Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the best optimal features while reducing the amount of data. Lastly, diagnosis prediction (classification) is achieved using learnable classifiers. The novel framework for the extraction and selection of features is based on deep learning, auto-encoder, and ACO. The performance of the proposed approach is evaluated using two medical image datasets: chest X-ray (CXR) and magnetic resonance imaging (MRI) for the prediction of the existence of COVID-19 and brain tumors. Accuracy is used as the main measure to compare the performance of the proposed approach with existing state-of-the-art methods. The proposed system achieves an average accuracy of 99.61% and 99.18%, outperforming all other methods in diagnosing the presence of COVID-19 and brain tumors, respectively. Based on the achieved results, it can be claimed that physicians or radiologists can confidently utilize the proposed approach for diagnosing COVID-19 patients and patients with specific brain tumors.
This study aims at identifying the notion of Post-Occupancy Evaluation (POE) pertinent to the performance of three general hospitals constructed inside the Sulaimani City, tracing the relationship between the quality of the indoor environments and medical staff (doctors and nurses) satisfaction level. Using some indoor environment elements in the right way will positively influence the mood, stress level of the medical staff, and patient recovery as a result. The POE toolkits (AEDET and ASPECT) have been implemented on targeted wards at the selected hospitals. AEDET and ASPECT questionnaires were distributed among 152 medical staff to obtain their perspectives. In total, 112 valid questionnaires were received. The medica
... Show MoreABSTRACT Background: Viral hepatitis places a heavy burden on the health care. Large number of patient with bleeding disorders has chronic hepatitis C infection, while few are chronic carriers of hepatitis B virus. Aims of study: evaluate the prevalence of HBV, HCV infection among patient with Von Willebrand disease and to find factors that associated with the chance of getting the infection.
Metaheuristics under the swarm intelligence (SI) class have proven to be efficient and have become popular methods for solving different optimization problems. Based on the usage of memory, metaheuristics can be classified into algorithms with memory and without memory (memory-less). The absence of memory in some metaheuristics will lead to the loss of the information gained in previous iterations. The metaheuristics tend to divert from promising areas of solutions search spaces which will lead to non-optimal solutions. This paper aims to review memory usage and its effect on the performance of the main SI-based metaheuristics. Investigation has been performed on SI metaheuristics, memory usage and memory-less metaheuristics, memory char
... Show MoreThe study aims at identifying the sources of information and explaining their role in e-learning from the viewpoint of the Iraqi college students. The researchers relied on the descriptive method of the survey method to collect data and know the point of view of undergraduate students from the Department of Information in the College of Arts / Tikrit University and the Department of Quranic Studies at the College of Arts / University of Baghdad. The questionnaire was used as an instrument of the study, the research sample is (120) students; each section has (60) male and female students. The study concluded that there are many types and forms of information sources that students receive through electronic educational platforms from text con
... Show MoreA Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton
... Show MoreTo maintain a sustained competitive position in the contemporary environment of knowledge economy, organizations as an open social systems must have an ability to learn and know how to adapt to rapid changes in a proper fashion so that organizational objectives will be achieved efficiently and effectively. A multilevel approach is adopted proposing that organizational learning suffers from the lack of interest about the strategic competitive performance of the organization. This remains implicit almost in all models of organizational learning and there is little focus on how learning organizations achieve sustainable competitive advantage . A dynamic model that captures t
... Show MoreThe recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach
... Show MoreSocio-scientific issues provide a great platform to both engage students in scientific topics and assess their understanding of scientific concepts. Nancy R. Singer, Amy Lannin, Maha Kareem, William Romine, and Katie Kline report on the STEM Literacy Project, a three-year National Science Foundation grant that aimed to improve STEM teachers’ knowledge and integration of literacy in their classrooms. They describe teachers’ professional learning, scenario-based assessments and other strategies they incorporated in their STEM classrooms, and how writing enables students to understand real-world issues.