Thesis (M.S. in Information Technology Management and M.S. in Systems Technology (Command, Control & Communications))--Naval Postgraduate School, June 2010, John Binstock. Thesis (M.S. in Systems Technology (Command, Control & Communications))--Naval Postgraduate School, June 2010, Michael Minukas. / Thesis Advisor(s): Fox, William ; Second Reader: Pfeiffer, Karl. "June 2010." Description based on title screen as viewed on July 14, 2010. Author(s) subject terms: Improvised Explosive Device, IED, Suicide Vest, Suicide Bomber, Standoff Detection, Detection Methodology. Includes bibliographical references (p. 103-109). Also available in print.

"Submitted in partial fulfillment of the requirements for the degree of Master of Business Administration from the Naval Postgraduate School, June 2010." / Advisor(s): Ferrer, Geraldo ; Brinkley, Douglas. "June 2010." "MBA Professional report"--Cover. Description based on title screen as viewed on July 14, 2010. Author(s) subject terms: Item Unique Identification, Littoral Combat Ship, Mission Package Support Facility, Unique Identification, Unique Item Identifier Includes bibliographical references (p. 83-87). Also available in print.

Thesis (M.S.)--University of Wisconsin--Madison, 1983. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 54-65).

Thesis (M.S.)--West Virginia University, 2006. / Title from document title page. Document formatted into pages; contains vii, 73 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 70-73).

Thesis (M.A.B.S.)--Multnomah School of the Bible, 1986. / Bibliography: leaves 56-64.

Law enforcement officials routinely rely on eyewitness identification evidence to solve crimes. Nonetheless, this form of evidence is prone to errors. Researchers have previously attempted to examine conditions under which such errors can be reduced. The present study examines whether giving witnesses an explicit not sure response option increases the accuracy of lineup identification decisions. 251 participants watched a mock crime video before viewing a lineup that either included the perpetrator, or was made up of innocent suspects. Results indicated that witnesses provided with a not sure option made fewer false identifications, fewer filler identifications, and a similar number of correct identifications as witnesses who were not provided with this option. Furthermore, these benefits occurred regardless of whether witnesses received otherwise biased or unbiased instructions. Results suggest that the inclusion of an explicit not sure response option is a simple procedure that can increase the quality of eyewitness lineup decisions.

A dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of requirements for the degree of Master of Science, School of Computer Science and Applied Mathematics. May 2017. / Biometric features have been widely implemented to be utilized for forensic and civil applications. Amongst many different kinds of biometric characteristics, the fingerprint is globally accepted and remains the mostly used biometric characteristic by commercial and industrial societies due to its easy acquisition, uniqueness, stability and reliability. There are currently various effective solutions available, however the fingerprint identification is still not considered a fully solved problem mainly due to accuracy and computational time requirements. Although many of the fingerprint recognition systems based on minutiae provide good accuracy, the systems with very large databases require fast and real time comparison of fingerprints, they often either fail to meet the high performance speed requirements or compromise the accuracy. For fingerprint matching that involves databases containing millions of fingerprints, real time identification can only be obtained through the implementation of optimal algorithms that may utilize the given hardware as robustly and efficiently as possible. There are currently no known distributed database and computing framework available that deal with real time solution for fingerprint recognition problem involving databases containing as many as sixty million fingerprints, the size which is close to the size of the South African population. This research proposal intends to serve two main purposes: 1) exploit and scale the best known minutiae matching algorithm for a minimum of sixty million fingerprints; and 2) design a framework for distributed database to deal with large fingerprint databases based on the results obtained in the former item. / GR2018

