With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

The aim of this research is controlling the amount of the robotic hand catching force using the artificial muscle wire as an actuator to achieve the desired response of the robotic hand in order to catch different things without destroying or dropping them; where the process is to be similar to that of human hand catching way. The proper selection of the amount of the catching force is achieved through out simulation using the fuzzy control technique. The mechanism of the arrangement of the muscle wires is proposed to achieve good force selections. The results indicate the feasibility of using this proposed technique which mimics human reasoning where as the weight of the caught peace increases, the force increases also with approximatel

Metal oxide nanoparticles, including iron oxide, are highly considered as one of the most important species of nanomaterials in a varied range of applications due to their optical, magnetic, and electrical properties. Iron oxides are common compounds, extensive in nature, and easily synthesized in the laboratory. In this paper, iron oxide nanoparticles were prepared by co-precipitation of (Fe⁺²) and (Fe⁺³) ions, using iron (II and III) sulfate as precursor material and NH₄OH solution as solvent at 90°C. After the synthesis of iron oxide particles, it was characterized using X-ray diffraction (XRD), infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). These tests confirmed the obtaining o

In the present study, the removal of zinc from synthetic waste water using emulsion liquid membrane extraction technique was investigated. Synthetic surfactant solution is used as the emulsifying agent. Diphenylthiocarbazon (ditizone) was used as the extracting agent dissolved in carbon tetrachloride as the organic solvent and sulfuric acid is used as the stripping agent. The parameters that influence the extraction percentage of Zn+2 were studied. These are the ratio of volume of organic solvent to volume of aqueous feed (0.5-4), ratio of volume of surfactant solution to volume of aqueous feed (0.2-1.6), pH of the aqueous feed solution (5-10), mixing intensity (100-1000) rpm, concentration of extracting agent (20-400) ppm, surfactant co

In this study, the flow and heat transfer characteristics of Al₂O₃-water nanofluids for a range of the Reynolds number of 3000, 4500, 6000 and 7500 with a range of volume concentration of 1%, 2%, 3% and 4% are studied numerically. The test rig consists of cold liquid loop, hot liquid loop and the test section which is counter flow double pipe heat exchanger with 1m length. The inner tube is made of smooth copper with diameter of 15mm. The outer tube is made of smooth copper with diameter of 50mm. The hot liquid flows through the outer tube and the cold liquid (or nanofluid) flow through the inner tube. The boundary condition of this study is thermally insulated the outer wall with uniform velocity a

This research explores the preparation of polypyrrole (PPy) using chemical oxidation and its enhancement with graphene oxide (GO) for optical sensor applications. PPy was synthesized by polymerizing pyrrole monomers with ferric chloride (Fe2Cl3) as the oxidant. The resulting PPy was then combined with GO to form a composite material, aiming to improve its electrical and optical properties. Polypyrrole nanofibers were obtained and after adding graphene oxide, the sensitivity increased. Characterization techniques including UV-Vis spectroscopy, DC conductivity measurements, Field Emission Scanning Electron Microscopy (FESEM) and response of photocurrent analysis were employed. The incorporation of GO into PPy resulted in a significant reducti

Renewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

1267 Objectives Aim to evaluate 198Au nanoparticles (AuNP) biodistribution and uptake in a human prostate model for treatment. Many phytochemicals are known to have anti-tumor properties but have short half-lives in vivo. We hypothesized that using these phytochemicals to formulate and coat AuNP would inhibit enzyme cleavage and enhance their anti-tumor properties. Initial evaluations were performed in SCID mice bearing PC3 tumors. Methods : 198AuNP were formulated with the following gum Arabic, epigalocatechin gallate (EGCg) pomegranate extract and mangiferin extract. The resultant nanoparticles were evaluated in normal mice and in human prostate bearing SCID mice. The tumor bearing mice were injected intratumorally with 3-5 uCi of 198A