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Full-Text Articles in Engineering

Analysis Of Various Classification Techniques For Computer Aided Detection System Of Pulmonary Nodules In Ct, Barath Narayanan Narayanan, Russell C. Hardie, Temesguen Messay Jun 2017

Analysis Of Various Classification Techniques For Computer Aided Detection System Of Pulmonary Nodules In Ct, Barath Narayanan Narayanan, Russell C. Hardie, Temesguen Messay

Russell C. Hardie

Lung cancer is the leading cause of cancer death in the United States. It usually exhibits its presence with the formation of pulmonary nodules. Nodules are round or oval-shaped growth present in the lung. Computed Tomography (CT) scans are used by radiologists to detect such nodules. Computer Aided Detection (CAD) of such nodules would aid in providing a second opinion to the radiologists and would be of valuable help in lung cancer screening. In this research, we study various feature selection methods for the CAD system framework proposed in FlyerScan. Algorithmic steps of FlyerScan include (i) local contrast enhancement (ii) …


Differential Tilt Variance Effects Of Turbulence In Imagery: Comparing Simulation With Theory, Daniel A. Lemaster, Russell C. Hardie, Szymon Gladysz, Matthew D. Howard, Michael Armand Rucci, Matthew E. Trippel, Jonathan D. Power, Barry K. Karch Jun 2017

Differential Tilt Variance Effects Of Turbulence In Imagery: Comparing Simulation With Theory, Daniel A. Lemaster, Russell C. Hardie, Szymon Gladysz, Matthew D. Howard, Michael Armand Rucci, Matthew E. Trippel, Jonathan D. Power, Barry K. Karch

Russell C. Hardie

Differential tilt variance is a useful metric for interpreting the distorting effects of turbulence in incoherent imaging systems. In this paper, we compare the theoretical model of differential tilt variance to simulations. Simulation is based on a Monte Carlo wave optics approach with split step propagation. Results show that the simulation closely matches theory. The results also show that care must be taken when selecting a method to estimate tilts.


Recursive Robust Pca Or Recursive Sparse Recovery In Large But Structured Noise, Chenlu Qiu, Namrata Vaswani, Brian Lois, Leslie Hogben Jun 2017

Recursive Robust Pca Or Recursive Sparse Recovery In Large But Structured Noise, Chenlu Qiu, Namrata Vaswani, Brian Lois, Leslie Hogben

Namrata Vaswani

This paper studies the recursive robust principal components analysis problem. If the outlier is the signal-of-interest, this problem can be interpreted as one of recursively recovering a time sequence of sparse vectors, St, in the presence of large but structured noise, Lt. The structure that we assume on Lt is that Lt is dense and lies in a low-dimensional subspace that is either fixed or changes slowly enough. A key application where this problem occurs is in video surveillance where the goal is to separate a slowly changing background (Lt) from moving foreground objects (St) on-the-fly. To solve the above …


Capturing Cognitive Fingerprints From Keystroke Dynamics, J. Morris Chang, Chi-Chen Fang, Kuan-Hsing Ho, Norene Kelly, Pei-Yuan Wu, Yixiao Ding, Chris Chu, Stephen B. Gilbert, Amed E. Kamal, Sun-Yuan Kung Jun 2017

Capturing Cognitive Fingerprints From Keystroke Dynamics, J. Morris Chang, Chi-Chen Fang, Kuan-Hsing Ho, Norene Kelly, Pei-Yuan Wu, Yixiao Ding, Chris Chu, Stephen B. Gilbert, Amed E. Kamal, Sun-Yuan Kung

Morris Chang

Conventional authentication systems identify a user only at the entry point. Keystroke dynamics can continuously authenticate users by their typing rhythms without extra devices. This article presents a new feature called cognitive typing rhythm (CTR) to continuously verify the identities of computer users. Two machine techniques, SVM and KRR, have been developed for the system. The best results from experiments conducted with 1,977 users show a false-rejection rate of 0.7 percent and a false-acceptance rate of 5.5 percent. CTR therefore constitutes a cognitive fingerprint for continuous. Its effectiveness has been verified through a large-scale dataset. This article is part of …


Network Connection Blocker, Method, And Computer Readable Memory For Monitoring Connections In A Computer Network And Blocking The Unwanted Connections, Douglas W. Jacobson, James A. Davis Jun 2017

Network Connection Blocker, Method, And Computer Readable Memory For Monitoring Connections In A Computer Network And Blocking The Unwanted Connections, Douglas W. Jacobson, James A. Davis

Douglas Jacobson

A network connection blocker for monitoring connections between host computers in a network and blocking the unwanted connections. The host computers transmit connection packets between each other in accordance with a network protocol suite when seeking to establish, providing network services with, and close the connections. The network protocol suite includes a connection oriented transport layer protocol. The network connection blocker comprises a network interface that receives the connection packets transmitted between the host computers. It also comprises a blocking module that processes the received connection packets to detect the unwanted connections. The blocking module then generates connection packets in …