Most below-knee prostheses are manufactured in Iraq without considering the fast progress in smart prostheses, which can offer movements in the desired directions according to the type of control system designed for this purpose. The proposed design appears to have the advantages of simplicity, affordability, better load distribution, suitability for subjects with transtibial amputation, and viability in countries with people having low socio-economic status. The designed prosthetics consisted of foot, ball, and socket joints, two stepper motors, a linkage system, and an EMG shield. All these materials were available in the local markets in Iraq. The experimental results showed t

Biomarkers to detect Alzheimer’s disease (AD) would enable patients to gain access to appropriate services and may facilitate the development of new therapies. Given the large numbers of people affected by AD, there is a need for a low-cost, easy to use method to detect AD patients. Potentially, the electroencephalogram (EEG) can play a valuable role in this, but at present no single EEG biomarker is robust enough for use in practice. This study aims to provide a methodological framework for the development of robust EEG biomarkers to detect AD with a clinically acceptable performance by exploiting the combined strengths of key biomarkers. A large number of existing and novel EEG biomarkers associated with slowing of EEG, reductio

                  In light of the corona pandemic, educational institutions have moved to learning and teaching via the Internet and e-learning ,and this is considered a turning  point in course of higher education in Iraq in particular and education in general, which generated a great challenge for educational institutions to achieve the highest possible levels in practices and processes to reach the highest quality of their outputs from graduate students to the labor market that auditing performance by adopting e-learning standards is one of the effective tools that help the management of educational institutions by providing information on the ex

Abstract

      The current research aims at identifying any of the dimensions of organizational learning abilities that are more influential in the knowledge capital of the university and the extent to which they can be applied effectively at Wasit University. The current research dealt with organizational learning abilities as an explanatory variable in four dimensions (Experimentation and openness, sharing and transfer of knowledge, dialogue, interaction with the external environment ), and knowledge capital as a transient variable, with four dimensions (human capital, structural capital, client capital, operational capital). The problem of research is the following questio

This research is a study of the difficulties of learning the Arabic language that faces Arabic language learners in the Kurdistan Region, by revealing its types and forms, which can be classified into two categories:

The first type has difficulties related to the educational system, the source of which is the Arabic language itself, the Arabic teacher or the learner studying the Arabic language or the educational curriculum, i.e. educational materials, or the educational process, i.e. the method used in teaching.

The second type: general difficulties related to the political aspect, the source of which is the policy of the Kurdistan Regional Government in marginalizing the Arabic language and replacing the forefront of th

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

Background: disruptive behavioral disorders among primary school children is oone of the most popular, which has  negative social, psychological, educational, and physical repercussions on children and families. Objective: This study sought to determine effect disruptive behavioral disorders quality of learning among school chil dren. Methods: A descriptive cross-sectional design study was conducted at Baquba primary schools in Diyala Governorate,  and the study period was extended from October 6th, 2024, to January 15th, 2025. A nonprobability purposive sample was  used to include 275 teachers working at selected Baquba primary schools, Iraq. Data were collected using a self-admin istered questionnaire, two components of the st