IT has its impact on all aspects of life, including its planning and operations. Based on the assumption that the plan can adapt any technique as an analytical tool within broader dimensions to include society in general and meet the requirements of that society. They have neutral values, meaning and usefulness rather than being adopted as abstract goals or objectives so that the planner or the decision-maker can benefit greatly from them. This information technology is summarized in three main axes: First: Geographic Information Systems. Second: computer modeling. Third: visual simulation and the Internet. The problem of research is that the decision-making environment of the plan is surrounded by uncertain information-planning conditio

Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

A new 4-thiazolidinone, substitutedbenzylidene-thiazolidinone and tetrazole were synthesized from thiosemicarbazone and hydrazone. The thiosemicarbazone was prepared by the reaction of thiosemicarbazide with aldehyde derivative from L-ascorbic acid in absolute ethanol using glacial acetic acid as a catalyst. 1, 3-thiazolidin-4-ones were synthesized from the condensation of thiosemicarbazones with chloroacetic acid in presence of anhydrous sodium acetate. A 1, 3- thiazolidine-4-one was reaction with several 4-substitutedaldehydes to produce new derivatives with a double bond at the position-5 of the 4-thiazolidinone ring. While the tetrazole compounds were synthesized by 1, 3-cycloaddition reaction of sodium azide and hydrazone compounds in

In this study, new oxazolidinone and thiazolidinone derivatives were synthesized through a three-step process. In the first step, o-aminothiophenol was reacted with p-aminobenzoic acid in hydrochloric acid to produce an amine containing a thiazole ring, achieving a product yield of 80%. The second step involves synthesizing Schiff bases (E1-E4) by reacting 4-(benzo[d]thiazol-2-yl)aniline with various aromatic aldehydes in the presence of glacial acetic acid. This reaction yields products of 76% to 90%. In the third step, the Schiff derivatives (E1-E4) are reacted with glycolic acid and thioglycolic acid to obtain the desired products. Oxazolidinone derivatives (N1-T1) were produced with rates ranging from 66% to 74%, while thiazolidin

The work in this paper involves the planning, design and implementation of a mobile learning system called Nahrain Mobile Learning System (NMLS). This system provides complete teaching resources, which can be accessed by the students, instructors and administrators through the mobile phones. It presents a viable alternative to Electronic learning. It focuses on the mobility and flexibility of the learning practice, and emphasizes the interaction between the learner and learning content. System users are categorized into three categories: administrators, instructors and students. Different learning activities can be carried out throughout the system, offering necessary communication tools to allow the users to communicate with each other

The Braille Recognition System is the process of capturing a Braille document image and turning its content into its equivalent natural language characters. The Braille Recognition System's cell transcription and Braille cell recognition are the two basic phases that follow one another. The Braille Recognition System is a technique for locating and recognizing a Braille document stored as an image, such as a jpeg, jpg, tiff, or gif image, and converting the text into a machine-readable format, such as a text file. BCR translates an image's pixel representation into its character representation. As workers at visually impaired schools and institutes, we profit from Braille recognition in a variety of ways. The Braille Recognition S

Compressing an image and reconstructing it without degrading its original quality is one of the challenges that still exist now a day. A coding system that considers both quality and compression rate is implemented in this work. The implemented system applies a high synthetic entropy coding schema to store the compressed image at the smallest size as possible without affecting its original quality. This coding schema is applied with two transform-based techniques, one with Discrete Cosine Transform and the other with Discrete Wavelet Transform. The implemented system was tested with different standard color images and the obtained results with different evaluation metrics have been shown. A comparison was made with some previous rel

Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o