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Diabetes genetic finder & predictor = أداة البحث والتنبؤ الجيني لمرض السكري
The diabetes genetic finder & predictor app is a comprehensive, user-friendly solution that revolutionizes diabetes care. This powerful app integrates a wide array of features designed to empower diabetes patients and enhance their overall well-being. A standout feature of the app is its ability to predict the risk of hereditary diabetes diseases, offering users early detection and intervention opportunities. It also predicts general diabetes risk, diabetic foot complications, and retinopathy. Users can monitor their blood sugar levels, heart rate, and oxygenation either manually or through smart watch integration. Additionally, users can enter their diabetes type and HbA1c levels.The app's medication management feature simplifies the complex task of tracking and organizing medications, providing timely reminders to ensure adherence to treatment plans. Users can scan QR codes on products to check their sugar content and suitability, schedule their medications, generate reports for specific periods, and access a comprehensive list of frequently asked questions about diabetes..
Developing secure auto-scaling military postponement e-service in Syria
This study is about developing a secure, autoscaling military postponement e-service in Syria, that allows Syrian citizens to conveniently access services provided by the Syrian Recruitment Department conveniently through their smartphones. Currently, many Syrian citizens need to use the services offered by the Recruitment Department, resulting in overcrowding in a single location for similar purposes. This situation places a significant burden on both citizens and the government. The mobile application will facilitate various services such as enlistment and postponing military service by employing a well-designed software architecture that ensures scalability and efficient distribution of these services.
Developing metaverse for AIU
Metaverse is the virtual world in which humans can see each other in the form of 3D and communicate with each other in a virtual place that looks exactly like the real world, but the developers of metaverse so far used these virtual worlds for profit purposes only, this is what prompted us to build a virtual world that basicly contain the university, which can help students communicate with each other, see teachers and obtain the information they need from university employees without having to travel long distances, this project provides a distance education service without dispensing the idea of interacting with teachers directly and seeing others. Our virtual world has the ability to connect with any virtual world because of it’s base structure, It’s scalable as much as we need because it’s connected to the blockchain.
Developing bus management system for AIU
To solve the problem of congestion in bus stops for students, members of the administrative and educational people at the Arab International University, an application was designed that allows the user to reserve a seat on the bus. The application provides prior reservation and enters the study time for the user, the application reminds him for the time of his going to the university. The basic functions of the application are designed according to the general analysis, The development of the application used Laravel, flutter frameworks, AI and MySQL database processing technology. The application has accomplished such functions as notification for location. The test of the application is running in good conditions. The use of the application will solve the problem of bus crowding. The efficiency of the platform makes it a very good candidate to be implemented for any person in Arab International University.
Developing a distributed medical system
Our project is a distributed medical system that is used by patients and multiple medical sectors such as doctors, pharmacists, analysis labs, hospitals, and medical insurance companies. The aim of the project is to add and store all the patient’s medical data in our system, such as previous treatments and past medical records from previous doctors, previous prescriptions and older lab test’s results, in addition, the insurance companies will have the ability to check on the medical treatment of its customers to do the necessary procedures needed for the them to perform their work. All of our actors are working in a secure and synchronized system in order to provide the best medical results possible, each actor has its own transactions to do in our system and can only manage and access the data allowed for him to perform his required job.
Designing a programming education system for children to program and simulate robots
JuniorCoders is an innovative educational platform designed to introduce programming and robotics concepts to kids and beginners. It provides an easy-to-use visual programming interface that allows users to create Arduino programs by dragging and dropping blocks of code. The system aims to make programming accessible and shareable, allowing them to create complex programs without having to learn a traditional programming language. Enables users to program and simulate robots using Arduino boards.
