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An edge detection algorithm matching visual contour perception
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For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.

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Publication Date
Sun Mar 01 2026
Journal Name
Journal Of Information Hiding And Multimedia Signal Processing
Designing a New Text Encryption Approach Based on Genetic Algorithm
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Today, data security is a major problem concerning organizations and indi- viduals. The confidentiality of information is associated with using reliable and robust encryption algorithms in systems. Cyber-attacks on data and systems have become prevalent and sophisticated, and are increasing rapidly; hence, the need for developing robust encryption algorithms is crucial nowadays. This paper proposes a new encryption algorithm using dynamic symmetric key cryptography to encrypt text files. It utilizes a secret key for encryption and decryption processes, where the key’s length is varied depending on the text size. This presented approach gives a trade-off between speed and security, making it suitable for various applications, such as secur

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Scopus
Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Scale-Invariant Feature Transform Algorithm with Fast Approximate Nearest Neighbor
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There is a great deal of systems dealing with image processing that are being used and developed on a daily basis. Those systems need the deployment of some basic operations such as detecting the Regions of Interest and matching those regions, in addition to the description of their properties. Those operations play a significant role in decision making which is necessary for the next operations depending on the assigned task. In order to accomplish those tasks, various algorithms have been introduced throughout years. One of the most popular algorithms is the Scale Invariant Feature Transform (SIFT). The efficiency of this algorithm is its performance in the process of detection and property description, and that is due to the fact that

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Publication Date
Fri Jan 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
BotDetectorFW: an optimized botnet detection framework based on five features-distance measures supported by comparisons of four machine learning classifiers using CICIDS2017 dataset
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<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver &amp; kroeber, overlap, and pearson correlation

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Publication Date
Fri Jan 01 2021
Journal Name
Artificial Intelligence For Covid-19
An Efficient Mixture of Deep and Machine Learning Models for COVID-19 and Tuberculosis Detection Using X-Ray Images in Resource Limited Settings
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Publication Date
Sat Oct 25 2025
Journal Name
Iet Networks
An Effective Technique of Zero‐Day Attack Detection in the Internet of Things Network Based on the Conventional Spike Neural Network Learning Method
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ABSTRACT<p>The fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and t</p> ... Show More
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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
Enhanced Chain-Cluster Based Mixed Routing Algorithm for Wireless Sensor Networks
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Energy efficiency is a significant aspect in designing robust routing protocols for wireless sensor networks (WSNs). A reliable routing protocol has to be energy efficient and adaptive to the network size. To achieve high energy conservation and data aggregation, there are two major techniques, clusters and chains. In clustering technique, sensor networks are often divided into non-overlapping subsets called clusters. In chain technique, sensor nodes will be connected with the closest two neighbors, starting with the farthest node from the base station till the closest node to the base station. Each technique has its own advantages and disadvantages which motivate some researchers to come up with a hybrid routing algorit

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Improved Firefly Algorithm with Variable Neighborhood Search for Data Clustering
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Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the

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Publication Date
Sun Oct 23 2022
Journal Name
Open Access Macedonian Journal Of Medical Sciences
Perception, Benefits, and Factors Affecting the Quality of Hospital Training Course for Pharmacy Students: A Qualitative Study with Recently Graduated Pharmacy Students
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BACKGROUND: Hospital training courses for pharmacy students were required to prepare students to meet the challenges of real-world hospital work. AIM: Because there have been few studies on the efficacy of such courses, we aimed to recognize recent graduates’ perceptions, benefits, and factors influencing the quality of hospital training courses for pharmacy students. METHODS: A qualitative study using a phenomenology approach was conducted in 2022 and included several hospitals in Baghdad, Iraq, using in-depth face-to-face individual-based semi-structured interviews. Until saturation, a convenient sample of recently graduated pharmacists was included. The obtained data were analyzed using a thematic content analysis approach

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Publication Date
Sun Jun 05 2022
Journal Name
Sport Tk-revista Euroamericana De Ciencias Del Deporte
Visual spatial attention and its impact on the accuracy of the diagonal spike in volleyball
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The primary aim of this research was to study visual spatial attention and its impact on the accuracy of the diagonal spike in volleyball. A total of 20 volleyball players of Baghdad participated in this study. The sample was homogeneous in terms of height, weight and age of the players. The tests used in the present study were: 1) Visual Spatial Attention Test. 2) Volleyball Spike Test. Based on the findings of the study, the researcher concluded that visual spatial attention has a significant impact on the accuracy of the diagonal spike in volleyball.

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Publication Date
Mon Sep 03 2018
Journal Name
Al-academy
Educational Novelty And Its Relation With Visual Thinking With The Students Of Artistic Education Department
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The two objectives of the current research are :-

  1. Uncover the views and opinions of the students of Artistic Education Department about the relation between educational novelty and its relation with visual . 
  2. Identifying the capabilities of the students of artistic education department .

            The society of the research is the  fourth class students of artistic education department -  College of Fine Arts  ( 83 students from both sexes ) .  It was chosen ( 60 ) students sample of  from both sexes by the researcher in order to conduct test upon them .The researcher has adopted descr

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