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Browsing by Author "Department of Computer Science"

Browsing by Author "Department of Computer Science"

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  • A 3D playground for t-SNE with explainable classification 
    Anbtawi, Wedad (2019)
    In this thesis, we build a web-based and interactive dimensionality reduction and visualization tool based on t-SNE. Our tool strives to run in the web browser at the client-side in real-time. In addition, we propose a new ...
  • A hybrid game theory and reinforcement learning approach for cyber-physical systems security 
    Khoury, Joseph Chawki (2019)
    Cyber-Physical Systems (CPS) like smart cities and industries 4.0 including nuclear power plants, oil and gas pipelines, electric power grids, railways, and other Critical Infrastructures (CI) are monitored and controlled ...
  • A method for verifying choreographies and their implementations 
    Khalil, Al-Abbass Adham (2019)
    A global choreography defines a communication pattern over a set of ports. The ports are partitioned into subsets, each subset being the ports that belong to a given process. From a choreography and an interaction architecture, ...
  • Accelerating Genome Analysis using Processing-in-Memory 
    Diab, Safaa (5/16/2022)
    Data movement between memory and the CPU is a bottleneck in data-intensive applications. The cause of this problem is the need for the computing unit to access data frequently in memory through a limited-bandwidth and ...
  • Accelerating Knowledge Graph Relationship Queries on GPUs 
    Mahmoud, Jamil (2024-05-14)
    Large graphs and networks, referred to as semantic graphs, have become essential for discovering relationships between entities, objects, or concepts in modern-day applications across various fields such as medicine, ...
  • AI System In The Real World: Capture Children Food Exposure Using Wearable Cameras 
    Zoughby, Yorgo (9/23/2020)
    Children’s dietary habits are influenced by complex factors. Identifying community-level influencers and measuring their effect is traditionally based on self-reported data and prone to measurement error. In addition, ...
  • Algorithms for Atom Reconfiguration in Quantum Simulators 
    El Sabeh, Remy (8/22/2022)
    The reconfiguration framework is an emerging framework that concerns finding a step-by-step transformation between two feasible solutions of a problem such that the transformation steps preserve a feasible solution. The ...
  • AraDialAug: A Meta-Learning and Data Augmentation Approach for Arabic Dialogue Generation 
    El Halabi, Assaad (2024-02-07)
    Arabic dialogue generation presents unique challenges due to the language's rich morphology and the scarcity of data resources. Recent advances have employed metalearning to facilitate fast adaptation of language models ...
  • Automated stock price prediction using machine learning 
    Moukalled, Mariam Ibrahim (2019)
    The financial market is a dynamic and composite system where people can buy and sell currencies, stocks, equities and derivatives over virtual platforms supported by brokers. The stock market – also known as the equity ...
  • Behavioural modeling and abstraction of concurrent programs. 
    Soueidi, Chukri Albert (2019)
    We address the problem of modeling, analyzing, and repairing finite-state and infinite-state concurrent programs. We define a textual notation for concurrent programs and implement it in the Eshmun tool. For finite-state ...
  • Data science approach for forecasting the demand on Lebanese Red Cross and civil defense in case of accidents. 
    Farhat, Elham Mohamad (2019)
    Being able to predict demand by the victims on Red Cross and Civil Defense services plays a vital role in Lebanon which has been reeling under the effect of regional struggles. This thesis attempts to explore data from ...
  • Detection of fake news in the Syrian war. 
    Al Feel, Roaa (2019)
    After almost eight years of conflict, the humanitarian situation in Syria continues to deteriorate year after year. With multiple opposing parties involved in the armed conflict, much of the news reported about the Syrian ...
  • Direct Speech to Speech Turkish to Arabic 
    Baali, Massa (4/23/2021)
    Dubbed series are gaining a lot of popularity in recent years with strong sup-port from major media services providers. Such popularity is fueled by studiesthat showed that dubbed versions of TV shows are more ...
  • Discrimination-aware task assignment in crowdsourcing. 
    El Atie, Christine Elie (2018)
    Algorithmic bias has been identified as a key challenge in many AI applications. One major source of bias is the data used to build these applications. For instance, many AI applications rely on crowdsourcing to generate ...
  • Efficient Suturing in Deformable Models 
    Younes, Georges Emile (9/20/2021)
    Surgical procedures are among the most complex medical interventions routinely performed. The suturing task, ubiquitous to most surgical interventions, has a steep learning curve. With the increased focus on minimally ...
  • Exploiting ransomware paranoia for execution prevention 
    Al Sabeh Ali Mazhar (2019)
    Ransomware attacks cost businesses more than $75 billion-year, and it is predicted to cost $6 trillion-year by 2021. These numbers demonstrate the havoc produced by ransomware on a large number of sectors and urge security ...
  • Exploring Processing-In-Memory Acceleration of Breath-First Search 
    Abdel Sater, Tarek (2/3/2021)
    In the traditional computer architecture, some applications suffer from the "memory wall" problem - workloads that exhibit dominant data movement costs and low data reuse would fully saturate the memory throughput of the ...
  • Extracting war incidents from news articles via deep Sequence Tagging 
    Sawaya, Nancy Joseph (2019)
    An important natural language processing (NLP) task is to extract structured information from free text. In this thesis, we focus on the problem of extracting war incidents from news articles. A war incident is a tuple ...
  • FACTFORMER: A TRANSFORMER BASED FACT CHECKER 
    Adesokan, Ademola (2023-09-07)
    Misinformation can undermine public trust and lead to misguided actions based on unreliable sources and fact-checking efforts. Traditional manual fact-checking systems suffer from several challenges, including issues ...
  • Fairness in Online Jobs 
    Gizzawi, Ahmad (5/29/2020)
    Online job marketplaces are becoming very popular. Either jobs or people are ranked by algorithms. For example, Google and Facebook job search return a ranked list of jobs given a search query. TaskRabbit and Fiverr, on ...

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