Miracle-dz/UniFAR-FTUs huggingface dataset:
System-level memory power and performance optimization for system-on-a-chip embedded systems

Power has become a first rate design issue in microprocessor design. Power efficiency is especially critical for battery-powered embedded systems. Technology trends are making data communication, both on-chip and off-chip, more expensive relative to computation. Evaluating power-performance design trade-offs at the architectural level still requires more research study. In this dissertation, we will show how microprocessor power, especially in the memory sub-system, is consumed during program execution. We also show that the external memory system in a low power System-on-a-Chip (SOC) embedded system has significant impact on overall system power. The source of memory power consumption is due to the data transmission, bandwidth limitation, and memory access overhead. We review and summarize the current research work on low power microprocessor architecture design in academic research community and in industry world. The work includes power modeling, power estimation tools and power optimization techniques. In addition, we summarize different power optimization into five categories and compare their effects and impacts to the overall system. Two solutions are proposed to reduce data bandwidth and to improve the power efficiency on the external memory bus. We first propose an external bus arbitrator to schedule the external bus requests in order to achieve better bus utilization. We propose a series of power aware arbitration schemes for the external bus request scheduling. On average, we observe a 22 percent performance speed up and 13 percent power savings compared to traditional arbitration schemes. In our second approach, we present a hardware-based, programmable external memory page remapping mechanism which can significantly improve system performance and decrease the power budget on external memory bus accesses. We employ graph-coloring techniques to guide the page mapping procedure. Our algorithm can significantly reduce the memory page miss rate by 70-80 percent on average. For a 4-bank SDRAM memory system, we reduce external memory access time by 11 percent, while reducing the associated power consumed by 11 percent.
Obstacle Avoidance Control for the REMUS Autonomous Underwater Vehicle

Abstract : As the Navy continues its development of unmanned underwater vehicles, the need for total autonomous missions grows. Autonomous Underwater Vehicles (AUV) allow for advances in mine warfare, harbor reconnaissance, undersea warfare and more. Information can be collected from AUVs and downloaded into a ship or battle group's network. As AUVs are developed it is clear forward-look sonar will be required to be able to detect obstacles in front of its search path. Common obstacles in the littoral environment include reefs and seawalls which an AUV will need to rise above to pass. This thesis examines the behavior and control system required for an AUV to maneuver over an obstacle in the vertical plane. Hydrodynamic modeling of a REMUS vehicle enables a series of equations of motion to be developed to be used in conjunction with a sliding mode controller to control the elevation of the AUV. A two-dimensional, 24 deg. vertical scan forward look sonar with a range of 100 m is modeled for obstacle detection. Sonar mappings from geographic range-bearing coordinates are developed for use in MATLAB simulations. The sonar 'image' of the vertical obstacle allows for an increasing altitude command that forces the AUV to pass safely over the obstacles at a reasonable rate of ascent and pitch angle. Once the AUV has passed over the obstacle, the vehicle returns to its regular search altitude. This controller is simulated over different types of obstacles.
Stepwise Pad Driver in Deep-Submicron Technology

In this report, we investigate the changes needed to implement a previous design of an energy efficient pad driver in a more modern 130 nm CMOS process, driving a load of 5 pF. A modified design procedure is presented and applied to a test case, resulting in a working driver. Simulations indicated energy savings of up to 50 percent compared to the traditional implementation of a pad driver, at switching times as low as 1.2 ns.
RHEOLOGICAL PROPERTIES OF CHEMICALLY MODIFIED ASPHALTS

