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Full-Text Articles in Engineering
Avatar Captcha : Telling Computers And Humans Apart Via Face Classification And Mouse Dynamics., Darryl Felix D’Souza
Avatar Captcha : Telling Computers And Humans Apart Via Face Classification And Mouse Dynamics., Darryl Felix D’Souza
Electronic Theses and Dissertations
Bots are malicious, automated computer programs that execute malicious scripts and predefined functions on an affected computer. They pose cybersecurity threats and are one of the most sophisticated and common types of cybercrime tools today. They spread viruses, generate spam, steal personal sensitive information, rig online polls and commit other types of online crime and fraud. They sneak into unprotected systems through the Internet by seeking vulnerable entry points. They access the system’s resources like a human user does. Now the question arises how do we counter this? How do we prevent bots and on the other hand allow human …
Temporal Contextual Descriptors And Applications To Emotion Analysis., Haythem Balti
Temporal Contextual Descriptors And Applications To Emotion Analysis., Haythem Balti
Electronic Theses and Dissertations
The current trends in technology suggest that the next generation of services and devices allows smarter customization and automatic context recognition. Computers learn the behavior of the users and can offer them customized services depending on the context, location, and preferences. One of the most important challenges in human-machine interaction is the proper understanding of human emotions by machines and automated systems. In the recent years, the progress made in machine learning and pattern recognition led to the development of algorithms that are able to learn the detection and identification of human emotions from experience. These algorithms use different modalities …
Complementary Layered Learning, Sean Mondesire
Complementary Layered Learning, Sean Mondesire
Electronic Theses and Dissertations
Layered learning is a machine learning paradigm used to develop autonomous robotic-based agents by decomposing a complex task into simpler subtasks and learns each sequentially. Although the paradigm continues to have success in multiple domains, performance can be unexpectedly unsatisfactory. Using Boolean-logic problems and autonomous agent navigation, we show poor performance is due to the learner forgetting how to perform earlier learned subtasks too quickly (favoring plasticity) or having difficulty learning new things (favoring stability). We demonstrate that this imbalance can hinder learning so that task performance is no better than that of a suboptimal learning technique, monolithic learning, which …
An Unsupervised Consensus Control Chart Pattern Recognition Framework, Siavash Haghtalab
An Unsupervised Consensus Control Chart Pattern Recognition Framework, Siavash Haghtalab
Electronic Theses and Dissertations
Early identification and detection of abnormal time series patterns is vital for a number of manufacturing. Slide shifts and alterations of time series patterns might be indicative of some anomaly in the production process, such as machinery malfunction. Usually due to the continuous flow of data monitoring of manufacturing processes requires automated Control Chart Pattern Recognition(CCPR) algorithms. The majority of CCPR literature consists of supervised classification algorithms. Less studies consider unsupervised versions of the problem. Despite the profound advantage of unsupervised methodology for less manual data labeling their use is limited due to the fact that their performance is not …
Sketchart: A Pen-Based Tool For Chart Generation And Interaction., Andres Vargas Gonzalez
Sketchart: A Pen-Based Tool For Chart Generation And Interaction., Andres Vargas Gonzalez
Electronic Theses and Dissertations
It has been shown that representing data with the right visualization increases the understanding of qualitative and quantitative information encoded in documents. However, current tools for generating such visualizations involve the use of traditional WIMP techniques, which perhaps makes free interaction and direct manipulation of the content harder. In this thesis, we present a pen-based prototype for data visualization using 10 different types of bar based charts. The prototype lets users sketch a chart and interact with the information once the drawing is identified. The prototype's user interface consists of an area to sketch and touch based elements that will …
On Kernel-Base Multi-Task Learning, Cong Li
On Kernel-Base Multi-Task Learning, Cong Li
Electronic Theses and Dissertations
Multi-Task Learning (MTL) has been an active research area in machine learning for two decades. By training multiple relevant tasks simultaneously with information shared across tasks, it is possible to improve the generalization performance of each task, compared to training each individual task independently. During the past decade, most MTL research has been based on the Regularization-Loss framework due to its flexibility in specifying various types of information sharing strategies, the opportunity it offers to yield a kernel-based methods and its capability in promoting sparse feature representations. However, certain limitations exist in both theoretical and practical aspects of Regularization-Loss-based MTL. …
Remote Sensing With Computational Intelligence Modelling For Monitoring The Ecosystem State And Hydraulic Pattern In A Constructed Wetland, Golam Mohiuddin
Remote Sensing With Computational Intelligence Modelling For Monitoring The Ecosystem State And Hydraulic Pattern In A Constructed Wetland, Golam Mohiuddin
Electronic Theses and Dissertations
Monitoring the heterogeneous aquatic environment such as the Stormwater Treatment Areas (STAs) located at the northeast of the Everglades is extremely important in understanding the land processes of the constructed wetland in its capacity to remove nutrient. Direct monitoring and measurements of ecosystem evolution and changing velocities at every single part of the STA are not always feasible. Integrated remote sensing, monitoring, and modeling technique can be a state-of-the-art tool to estimate the spatial and temporal distributions of flow velocity regimes and ecological functioning in such dynamic aquatic environments. In this presentation, comparison between four computational intelligence models including Extreme …
Human-Robot Interaction For Multi-Robot Systems, Bennie Lewis
Human-Robot Interaction For Multi-Robot Systems, Bennie Lewis
Electronic Theses and Dissertations
Designing an effective human-robot interaction paradigm is particularly important for complex tasks such as multi-robot manipulation that require the human and robot to work together in a tightly coupled fashion. Although increasing the number of robots can expand the area that the robots can cover within a bounded period of time, a poor human-robot interface will ultimately compromise the performance of the team of robots. However, introducing a human operator to the team of robots, does not automatically improve performance due to the difficulty of teleoperating mobile robots with manipulators. The human operator’s concentration is divided not only among multiple …