Browsing by Author "Ha, Dong S."
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- AI-ML Powered Pig Behavior Classification and Body Weight PredictionBharadwaj, Sanjana Manjunath (Virginia Tech, 2024-05-31)Precision livestock farming technologies have been widely researched over the last decade. These technologies help in monitoring animal health and welfare parameters in a continuous, automated fashion. Under this umbrella of precision livestock farming, this study focuses on activity classification and body weight prediction in pigs. Activity monitoring is essential for understanding the health and growth of pigs. To automate this task effectively, we propose efficient and accurate sensor-based deep learning (DL) solutions. Among these, the 2D Residual Networks emerged as the best performing model, achieving an accuracy of 95.6%. This accuracy was 15.6% higher than that of other machine learning approaches. Additionally, accurate pig weight estimation is crucial for pork production, as it provides valuable insights into growth rates, disease prevalence, and overall health. Traditional manual methods of estimating pig weights are time-consuming and labor-intensive. To address this issue, we propose a novel approach that utilizes deep learning techniques on depth images for weight prediction. Through a custom image preprocessing pipeline, we train DL models to extract meaningful information from depth images for weight prediction. Our findings show that XceptionNet gives promising results, with a mean absolute error of 2.82 kg and a mean absolute percentage error of 7.42%. In comparison, the best performing statistical model, support vector machine, achieved a mean absolute error of 4.51 kg mean absolute percentage error of 15.56%.
- All Digital FM DemodulatorNair, Kartik (Virginia Tech, 2019-09-20)The proposed demodulator is an all-digital implementation of a FM demodulator. The proposed design intends to implement a FM demodulator for high-speed applications, which makes the requirements for analog components minimal. The proposed circuit is an all-digital quadrature demodulator, where the individual components have been implemented without using any multipliers. The topology uses a Pulse width modulation (PWM) block to avoid the need for a DAC. The Xilinx virtex-7 FPGA has been used as the reference device for the work. The circuit is validated through behavioral simulations and the results conclude the proposed circuit demodulates the targeted FM channel and provides the spectrum information for the targeted FM channel
- Analysis and Design of a DCM SEPIC PFC with Adjustable Output VoltageChen, Rui (Virginia Tech, 2015-03-31)Power Factor Correction rectifiers are widely adopted as the first stage in most grid-tied power conversion systems. Among all PFC converts for single phase system, Boost PFC is the most popular one due to simplicity of structure and high performance. Although the efficiency of Boost PFC keeps increasing with the evolution of semiconductor technology, the intrinsic feature of high output voltage may result cumbersome system structure with multiple power conversion stages and even diminished system efficiency. This disadvantage is aggravated especially in systems where resonant converters are selected as second stage. Especially for domestic induction cooker application, step-down PFC with wide range output regulation capability would be a reasonable solution, Conventional induction cooker is composed by input filter, diode-bridge rectifier, and full bridge or half bridge series resonant circuit (SRC). High frequency magnetic field is induced through the switching action to heat the pan. The power level is usually controlled through pulse frequency modulation (PFM). In such configuration, first, a bulky input differential filter is required to filter out the high frequency operating current in SRC. Second, as the output power decreases, the operating point of SRC is moved away from the optimum point, which would result large amount circulating energy. Third, when the pan is made of well conducting and non-ferromagnetic material such as aluminum, due to the heating resistance become much smaller and peak output voltage of the switching bridge equals to the peak voltage of the grid, operating the SRC at the series resonant frequency can result excessive current flowing through the switch and the heating coil. Thus for pan with smaller heating resistance, even at maximum power, the operating frequency is pushed further away from the series resonant point, which also results efficiency loss. To address these potential issues, a PFC circuit features continuous conducting input current, high power factor, step-down capability and wide range output regulation would be preferred. The Analysis and design work is present in this article for a non-isolated hard switching DCM SEPIC PFC. Due to DCM operation of SPEIC converter, wide adjustable step-down output voltage, continuous conduction of input current and elimination of reverse recovery loss can be achieved at same time. The thesis begins with circuit operation analysis for both DC-DC and PFC operation. Based on averaged switching model, small signal model and corresponding transfer functions are derived. Especially, the impact from small intermediate capacitor on steady state value are discussed. With the concept of ripple steering, theoretic analysis is applied to SEPIC converter with two coupled inductors. The results indicate if the coupling coefficient is well designed, the equivalent input inductance can be multiple times larger than the self-inductance. Because of this, while maintaining input current ripple same, the two inductors of SEPIC can be implemented with two smaller coupled inductors. Thus both the total volume of inductors and the total number of windings can be reduced, and the power density and efficiency can be improved. Based on magnetic reluctance model, a corresponding winding scheme to control the coupling coefficient between two coupled inductors is analyzed. Also the impact of coupled inductors on the small signal transfer function is discussed. For the voltage follower control scheme of DCM PFC, single loop controller and notch filter design are discussed. With properly designed notch filter or the PR controller in another word, the closed loop bandwidth can be increased; simple PI controller is sufficient to achieve high power factor; THD of the input current can be greatly reduced. Finally, to validate the analysis and design procedure, a 1 kW prototype is built. With 120 Vrms AC input, 60V to 100V output, experimental results demonstrate unity power factor, wide output voltage regulation can be achieved within a single stage, and the 1 kW efficiency is around 93%.
