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Gene Expression Analysis via Spatial Clustering and Evaluation Indexing
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The density-based spatial clustering for applications with noise (DBSCAN) is one of the most popular applications of clustering in data mining, and it is used to identify useful patterns and interesting distributions in the underlying data. Aggregation methods for classifying nonlinear aggregated data. In particular, DNA methylations, gene expression. That show the differentially skewed by distance sites and grouped nonlinearly by cancer daisies and the change Situations for gene excretion on it. Under these conditions, DBSCAN is expected to have a desirable clustering feature i that can be used to show the results of the changes. This research reviews the DBSCAN and compares its performance with other algorithms, such as the traditional number of clustering, K-mean particle swarm optimization (PSO), and Grey–Wolf optimization (GWO). This method offers high performance for improvement. The DBSCAN algorithm also offers better results of clusters and gives better performance assessment according to the results shown in this study.

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Building a Reliable Steganography System Using Random Key in a spatial Domain of Image
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With time progress importance of hiding information become more and more and all steganography applications is like computer games between hiding and extracting data, or like thieves and police men always thieve hides from police men in different ways to keep him out of prison. The sender always hides information in new way in order not to be understood by the attackers and only the authorized receiver can open the hiding message. This paper explores our proposed random method in detail, how chooses locations of pixel in randomly , how to choose a random bit to hide information in the chosen pixel, how it different from other approaches, how applying information hiding criteria on the proposed project, and attempts to test out in code, and

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Publication Date
Thu Jan 13 2022
Journal Name
Medical & Biological Engineering & Computing
An integrated entropy-spatial framework for automatic gender recognition enhancement of emotion-based EEGs
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Publication Date
Tue Sep 07 2021
Journal Name
مجلة دراسات تربوية
Spatial variation of students in secondary school in Iraq for the 2006- 2011 period
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The research, whose goal was to study students' failure in secondary school in Iraq, found that 50% of the Iraqi governorates achieved the lowest student failure rates, and Baghdad governorate had the highest percentage of repeaters. And that half of the provinces in Iraq have males constitute 70% of the repeaters, and failure in the exam represented 79.7% of the reasons for failure, and that half of the students who failed are confined to the first and third intermediate grades at a rate of 51.9% , and the research revealed that the security instability was the most influential factor in Students fai

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Publication Date
Wed Jun 24 2026
Journal Name
Acta Scientiarum Polonorum Administratio Locorum
Reinvigorating cultural meaning through spatial experience: A triadic model for place-based architectural learning
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Historical cultural environments are a repository of values and symbols that pass down across generations through spatial experiences. Despite their intellectual and cultural potential, their role in fostering belonging and identity has declined; they are often viewed as silent landmarks, isolated from lived experiences. This highlights the need for an integrated model that makes spatial experience a stimulating process for reinvigorating the meaning inherent in historical contexts and reconnecting the new generation with their cultural roots. This research aims to explore how cultural meaning in historical contexts can be reactivated through spatial experience. To achieve this, the study proposes a triadic model – physical encoun

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Publication Date
Sun Oct 01 2017
Journal Name
Ieee Transactions On Neural Systems And Rehabilitation Engineering
A Framework of Temporal-Spatial Descriptors-Based Feature Extraction for Improved Myoelectric Pattern Recognition
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Publication Date
Fri Dec 01 2023
Journal Name
Applied Energy
Deep clustering of Lagrangian trajectory for multi-task learning to energy saving in intelligent buildings using cooperative multi-agent
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The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

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Publication Date
Tue Dec 16 2014
Journal Name
Iraqi National Journal Of Chemistry
Synthesis of Novel Heterocyclic Compounds via Schiff bases
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In the present study a series of some four-,five-and seven-membered heterocyclic compounds have been synthesized by the reaetion of Schiff bases (1a,b) with chloroacetyl chloride, sodium azide, thioglycolic acid or various anhydrides to give azetidinone (2a,b), tetrazole (3a,b), thiazolidinone (4a,b) and 1,3-oxazepine derivatives (5-8a,b) respectively. Schiff bases (1a,b)were prepared from the reaction of p-toluidine with aromatic aldehydes. All synthesized compounds were characterized by physical properties and spectral data.

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Publication Date
Sun Jan 01 2023
Journal Name
Proceedings Of International Conference On Data Science And Applications
Very Low Illumination Image Enhancement via Lightness Mapping
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Publication Date
Tue Jun 01 2021
Journal Name
Al-nahrain Journal Of Science
Medical Image Denoising Via Matrix Norm Minimization Problems
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This paper presents the matrix completion problem for image denoising. Three problems based on matrix norm are performing: Spectral norm minimization problem (SNP), Nuclear norm minimization problem (NNP), and Weighted nuclear norm minimization problem (WNNP). In general, images representing by a matrix this matrix contains the information of the image, some information is irrelevant or unfavorable, so to overcome this unwanted information in the image matrix, information completion is used to comperes the matrix and remove this unwanted information. The unwanted information is handled by defining {0,1}-operator under some threshold. Applying this operator on a given ma

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Publication Date
Fri Jan 30 2026
Journal Name
Iraqi Journal Of Science
Supra Topological Spaces Via Delta-Semi-Open Sets
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The significance of supra topological spaces as a subject of study cannot be overstated, as they represent a broader framework than traditional topological spaces. Numerous scholars have proposed extensions to supra open sets, including supra semi-open sets, supra delta-open sets and others. In this paper, the concept of supra delta-semi-open set was introduced within the generalizations of the supra topology of sets. Our investigation involves harnessing this category of sets to introduce new notions in these spaces, specifically supra delta-semi-limit points, supra delta-semi-derive points and examining their relationship with supra semi-open. Building upon this set classification, we introduce several additional concepts such as

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