يهدف البحث الحالي إلى معرفة اثر التدريس بطريقة التنقيب الحواري في حفظ النصوص الأدبية لدى طلبة قسم اللغة الكردية، اختارت الباحثة طلبة المرحلة الثانية في قسم اللغة الكردية بكلية التربية ابن رشد، للعام الدراسي
(2008-2009) ميدان لتطبيق تجربتها.
تألفت عينة الدراسة من (48) طالبا وطالبة، تم توزيعها عشوائيا إلى مجموعتين، مجموعة ضابطة (درست بالطريقة الاعتيادية) تألفت من (23) طالبا وطالبة ومجموعة تجريبية (درست بطريقة الت

رمت الدراسة التعرف بمستويات التفكير الهندسي لدى طلبة قسم الرياضيات في كلية التربية / ابن الهيثم - جامعة بغداد، ولتحقيق هدف الدراسة تم اعتماد مقياس الحربي(2003) المعد على البيئة السعودية ويتكون من (25)  فقرة موزعه على خمسة مستويات وهي (المستوى البصري ، التحليلي ، شبه الاستدلالي، الاستدلالي، المجرد وبلغت عينة الدراسة (206) طلاب من طلبة قسم الرياضيات في كلية التربية- ابن الهيثم بجامعة بغداد تم اختيارهم بالطريقة ال

هدف البحث الحالي الى قياس اسلوب الفكر المثالي عند طلبة قسم الكيمياء، كلية التربية للعلوم الصرفة ابن الهيثم. وقياس مدى الفكر المثالي حسب الصف الدراسي للمرحلة الجامعية. ولتحقيق هدفا البحث تم اتباع المنهج الوصفي. وتم تحديد مجتمع البحث بجميع طلبة قسم الكيمياء وللصفوف الاربعة ( الاولى ، الثانية، الثالثة، الرابعة) . وتم اختيار مجموعة من كل صف دراسي لتكون عينة للبحث الحالي. وتم اعداد اداة لقياس التفكير المثالي عند ع

Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

Objectives: The study intends to identify the sources of work-related stress that might face the nurses working at
psychiatric wards in Baghdad psychiatric hospitals and to find out a relationship between the levels of stress and
some demographic characteristics.
Methodology: A descriptive study was achieved from the 10th of December, 2013 through the 10th of March, 2014.
Non-probability purposive samples of 94 nurses who work in psychiatric wards of Baghdad psychiatric hospitals
were recruited to meet the study objectives. Psychological Stress Inventory (PSI) the Arabic version, which was
modified by Abu Al-Hussein (2010) (20), was used. Data were analyzed by using the statistical analysis program of
SPSS 19th versi

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

Background: Depression is a common mental disorder that presents with depressed mood;it can become chronic or recurrent and affect dental health .Thus this research aimed to assess the prevalence and severity of dental caries among students with different grade of depression in relation to physicochemical characteristics of stimulated whole saliva. Materials and methods: The total sample involved for depression status assessment is composed of 800 students for both gender aged 15 years old that were selected randomly , This was performed using children depression inventory (CDI) index that divided the students into four groups of depression(low or average grade, high average grade, elevated grade and very elevated grade). The diagnosis and

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

In modern era, which requires the use of networks in the transmission of data across distances, the transport or storage of such data is required to be safe. The protection methods are developed to ensure data security. New schemes are proposed that merge crypto graphical principles with other systems to enhance information security. Chaos maps are one of interesting systems which are merged with cryptography for better encryption performance. Biometrics is considered an effective element in many access security systems. In this paper, two systems which are fingerprint biometrics and chaos logistic map are combined in the encryption of a text message to produce strong cipher that can withstand many types of attacks. The histogram analysis o

Data steganography is a technique used to hide data, secret message, within another data, cover carrier. It is considered as a part of information security. Audio steganography is a type of data steganography, where the secret message is hidden in audio carrier. This paper proposes an efficient audio steganography method that uses LSB technique. The proposed method enhances steganography performance by exploiting all carrier samples and balancing between hiding capacity and distortion ratio. It suggests an adaptive number of hiding bits for each audio sample depending on the secret message size, the cover carrier size, and the signal to noise ratio (SNR). Comparison results show that the proposed method outperforms state of the art methods