- The Application of Doppler LIDAR Technology for Rail Inspection and Track Geometry AssessmentTaheriandani, Masood (Virginia Tech, 2016-05-17)The ability of a Doppler LIDAR (Light Detection and Ranging) system to measure the speed of a moving rail vehicle in a non-contacting manner is extended to capture the lateral and vertical irregularities of the track itself and to evaluate the rail track quality. Using two pairs of lenses to capture speed signals from both rails individually, the track speed, curvature, and lateral and vertical geometry variations on each side are determined. LIDAR lenses are installed with a slight forward angle to generate velocity signals that contain two components: 1) the left and right track speeds, and 2) any lateral and/or vertical speed caused by track motion and/or spatial irregularities. The LIDAR system collects and outputs the track information in time domain. Separating each speed component (forward, vertical, and lateral) is possible due to the inherent separation of each phenomenon with respect to its spatial/temporal frequencies and related bandwidths. For the measurements to be beneficial in practice, the LIDAR data must be spatially located along the track. A data-mapping algorithm is then simultaneously developed to spatially match the LIDAR track geometry measurements with reference spatial data, accurately locating the measurements along the track and eliminating the need for a Global Positioning System (GPS). A laboratory-grade LIDAR system with four Doppler channels, developed at the Railway Technologies Laboratory (RTL) of Virginia Tech, is body-mounted and tested onboard a geometry measurement railcar. The test results indicate a close match between the LIDAR measurements and those made with existing sensors onboard the railcar. The field-testing conducted during this study indicates that LIDAR sensors could provide a reliable, non-contact track-monitoring instrument for field use, in various weather and track conditions, potentially in a semi-autonomous or autonomous manner. A length-based track quality index (TQI) is established to quantify the track geometry condition based on the geometry data collected by the LIDAR sensors. A phenomenological rail deterioration model is developed to predict the future degradation of geometry quality over the short track segments. The introduced LIDAR's TQI is considered as the condition-parameter, and an internal variable is assumed to govern the rail geometry degradation through a deterioration rule. The method includes the historical data, current track conditions collected by the LIDAR system, and traffic data to calculate the track deterioration condition and identify the geometry defects. In addition to rail geometry inspection, a LIDAR system can potentially be used to monitor the rail surface structure and integrity. This is possible due to the fact that the Doppler shift imposed on the laser radiation reflected from a moving surface has the Doppler bandwidth broadened in proportion to the height and width of the surface features. Two LIDAR-based rail surface measures are introduced based on LIDAR measurements to identify different rail surface conditions and materials.
- Application of Multifunctional Doppler LIDAR for Non-contact Track Speed, Distance, and Curvature AssessmentMunoz, Joshua (Virginia Tech, 2015-12-08)The primary focus of this research is evaluation of feasibility, applicability, and accuracy of Doppler Light Detection And Ranging (LIDAR) sensors as non-contact means for measuring track speed, distance traveled, and curvature. Speed histories, currently measured with a rotary, wheel-mounted encoder, serve a number of useful purposes, one significant use involving derailment investigations. Distance calculation provides a spatial reference system for operators to locate track sections of interest. Railroad curves, using an IMU to measure curvature, are monitored to maintain track infrastructure within regulations. Speed measured with high accuracy leads to high-fidelity distance and curvature data through utilization of processor clock rate and left-and right-rail speed differentials during curve navigation, respectively. Wheel-mounted encoders, or tachometers, provide a relatively low-resolution speed profile, exhibit increased noise with increasing speed, and are subject to the inertial behavior of the rail car which affects output data. The IMU used to measure curvature is dependent on acceleration and yaw rate sensitivity and experiences difficulty in low-speed conditions. Preliminary system tests onboard a 'Hy-Rail' utility vehicle capable of traveling on rail show speed capture is possible using the rails as the reference moving target and furthermore, obtaining speed profiles from both rails allows for the calculation of speed differentials in curves to estimate degrees curvature. Ground truth distance calibration and curve measurement were also carried out. Distance calibration involved placement of spatial landmarks detected by a sensor to synchronize distance measurements as a pre-processing procedure. Curvature ground truth measurements provided a reference system to confirm measurement results and observe alignment variation throughout a curve. Primary testing occurred onboard a track geometry rail car, measuring rail speed over substantial mileage in various weather conditions, providing high-accuracy data to further calculate distance and curvature along the test routes. Tests results indicate the LIDAR system measures speed at higher accuracy than the encoder, absent of noise influenced by increasing speed. Distance calculation is also high in accuracy, results showing high correlation with encoder and ground truth data. Finally, curvature calculation using speed data is shown to have good correlation with IMU measurements and a resolution capable of revealing localized track alignments. Further investigations involve a curve measurement algorithm and speed calibration method independent from external reference systems, namely encoder and ground truth data. The speed calibration results show a high correlation with speed data from the track geometry vehicle. It is recommended that the study be extended to provide assessment of the LIDAR's sensitivity to car body motion in order to better isolate the embedded behavior in the speed and curvature profiles. Furthermore, in the interest of progressing the system toward a commercially viable unit, methods for self-calibration and pre-processing to allow for fully independent operation is highly encouraged.
