Matching Items (98)

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Time-Frequency Analysis of Peptide Microarray Data: Application to Brain Cancer Immunosignatures

Description

One of the gravest dangers facing cancer patients is an extended symptom-free lull between tumor initiation and the first diagnosis. Detection of tumors is critical for effective intervention. Using the

One of the gravest dangers facing cancer patients is an extended symptom-free lull between tumor initiation and the first diagnosis. Detection of tumors is critical for effective intervention. Using the body’s immune system to detect and amplify tumor-specific signals may enable detection of cancer using an inexpensive immunoassay. Immunosignatures are one such assay: they provide a map of antibody interactions with random-sequence peptides. They enable detection of disease-specific patterns using classic train/test methods. However, to date, very little effort has gone into extracting information from the sequence of peptides that interact with disease-specific antibodies. Because it is difficult to represent all possible antigen peptides in a microarray format, we chose to synthesize only 330,000 peptides on a single immunosignature microarray. The 330,000 random-sequence peptides on the microarray represent 83% of all tetramers and 27% of all pentamers, creating an unbiased but substantial gap in the coverage of total sequence space. We therefore chose to examine many relatively short motifs from these random-sequence peptides. Time-variant analysis of recurrent subsequences provided a means to dissect amino acid sequences from the peptides while simultaneously retaining the antibody–peptide binding intensities. We first used a simple experiment in which monoclonal antibodies with known linear epitopes were exposed to these random-sequence peptides, and their binding intensities were used to create our algorithm. We then demonstrated the performance of the proposed algorithm by examining immunosignatures from patients with Glioblastoma multiformae (GBM), an aggressive form of brain cancer. Eight different frameshift targets were identified from the random-sequence peptides using this technique. If immune-reactive antigens can be identified using a relatively simple immune assay, it might enable a diagnostic test with sufficient sensitivity to detect tumors in a clinically useful way.

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Date Created
  • 2015-06-18

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Electric Field Sensing

Description

This project examines the science of electric field sensing and completes experiments, gathering data to support its utility for various applications. The basic system consists of a transmitter, receiver, and

This project examines the science of electric field sensing and completes experiments, gathering data to support its utility for various applications. The basic system consists of a transmitter, receiver, and lock-in amplifier. The primary goal of the study was to determine if such a system could detect a human disturbance, due to the capacitance of a human body, and such a thesis was supported. Much different results were obtained when a person disturbed the electric field transmitted by the system than when other types of objects, such as chairs and electronic devices, were placed in the field. In fact, there was a distinct difference between persons of varied sizes as well. This thesis goes through the basic design of the system and the process of experimental design for determining the capabilities of such an electric field sensing system.

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Date Created
  • 2013-05

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Developing a Flexible Electric and Magnetic Field Imaging Blanket

Description

Recently, electric and magnetic field sensing has come of interest to the military for a variety of applications, including imaging circuitry and detecting explosive devices. This thesis describes research at

Recently, electric and magnetic field sensing has come of interest to the military for a variety of applications, including imaging circuitry and detecting explosive devices. This thesis describes research at the ASU's Flexible Electronics and Display Center (FEDC) towards the development of a flexible electric and magnetic field imaging blanket. D-dot sensors, which detect changes in electric flux, were chosen for electric field sensing, and a single D-dot sensor in combination with a lock-in amplifier was used to detect individuals passing through an oscillating electric field. This was then developed into a 1 x 16 array of D-dot sensors used to image the field generated by two parallel wires. After the fabrication of a two-dimensional array, it was discovered that commercial field effect transistors did not have a high enough off-resistance to isolate the sensor form the column line. Three alternative solutions were proposed. The first was a one-dimensional array combined with a mechanical stepper to move the array across the E-field pattern. The second was a 1 x 16 strip detector combined with the techniques of computed tomography to reconstruct the image of the field. Such techniques include filtered back projection and algebraic iterative reconstruction (AIR). Lastly, an array of D-dot sensors was fabricated on a flexible substrate, enabled by the high off-resistance of the thin film transistors produced by the FEDC. The research on magnetic field imaging began with a feasibility study of three different types of magnetic field sensors: planar spiral inductors, Hall effect sensors, and giant magnetoresistance (GMR). An experimental array of these sensors was designed and fabricated, and the sensors were used to image the fringe fields of a Helmholtz coil. Furthermore, combining the inductors with the other two types of sensors resulted in three-dimensional sensors. From these measurements, it was determined that planar spiral inductors and Hall effect sensors are best suited for future imaging arrays.

