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Association rules mining using cuckoo search algorithm
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Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.

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Publication Date
Sun Jul 01 2018
Journal Name
Ieee Transactions On Intelligent Transportation Systems
Real-Time Intersection-Based Segment Aware Routing Algorithm for Urban Vehicular Networks
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High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination

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Publication Date
Mon Sep 25 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Algorithm to Solve Linear Volterra Fractional Integro-Differential Equation via Elzaki Transform
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       In this work, Elzaki transform (ET) introduced by Tarig Elzaki is applied to solve linear Volterra fractional integro-differential equations (LVFIDE). The fractional derivative is considered in the Riemman-Liouville sense. The procedure is based on the application of (ET) to (LVFIDE) and using properties of (ET) and its inverse. Finally, some examples are solved to show that this is computationally efficient and accurate.

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
An Efficient Algorithm for Fuzzy Linear Fractional Programming Problems via Ranking Function
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In many applications such as production, planning, the decision maker is important in optimizing an objective function that has fuzzy ratio two functions which can be handed using fuzzy fractional programming problem technique. A special class of optimization technique named fuzzy fractional programming problem is considered in this work when the coefficients of objective function are fuzzy. New ranking function is proposed and used to convert the data of the fuzzy fractional programming problem from fuzzy number to crisp number so that the shortcoming when treating the original fuzzy problem can be avoided. Here a novel ranking function approach of ordinary fuzzy numbers is adopted for ranking of triangular fuzzy numbers with simpler an

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Publication Date
Thu Jul 01 2021
Journal Name
Journal Of Physics: Conference Series
An Evolutionary Algorithm for Task scheduling Problem in the Cloud-Fog environment
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Abstract<p>The rapid and enormous growth of the Internet of Things, as well as its widespread adoption, has resulted in the production of massive quantities of data that must be processed and sent to the cloud, but the delay in processing the data and the time it takes to send it to the cloud has resulted in the emergence of fog, a new generation of cloud in which the fog serves as an extension of cloud services at the edge of the network, reducing latency and traffic. The distribution of computational resources to minimize makespan and running costs is one of the disadvantages of fog computing. This paper provides a new approach for improving the task scheduling problem in a Cloud-Fog environme</p> ... Show More
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Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Counting Functions to Generate The Primes in the RSA Algorithm and Diffie-Hellman Key Exchange
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        The Rivest–Shamir–Adleman (RSA) and the Diffie-Hellman (DH) key exchange are famous methods for encryption. These methods  depended on selecting the primes p and q in order  to be secure enough . This paper shows that the named methods used the primes which are found by some arithmetical function .In the other sense, no need to think about getting primes p and q and how they are secure enough, since the arithmetical function enable to build the primes in such complicated way to be secure. Moreover, this article   gives  new construction  of the  RSA  algorithm and DH key  exchange using the

primes p,qfrom areal number x.

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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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Publication Date
Mon Jul 07 2025
Journal Name
Modern Sport
Job commitment and its relation to the behavior of citizenship in physical education teachers Directorate of Education Baghdad AL- Karkh THird Search submitted by Research
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Publication Date
Tue Jun 25 2024
Journal Name
World Academy Of Sciences Journal
Expression of programmed death ligand 1 in patients with triple‑negative breast cancer: Association with clinicopathological parameters
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The utilization of targeted therapy for programmed death ligand 1 (PD‑L1) has emerged as a prominent focus in contemporary clinical trials, particularly in the context of immune checkpoint inhibitors. The prognostic significance of the expression of PD‑L1 in invasive mammary cancer remains a subject of discussion in clinical oncology, requiring further exploration, despite its recognition as a biomarker for responsiveness to anti‑PDL1 immunotherapy. The present study was conducted to investigate the immunohistological expression of PD‑L1 in women with triple‑negative breast cancer (TNBC), with a particular focus for searching for the associated clinical and pathological characteristics. The present retrospective study examined the

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Publication Date
Sat Jun 01 2024
Journal Name
Al-nahrain Journal Of Science
The Association Between Immune-Histochemical Expressions of Program Death Ligand with some Aggressive Features of Prostate Cancer
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Prostate cancer (PC), accounts for more than one-fourth of all cancer diagnoses, and the most frequently diagnosed cancer among men in 2022. The immunoglobulin (IG) Program death ligand-1(PD-1) cell surface receptor is predominantly expressed on the surface of many cells. The purpose of this study was to demonstrate the relationship between Program death ligand expression and some aggressive features of prostate cancer including perineural invasion, vascular invasion and necrosis. Thirty cases of prostate cancer with age range from 60 to 80 year old and 30 cases of normal prostate tissue with age under 25 year old were separated into two groups in a retrospective case-control

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Publication Date
Wed Nov 01 2023
Journal Name
Journal Of Medicine And Life
Association between <i>CNR1</i> gene polymorphisms and susceptibility to diabetic nephropathy in Iraqi patients with T2DM
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In individuals with type 2 diabetes mellitus (T2DM), the cannabinoid receptor 1 (CNR1) gene polymorphism has been linked to diabetic nephropathy (DN). Different renal disorders, including DN, have been found to alter cannabinoid (CB) receptor expression and activation. This cross-sectional study aimed to investigate the relationship between CNR1 rs1776966256 and rs1243008337 genetic variants and the risk of developing DN in Iraqi patients with T2DM. The study included 100 patients with T2DM, divided into two groups: 50 with DN and 50 without DN. Genotyping of CNR1 rs1776966256 and rs1243008337 polymorphisms was conducted using PCR in DN patients and control samples. The distribution of rs1776966256 and rs1243008337 genotypes and alleles bet

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