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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 Sep 07 2014
Journal Name
Baghdad Science Journal
Detection of RAF fusion transcripts in FFPE samples of Medullablastoma and Ependymom in Iraqi children with RT-RQPCR assays
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Medulloblastomas and ependymomas are the most common malignant brain tumors in children. However genetic abnormalities associated with their development and prognosis remain unclear. Recently two gene fusions, KIAA1549–BRAF and SRGAP3–RAF1 have been detected in a number of brain tumours. We report here our development and validation of RT-RQPCR assays to detect various isoforms of these two fusion genes in formalin fixed paraffin embedded (FFPE) tissues of medulloblastoma and ependymoma. We examined these fusion genes in 44 paediatric brain tumours, 33 medulloblastomas and 11 ependymomas. We detected both fusion transcripts in 8/33, 5/33 SRGAP3 ex10/RAF1 ex10, and 3/33 KIAA1549 ex16/BRAF ex9, meduloblastomas but none in the 11 ep

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Publication Date
Tue Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
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Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Sun Apr 30 2023
Journal Name
Al-kindy College Medical Journal
Comparison between Quantitative Computed Tomography and Dual-Energy X-Ray Absorptiometry in the Detection of Osteoporosis in Postmenopausal Women
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Background: Osteoporosis is denoted by low bone mass and microarchitectural breakdown of bone tissue, directing to increased fracture risk and bone fragility. Fractures may lead to a decreased quality of life and increased medical costs. Thus, osteoporosis is widely considered a significant health concern.

Objective. This study aimed to compare quantitative computed tomography (QCT) and dual-energy X-Ray absorptiometry (DXA) to detect osteoporosis in postmenopausal women.

Subjects and Methods. We measured spinal volumetric bone mineral density (BMD) with QCT and areal spinal and hip BMD with DXA in 164 postmenopausal women. We calculated the osteo

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Publication Date
Tue Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
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Scopus (77)
Crossref (54)
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Publication Date
Tue Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
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Scopus (77)
Crossref (54)
Scopus Clarivate Crossref
Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Serum total sialic acid levels as an indicator
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Forty patients with acute lymphoblastic leukemia(ALL) were tested for the serum levels of total sialic acid(TSA) and the immunoglobulins before and after treatnemnt with six diffrent chemotherapy protocols while significantly

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Publication Date
Thu May 01 1997
Journal Name
Polymer-plastics Technology And Engineering
An Efficient Method for Real Gas Pseudopressure Calculation
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Publication Date
Thu Apr 03 2025
Journal Name
Aip Conference Proceedings
The left-right derivation of an AT-algebra
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This work aims to introduce the concepts of left and right derivations in an AT-algebra and discuss some interesting theorems of these concepts. Also, a fuzzy derivation of an AT-subalgebra, a fuzzy right (left) derivation ideal, a fuzzy derivation of AT-subalgebra, and a fuzzy right (left) derivation ideal are studied. Finally, a level derivation of AT-algebras is defined and some propositions are achieved.

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Publication Date
Fri Jan 01 2021
Journal Name
دار الكتب والوثائق العراقيه
Fundamentals Concept in Metorology an Introductory Survey - ISBNiraq.org
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Fundamentals Concept in Metorology an Introductory Survey - ISBNiraq.org

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