Asphalt chemically modified with furfural and furyl acrolein was performance graded (PG), and its performance was predicted according the criteria developed by the Strategic Highway Research Program (SHRP). These asphalts were aged in a thin film oven, a rolling thin film oven, and a pressure aging vessel to investigate the aging behaviors of the chemically modified asphalts. The rheological properties were determined from 10 deg C through 70 deg C by the dynamic shear rheometer and from -25 deg C through -5 deg C by the bending beam rheometer. By using the SHRP criteria chemical modification was shown to increase the temperature range over which the asphalt can be used by primarily increasing the high-temperature stiffness of the asphalt. Differences in properties and PG grading were observed when the asphalts were aged in a rolling thin film oven compared with that when they were aged in the thin film oven, especially for the modified asphalts. The resistance to rutting was predicted to increase with chemical modification. The resistance to fatigue was predicted to change insignificantly at the range of temperatures considered in the PG specifications. The low-temperature properties were not significantly affected because of modification.
Evaluation of the Effects of Variable Helmet Weight on Human Response During Lateral +Gy Impact

Abstract : Helmet-mounted systems (HMS) are designed to enhance pilot performance, but may also affect pilot safety by increasing the potential for neck injury during ejection due to the change in helmet inertial properties. A series of tests was conducted by AFRL/HEPA on a horizontal impulse accelerator using human subjects to investigate the effects of helmet inertial properties on human response to short duration sideward impacts of variable magnitude. The effects of headrest contour and gender were also investigated. Maximum neck load values obtained in this study will be used to establish head/neck injury criteria for helmet-mounted systems and for the implementation of improvements in bracing techniques to minimize pilot injury during ejections.
Using Hidden Markov Models to Segment and Classify Wrist Motions Related to Eating Activities

Advances in body sensing and mobile health technology have created new opportunities for empowering people to take a more active role in managing their health. Measurements of dietary intake are commonly used for the study and treatment of obesity. However, the most widely used tools rely upon self-report and require considerable manual effort, leading to underreporting of consumption, non-compliance, and discontinued use over the long term. We are investigating the use of wrist-worn accelerometers and gyroscopes to automatically recognize eating gestures. In order to improve recognition accuracy, we studied the sequential dependency of actions during eating. In chapter 2 we first undertook the task of finding a set of wrist motion gestures which were small and descriptive enough to model the actions performed by an eater during consumption of a meal. We found a set of four actions rest, utensiling, bite, and drink; any alternative gestures is referred as the other gesture. The stability of the definitions for gestures was evaluated using an inter-rater reliability test. Later, in chapter 3, 25 meals were hand labeled an used to study the existence of sequential dependence of the gestures. To study this, three types of classifiers were built: 1) a K-nearest neighbor classifier which uses no sequential context, 2) a hidden Markov model (HMM) which captures the sequential context of sub-gesture motions, and 3) HMMs that model inter-gesture sequential dependencies. We built first-order to sixth-order HMMs to evaluate the usefulness of increasing amounts of sequential dependence to aid recognition. The first two were our baseline algorithms. We found that the adding knowledge of the sequential dependence of gestures achieved an accuracy of 96.5%, which is an improvement of 20.7% and 12.2% over the KNN and subgesture HMM. Lastly, in chapter 4, we automatically segmented a continuous wrist motion signal and assessed its classification performance for each of the three classifiers. Again, the knowledge of sequential dependence enhances the recognition of gestures in unsegmented data, achieving 90% accuracy and improving 30.1% and 18.9% over the KNN and the sub-gesture HMM.
LOW-COST VIDEO IMAGE PROCESSING SYSTEM FOR EVALUATING PAVEMENT SURFACE DISTRESS

Most pavement condition surveys use rating systems in which pavement distress is measured by type, extent, and severity. Rating either bituminous or portland cement concrete pavements by the pavement condition rating (PCR) or similar systems is tedious and time-consuming. In most instances, distress measurement is subjective, which affects the actual rating. Improved data collection and data processing methods are thus needed to expedite pavement evaluation that can be used as input in pavement management systems. Recent advances in computer technology now permit the identification and quantification of distress types that can be measured by width, length, or area by automatic analyses of images captured by a microcomputer from video or film recordings. The development of a low-cost system for video image pavement distress analysis is described; the system allows the identification, classification, and quantification of commonly occurring pavement distress types in terms of severity and extent. Once pavement distress is identified, quantified, and classified, the system can be combined with rating procedures (such as PCR) to obtain a quantitative measure of pavement condition. Hardware and software characteristics of the system are described in detail. Diagrams showing the connection of system components and procedural steps leading to the calculation of a pavement rating are also included. Distress identification and classification is currently limited to distress types that can be quantified by width, length, geometry, or area covered by the distress.
Graphene FET circuit-level device modelling