Specific emitter identification refers to the process of performing identification of radio frequency transmitters by exploiting unique variations in emitted signals, caused by hardware variations. In previous research, specific emitter identification was successfully performed on GSM handsets. However, no research has been done on the implementation of specific emitter identification of GSM handsets on an FPGA platform. This study focuses on feature extraction and identification algorithms, as well as the implementation of the identification algorithm on an FPGA. During this study, phase modulation error was used, as previous research indicated that phase modulation error is an effective feature set for identification purposes. As the implementation of a classification algorithm on an FPGA was required, a trade-off between complexity and feasibility needed to be made during the selection process. The artificial neural network was selected as the optimal classifier for implementation on an FPGA. The algorithm was first implemented in software and used as the basis for the design on an FPGA. A piece-wise linear approximation of a sigmoid function was used to approximate the activation function, where a look-up table was used to store the parameters. The off-line training of the artificial neural network was performed in software using the back-propagation gradient descent algorithm. Good results for the identification of GSM handsets on an FPGA were obtained, with a true acceptance ratio of 97.0%. This result is similar to the performance obtained in previous research performed in software. In this study, it was found that specific emitter identification of GSM handsets can be performed on an FPGA. Real-world applications for this technology include general cellular handset identification and access control. / MSc (Electrical and Electronic Engineering), North-West University, Potchefstroom Campus, 2015

Specific emitter identification refers to the process of performing identification of radio frequency transmitters by exploiting unique variations in emitted signals, caused by hardware variations. In previous research, specific emitter identification was successfully performed on GSM handsets. However, no research has been done on the implementation of specific emitter identification of GSM handsets on an FPGA platform. This study focuses on feature extraction and identification algorithms, as well as the implementation of the identification algorithm on an FPGA. During this study, phase modulation error was used, as previous research indicated that phase modulation error is an effective feature set for identification purposes. As the implementation of a classification algorithm on an FPGA was required, a trade-off between complexity and feasibility needed to be made during the selection process. The artificial neural network was selected as the optimal classifier for implementation on an FPGA. The algorithm was first implemented in software and used as the basis for the design on an FPGA. A piece-wise linear approximation of a sigmoid function was used to approximate the activation function, where a look-up table was used to store the parameters. The off-line training of the artificial neural network was performed in software using the back-propagation gradient descent algorithm. Good results for the identification of GSM handsets on an FPGA were obtained, with a true acceptance ratio of 97.0%. This result is similar to the performance obtained in previous research performed in software. In this study, it was found that specific emitter identification of GSM handsets can be performed on an FPGA. Real-world applications for this technology include general cellular handset identification and access control. / MSc (Electrical and Electronic Engineering), North-West University, Potchefstroom Campus, 2015

M.Sc. (Information Technology) / Biometrics is a unique method used to identify humans by distinct biological characterises. In recent years biometrics are showing up everywhere from homes, workplaces, schools and banks. This identification method is rapidly replacing existing methods such as passwords since it offers a higher level of security compared to existing methods. Fingerprints are the most common biometric choice. However fingerprint biometrics is showing limitations. Since fingerprints are an external trait, it can be exposed to many situations (cuts, dirt, wear and tear, and skin conditions) that may impact the biometric captured. These factors can cause security and usability issues. There have been a number of successful attempts such as alteration of fingerprints and gummy fingers which are used to bypass fingerprint readers. An emerging biometric called finger-vein recognition was invented to overcome the issues that fingerprint biometrics have. Finger-vein recognition which is based on the vascular patterns that exist inside the finger, claim to have superior usability characteristics where less false acceptance or rejections occur. Since the finger-vein recognition is based on an internal trait it is assumed that external factors such as scars or even dirt will not affect the biometric collected. This dissertation aims to investigate the limitations of fingerprints and to determine whether finger-vein recognition can address these limitations. During the course of the dissertation applicable fields such as construction and mining will be identified for finger-vein recognition where fingerprint recognition has shown weakness. Together, fingerprint and finger-vein technologies will be used in a mining industry to perform minor experiments. The results of these experiments will be used to determine if finger-vein addresses the fundamental limitations of fingerprint biometrics in these industries. The main purposes of the dissertation will be to investigate finger-vein technology, the applicable fields and whether finger-vein recognition can solve the problems fingerprint recognition imposes in certain industries.