Matching Items (10)

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Acoustic Gunshot Detection Device Design and Power Management

Description

The following report provides details on the development of a protective enclosure and power system for an anti-poaching gunshot detection system to be implemented in Costa Rica. The development of

The following report provides details on the development of a protective enclosure and power system for an anti-poaching gunshot detection system to be implemented in Costa Rica. The development of a gunshot detection system is part of an ongoing project started by the Acoustic Ecology Lab at Arizona State University in partnership with the Phoenix Zoo. As a whole, the project entails the development of a gunshot detection algorithm, wireless mesh alert system, device enclosure, and self-sustaining power system. For testing purposes, four devices, with different power system setups, were developed. Future developments are discussed and include further testing, more specialized mounting techniques, and the eventual expansion of the initial device network. This report presents the initial development of the protective enclosure and power system of the anti-poaching system that can be implemented in wildlife sanctuaries around the world.

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Date Created
  • 2020-05

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Evaluation of Norovirus Detection in Dilute Solutions

Description

In this project, biochemical characteristics of peptide binding agents, synthetic antibodies or synbodies, were examined with respect to the capture efficiency and specific binding ability to norovirus. Norovirus, although generally

In this project, biochemical characteristics of peptide binding agents, synthetic antibodies or synbodies, were examined with respect to the capture efficiency and specific binding ability to norovirus. Norovirus, although generally not a deadly pathogen, is the most common cause of acute gastroenteritis and outbreaks present a large social and financial burden to the healthcare and food service industries. With Dr. Diehnelt's laboratory group, a platform has been developed that enables us to rapidly construct peptide-based affinity ligands that can be characterized for binding to norovirus. The design needed to display clear results, be simple to operate, and be inexpensive to produce and use. Four synbodies, originally engineered with a specificity to the GII.4 Minerva genotype were tested with different virus strains varying in similarity to the GII.4 Minerva between 43% and 95.4%. Initial assays utilized norovirus-like particles to qualitatively compare the capture efficiency of the different synbodies without utilizing limited resources. To quantify the amount of actual virus captured by the synbodies, western blots with RT-PCR and RT-qPCR were utilized. The results indicated the synbodies were able to enrich the dilute solutions of the different noroviruses utilizing a magnetic bead pull-down assay. The capture efficiencies of the synbodies were comparable to currently utilized binding agents such as aptamers and porcine gastric mucine magnetic beads. This thesis presents data collected over nearly two years of research at the Center for Innovations in Medicine at the Biodesign Institute located at Arizona State University.

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Created

Date Created
  • 2016-05

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Cryptojacking Detection: A Classification and Comparison of Malicious Cryptocurrency Mining Detection Systems

Description

Cryptojacking is a process in which a program utilizes a user’s CPU to mine cryptocurrencies unknown to the user. Since cryptojacking is a relatively new problem and its impact is

Cryptojacking is a process in which a program utilizes a user’s CPU to mine cryptocurrencies unknown to the user. Since cryptojacking is a relatively new problem and its impact is still limited, very little has been done to combat it. Multiple studies have been conducted where a cryptojacking detection system is implemented, but none of these systems have truly solved the problem. This thesis surveys existing studies and provides a classification and evaluation of each detection system with the aim of determining their pros and cons. The result of the evaluation indicates that it might be possible to bypass detection of existing systems by modifying the cryptojacking code. In addition to this classification, I developed an automatic code instrumentation program that replaces specific instructions with functionally similar sequences as a way to show how easy it is to implement simple obfuscation to bypass detection by existing systems.

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Created

Date Created
  • 2021-05

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Cost-Effective Proximity Object Sensing

Description

The increasing presence and affordability of sensors provides the opportunity to make novel and creative designs for underserved markets like the legally blind. Here we explore how mathematical methods and

The increasing presence and affordability of sensors provides the opportunity to make novel and creative designs for underserved markets like the legally blind. Here we explore how mathematical methods and device coordination can be utilized to improve the functionality of inexpensive proximity sensing electronics in order to create designs that are versatile, durable, low cost, and simple. Devices utilizing various acoustic and electromagnetic wave frequencies like ultrasonic rangefinders, radars, Lidar rangefinders, webcams, and infrared rangefinders and the concepts of Sensor Fusion, Frequency Modulated Continuous Wave radar, and Phased Arrays were explored. The effects of various factors on the propagation of different wave signals was also investigated. The devices selected to be incorporated into designs were the HB100 DRO Radar Doppler Sensor (as an FMCW radar), HC-SR04 Ultrasonic Sensor, and Maxbotix Ultrasonic Rangefinder \u2014 EZ3. Three designs were ultimately developed and dubbed the "Rad-Son Fusion", the "Tri-Beam Scanner", and the "Dual-Receiver Ranger". The "Rad-Son Fusion" employs the Sensor Fusion of an FMCW radar and Ultrasonic sensor through a weighted average of the distance reading from the two sensors. The "Tri-Beam Scanner" utilizes a beam-forming Digital Phased Array of ultrasonic sensors to scan its surroundings. The "Dual-Receiver Ranger" uses the convolved result from to two modified HC-SR04 sensors to determine the time of flight and ultimately an object's distance. After conducting hardware experiments to determine the feasibility of each design, the "Dual-Receiver Ranger" was prototyped and tested to demonstrate the potential of the concept. The designs were later compared based on proposed requirements and possible improvements and challenges associated with the designs are discussed.

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Created

Date Created
  • 2016-05

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Categorizing and Discovering Social Bots

Description

Bots tamper with social media networks by artificially inflating the popularity of certain topics. In this paper, we define what a bot is, we detail different motivations for bots, we

Bots tamper with social media networks by artificially inflating the popularity of certain topics. In this paper, we define what a bot is, we detail different motivations for bots, we describe previous work in bot detection and observation, and then we perform bot detection of our own. For our bot detection, we are interested in bots on Twitter that tweet Arabic extremist-like phrases. A testing dataset is collected using the honeypot method, and five different heuristics are measured for their effectiveness in detecting bots. The model underperformed, but we have laid the ground-work for a vastly untapped focus on bot detection: extremist ideal diffusion through bots.

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Created

Date Created
  • 2015-05

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Real time detection of trace pharmaceuticals under a flow using flexible screen printed electrodes

Description

Acetaminophen, commonly found in Tylenol and other over the counter (OTC) pharmaceuticals, was electrochemically characterized on custom made, flexible, screen printed electrodes (SPEs) to serve as a model target pharmaceutical

Acetaminophen, commonly found in Tylenol and other over the counter (OTC) pharmaceuticals, was electrochemically characterized on custom made, flexible, screen printed electrodes (SPEs) to serve as a model target pharmaceutical found in flowing water lines. Carbon, silver/silver chloride, and insulator paste inks were printed onto polyethylene naphthalateolyester (PEN) using custom made stencils for a 4x1 array of 3-electrode electrochemical cells. Cyclic voltammetry was performed to find the electrical potential corresponding to the greatest current response and the experiments were conducted using amperometric current-time mode (AMP*i-t). The physical limitations of SPEs as well as the detection limitations of the target, such as pH and temperature were tested. A concentration gradient of the target was fitted with a linear curve (R2 0.99), and a lower limit of detection of 14.5 μM. It was also found that both pH and temperature affect the current produced by acetaminophen at a fixed concentration, and that the sensors can detect target in a continuous flow. A flow apparatus consisting of an inlet and effluent pipe served as the flow model into which a rolled up flexible electrode array was inserted. The broader goal of this research is to develop a highly sensitive electrode array on flexible substrates which can detect multiple targets simultaneously. Acetaminophen was chosen due to its electro-active properties and its presence in most public water lines in the United States.

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Created

Date Created
  • 2014-05

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Biology-based matched signal processing and physics-based modeling for improved detection

Description

Peptide microarrays have been used in molecular biology to profile immune responses and develop diagnostic tools. When the microarrays are printed with random peptide sequences, they can be used

Peptide microarrays have been used in molecular biology to profile immune responses and develop diagnostic tools. When the microarrays are printed with random peptide sequences, they can be used to identify antigen antibody binding patterns or immunosignatures. In this thesis, an advanced signal processing method is proposed to estimate epitope antigen subsequences as well as identify mimotope antigen subsequences that mimic the structure of epitopes from random-sequence peptide microarrays. The method first maps peptide sequences to linear expansions of highly-localized one-dimensional (1-D) time-varying signals and uses a time-frequency processing technique to detect recurring patterns in subsequences. This technique is matched to the aforementioned mapping scheme, and it allows for an inherent analysis on how substitutions in the subsequences can affect antibody binding strength. The performance of the proposed method is demonstrated by estimating epitopes and identifying potential mimotopes for eight monoclonal antibody samples.

The proposed mapping is generalized to express information on a protein's sequence location, structure and function onto a highly localized three-dimensional (3-D) Gaussian waveform. In particular, as analysis of protein homology has shown that incorporating different kinds of information into an alignment process can yield more robust alignment results, a pairwise protein structure alignment method is proposed based on a joint similarity measure of multiple mapped protein attributes. The 3-D mapping allocates protein properties into distinct regions in the time-frequency plane in order to simplify the alignment process by including all relevant information into a single, highly customizable waveform. Simulations demonstrate the improved performance of the joint alignment approach to infer relationships between proteins, and they provide information on mutations that cause changes to both the sequence and structure of a protein.

In addition to the biology-based signal processing methods, a statistical method is considered that uses a physics-based model to improve processing performance. In particular, an externally developed physics-based model for sea clutter is examined when detecting a low radar cross-section target in heavy sea clutter. This novel model includes a process that generates random dynamic sea clutter based on the governing physics of water gravity and capillary waves and a finite-difference time-domain electromagnetics simulation process based on Maxwell's equations propagating the radar signal. A subspace clutter suppression detector is applied to remove dominant clutter eigenmodes, and its improved performance over matched filtering is demonstrated using simulations.

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Created

Date Created
  • 2014

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Development of dose verification detectors towards improving proton therapy outcomes

Description

The challenge of radiation therapy is to maximize the dose to the tumor while simultaneously minimizing the dose elsewhere. Proton therapy is well suited to this challenge due to the

The challenge of radiation therapy is to maximize the dose to the tumor while simultaneously minimizing the dose elsewhere. Proton therapy is well suited to this challenge due to the way protons slow down in matter. As the proton slows down, the rate of energy loss per unit path length continuously increases leading to a sharp dose near the end of range. Unlike conventional radiation therapy, protons stop inside the patient, sparing tissue beyond the tumor. Proton therapy should be superior to existing modalities, however, because protons stop inside the patient, there is uncertainty in the range. “Range uncertainty” causes doctors to take a conservative approach in treatment planning, counteracting the advantages offered by proton therapy. Range uncertainty prevents proton therapy from reaching its full potential.

A new method of delivering protons, pencil-beam scanning (PBS), has become the new standard for treatment over the past few years. PBS utilizes magnets to raster scan a thin proton beam across the tumor at discrete locations and using many discrete pulses of typically 10 ms duration each. The depth is controlled by changing the beam energy. The discretization in time of the proton delivery allows for new methods of dose verification, however few devices have been developed which can meet the bandwidth demands of PBS.

In this work, two devices have been developed to perform dose verification and monitoring with an emphasis placed on fast response times. Measurements were performed at the Mayo Clinic. One detector addresses range uncertainty by measuring prompt gamma-rays emitted during treatment. The range detector presented in this work is able to measure the proton range in-vivo to within 1.1 mm at depths up to 11 cm in less than 500 ms and up to 7.5 cm in less than 200 ms. A beam fluence detector presented in this work is able to measure the position and shape of each beam spot. It is hoped that this work may lead to a further maturation of detection techniques in proton therapy, helping the treatment to reach its full potential to improve the outcomes in patients.