- Battery Cell Monitoring UnitDanson, Eric C. (Virginia Tech, 2023-04-12)The proposed cell monitoring unit for sensing voltage, current, and temperature in a 12-cell 18650 lithium-ion battery module aims to be low-power, serving as the core of an energy-efficient battery management system and facilitating battery management functions with cell data. Notable features include a switchable voltage divider, a single op-amp differential amplifier and level shifter, and a high-precision composite amplifier. The proposed circuit is implemented on a printed circuit board. Measurement results show that the highest power dissipation under continuous operation is from the current sensing circuit at 6.03 mW under a 4 A string current, followed by the voltage sensing at 2.52 mW for the top cell and the temperature sensing at 34.9 μW. The measured power figures include the power dissipation from the battery cells in addition to the cell monitoring unit. The maximum output error is 68 mV for cell voltages up to 44.4 V, 36 mA for current up to 4 A, and 0.37 ◦C for temperature up to 73 ◦C.
- Biological Agent Sensing Integrated Circuit (BASIC): A New Complementary Metal-oxide-semiconductor (CMOS) Magnetic Biosensor SystemZheng, Yi (Virginia Tech, 2014-06-10)Fast and accurate diagnosis is always in demand by modern medical professionals and in the area of national defense. At present, limitations of testing speed, sample conditions, and levels of precision exist under current technologies, which are usually slow and involve testing the specimen under laboratory conditions. Typically, these methods also involve several biochemical processing steps and subsequent detection of low energy luminescence or electrical changes, all of which reduce the speed of the test as well as limit the precision. In order to solve these problems and improve the sensing performance, this project proposes an innovative CMOS magnetic biological sensor system for rapidly testing the presence of potential pathogens and bioterrorism agents (zoonotic microorganisms) both in specimens and especially in the environment. The sensor uses an electromagnetic detection mechanism to measure changes in the number of microorganisms--tagged by iron nanoparticles--that are placed on the surface of an integrated circuit (IC) chip. Measured magnetic effects are transformed into electronic signals that count the number and type of organisms present. This biosensor introduces a novel design of a conical-shaped inductor, which achieves ultra-accuracy of sensing biological pathogens. The whole system is integrated on a single chip based on the fabrication process of IBM 180 nm (CMOS_IBM_7RF), which makes the sensor small-sized, portable, high speed, and low cost. The results of designing, simulating, and fabricating the sensor are reported in this dissertation.
- CCM Totem Pole Bridgeless PFC with Ultra Fast IGBTZhou, Bo (Virginia Tech, 2014-12-09)The totem pole PFC suffers from the Mosfet body diode reverse recovery issue which limits this topology adopted in the CCM high power condition. As the ultra-fast IGBT which is capable of providing 100 kHz switching frequency is available in the market, it is possible to apply the totem pole PFC in CCM high power condition. The thesis provides a method by implementing the ultra-fast IGBT and SiC diode to replace the MOSFET in this topology. To verify the method, a universal CCM totem pole PFC is designed and tested. The design adopts the ADP1048 programmable digital PFC controller by adding external logic gate for totem-pole PFC. ADP1048 greatly simplifies the design process and satisfies the design requirements. The experiment results verify that the totem-pole PFC can be applied into CCM high power condition by using the method. The DC output voltage is well regulated. The power factor is higher than 0.98 when the load is above 400W. The measured efficiency can achieve up to 96.8% at low line and 98.2% at high line condition with switching frequency 80 kHz.
- Characterization and Application of Wide-Band-Gap Devices for High Frequency Power ConversionLiu, Zhengyang (Virginia Tech, 2017-06-08)Advanced power semiconductor devices have consistently proven to be a major force in pushing the progressive development of power conversion technology. The emerging wide-band-gap (WBG) material based power semiconductor devices are considered as gaming changing devices which can exceed the limit of silicon (Si) and be used to pursue groundbreaking high-frequency, high-efficiency, and high-power-density power conversion. The switching performance of cascode GaN HEMT is studied at first. An accurate behavior-level simulation model is developed with comprehensive consideration of the impacts of parasitics. Then based on the simulation model, detailed loss breakdown and loss mechanism analysis are studied. The cascode GaN HEMT has high turn-on loss due to the reverse recovery charge and junction capacitor charge, and the common source inductance (CSI) of the package; while the turn-off loss is extremely small attributing to unique current source turn off mechanism of the cascode structure. With this unique feature, the critical conduction mode (CRM) soft switching technique is applied to reduce the dominant turn on loss and significantly increase converter efficiency. The switching frequency is successfully pushed to 5MHz while maintaining high efficiency and good thermal performance. Traditional packaging method is becoming a bottle neck to fully utilize the advantages of GaN HEMT. So an investigation of the package influence on the cascode GaN HEMT is also conducted. Several critical parasitic inductance are identified, which cause high turn on loss and high parasitic ringing that may lead to device failure. To solve the issue, the stack-die package is proposed to eliminate all critical parasitic inductance, and as a result, reducing turn on loss by half and avoiding potential failure mode of the cascode GaN device effectively. Utilizing soft switching and enhanced packaging, a GaN-based MHz totem-pole PFC rectifier is demonstrated with 99% peak efficiency and 700 W/in3 power density. The switching frequency of the PFC is more than ten times higher than the state-of-the-art industry product while it achieves best possible efficiency and power density. Integrated power module and integrated PCB winding coupled inductor are all studied and applied in this PFC. Furthermore, the technology of soft switching totem-pole PFC is extended to a bidirectional rectifier/inverter design. By using SiC MOSFETs, both operating voltage and power are dramatically increased so that it is successfully applied into a bidirectional on-board charger (OBC) which achieves significantly improved efficiency and power density comparing to the best of industrial practice. In addition, a novel 2-stage system architecture and control strategy are proposed and demonstrated in the OBC system. As a continued extension, the critical mode based soft switching rectifier/inverter technology is applied to three-phase AC/DC converter. The inherent drawback of critical mode due to variable frequency operation is overcome by the proposed new modulation method with the idea of frequency synchronization. It is the first time that a critical mode based modulation is demonstrated in the most conventional three phase H-bridge AC/DC converter, and with 99% plus efficiency at above 300 kHz switching frequency.
- Computational Modeling for Differential Analysis of RNA-seq and Methylation dataWang, Xiao (Virginia Tech, 2016-08-16)Computational systems biology is an inter-disciplinary field that aims to develop computational approaches for a system-level understanding of biological systems. Advances in high-throughput biotechnology offer broad scope and high resolution in multiple disciplines. However, it is still a major challenge to extract biologically meaningful information from the overwhelming amount of data generated from biological systems. Effective computational approaches are of pressing need to reveal the functional components. Thus, in this dissertation work, we aim to develop computational approaches for differential analysis of RNA-seq and methylation data to detect aberrant events associated with cancers. We develop a novel Bayesian approach, BayesIso, to identify differentially expressed isoforms from RNA-seq data. BayesIso features a joint model of the variability of RNA-seq data and the differential state of isoforms. BayesIso can not only account for the variability of RNA-seq data but also combines the differential states of isoforms as hidden variables for differential analysis. The differential states of isoforms are estimated jointly with other model parameters through a sampling process, providing an improved performance in detecting isoforms of less differentially expressed. We propose to develop a novel probabilistic approach, DM-BLD, in a Bayesian framework to identify differentially methylated genes. The DM-BLD approach features a hierarchical model, built upon Markov random field models, to capture both the local dependency of measured loci and the dependency of methylation change. A Gibbs sampling procedure is designed to estimate the posterior distribution of the methylation change of CpG sites. Then, the differential methylation score of a gene is calculated from the estimated methylation changes of the involved CpG sites and the significance of genes is assessed by permutation-based statistical tests. We have demonstrated the advantage of the proposed Bayesian approaches over conventional methods for differential analysis of RNA-seq data and methylation data. The joint estimation of the posterior distributions of the variables and model parameters using sampling procedure has demonstrated the advantage in detecting isoforms or methylated genes of less differential. The applications to breast cancer data shed light on understanding the molecular mechanisms underlying breast cancer recurrence, aiming to identify new molecular targets for breast cancer treatment.
- Concurrent detection of transient faults in microprocessorsKhan, Mohammad Ziaullah (Virginia Polytechnic Institute and State University, 1989)A large number of errors in digital systems are due to the presence of transient faults. This is especially true of microprocessor-based systems working in a radiation environment that experience transient faults due to single event upsets. These upsets cause a temporary change in the state of the system without any permanent damage. Because of their random and non-recurring nature, transient faults are difficult to detect and isolate, hence they become a source of major concern, especially in critical real-time application areas. Concurrent detection of these errors is necessary for real-time operation. Most existing fault tolerance schemes either use redundancy to mask effects of transient faults or monitor the system for abnormal operations and then perform recovery operation. Although very effective, redundancy schemes incur substantial overhead that makes them unsuitable for small systems. Most monitoring schemes, on the other hand, only detect control flow errors. A new approach called Concurrent Processor Monitoring for on-line detection of transient faults is proposed that attempts to achieve high error coverage with small error detection latency. The concept of the execution profile of an instruction is defined and is used for detecting control flow and execution errors. To implement this scheme, a watchdog processor is designed for monitoring operation of the main processor. The effectiveness of this technique is demonstrated through computer simulations.
- Control and Modeling of High-Frequency Voltage Regulator Modules for Microprocessor ApplicationLi, Virginia (Virginia Tech, 2021-06-11)The future voltage regulator module (VRM) challenges of high bandwidth control with fast transient response, high current output, simple implementation, and efficient 48V solution are tackled in this dissertation. With the push for control bandwidth to meet design specifications for microprocessor VRM with larger and faster load transients, control can be saturated and lost for a significant period of time during transient. During this time, undesirable transient responses such as large undershoot and ringback occurs. Due to the loss of control, the existing tools to study the dynamic behavior of the system, such as small signal model, are insufficient to analyze the behavior of the system during this time. In order to have a better understanding of the system dynamic performance, the operation the VRM is analyzed in the state-plane for a clear visual understanding of the steady-state and transient behaviors. Using the state-plane, a simplified state-plane trajectory control is proposed for constant on-time (COT) control to achieve the best transient possible for applications with adaptive voltage positioning (AVP). When the COT control is lost during a load step-up transient, the state-plane trajectory control will extend on-time to provide the a near optimal transient response. By observing the COT control law in the state-plane, a simplified state-plane trajectory control with analog implementation is proposed to achieve the best transient possible with smooth transitions in and out of the steady-state COT control. The concept of the simplified state-plane trajectory control is then extended to multiphase COT. For multiphase operation, additional operating behavior, such as phase overlapping during transient and interleaving during steady-state, need to be taken into consideration to design the desired state-plane trajectory control. A simple state-plane trajectory control with improved Ton extension is proposed and verified using multiphase COT control. After tackling the state-plane trajectory control for current mode COT, the idea is then extended to V2 COT. V2 COT is a more advanced current mode control which requires a more advanced state-plane trajectory control to COT. By calculating the intersection of the extended on-stage trajectory during transient and the ideal off trajectory in the form of a current limiting wall, a near optimal transient response can be achieved. For V2 COT with state-plane trajectory control, implementations using inductor vs. capacitor current, effect of component tolerance, and effect of IC delay are studied. The proposed state-plane trajectory control is then extended to enhanced V2 COT. Aside from tackling existing VRM challenges, the future datacenter 48V VRM challenge of a high efficiency, high power density solution to meet the VRM specifications is studied. The sigma converter is proposed for the 48V VRM solution due to exhibition of high efficiency and high-power density from hardware evaluation. An accurate model for the sigma converter is derived using the new modeling approach of modularizing the small signal components. Using the proposed model, the sigma converter is shown to naturally have very low output impedance, making the sigma converter suitable for microprocessor applications. The sigma converter is designed and optimized to achieve AVP and very fast transient response using both voltage-mode and current-mode controls.
- Coupled Adjoint-based Sensitivity Analysis using a FSI Method in Time Spectral FormKim, Hyunsoon (Virginia Tech, 2019-09-26)A time spectral and coupled adjoint based sensitivity analysis of rotor blade is carried out in this study. The time spectral method is an efficient technique to solve unsteady periodic problems by transforming unsteady equation of motion to a steady state one. Due to the availability of the governing equations in the steady form, the steady form of the adjoint equations can be applied for the sensitivity analysis of the coupled fluid-structure system. An expensive computational time and memory requirement for the unsteady adjoint sensitivity analysis is thus avoided. A coupled analysis of fluid, structural, and flight dynamics is carried out through a CFD/CSD/CA coupling procedure that combines FSI analysis with enforced trim condition. Coupled sensitivity analysis results and their validations are presented and compared with aerodynamics only sensitivity analysis results. The fluid-structure coupled adjoint based sensitivity analysis will be applied to the shape optimization of a rotor blade in the future work. Minimization of required power is the objective of the optimization problem with constraints on thrust and drag of the rotor. The bump functions are considered as the design variables. Rotor blade shape changes are obtained by using the bump function on the surface of the airfoil sections along the span.
