Research Interests: Geographical Information System (GIS), Database, Wireless/Sensor Network and Computer Vision. Publications:
Previous Research Projects: Alexandria Archeology GIS Mapping: Digitally preserve important historic maps for the Alexandria Archaeology Museum beginning with the area outside of Old Town Alexandria where archaeological resources are most threatened by expanding development. SenseEye: SenseEye is a multi-tier network of heterogeneous wireless nodes and cameras, which was employed to show a multi-tier sensor network can reconcile the traditionally conflicting systems goals of latency and energy efficiency. A surveillance application was employed using SensEye comprising three tasks: object detection, recognition and tracking. Novel mechanisms were designed for low-power low-latency detection, low-latency wakeups, efficient recognition and tracking. An experimental evaluation shows that, when compared to a single-tier prototype, our multi-tier SensEye can achieve an order of magnitude reduction in energy usage while providing comparable surveillance accuracy. Acromegaly: Acromegaly is a hormonal disorder. Acromegaly means extremities and enlargements in Greek. Its typical symtoms are disfiguring growth of the bones of the skull and swelling of the face, hands, and feet. A facial features enlargement is the second most prevalent symptom with a prevalence over 95%. It includes protruded jaws, eye brows, and cheekbones, and enlarged lips and nose. The goal in this project is to detect acromegaly automatically from generic frontal facial photographs so that it can be diagnosed and recognized in a timely manner. In collaboration with Volker Blanz, Erik G. Learned-Miller and others, a classification system which prescreens patients for acromegaly using the Morphable model and Support Vector Machines (SVMs) was developed. Micro Traffic Simulation of Truck Activities: Transportation professionals have long realized the importance of incorporating truck characteristics into transportation design and traffic operations. Large trucks differ dramatically from passenger cars in many physical and operational characteristics. They are longer, wider, heavier, less maneuverable, and have slower acceleration and deceleration rates and higher emissions outputs than passenger cars. Thus they can cause traffic disturbances leading to the generation of shock waves, traffic delays, adverse variations in vehicle speeds, etc. In addition, their larger size and inertia pose safety concerns in case of crashes and may influence the response of passenger vehicles drivers. On the other hand, their movements also can be impacted by road conditions such as intersection geometric characteristics. These impacts can be more serious and complex at tight intersections on surface street networks. This project prevides a framework to simulate the impacts of truck activities at tight intersections on surface streets, proposes simulation methods to quantify those impacts, and presents the results from the study on those impacts on the south Boston local street network near the Boston Container Terminal using a modified surface street network simulation model in Traffic Software Integrated System (TSIS) 5.1. Presentations:
Vulnerability of Wireless Routing Protocols Term Segmentation for Chinese CLIR Course Projects:
Vulnerability of Wireless Routing Protocols Radio Wave Receiving Strength Estimation on Wireless Laptop Analysis of Blue Line Extension to Fort Belvoir in Northern Virginia Travel Demand Modeling for Hadley/Route 9 Corridor in Massachusetts Below are some links to some friends, co-authors, and affiliated groups. | |||
