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        A Visualization Training Tool for Optimum Cutting Range During Urethral Dissection in Robot-Assisted Radical Prostatectomy: A deep learning approach 

        Kharbach , Sarah Lotfi (2021 , Master Thesis)
        Surgical training and skills assessment is one of the methodologies used by clinical practitioners to master their skills in a fault-tolerant, safe and risk-free environment. Software training tools is one of them. Narrowing ...
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        Accurate Classification of Partial Discharge Phenomena in Power Transformers in the Presence of Noise 

        Fernandez, Rachael (2017 , Master Thesis)
        The objective of this research is to accurately classify different types of Partial Discharge (PD) phenomenon that occurs in transformers in the presence of noise. A PD is an electrical discharge or spark that bridges a ...
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        ADVANCED MACHINE LEARNING TECHNIQUES FOR ARRHYTHMIA CLASSIFICATION 

        ABOUMADI, ABDULLA MARAWAN (06-2 , Master Thesis)
        With the development of Internet-of-Things (IoT) applications, the concept of smart healthcare applications has gradually emerged to be the main factor in medicine. In fact, this raises the need to have a secure system ...
      • AI FOR MELTDOWN DETECTION IN AUTISM USING WEARABLE SENSORS. 

        ALBAN, AHMAD YOUSEF QADEIB (06-2 , Master Thesis)
        Autism spectrum disorder is a neurodevelopmental disorder that is associated with many symptoms, such as impairments in social skills, communication, and abnormal behaviors. Children on the spectrum exhibit atypical, ...
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        An efficient PPG Compression Technique for Wearable Health Devices 

        ABDULKADER, SEEBA SULEKHA (2021 , Master Thesis)
        Photoplethysmography is a simple, widely used, low-cost technique to acquire important diagnostic information for assessing significant physiological parameters of the human body based on the amount of light reflected from ...
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        Application of Machine Learning Techniques for The Prediction of Decompressive Hemicraniectomy Prognosis in Acute Ischemic Stroke 

        Ali, Rahma Saleh (2019 , Master Thesis)
        Stroke is one of the leading causes of death in the world with the number of people suffering from it increasing every year. Ischemic strokes, one of the two main types of stroke, occur when blood clots block brain ...
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        ARABIC QUESTION ANSWERING ON THE HOLY QUR'AN 

        MALHAS, RANA R. (2023 , Dissertation)
        In this dissertation,we address the need for an intelligent machine reading at scale (MRS) Question Answering (QA) system on the Holy Qur'an, given the permanent interest of inquisitors and knowledge seekers in this sacred ...
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        Automated Segmentation of Cerebral Aneurysm Using a Novel Statistical Multiresolution Approach 

        Regaya, Yousra Mounir (2018 , Master Thesis)
        Cerebral Aneurysm (CA) is a vascular disease that threatens the lives of many adults. It a ects almost 1:5 - 5% of the general population. Sub- Arachnoid Hemorrhage (SAH), resulted by a ruptured CA, has high rates ...
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        Bagged Randomized Conceptual Machine Learning Method 

        Ali, Mohamed Abdalhakem Taha (2018 , Master Thesis)
        Formal concept analysis (FCA) is a scientific approach aiming to investigate, analyze and represent the conceptual knowledge deduced from the data in conceptual structures (lattice). Recently many researchers are counting ...
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        Blockchain Technology and Reputation System for Smart Grids to Address Cyber-Attacks 

        ALKAEED, MAHDI KHALAF (2021 , Master Thesis)
        The smart grid model has made a big technological leap over the traditional electrical grid. This model contributes to protecting the physical environment as it provides many benefits such as improved quality of services, ...
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        Building a Test Collection for Significant-Event Detection in Arabic Tweets 

        Almerekhi, Hind Ali (2016 , Master Thesis)
        With the increasing popularity of microblogging services like Twitter, researchers discov- ered a rich medium for tackling real-life problems like event detection. However, event detection in Twitter is often obstructed ...
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        Client-based confidential data sharing using untrusted clouds 

        Kamal, Naheel Faisal (2021 , Master Thesis)
        Cloud storage has been used widely by organizations and individuals. However, using known cloud providers is not a solution that can fit the needs of many entities that need to store private and sensitive data. This is due ...
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        A COMPREHENSIVE FRAMEWORK FOR DESIGN AND EVALUATION OF M-LEARNING APPLICATIONS 

        Hassen, Abdulahi Mohamed (2016 , Master Thesis)
        Human-computer interaction (HCI) communities and Mobile Learning Communities (MLCs) are well aware of the challenges that mobile devices impose when it comes to conducting proper usability and user experience evaluations ...
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        Conceptual Based Hidden Data Analytics and Reduction Method for System Interface Enhancement Through Handheld devices 

        Babi, Syrinne Adnan (2016 , Master Thesis)
        With the increasing demand placed on online systems by users, many organizations and companies are seeking to enhance their online interfaces to facilitate the search process on their hidden databases. Usually, users issue ...
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        Conceptual data sampling for image segmentation- an application for breast cancer images 

        Awan, Zainab Khalid (2017 , Master Thesis)
        At the present time data analytics have become a buzzword for the in- formation technology sector. In an attempt to analyze data; one may follow various paths. Be it deploying sophisticated technologies to process big ...
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        A conceptual heuristic for solving the maximum clique problem 

        Safi, Zeineb (2017 , Master Thesis)
        The maximum clique problem (MCP) is the problem of finding the clique with maximum cardinality in a graph. It has been intensively studied for years by computer scientists and mathematicians. It has many practical applications ...
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        DDI: Drones Detection and Identification using Deep Learning Techniques 

        AL-EMADI, SARA ABDULRAZAQ (2021 , Master Thesis)
        Drones are becoming increasingly popular not only for recreational purposes but in day-to-day applications in engineering, medicine, logistics, security and others. Besides their useful applications, an alarming concern ...
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        DDoS: DeepDefence and Machine Learning for identifying attacks 

        Bhati, Akhilesh (2020 , Master Thesis)
        Distributed Denial of Service (DDoS) attacks are very common type of computer attack in the world of internet today. Automatically detecting such type of DDoS attack packets & dropping them before passing through the ...
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        Deanonymizing tor hidden service users through bitcoin transactions analysis 

        Al Jawaheri, Husam Basil (2017 , Master Thesis)
        With the rapid increase of threats on the Internet, people are continuously seeking privacy and anonymity. Services such as Bitcoin and Tor were introduced to provide anonymity for online transactions and Web browsing. Due ...
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        Deep Learning Based Approach For Prediction Of Cloud Resource Needs 

        Al- Qutan, Anwar (2018 , Professional Masters Project)
        Cloud computing allows scaling applications to serve dynamic and time-varying workloads and to avoid application performance degradation, while keeping low provisioning costs. But, resource demand of applications need to ...

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