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Machine learning models for predicting morphological traits and optimizing genotype and planting date in roselle (Hibiscus Sabdariffa L.)
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Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genotype-by-environment interactions. Permutation-based feature importance analysis further revealed that planting date had a more significant impact on trait variation than genotype. To identify optimal combinations of genotype and planting date for maximizing morphological traits, the RF model was integrated with the Non-dominated Sorting Genetic Algorithm II (NSGA-II). According to the RF–NSGA-II optimization results, the optimal values, including 26 branches per plant, a growth period of 176 days, 116 bolls per plant, and 1517 seed numbers per plant, were achieved with the Qaleganj genotype planted on May 5. Collectively, these findings highlight the potential of integrating machine learning and evolutionary optimization algorithms as powerful computational tools for crop improvement and agronomic decision-making.

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Publication Date
Thu Jul 01 1999
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
Insects associated with inflorescence rot disease of date in Iraq
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Four species of insects, Carpophillus obsoletus Er., Carpophilus sp., Bitoma lycnformis Wall and Scatopse sp., were found in association with infected spathes of date palm with Mauginella scaettae Cav. The later fungus was the dominant species isolated in pure cultures both from diseased spathes and from contaminated insects. Bitoma lycriformis is the first record for Iraq.

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Publication Date
Sun Dec 01 2013
Journal Name
Baghdad Science Journal
The Ecology and geographical distribution for the species of the genus Salvia L. of labiatae in Iraq
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The study included general survey of some districts of Iraq in order to determinate new distribution areas for 33 species of the genus salvia L. ,new collections obtained , new locations for many species recorded. Observed specimens in most Iraqi herbaria were studies and identified. ,the flowering period were also studied

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Publication Date
Sun Dec 01 2013
Journal Name
Baghdad Science Journal
Linear Increasing in Radial Electronic Density Distribution for K and L Shells throughout Some Be-Like Ions
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Maximum values of one particle radial electronic density distribution has been calculated by using Hartree-Fock (HF)wave function with data published by[A. Sarsa et al. Atomic Data and Nuclear Data Tables 88 (2004) 163–202] for K and L shells for some Be-like ions. The Results confirm that there is a linear behavior restricted the increasing of maximum points of one particle radial electronic density distribution for K and L shells throughout some Be-like ions. This linear behavior can be described by using the nth term formula of arithmetic sequence, that can be used to calculate the maximum radial electronic density distribution for any ion within Be like ions for Z<20.

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Publication Date
Sun Dec 01 2013
Journal Name
Baghdad Science Journal
The Ecology and geographical distribution for the species of the genus Salvia L. of labiatae in Iraq
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The study included general survey of some districts of Iraq in order to determinate new distribution areas for 33 species of the genus salvia L. ,new collections obtained , new locations for many species recorded. Observed specimens in most Iraqi herbaria were studies and identified. ,the flowering period were also studied

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Publication Date
Thu Sep 15 2022
Journal Name
Knowledge And Information Systems
Multiresolution hierarchical support vector machine for classification of large datasets
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Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

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Publication Date
Fri Sep 26 2025
Journal Name
Applied Data Science And Analysis
Deep Learning in Genomic Sequencing: Advanced Algorithms for HIV/AIDS Strain Prediction and Drug Resistance Analysis
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Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id

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Publication Date
Fri Jan 01 2021
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Evaluation of Morphological (Macroscopic and Microscopic) Parameters of Placentas in Pregnancies Complicated by Preeclampsia, Diabetes and Preeclampsia and Diabetes.
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This study was done to compare the morphometric parameters of placentas in well controlled patients with preeclampsia, diabetes, and preeclampsia-diabetes with that of normal uncomplicated placentas. Patients & Methods: A total of Twenty four placentas were freshly collected. Six placentas for control group and eighteen placentas for complicated group (preeclamptic-diabetic and preeclamptic--diabetic subgroups). The placentas were grossly examined (shape, number of cotyledons, weight, and thickness). After suitable fixation, tissue processing and sectioning, the sections were stained by hematoxylin and eosin to study the general morphology and morphometry of the following parameters: number of terminal villi, number of syncytial knots, numb

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Publication Date
Tue Feb 05 2019
Journal Name
Journal Of The College Of Education For Women
Technology Usage in English Language Teaching and Learning: Reality and Dream
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The aim of the study is to diagnose the real level of technology usage in teaching and learning EFL at university from teachers and students’ viewpoints, and see if it is possible to achieve something of the researchers’ dream - accessing top universities. Two questionnaires have been used to measure the range of technology usage in Colleges of Education for Women, Baghdad and Iraqi Universities, and College of Basic Education. The results have shown that the reality of using technology is still away from the dream. The results have been ascribed to two reasons: The first is the little knowledge of using technology in teaching, and the second is that technology is not included in the curriculum.

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
The Use of the Regression Tree and the Support Vector Machine in the Classification of the Iraqi Stock Exchange for the Period 2019-2020
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 The financial markets are one of the sectors whose data is characterized by continuous movement in most of the times and it is constantly changing, so it is difficult to predict its trends , and this leads to the need of methods , means and techniques for making decisions, and that pushes investors and analysts in the financial markets to use various and different methods in order to reach at predicting the movement of the direction of the financial markets. In order to reach the goal of making decisions in different investments, where the algorithm of the support vector machine and the CART regression tree algorithm are used to classify the stock data in order to determine

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Publication Date
Wed Nov 01 2017
Journal Name
Biochemical Engineering Journal
Waste date seed oil extract as an alternative feedstock for Poly(3-hydroxybutyrate) synthesis
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