Natural settings make it challenging to identify facial expressions since head position, illumination level, and occlusion vary. Thus, developing a more generic model without front-facing images alone is quite crucial. This research proposes a facial expression recognition model based on pre-trained deep convolutional neural networks with transfer learning. The model was trained on several cases to classify face expressions into seven classifications efficiently. The proposed system used the EfficientNetB0 model that has one dense dropout layer. The model first rescales and norms the input dataset in the input layer that takes images of a larger resolution to get better results. After entering 7 blocks sequential in each one, the data convolution two times, then speeding up training and avoiding overfitting by adding a dropout layer and batch normalization layer. The model achieves an accuracy of 70.60% when features are frozen, and the classifier is unfrozen. In contrast, the Fine Tune model achieves the highest accuracy, 72.69%, by unfreezing the feature extractor and training the entire model.
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
... Show MoreThe 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
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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
... Show MoreThe ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi
... Show MoreManual fruit picking is labor-intensive and can damage fruit. Fully mechanized picking is efficient, but it also risks fruit damage. Therefore, semi-automated tools are needed to improve bitter orange picking. This paper presents a smart manual picker designed to facilitate picking while predicting fruit maturity based on picking force as well as various chemical and physical parameters using machine learning (ML). The study methodology consists of five stages: (1) manufacturing the smart picker, (2) picking 50 bitter orange samples, (3) measuring the characteristics of the bitter oranges in the laboratory, (4) training different ML models, and (5) identifying the most accurate model for predicting fruit maturity. The results indicate that
... Show MoreWith its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques. T
... Show MoreBackground: EBV infection in tissue micro-environment is challenged by the precisely regulated survivaland apoptosis mechanisms. Abnormal bcl-2 proto-oncogene expression in colonic carcinomas allowsaccumulation and propagation of these genetically altered cells.Objective: To analyze the relevant concordance of BCL-2 gene , EBNA1 s and LMP-1-EBV expression inissues from a group of Iraqi patients with colonic adenocarcinomas.Patients and Methods: One hundred (100) tissue biopsies, belonged to (40) patients with colorectalcancers, (40) patients with benign colon tumors, and (20) apparently normal colorectal control tissues,were enrolled in this study. The detection of EBNA1 s and LMP-1-EBV as well as BCL-2 was done byimmunohistochemist
... Show MoreThe present investigation aims to determine the effects of aflatoxin B1 (AFB1) on biotransformation and antioxidant genes and the protective effects of curcumin, present in turmeric (Curcuma longa) powder (TMP). Specifically, the study included four groups of albino mice were fed for 30 days on diet Group I: Control, Group II: animals fed on the conventional basal diet supplemented with 0.5% food grade TMP that supplied 74 mg/kg total curcuminoids. Group III contained animals reared on conventional basal diet supplemented with 1.0 ppm AFB1 supplied by ground aflatoxin culture material (760 ppm AFB1). Finally, Group IV comprised of albino mice fed with basal diet supplemented with 1.0 ppm AFB1 and 0.5% TMP that supplied 74 mg/kg of the
... Show MoreBackground: Malignant lymphomas represent about 5% of all malignancy of the head and neck region which can involve lymph nodes as well as soft tissue and bone of the maxillofacial region. Apoptosis is considered a vital component of various processes including normal cell turnover, proper development and functioning of the immune system. Inappropriate apoptosis is a factor in many human conditions including neurodegenerative diseases, ischemic damage, autoimmune disorders and many types of cancer. Expression of p53 Proteins in Hodgkin׳s and Non Hodgkin׳s lymphomas suggested that it can help in monitoring of patients and the markers may aid in controlling the progression of lymphoma and detect the degree of aggressiveness of the diseas
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