Assessment of the application of automatic vehicle identification technology to traffic management : Appendix C, Evaluation of potential applications of automatic vehicle monitoring to traffic management /

Mode of access: Internet.

Assessment of the application of automatic vehicle identification technology to traffic management : Appendix B, Evaluation of potential applications of automatic vehicle identification to traffic management /

Mode of access: Internet.

Direct and general support maintenance manual : transmission, automatic, 2520-066-4240 (Allison Div., GMC model TX 100-1).

Includes index.

Direct and general support maintenance manual for transmission assembly, automatic, model TX 200-2A, Allison Division, GM, 2520-860-7342, transmission assembly, automatic, model TX 200-2B, Allison Division, GM, 2520-964-9207, transmission assembly, automatic, model TX 200-6, Allison Division, GM, 2520-045-3108.

Includes index.

Operator's manual, carrier, guided missile equipment, self-propelled : M730 (1450-00-930-8749) and M730A1 (1450-01-121-2122).

Includes index.

Organizational maintenance manual for carrier, guided missile equipment, self-propelled, M730 (1450-00-930-8749) and M730A1 (1450-01-121-2122).

Includes index.

Direct support and general support maintenance manual : loader-transporter, guided missile, XM501E3 (Hawk guided missile system), part number 11675300, NSN 1450-00-066-8873.

Includes index.

Operator's manual : loader-transporter, guided missile, XM501E3 (Hawk guided missile system) (1450-00-066-8873).

"March 1988."

Organizational maintenance manual : loader-transporter, guided missile, XM501E3 (Hawk guided missile system), part number 11675300, NSN 1450-00-066-8873).

"June 1979."

Operator's and organizational maintenance manual : alarm, chemical agent, automatic, portable, manpack, M8 (NSN 665-00-935-6955) ... w/power supply for truck, 2 1/2 ton, M18 (NSN 6665-00-169-1454).

Includes index.

Organizational maintenance manual including repair parts and special tools lists : installation kits for alarm, chemical agent, automatic, portable, for truck, 2-1/2 ton, M13 (FSN 6665-479-2718) ... w/power supply for truck, utility, 1/4 ton, M16 (FSN 6665-479-2716).

Includes index.

Direct support and general support maintenance repair parts and special tools list including depot maintenance repair parts and special tools for azimuth laying set, guided missile AN/TSQ-110(X0-1) 1430-00-399-5318, encoder, shaft angle, digital (in container) 1430-01-034-2268, gyro reference unit (in container) 1430-01-033-4044 ...

Includes index.

Direct support, general support, and depot maintenance repair parts and special tools list for transmission, automatic, with container, assembly model TX 200-2A ... transmission, automatic ... assembly model TX 200-2B ... transmission, automatic ... assembly model TX 200-6, Allison Division, GM 2520-133-9635.

Includes index.

A framework for automatic feature extraction from airborne light detection and ranging data

Recent advances in airborne Light Detection and Ranging (LIDAR) technology allow rapid and inexpensive measurements of topography over large areas. Airborne LIDAR systems usually return a 3-dimensional cloud of point measurements from reflective objects scanned by the laser beneath the flight path. This technology is becoming a primary method for extracting information of different kinds of geometrical objects, such as high-resolution digital terrain models (DTMs), buildings and trees, etc. In the past decade, LIDAR gets more and more interest from researchers in the field of remote sensing and GIS. Compared to the traditional data sources, such as aerial photography and satellite images, LIDAR measurements are not influenced by sun shadow and relief displacement. However, voluminous data pose a new challenge for automated extraction the geometrical information from LIDAR measurements because many raster image processing techniques cannot be directly applied to irregularly spaced LIDAR points. ^ In this dissertation, a framework is proposed to filter out information about different kinds of geometrical objects, such as terrain and buildings from LIDAR automatically. They are essential to numerous applications such as flood modeling, landslide prediction and hurricane animation. The framework consists of several intuitive algorithms. Firstly, a progressive morphological filter was developed to detect non-ground LIDAR measurements. By gradually increasing the window size and elevation difference threshold of the filter, the measurements of vehicles, vegetation, and buildings are removed, while ground data are preserved. Then, building measurements are identified from no-ground measurements using a region growing algorithm based on the plane-fitting technique. Raw footprints for segmented building measurements are derived by connecting boundary points and are further simplified and adjusted by several proposed operations to remove noise, which is caused by irregularly spaced LIDAR measurements. To reconstruct 3D building models, the raw 2D topology of each building is first extracted and then further adjusted. Since the adjusting operations for simple building models do not work well on 2D topology, 2D snake algorithm is proposed to adjust 2D topology. The 2D snake algorithm consists of newly defined energy functions for topology adjusting and a linear algorithm to find the minimal energy value of 2D snake problems. Data sets from urbanized areas including large institutional, commercial, and small residential buildings were employed to test the proposed framework. The results demonstrated that the proposed framework achieves a very good performance. ^

Open-source virtual bronchoscopy for image guided navigation

This thesis describes the development of an open-source system for virtual bronchoscopy used in combination with electromagnetic instrument tracking. The end application is virtual navigation of the lung for biopsy of early stage cancer nodules. The open-source platform 3D Slicer was used for creating freely available algorithms for virtual bronchscopy. Firstly, the development of an open-source semi-automatic algorithm for prediction of solitary pulmonary nodule malignancy is presented. This approach may help the physician decide whether to proceed with biopsy of the nodule. The user-selected nodule is segmented in order to extract radiological characteristics (i.e., size, location, edge smoothness, calcification presence, cavity wall thickness) which are combined with patient information to calculate likelihood of malignancy. The overall accuracy of the algorithm is shown to be high compared to independent experts' assessment of malignancy. The algorithm is also compared with two different predictors, and our approach is shown to provide the best overall prediction accuracy. The development of an airway segmentation algorithm which extracts the airway tree from surrounding structures on chest Computed Tomography (CT) images is then described. This represents the first fundamental step toward the creation of a virtual bronchoscopy system. Clinical and ex-vivo images are used to evaluate performance of the algorithm. Different CT scan parameters are investigated and parameters for successful airway segmentation are optimized. Slice thickness is the most affecting parameter, while variation of reconstruction kernel and radiation dose is shown to be less critical. Airway segmentation is used to create a 3D rendered model of the airway tree for virtual navigation. Finally, the first open-source virtual bronchoscopy system was combined with electromagnetic tracking of the bronchoscope for the development of a GPS-like system for navigating within the lungs. Tools for pre-procedural planning and for helping with navigation are provided. Registration between the lungs of the patient and the virtually reconstructed airway tree is achieved using a landmark-based approach. In an attempt to reduce difficulties with registration errors, we also implemented a landmark-free registration method based on a balanced airway survey. In-vitro and in-vivo testing showed good accuracy for this registration approach. The centreline of the 3D airway model is extracted and used to compensate for possible registration errors. Tools are provided to select a target for biopsy on the patient CT image, and pathways from the trachea towards the selected targets are automatically created. The pathways guide the physician during navigation, while distance to target information is updated in real-time and presented to the user. During navigation, video from the bronchoscope is streamed and presented to the physician next to the 3D rendered image. The electromagnetic tracking is implemented with 5 DOF sensing that does not provide roll rotation information. An intensity-based image registration approach is implemented to rotate the virtual image according to the bronchoscope's rotations. The virtual bronchoscopy system is shown to be easy to use and accurate in replicating the clinical setting, as demonstrated in the pre-clinical environment of a breathing lung method. Animal studies were performed to evaluate the overall system performance.