaceae, Asteraceae, Brassicaceae, Boraginaceae, Capparaceae, Caryophyllaceae, Cistaceae, Colchicaceae, Convolvulaceae, Cynomoriaceae, Fabaceae, Frankeniaceae, Lamiaceae, Liliaceae, Malvaceae, Orobanchaceae, Plantaginaceae, Poaceae, Polygonaceae, Ranunculaceae, Solanaceae, Tamaricaceae,Typhaceae, Zygophyllaceae). Asteraceae family is the largest number of species found in abundance in this lake, followed by the Fabaceae family.

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Publication Date
Sun Oct 21 2018
Journal Name
Al–bahith Al–a'alami
The credibility of the official government spokesman to the Iraqi public / Survey Study
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The official spokesperson considered responsible for the transmission of information and communication messages that convey the government’s view on the various political and economic issues that affect the public opinion towards the performance achieved by the various governmental institutions and for the purpose of communicating with the media in a positive and effective manner, a number of institutions in the world in general and in Iraq in particular have nominated a spokesman to coordinate the efforts and the dissemination of news and the preparation of press conferences to contribute to the achievement of a positive and effective level between the government and the media, so this study has tackled to deal with the credibility of

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