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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
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
Optimal UAV Deployment for Data Collection in Deadline-based IoT Applications
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The deployment of UAVs is one of the key challenges in UAV-based communications while using UAVs for IoT applications. In this article, a new scheme for energy efficient data collection with a deadline time for the Internet of things (IoT) using the Unmanned Aerial Vehicles (UAV) is presented. We provided a new data collection method, which was set to collect IoT node data by providing an efficient deployment and mobility of multiple UAV, used to collect data from ground internet of things devices in a given deadline time. In the proposed method, data collection was done with minimum energy consumption of IoTs as well as UAVs. In order to find an optimal solution to this problem, we will first provide a mixed integer linear programming m

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Publication Date
Mon Dec 25 2023
Journal Name
Ieee Access
ITor-SDN: Intelligent Tor Networks-Based SDN for Data Forwarding Management
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Tor (The Onion Routing) network was designed to enable users to browse the Internet anonymously. It is known for its anonymity and privacy security feature against many agents who desire to observe the area of users or chase users’ browsing conventions. This anonymity stems from the encryption and decryption of Tor traffic. That is, the client’s traffic should be subject to encryption and decryption before the sending and receiving process, which leads to delay and even interruption in data flow. The exchange of cryptographic keys between network devices plays a pivotal and critical role in facilitating secure communication and ensuring the integrity of cryptographic procedures. This essential process is time-consuming, which causes del

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Perceptually Important Points-Based Data Aggregation Method for Wireless Sensor Networks
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The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Fuzzy Subspaces For Fuzzy space of Orderings
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The purpose of this paper is to define fuzzy subspaces for fuzzy space of orderings and we prove some results about this definition in which it leads to a lot of new results on fuzzy space of orderings. Also we define the sum and product over such spaces such that: If f = < a1,…,an > and g = < b1,…bm>, their sum and product are f + g = < a1…,an, b1, …, bm> and f × g =. for all a1,…,an,b1,…,bm ? G

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Publication Date
Sun Jan 01 2017
Journal Name
Disease Markers
Genotyping of<i> IL-4</i> −590 (C&gt;T) Gene in Iraqi Asthma Patients
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This study is the first investigation in Iraq dealing with genotyping of IL-4 −590 (C>T) gene, especially in Iraqi patients with asthma. We studied forty-eight blood samples collected from patients with asthma and compared with age-matched 25 healthy individuals as controls. The polymorphism results of IL-4 −590 (C>T) gene by using amplification refractory mutation system (ARMS-PCR) showed the presence of C and T alleles and three genotypes (CC, CT, and TT). Interestingly the frequency of C allele and CC genotype was higher in patients with asthma in comparison with the same allele and geno

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Publication Date
Thu Jan 20 2022
Journal Name
Webology
Hybrid Intrusion Detection System based on DNA Encoding, Teiresias Algorithm and Clustering Method
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Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Developing Load Balancing for IoT - Cloud Computing Based on Advanced Firefly and Weighted Round Robin Algorithms
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The evolution of the Internet of things (IoT) led to connect billions of heterogeneous physical devices together to improve the quality of human life by collecting data from their environment. However, there is a need to store huge data in big storage and high computational capabilities.   Cloud computing can be used to store big data.  The data of IoT devices is transferred using two types of protocols: Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP). This paper aims to make a high performance and more reliable system through efficient use of resources. Thus, load balancing in cloud computing is used to dynamically distribute the workload across nodes to avoid overloading any individual r

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Publication Date
Sun Jul 31 2022
Journal Name
Iraqi Journal Of Science
Gentamicin Variably Affects amrZ and rhl gene Expression in Swarmer Cells of Pseudomonas aeruginosa
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       Swarming is one of the most important virulence factors used by bacteria to invade new sites. This study aimed to test the effects of gentamicin on swarming motility of Pseudomonas aeruginosa, both phenotypically and molecularly. The present results revealed that 11/25 isolates had gentamicin MIC of 1024 µg/ml.  However, gentamicin at sub-minimal inhibitory concentration significantly (P< 0.05) reduced the diameter of swarming in all P. aeruginosa isolates. Noticeably the mean and median swarming diameter before treatment with gentamicin 5.557 and 5.816 cm respectively had significantly (P < 0.001) reduced to 0.871 and 0.766 cm respectively. At the molecular level, amrZ (a global regulator of multiple genes) and

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Publication Date
Wed Aug 30 2023
Journal Name
Biomedicine
Gene expression of Interleukin-10 and Foxp3 as critical biomarkers in rheumatoid arthritis patients
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Introduction and Aim: Forkhead box P3 (FOXP3) and interleukin-10 (IL-10) are the key regulators controlling the activity of Treg cells, which are crucial for maintaining immune tolerance and reducing autoimmune reactions. The objective of this study was to investigate the potential utility of elevated levels of FOXP3 and IL-10 gene expression as a diagnostic indicator in patients with rheumatoid arthritis (RA).   Materials and Methods: The study used quantitative polymerase chain reaction (qPCR) to examine the expression levels of FOXP3 and IL-10 transcripts in whole blood samples from Iraqi patients with rheumatoid arthritis. A group of healthy control subjects were also included in the study.   Results: In blood samples taken fr

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Publication Date
Thu Nov 16 2023
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Evaluating TLR4 Gene Expression to Monitor Disease Progression in Iraqi Patients with Rheumatoid Arthritis
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Background: Toll-like receptors (TLRs) play a significant role in the activation of adaptive immunity and may have an essential role in the development of rheumatoid arthritis (RA). Objectives: To assess the gene expression of TLR4 in individuals with RA compared to healthy individuals. Methods: From July to December 2022. A total of 100 individuals were encompassed in the study, consisting of 50 individuals diagnosed with RA, of whom 42 were females and 8 were males, with an average age of 45.22 years. Additionally, there were 50 healthy control participants, 40 of whom were females and 10 were males, with an average age of 45.64 years. To assess the TLR4 transcript levels, blood samples were collected from each participant, and RN

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