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

       Remote sensing is a source of up-to-date information. The present study relied on various approaches for gathering information, including descriptive, quantitative and quantitative analytical processes. Particularly,  we conducted the analysis of the satellite data ETM + of the satellite Landsat7 and the digital models of Digital Elevation Model of SRTM using ArcGIS9.2. The model depends on primary mathematical equations and  constitutes an essential base for GIS applications that rely on data, computer, and software, performing the processes of data entry, analysis and processing. This paper deals with the geomorphological characteristics of a selected study area in Kirkuk province. The cha

Although the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of t

      Background: Left ventricular function and volumes have major diagnostic and prognostic importance in patients with various cardiac diseases, such as ischemic heart disease which is a life-threatening heart disease condition characterized by systolic dysfunction and a decrease in cardiac output. 

According to left ventricular ejection fraction, the degree of ischemic heart disease was classified as mild, moderate, and severe. To determine cardiac function and hemodynamics, the echocardiography technique is used, which is a noninvasive diagnostic method.

Patients and Methods: The study included 216 patients between 25 and 75 years old; 121 males and 95 females; 265 normal individuals (age range: 25 to 75 years ol

       Recently, much secured data has been sent across the internet and networks. Steganography is very important because it conceals secure data in images, texts, audios, protocols, videos, or other mediums. Video steganography is the method of concealing data in frames of video format. A video is a collection of frames or images used for hidden script messages. This paper proposes a technique to encrypt secret messages using DNA and a 3D chaotic map in video frames using the raster method. This technique uses three steps: Firstly, converting video frames into raster to extract features from each frame. Secondly, encryption of secret messages using encoded forms of DNA bases, inverse/inverse complements of DNA, a

Image is an important digital information that used in many internet of things (IoT) applications such as transport, healthcare, agriculture, military, vehicles and wildlife. etc. Also, any image has very important characteristic such as large size, strong correlation and huge redundancy, therefore, encrypting it by using single key Advanced Encryption Standard (AES) through IoT communication technologies makes it vulnerable to many threats, thus, the pixels that have the same values will be encrypted to another pixels that have same values when they use the same key. The contribution of this work is to increase the security of transferred image. This paper proposed multiple key AES algorithm (MECCAES) to improve the security of the tran

     In this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used:  local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the

Enhancement of the performance for hybrid solar air conditioning system was presented in this paper. The refrigerant temperature leaving the condenser was controlled using three-way valve, this valve was installed after the compressor to regulate refrigerant flow rate towards the solar system. A control system using data logger, sensors and computer was proposed to set the opening valve ratio. The function of control program using LabVIEW software is to obtain a minimum refrigerant temperature from the condenser outlet to enhance the overall COP of the unit by increasing the degree of subcooled refrigerant. A variable load electrical heater with coiled pipe was used instead of the solar collector and the storage tank to simulate the sola