Designing & Implementing an IDS in SDN
Solving the problem of the various type of unknown attacks that are hitting not only companies but also high level business individuals, of course we know that there is no way to stop the attacks permanently but this project is attempting to reduce these attacks to the possible minimum where it can detect the attack and declare its type so that the hostile can at least know what is the type of attacks on him and what to do in response and build a higher security. This system is implemented using the SDN environment and IDS technology for monitoring the traffic on the network and for detecting the attack and its type. Also the SDN technology has a built-in OpenFlow protocol. To work in an OF environment, any device that wants to communicate to an SDN controller must support the OpenFlow protocol.
Design and implementation of an array of patch antenna
Wireless technology is one of the main areas of research in global communication systems today and the study of communication systems is incomplete without an understanding of the process and manufacture of antennas. This was the main reason for choosing this project to focus on this area. This paper presents the design and implementation of an antenna array consisting of 4 patch antenna elements that work on 2.4GHz frequency,the substrate FR4, It was analyzed using HFSS (High Frequency Simulator Structure). In order to achieve a gain of 7 db, and a reflection coefficient of s11 of -10db Then the board was printed And he made measurements in the laboratory on the spectrum analyzer and the kit for the antennas As a result of the measurements, we obtained the antenna gain, the antenna radiation pattern, and the s11
Deepfake detection = اكتشاف التزييف العميق
In the rapidly evolving era of artificial intelligence, addressing the escalating threats of deepfake technology becomes a necessity because of the increasing sophistication of AI algorithms in generating deceptive content, and since it threatens the integrity of information across diverse data. The main objective is to build a sophisticated AI-driven system to detect different types of deepfake in text, audio, and images. In English text deepfake detection, multiple pre-trained tokenizers have been used, but XLNET and BERT stand out with identifying objects outside the dataset with an accuracy of 0.9809 and both have been generalized & trained using LSTM. In Arabic text deepfake detection, Arabert has been trained using LSTM which led with an accuracy of 99.53% by generalizing the model. Both English and Arabic datasets have been generated to enhance the accuracy and effectiveness of the models. Audio deepfake detection has been generalized too, using Random Forest with an accuracy of 98.259%.
Deepfake detection
Recently, various techniques of manipulating the video content have become available to everyone – online, one can find free applications e.g., for face swapping in videos. Such universal accessibility carries a notable risk of flooding online content with false information, affecting not only the greats of this world, but also the whole societies, also the rapid progress in synthetic image generation and manipulation has now come to a point where it raises significant concerns for the implications towards society. It is therefore necessary to develop a verification tool that will help assess the authenticity of the videos posted on the internet. This project describes the approach of using artificial intelligence solutions to detect doctored videos.
Deepfake detection
The rise of large language models (LLMs) and the increasing sophistication of deepfake images have made detecting synthetic content a pressing challenge. Several approaches have been proposed to tackle this problem, including statistical analysis, and machine learning algorithms. In this project, A novel zero-shot approach is proposed that utilizes the power of LLMs to detect fake text. The pre-trained LLM is fine-tuned to enhance its ability to differentiate real and fake text. The approach uses the LLM to detect text by analyzing the log probabilities of the text. For detecting fake images, computer vision algorithms and neural networks are used to analyze facial features. The facial region is cropped and preprocessed and the neural network identifies patterns indicative of synthetic content.
Deepfake
The technology used to create such digital content has quickly become accessible to the masses, such as “DEEPFAKE.” Deep fakes refer to manipulated videos, or other digital representations produced by sophisticated artificial intelligence, that yields to synthesize a sequence of face images and voices of characters corresponding to their identities, such as voice tone, facial expression, with a good lip synchronization. Therefore, this study is about developing real-time video generation software, which generates a target video from a single input image. Several methods and algorithms have been applied to detect, analyze personalize facial expression, voice and natural head poses to present a life-like image instead of a low quality one.
Deep learning methods for converting speech to text = تقنيات التعلم العميق في تحويل الصوت إلى نص
Aims to design and develop a system capable of extracting audio content from films and audio recordings and converting it into text using deep learning techniques. This is done by analyzing audio patterns, extracting sounds and words from the video, and then converting them into written text. Deep learning, a branch of artificial intelligence, is used to accomplish this task. The study also includes comparing different deep learning techniques to determine their effectiveness in this context.
