A few examinations have endeavored to assess a definitive shear quality of a fiber fortified polymer (FRP)- strengthened solid shallow shafts. Be that as it may, need data announced for examining the solid profound pillars strengthened with FRP bars. The majority of these investigations don't think about the blend of the rigidity of both FRP support and cement. This examination builds up a basic swagger adequacy factor model to evaluate the referenced issue. Two sorts of disappointment modes; concrete part and pulverizing disappointment modes were examined. Protection from corner to corner part is chiefly given by the longitudinal FRP support, steel shear fortification, and cement rigidity. The proposed model has been confirmed util

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

The role of drain in agricultural lands is to remove excess surface and subsurface water to create a good environment for root growth and to increase crops yield. The main objective of this research was to evaluate the performance of closed drains when using textile filter instead of crushed gravel filter. The research has been executed in the laboratory using a sand tank model and by using two types of the soil. One of soils was light soil (sandy soil) and the other heavy soil (loamy soil). The tests were classified into four cases; each case was supplied discharge during 10 days. The results showed that the amount of out flow when using graded crushed gravel filter is greater than the amount of out flow in case of usin

Objectives: Many medication errors occur in the hospital, and these can endanger patients. The purpose of this study was to evaluate the incidence of medication errors in hospitalized patients, and to categorize the most frequent types of errors, and to asses the possible measures that may prevent the occurrence of such errors.
Methods: A prospective, exploratory, and evaluative study, using direct observation method to detect medication errors in adult hospitalized patients in medical and surgical units in Baquba Teaching Hospital- Diyala-Iraq.. The files of 299 patients had been reviewed from July 2009 to September 2009, including medication orders and treatment sheets to detect existing errors. The detected errors were recorded and

Antacids are commonly used drugs which are considered inert and free of pharmacological effect by many patients and physicians. They are weak bases that neutralize the gastric acid and relief pain. These weak bases dissociate to neutralize gastric acid and form neutral salts. The ultimate goal of antacid therapy is to reduce the concentration and a total load of acid in gastric juice to a pH 4 - 5. This in vitro study was promised to study the acid neutralizing capacity (ANC) of six commonly available antacids tablets in the Iraqi market by using back titration method. The highest ANC values were for Rennie (17.131± 0.083 and 16.926± 0.052 mEq) in two different hydrochloric acid (HCl) concentrations 1N and 0.5 N, respectively. The static

The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

Nowadays, the field of radionuclide treatment is enjoying an exciting stage and preparing for further growth and progress in the future. For instance, in Asia, the large spread of liver and thyroid diseases has resulted in several new developments/clinical trials using molecular radiotherapy (i.e. targeted radionuclide therapy). Iodine-124 has unique physical properties including long half-life that adding an advantage for pharmacokinetics and radiopharmaceutical analysis. One of its applications in nuclear medicine is in Positron Emission Tomography (PET).

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi