704 research outputs found

    Chemical Analysis, Databasing, and Statistical Analysis of Smokeless Powders for Forensic Application

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    Smokeless powders are a set of energetic materials, known as low explosives, which are typically utilized for reloading ammunition. There are three types which differ in their primary energetic materials; where single base powders contain nitrocellulose as their primary energetic material, double and triple base powders contain nitroglycerin in addition to nitrocellulose, and triple base powders also contain nitroguanidine. Additional organic compounds, while not proprietary to specific manufacturers, are added to the powders in varied ratios during the manufacturing process to optimize the ballistic performance of the powders. The additional compounds function as stabilizers, plasticizers, flash suppressants, deterrents, and opacifiers. Of the three smokeless powder types, single and double base powders are commercially available, and have been heavily utilized in the manufacture of improvised explosive devices. Forensic smokeless powder samples are currently analyzed using multiple analytical techniques. Combined microscopic, macroscopic, and instrumental techniques are used to evaluate the sample, and the information obtained is used to generate a list of potential distributors. Gas chromatography – mass spectrometry (GC-MS) is arguably the most useful of the instrumental techniques since it distinguishes single and double base powders, and provides additional information about the relative ratios of all the analytes present in the sample. However, forensic smokeless powder samples are still limited to being classified as either single or double base powders, based on the absence or presence of nitroglycerin, respectively. In this work, the goal was to develop statistically valid classes, beyond the single and double base designations, based on multiple organic compounds which are commonly encountered in commercial smokeless powders. Several chemometric techniques were applied to smokeless powder GC-MS data for determination of the classes, and for assignment of test samples to these novel classes. The total ion spectrum (TIS), which is calculated from the GC-MS data for each sample, is obtained by summing the intensities for each mass-to-charge (m/z) ratio across the entire chromatographic profile. A TIS matrix comprising data for 726 smokeless powder samples was subject to agglomerative hierarchical cluster (AHC) analysis, and six distinct classes were identified. Within each class, a single m/z ratio had the highest intensity for the majority of samples, though the m/z ratio was not always unique to the specific class. Based on these observations, a new classification method known as the Intense Ion Rule (IIR) was developed and used for the assignment of test samples to the AHC designated classes. Discriminant models were developed for assignment of test samples to the AHC designated classes using k-Nearest Neighbors (kNN) and linear and quadratic discriminant analyses (LDA and QDA, respectively). Each of the models were optimized using leave-one-out (LOO) and leave-group-out (LGO) cross-validation, and the performance of the models was evaluated by calculating correct classification rates for assignment of the cross-validation (CV) samples to the AHC designated classes. The optimized models were utilized to assign test samples to the AHC designated classes. Overall, the QDA LGO model achieved the highest correct classification rates for assignment of both the CV samples and the test samples to the AHC designated classes. In forensic application, the goal of an explosives analyst is to ascertain the manufacturer of a smokeless powder sample. In addition, knowledge about the probability of a forensic sample being produced by a specific manufacturer could potentially decrease the time invested by an analyst during investigation by providing a shorter list of potential manufacturers. In this work, Bayes* Theorem and Bayesian Networks were investigated as an additional tool to be utilized in forensic casework. Bayesian Networks were generated and used to calculate posterior probabilities of a test sample belonging to specific manufacturers. The networks were designed to include manufacturer controlled powder characteristics such as shape, color, and dimension; as well as, the relative intensities of the class associated ions determined from cluster analysis. Samples were predicted to belong to a manufacturer based on the highest posterior probability. Overall percent correct rates were determined by calculating the percentage of correct predictions; that is, where the known and predicted manufacturer were the same. The initial overall percent correct rate was 66%. The dimensions of the smokeless powders were added to the network as average diameter and average length nodes. Addition of average diameter and length resulted in an overall prediction rate of 70%

    Design of software radio

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    Software Define Radio (SDR) has become a prevalent technology in wireless systems. In SDR some or all of the signal specific handling is implemented in software functions, while other functions like decimation, interpolation, digital up-conversion and digital down conversion are done on reprogrammable Digital Signal Processor or Field Programmable Gate Arrays.Twelve laboratory exercises have been designed to lead the student through the process of using the Universal Software Radio peripheral (USRP) hardware and GNU Radio open source software

    Accelerating MRI Data Acquisition Using Parallel Imaging and Compressed Sensing

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    Magnetic Resonance Imaging (MRI) scanners are one of important medical instruments, which can achieve more information of soft issues in human body than other medical instruments, such as Ultrasound, Computed Tomography (CT), Single Photon Emission Computed Tomography (SPECT), Positron Emission Tomography (PET), etc. But MRI\u27s scanning is slow for patience of doctors and patients. In this dissertation, the author proposes some methods of parallel imaging and compressed sensing to accelerate MRI data acquisition. Firstly, a method is proposed to improve the conventional GRAPPA using cross-sampled auto-calibration data. This method use cross-sampled auto-calibration data instead of the conventional parallel-sampled auto-calibration data to estimate the linear kernel model of the conventional GRAPPA. The simulations and experiments show that the cross-sampled GRAPPA can decrease the quantity of ACS lines and reduce the aliasing artifacts comparing to the conventional GRAPPA under same reduction factors. Secondly, a Hybrid encoding method is proposed to accelerate the MRI data acquisition using compressed sensing. This method completely changes the conventional Fourier encoding into Hybrid encoding, which combines the benefits of Fourier and Circulant random encoding, under 2D and 3D situation, through the proposed special hybrid encoding pulse sequences. The simulations and experiments illustrate that the images can be reconstructed by the proposed Hybrid encoding method to reserve more details and resolutions than the conventional Fourier encoding method. Thirdly, a pseudo 2D random sampling method is proposed by dynamically swapping the gradients of x and y axes on pulse sequences, which can be implemented physically as the convention 1D random sampling method. The simulations show that the proposed method can reserve more details than the convention 1D random sampling method. These methods can recover images to achieve better qualities under same situations than the conventional methods. Using these methods, the MRI data acquisitions can be accelerated comparing to the conventional methods

