Explosive hazards, above and below ground, are a serious threat to civilians and soldiers. In an attempt to mitigate these threats, different forms of explosive hazard detection (EHD) exist; e.g, multi-sensor hand-held platforms, downward looking and forward looking vehicle mounted platforms, etc. Robust detection of these threats resides in the processing and fusion of different data from multiple sensing modalities, e.g., radar, infrared, electromagnetic induction (EMI), etc. The focus of this thesis is on the implementation of two new algorithms to form a new energy-based prescreener in hand-held ground penetrating radar (GPR). First, B-scan signal data is curvelet filtered using either Reverse- Reconstruction followed by Enhancement (RRE) or selectivity with respect to wedge information in the Curvelet transform, Wedge Selection (WS). Next, the result of a bank of matched filter are aggregated and run a size contrast filter with Bhattacharyya distance. Alarms are then combined using weighted mean shift clustering. Results are demonstrated in the context of receiver operating characteristics (ROC) curve performance on data from a U.S. Army test site that contains multiple target and clutter types, burial depths, and times of the day.

Substantial interest resides in identifying sensors, algorithms and fusion theories to detect explosive hazards. This is a significant research effort because it impacts the safety and lives of civilians and soldiers alike. However, a challenging aspect of this field is we are not in conflict with the threats (objects) per se. Instead, we are dealing with people and their changing strategies and preferred method of delivery. Herein, I investigate one method of threat delivery, side attack explosive ballistics (SAEB). In particular, I explore a vehicle-mounted synthetic aperture acoustic (SAA) platform. First, a wide band SAA signal is decomposed into a higher spectral resolution signal. Next, different multi/hyperspectral signal processing techniques are explored for manual band analysis and selection. Last, a convolutional neural network (CNN) is used for filter (e.g., enhancement and/or feature) learning and classification relative to the full signal versus different subbands. Performance is assessed in the context of receiver operating characteristic (ROC) curves on data from a U.S. Army test site that contains multiple target and clutter types, levels of concealment and times of day. Preliminary results indicate that a machine learned CNN solution can achieve better performance than our previously established human engineered Fraz feature with kernel support vector machine classification.

The purpose of this study was to identify a potentiation effect on 30 meter (m) fly sprint performance in collegiate sprinters and jumpers (M=21, W=5) following an acute bout of whole-body vibration. The WBV protocol consisted of one 30 second bout at 50 Hz, ~3 mm amplitude, and 60 seconds rest before a 30m fly sprint. Sprint times were measured using timing gates, and characteristics of strength and power were measured using a force plate. Analysis included measures of jump height, peak power, peak force, and rate of force development. Each subject participated in 3 separate trials using randomized treatment sessions over 3 months of preparation training. The control condition consisted of no vibration and WBV treatment 1 and 2 incorporated vibration. Statistics comparing the average sprint times showed no treatment effects. The results of this study indicate that WBV at 50 Hz and ~3 mm amplitude has no effect on sprint times.

Thesis (Ph.D.)--Boston University / The widespread use of Improvised Explosive Devices (IEDs) in the Wars in Iraq and Afghanistan has caused a dramatic increase in shockwave-induced mild Traumatic Brain Injury (mTBI), leading mTBI to be dubbed the 'signature injury' of modern warfare. Currently, the pathology of shockwave-induced mTBI is unknown , and it is diagnosis is based on self-reported symptoms and combat history. While the etiological mechanism has not yet been determined , it is becoming increasingly accepted that shockwaves themselves are the brain-damaging agent that emanate from IEDs. To assess how mild, sub-lethal shockwaves might damage brain tissue, we developed an in vitro assay to deliver shockwaves to neuronal cells in culture, and then assayed several properties of these cells that affect their function. This assay involved exposing rat cortical and hippocampal primary neuronal cultures to shockwaves of increasing magnitude generated with a biolistic Gene Gun. The Gene Gun produces shockwaves of sufficient overpressure to cause cognitive impairment in animal models of shockwave-induced mTBI. Our results show that overpressures of ~1.0 pound per square inch (psi) caused transient membrane permeability for molecules up to ~12 nanometers in diameter. This change in membrane permeability was accompanied by a transient decrease in cellular ATP levels and synaptic densities. This synaptic degeneration correlated with changes in the level and phosphorylation state of several synaptic proteins examined. Similar results were observed in dissected rat retinas suggesting that these shockwave-induced effects can occur in complex tissues, such as the brain. Based on these findings we propose that shockwaves damage cellular membranes, leading to a decrease in intracellular ATP, and ultimately to a reduced numbers of synapses, the part of neurons most important for learning, memory and behavior. Additional experiments in whole animals will be required to ascertain whether shockwave-induced cellular damage and synaptic degeneration plays an etiological role in shockwave-induced mTBI.

