Information and Computer Science‎

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    (2021) Saeed, Ezz AL-Dean; Hawash, Ziad
    "E-book” is a web-based social media Application, specified for reading and communication activities. The system provides services for anyone in the world either a reader, Author or students. The program provides many services for readers who want to read and discuss what they have read with other people, as well as Authors who want to spread their ideas and talent to the world, as well as Students that need books with acceptable price. The program is mint to be a social media for books, helping our customers to find any book they want and spread their opinion about it or even Publish their own in a fast, easy and the best way possible, and even helping them create new friends and chat with them.
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    Enterprise Resource Planning for Gatouh Lebanon Using Odoo
    (2022) Moghrabi, Rana; Faqeeh, Rafah; Odeh, Alaa; Zatar, Duha
    This project is made within partnership with Gatouh Lebanon company which is one of the largest sweets companies in Nablus, by developing an Enterprise resource planning system (ERP) using odoo application platform. It is a type of software that is used to manage day-to-day business activities in the fields of accounting, sales, points of sale, website, inventory, HR and so on, integrating all these applications together to enable the data flow between them to eliminate data duplication and provide data integrity with a single source of truth. Linking all the points of sale of the company together, providing uniformity of prices and controlling of all transactions with multi level of security for all company transactions. Developing a website with simple design that supports easy and fast navigation and levels of customizability and variants of products Which provides the buyer with a comfortable buying environment that meets his needs and tastes.This project aims to increase the company productivity, efficiency, security, quality and the performance of Gatouh Lebanon
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    Recipes Recommender System
    (2022) Nana, Mais; Musleh, Amal; zraiq, Hala
    Recommendation systems are tools for interacting with large and complex information spaces, they provide a personalized view of these spaces, giving priority to the elements that are likely to be of interest to the user. Most of the big players in the industry like Google, Amazon, EBay, etc. use some sort of recommendation system in the background to recommend personalized products, ads, and videos. Recommendation systems play an important role in helping people find recipes that interest them and match their eating habits, and recommendation systems make use of user profiles, user browsing history, search history, and filtering technologies to gather information and help users find the right information from a large volume of data. The system is a mobile application that works on Android and iOS built using the filter and is used by all ages easily. To build this application, the content-based systems algorithm was used. Goals and Objectives ● Find recipes similar to the user's taste. ● Facilitate the process of preparing and finding meals for users ● Give a satisfactory outcome from the research process
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    Automating Arabic Tags Creation for Annotating Web Contents
    (2022) Alhasan, Jana; Sulaiman, Shahd; Barham, Batool
    Web Annotation becomes an important collaboration technique for users of the web. In order to increase universal collaboration, it is vital for annotators to contact the most related people that share the same interests. Although annotations themselves can be used to exchange ideas and experts, the improper writing of their attached notes could decrease the intended collaboration due to the lack of expressing ideas clearly. Adorning annotations with proper tags makes it easier for annotators to express their feelings, emotions, and interests through their submitted annotations. The ability to use the tags in searching for annotations leads to reaching the most related tags to one's interests and this indeed increases changing ideas between annotators and hence their collaboration. However, expressing the ideas in annotations with proper tags is not an easy task for most annotators. On the opposite side, attaching improper tags loses the soul and the intention of creating annotations which decreases the amount of collaboration. This work is related to automating the process of tags' suggestion by studying the texts selected by annotators over the web. Suggesting proper tags takes into account the part of speech of the annotated texts. The experimental results conducted in the work are related to finding the most suitable threshold for the percentage number of tag suggestions.
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    Traffic-Sign Recognition Using Mask R-CNN
    (2022) Bdair, Lina
    Due to the rapid developments occurring in the world, especially in the field of social media, we started to witness great impacts upon human’s cognitive systems. For example, concepts like short-term memories, distractions and forgetfulness became very prevalent. This study stemmed from these changes. We have developed a traffic-sign detection software model - usable in vehicles’ systems. Its main objective to help drivers remember traffic laws and aid them to focus while driving. The software is developed using Keras, which is a high-level deep learning API, and TensorFlow, an end-to-end open-source platform for machine learning. We used deep neural network Mask R-CNN as a model, which was trained and evaluated on a Small Traffic sign Dataset containing traffic sign images of three categories which this small data is trained on large dataset called COCO, with 5 epochs each epoch takes about 5 hours in training step. At the end of 5 epochs the proposed model training had a mean average precision (mAP) of 93% and the system was able to recognize input images based on the train model and the output was protected object in each image, we also used libraries of OpenCV for real time detection. Proving the positive outcomes of this model, we are exploring the potential of using it to improve upon driving schools’ systems, and car manufacturing systems. Moreover, we aim to explore a potential linkage between the vehicles that have the model installed in them and some governmental systems. This linkage works to alert officials regarding any violation of traffic laws, and will allow for officials to keep an online database of the vehicles and their behaviors on the roads.