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 genoty

The research aims to identify motivated to join the Evening Studies students to the College of Education at the University of Tikrit sections. In addition to knowledge of the differences in the degree of motivation of students according to gender, specialty, educational stage. To achieve the objectives of the research scholar us a measure consisting of (34) paragraph formulated positively, have been applied to a stratified random sample strength (500) students.

    The results showed that the degree of motivation was very big on all areas of the college and class, reaching the percentage of response (84.3%), and professional motives came first prize as a percentage of (93.8%), in addition

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

ABSTRACTBackground: In Medical ethics education, improving medical student’s attitudes toward respecting the right of patients is an essential task. The medical students’ attitude has been affected by social, educational and personality background factors.Objective: To investigate medical student’s attitudes regarding medical ethics courses.Method: The study was conducted in Al-Kindy College of Medicine on academic year (2013 -2014) for the period from January to September. A cross- sectional study design was adopted with a self- administered questionnaire form distributed to medical students in the 5th-6th under graduate grades. The questionnaire consisted of 31 items relevant to student’s opinion about attitudes concerning ethi

Research aims to know the impact beyond the defined in the collection. The research community is the second school students at Baghdad University and a research sample (63) students, the number of experimental group (27) students and a control group (30) students.  The researcher was rewarded in variable lifetime for students and educational attainment and educational level of the parents and the educational level of mothers. The researcher has developed a test took the number of paragraphs (20).  A test was true after it has been submitted to the Group of arbitrators. The test was consistent with test method used and the reliability coefficient (0, 88). Either the statistical methods used by the researcher are: Pearson correla

Background Depression is one of the most common medical illnesses worldwide. Medical students during their training will be subjected to many stressors, both mentally and emotionally. Objectives Assess the prevalence of depressive symptoms among medical students and to identify any association between depressive symptoms and some socio-demographic factors.

This study aims to prepare educational sessions for the strategy (team-pair-solo) in practical volleyball lessons for female students and identifying its effect on learning the accuracy of the spiking skill in volleyball. An experimental design with experimental and control groups was employed on a purposive sample of (30) female students who were to constitute (42.254%) from their community represented by the sophomores at the College of Physical Education and Sports Sciences for Girls / University of Baghdad who are in good standing in the morning study for the academic year (2022-2023), whose total number is (71) students. According to the determinants of the experimental design, participants were divided into two equal groups, a

The current study is considered a field study to measure the level of satisfaction of the academic programs of Media Masters students. That was accomplished through surveying the attitudes of the students who are enrolled in the faculties of media at the following universities: (Petra University, The Middle East University (MEU), and Al-Yarmouk University). Those students were enrolled in the master’s program within the formal educational system during the second semester of the academic year (2015 – 2016). This survey aims to identify the services, facilities and academic programs provided by the concerned faculties. It, also, aims to identify the public relations, administrative, educational and services aspects of those faculties.

Clothes are considered a means of aesthetic and artistic expression that help to hide the flaws of the body and highlight its merits , it has importance in people's lives as it reflects the individual's idea of himself and his personality. Whereas  the appreciation  in clothing  is a reflection of a person's sense of artistic components and the application of this sense to the clothes of his choice. Regarding the differences in clothing tastes by the university students according to the following variables (gender, specialization, stage of study,  age, monthly income), the current research is considered quantitative descriptive research that is concerned with studying a phenomenon that exists in reality, measuring it

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class