Rutting has a significant impact on the pavements' performance. Rutting depth is often used as a parameter to assess the quality of pavements. The Asphalt Institute (AI) design method prescribes a maximum allowable rutting depth of 13mm, whereas the AASHTO design method stipulates a critical serviceability index of 2.5 which is equivalent to an average rutting depth of 15mm. In this research, static and repeated compression tests were performed to evaluate the permanent strain based on (1) the relationship between mix properties (asphalt content and type), and (2) testing temperature. The results indicated that the accumulated plastic strain was higher during the repeated load test than that during the static load tests. Notably, temperatur
... Show MoreDiacerein (DCN) is a semi-synthetic anthraquinone derivative of Rhein that is indicated for the management of osteoarthritis. Diacerein exhibits poor dissolution in the GIT fluids and suffers from low bioavailability upon oral administration in addition to the laxative effect of Rhein metabolites. The aim of the present study was to develop novasomal vesicles with optimized entrapment efficiency and size to serve as a carrier for transdermal delivery of diacerein. Novasomal vesicles were prepared by thin film hydration method thin film hydration. The prepared vesicles were optimized utilizing different surfactant to cholesterol molar ration, sonication type, different sonication times and varying fatty acid level. The prepared vesicles were
... Show MoreIn light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen
... Show MoreThe present work is an attempt to develop design data for an Iraqi roof and wall constructions using the latest ASHRAE Radiant Time Series (RTS) cooling load calculation method. The work involves calculation of cooling load theoretically by introducing the design data for Iraq, and verifies the results experimentally by field measurements. Technical specifications of Iraqi construction materials are used to derive the conduction time factors that needed in RTS method calculations. Special software published by Oklahoma state university is used to extract the conduction factors according to the technical specifications of Iraqi construction materials. Good agreement between the average theoretical and measured cooli
... Show MoreFicus (FIC) leaf extract used as corrosion inhibitor for carbon steel alloy (C.S) in two corrosive environments (saline and acidic) with four concentrations (1, 2, 3 and 4 ppm) at varied temperature range between (298-328 K) using electrochemical polarization measurements. The importance of this work focused on the use the green chemistry that is far from the chemical materials effect. The results of polarization presented the FIC inhibitor consider a mixed type (anodic and cathodic) inhibitor. Tafel curve used to evaluate the corrosion inhibition activity. In a saline medium, the best inhibitor efficiency reaches to (87%) in 2 ppm and IE% reach to (99%) for HCl medium inhibited by 1ppm. Langmuir isotherm obeys the study by thermodynamic pa
... Show MoreThe Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats. This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat
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