Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation of an Accurate Three-Dimensional Helical Slow-Wave Circuit Model

The helical slow-wave circuit embodies a helical coil of rectangular tape supported in a metal barrel by dielectric support rods. Although the helix slow-wave circuit remains the mainstay of the traveling-wave tube (TWT) industry because of its exceptionally wide bandwidth, a full helical circuit, without significant dimensional approximations, has not been successfully modeled until now. Numerous attempts have been made to analyze the helical slow-wave circuit so that the performance could be accurately predicted without actually building it, but because of its complex geometry, many geometrical approximations became necessary rendering the previous models inaccurate. In the course of this research it has been demonstrated that using the simulation code, MAFIA, the helical structure can be modeled with actual tape width and thickness, dielectric support rod geometry and materials. To demonstrate the accuracy of the MAFIA model, the cold-test parameters including dispersion, on-axis interaction impedance and attenuation have been calculated for several helical TWT slow-wave circuits with a variety of support rod geometries including rectangular and T-shaped rods, as well as various support rod materials including isotropic, anisotropic and partially metal coated dielectrics. Compared with experimentally measured results, the agreement is excellent. With the accuracy of the MAFIA helical model validated, the code was used to investigate several conventional geometric approximations in an attempt to obtain the most computationally efficient model. Several simplifications were made to a standard model including replacing the helical tape with filaments, and replacing rectangular support rods with shapes conforming to the cylindrical coordinate system with effective permittivity. The approximate models are compared with the standard model in terms of cold-test characteristics and computational time. The model was also used to determine the sensitivity of various circuit parameters including typical manufacturing dimensional tolerances and support rod permittivity. By varying the circuit parameters of an accurate model using MAFIA, these sensitivities can be computed for manufacturing concerns, and design optimization previous to fabrication, thus eliminating the need for costly experimental iterations. Several variations were made to a standard helical circuit using MAFIA to investigate the effect that variations on helical tape and support rod width, metallized loading height and support rod permittivity, have on TWT cold-test characteristics.
Fracture Mechanisms in Organic-Rich Shales: Role of Kerogen

In this work we study role of kerogen in the fracture properties of organic-rich shales and, in particular, in the ductility of shales. The presence of kerogen and clays in shale is known to increase the ductility. We propose here a multiscale approach to develop a fine understanding of shale ductility from the molecular scale. We develop and validate a methodology at the molecular scale that can capture the toughness and ductility of a material. We apply this methodology successfully to a silica polymorph and to a kerogen analog, and we confirm the significant ductility of kerogen. Interestingly the silica-kerogen interface exhibits a similar ductility, which is central for the properties of the heterogeneous shale. Finally, we consider a tentative upscaling considering the pull out phenomenon as a likely mechanism of fracture of the shale.
Antioxidant and Antimicrobial Activity of Bunias Orientalis L. and Scorzonera Hispanica L. Ethanol Extracts

The current study was aimed to evaluate an accumulation in plant raw material of Bunias orientalis L. and Scorzonera hispanica L. the total content of phenolic compounds, phenolic acids, flavonoids, antioxidant activity (by DPPH-method) and reducing power of alcoholic extracts. Raw of investigated plants collected from experimental collections of M.M. Gryshko National Botanical Garden of the NAS of Ukraine (Kyiv) and dried for next investigation. Obtained results showed that total content of polyphenols in the above-ground parts of B. orientalis extracts was 52.88 mg g-1 GAE (gallic acid equivalent), phenolic acids – 11.29 mg g-1 CAE (caffeic acid equivalent), flavonoids – 39.91 mg g-1 QE (quercetin equivalent), antioxidant activity – 8.94 mg g-1 TE (Trolox equivalent) and reducing power of extracts – 184.59 mg g-1 TE (Trolox equivalent). Total content of polyphenols in the above-ground parts of S. hispanica plants was 60.16 mg g-1 GAE, phenolic acids – 20.71 mg g-1 CAE, flavonoids – 36.24 mg g-1 QE, antioxidant activity – 5.35 mg g-1 TE and reducing power of extracts – 125.40 mg g-1 TE. Also, total content of polyphenols in the roots of B. orientalis extracts was 9.75 mg g-1 GAE, phenolic acids – 1.73 mg g-1 CAE and reducing power of extracts – 138.70 mg g-1 TE. Root extracts of S. hispanica had total content of polyphenols of 10.87 mg g-1 GAE, phenolic acids – 2.62 mg g-1 CAE and reducing power of extracts – 110.96 mg g-1 TE. Flavonoids and antioxidant activity in the root extracts of both species weren’t determined. The antimicrobial activity of alcoholic extracts of two investigated species was tested against 8 microorganisms by disc diffusion method. It was found that higher activity against microbial strains had alcoholic extracts of B. orientalis roots.
Digitally Controlled Active Power Filter for AESA Radar

