The study aims to identify the cognitive bias and the level of emotional thinking among university students, besides, identifying the significant differences between male and female students regarding those two variables, and determine if there is a correlation between cognitive bias and emotional thinking. To this end, two scales were adopted to collect needed data: cognitive bias scale designed by (Al-any, 2015), composed of (14) items, and emotional thinking scale designed by (Abdu Allah, 2017), consisted of (27) items. These two scales were administered to (140) students composed the study sample. They were chosen from four different colleges at Al-mustansiriyah University for the academic year (2017-1018). The findings revealed that

المقدمة :يعد سرطان المثانة من بين أكثر أنواع السرطانات انتشارًا في جميع أنحاء العالم، حيث تم الإبلاغ عن 549,393 حالة جديدة في عام 2018 وما يقرب من ٪3 من جميع تشخيصات السرطان الجديدة و ٪2.1 من جميع وفيات السرطان ناتجة عن سرطان المثانة البولية. الاهداف: تهدف هذه الدراسة إلى استكشاف كفاءة وظائف الجهاز البولي بواسطة اجراء اختبارات وظائف الكلى ومستويات الايونات لمرضى سرطان المثانة. المنهجية: تم تحديد جميع الافراد الم

Nowadays, still images are used everywhere in the digital world. The shortages of storage capacity and transmission bandwidth make efficient compression solutions essential. A revolutionary mathematics tool, wavelet transform, has already shown its power in image processing. The major topic of this paper, is improve the compresses of still images by Multiwavelet based on estimation the high Multiwavelet coefficients in high frequencies sub band  by interpolation instead of sending all Multiwavelet coefficients. When comparing the proposed approach with other compression methods Good result obtained

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

The esterification reaction of ethyl alcohol and acetic acid catalyzed by the ion exchange resin, Amberlyst 15, was investigated. The experimental study was implemented in an isothermal batch reactor. Catalyst loading, initial molar ratio, mixing time and temperature as being the most effective parameters, were extensively studied and discussed. A maximum final conversion of 75% was obtained at 70°C, acid to ethyl alcohol mole ratio of 1/2 and 10 g catalyst loading. Kinetic of the reaction was correlated with Langmuir-Hanshelwood model (LHM). The total rate constant and the adsorption equilibrium of water as a function of the temperature was calculated. The activation energies were found to be as 113876.9 and -49474.95 KJ per Kmol of ac

The aim of the present study was to distinguish between healthy children and those with epilepsy by electroencephalography (EEG). Two biomarkers including Hurst exponents (H) and Tsallis entropy (TE) were used to investigate the background activity of EEG of 10 healthy children and 10 with epilepsy. EEG artifacts were removed using Savitzky-Golay (SG) filter. As it hypothesize, there was a significant changes in irregularity and complexity in epileptic EEG in comparison with healthy control subjects using t-test (p< 0.05). The increasing in complexity changes were observed in H and TE results of epileptic subjects make them suggested EEG biomarker associated with epilepsy and a reliable tool for detection and identification of this di

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a