Miracle-dz/UniFAR-FTUs huggingface dataset:
Structuring the Analysis of Wealth Inequality using the Functions of Wealth: A Class-Based Approach

We integrate concepts from sociology into the economic analysis of inequality and propose a relational approach focusing on di erent functions of wealth. We operationalize these functions by empirically analyzing the groups of renters, owners, and capitalists. Employing European and US data, we nd that classifying households based on these functions of wealth aligns well with the income and wealth distribution, in ways that vary considerably across countries. Our approach allows us to distinguish between wealth as a means of capitalist production, as a substitute for public wealth (precautionary wealth), and as a source of non-cash income (housing wealth used). We propose new measures of inequality directly linked to social realities. JEL Classi cations: D14, D15, D31, D63, Z13
Planar Antennas for CubeSat Missions

CubeSats are a type of pico-satellites that have a standardized size of 10 x 10 x 10 cm3 (1U), or 1U multiples, and weigh less than 1.33 kg per cubic unit. A few challenges arise when designing an antenna to be integrated in the CubeSat’s small structure. Miniaturization techniques must be used to shrink antenna size and deployable antennas solutions can be used when bigger antenna apertures are needed e.g., in applications that require a high gain antenna. Also, special challenges arise due to the harsh environment in space. This paper presents two different planar antennas solutions, for CubeSat applications. First, a circularly polarized patch antenna for the ISTsat-1 CubeSat, is developed. Secondly, a reflect array (RA) antenna is developed for a possible ISTsat-2 mission. The antenna for ISTsat-1 operates in the L band, more specifically 1090 MHz, and is for an automatic dependent surveillance broadcast mission (ADS-B). The second antenna operates in the Ka uplink band of 27 31 GHz, and can be used for multiple applications, e.g. fast mobile broadband access. The antenna for ISTsat-1 has 3.1 dB of gain, when integrated onto the CubeSat. Also, it has 16 MHz of bandwidth, centered around 1090 MHz, and an axial ratio of 0.5 MHz with a 4 MHz bandwidth. The RA antenna has 26 dB of gain, at 30 GHz, with a large bandwidth (27.5 31 GHz) that covers almost the entire Ka uplink band. The antenna is circularly polarized, with a axial ratio lower than 3 dB throughout the whole band. Both antennas are fabricated in space ready substrates, with good thermal and low outgassing properties.
Degeneracy-aware Imaging Sonar SLAM

—High-frequency imaging sonar sensors have recently been applied to aid underwater vehicle localization, by providing frame-to-frame odometry measurements or loop closures over large time-scales. Previous methods have often assumed a planar environment, thereby restricting the use of such algorithms mostly to seaﬂoor mapping. We propose an algorithm to generate pose-to-pose constraints for pairs of sonar images, which may also be applied to larger sets of images, that makes no assumptions about the environmental geometry. The algorithm is sensitive to the inherent degeneracies of the imaging sonar sensor model, and may be tuned to trade off between providing more constraints on the sensor motion and not over-ﬁtting to noise in the measurements. For real-time localization, we fuse the resulting pair-wise sonar pose constraints with vehicle odometry in a pose graph optimization framework. We rigorously evaluate the proposed method and demonstrate improvement in accuracy over previously proposed formulations both in simulation and real-world experiments.
Methodology for Product Development Process Structuring and Improvement

Product development is multidisciplinary activity which is dynamic, creative, uncertain, highly iterative and strongly reliant on communication, making it particularly complex. Research on the topic shows that having a well-defined development framework, whether it be process-based or information-based, is a critical success factor for new products. Research also shows that some sort of product development structure is already being used in large manufacturing firms, particularly in the aerospace and automotive industries. This work proposes a methodology for structuring the development process of small engineering firms or teams which relies on modelling to describe the processes and support their improvement. It was applied and continuously revised in a practical environment consisting of a team of 30 engineering students designing and building a race car. Results show that implementing the methodology is time-consuming, particularly for small, understaffed teams, but that useful insights such as new organizational structures, new process approaches and better knowledge of influence of external factors can be drawn from its implementation.
Comparison of Microleakage between Resin-based and Bioceramic-based Root Canal Sealers by Fluid Filtration Technique

