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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
Fri Feb 10 2023
Journal Name
Dentistry Journal
The Role of Social Media in Communication and Learning at the Time of COVID-19 Lockdown—An Online Survey
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This study aimed to assess orthodontic postgraduate students’ use of social media during the COVID-19 lockdown. Ninety-four postgraduate students (67 master’s students and 27 doctoral students) were enrolled in the study and asked to fill in an online questionnaire by answering questions regarding their use of social media during the COVID-19 lockdown. The frequency distributions and percentages were calculated using SPSS software. The results showed that 99% of the students used social media. The most frequently used type of social media was Facebook, 94%, followed by YouTube, 78%, and Instagram, 65%, while Twitter and Linkedin were used less, and no one used Blogger. About 63% of the students used elements of social media to l

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Publication Date
Sun Jul 06 2014
Journal Name
Journal Of Educational And Psychological Researches
The influence of Online Training Courses on Iraqi EFL Instructors Teaching and Learning Process
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For over a decade, educational technology has been used sparingly in our schools and universities. Online training courses have been used since 2003 to fill the gaps in our learning system and to add extra program besides classroom learning. This paper aims to investigate the Iraqi EFL instructors’ participating in online training courses and its influence on the process of teaching and learning.

       The sample of present study consists of 30 instructors from University of Baghdad. The questionnaire of sixteen items was constructed. After ensuring validity and reliability of questionnaire, it was applied on March 2013 and the result shows that most of instructors improve their teaching methods b

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Publication Date
Mon Apr 01 2024
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Classification of grapevine leaves images using VGG-16 and VGG-19 deep learning nets
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The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

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Publication Date
Thu Jun 30 2016
Journal Name
Al-kindy College Medical Journal
Integrated Problem Based Learning (PBL) Evaluation by Students in Kerbala Medical College
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Background: Scientific education aims to be inclusive and to improve students learning achievements, through appropriate teaching and learning. Problem Based Learning (PBL) system, a student centered method, started in the second half of the previous century and is expanding progressively, organizes learning around problems and students learn about a subject through the experience of solving these problems.Objectives:To assess the opinions of undergraduate medical students regarding learning outcomes of PBL in small group teaching and to explore their views about the role of tutors and methods of evaluation. Type of the study: A cross-sectional study.Methods: This study was conducted in Kerbala Medical Colleges among second year students

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Global Pharma Technology
Evalution of the effect of Gigaspora margarita and Glomus desriticola fungi in stimulating the resistance of the capsicum annuum L. plant towards chromium and lead
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The present study was conducted to evaluate the effect of fungi Gigaspora margarita and Glomus desriticola in stimulating the resistance of the capsicum annuum L. towards the chromium and lead after 60 days, planting and using the pots in the glass house. The highest concentration of chromium and lead in the root was found in the presence of the mycorrhizal mixture (194.93, 150.40) μg / g, respectively, compared to the lowest concentration (90.69, 79.37) μg / g respectively, while the highest concentration of chromium and lead in the shoot was found in the presence of the mycorrhizal mixture (94.63, 79.33) μg / g respectively, compared with the lowest concentration in the control treatment (72.58, 60.70) μg / g respectively. The results

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Publication Date
Wed Dec 29 2021
Journal Name
Anatolian Congresses 8th International Applied Sciences Congress
The Effect of Twin-Row Silage Maize Harvesting on Single Row Silage Machine Performance
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In this study, the harvest of maize silage with the cross double row sowing method were tested with a single row disc silage machine in two different PTO applications (540 and 540E min-1) and at two different working speeds v1, v2 (1.8 and 2.5 km h-1). The possibilities of harvesting with a single row machine were revealed, and performance characteristics such as hourly fuel consumption, field-product fuel consumption and PTO power consumption were determined in the trials. The best results in terms of hourly fuel consumption and PTO power consumption were determined in the 540E PTO application and V1 working speed. When the fuel consumption of the field-product is evaluated, it is obtained with V2 working speed and 540E PTO application. As

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Publication Date
Sun Mar 01 2020
Journal Name
Fisheries & Aquatic Life
Directional fluctuating asymmetry in certain morphological characters as a pollution indicator: Tigris catfish (<i>Silurus triostegus</i>) collected from the Euphrates, Tigris, and Shatt al-Arab Rivers in Iraq
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Abstract<p>The relationship between pollution levels in river sediment and fluctuating asymmetry of resident silurid fish species, <italic>Silurus triostegus</italic> Heckel, was assessed. Eight bilateral body proportions were analyzed in 1,500 fish from eight river locations. Sediment pollution was measured based on the analysis of heavy metals (Cd, Cr, Cu, Ni, Pb and Zn) and organochlorine pesticides (DDT, DDD, DDE, chlordane, dieldrin, and lindane). The mean quotient approach (mERMq) was used to characterize sediment toxicity, which ranged from low to moderate levels for heavy metals and from low to severe for organochlorides. Variation was noted in the measurements of fish body mor</p> ... Show More
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Publication Date
Sun Sep 25 2022
Journal Name
Lubricants
Development of Hybrid Intelligent Models for Prediction Machining Performance Measure in End Milling of Ti6Al4V Alloy with PVD Coated Tool under Dry Cutting Conditions
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Ti6Al4V alloy is widely used in aerospace and medical applications. It is classified as a difficult to machine material due to its low thermal conductivity and high chemical reactivity. In this study, hybrid intelligent models have been developed to predict surface roughness when end milling Ti6Al4V alloy with a Physical Vapor Deposition PVD coated tool under dry cutting conditions. Back propagation neural network (BPNN) has been hybridized with two heuristic optimization techniques, namely: gravitational search algorithm (GSA) and genetic algorithm (GA). Taguchi method was used with an L27 orthogonal array to generate 27 experiment runs. Design expert software was used to do analysis of variances (ANOVA). The experimental data were

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Publication Date
Fri Jun 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
The Effect of the Stability of Some Commodity Activities in Iraq on the Estimation of the Statistical Data Models for the Period (1988-2000)
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There is an assumption implicit but fundamental theory behind the decline by the time series used in the estimate, namely that the time series has a sleep feature Stationary or the language of Engle Gernger chains are integrated level zero, which indicated by I (0). It is well known, for example, tables of t-statistic is designed primarily to deal with the results of the regression that uses static strings. This assumption has been previously treated as an axiom the mid-seventies, where researchers are conducting studies of applied without taking into account the properties of time series used prior to the assessment, was to accept the results of these tests Bmanueh and delivery capabilities based on the applicability of the theo

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Publication Date
Wed May 29 2019
Journal Name
Iraqi Journal Of Physics
Improvement the efficiency of SnO2/n-Si detector by engraving method using a CNC machine
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Tin oxide was deposited by using vacuum thermal method on silicon wafer engraved by Computer Numerical Controlled (CNC) Machine. The inscription was engraved by diamond-made brine. Deep 0.05 mm in the form of concentric squares. Electrical results in the dark were shown high value of forward current and the high value of the detection factor from 6.42 before engraving to 10.41 after engraving. (I-V) characters in illumination with powers (50, 100, 150, 200, 250) mW/cm2 show Improved properties of the detector, Especially at power (150, 200, 250) mW/cm2. Response improved in rise time from 2.4 μs to 0.72 μs and time of inactivity improved 515.2 μs to 44.2 μs. Sensitivity angle increased at zone from 40o to 65o.

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