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jeasiq-3045
The Cluster Analysis by Using Nonparametric Cubic B-Spline Modeling for Longitudinal Data
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Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroups by penalizing the pairwise distances between the coefficients of the cubic B-spline model using one of the common penalize functions, the Minimax Concave Penalty function (MCP). This method, in turn, works to determine the number of clusters through one of the model selection criteria, Bayesian information criteria (BIC), and we used optimization methods to solve their equations. Therefore, we applied the alternative direction method of the ADMM multiplier algorithm to reach approximate solutions to find the estimators of the nonparametric model using R statistical software.
Longitudinally balanced data were generated in the simulation study, as the number of subjects was 60 and the number of repeats (time) was 10 for each subject. The simulation was iterated 100 times, and it showed that employing the MCP partial methods on the cubic model can group profiles into clusters, which is the aim of this paper.

 

Paper type: Research paper.

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Publication Date
Mon Apr 01 2019
Journal Name
2019 International Conference On Automation, Computational And Technology Management (icactm)
Multi-Resolution Hierarchical Structure for Efficient Data Aggregation and Mining of Big Data
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Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

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Publication Date
Thu Dec 01 2011
Journal Name
Iraqi Journal Of Physics
Multilayer Perceptron for analyzing satellite data
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Different ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Data Aggregation in Wireless Sensor Networks Using Modified Voronoi Fuzzy Clustering Algorithm
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Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le

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Publication Date
Wed Dec 03 2025
Journal Name
University Of Kirkuk Journal For Administrative And Economic Science
Anova For Fuzzy Data With Practical in The Medical Field
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This research study Blur groups (Fuzzy Sets) which is the perception of the most modern in the application in various practical and theoretical areas and in various fields of life, was addressed to the fuzzy random variable whose value is not real, but the numbers Millbh because it expresses the mysterious phenomena or uncertain with measurements are not assertive. Fuzzy data were presented for binocular test and analysis of variance method of random Fuzzy variables , where this method depends on a number of assumptions, which is a problem that prevents the use of this method in the case of non-realized.

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Publication Date
Tue Jan 01 2019
Journal Name
Indian Journal Of Ecology
Horizontal variability of some soil properties in wasit governorate by using time series analysis
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Publication Date
Tue Mar 21 2023
Journal Name
International Journal Of Interactive Mobile Technologies (ijim)
Study the Effect of Using Google Classroom on the Academic Performance Under the Covid19 Pandemic Using Data Mining Technique
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— In light of the pandemic that has swept the world, the use of e-learning in educational institutions has become an urgent necessity for continued knowledge communication with students. Educational institutions can benefit from the free tools that Google provide and from these applications, Google classroom which is characterized by ease of use, but the efficiency of using Google classroom is affected by several variables not studied in previous studies Clearly, this study aimed to identify the use of Google classroom as a system for managing e-learning and the factors affecting the performance of students and lecturer. The data of this study were collected from 219 members of the faculty and students at the College of Administra

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Chaotic behaviour of the Rossler model and its analysis by using bifurcations of limit cycles and chaotic attractors
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The behaviour of certain dynamical nonlinear systems are described in term as chaos, i.e., systems' variables change with the time, displaying very sensitivity to initial conditions of chaotic dynamics. In this paper, we study archetype systems of ordinary differential equations in two-dimensional phase spaces of the Rössler model. A system displays continuous time chaos and is explained by three coupled nonlinear differential equations. We study its characteristics and determine the control parameters that lead to different behavior of the system output, periodic, quasi-periodic and chaos. The time series, attractor, Fast Fourier Transformation and bifurcation diagram for different values have been described.

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Publication Date
Thu Feb 29 2024
Journal Name
Banks And Bank Systems
Fiscal and real repercussions of the Central Bank of Iraq’s real estate initiatives by using Multiple Correspondence Analysis
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The importance of the study stems from the fact that Iraq’s economy is facing a housing crisis, especially in the Iraqi capital, Baghdad, great demographic pressure due to pronounced population growth over the past two decades. The Central Bank of Iraq undertakes several initiatives represented in granting real estate loans, mainly through the Real Estate Bank at very low interest, and in the last two years, the interest has become zero. The purpose of the study is to analyze the fiscal implications of the Iraqi central bank’s real estate initiatives, as well as its real impact on the spatial dimension of the Iraqi governorates through new housing in those governorates. Using data mainly from the Central Bank of Iraq’s bulleti

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
The Prevalence of Hepatitis B Virus in High Risk Groups in Nineveh Governorate / Iraq
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Hepatitis B is an inflammation of the liver that caused by Hepatitis B virus (HBV) which is DNA virus that infects the human and some kinds of animals such as chimpanzees and birds. This disease considered as the major disease of mankind and a serious global public health problem. HBsAg, HBeAg, HBcAb, HBeAb and HBsAb are markers used to detect the presence and the stage of infection. The current study included (181) individuals from both sexes, (137) males and (44) females. By ratio 3.11: 1.The mean age of patients 2.4033 ± 0.83519 (range 18-73) years as follows < 20 (11.6%), 21–40 (47.5%), 41–60 (29.8%) and > 60 (11.0%) . These patients are 73 (40.4%) Blood donors from Central Blood Bank, 88 (48.6%) Chronic kidney failure at Ibn –

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
A New Green Approach of CFIA Technique for Direct Assay with a High Throughput of Sulfamethoxazole Drugs Using Condensation Reaction with NQS Agent
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A new design of manifold flow injection (FI) coupling with a merging zone technique was studied for sulfamethoxazole determination spectrophotometrically. The semiautomated FI method has many advantages such as being fast, simple, highly accurate, economical with high throughput . The suggested method based on the production of the orange- colored compound of SMZ with (NQS)1,2-Naphthoquinone-4-Sulphonic acid Sodium salt in alkaline media NaOH at λmax 496nm.The linearity range of sulfamethoxazole was  3-100  μg. mL-1, with (LOD) was 0.593 μg. mL-1 and the RSD% is about 1.25 and the recovery is 100.73%. All various physical and chemical parameters that have an effect on the stability and development of

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