This master thesis demonstrate a digitally controlled Active Power Filter, which is used for eliminating low frequency distortion from a pulsating load. As a result, the current on the power supply will be uniform. The main tasks in this master thesis was to design a circuit, build a prototype, program a Digital Signal Processor, do a verification and make an evaluation. The Active Power Filter is average inductance current controlled, with a voltage controller as an outer loop. A state space representation was used for creating a model for the Active Power Filter and a controller. The Active Power Filter with the controller was simulated in SIMULINK in order to evaluating the controller performance. Thereafter, the controller parameter was implemented in a microprocessor and verified with the Active Power Filter, a pulsating load and DC/DC-converter. The Active Power Filter has not been integrated with the existing DC/DC-converter except for the switching frequency being the same. Therefore, there are some conflicts between the controllers in the two devices. The result of this master thesis show that by combining a passive-filter, active-filter and a DC/DC-converter, it is possible to get an undisturbed power supply on the input of the DC/DC-converter. It has also been shown that it is possible to decrease 300Hz distortion. Also by using a digital control it is possible to create an adaptive system. As a result, the pulsating load characteristics can vary and the Digital Signal Processor will adjust the reference value for that specific load.
The impact of demand-controlled and economizer ventilation strategies on energy use in buildings

The overall objective of this work was to evaluate typical energy requirements associated with alternative ventilation control strategies for constant-air-volume (CAV) systems in commercial buildings. The strategies included different combinations of economizer and demand-controlled ventilation, and energy analyses were performed for four typical building types, eight alternative ventilation systems, and twenty US climates. Only single-zone buildings were considered so that simultaneous heating and cooling did not exist. The energy savings associated with economizer and demand-controlled ventilation strategies were found to be very significant for both heating and cooling. In general, the greatest savings in electrical usage for cooling with the addition of demand-controlled ventilation occur in situations where the opportunities for economizer cooling are less. This is true for warm and humid climates and for buildings that have relatively low internal gains (i.e., low occupant densities). As much as 20% savings in electrical energy for cooling were possible with demand-controlled ventilation. The savings in heating energy associated with demand-controlled ventilation were generally much larger but were strongly dependent upon the building type and occupancy schedule. Significantly greater savings were found for buildings with highly variable occupancy schedules and large internal gains (i.e., restaurants) as compared with office buildings. In somemore » cases, the primary heating energy was virtually eliminated by demand-controlled ventilation as compared with fixed ventilation rates. For both heating and cooling, the savings associated with demand-controlled ventilation are dependent on the fixed minimum ventilation rate of the base case at design conditions. « less
A General Framework for Analyzing, Characterizing, and Implementing Spectrally Modulated, Spectrally Encoded Signals

Abstract : Fourth generation (4G) communications will support many capabilities while providing universal, high speed access. One potential enabler for these capabilities is software defined radio (SDR). When controlled by cognitive radio (CR) principles, the required waveform diversity is achieved via a synergistic union called CR-based SDR. Research is rapidly progressing in SDR hardware and software venues, but current CR-based SDR research lacks the theoretical foundation and analytic framework to permit efficient implementation. This limitation is addressed here by introducing a general framework for analyzing, characterizing, and implementing spectrally modulated, spectrally encoded (SMSE) signals within CR-based SDR architectures. Given orthogonal frequency division multiplexing (OFDM) is a 4G candidate signal, OFDM-based signals are collectively classified as SMSE since modulation and encoding are spectrally applied. The proposed framework provides analytic commonality and unification of SMSE signals. Applicability is first shown for candidate 4G signals, and resultant analytic expressions agree with published results. Implementability is then demonstrated in multiple coexistence scenarios via modeling and simulation to reinforce practical utility.
Development of Injury Probability Function for the Thorax of a Pedestrian Dummy Based on Two-Dimensional Evaluation of Chest Deflection Using Human and Pedestrian Dummy FE Models

This paper will discuss that in a pedestrian accident, the loading direction to the pedestrian thorax is affected by the posture of the pedestrian upon impact and a subsequent rotation of the upper body. Because of this, in order to predict pedestrian thoracic fractures accurately, injury criteria for the thoracic deflection formulated in one single loading direction (frontal or lateral) are not sufficient and evaluation of thoracic fractures due to loadings in different directions is required. This study investigated a technique for two-dimensional evaluation of thoracic deflection using human and dummy FE models and formulated injury probability functions for the thorax of a pedestrian dummy.
Application of Fuzzy State Aggregation and Policy Hill Climbing to Multi-Agent Systems in Stochastic Environments