Deep learning approach for text summarization
Machine learning and deep learning, as we know, have started ruling over almost every field in the computing industry and so, has revolutionized the process of text summarization too. Automatic text summarization is an advancing realm of the natural language processing research in which concise textual summaries are generated from lengthy input documents. Extensive research has been carried out on how automatic summarization can be prosecuted through various extractive and abstractive techniques. In this paper, we address all the approaches to text summarization and present the modus operandi of an Architecture called Encoder Decoder, under the machine learning approach.
Deep fake detection
Deep learning has been successfully applied to solve various complex problems ranging from big data analytics to computer vision and human-level control. Deep learning advances however have also been employed to create software that can cause threats to privacy, democracy and national security. One of those deep learning-powered applications recently emerged is “deepfake”. Deepfake algorithms can create fake images and videos that humans cannot distinguish them from authentic ones. The proposal of technologies that can automatically detect and assess the integrity of digital visual media is therefore indispensable.
Dataset Studio
Data is the new oil, which means that AI engineers can face difficulties in locating suitable datasets. Dataset Studio is a comprehensive platform designed to support AI engineers in the creation and optimization of datasets. This project offers a diverse range of services that encompass data collection, data augmentation, and data classification. As a result, this software empowers engineers by automatically generating structured data through the utilization of advanced tools and AI techniques. By automating the laborious tasks of manual data collection and extraction, Dataset Studio effectively streamlines the workflow for AI engineers, enabling them to save valuable time and focus on the more intricate aspects of dataset development and refinement.
Crowd investment platform
Investment platforms are challenging the grip of massive business on the venture sector and are providing new means of power to the crowds. It is of no surprise that new and interesting equity sharing platforms are now disrupting the convention practices of the market. There are a number of concerns that the user faces, including legal, commercial and security concerns, as well as concerns about trusting these platforms in investment operations, especially in the financial transfer process between the user and companies. We built a site that reduces the presence of these concerns and protects the user from fraud, as we store money transfers and investment operations between users and companies or users and other users within a smart contract that brings them together and the amount that will be invested in the blockchain that encodes this contract and makes it public only to its owners.
Crime detection camera
This paper presents a comprehensive crime detection system that uses a combination of hardware and software to monitor homes and communities in real time. The system consists of a Raspberry Pi 4B, a Raspberry Pi Camera V2, a flame sensor, an MQ-6 gas sensor, and a microphone, which are all connected to a database management system powered by MySQL. The data collected from these devices is analyzed by machine learning algorithms to detect crimes, such as theft or robbery, as well as fires and gas leaks. The system also includes a mobile app, ‘Safe Home’ which provides live video monitoring and real-time notifications to users, and an employee dashboard to monitor all statistics and manage all implemented systems.
Covid-19 tracking application with user helping features
The era of mobile technology opens the windows to the mobile apps. The websites are vanishing and the mobile phones are emerging. In light of the development of applications on mobile and their widespread spread, especially Service (SOA) ones. It’s the time to change from conventional websites to apps, which has become the part of our daily routine. We are introducing “Covid 19 Tracker” “Covid 19 Tracker” is an interactive App used to assist the Ministry of Health to provide protection and health care for citizens and residents referred to domestic isolation or quarantine; to ensure their safety and enhance their recovery procedures.
Cooperative tool
Online collaboration is fast becoming a permanent feature of the modern workplace. Companies and organizations are attracted by the cost-effective technology allowing employees to work together anywhere, at any time using any internet-enabled device. Online collaboration gives team members the tools they need to work with others from any location, including from home and while travelling. This drastically reduces “downtime” and allows people to be productive when it best suits them therefore we propose a website that provides content (videoconference, real-time Chat, whiteboard).