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Date Created
  • 2015-05

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DESIGN OF SIGNAL PROCESSING ALGORITHMS AND DEVELOPMENT OF A REAL-TIME SYSTEM FOR MAPPING AUDIO TO HAPTICS FOR COCHLEAR IMPLANT USERS

Description

In the field of electronic music, haptic feedback is a crucial feature of digital musical instruments (DMIs) because it gives the musician a more immersive experience. This feedback might come

In the field of electronic music, haptic feedback is a crucial feature of digital musical instruments (DMIs) because it gives the musician a more immersive experience. This feedback might come in the form of a wearable haptic device that vibrates in response to music. Such advancements in the electronic music field are applicable to the field of speech and hearing. More specifically, wearable haptic feedback devices can enhance the musical listening experience for people who use cochlear implant (CI) devices.
This Honors Thesis is a continuation of Prof. Lauren Hayes’s and Dr. Xin Luo’s research initiative, Haptic Electronic Audio Research into Musical Experience (HEAR-ME), which investigates how to enhance the musical listening experience for CI users using a wearable haptic system. The goals of this Honors Thesis are to adapt Prof. Hayes’s system code from the Max visual programming language into the C++ object-oriented programming language and to study the results of the developed C++ codes. This adaptation allows the system to operate in real-time and independently of a computer.
Towards these goals, two signal processing algorithms were developed and programmed in C++. The first algorithm is a thresholding method, which outputs a pulse of a predefined width when the input signal falls below some threshold in amplitude. The second algorithm is a root-mean-square (RMS) method, which outputs a pulse-width modulation signal with a fixed period and with a duty cycle dependent on the RMS of the input signal. The thresholding method was found to work best with speech, and the RMS method was found to work best with music. Future work entails the design of adaptive signal processing algorithms to allow the system to work more effectively on speech in a noisy environment and to emphasize a variety of elements in music.

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Date Created
  • 2019-12

Structural Health Monitoring: Acoustic Emissions

Description

Non-Destructive Testing (NDT) is integral to preserving the structural health of materials. Techniques that fall under the NDT category are able to evaluate integrity and condition of a material

Non-Destructive Testing (NDT) is integral to preserving the structural health of materials. Techniques that fall under the NDT category are able to evaluate integrity and condition of a material without permanently altering any property of the material. Additionally, they can typically be used while the material is in active use instead of needing downtime for inspection.
The two general categories of structural health monitoring (SHM) systems include passive and active monitoring. Active SHM systems utilize an input of energy to monitor the health of a structure (such as sound waves in ultrasonics), while passive systems do not. As such, passive SHM tends to be more desirable. A system could be permanently fixed to a critical location, passively accepting signals until it records a damage event, then localize and characterize the damage. This is the goal of acoustic emissions testing.
When certain types of damage occur, such as matrix cracking or delamination in composites, the corresponding release of energy creates sound waves, or acoustic emissions, that propagate through the material. Audio sensors fixed to the surface can pick up data from both the time and frequency domains of the wave. With proper data analysis, a time of arrival (TOA) can be calculated for each sensor allowing for localization of the damage event. The frequency data can be used to characterize the damage.
In traditional acoustic emissions testing, the TOA combined with wave velocity and information about signal attenuation in the material is used to localize events. However, in instances of complex geometries or anisotropic materials (such as carbon fibre composites), velocity and attenuation can vary wildly based on the direction of interest. In these cases, localization can be based off of the time of arrival distances for each sensor pair. This technique is called Delta T mapping, and is the main focus of this study.

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Created

Date Created
  • 2019-05

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RNS-Based NTT Polynomial Multiplier for Lattice-Based Cryptography

Description

Lattice-based Cryptography is an up and coming field of cryptography that utilizes the difficulty of lattice problems to design lattice-based cryptosystems that are resistant to quantum attacks and applicable to

Lattice-based Cryptography is an up and coming field of cryptography that utilizes the difficulty of lattice problems to design lattice-based cryptosystems that are resistant to quantum attacks and applicable to Fully Homomorphic Encryption schemes (FHE). In this thesis, the parallelization of the Residue Number System (RNS) and algorithmic efficiency of the Number Theoretic Transform (NTT) are combined to tackle the most significant bottleneck of polynomial ring multiplication with the hardware design of an optimized RNS-based NTT polynomial multiplier. The design utilizes Negative Wrapped Convolution, the NTT, RNS Montgomery reduction with Bajard and Shenoy extensions, and optimized modular 32-bit channel arithmetic for nine RNS channels to accomplish an RNS polynomial multiplication. In addition to a full software implementation of the whole system, a pipelined and optimized RNS-based NTT unit with 4 RNS butterflies is implemented on the Xilinx Artix-7 FPGA(xc7a200tlffg1156-2L) for size and delay estimates. The hardware implementation achieves an operating frequency of 47.043 MHz and utilizes 13239 LUT's, 4010 FF's, and 330 DSP blocks, allowing for multiple simultaneously operating NTT units depending on FGPA size constraints.