A proof of concept is created that demonstrates how low-cost sensors and a simple software solution can be used to proactively detect IED placement. The main goal is to detect suspicious behavior; Specifically we derive requirements that loitering, meandering, improper location and object placement shall be detected. Current methods being used to detect Improvised Explosive Devices (IEDs) are costly in terms of equipment and risk to life, and many are retroactive; IED detection occurs long after explosives are placed. A prototype system is explored with the quality attributes of being low-cost, proactive and using simple software methods. A wireless sensor network of simple sensors may alert authorities to people in the act of placing IEDs. Previous work with Crossbow Motes showed that a network of infrared motion sensors can be used to detect loitering. In this prototype nine other sensors are reverse engineered to determine their true operating specifications. Then a prototype sensor network is developed to explore which low-cost sensors can be used to detect suspicious behavior. The results indicate that five low-cost sensors are effective in detecting suspicious behavior: infrared motion, infrared distance, light, force sensors and pressure sensors meet our requirements.

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<p dir="ltr">Gas chromatography-mass spectrometry (GC-MS) is a frequently used technique in forensic chemistry for the identification of controlled substances and explosives. GC-MS can be coupled with solid-phase microextraction (SPME), in which a fiber with a sorptive coating is placed into the headspace above a sample or directly immersed in a liquid sample. Analytes are adsorbed onto the fiber which is then placed inside the heated GC inlet for desorption.</p><p dir="ltr">Illicit drugs are often found in the form of impure solids, mixed with other drugs, adulterants, and diluents. A simple method for the quick identification of drugs including methamphetamine, cocaine, heroin, fentanyl, and pharmaceutical tablets was developed. Headspace SPME methods were utilized with an elevated extraction temperature for the detection of various drugs in powder and tablet form. An extraction temperature of 120°C was used to encourage analytes into the headspace of the vial. A sample of the solid drug was placed in a headspace vial with no prior sample preparation or clean-up. This vial was then heated inside of an agitator where the sample was extracted. It was found that drugs in solid and tablet form can be detected using this high temperature headspace SPME method at the temperature of 120°C with no prior sample preparation. This method is simple, efficient, and cost effective for the detection of legal and illicit drugs in solid form.</p><p dir="ltr">Headspace SPME may also be used for the analysis of explosive materials. Canines trained at detecting hidden explosives should be trained using real explosive materials that have minimal contamination by other explosive odors to ensure accurate identification of potential threats. Therefore, the potential for cross-contamination between training aids is of importance. There are various storage methods in use by canine handlers such as plastic and cloth bags, but these can lead to cross-contamination between training aids during storage. Alternatively, odor-permeable membrane devices (OPMDs) may store training aides and be used as a delivery device. A membrane in the OPMD allows for volatile compounds from the training aids to be released during training while helping to prevent contaminants from entering the device. OPMDs were used in addition to traditional storage containers to monitor the contamination and degradation of 14 explosives used as canine training aids. Samples included explosives that contain highly volatile compounds like dynamite and explosives with less volatile compounds like RDX. Explosives were stored individually using traditional storage bags or inside of an OPMD at two locations, IUPUI and an Indianapolis Metropolitan Police Department. The police department actively used the training aids during canine trainings. Samples from each storage type at both locations were collected at 0, 3, 6, and 9 months and analyzed using Fourier transform infrared (FTIR) spectroscopy and GC-MS with SPME. FTIR analyses showed no signs of degradation of the training aids from any timepoint or location. GC-MS identified cross-contamination from ethylene glycol dinitrate and/or 2,3-dimethyl-2,3-dinitrobutane across almost all samples regardless of storage condition. The contamination was found to be higher among training aids that were stored in traditional ways and were in active use by canine teams. Additionally, Time 0 had the highest level of contamination, indicating that explosive training aids are received from the vendors with initial cross-contamination.</p><p dir="ltr">To test the initial cross-contamination levels of training aids, 11 explosive materials were ordered from three different vendors. A 1-gram sample of each was collected and analyzed using SPME with GC-MS. In several cases, explosive materials that are commercially available already exhibit elevated levels of contamination. This indicates that training aids must be acquiring contamination during manufacturing and/or storage at the vendor facility. The cross-contamination of explosive canine training aids stored in OPMDs was further evaluated and compared to traditional storage methods. This was done by storing various combinations of storage containers such as cloth bags, velcro bags, and OPMDs along with explosives and using activated charcoal strips to collect the volatile compounds such as 2,3-dimethyl-2,3-dinitrobutane and ethylene glycol dinitrate. Only one type of storage container, a velcro bag, showed evidence of contamination, indicating that OPMDs may not further prevent cross-contamination of explosive training aids.</p>