Objectives: The aim of this study was to compare the microleakage between resin-based (AH Plus®) and bioceramic-based (EndoSequence BC Sealer®) root canal sealers using the fluid filtration technique. Materials and methods: Seventy extracted human mandibular premolars resected 12 mm from the apex were instrumented to size 50/. 04 using the Mtwo rotary system. They were then randomly divided into three experimental groups based on obturation technique and sealer (G1: AH Plus obturated by warm vertical compaction, G2: EndoSequence BC Sealer obturated by sealer-based technique, and G3: EndoSequence BC Sealer obturated by warm vertical compaction), and two control groups. After their completed obturations, the samples were stored in containers of 100 percent relative humidity for seven days. Microleakage was assessed using fluid filtration method, employing a pressure equivalent to 30 cmH2O through a 1-mm diameter capillary tube. Statistical analysis was performed using the one-way ANOVA test followed by Dunnett T3 for multiple comparison tests at the 0.05 significance level. Results: The leakage rate of EndoSequence BC Sealer by sealer-based technique group were statistically significantly higher than EndoSequence BC Sealer by warm vertical compaction group (p = 0.013). However, no significant difference was found between the AH Plus group and both the EndoSequence BC Sealer groups (p > 0.05).
Design and Simulation of 3D Printed Check Valves Using Fluid- Structure Interaction

Passive, one-way valves, also known as check valves, while common at the macro scale, are an essential microfluidic feature that facilitates flow rectification. These structures are commonly used in micropump configurations to control flow. Check valves have numerous applications within microfluidics with the large majority being fabricated by replica molding. There has been a shift towards 3D printing microfluidics to reduce the time and cost associated with developing prototypes. Only a handful of studies have developed microvalves using stereolithography (SLA). However, fused deposition modeling (FDM) printers are more widely available and cost effective compared to SLA. This study focused on analyzing the range of valve thicknesses necessary to promote forward flow using commonly available FDM filaments. An arbitrary LagrangianEulerian model, a form of fluid-structure interaction (FSI), was set-up in COMSOL Multiphysics 4.2a. Five 3D printer filament materials were compared in simulations of valve deformation over a 0.75 second transient period using the material properties of PDMS as a baseline. The maximum valve deflection for ABS, nylon, PETG, PLA, and TPU was 3.34, 3.08, 3.37, 3.00, and 6.45 μm, respectively. The simulation resulted in a maximum valve deformation of 6.65 μm for PDMS. As expected, materials with a Young’s modulus close to PDMS allows valve structures to actuate with adequate forward flow.
Automatic Fusion of Three-Dimensional Surfaces

This project’s goal is to present an automatic approach to three-dimensional reconstruction of an object with arbitrary topology, based on surface fusion. This approach uses previously aligned surfaces and copes with both alignment errors and scanner noise. The proposed method consists of two major steps: the extraction of an isosurface distant from the object’s real surface followed by ray casting from this surface towards the existing range images. By using the intersection points between theses rays and these range images, an estimate position of the object’s real surface is attained. The combination of these two steps, contrary to other methods, takes full advantage of the available information provided by the range images. This yields a reduction in both alignment errors and scanner noise disturbances. Experimental results demonstrate that this method successfully reconstructs the surface of an object with arbitrary topology.
Intelligent agent for call center: Using data mining techniques and OLAP for automatic answering internet usage problems

