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Background: During the pandemic, Corona virus forced many people, especially students, to spend more time than before on the computer and smartphone to study and communicate. The poor posture of the body may have worse effect on its body parts , most of which is the cervical spine (forward head posture). Objective: To assess the incidence of neck pain and the associated factors among undergraduate medical students related to position during E learning Subjects and Methods: Cross-sectional study was conducted among medical students in three Iraqi universities during 2021. The sample size was 152. Online questionnaire by Google forms sampling method were used to collect the data which was analysed using SPSS 25. Results: The percentage of students who suffered cervical pain was (80.3%) of the 152 who participated in this study and the majority of those who suffered pain were complained from increase pain during the pandemic (72.1%). This study also showed the students recumbent on the floor 67 (44.1%) more than those who use the table and chair 62 (40.8%) during E-learning. The percentage of students who use the phone for more than 4 hours were (73.7%). |
It takes a lot of time to classify the banana slices by sweetness level using traditional methods. By assessing the quality of fruits more focus is placed on its sweetness as well as the color since they affect the taste. The reason for sorting banana slices by their sweetness is to estimate the ripeness of bananas using the sweetness and color values of the slices. This classifying system assists in establishing the degree of ripeness of bananas needed for processing and consumption. The purpose of this article is to compare the efficiency of the SVM-linear, SVM-polynomial, and LDA classification of the sweetness of banana slices by their LRV level. The result of the experiment showed that the highest accuracy of 96.66% was achieved by the
... Show MoreEstimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes
... Show MoreGender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea
... Show MoreAnalyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col
... Show MoreSentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l
... Show MoreBackground: The purpose of this study was to compare regional bond strength at middle and cervical thirds of the root canal among glass fiber-reinforced composite (FRC) endodontic posts cemented with different cements, using the push-out test to compare the performance (retention) of two types of luting cements; polycarboxylate cement and Zinc phosphate cement used to cement translucent fiber post and to compare the result of the push-out test at different storage times;1 week ,1month and 2 months. Materials and methods: Ninety caries-free, recently extracted single-rooted human teeth with straight root canals was used in this study, The root canals were endodontically instrumented at a working length of 0.5 mm from the apex by m
... Show MoreObjective: To assess the effect of six-minute walk test on health-related quality of life in patients undergone coronary artery bypass graft surgery at Iraqi center for heart diseases. Material: This descriptive study was conducted from 8th August, 2022 to 10th January, 2023. A non-probability purposive sample of 50 patients undergoing coronary artery bypass graft surgery at Iraqi center for heart diseases was included in the study. A questionnaire composed of three parts; sociodemographic and clinical data, six-minute walk test (6MWT) and health-related quality of life (HRQoL) were used. SPSS version 26 was utilized to analyze data. Results: Patient’s performance showed highly significant statistical differences at p<0.05 betw
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