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 ma

     Medical Ultrasound (US) has many features that make it widely used in the world. These features are safety, availability and low cost. However, despite these features, the ultrasound suffers from problems. These problems are speckle noise and artifacts. In this paper, a new method is proposed to improve US images by removing speckle noise and reducing artifacts to enhance the contrast of the image. The proposed method involves algorithms for image preprocessing and segmentation. A median filter is used to smooth the image in the pre-processing. Additionally, to obtain best results, applying median filter with different kernel values. We take the better output of the median filter and feed it into the Gaussian filter, which then

Nowadays, the advances in information and communication technologies open the wide door to realize the digital world’s dream. Besides, within the clear scientific scope in all fields, especially the medical field, it has become necessary to harness all the scientific capabilities to serve people, especially in medical-related services. The medical images represent the basis of clinical diagnosis and the source of telehealth and teleconsultation processes. The exchange of these images can be subject to several challenges, such as transmission bandwidth, time delivery, fraud, tampering, modifying, privacy, and more. This paper will introduce an algorithm consisting a combination of compression and encryption techniques to meet such chall

Coronavirus: (COVID-19) is a recently discovered viral disease caused by a new strain of coronavirus.

The majority of patients with corona-virus infections will have a mild-moderate respiratory disease that recovers without special care. Most often, the elderly, and others with chronic medical conditions such as asthma, coronary disease, respiratory illness, and malignancy are seriously ill.

    COVID-19 is spread mostly by salivary droplets or nasal secretions when an infected person coughs or sneezes.

    COVID-19 causes severe acute respiratory illness (SARS-COV-2). The first incidence was recorded in Wuhan, China, in 2019.  Since then it spreads leading to a pandemic.

Pandemic COVID-19 is a contagious disease affecting more than 200 countries, territories, and regions. Recently, Iraq is one of the countries that have immensely suffered from this outbreak. The Kurdistan Region of Iraq (KRI) is also prone to the disease. Until now, more than 23,000 confirmed cases have been recorded in the region. Since the onset of the COVID-19 in Wuhan, based on epidemiological modelling, researchers have used various models to predict the future of the epidemic and the time of peak, yielding diverse numbers in different countries. This study aims to estimate the basic reproductive number [R₀] for COVID-19 in KRI, using the standard SIR (Susceptible-Infected-Removed) epidemic model. A system of non

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

The covid-19 pandemic sweeping the world and has rendered a large proportion of the workforce as they are unable to commute to work. This has resulted in employees and employers seeking alternative work arrangements, including the software industry. Then comes the need for the global market and international presence of many companies to implement the global virtual teams (GVTs). GVTs members are gradually engaged in globalized business environments across space, time and organizational boundaries via information and communication technologies. Despite the advancement of technology, the project managers are still facing many challenges in communication. Hense, to become a successful project manager still a big challenge for them. This study