This thesis presents models for a graphene based field effect transistor (GFET). The graphene material has been widely studied since its synthesis in 2004 and the material holds promise for the next generation electronic applications. Therefore, there is a need to model its device characteristics. In this respect the contributions presented here are, firstly, a SPICE-compatible model for both dual gate and single gate graphene transistors. The derivation of the carrier transport of both hole and electron conduction results in a set of analytical equations. These derivations cover the three identified regions of operation as well as the boundary voltage conditions that define the regions. The Jacobian entries are shown to be continuous across the region boundaries. Secondly, circuit levels model of a single-layer GFET and multi layer GFET suitable for a direct implementation in SPICE. In this contribution, a more accurate threshold voltage compared to other models is derived. This contribution also shows how models can be extended to as many layers the graphene channelled transistor has. Finally, the introduction of a thermionic resistance, which is modelled in parallel with the resistance due to gate induced charges, provides a model for the temperature dependent channel resistance. The contribution goes further to derive equations between the off current and the vertical electric fields. Thus, giving a good estimation of the tunable bandgap opening in graphene. The models in this contributions are validated against experimentally measured transistor characteristics which have been carried out by other research groups and the models show a good agreement in all cases validated. The thesis equally presents the use of a floating gate to optimize the transistors characteristics. To illustrate these contributions, algorithms of the models have been implemented on the following CAD tools, HSPICE, VHDL-AMS and Berkeley SPICE. During the course of this work one journal and five conference papers have been published.
Mobility Measurements of a Simulated Semi-Infinite Beam Using a Laser Doppler Velocimeter.

Abstract : An experiment involving the measurement of the vibratory response of a simulated semi-infinite beam was carried out at the Defence Research Establishment Atlantic (DREA) in support of the Ship Noise Project. The primary purpose of the experiment was to establish whether DREA's laser doppler velocimeter (LDV) would be an adequate tool for such measurements in a larger scale test. Secondary purposes included verification of the power flow finite element analysis method for a simple test case and examination of various damping treatments to determine the most effective. Results of the testing showed that the LDV was an excellent noncontacting sensor for the measurement of low level velocity signals providing that care is taken to check the focus of the laser to insure it maintains a lock' on the target and that the signal is kept at a reasonably small level. The use of DREA's milling table allowed for excellent position control and such a system would be ideal for a larger scale test. Of the various thicknesses of damping material applied, the 3/8" treatment seemed to be the most effective.
Analyzing the Performance of the Epiphany Processor

Our need for computational power steadily increases as we strive to solve more complex problems. As the increase of computational power of \acp{CPU} is slowing down, due to increasingly smaller and more complex designs, it may be a good idea to look into different processor designs. At the same time, the need for low-power processors are increasing. There is many reasons for this. The desire to reduce costs and produce more environmentally friendly data centers is one. Another is to reduce the heat dissapation, which is more important the smaller the processor design is. Lastly, mobile devices are becoming increasingly popular. In this project, I will look into the performance of the Epiphany processor using the Parallella device. This is a new design of a small and low-power processor. The processor I am testing contains 16 processor cores. There exists a design for a version with 64 cores, and future versions will have even more. To have a reference point for the performance of the Epiphany, similar implementations are run and measured on the main processor of the Parallella, a Xilinx Zynq7000 Series.
Modelling Spray Pressure Effects on Droplet Size Distribution from Agricultural Nozzles