- A Deep Learning Approach to Side-Channel Analysis of Cryptographic HardwareRamezanpour, Keyvan (Virginia Tech, 2020-09-08)With increased growth of the Internet of Things (IoT) and physical exposure of devices to adversaries, a class of physical attacks called side-channel analysis (SCA) has emerged which compromises the security of systems. While security claims of cryptographic algorithms are based on the complexity of classical cryptanalysis attacks, they exclude information leakage by implementations on hardware platforms. Recent standardization processes require assessment of hardware security against SCA. In this dissertation, we study SCA based on deep learning techniques (DL-SCA) as a universal analysis toolbox for assessing the leakage of secret information by hardware implementations. We demonstrate that DL-SCA techniques provide a trade-off between the amount of prior knowledge of a hardware implementation and the amount of measurements required to identify the secret key. A DL-SCA based on supervised learning requires a training set, including information about the details of the hardware implementation, for a successful attack. Supervised learning has been widely used in power analysis (PA) to recover the secret key with a limited size of measurements. We demonstrate a similar trend in fault injection analysis (FIA) by introducing fault intensity map analysis with a neural network key distinguisher (FIMA-NN). We use dynamic timing simulations on an ASIC implementation of AES to develop a statistical model for biased fault injection. We employ the model to train a convolutional neural network (CNN) key distinguisher that achieves a superior efficiency, nearly $10times$, compared to classical FIA techniques. When a priori knowledge of the details of hardware implementations is limited, we propose DL-SCA techniques based on unsupervised learning, called SCAUL, to extract the secret information from measurements without requiring a training set. We further demonstrate the application of reinforcement learning by introducing the SCARL attack, to estimate a proper model for the leakage of secret data in a self-supervised approach. We demonstrate the success of SCAUL and SCARL attacks using power measurements from FPGA implementations of the AES and Ascon authenticated ciphers, respectively, to recover entire 128-bit secret keys without using any prior knowledge or training data.
- Design, Modeling and Tests of Electromagnetic Energy Harvesting Systems for Railway Track and Car ApplicationsPan, Yu (Virginia Tech, 2020-01-22)This study proposes various methods to harvest the mechanical energy present in railcar suspensions and railroad tracks to generate electricity that is suitable for onboard or trackside electronics, using electromagnetic generators. Compact electromagnetic energy harvesters that can be installed onboard railcars or wayside on railroad tracks are designed, fabricated, and tested. The designs integrate a mechanical motion rectifier (MMR) with embedded one-way clutches in the bevel gears in order to convert the bi-directional mechanical energy that commonly exists in the form of vibrations into a unidirectional rotation of the generator. The ball screw mechanism is configured such that it has reduced backlash and thus can more efficiently harvest energy from low-amplitude vibrations. Two prototype harvesters are fabricated and tested extensively in the laboratory using a suspension dynamometer and in the field onboard a railcar and on a test track. A power management system with an energy storage circuit has also been developed for this onboard harvester. The laboratory evaluation indicate that the harvesters are capable of harvesting power with sufficient current and voltage for successfully powering light electronics or charging a low demand battery pack. The harvested power varies widely from a few to tens of Watts, depending on the resistive load across the harvester and the amplitude and frequency of the mechanical motion. The laboratory test results are verified through field testing. One harvester is tested onboard a freight railcar, placing it across the wedge suspension, to use the small amount of relative displacement at the wedge suspension to harvest energy. A second harvester is placed on a test track to use the vertical motion that occurs due to passing wheels for wayside energy harvesting. Both onboard and wayside tests confirm the laboratory test results in terms of the success of the design concept in providing low-power electrical power. The harvester design is further integrated into a conventional railroad tie for ease of field installation and for improving the efficiency of harvesting the mechanical energy at the rail. The integrated design, referred to as the "smart tie," not only protects the energy harvester, the wiring harness, and supporting electronics from the maintenance-of-the-way equipment, but also positions the harvester in a mechanically advantageous position that can maximize the track-induced motion, and hence the harvested power. Although for testing purposes, the smart tie uses a modified composite tie, it can be integrated into other track tie arrangements that are used for revenue service track, including concrete and wooden ties. A prototype smart tie is fabricated for laboratory testing, and the results nearly surpass the results obtained earlier from the wayside harvester. The smart tie is currently being considered for revenue service field testing over an extended length of time, potentially at a railroad mega site or similarly suitable location.
- An Efficient Automatic Test Pattern Generator forStuck-Open Faults in CMOS Combinational CircuitsLee, Hyung K.; Ha, Dong S. (Hindawi, 1994-01-01)In this paper, we describe a highly efficient automatic test pattern generator for stuck-open (SOP) faults, calledSOPRANO, in CMOS combinational circuits. The key idea of SOPRANO is to convert a CMOS circuit into anequivalent gate level circuit and SOP faults into the equivalent stuck-at faults. Then SOPRANO derives testpatterns for SOP faults using a gate level test pattern generator. Several techniques to reduce the test set sizeare introduced in SOPRANO. Experimental results performed on eight benchmark circuits show that SOPRANOachieves high SOP fault coverage and short processing time.