Abstract : Reinforcement learning is one of the more attractive machine learning technologies, due to its unsupervised learning structure and ability to continually even as the operating environment changes. Applying this learning to multiple cooperative software agents (a multi-agent system) not only allows each individual agent to learn from its own experience, but also opens up the opportunity for the individual agents to learn from the other agents in the system, thus accelerating the rate of learning. This research presents the novel use of fuzzy state aggregation, as the means of function approximation, combined with the policy hill climbing methods of Win or Lose Fast (WoLF) and policy-dynamics based WoLF (PD-WoLF). The combination of fast policy hill climbing (PHC) and fuzzy state aggregation (FSA) function approximation is tested in two stochastic environments; Tileworld and the robot soccer domain, RoboCup. The Tileworld results demonstrate that a single agent using the combination of FSA and PHC learns quicker and performs better than combined fuzzy state aggregation and Q-learning lone. Results from the RoboCup domain again illustrate that the policy hill climbing algorithms perform better than Q-learning alone in a multi-agent environment. The learning is further enhanced by allowing the agents to share their experience through a weighted strategy sharing.
Dynamic two phase flow models for flushing

This thesis aims at modeling the separated liquid-liquid flows with application for flushing. In the beginning, there will be a short review of the governing equations and the fundamental concepts used in this thesis. Two models are introduced and developed based on two previous PhD dissertations from NTNU(Trygve Wangensteen and Tor Kindsbekken Kjeldby). The properties of the fluids in these models are based on Oil, Exxsol D80, mu_o=1.79 [cP] and tapped water, mu_w=1.11 [cP]. These models will be numerically developed for both dynamic and stationary flows. The numerical scheme used for these models is explicit. A complete explanation about discretization is given in chapter 4. After developing the dynamic and stationary solutions for both models, there will be two major case studies. The first one is to understand when the dynamic and stationary solutions depart from one another as the mixture velocity varies between low velocities to high velocities. It turns out that The solutions look quite similar until the mixture velocity reaches the value of around U_M=1 [m/s]. Then the solutions become more and more different especially at the oil front. The second case study is about keeping the mixture velocity constant and varying the pipe angle. The pipe angle variation range lies between -2.5 and +5 degrees. For negative inclinations, the dynamic and stationary solutions agree quite well. However when the positive slope is put to the test and gravity is acting against the flow, the dynamic and stationary solutions differ more. \\ Finally there will be a discussion on where this different behavior stems from. The two fluid model introduced at the beginning of this report is studied closely, term by term. These terms represent the frictional forces that balance the pressure gradient in the pipe. These forces are plotted for four different cases with mixture velocities varying from U_M=0.25 [m/s] to U_M=5 [m/s]. These figures reveal which forces dominate the solution for relatively low and high mixture velocities. The dominating forces are the ones that balance the pressure gradient. It turns out that the level gradient is quite significant and a dominant term in almost all cases. However as the mixture velocity increases, the acceleration terms grow to the same order of magnitude as the level gradient. But for the most part, the spatial and the temporal acceleration act symmetrically, and in effect cancel each other out. There will be a thorough discussion about this in the final chapter.
Design, development and characterization of a handheld electrochemical analyzer system : in the perspective of DNA biosensors for foodbourne pathogen detection

Detailed in this work is the design and development of a novel handheld electrochemical analyzer system interfaced to smart phone. The custom made electrochemical analyzer is versatile, cost-effective and can be used for real-time applications. The electrochemical analyzer was characterised for electron transfer events associated with chemical and biological samples. The presented design was implemented based on the Arduino Nano open source electronics prototyping platform. This platform includes a microcontroller, which is then connected to a custom made electrochemical analyzer circuit. In a novel approach, the versatility of the instrument was further demonstrated by employing the electrochemical analyzer to a modified electrochemical cell which formed the basis of a DNA biosensor. The cyclic voltammetry technique was used to impose a triangular waveform on an electrochemical cell and the resulting current through the cell was then monitored. The DNA biosensor generated unique electrical signals in real-time between complementary and non-complementary oligonucleotides sequences of the Bacillus cereus DNA and it proved to be effective. Investigations were also undertaken by employing a commercial electrochemical analyzer for label-free detection of DNA hybridization using impedimetric, potentiometric and amperometric techniques. Impedance measurements are performed without using additional redox probes. The effects of hybridization and non-specific binding were compared when the probe DNA molecules were immobilized by different immobilization methods on a conducting polymer matrix. The results showed that the probe DNA immobilized using electrochemical adsorption yielded better hybridization signals compared to other immobilization methods. Control experiments were also performed to prove the specificity of the biosensor in the presence of noncomplementary oligonucleotide and no unspecific bonding with the immobilized probe was observed. The performance of the DNA sensor proved to be effective in terms of selectivity, sensitivity and reproducibility of hybridization events. Analysis of these DNA probes showed that the minimum level of detection was 33.3 pg/ml (103 CFU/ml). The implications of the experimental results obtained are discussed as are the insights they provide into further development of the analyzer. Future work would include interface of a smaller scale sensor heads to use in a handheld electrochemical analyzer system to detect environmental variables including pathogenic micro-organisms in realtime. Individual sensors are based on the unique DNA signature of the specific foodborne bacterial pathogen(s) will be developed. Based on sensor identification of these pathogens, it will be possible to detect them directly from the food source.
Closed- and Open-world Reasoning in DL-Lite for Cloud Infrastructure Security (Extended Abstract)