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Created

Date Created
  • 2019

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Detection, prediction and control of epileptic seizures

Description

From time immemorial, epilepsy has persisted to be one of the greatest impediments to human life for those stricken by it. As the fourth most common neurological disorder, epilepsy causes

From time immemorial, epilepsy has persisted to be one of the greatest impediments to human life for those stricken by it. As the fourth most common neurological disorder, epilepsy causes paroxysmal electrical discharges in the brain that manifest as seizures. Seizures have the effect of debilitating patients on a physical and psychological level. Although not lethal by themselves, they can bring about total disruption in consciousness which can, in hazardous conditions, lead to fatality. Roughly 1\% of the world population suffer from epilepsy and another 30 to 50 new cases per 100,000 increase the number of affected annually. Controlling seizures in epileptic patients has therefore become a great medical and, in recent years, engineering challenge.

In this study, the conditions of human seizures are recreated in an animal model of temporal lobe epilepsy. The rodents used in this study are chemically induced to become chronically epileptic. Their Electroencephalogram (EEG) data is then recorded and analyzed to detect and predict seizures; with the ultimate goal being the control and complete suppression of seizures.

Two methods, the maximum Lyapunov exponent and the Generalized Partial Directed Coherence (GPDC), are applied on EEG data to extract meaningful information. Their effectiveness have been reported in the literature for the purpose of prediction of seizures and seizure focus localization. This study integrates these measures, through some modifications, to robustly detect seizures and separately find precursors to them and in consequence provide stimulation to the epileptic brain of rats in order to suppress seizures. Additionally open-loop stimulation with biphasic currents of various pairs of sites in differing lengths of time have helped us create control efficacy maps. While GPDC tells us about the possible location of the focus, control efficacy maps tells us how effective stimulating a certain pair of sites will be.

The results from computations performed on the data are presented and the feasibility of the control problem is discussed. The results show a new reliable means of seizure detection even in the presence of artifacts in the data. The seizure precursors provide a means of prediction, in the order of tens of minutes, prior to seizures. Closed loop stimulation experiments based on these precursors and control efficacy maps on the epileptic animals show a maximum reduction of seizure frequency by 24.26\% in one animal and reduction of length of seizures by 51.77\% in another. Thus, through this study it was shown that the implementation of the methods can ameliorate seizures in an epileptic patient. It is expected that the new knowledge and experimental techniques will provide a guide for future research in an effort to ultimately eliminate seizures in epileptic patients.

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Created

Date Created
  • 2016

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3D rooftop detection and modeling using orthographic aerial images

Description

Detection of extruded features like rooftops and trees in aerial images automatically is a very active area of research. Elevated features identified from aerial imagery have potential applications in urban

Detection of extruded features like rooftops and trees in aerial images automatically is a very active area of research. Elevated features identified from aerial imagery have potential applications in urban planning, identifying cover in military training or flight training. Detection of such features using commonly available geospatial data like orthographic aerial imagery is very challenging because rooftop and tree textures are often camouflaged by similar looking features like roads, ground and grass. So, additonal data such as LIDAR, multispectral imagery and multiple viewpoints are exploited for more accurate detection. However, such data is often not available, or may be improperly registered or inacurate. In this thesis, we discuss a novel framework that only uses orthographic images for detection and modeling of rooftops. A segmentation scheme that initializes by assigning either foreground (rooftop) or background labels to certain pixels in the image based on shadows is proposed. Then it employs grabcut to assign one of those two labels to the rest of the pixels based on initial labeling. Parametric model fitting is performed on the segmented results in order to create a 3D scene and to facilitate roof-shape and height estimation. The framework can also benefit from additional geospatial data such as streetmaps and LIDAR, if available.

Contributors

Agent

Created

Date Created
  • 2013