For spray applications, drop size is the most important feature as it affects all aspects of a phytosanitary treatment: biological efficacy, environmental pollution, and operator safety. In turn, drop size distribution depends on nozzle type, liquid properties, and working pressure. In this research, three nozzles were studied under ordinary working conditions and the effect of pressure on drop size distribution was assessed. The nozzles under test, all from Albuz (France), were an orange hollow cone nozzle ATR 80 (European color code), an air induction flat spray nozzle AVI 11003, and an air induction hollow cone nozzle TVI 8002. The ATR 80 and the TVI 8002 nozzles were tested at four pressure values: 0.3, 0.5, 1.0, and 1.5 MPa; the AVI 11003 nozzle was tested at 0.3 and 0.5 MPa. The drop size measurement technique was based on the liquid immersion method by using a custom-made test bench; spray quality parameters were computed by means of suitable functions written in R language. Results showed that an increase in working pressure caused an increase in drop pulverization regardless of the type of nozzle, and drop pulverization was higher for the turbulence nozzle than for the two air induction nozzles. Based on skewness and kurtosis values, the theoretical gamma distribution was the most adapt to fit the experimental data. The scale parameter showed a decreasing trend with the increase in the pressure, a clear index of higher drop pulverization.
Silicon Carbide Sigma-Delta Modulatorfor High Temperature Applications

Analog and mixed-signal electronics capable of operating at elevated ambient temperatures up to 600 oC are widely needed to support some high-cost in-situ sensor applications in industry. Silicon-based devices or integrated circuits (ICs) do not operate beyond 300 oC without any extra cooling system. However, Silicon Carbide (SiC) is a promising material to operate at such high temperature reliably due to its wide bandgap and high thermal conductivity. Although there are still many challenges with respect to the design and fabrication of SiC-based ICs, this research work targets on realizing a novel highly-integrated data conversion IC using our in-house low-voltage 4H-SiC vertical bipolar technology. In this research work, the first sigma-delta modulator on SiC technology for high temperature applications has been demonstrated. The thesis gives a detailed description of the entire process used to implement the in-house sigma-delta modulator, which covers: device modelling, modulator system-level and circuit-level design, high temperature measurements and performance evaluation. The fabricated sigma-delta modulator occupies around 6.9 mm x 2.8 mm chip area which contains 104 BJTs, 92 integrated-resistors, 8 integrated-capacitors and only one metal layer. From 27 oC up to 450 oC, the modulator performs properly and achieves 53 dB dynamic range in average within 1 kHz bandwidth, which is consistent with the simulation. However with increasing temperature, the modulator input amplitude at peak SNDR becomes smaller due to the saturation of its internal integrators. At 500oC the modulator operates, but the dynamic range drops to 40 dB. The modulator is powered with ±7.5 V and sampled by a 512 kHz clock. In addition, the most critical analog building block of the modulator, the fully-differential OpAmp has also been characterized individually up to 500 oC with promising performance. Consequently, these results show the feasibility to further investigate SiC-based ICs for high temperature applications.
Quantification of Spatial Structure Characteristics of Typical Natural Secondary Forest Gaps in Northeastern China

Background: To understand the theory of forest cycle and reveal the relationship between forest gaps and forest structure, species composition and biodiversity, we need to study the spatial structure of forest gaps. However, the complexity of natural secondary forest structure makes it difficult to quantify the spatial structure characteristics of gaps in large areas by field measurement. In this study, aerial orthophotos, and light detection and ranging (LiDAR), were used as data sources. The experimental area was Maoer Mountain Forest Farm, a typical natural secondary forest in northeastern China, and we used the investigation data of forest resources as reference material. We extracted 1343 forest gaps by manual digitization combined with canopy height model correction. The spatial characteristics of the extracted gaps were quantified from the spatial characteristics (area, shape complexity index), spatial heterogeneity (gap height diversity index) and spatial distribution characteristics (Clark–Evans index) of individual gaps.Results: In the three types of natural secondary forest, the frequency distribution of gap area showed a negative exponential distribution: 90% of the gap area was less than 100 m2. As forests aged, the proportion of gap area decreased from young forest to near-mature forest, and increased from near-mature forest to over-mature forest. The maximum frequency range of shape index changed from 1.2 to 1.4 for young forest, middle age forest and near-mature forest; and which is from 1.4 to 1.6 for mature forest and over-mature forest. The gap height diversity index increased from young forest to near-mature forest, decreased when the forest was mature and increased when it was over-mature. The spatial pattern of forest gaps was mainly random. The proportion of random distribution increased from young forest to middle-aged forest, decreased from near-mature forest to mature forest and increased from over-mature forest.Conclusions: Most of the gaps in the natural secondary forest were small and medium-sized; the shapes were complex; the internal spatial heterogeneity was high; and the gaps were mostly randomly distributed. Use of aerial orthophoto and canopy height model sets was efficient and reliable in quantifying the spatial characteristics of forest gaps, and can replace the time-consuming (and usually field-based) measurement of their subjective spatial characteristics.
Perbandingan Metode Eigenface, Fisherface, dan LBPH pada Sistem Pengenalan Wajah

dan pose yang Selain kondisi cahaya, jarak, kualitas kamera merupakan tantangan untuk merancang sistem pengenalan wajah secara real-time dengan tingkat akurasi yang tinggi. Terdapat berbagai jenis metode pengenalan wajah, diantaranya adalah Eigenface, Fisherface, dan Local Binary Patterns Histograms (LBPH). Penelitian ini dilakukan untuk membandingan metode pengenalan wajah antara Eigenface, Fisherface, dan LBPH dalam perubahan tingkat kecerahan, ekspresi wajah, dan tingkat akurasi pengenalan wajah. Berdasarkan hasil analisis dan pembahasan perbandingan ketiga metode pengenalan wajah tersebut, dapat ditarik kesimpulan metode merupakan metode yang paling akurat dan eﬁsien dibandingkan dengan metode Eigenface dan Fisherface.
Experimental Evaluation of a Joint Cognitive System for 4D Trajectory Management

Effective joint human-automation coordination is essential in order to support the central role of the human operator in foreseen future trajectory-based air traffic operations. The SESAR WP-E project C-SHARE aims to achieve this by taking a Cognitive Systems Engineering approach, based upon accomplishing joint human and automation cognition through a shared representation of 4D-trajectory management. In foregoing research, a work domain model and a joint human-machine interface has been developed to support the human operator in the task of en-route 4D trajectory re-planning. This paper presents the findings of two experiments that aimed to determine the effect of both the initial level of traffic orderliness (i.e., structured versus unstructured traffic) and the scale of perturbations acting upon the airspace (e.g., number of conflicts and restricted areas) on the overall effectiveness of such a system. The findings of the experimental evaluation show that the C-SHARE approach to joint human-automation coordination in perturbation management is promising. Further, the experiment subjects accepted the tool and found it supportive for the task at hand, resulting in a manageable degree of workload during all experiment scenarios.
The Study of Body Weight, Haematological and Serum Biochemical Parameters, Liver and Kidney Texture in Rats Fed Corn Oil

The present study aimed to investigate the effect of Afia corn oil (C.O.) 0.3 ml/rat on animals body weight (B.W.), foodintake, organs weight of liver, and kidney, some haematological and serum biochemical parameters, liver and kidney sections, orally by gavage in adult male rats for 4 weeks. Serum total cholesterol, Serum triglyceride (TG) and Low density lipoprotein (LDL) were decreased significantly from control group. While non significant change occurred in animals B.W. , foodintake, organs weight, haematological parameters, and high density lipoprotein (HDL), also histological sections of liver and kidney were similar to those of control group. The results of the present study indicating that Afia C.O. offering health benefits through decreasing of cholesterol, TG, and LDL concentrations.