Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

   The moisture sorption isotherms of Mefenamic acid tablets were investigated by measuring the experimental equilibrium moisture content (EMC) using the static method of saturated salt solutions at three temperatures (25, 35, and 45°C) and water activity range from 0.056 to 0.8434. The results showed that EMC increased when relative humidity increased and the sorption capacity decreased, the tablets became less hygroscopic and more stable when the temperature increased at constant water activity. The sorption curves had a sigmoid shape, type II according to Brunauer’s classification. The hysteresis effect was significant along with the whole sorption process. The results were fitted to three models: Oswin, Smith, and Guggen

The research aims to define the images of financial aid that it provides within their tasks (central banks to governments) and how it can affect the indicators of banking stability, as well as monitoring the levels of banking stability in the Iraqi economy through the indicators used by the Central Bank of Iraq, and the importance of research in banking stability lies in Iraq, because any decrease in the movement of the aggregate banking stability index will reflect negatively on the financial sector in Iraq. Therefore, the Central Bank sought to provide financial aid to the government through a group of components, some of which are represented by initiatives that contribute to revitalizing the national economy and the other hel

Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

Computer systems and networks are being used in almost every aspect of our daily life, the security threats to computers and networks have increased significantly. Usually, password-based user authentication is used to authenticate the legitimate user. However, this method has many gaps such as password sharing, brute force attack, dictionary attack and guessing. Keystroke dynamics is one of the famous and inexpensive behavioral biometric technologies, which authenticate a user based on the analysis of his/her typing rhythm. In this way, intrusion becomes more difficult because the password as well as the typing speed must match with the correct keystroke patterns. This thesis considers static keystroke dynamics as a transparent layer of t

The present study aims to study the content and spatial distribution of lead (Pb) contamination in the soils of some Baghdad cities (Middle of Iraq). Twenty soil samples were randomly collected from different land-use in the studied area at a depth between 5 to 30 cm. Ten samples are collected from Al-Rissafa side areas (Adhamiya, Al-Wazeeria (Battery Manufacturer), Shikh Omer, Ziyouna, Karada, Shaab, Sadr city, Al-Za’franiya, Al-Dora expressway, and Alselikh ) and other ten samples are collected from Al-Krakh side areas Al-Dora, Al-Masafi junction, Al-Dora, Sayidia, Al-Salam university college, Al-Bayaa (Industrial District), Jehad, Amirya, Abu Ghraib, Al-hurriya, and Kadhimiya. The soil samples have been analyzed for the lead (P

Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm