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Fuzzy C means Based Evaluation Algorithms For Cancer Gene Expression Data Clustering
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The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, which is used to cluster genes. FCM allows an object to belong to two or more clusters with a membership grade between zero and one and the sum of belonging to all clusters of each gene is equal to one. This paradigm is useful when dealing with microarray data. The total time required to implement the first model is 22.2589 s. The second model combines FCM and particle swarm optimization (PSO) to obtain better results. The hybrid algorithm, i.e., FCM–PSO, uses the DB index as objective function. The experimental results show that the proposed hybrid FCM–PSO method is effective. The total time of implementation of this model is 89.6087 s. The third model combines FCM with a genetic algorithm (GA) to obtain better results. This hybrid algorithm also uses the DB index as objective function. The experimental results show that the proposed hybrid FCM–GA method is effective. Its total time of implementation is 50.8021 s. In addition, this study uses cluster validity indexes to determine the best partitioning for the underlying data. Internal validity indexes include the Jaccard, Davies Bouldin, Dunn, Xie–Beni, and silhouette. Meanwhile, external validity indexes include Minkowski, adjusted Rand, and percentage of correctly categorized pairings. Experiments conducted on brain tumor gene expression data demonstrate that the techniques used in this study outperform traditional models in terms of stability and biological significance.

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Publication Date
Tue Feb 01 2022
Journal Name
Journal Of Engineering
Self-Repairing Technique Based on Microcapsules for Cementitious Composites- A Review
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Self-repairing technology based on micro-capsules is an efficient solution for repairing cracked cementitious composites. Self-repairing based on microcapsules begins with the occurrence of cracks and develops by releasing self-repairing factors in the cracks located in concrete. Based on previous comprehensive studies, this paper provides an overview of various repairing factors and investigative methodologies. There has recently been a lack of consensus on the most efficient criteria for assessing self-repairing based on microcapsules and the smart solutions for improving capsule survival ratios during mixing. The most commonly utilized self-repairing efficiency assessment indicators are mechanical resistance and durab

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Publication Date
Sun Apr 01 2018
Journal Name
2018 9th International Conference On Information And Communication Systems (icics)
An intersection-based segment aware algorithm for geographic routing in VANETs
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In networking communication systems like vehicular ad hoc networks, the high vehicular mobility leads to rapid shifts in vehicle densities, incoherence in inter-vehicle communications, and challenges for routing algorithms. It is necessary that the routing algorithm avoids transmitting the pockets via segments where the network density is low and the scale of network disconnections is high as this could lead to packet loss, interruptions and increased communication overhead in route recovery. Hence, attention needs to be paid to both segment status and traffic. The aim of this paper is to present an intersection-based segment aware algorithm for geographic routing in vehicular ad hoc networks. This algorithm makes available the best route f

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Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Carbon-13 Characterization and Modelling for Temperature Measurement-Based Proton Frequency
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The physical substance at high energy level with specific circumstances; tend to behave harsh and complicated, meanwhile, sustaining equilibrium or non-equilibrium thermodynamic of the system. Measurement of the temperature by ordinary techniques in these cases is not applicable at all. Likewise, there is a need to apply mathematical models in numerous critical applications to measure the temperature accurately at an atomic level of the matter. Those mathematical models follow statistical rules with different distribution approaches of quantities energy of the system. However, these approaches have functional effects at microscopic and macroscopic levels of that system. Therefore, this research study represents an innovative of a wi

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Publication Date
Mon Jul 15 2019
Journal Name
Iet Microwaves, Antennas & Propagation
Hilbert metamaterial printed antenna based on organic substrates for energy harvesting
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Abstract In this study, an investigation is conducted to realise the possibility of organic materials use in radio frequency (RF) electronics for RF-energy harvesting. Iraqi palm tree remnants mixed with nickel oxide nanoparticles hosted in polyethylene, INP substrates, is proposed for this study. Moreover, a metamaterial (MTM) antenna is printed on the created INP substrate of 0.8 mm thickness using silver nanoparticles conductive ink. The fabricated antenna performances are instigated numerically than validated experimentally in terms of S11 spectra and radiation patterns. It is found that the proposed antenna shows an ultra-wide band matching bandwidth to cover the frequencies from 2.4 to 10 GHz with bore-sight gain variation from 2.2 to

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Fri Dec 01 2023
Journal Name
Ieee Antennas And Wireless Propagation Letters
Stabilized and Fast Method for Compressive-Sensing-Based Method of Moments
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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
Severity Based Light-Weight Encryption Model for Secure Medical Information System
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Publication Date
Wed May 10 2017
Journal Name
Journal Of The College Of Languages (jcl)
ФОРМИРОВАНИЕ КОММУНИКАТИВНО-РЕЧЕВОЙ КОМПЕТЕНЦИИ СТУДЕНТОВ КАФЕДРЫ Р The formation of verbal communication for students of Russian Language Department at College of Languages at University of Baghdad by using multiple technological means
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В статье рассматривается вопрос об использовании мультимедийных средств для оптимизации процесса формирования коммуникативной компетенции  в иракской аудитории с привлечением компьютерных технологий. Статья посвящена  использованию мультимедийных технологий  и  различных  приемов формирования интереса к русскому языку. Включение в процесс обучения коммуникативно-значимого, аутентичн

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Publication Date
Thu Nov 08 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
The Means and the Difficulties Faced by Maternal and Child Health Nursing Students in Obtaining Scientific Information in Practical training
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Objective: The aim of this study is to determine the means and the difficulties faced by students of
nursing maternal and child health nursing / College of Nursing / University of Baghdad in obtaining scientific
information in practical training.
Methodology: A purposive sample of (100) Nursing college student - Maternal and Child Health Nursing
Department were selected. Data were collected through the use of the questionnaire form during the
period from the November 2010 to April 2011. Descriptive statistical procedures were used to analyze the
data.
Results: The results showed that the highest percentage of members of the study sample aged between
(20-21 years), females are the most inhabitants of the city of Ba

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
The commercial dealing means in the Albidaya Walnihaya book by Iben Katheer Al Dimashqi (701-774 A.H./1301-1372 A.D.)
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Iben Katheer Al Dimashqi is considered among the eminent scholars in the eighth Hijri century / fourteenth Gregorian century. He acquired eminent academic and social standing. His book Albidaya Walnihaya is considered among the important historical sources. This book's study of the subject of commercial dealing methods clarifies that the commercial dealing methods dealt by the people throughout the successive historical eras were multiple, most prominent of which was money (whether Dirhams, Dinars, measures (mikyals), weights (like Sa') in addition to other means like usury. But here we notice that Iben Katheer stressed that usury must be prohibited because it is religiously forbidden and cited many Quranic verses and Prophetic sayings w

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