This study proposes a system for an automatic question analysis and answering using data mining techniques and OLAP. By applying information extraction techniques, relevant information is taken out from of the Internet connection questions provided by users. By using data mining, user profiles and their questions on the Internet usage are used as input for the system. Two steps clustering by SOM and K-Means algorithms are used to segment user data on their characteristics which obtained from user profile. Then output from clustering and question extraction are used for OLAP (Online Analytical Processing) to analyze the cause of the Internet usage problems. After internet usage questions have been asked to the systems, the answers for solving the Internet connections for cases are replied interactively. Results from this study reveal that it is practical to develop an automatic question answering system. The proposed automatic system had been tested with sample questions from the Internet Service Provider, Call Center in Thailand. Precision of the automatic system is about 70% which is good. This study offers useful information regarding the areas of data mining for Call Center or Customer Relationship Management Center.
Durability of Hybrid Large Area Additive Tooling for Vacuum Infusion of Composites

Durability of Hybrid Large Area Additive Tooling for Vacuum Infusion of Composites Nathan Joseph Northrup Department of Manufacturing Engineering, BYU Master of Science The purpose of this research was to scientifically validate potential cost-saving measures for production of large area additively manufactured tooling for vacuum infusion of composites. These cost saving measures included using a hybrid additive/subtractive manufacturing system to fabricate the mold, requiring lower capital cost and creating shorter lead times. Fiberglass reinforcement was used instead of carbon in the mold material. The validation was done by designing and fabricating a mold for a custom test artifact and analyzing the surface geometry over the course of multiple infusions until tool failure. After printing and machining, the mold required a sealer in order to maintain vacuum integrity. The mold was able to produce 10 parts successfully before the sealed tool surface began to tangibly roughen, resulting in increased difficulty of demolding and a rougher surface finish. After the 14th infusion, the part required destructive force to be removed from the mold. The surface geometry remained consistent within ±0.5 mm of the design over the course of the infusions, and no significant trends in tool wear were observed during this time. In order to quantify the change in roughness, profilometry measurements were taken on the finished mold, and the measured area roughness value SA changed from 0.293 μm to 2.27 μm over the course of the infusions. Based on these results, it was concluded that an increase in surface adhesion is the principal mode of tool failure over the life of these tools. In addition, it was concluded that the minimum tool life for this combination of mold making methods and materials is 14 parts, as this result was obtained under an extreme case in abrasive part geometry and materials for vacuum infusion processing. Thus, this combination of methods and materials is suitable for prototyping of composite parts or short production runs.
Semantic Segmentation of Cranial computed tomography scans using U-nets

Neuroimaging has introduced numerous modalities to support clinical diagnostics. Thanks to its wide availability and affordability, most primary care units and hospitals utilise computed tomography (CT) for the initial assessment of neurodegenerative diseases such as, dementia disorders, most often to assess brain integrity visually and to exclude co-pathologies. Furthermore, CT provides short scan times; which makes it suitable for restless and uncooperative patients, as is often the case in the later stages of dementia. However, in specialized clinical and research settings, magnetic resonance imaging (MRI) is predominantly used for brain segmentation of grey matter (GM), white matter (WM) and cerebrospinal fluid (CSF) which allows automated quantitative approaches to assess brain integrity and derive regional tissue volumes. [1] Here, we present an automatic deep learning approach to improve the usability of clinical CT with regards to quantifying and visualizing different tissue classes of brain. Little has been explored in terms of computational CT segmentation, existing methods employ manual labels to develop segmentation algorithms. [2] We propose a CT segmentation method based on training deep learning models on automated MRI segmentation labels extracted with existing brain segmentation software, SPM12[3]. The MRI labels thus functions as input for training a deep learning model to perform segmentation of a CT scan as comparable to the corresponding MRI scan. We employed U-Net, a deep learning network designed for biomedical image semantic segmentation, which enables the classification of input image information at a pixel (2D) or voxel (3D) level. The ultimate goal of our study is to create a deep learning model that accepts CT scans as input and predicts tissue classes in individual space independent of MRIderived information with accuracy comparable to existing MRI segmentation methods.
Performance limitations of 40 Gb/s SSB MB-OFDM metropolitan networks induced by phase-to-intensity conversion of laser phase noise

