Theoretical and applied evaluations of facial composite systems

Police often use facial composites during their investigations, yet research suggests that facial composites are generally not effective. The present research included two experiments on facial composites. The first experiment was designed to test the usefulness of the encoding specificity principle for determining when facial composites will be effective. Instructions were used to encourage holistic or featural cues at encoding. The method used to construct facial composites was manipulated to encourage holistic or featural cues at retrieval. The encoding specificity principle suggests that an interaction effect should occur. If the same cues are used at encoding and retrieval, better composites should be constructed than when the cues are not the same. However, neither the expected interaction nor the main effects for encoding and retrieval were significant. The second study was conducted to assess the effectiveness of composites generated by two different facial composite construction systems, E-Fit and Mac-A-Mug Pro. These systems differ in that the E-Fit system uses more sophisticated methods of composite construction and may construct better quality facial composites. A comparison of E-Fit and Mac-A-Mug Pro composites demonstrated that E-Fit composites were of better quality than Mac-A-Mug Pro composites. However, neither E-Fit nor Mac-A-Mug Pro composites were useful for identifying the target person from a photograph lineup. Further, lineup performance was at floor level such that both E-Fit and Mac-A-Mug Pro composites were no more useful than a verbal description. Possible limitations of the studies are discussed, as well as suggestions for future research. ^

A systems model for community injury prevention

The purpose of this study was to develop, explicate, and validate a comprehensive model in order to more effectively assess community injury prevention needs, plan and target efforts, identify potential interventions, and provide a framework for an outcome-based evaluation of the effectiveness of interventions. A systems model approach was developed to conceptualize the major components of inputs, efforts, outcomes and feedback within a community setting. Profiling of multiple data sources demonstrated a community feedback mechanism that increased awareness of priority issues and elicited support from traditional as well as non-traditional injury prevention partners. Injury countermeasures including education, enforcement, engineering, and economic incentives were presented for their potential synergistic effect impacting on knowledge, attitudes, or behaviors of a targeted population. Levels of outcome data were classified into ultimate, intermediate and immediate indicators to assist with determining the effectiveness of intervention efforts. A collaboration between business and health care was successful in achieving data access and use of an emergency department level of injury data for monitoring of the impact of community interventions. Evaluation of injury events and preventive efforts within the context of a dynamic community systems environment was applied to a study community with examples detailing actual profiling and trending of injuries. The resulting model of community injury prevention was validated using a community focus group, community injury prevention coordinators, and injury prevention national experts. ^

The development of optimized high performance liquid chromatography systems for the analysis of improvised explosives

Existing instrumental techniques must be adaptable to the analysis of novel explosives if science is to keep up with the practices of terrorists and criminals. The focus of this work has been the development of analytical techniques for the analysis of two types of novel explosives: ascorbic acid-based propellants, and improvised mixtures of concentrated hydrogen peroxide/fuel. In recent years, the use of these explosives in improvised explosive devices (IEDs) has increased. It is therefore important to develop methods which permit the identification of the nature of the original explosive from post-blast residues. Ascorbic acid-based propellants are low explosives which employ an ascorbic acid fuel source with a nitrate/perchlorate oxidizer. A method which utilized ion chromatography with indirect photometric detection was optimized for the analysis of intact propellants. Post-burn and post-blast residues if these propellants were analyzed. It was determined that the ascorbic acid fuel and nitrate oxidizer could be detected in intact propellants, as well as in the post-burn and post-blast residues. Degradation products of the nitrate and perchlorate oxidizers were also detected. With a quadrupole time-of-flight mass spectrometer (QToFMS), exact mass measurements are possible. When an HPLC instrument is coupled to a QToFMS, the combination of retention time with accurate mass measurements, mass spectral fragmentation information, and isotopic abundance patterns allows for the unequivocal identification of a target analyte. An optimized HPLC-ESI-QToFMS method was applied to the analysis of ascorbic acid-based propellants. Exact mass measurements were collected for the fuel and oxidizer anions, and their degradation products. Ascorbic acid was detected in the intact samples and half of the propellants subjected to open burning; the intact fuel molecule was not detected in any of the post-blast residue. Two methods were optimized for the analysis of trace levels of hydrogen peroxide: HPLC with fluorescence detection (HPLC-FD), and HPLC with electrochemical detection (HPLC-ED). Both techniques were extremely selective for hydrogen peroxide. Both methods were applied to the analysis of post-blast debris from improvised mixtures of concentrated hydrogen peroxide/fuel; hydrogen peroxide was detected on variety of substrates. Hydrogen peroxide was detected in the post-blast residues of the improvised explosives TATP and HMTD.

Scheduling medical application workloads on virtualized computing systems

This dissertation presents and evaluates a methodology for scheduling medical application workloads in virtualized computing environments. Such environments are being widely adopted by providers of "cloud computing" services. In the context of provisioning resources for medical applications, such environments allow users to deploy applications on distributed computing resources while keeping their data secure. Furthermore, higher level services that further abstract the infrastructure-related issues can be built on top of such infrastructures. For example, a medical imaging service can allow medical professionals to process their data in the cloud, easing them from the burden of having to deploy and manage these resources themselves. In this work, we focus on issues related to scheduling scientific workloads on virtualized environments. We build upon the knowledge base of traditional parallel job scheduling to address the specific case of medical applications while harnessing the benefits afforded by virtualization technology. To this end, we provide the following contributions: (1) An in-depth analysis of the execution characteristics of the target applications when run in virtualized environments. (2) A performance prediction methodology applicable to the target environment. (3) A scheduling algorithm that harnesses application knowledge and virtualization-related benefits to provide strong scheduling performance and quality of service guarantees. In the process of addressing these pertinent issues for our target user base (i.e. medical professionals and researchers), we provide insight that benefits a large community of scientific application users in industry and academia. Our execution time prediction and scheduling methodologies are implemented and evaluated on a real system running popular scientific applications. We find that we are able to predict the execution time of a number of these applications with an average error of 15%. Our scheduling methodology, which is tested with medical image processing workloads, is compared to that of two baseline scheduling solutions and we find that it outperforms them in terms of both the number of jobs processed and resource utilization by 20–30%, without violating any deadlines. We conclude that our solution is a viable approach to supporting the computational needs of medical users, even if the cloud computing paradigm is not widely adopted in its current form.

VHITS: Vertical handoff initiation and target selection in a heterogeneous wireless network

Global connectivity, for anyone, at anyplace, at anytime, to provide high-speed, high-quality, and reliable communication channels for mobile devices, is now becoming a reality. The credit mainly goes to the recent technological advances in wireless communications comprised of a wide range of technologies, services, and applications to fulfill the particular needs of end-users in different deployment scenarios (Wi-Fi, WiMAX, and 3G/4G cellular systems). In such a heterogeneous wireless environment, one of the key ingredients to provide efficient ubiquitous computing with guaranteed quality and continuity of service is the design of intelligent handoff algorithms. Traditional single-metric handoff decision algorithms, such as Received Signal Strength (RSS) based, are not efficient and intelligent enough to minimize the number of unnecessary handoffs, decision delays, and call-dropping and/or blocking probabilities. This research presented a novel approach for the design and implementation of a multi-criteria vertical handoff algorithm for heterogeneous wireless networks. Several parallel Fuzzy Logic Controllers were utilized in combination with different types of ranking algorithms and metric weighting schemes to implement two major modules: the first module estimated the necessity of handoff, and the other module was developed to select the best network as the target of handoff. Simulations based on different traffic classes, utilizing various types of wireless networks were carried out by implementing a wireless test-bed inspired by the concept of Rudimentary Network Emulator (RUNE). Simulation results indicated that the proposed scheme provided better performance in terms of minimizing the unnecessary handoffs, call dropping, and call blocking and handoff blocking probabilities. When subjected to Conversational traffic and compared against the RSS-based reference algorithm, the proposed scheme, utilizing the FTOPSIS ranking algorithm, was able to reduce the average outage probability of MSs moving with high speeds by 17%, new call blocking probability by 22%, the handoff blocking probability by 16%, and the average handoff rate by 40%. The significant reduction in the resulted handoff rate provides MS with efficient power consumption, and more available battery life. These percentages indicated a higher probability of guaranteed session continuity and quality of the currently utilized service, resulting in higher user satisfaction levels.

Field programmable gate array based target detection and gesture recognition

The move from Standard Definition (SD) to High Definition (HD) represents a six times increases in data, which needs to be processed. With expanding resolutions and evolving compression, there is a need for high performance with flexible architectures to allow for quick upgrade ability. The technology advances in image display resolutions, advanced compression techniques, and video intelligence. Software implementation of these systems can attain accuracy with tradeoffs among processing performance (to achieve specified frame rates, working on large image data sets), power and cost constraints. There is a need for new architectures to be in pace with the fast innovations in video and imaging. It contains dedicated hardware implementation of the pixel and frame rate processes on Field Programmable Gate Array (FPGA) to achieve the real-time performance. ^ The following outlines the contributions of the dissertation. (1) We develop a target detection system by applying a novel running average mean threshold (RAMT) approach to globalize the threshold required for background subtraction. This approach adapts the threshold automatically to different environments (indoor and outdoor) and different targets (humans and vehicles). For low power consumption and better performance, we design the complete system on FPGA. (2) We introduce a safe distance factor and develop an algorithm for occlusion occurrence detection during target tracking. A novel mean-threshold is calculated by motion-position analysis. (3) A new strategy for gesture recognition is developed using Combinational Neural Networks (CNN) based on a tree structure. Analysis of the method is done on American Sign Language (ASL) gestures. We introduce novel point of interests approach to reduce the feature vector size and gradient threshold approach for accurate classification. (4) We design a gesture recognition system using a hardware/ software co-simulation neural network for high speed and low memory storage requirements provided by the FPGA. We develop an innovative maximum distant algorithm which uses only 0.39% of the image as the feature vector to train and test the system design. Database set gestures involved in different applications may vary. Therefore, it is highly essential to keep the feature vector as low as possible while maintaining the same accuracy and performance^

Linking Old Librarianship to New: Aligning 5-Steps of The Innovator's DNA in Creating Thematic Discovery Systems for the Everglades

This poster presentation from the May 2015 Florida Library Association Conference, along with the Everglades Explorer discovery portal at http://ee.fiu.edu, demonstrates how traditional bibliographic and curatorial principles can be applied to: 1) selection, cross-walking and aggregation of metadata linking end-users to wide-spread digital resources from multiple silos; 2) harvesting of select PDFs, HTML and media for web archiving and access; 3) selection of CMS domains, sub-domains and folders for targeted searching using an API. Choosing content for this discovery portal is comparable to past scholarly practice of creating and publishing subject bibliographies, except metadata and data are housed in relational databases. This new and yet traditional capacity coincides with: Growth of bibliographic utilities (MarcEdit); Evolution of open-source discovery systems (eXtensible Catalog); Development of target-capable web crawling and archiving systems (Archive-it); and specialized search APIs (Google). At the same time, historical and technical changes – specifically the increasing fluidity and re-purposing of syndicated metadata – make this possible. It equally stems from the expansion of freely accessible digitized legacy and born-digital resources. Innovation principles helped frame the process by which the thematic Everglades discovery portal was created at Florida International University. The path -- to providing for more effective searching and co-location of digital scientific, educational and historical material related to the Everglades -- is contextualized through five concepts found within Dyer and Christensen’s “The Innovator’s DNA: Mastering the five skills of disruptive innovators (2011). The project also aligns with Ranganathan’s Laws of Library Science, especially the 4th Law -- to "save the time of the user.”

The Development of High Performance Liquid Chromatography Systems for the Analysis of Improvised Explosives

Existing instrumental techniques must be adaptable to the analysis of novel explosives if science is to keep up with the practices of terrorists and criminals. The focus of this work has been the development of analytical techniques for the analysis of two types of novel explosives: ascorbic acid-based propellants, and improvised mixtures of concentrated hydrogen peroxide/fuel. In recent years, the use of these explosives in improvised explosive devices (IEDs) has increased. It is therefore important to develop methods which permit the identification of the nature of the original explosive from post-blast residues. Ascorbic acid-based propellants are low explosives which employ an ascorbic acid fuel source with a nitrate/perchlorate oxidizer. A method which utilized ion chromatography with indirect photometric detection was optimized for the analysis of intact propellants. Post-burn and post-blast residues if these propellants were analyzed. It was determined that the ascorbic acid fuel and nitrate oxidizer could be detected in intact propellants, as well as in the post-burn and post-blast residues. Degradation products of the nitrate and perchlorate oxidizers were also detected. With a quadrupole time-of-flight mass spectrometer (QToFMS), exact mass measurements are possible. When an HPLC instrument is coupled to a QToFMS, the combination of retention time with accurate mass measurements, mass spectral fragmentation information, and isotopic abundance patterns allows for the unequivocal identification of a target analyte. An optimized HPLC-ESI-QToFMS method was applied to the analysis of ascorbic acid-based propellants. Exact mass measurements were collected for the fuel and oxidizer anions, and their degradation products. Ascorbic acid was detected in the intact samples and half of the propellants subjected to open burning; the intact fuel molecule was not detected in any of the post-blast residue. Two methods were optimized for the analysis of trace levels of hydrogen peroxide: HPLC with fluorescence detection (HPLC-FD), and HPLC with electrochemical detection (HPLC-ED). Both techniques were extremely selective for hydrogen peroxide. Both methods were applied to the analysis of post-blast debris from improvised mixtures of concentrated hydrogen peroxide/fuel; hydrogen peroxide was detected on variety of substrates. Hydrogen peroxide was detected in the post-blast residues of the improvised explosives TATP and HMTD.