Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained were 96.5% and 93.47%, respectively, before applying balancing to the data. In addition, 98.59% and 97.18%, respectively, after applying the balancing technique The extreme gradient boosting (XGBoost) technique had been applied to selecting the important features and the Pearson correlation for finding the correlation between features.
The combustion and pyrolysis processes of sewage sludge were studied in the current report. Two kinds of sewage sludge(SS) were used, SS the sewage sludge was not treated, while SS-U90KHz the ultrasonic bath pre-treated sewage sludge with a frequency of 90KHz was not treated. Wastewater treatment plants are the origins of waste sludge. Analyses were performed roughly and finally. Thermogravimetric research analyzed the thermal behaviour of the analysed sewage bucket (TGA). The samples were heated at a constant rate of 25 to 800 Celsius by air (combustion) and nitrogen flow (pyrolysis). For sludges which have been investigated. In the TG/DTG curves, comparable thermal profiles were available. All of the TG/curves DTG’s were divided into th
... Show MoreThis research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
The use of blended cement in concrete provides economic, energy savings, and ecological benefits, and also provides. Improvement in the properties of materials incorporating blended cements. The major aim of this investigation is to develop blended cement technology using grinded local rocks . The research includes information on constituent materials, manufacturing processes and performance characteristics of blended cements made with replacement (10 and 20) % of grinded local rocks (limestone, quartzite and porcelinite) from cement.
The main conclusion of this study was that all ty
... Show MoreZinc oxide thin films were deposited by chemical spray pyrolysis onto glass substrates which are held at a temperature of 673 K. Some structural, electrical, optical and gas sensing properties of films were studied. The resistance of ZnO thin film exhibits a change of magnitude as the ambient gas is cycled from air to oxygen and nitrogen dioxide
The influence and hazard of fire flame are one of the most important parameters that affecting the durability and strength of structural members. This research studied the influence of fire flame on the behavior of reinforced concrete beams affected by repeated load. Nine self- compacted reinforced concrete beams were castellated, all have the same geometric layout (0.15x0.15x1.00) m, reinforcement details and compressive strength (50 Mpa).
To estimate the effect of fire flame disaster, four temperatures were adopted (200, 300, 400 and 500) oC and two method of cooling were used (graduated and sudden). In the first cooling method, graduated, the tested beams were leaved to cool in air while in the seco
... Show MoreTin Selenide (SnSe) Nano crystalline thin films of thickness 400±20 nm were deposited on glass substrate by thermal evaporation technique at R.T under a vacuum of ∼ 2 × 10− 5 mbar to study the effect of annealing temperatures (as-deposited, 100, 150 and 200) °C on its structural, surface morphology and optical properties. The films structure was characterized using X-ray diffraction (XRD) which showed that all the films have polycrystalline in nature and orthorhombic structure, with the preferred orientation along the (111) plane. These films was synthesized of very fine crystallites size of (14.8-24.5) nm, the effect of annealing temperatures on the cell parameters, crystallite size and dislocation density were observed.
... Show MoreCdS and CdS:Sn thin films were successfully deposited on glass
substrates by spray pyrolysis method. The films were grown at
substrate temperatures 300 C°. The effects of Sn concentration on the
structural and optical properties were studied.
The XRD profiles showed that the films are polycrystalline with
hexagonal structure grown preferentially along the (002) axis. The
optical studies exhibit direct allowed transition. Energy band gap
vary from 3.2 to 2.7 eV.
Background: Animal bite is one of the public health problems all over the world, especially in poor countries. Animal bites have an impact on human health due to rabies disease, which is a viral transmitted disease from animal to human with a high mortality rate.
Objective: To determine the epidemiological characteristics of animal bite cases by person, time, and place.
Method: Descriptive cross sectional study was done by reviewing cases caused by animal bites., Data including the demographic characteristics of age, gender, occupation, site of bite, and attending health institutions searching treatment were all included.
Results: There were 11600 animal bite cases. Most of bites caused by stray dogs 11577(99.8%), and the males