Infrastructure in the cloud is deployed through configuration files, which specify the resources to be created, their settings, and their connectivity. We aim to model infrastructure before deployment and reason about it so that potential vulnerabilities can be discovered and security best practices enforced. Description logics are a good match for such modeling efforts and allow for a succinct and natural description of cloud infrastructure. Their open-world assumption allows capturing the distributed nature of the cloud, where a newly deployed infrastructure could connect to pre-existing resources not necessarily owned by the same user. However, parts of the infrastructure that are fully known need closed-world reasoning, calling for the usage of expressive formalisms, which increase the computational complexity of reasoning. Here, we suggest an extension of DL-LiteF that is tailored for capturing such cloud infrastructure. Our logic allows combining a core part that is completely defined (closed-world) and interacts with a partially known environment (open-world). We show that this extension preserves the first-order rewritability of DL-LiteF for knowledge-base satisfiability and conjunctive query answering. Security properties combine universal and existential reasoning about infrastructure. Thus, we also consider the problem of conjunctive query satisfiability and show that it can be solved in logarithmic space in data complexity.
Improving Soldier Factors in Prediction Models

Abstract : Report developed under SBIR contract for topic A98-163. A key decision made at the highest levels of any military is the trade-off between allocating resources to system acquisition versus allocating resources to maintain force readiness through training. Advanced Distributed Simulations (ADS) provide a mechanism for tactical combat training through man-in-the-loop simulators and Computer Generated Forces (CGF). The potential for using ADS to address the trade-offs for allocating resources is dampened by the unrealistic behavior of CGF. Phase 1 of this project produced algorithms, data structures, and a methodology for incorporating the effects of training and environmental stressors to improve CGF behavioral realism. in Phase 11, we expanded and enhanced the technical feasibility for including these effects in CGF entities on simulated battlefields. The resulting product is called the Training Effects and Stressor Integration Module (TESTIM). it can provide the Army with the ability to improve the realism of CGF entities in ADS and other human performance models. TESTIM can also be used to assess the expected payoff of training in terms of improved performance.
Multi-Scale Optical Coherence Tomography Imaging

An optical modality capable of quantitative, label-free, high-speed and high-resolution imaging across spatiotemporal scales coupled with sophisticated software for image reconstruction and quantitative analyses would be of great utility to scientists and engineers in the medical and life sciences fields. Currently, a combination of optical imaging techniques and software packages are needed to address the list of capabilities described previously. Optical coherence tomography is an optical imaging technique based on low coherence interferometry capable of measuring light backscattered from the sample at micrometer-level resolutions over millimeter-level penetration depths in biological tissue. Phase-sensitive extensions of OCT enable the functional assessment of biological tissue samples as well as the structural examination of samples down to the single-cell level. This dissertation describes the development and application of high-speed real-time multi-functional spectral-domain OCT (MF-SD-OCT) for structural and functional examination of biological samples across spatiotemporal scales. A discussion of the development of a GPU-accelerated high-speed MF-SD-OCT imaging system accompanied by demonstrations of the performance enhancements due to the GPU are presented initially. Next, the development of MF-SD-OCT-based quantitative methods for the structural and functional assessment and characterization and classification of biological tissue samples is discussed. The utility of these methods is demonstrated through structural, functional and optical characterization and classification of peripheral nerve and muscle tissue. The dissertation concludes with a discussion of the improvements made to spectral-domain optical coherence phase microscopy (SD-OCPM) to enable dynamic live cell imaging and the application of dynamic live cell SD-OCPM for morphological visualization of cheek epithelial cells and examination of functionally stimulated morphological changes in neurons. The work described in this dissertation demonstrates the versatility of OCT imaging technology to perform quantitative, label-free, high-speed and high-resolution imaging across spatiotemporal scales, enabling the examination of native dynamic tissue and cellular physiology.