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Date Created
  • 2020

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Robust Target Detection Methods: Performance Analysis and Experimental Validation

Description

Constant false alarm rate is one of the essential algorithms in a RADAR detection system. It allows the RADAR system to dynamically set thresholds based on the data power level

Constant false alarm rate is one of the essential algorithms in a RADAR detection system. It allows the RADAR system to dynamically set thresholds based on the data power level to distinguish targets with interfering noise and clutters.

To have a better acknowledgment of constant false alarm rate approaches performance, three clutter models, Gamma, Weibull, and Log-normal, have been introduced to evaluate the detection's capability of each constant false alarm rate algorithm.

The order statistical constant false alarm rate approach outperforms other conventional constant false alarm rate methods, especially in clutter evolved environments. However, this method requires high power consumption due to repeat sorting.
In the automotive RADAR system, the computational complexity of algorithms is essential because this system is in real-time. Therefore, the algorithms must be fast and efficient to ensure low power consumption and processing time.

The reduced computational complexity implementations of cell-averaging and order statistic constant false alarm rate were explored. Their big O and processing time has been reduced.

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Created

Date Created
  • 2020

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Radiation detection and imaging: neutrons and electric fields

Description

The work presented in this manuscript has the overarching theme of radiation. The two forms of radiation of interest are neutrons, i.e. nuclear, and electric fields. The ability

The work presented in this manuscript has the overarching theme of radiation. The two forms of radiation of interest are neutrons, i.e. nuclear, and electric fields. The ability to detect such forms of radiation have significant security implications that could also be extended to very practical industrial applications. The goal is therefore to detect, and even image, such radiation sources.

The method to do so revolved around the concept of building large-area sensor arrays. By covering a large area, we can increase the probability of detection and gather more data to build a more complete and clearer view of the environment. Large-area circuitry can be achieved cost-effectively by leveraging the thin-film transistor process of the display industry. With production of displays increasing with the explosion of mobile devices and continued growth in sales of flat panel monitors and television, the cost to build a unit continues to decrease.

Using a thin-film process also allows for flexible electronics, which could be taken advantage of in-house at the Flexible Electronics and Display Center. Flexible electronics implies new form factors and applications that would not otherwise be possible with their single crystal counterparts. To be able to effectively use thin-film technology, novel ways of overcoming the drawbacks of the thin-film process, namely the lower performance scale.

The two deliverable devices that underwent development are a preamplifier used in an active pixel sensor for neutron detection and a passive electric field imaging array. This thesis will cover the theory and process behind realizing these devices.

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Created

Date Created
  • 2015

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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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Date Created
  • 2014

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New passive methodology for power cable monitoring and fault location

Description

The utilization of power cables is increasing with the development of renewable energy and the maintenance replacement of old overhead power lines. Therefore, effective monitoring and accurate fault location for

The utilization of power cables is increasing with the development of renewable energy and the maintenance replacement of old overhead power lines. Therefore, effective monitoring and accurate fault location for power cables are very important for the sake of a stable power supply.

The recent technologies for power cable diagnosis and temperature monitoring system are described including their intrinsic limitations for cable health assessment. Power cable fault location methods are reviewed with two main categories: off-line and on-line data based methods.

As a diagnostic and fault location approach, a new passive methodology is introduced. This methodology is based on analyzing the resonant frequencies of the transfer function between the input and output of the power cable system. The equivalent pi model is applied to the resonant frequency calculation for the selected underground power cable transmission system.

The characteristics of the resonant frequencies are studied by analytical derivations and PSCAD simulations. It is found that the variation of load magnitudes and change of positive power factors (i.e., inductive loads) do not affect resonant frequencies significantly, but there is considerable movement of resonant frequencies under change of negative power factors (i.e., capacitive loads).

Power cable fault conditions introduce new resonant frequencies in accordance with fault positions. Similar behaviors of the resonant frequencies are shown in a transformer (TR) connected power cable system with frequency shifts caused by the TR impedance.

The resonant frequencies can be extracted by frequency analysis of power signals and the inherent noise in these signals plays a key role to measure the resonant frequencies. Window functions provide an effective tool for improving resonant frequency discernment. The frequency analysis is implemented on noise laden PSCAD simulation signals and it reveals identical resonant frequency characteristics with theoretical studies.

Finally, the noise levels of real voltage and current signals, which are acquired from an operating power plant, are estimated and the resonant frequencies are extracted by applying window functions, and these results prove that the resonant frequency can be used as an assessment for the internal changes in power cable parameters such as defects and faults.

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Date Created
  • 2015