Causal words and phrases, like "if," "so that," and "because" are used to show a cause-effect relationship between two parts of a sentence. By extracting enough sentences with these words and phrases from online texts, these causal relationships can form the foundation of a knowledge base, which a computer can draw from to determine logical links between real-world entities. For example, the sentence "It was raining, so I brought an umbrella" shows a causal link between a cause - rain - and an effect - bringing an umbrella. With enough similar entries, a knowledge base can demonstrate with high certainty that this is a meaningful cause-effect pair, and a computer can use this type of information for a variety of natural language processing and artificial intelligence uses. In this project, we used causal sentences from the Gutenberg Project, an online repository of freely downloadable texts, along with parsing and stemming techniques, to create a knowledge base that computers can access to determine expected causes and effects for various situations.

Many attempts were made in the past to monitor a driver’s visual and cognitive distractions. Yet, most of the techniques did not become a practical application due to their contact-based nature of monitoring. Among others, biomarkers and physiology sensors were proposed for the monitoring . The disadvantage of these technologies is that they require close contact with the driver, which not only offers an uncomfortable driving environment but also introduces significant amount of motion error in the measurements. In our previous study, we demonstrated the correlation of increased blood perfusion in the supraorbital muscles and machine operator’s mental overloading [4]. The proposed work aims at extending this research by developing a real-time feedback system to alert the operator about his/her psychological status based on the facial thermal signature.
A driving simulator will be used as a test bed in the indoor laboratory setup. Primary efforts will be focused on the development of software modules and hardware components. The software modules will analyze the facial thermal signature in real-time and send digital triggers to the hardware components. Depending on the trigger types, the hardware components will alter the vehicle’s ambience in order to achieve a desired psychological state of the driver. Take for example drowsiness while driving that is a leading cause of major accidents. The proposed feedback system will detect the driver’s psychological state from his/her facial physiology and alert the driver by providing audio cues or by changing music in the vehicle.
Undergraduate Involvement: The student will assist in designing the experiment and implementing the software modules and hardware components. In particular, they will be involved in analysis of the thermal signals via various pattern classification algorithms. The students will also be interacting with doctoral candidates at the University of Houston-Central campus which will be pivotal in their pursuit for the higher education.

The industrialization in the past century has significantly changed the way we function on daily basis. It has provided means through which ample of physical comfort is affordable to anyone at anytime. Yet, our daily routine is increasingly becoming stressful. Indeed, stress seems to be a chronic disease of the modern human which can be directly linked to anxiety, frustration, depression and fatigue. These psychological variables are root-causes for suboptimal human performance. Millions of dollars have been spent by pharmaceutical firms and the government agencies on the research and development of stress relieving medications with a little success. Meditation, yet another venue, has been explored by neuroscientists in the recent years. However, the obtrusive measurement methods such as EEG and functional Magnetic Resonance Imaging (fMRI), used in their studies have made the efforts limited to artificial experimental scenarios. Hence, the role of meditation has not been understood completely for realistic field studies. A case in point is students’ stress measurement while attending course exams. In this research we propose to consider facial physiology in understanding effectiveness of meditation in human performance enhancement. The facial physiology can be extracted via a mid-wave (3-5µ) infrared camera in a contact-free manner; making the technology suitable for continuous monitoring. Our previous work demonstrated significance of the facial physiology in mental stress monitoring . The proposed research aims at evaluating stress relieving options in particular, meditation via the thermal imagery.
A series of psychophysiological experiments will be conducted in the laboratory setup to introduce stress in participants. The participants will be randomly assigned to controlled and experimental groups. The experimental group will go through a few days of meditation sessions before they will be introduced to stressful situations. The control groups will not be exposed to meditation. Participants’ facial physiology will be captured during the experimental periods. In addition to the existing algorithms, new image and signal processing algorithms will be developed for extracting the facial physiological responses. Finally, machine learning and statistical-based algorithms will be employed to uncover thermal patterns related to stress.
Undergraduate Involvement: This interdisciplinary research will offer a unique opportunity to the student in interacting with experts from different academic areas including behavior science, computer science and applied mathematics. The students will be involved in various phases of the research ranging from experimental design to data mining. The students will also be interacting with doctoral candidates at the University of Houston-Central campus which will be pivotal in their pursuit for the higher education.

The objective of this project is to create a program for brain states analysis, in particular, the comparison of meditative states to other brain states. Applications on iPad and Android and a website for information sharing will be included in the project. Mental discipline and meditative practice can change the workings of the brain and allow people to achieve different levels of awareness. The brain is an electrochemical organ using electromagnetic energy to function. Electrical activity emanating from the brain is displayed in the form of brainwaves. The objective of this project is to create a program that is able to analyze these brainwaves when a person is in various states. In particular, we are interested in comparing the brain state of persons in meditative state to brain states of a person during exercise, sleep, study, etc. The program can display the brainwaves in a graph and do a peer-to-peer comparison between different states. The development of such a program has been started in Spring 2011 with a group of students at the University of Houston-Downtown supported by the CAHSI program. Currently, we are collaborating with researchers in the University of Canberra, Australia, in brain waves data collection and analysis.

We has launched a collaborative project with faculty at the Human Interface Branch of NASA and the School of human Sciences and Humanities, University of Houston Clear Lake. The “Usability Design of Brain Wave Control Interface” project will use brain waves to control operations on a device interface. The project will involve students in research activities. The project will use Emotiv SDK to design an interface software that controls operations using keyboard and mouse using brain signals from Emotiv headsets.