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Full-Text Articles in Engineering
Receiver Operating Characteristic And Location Analysis Of Simulated Near-Infrared Tomography Images, Xiaomei Song, Brian W. Pogue, Hamid Dehghani, Shudong Jiang, Keith D. Paulsen, Tor D. Tosteson
Receiver Operating Characteristic And Location Analysis Of Simulated Near-Infrared Tomography Images, Xiaomei Song, Brian W. Pogue, Hamid Dehghani, Shudong Jiang, Keith D. Paulsen, Tor D. Tosteson
Dartmouth Scholarship
Receiver operating characteristic (ROC) analysis was performed on simulated near-infrared tomography images, using both human observer and contrast-to-noise ratio (CNR) computational assessment, for application in breast cancer imaging. In the analysis, a nonparametric approach was applied for estimating the ROC curves. Human observer detection of objects had superior capability to localize the presence of heterogeneities when the objects were small with high contrast, with a minimum detectable threshold of CNR near 3.0 to 3.3 in the images. Human observers were able to detect heterogeneities in the images below a size limit of 4 mm, yet could not accurately find the …
A Pre-Crash Simulator To Evaluate Vehicle Collision Prediction Algorithms, Dana Desrosiers, Charles Birdsong, Peter Schuster
A Pre-Crash Simulator To Evaluate Vehicle Collision Prediction Algorithms, Dana Desrosiers, Charles Birdsong, Peter Schuster
Mechanical Engineering
This paper describes a software simulator for pre-crash collision predictions. The simulator is a surrogate test bed for evaluating the performance of proposed pre-crash algorithms. It reads data from a file, transfers distance and angular position of a target to a test algorithm, and then records the algorithm’s predictions. To illustrate the simulator functionality, a simplified test algorithm is also described. This algorithm predicts collision risks based on assumptions about the size and acceleration of a target object, and the turning and braking limits of the host vehicle. The test algorithm is shown to be effective for cases where both …
Nesting System With Quantization And Knowledge Base Applied, Leszek Koszalka, Grzegorz Chmaj
Nesting System With Quantization And Knowledge Base Applied, Leszek Koszalka, Grzegorz Chmaj
Electrical & Computer Engineering Faculty Research
Nesting algorithms deal with placing two dimensional shapes on the given canvas. In this paper a binary way of solving the nesting problem is proposed. Geometric shapes are quantized into binary form, which is used to operate on them. After finishing nesting they are converted back into original geometrical form. Investigations showed, that there is a big influence of quantization accuracy for the nesting effect. However, greater accuracy results with longer time of computation. The proposed knowledge base system is able to strongly reduce the computational time.
Optimal Area Covering Using Genetic Algorithms, Paulo A. Jimenez, Bijan Shirinzadeh, Ann Nicholson, Gursel Alici
Optimal Area Covering Using Genetic Algorithms, Paulo A. Jimenez, Bijan Shirinzadeh, Ann Nicholson, Gursel Alici
Faculty of Engineering - Papers (Archive)
Path planning problems involve computing or finding a collision free path between two positions. A special kind of path planning is complete coverage path planning, where a robot sweeps all area of free space in an environment. There are different methods to cover the complete area; however, they are not designed to optimize the process. This paper proposes a novel method of complete coverage path planning based on genetic algorithms. In order to check the viability of this approach the optimal path is tested in a virtual environment. The simulation results confirm the feasibility of this method.
Using Pareto Fronts To Evaluate Polyp Detection Algorithms For Ct Colonography, Adam Huang, Jiang Li, Ronald M. Summers, Nicholas Petrick, Amy K. Hara
Using Pareto Fronts To Evaluate Polyp Detection Algorithms For Ct Colonography, Adam Huang, Jiang Li, Ronald M. Summers, Nicholas Petrick, Amy K. Hara
Electrical & Computer Engineering Faculty Publications
We evaluate and improve an existing curvature-based region growing algorithm for colonic polyp detection for our CT colonography (CTC) computer-aided detection (CAD) system by using Pareto fronts. The performance of a polyp detection algorithm involves two conflicting objectives, minimizing both false negative (FN) and false positive (FP) detection rates. This problem does not produce a single optimal solution but a set of solutions known as a Pareto front. Any solution in a Pareto front can only outperform other solutions in one of the two competing objectives. Using evolutionary algorithms to find the Pareto fronts for multi-objective optimization problems has been …