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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
Sun Sep 03 2023
Journal Name
Iraqi Journal Of Computers, Communications, Control & Systems Engineering (ijccce)
Efficient Iris Image Recognition System Based on Machine Learning Approach
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HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023

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Publication Date
Fri Nov 03 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences( P-issn 1683 - 3597 E-issn 2521 - 3512)
Possible Protective Anticancer effect of Ethanol Fraction of Iraqi Hibiscus Tiliaceus L. Leaves Extract on Diethylnitrosamine-induced Hepatocarcinogenesis in Male Rats
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Abstract  Liver cancer with hepatocellular carcinoma a serious clinical illness that progresses quickly and has a bad prognosis because to increased malignancy. Fibrosis is the precursor of liver cancer, which progresses to cirrhosis and carcinoma Diethylnitrosamine (DEN) is a chemical molecule that has been used as a carcinogenic agent to promote cancer in test animals because of its strong carcinogenic potential. Herbal plants have long been used as inexpensive, effective alternatives to pharmaceuticals in various liver-associated complications, since they contain many bioactive compounds useful in liver disorders. Hibiscus tiliaceus L. (Malvaceae) contain various phytochemicals in the plant extracts such as Flavonoids, phe

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Publication Date
Mon Oct 30 2023
Journal Name
Aro-the Scientific Journal Of Koya University
Enhancing Upper Limb Prosthetic Control in Amputees Using Non-invasive EEG and EMG Signals with Machine Learning Techniques
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Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte

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Publication Date
Thu Mar 02 2023
Journal Name
Applied Sciences
Machine Learning Techniques to Detect a DDoS Attack in SDN: A Systematic Review
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The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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Publication Date
Sat May 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Effect of adding different level of Bay laurel (Laurus nobilis L.) powder to diet on productive performance and some physiological traits for female Quail
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Abstract<p>This study was conducted at the Poultry Research Station, Animal Resources Research Department at the Agricultural Research Department / Ministry of Agriculture - Baghdad Abu Ghraib. To find the effect of adding different proportions of Bay Laurus powder on productive performance and some physiological characteristics of birds during the production stage as Eight Hundreds Female birds of quail were used at the age of 45 days, randomly deployed to 4 treatments with two replicates (100 birds / replicate ) each, and the bay laurel powder was added in the proportions 0.0, 0.5, 1.0, and 1.5% to the diets and for a period of 60 days divided into 4 periods of 15-day .The results indicated si</p> ... Show More
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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Effect of Humic acid, Cytokinin and Arginine on Growth and Yield Traits of Bean Plant Phaseolus vulgaris L. under salt stress
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To achieve optimal plant growth and production under salt stress, some products were added in adequate quantities to give a good yield, especially bean plants which are sensitive to salinity. For this purpose, this experiment was carried out during the spring growing season in 2022 in Baghdad, to study the effects of humic acid, cytokinin, arginine and their interaction with 9 parameters that reflect the overall traits of vegetative growth and yield of common bean plants Phaseolus vulgaris L. var. Astraid (from MONARCH seeds, China). The factorial design with 3 replicates was used, each with 7 plants treated via foliar spraying or by addition to the soil. The first factor included three groups; H0, H1 and H2 (0, 6, 12 Kg.h-1 H

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Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials &amp; Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
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Publication Date
Wed Mar 01 2017
Journal Name
Auditing & Interior Magazine Of Educational &scientific Studies
Seeds morphological study of different species of Medicago L., Leguminosae (Fabaceae) family in Iraq.
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This research delts with study seven species of seeds and wild varieties wild belonging to the genus Medicago L., these species are: M. constricta Dur., M. coronata (L.) Bartal., M. intertexta (L.) Mill., M. intertexta.var. ciliaris (L.) Hyen., M. laciniata (L.) Mill., M. lupulina L., M. minima (L.) Bartal. and M. sativa L., the research involved characteristics of shapes, dimensions, colors and the nature of the surface ornamentation of seeds and also the hilum site. the seeds forms ranged between crescent, reniform and ovate, in addition there was a clear difference in seeds dimensions in height and width, while, the color has been vary between light brown to brown and dark brown. The nature of the surface ornamentation was smooth, retic

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Publication Date
Sun Jan 01 2017
Journal Name
Euphrates Journal Of Agriculture Science
EFFECT OF ERRIGATION WATER SALINITY ON SOME GROWTH AND GRAINS YIELD TRAITS OF SOME OAT CULTIVARS (Avena sativa L.)
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Two years field experiment was carried out at Agricultural Fields, College of Agriculture, Baghdad University, Al-Jadriya during 2014-2015 and 2015-2016 to determine the effect of salinity of irrigation water on growth and grain yield of three oat cultivars. The experiments were laid out according to randomized complete blocks design having split plot arrangements with two factors; first factor included three oat cultivars (Shifaa, Hamel and Pimula) while the second factor included three levels of salinity of irrigation water (3, 6 and 9 dS.m-1 ) in addition to the control (river water with salinity level of 1.164 dS.m-1 ) with three replicates. Results revealed a significant effect of salinity of irrigation water on all studied traits. Mea

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