    Design of software radio

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    Software Define Radio (SDR) has become a prevalent technology in wireless systems. In SDR some or all of the signal specific handling is implemented in software functions, while other functions like decimation, interpolation, digital up-conversion and digital down conversion are done on reprogrammable Digital Signal Processor or Field Programmable Gate Arrays.Twelve laboratory exercises have been designed to lead the student through the process of using the Universal Software Radio peripheral (USRP) hardware and GNU Radio open source software

    Unified Theory for Biorthogonal Modulated Filter Banks

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    Modulated filter banks (MFBs) are practical signal decomposition tools for M -channel multirate systems. They combine high subfilter selectivity with efficient realization based on polyphase filters and block transforms. Consequently, the O(M 2 ) burden of computations in a general filter bank (FB) is reduced to O(M log2 M ) - the latter being a complexity order comparable with the FFT-like transforms.Often hiding from the plain sight, these versatile digital signal processing tools have important role in various professional and everyday life applications of information and communications technology, including audiovisual communications and media storage (e.g., audio codecs for low-energy music playback in portable devices, as well as communication waveform processing and channelization). The algorithmic efficiency implies low cost, small size, and extended battery life, bringing the devices close to our skins.The main objective of this thesis is to formulate a generalized and unified approach to the MFBs, which includes, in addition to the deep theoretical background behind these banks, both their design by using appropriate optimization techniques and efficient algorithmic realizations. The FBs discussed in this thesis are discrete-time time-frequency decomposition/reconstruction, or equivalently, analysis-synthesis systems, where the subfilters are generated through modulation from either a single or two prototype filters. The perfect reconstruction (PR) property is a particularly important characteristics of the MFBs and this is the core theme of this thesis. In the presented biorthogonal arbitrary-delay exponentially modulated filter bank (EMFB), the PR property can be maintained also for complex-valued signals.The EMFB concept is quite flexible, since it may respond to the various requirements given to a subband processing system: low-delay PR prototype design, subfilters having symmetric impulse responses, efficient algorithms, and the definition covers odd and even-stacked cosine-modulated FBs as special cases. Oversampling schemes for the subsignals prove out to be advantageous in subband processing problems requiring phase information about the localized frequency components. In addition, the MFBs have strong connections with the lapped transform (LT) theory, especially with the class of LTs grounded in parametric window functions.<br/

    N-bit ΔΣ optical transmitter for Digitized Radio Over Fiber Fronthaul Transmission

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    According to an estimate by the Global Technology, Media and Telecom (GTMT) team, global mobile data traffic grew 70% in 2012, which was nearly 12 times the size of the entire global Internet in 2000. In the future, the amount of data traffic will grow at a pace never seen before. Many recent forecasts project mobile data traffic to grow more than 24 between 2010 and 2015, and much higher beyond 2015. To catch up with the need and to remain competitive, network operators need to increase the broadband capability of their networks fast. This poses a big challenge for wireless communication system designers. Researchers have been working on innovative systems that will provide several Gbit/s over the air interface. Digitized radio over fiber (DROF) offers the capability to support various current and future wireless standards, independent of wireless system specifics if the carrier frequency falls within the passband of the ROF link. For example, the same ROF links should be able to transmit either time-division multiple access (TDMA), code-division multiple access (CDMA), or orthogonal frequency-division multiple access (OFDMA) radio signals without modification if their carrier frequencies are the same. Properly designed, the ROF link can also carry multiple RF carriers simultaneously in a subcarrier-multiplexing manner and support multi-standard radio. If the ROF link is properly designed, the portable device should be unaware of the existence of fiber in its radio path. Essentially, radio over fiber (ROF) is an analog communications system, and with DROF, the signal it carries is digital. Since nonlinear distortions, limited dynamic range, and cumulating noise are major concerns with the analog ROF backbone; alternative approaches are also investigated by researchers. One approach is to transmit a digitized RF signal over fiber from the base station to the radio access point. The falling cost of high-speed digital-to-analog converter (DAC) and analog-to-digital converter (ADC) converters has led to heightened recent interest in digitized radio over fiber links (DROF). In DROF, the I and Q baseband digital signals immediately after the digital signal processor are converted to optical and transported via the fiber. This means that the remote radio heads can be relatively simple too, consisting of DAC converters, up-converters, and amplifiers in the downlink direction and ADC converters, down-converters, and amplifiers in the uplink direction. Signal processing and modulation functions will take place in the central base station (CBS). Therefore, this architecture also satisfies the requirement that the RAP remains small and relatively simple. Such digital links are uses for current wireless systems (UMTS, WiMAX, and LTE) to connect digital base stations to remote radio heads. In order to use optical fiber to deliver radio signal to remote antennas, methods include the use of an intensity modulator to introduce an RF subcarrier onto the intensity of a CW laser source. This method cannot be extended to millimetre waves due to the limited bandwidth of available modulators. A novel transmitter architecture for the generation and distribution of GHz RF signals is described in this work. One of the principal objectives of this Master Thesis is to present the development of a digitized radio over fiber optical transmission systems under advanced modulation formats. We analyze the impact of chromatic dispersion and nonlinear microwave devices distortions considering one optical subcarrier carrying multiple RF signals
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