- Electromechanical Design and Development of the Virginia Tech Roller Rig Testing Facility for Wheel-rail Contact Mechanics and DynamicsHosseinipour, Milad (Virginia Tech, 2016-09-28)The electromechanical design and development of a sophisticated roller rig testing facility at the Railway Technologies Laboratory (RTL) of Virginia Polytechnic and State University (VT) is presented. The VT Roller Rig is intended for studying the complex dynamics and mechanics at the wheel-rail interface of railway vehicles in a controlled laboratory environment. Such measurements require excellent powering and driving architecture, high-performance motion control, accurate measurements, and relatively noise-free data acquisition systems. It is critical to accurately control the relative dynamics and positioning of rotating bodies to emulate field conditions. To measure the contact forces and moments, special care must be taken to ensure any noise, such as mechanical vibration, electrical crosstalk, and electromagnetic interference (EMI) are kept to a minimum. This document describes the steps towards design and development of all electromechanical subsystems of the VT Roller Rig, including the powertrain, power electronics, motion control systems, sensors, data acquisition units, safety and monitoring circuits, and general practices followed for satisfying the local and international codes of practice. The VT Roller Rig is comprised of a wheel and a roller in a vertical configuration that simulate the single-wheel/rail interaction in one-fourth scale. The roller is five times larger than the scaled wheel to keep the contact patch distortion that is inevitable with a roller rig to a minimum. This setup is driven by two independent AC servo motors that control the velocity of the wheel and roller using state-of-the-art motion control technologies. Six linear actuators allow for adjusting the simulated load, wheel angle of attack, rail cant, and lateral position of the wheel on the rail. All motion controls are performed using digital servo drives, manufactured by Kollmorgen, VA, USA. A number of sensors measure the contact patch parameters including force, torque, displacement, rotation, speed, acceleration, and contact patch geometry. A unified communication protocol between the actuators and sensors minimizes data conversion time, which allows for servo update rates of up to 48kHz. This provides an unmatched bandwidth for performing various dynamics, vibrations, and transient tests, as well as static steady-state conditions. The VT Roller Rig has been debugged and commissioned successfully. The hardware and software components are tested both individually and within the system. The VT Roller Rig can control the creepage within 0.3RPM of the commanded value, while actively controlling the relative position of the rotating bodies with an unprecedented level of accuracy, no more than 16nm of the target location. The contact force measurement dynamometers can dynamically capture the contact forces to within 13.6N accuracy, for up to 10kN. The instantaneous torque in each driveline can be measured with better than 6.1Nm resolution. The VT Roller Rig Motion Programming Interface (MPI) is highly flexible for both programmers and non-programmers. All common motion control algorithms in the servo motion industry have been successfully implemented on the Rig. The VT Roller Rig MPI accepts third party motion algorithms in C, C++, and any .Net language. It successfully communicates with other design and analytics software such as Matlab, Simulink, and LabVIEW for performing custom-designed routines. It also provides the infrastructure for linking the Rig's hardware with commercial multibody dynamics software such as Simpack, NUCARS, and Vampire, which is a milestone for hardware-in-the-loop testing of railroad systems.
- Embedded Passivated-electrode Insulator-based DielectrophoresisShake, Tyler Joseph (Virginia Tech, 2014-03-26)Pathogens in drinking water are the cause of over 1.5 million deaths around the world every year, mostly in developing countries. Practical, cheap, and effective tools for detection of these pathogens are critical to advance public health in many areas around the globe. Micro electro-mechanical systems (MEMS) are miniaturized structures that can be used for a variety of purposes, including, but not limited to, small scale sensors. Therefore, MEMS can be used in place of expensive laboratory equipment and offer a cheap and practical tool for pathogen detection. The presented work's research objective is to introduce a new technique called embedded passivated-electrode insulator-based dielectrophoresis (EπDEP) for preconcentration, separation, or enrichment of bioparticles, including living cells. This new method combines traditional electrode-based DEP and insulator-based DEP with the objective of enhancing the electric field strength and capture efficiency within the microfluidic channel while alleviating direct contact between the electrode and the fluid. The EπDEP chip contains embedded electrodes within the microfluidic channel covered by a thin passivation layer of only 4 μm. The channel was designed with two nonaligned vertical columns of insulated microposts (200 μm diameter, 50 μm spacing) located between the electrodes (600 μm wide, 600 μm horizontal spacing) to generate the nonuniform electric field lines to concentrate cells while maintaining steady flow in the channel. The performance of the chip was demonstrated using Gram-negative (Escherichia coli) and Gram-positive (Staphylococcus aureus) bacterial pathogens in aqueous media. Trapping efficiencies of 100% were obtained for both pathogens at an applied AC voltage of 50 V peak-to-peak and flow rates as high as 10 uL/min.
