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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 Jan 01 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
The use of ARIMA, LSTM and GRU models in time series hybridization with practical application
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The importance of forecasting has emerged in the economic field in order to achieve economic growth, as forecasting is one of the important topics in the analysis of time series, and accurate forecasting of time series is one of the most important challenges in which we seek to make the best decision. The aim of the research is to suggest the use of hybrid models for forecasting the daily crude oil prices as the hybrid model consists of integrating the linear component, which represents Box Jenkins models and the non-linear component, which represents one of the methods of artificial intelligence, which is long short term memory (LSTM) and the gated recurrent unit (GRU) which represents deep learning models. It was found that the proposed h

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Publication Date
Tue Jul 19 2011
Journal Name
Archives Of Agronomy And Soil Science
Differential allelopathic potential of sunflower (Helianthus annuus L.) genotypes on weeds and wheat (Triticum aestivum L.) crop
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Studies were conducted to screen eight sunflower (Helianthus annuus L.) genotypes for their allelopathic potential against weeds and wheat crop, which customarily follows sunflower in Iraq. All sunflower genotypes significantly inhibited the total number and biomass of companion weeds and the magnitude of inhibition was genotype dependent. Among the eight genotypes tested, Sin-Altheeb and Coupon were the most weed-suppressing cultivars, and Euroflor and Shumoos were the least. A subsequent field experiment indicated that sunflower residues incorporated into the field soil significantly inhibited the total number and biomass of weeds growing in the wheat field. Sunflower genotypes Sin-Altheeb and Coupon appeared to inhibit total weed number

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Publication Date
Fri Jul 10 2020
Journal Name
Int. J. Agricult. Stat. Sci
STUDY EVALUATION AND ANALYSIS OF THE PROPERTIES OF SOME PERFORMANCE STANDARDS FOR AGRICULTURAL TRACTOR AND SORGHUM BICOLOR (L.) MOENCH YIELD
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A field experiment was conducted in an agricultural field in Al-Hindia district, Karbala governorate in a silty clay soil during the year 2020. The research included a study of two factors, the first is the depth of plowing at two levels, namely 13 and 20 cm, which represented the main blocks. The second is the tire inflation pressure at two levels, namely (70 and 140 kPa), which represented the secondary blocks. Slippage percentage, field efficiency, leaf area, and 300 grain weight were studied. The experiment was carried out using a split-plot system under a Randomized complete block design, at three replications. The tillage depth of 13 cm exceeds/transcend by giving it the least slippage of (11.01%), the highest field efficiency of (50.

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Publication Date
Fri Feb 23 2018
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Phytochemical and Pharmacological Study of Valepotriates in Valeriana officinalis L. F.Valerianeceae Cultivated in Iraq
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This study concerned with phytochemical investigation and methods of extraction and separation of active constituents from Valeriana officinalis plant cultivated in Iraq. Due to the large number of active constituents in Valeriana officinalis, it was necessary to make analytical study of its constituents to determine the chemical nature of these constituents and then determine the main classes (terpenes and iridoids) using chemical reagents specific for each class. Different organic solvents like ethanol (70%) used in soxhlet apparatus and hexane, ethyl acetate and methanol were used separately to extract the main active constituents by maceration. Through comparison between these solvents using thin layer chromatograph

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Poisson Regression and Conway Maxwell Poisson Models Using Simulation
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Regression models are one of the most important models used in modern studies, especially research and health studies because of the important results they achieve. Two regression models were used: Poisson Regression Model and Conway-Max Well-  Poisson), where this study aimed to make a comparison between the two models and choose the best one between them using the simulation method and at different sample sizes (n = 25,50,100) and with repetitions (r = 1000). The Matlab program was adopted.) to conduct a simulation experiment, where the results showed the superiority of the Poisson model through the mean square error criterion (MSE) and also through the Akaiki criterion (AIC) for the same distribution.

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Comparison among variable selection models and its application to health dataset
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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Using VGG Models with Intermediate Layer Feature Maps for Static Hand Gesture Recognition
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A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

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Publication Date
Wed Apr 01 2009
Journal Name
International Journal Of Applied Environmental Sciences
An expert System for Predicting the Effects of Noise Pollution on Grass Trimming Task Using Fuzzy Modeling
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Grass trimming operation is widely done in Malaysia for the purpose of maintaining highways. Large number of operators engaged in this work encounters high level of noise generated by back pack type grass trimmer used for this purpose. High level of noise exposure gives different kinds of ill effect on human operators. Exact nature of deteriorated work performance is not known. For predicting the work efficiency deterioration, fuzzy tool has been used in present research. It has been established that a fuzzy computing system will help in identification and analysis of fuzzy models fuzzy system offers a convenient way of representing the relationships between the inputs and outputs of a system in the form of IF-THEN rules. The paper presents

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Delignification of Date Palm Fronds using Modified Organosolv Technique
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Abstract

  In this study, modified organic solvent (organosolv) method was applied to remove high lignin content in the date palm fronds (type Al-Zahdi) which was taken from the Iraqi gardens. In modified organosolv, lignocellulosic material is fractionated into its constituents (lignin, cellulose and hemicellulose). In this process, solvent (organic)-water is brought into contact with the lignocellulosic biomass at high temperature, using stainless steel reactor (digester). Therefor; most of hemicellulose will remove from the biomass, while the solid residue (mainly cellulose) can be used in various industrial fields. Three variables were studied in this process: temperature, ratio of ethano

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Publication Date
Sat Jul 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Performance Evaluation of Two Date Palm Frond Cutting Saws
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Abstract<p>Traditional tree management is laborious and costly, thus this work aimed to study the performance of two different types of frond cutting saws (reciprocating saw and vibrating saw) and examine the two saws on five date palm varieties. Four parameters were examined, including cutting time for a single frond, the power needed for cutting a single frond, frond cutting productivity expressed as tree/h, and vibration conveyed to the worker’s hand. A field experiment was designed according to the nested randomized complete block design, including five date palm varieties as the main plot and the type of saw as a sub-plot. Means were compared using the least significant differences (LSD 0</p> ... Show More
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