Browsing by Subject "Machine learning."

Now showing items 1-20 of 42

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 study on liquid state machine for pattern recognition -

Al Zoubi, Obada Mohammad Yasser, (2016)

Spiking Neural Networks (SNNs) are a new promising approach for machine learning because they increase the ratio of biological realism, and thus the ability to capture complex data patterns. SNNs belong to the third ...
Arabic named entity recognition via deep co-learning -

Helwe, Chadi Talal, (2017)

Named entity recognition (NER) is the task of identifying named entities such as locations, persons, and organizations in a given piece of text. NER plays a signi cant role in many applications including information ...
Automated detection and measurement of corneal haze using optical coherence tomography images -

Chokr, Manal Mouin, (2017)

The cornea typically constitutes two-thirds of the eye’s optical power; a healthy one has a dome shape. However, a vision disorder so-called Keratoconus, which is especially prevalent in the Middle East and Gulf area, may ...
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 ...
A context-aware design for emotion recognition in natural settings -

Farra, Noura Abdul Aziz (2013)

A major issue in achieving automated emotion recognition systems that perform well outside the lab is the use of real-world data that reflects the occurrence of emotions in everyday life. Furthermore, situational context ...
Context-aware dynamic designs for energy efficient mobile sensing -

Taleb, Sirine Hassan (2017)

Technological advances in the past decade have driven a significant evolution of various technologies towards Internet of Things (IoT) in domains such as sensing, communications, and computing. In particular, today's smart ...
Crowd attributes estimation using support vector machine and deep learning with multi-source sensor fusion.

Hassoun, Karim Mohamad Ali (2019)

Unfortunate tragedies have previously been the result of high-density human crowds or pedestrian flow. In addition to, crowd behavior as a reaction to an incident aggravates the complexity and disruption of human flow, ...
Data mining methodologies for yield prediction in semiconductor manufacturing.

Baly, Ramy Georges. (2012)

Increasing yield is a primary concern to IC manufacturing companies as it dictates the readiness of a new process for high volume manufacturing. In order to expedite the process of discovering yield issues, companies have ...
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 ...
Digital billboards advertisements’ effects on drivers’ performance and attention.

Abou Marak-Brome, Reem Akram (2019)

There is increasing interest in attempting to reduce the problem of driver distraction with the aim of decreasing the rate of road accidents and improving road traffic safety. Many existing work in the literature focuses ...
Digital technology and emotions :a framework for the dynamic understanding of human-computer interaction -

Constantine, Layale Rafic, (2013)

Humans are nowadays surrounded by digital devices that weaved themselves into the fabric of their everyday life in an intelligent way. This is the result of recent advancements in the “Human Computing” domain that witnessed ...
Emotion recognition from text and physiological data -

Awwad, Ramy Anwar, (2014)

Ability to feel emotions is known to be an intrinsic property of human beings. At every moment of our life, we unconsciously respond emotionally to everything that happens around us. Emotions are normally triggered by a ...
Emotion recognition from textual data -

Shaheen, Shadi Ibrahim, (2013)

In today’s world and with the growth of internet community, textual data has proven to be the main tool of communication in human-machines or human-human interaction, where a large proportion of information is stored in ...
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 ...
Hierarchical temporal memory : an investigative look into a new cortical algorithm -

Mitri, Nicholas Gabi, (2015)

The connectionist approach to artificial intelligence has made many attempts to capture the essence of intelligence by adopting some of the principles underlying the operation of the human brain. Since its emergence in the ...
Holistic approach to energy efficiency in context-aware mobile sensing

Kain, Raslan Hussein (2019)

Mobile devices and sensors have limited battery lifespan thus limiting their feasibility in context recognition applications. As a result, there is a need to provide mechanisms for energy-efficient operation of sensors in ...
Humanitarian visual and semantic computing : crisis-related image tweets classification -

Jomaa, Hadi Samer, (2016)

When the public and first responders are flooding the internet with often annotated images and texts during natural disasters, rescue teams are overwhelmed to prioritize often scarce resources. Given that most of the efforts ...
Hybrid optimization techniques for oil field development -

Hamida, Zachary (2016)

This study aims at introducing a problem-specific modified Genetic Algorithm (GA) approach for optimal well placement in oil fields. The evolution method used in this algorithm includes a novel genetic operator named ...

Now showing items 1-20 of 42

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Browsing by Subject "Machine learning."

Browsing by Subject "Machine learning."

Search AUB ScholarWorks

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Copyright Statement