- Enabling Approximate Storage through Lossy Media Data CompressionWorek, Brian David (Virginia Tech, 2019-02-08)Memory capacity, bandwidth, and energy all continue to present hurdles in the quest for efficient, high-speed computing. Recognition, mining, and synthesis (RMS) applications in particular are limited by the efficiency of the memory subsystem due to their large datasets and need to frequently access memory. RMS applications, such as those in machine learning, deliver intelligent analysis and decision making through their ability to learn, identify, and create complex data models. To meet growing demand for RMS application deployment in battery constrained devices, such as mobile and Internet-of-Things, designers will need novel techniques to improve system energy consumption and performance. Fortunately, many RMS applications demonstrate inherent error resilience, a property that allows them to produce acceptable outputs even when data used in computation contain errors. Approximate storage techniques across circuits, architectures, and algorithms exploit this property to improve the energy consumption and performance of the memory subsystem through quality-energy scaling. This thesis reviews state of the art techniques in approximate storage and presents our own contribution that uses lossy compression to reduce the storage cost of media data.
- Energy Efficient Deep Spiking Recurrent Neural Networks: A Reservoir Computing-Based ApproachHamedani, Kian (Virginia Tech, 2020-06-18)Recurrent neural networks (RNNs) have been widely used for supervised pattern recognition and exploring the underlying spatio-temporal correlation. However, due to the vanishing/exploding gradient problem, training a fully connected RNN in many cases is very difficult or even impossible. The difficulties of training traditional RNNs, led us to reservoir computing (RC) which recently attracted a lot of attention due to its simple training methods and fixed weights at its recurrent layer. There are three different categories of RC systems, namely, echo state networks (ESNs), liquid state machines (LSMs), and delayed feedback reservoirs (DFRs). In this dissertation a novel structure of RNNs which is inspired by dynamic delayed feedback loops is introduced. In the reservoir (recurrent) layer of DFR, only one neuron is required which makes DFRs extremely suitable for hardware implementations. The main motivation of this dissertation is to introduce an energy efficient, and easy to train RNN while this model achieves high performances in different tasks compared to the state-of-the-art. To improve the energy efficiency of our model, we propose to adopt spiking neurons as the information processing unit of DFR. Spiking neural networks (SNNs) are the most biologically plausible and energy efficient class of artificial neural networks (ANNs). The traditional analog ANNs have marginal similarity with the brain-like information processing. It is clear that the biological neurons communicate together through spikes. Therefore, artificial SNNs have been introduced to mimic the biological neurons. On the other hand, the hardware implementation of SNNs have shown to be extremely energy efficient. Towards achieving this overarching goal, this dissertation presents a spiking DFR (SDFR) with novel encoding schemes, and defense mechanisms against adversarial attacks. To verify the effectiveness and performance of the SDFR, it is adopted in three different applications where there exists a significant Spatio-temporal correlations. These three applications are attack detection in smart grids, spectrum sensing of multi-input-multi-output(MIMO)-orthogonal frequency division multiplexing (OFDM) Dynamic Spectrum Sharing (DSS) systems, and video-based face recognition. In this dissertation, the performance of SDFR is first verified in cyber attack detection in Smart grids. Smart grids are a new generation of power grids which guarantee a more reliable and efficient transmission and delivery of power to the costumers. A more reliable and efficient power generation and distribution can be realized through the integration of internet, telecommunication, and energy technologies. The convergence of different technologies, brings up opportunities, but the challenges are also inevitable. One of the major challenges that pose threat to the smart grids is cyber-attacks. A novel method is developed to detect false data injection (FDI) attacks in smart grids. The second novel application of SDFR is the spectrum sensing of MIMO-OFDM DSS systems. DSS is being implemented in the fifth generation of wireless communication systems (5G) to improve the spectrum efficiency. In a MIMO-OFDM system, not all the subcarriers are utilized simultaneously by the primary user (PU). Therefore, it is essential to sense the idle frequency bands and assign them to the secondary user (SU). The effectiveness of SDFR in capturing the spatio-temporal correlation of MIMO-OFDM time-series and predicting the availability of frequency bands in the future time slots is studied as well. In the third application, the SDFR is modified to be adopted in video-based face recognition. In this task, the SDFR is leveraged to recognize the identities of different subjects while they rotate their heads in different angles. Another contribution of this dissertation is to propose a novel encoding scheme of spiking neurons which is inspired by the cognitive studies of rats. For the first time, the multiplexing of multiple neural codes is introduced and it is shown that the robustness and resilience of the spiking neurons is increased against noisy data, and adversarial attacks, respectively. Adversarial attacks are small and imperceptible perturbations of the input data, which have shown to be able to fool deep learning (DL) models. So far, many adversarial attack and defense mechanisms have been introduced for DL models. Compromising the security and reliability of artificial intelligence (AI) systems is a major concern of government, industry and cyber-security researchers, in that insufficient protections can compromise the security and privacy of everyone in society. Finally, a defense mechanism to protect spiking neurons against adversarial attacks is introduced for the first time. In a nutshell, this dissertation presents a novel energy efficient deep spiking recurrent neural network which is inspired by delayed dynamic loops. The effectiveness of the introduced model is verified in several different applications. At the end, novel encoding and defense mechanisms are introduced which improve the robustness of the model against noise and adversarial attacks.