This paper presents the matrix completion problem for image denoising. Three problems based on matrix norm are performing: Spectral norm minimization problem (SNP), Nuclear norm minimization problem (NNP), and Weighted nuclear norm minimization problem (WNNP). In general, images representing by a matrix this matrix contains the information of the image, some information is irrelevant or unfavorable, so to overcome this unwanted information in the image matrix, information completion is used to comperes the matrix and remove this unwanted information. The unwanted information is handled by defining {0,1}-operator under some threshold. Applying this operator on a given matrix keeps the important information in the image and removing the unwanted information by solving the matrix completion problem that is defined by P. The quadratic programming use to solve the given three norm-based minimization problems. To improve the optimal solution a weighted exponential is used to compute the weighted vector of spectral that use to improve the threshold of optimal low rank that getting from solving the nuclear norm and spectral norm problems. The result of applying the proposed method on different types of images is given by adopting some metrics. The results showed the ability of the given methods.
Secured multimedia data has grown in importance over the last few decades to safeguard multimedia content from unwanted users. Generally speaking, a number of methods have been employed to hide important visual data from eavesdroppers, one of which is chaotic encryption. This review article will examine chaotic encryption methods currently in use, highlighting their benefits and drawbacks in terms of their applicability for picture security.
In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.
... Show MoreBackground: Assessment is an important part of the learning cascade in education. Students realize it as an influential motivator to direct and guide their learning. The method of assessment determines the way the students reach high levels of learning. It has been documented that one of factor affecting students’ choice of learning approach is the way how assessment is being performed. Many methods of assessment namely multiple choice questions, essay questions and others are mainly used to assess basic science knowledge in undergraduate education. Objectives: The aim of this study is to compare multiple choice questions (MCQ) and essay questions (EQ) (record the success and failure rate of multiple choice questions (MCQ) and essay quest
... Show MoreSecure storage of confidential medical information is critical to healthcare organizations seeking to protect patient's privacy and comply with regulatory requirements. This paper presents a new scheme for secure storage of medical data using Chaskey cryptography and blockchain technology. The system uses Chaskey encryption to ensure integrity and confidentiality of medical data, blockchain technology to provide a scalable and decentralized storage solution. The system also uses Bflow segmentation and vertical segmentation technologies to enhance scalability and manage the stored data. In addition, the system uses smart contracts to enforce access control policies and other security measures. The description of the system detailing and p
... Show MoreThe COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T
... Show MoreBackground: Intestinal parasitic infections including amoebiasis, blastocystosis, giardiasis, are all worldwide distribution with harmful effects, it is an important cause of morbidity and death rate in the poor countries. Objective: This study was done to collect information of the frequency of these diseases in some regions of Baghdad. Our objectives are to detect the frequency of human pathogenic parasites in some regions of Baghdad in stool samples of patients who would attend to AL-Kindy Teaching Hospital, Medical City Teaching Hospital and to determine the most common age group affected. Materials and Methods: Data were collected from Al-Kindy Teaching Hospital and Medical City Teaching Hospital, in the lab of parasitology fro
... Show MoreElectronic learning was used as a substitute method for learning during the COVID-19 pandemic to conduct scientific materials and perform student assessment; this study aimed to investigate academic staff opinions toward electronic education. A cross-sectional study with a web-based questionnaire distributed to academic staff in different medical colleges in Iraq. After de-identification, data were collected and analyzed with statistical software to determine the significance between variables. A total of 256 participants were enrolled in the study: 83% were not satisfied or neutral to online learning, 80% showed a poor benefit from delivery of the practical electronic knowledge and 25% for theoretical sessions with a significant difference
... Show MoreThe Al-Kindy College Medical Journal (KCMJ) is an Iraqi scholarly journal published by the Al-Kindy College of Medicine, University of Baghdad. It was officially founded in 2004. It is a peer-reviewed journal, published in both online and printed forms. It has a mission to offer a publication platform that mirrors recent knowledge and findings in the field of medicine and medical sciences. It publishes various types of articles, including editorial, review article, research article, brief report, case report, and letter to editor. It accepts articles in the English language. It was biannually published till 2021 when it started to launch three issues per year. The journal is registered with numerous partners, including Iraqi Academi
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