Multi-band (MB) orthogonal frequency division multiplexing (OFDM) signals have recently been proposed to be used in optical metropolitan (metro) networks. MB-OFDM signals transmission provides increased bandwidth allocation flexibility, high spectral efficiency, higher capacity provisioning granularity and high tolerance to linear fibre distortion effects. Metro network implementation cost restriction can be meet by employing direct-detection (DD) OFDM. However, although DD-OFDM presents robustness against phase fluctuations, fibre chromatic dispersion (CD) causes phase-to-intensity conversion of laser phase noise, leading to performance degradation in DD-OFDM systems. The objective of this work is to evaluate through numerical simulation the maximum laser linewidth and maximum reach of a 40 Gb/s single sideband (SSB) MB-OFDM metro ring limited by laser phase noise. In this work, the transmission of MB-OFDM signals employing virtual carriers is studied. For a 3-band MBOFDM system with laser linewidths as high as 5 MHz, it is demonstrated that the penalty of the required optical signal-to-noise ratio (OSNR) to achieve a bit error rate (BER) of 10−3 after a fibre span of 500 km does not exceeds 1 dB. The results considering a real network show that, using a Gaussian BS, it is possible to transverse 5 fibre spans of 40 km with a maximum laser linewidth of 10 kHz for BER < 10−3. A highly selective 2nd-order super Gaussian BS is also evaluated and it is shown that the MB-OFDM signal can travel through more than 7 spans of 40 km for laser linewidths up to 100 kHz.
CMOS Digital Circuits Test Preparation (September 2007)

—The test flow that is currently used by AMI Semiconductor (AMIS) is starting to be not enough for providing an acceptable fault detection level. A new test flow is developed in partnership with AMIS, one that is optimized in both fault detection and total number of test patterns, using commercial software such as Tetramax®, from Synopsys®, the Programming Language Interface (PLI), and Verilog-XL®, from Cadence®. Two voltage fault models are used: Line Stuck-At (LSA), Bridging (BRI), and one current fault model: Idd quiescent (IDDQ). With this new test flow it is possible to obtain, in average, a reduction of 36.71% in the number of voltage test vectors, and a bridging fault detection 8.65% superior, for the benchmark circuits that are tested, when compared with the test flow presently used by AMIS.
Deep Learning Based Bayesian Filtering for Catheter Tip Tracking in X-ray Fluoroscopy

Medical instrument tracking is beneficial for motion compensation in image guidance during interventions. In this paper, we propose a deep learning based Bayesian filtering approach for accurate and robust tracking of catheter tip in X-ray fluoroscopy. The approach integrates the detection outcome of a deep neural network and the motion estimation between X-ray images using a particle filtering framework. The proposed method has been validated on 34 clinical X-ray sequences, achieving accurate catheter tip tracking in the experiment, showing the potential of being used in image guidance for interventions.
Planning under Uncertainty for Search and Rescue

Partially observable Markov decision processes (POMDPs) provide a framework for planning under uncertainty. We present an application of POMDPs in a realistic search and rescue situation. Specifically, the aim of the problem is to find victims in a disaster environment. We will define, implement and test a POMDP model that suits the problem and its characteristics. The environment and its features will be learned (by letting the robot interact with it) and taken into account when building the model. It can be concluded that POMDP based solutions, and this solution in particular, work well in these search and rescue scenarios.
Monolithic Power Combiners in CMOS technologies for WLAN applications

This paper presents a study of different monolithic power combining structures. The first step was to analyze using an electromagnetic simulator some circular spiral inductors and compare the results with experimental measurements. The simulator is a 2.5-D electromagnetic simulator, the ADS Momentum. The inductors were made in CMOS 0.18 μm technology. The most common power combining structures are coupled inductors transformer, transmission line transformer and LC baluns. Wilkinson coupler and branchline coupler are included in this paper. These structures are studied in this dissertation and later will be designed with the least possible insertion losses. Finally a selected power combiner will be built and included in a power amplifier application. Keywords-component; Inductors; Transformers; Power Combiners; Radio-Frequency; CMOS
Probabilistic Roadmaps for Aircraft 4D Path Planning

