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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 Jun 30 2015
Journal Name
International Journal Of Computer Techniques
Multifractal-Based Features for Medical Images Classification
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This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

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Publication Date
Thu Oct 21 2021
Journal Name
The 3rd Al-noor International Conference Of Science And Technology 2021 Muscat-oman
Gama Platform Survey for Agent-Based Modelling
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The agent-based modeling is currently utilized extensively to analyze complex systems. It supported such growth, because it was able to convey distinct levels of interaction in a complex detailed environment. Meanwhile, agent-based models incline to be progressively complex. Thus, powerful modeling and simulation techniques are needed to address this rise in complexity. In recent years, a number of platforms for developing agent-based models have been developed. Actually, in most of the agents, often discrete representation of the environment, and one level of interaction are presented, where two or three are regarded hardly in various agent-based models. The key issue is that modellers work in these areas is not assisted by simulation plat

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Publication Date
Sat Dec 03 2022
Journal Name
Tikrit Journal Of Pure Science
A Pixel Based Method for Image Compression
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The basic solution to overcome difficult issues related to huge size of digital images is to recruited image compression techniques to reduce images size for efficient storage and fast transmission. In this paper, a new scheme of pixel base technique is proposed for grayscale image compression that implicitly utilize hybrid techniques of spatial modelling base technique of minimum residual along with transformed technique of Discrete Wavelet Transform (DWT) that also impels mixed between lossless and lossy techniques to ensure highly performance in terms of compression ratio and quality. The proposed technique has been applied on a set of standard test images and the results obtained are significantly encourage compared with Joint P

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Publication Date
Sat Oct 08 2022
Journal Name
Aro-the Scientific Journal Of Koya University
Data Analytics and Techniques
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Big data of different types, such as texts and images, are rapidly generated from the internet and other applications. Dealing with this data using traditional methods is not practical since it is available in various sizes, types, and processing speed requirements. Therefore, data analytics has become an important tool because only meaningful information is analyzed and extracted, which makes it essential for big data applications to analyze and extract useful information. This paper presents several innovative methods that use data analytics techniques to improve the analysis process and data management. Furthermore, this paper discusses how the revolution of data analytics based on artificial intelligence algorithms might provide

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Big-data Management using Map Reduce on Cloud: Case study, EEG Images' Data
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Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r

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Publication Date
Tue Mar 01 2016
Journal Name
Journal Of Pharmaceutical Sciences
Development and Evaluation of Biodegradable Particles Coloaded With Antigen and the Toll-Like Receptor Agonist, Pentaerythritol Lipid A, as a Cancer Vaccine
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Publication Date
Thu Dec 13 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Evaluation of Women's Knowledge about Risk Factors and Early Detection of Breast Cancer at Ibn Rushd College of Education in Baghdad University
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Objective: Evaluation of women's knowledge about risk factors and early detection of breast cancer at
Ibn Rushd college of education in Baghdad University.
Methodology: The study sample included (184) women in the Ibn Rushd College / University of
Baghdad, whose age ranged between (17-58) years. Data were collected through a structured
questionnaire prepared by the National Cancer Research Center which were answered during a scientific
symposium about breast cancer. The score was calculated by correcting the results of the answer, giving
one score for each correct answer and then estimating the level of knowledge and inputting all data in a
statistical program.
Results: The results showed limited level of women's

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Publication Date
Sun Jun 04 2017
Journal Name
Baghdad Science Journal
Detection of zpx gene of Cronobacter sakazakii isolated from Clinical samples for Iraqi children under Two Years
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The study included 200 samples were collected from children under two years included (50 samples from each of Cerebrospinal fluid, Blood, Stool and Urine) from, (Central Children Hospital and Children's Protections Educational Hospital) The Iraqi Ministry of Health, the Department of Health Baghdad .the period from the first of 2015 September to the first of December 2015, Were obtained isolates bacterial subjected to the cultural, microscopic and biochemical examination and diagnosed to the species by using vitek2 system .The results showed there were contamination in 6.5% of clinical samples. The diagnosed colonies which gave pink color on the MacConkey agar, golden yellow color on the Trypton Soy agar and green color on t

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
A Tri-Gene Ontology Migration Operator for Improving the Performance of Meta-heuristics in Complex Detection Problems
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      Detecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulate

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Publication Date
Sun Jun 02 2019
Journal Name
Baghdad Science Journal
Properties of a Complete Fuzzy Normed Algebra
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          The aim of this paper is to translate the basic properties of the classical complete normed algebra to the complete fuzzy normed algebra at this end a proof of multiplication fuzzy continuous is given. Also a proof of every fuzzy normed algebra  without identity can be embedded into fuzzy normed algebra  with identity  and  is an ideal in  is given. Moreover the proof of the resolvent set of a non zero element in complete fuzzy normed space is equal to the set of complex numbers is given. Finally basic properties of the resolvent space of a complete fuzzy normed algebra is given.

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