الانهار اصبحت مشبعة بثاني اوكسيد الكربون بشكل عالي وبذلك فهي تلعب دور مهم في كميات الكربون العالمية. لزيادة فهمنا حول مصادر الكربون المتوفرة في النظم البيئية النهرية، تم اجراء هذه الدراسة حول تأثير الكربون العضوي المذاب والحرارة (العوامل الرئيسية لتغير المناخ) كمحركات رئيسية لوفرة ثاني اوكسيد الكربون في الانهار. تم جمع العينات من خمسة واربعون موقع في ثلاثة اجزاء رئيسية لنهر دجلة داخل مدينة بغداد خلال فص

The research deals with the important and modern two subjects, strategic leadership which have six demotions and knowledge management
(four demotions') . the gools & the research is to know the relation & the effect them in the oil ministry (project department) , the sample was (50) persons who works in the department the questionnaire was the tool of data gathering .

The research divided to four parties, the first  to the theotical review of the research variables, the second to the research methrology, the third to analysis and discoed the empirical results the last to the conclusions and recommendations .

دور التدقيق الاستراتيجي لإدارة الموارد البشرية في بلورة القدرات التنظيمية دراسة استطلاعية في رئاسة جامعة بغداد

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.

Estimating the semantic similarity between short texts plays an increasingly prominent role in many fields related to text mining and natural language processing applications, especially with the large increase in the volume of textual data that is produced daily. Traditional approaches for calculating the degree of similarity between two texts, based on the words they share, do not perform well with short texts because two similar texts may be written in different terms by employing synonyms. As a result, short texts should be semantically compared. In this paper, a semantic similarity measurement method between texts is presented which combines knowledge-based and corpus-based semantic information to build a semantic network that repre

To achieve safe security to transfer data from the sender to receiver, cryptography is one way that is used for such purposes. However, to increase the level of data security, DNA as a new term was introduced to cryptography. The DNA can be easily used to store and transfer the data, and it becomes an effective procedure for such aims and used to implement the computation. A new cryptography system is proposed, consisting of two phases: the encryption phase and the decryption phase. The encryption phase includes six steps, starting by converting plaintext to their equivalent ASCII values and converting them to binary values. After that, the binary values are converted to DNA characters and then converted to their equivalent complementary DN

Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T