The responsible entities for Air Traﬃc Management (ATM) around the world are integrating innovative procedures to cope with the constant rise in air traﬃc. New technologies such as System Wide Information Management (SWIM) aim at improving the eﬃciency and safety levels of operations while reducing costs and emissions. The SWIM program releases an overwhelming amount of aviation information in a machine-readable format, which is not fully exploitable by humans. To leverage aviation data, a Smarter Auto-Flight Control System (SAFCS) is being developed, which continuously monitors, analyzes, plans and executes airborne missions. It supports pilot decision making by suggesting routes computed by path planning algorithms. Probabilistic Roadmap (PRM) is a path planning algorithm particularly eﬃcient at dealing with high dimensional problems and multiple queries. First, it creates a graph by sampling the planning environment and then resorts to a search algorithm for computing a path. Over the last two decades, PRM has been subject to several research papers, some of which extend it to include anytime, dynamic and online capabilities. The SAFCS framework and the integration of the PRM planning family are meticulously discussed. Solid reasoning is provided for the changes introduced relatively to the original algorithms. Lastly, the planners’ performance is subject to evaluation and the conclusions drawn from results are stated.
Multi-Scale Approach for Self-Assembly 3 and Protein Folding

Self-assembly, driven by non-covalent interactions like van der Waals and hydrogen 7 bonds, fulfills a crucial role in the supramolecular organization and assembling of 8 the biological matter. Living being are complex organisms where matter is self9 organized on different length scales in a kind of biological network. A primary 10 role is played by the proteins that control the majority of chemical processes in 11 the cell. Proteins are synthesized as long polymer chains composed by hundreds 12 of monomers, taken from 20 different amino acids. Among the huge amount of 13 possible amino acid sequences, nature has selected those that are able to fold into 14 specific functionalized structures, known as native protein structures. The relation 15 between the sequence code and the native structure and the way that proteins fold 16 represents a significant example of biological self-assembly. 17
Image Fusion for the Detection of Camouflaged People

— The use of thermal imaging is a benefit for the Armed Forces. Due to their advantages, they have a large number of applications, including the detection of camouflaged people. For better results, the thermal information can be merged with the color information which allows a greater detail, resulting in a greater degree of security. The present study implemented as pixel level image fusion methods: Principal Components Analysis; Laplacian Pyramid; and Discrete Wavelet Transform. A qualitative analysis concluded that the method which performs better is the one that uses Wavelets, followed by the Laplacian Pyramid and finally the PCA. A quantitative analysis was made using as performance metrics: Standard Deviation, Entropy, Spatial Frequency, Mutual Information, Fusion Quality Index and Structural Similarity Index. The values obtained support the conclusions drawn from the qualitative analysis. The Mutual Information, Fusion Quality Index and Structural Similarity Index are the appropriate metrics to measure the quality of image fusion as they take into account the relationship between the fused image and the input images.
Bandwidth-Aware Page Placement in NUMA

Page placement is a critical problem for memory-intensive applications running on a shared-memory multiprocessor with a non-uniform memory access (NUMA) architecture. State-of-the-art page placement mechanisms interleave pages evenly across NUMA nodes. However, this approach fails to maximize memory throughput in modern NUMA systems, characterized by asymmetric bandwidths and latencies, and sensitive to memory contention and interconnect congestion phenomena.We propose BWAP, a novel page placement mechanism based on asymmetric weighted page interleaving. BWAP combines an analytical performance model of the target NUMA system with on-line iterative tuning of page distribution for a given memory-intensive application. Our experimental evaluation with representative memory-intensive workloads shows that BWAP performs up to 66% better than state-of-the-art techniques. These gains are particularly relevant when multiple co-located applications run in disjoint partitions of a large NUMA machine or when applications do not scale up to the total number of cores.