Miracle-dz/UniFAR-FTUs huggingface dataset:
Quality Control of Outsourced LiDAR Data Acquired with a UAV: A Case Study

Over the last few decades, we witnessed a revolution in acquiring very high resolution and accurate geo-information. One of the reasons was the advances in photonics and LiDAR, which had a remarkable impact in applications requiring information with high accuracy and/or elevated completeness, such as flood modelling, forestry, construction, and mining. Also, miniaturization within electronics played an important role as it allowed smaller and lighter aerial cameras and LiDAR systems to be carried by unmanned aerial vehicles (UAV). While the use of aerial imagery acquired with UAV is becoming a standard procedure in geo-information extraction for several applications, the use of LiDAR for this purpose is still in its infancy. In several countries, companies have started to commercialize products derived from LiDAR data acquired using a UAV but not always with the necessary expertise and experience. The LIDAR-derived products’ price has become very attractive, but their quality must meet the contracted specifications. Few studies have reported on the quality of outsourced LiDAR data acquired with UAV and the problems that need to be handled during production. There can be significant differences between the planning and execution of a commercial project and a research field campaign, particularly concerning the size of the surveyed area, the volume of the acquired data, and the strip processing. This work addresses the quality control of LiDAR UAV data through outsourcing to develop a modelling-based flood forecast and alert system. The contracted company used the Phoenix Scout-16 from Phoenix LiDAR Systems, carrying a Velodyne VLP-16 and mounted on a DJI Matrice 600 PRO Hexacopter for an area of 560 ha along a flood-prone area of the Águeda River in Central Portugal.
Performance of a Reduced NOx Diffusion Flame Combustor for the MS5002 Gas Turbine

This paper describes a reduced NOx diffusion flame combustor that has been developed for the MS5002 gas turbine. Laboratory tests have shown that when firing with natural gas, without water or steam injection, NOx emissions from the new combustor are about 40% lower than NOx emissions from the standard MS5002 combustor. CO emissions are virtually unchanged at base load, but increase at part load conditions. The laboratory results were confirmed in 1997 by a commercial demonstration test at a British Petroleum site in Prudhoe Bay, Alaska.The standard MS5002 gas turbine is equipped with a conventional, swirl stabilized diffusion flame combustion system. The twelve standard combustors in an MS5002 turbine are cylindrical cans, approximately 27 cm (10.5 inches) in diameter and 112 cm (44 inches) long. A small, annular, vortex generator surrounds the single fuel nozzle that is centered at the inlet to each can. The walls of the cans are louvered for cooling, and contain an array of mixing and dilution holes that provide the air needed to complete combustion and dilute the burned gas to the desired turbine inlet temperature.The new, reduced NOx emissions combustor (referred to as a “lean head end”, or LHE, combustor) retains all of the key features of the conventional combustor: the only significant difference is the arrangement of the mixing and dilution holes in the cylindrical combustor can. By optimizing the number, diameter, and location of these holes, NOx emissions were substantially reduced. The materials of construction, fuel nozzle, and total combustor air flow were unchanged.The differences in NOx emissions between the standard and LHE combustors, as well as the variations in NOx emissions with firing temperature, were well correlated using turbulent flame length arguments. Details of this correlation are also presented.Copyright © 1999 by ASME
A Classification Scheme for Sediments and Habitats on Exposed Intertidal Flats with Multi-Frequency Polarimetric SAR

We developed an extension of a previously proposed classification scheme that is based upon Freeman–Durden and Cloude–Pottier decompositions of polarimetric Synthetic Aperture Radar (SAR) data, along with a Double-Bounce Eigenvalue Relative Difference (DERD) parameter, and a Random Forest (RF) classifier. The extension was done, firstly, by using dual-copolarization SAR data acquired at shorter wavelengths (C- and X-band, in addition to the previously used L-band) and, secondly, by adding indicators derived from the (polarimetric) Kennaugh elements. The performance of the newly developed classification scheme, herein abbreviated as FCDK-RF, was tested using SAR data of exposed intertidal flats. We demonstrate that the FCDK-RF scheme is capable of distinguishing between different sediment types, namely mud and sand, at high spatial accuracies. Moreover, the classification scheme shows good potential in the detection of bivalve beds on the exposed flats. Our results show that the developed FCDK-RF scheme can be applied for the mapping of sediments and habitats in the Wadden Sea on the German North Sea coast using multi-frequency and multi-polarization SAR from ALOS-2 (L-band), Radarsat-2 (C-band) and TerraSAR-X (X-band).
Deep Localization of Static Scans in Mobile Mapping Point Clouds

Mobile laser scanning (MLS) systems are often used to efficiently acquire reference data covering a large-scale scene. The terrestrial laser scanner (TLS) can easily collect high point density data of local scene. Localization of static TLS scans in mobile mapping point clouds can afford detailed geographic information for many specific tasks especially in autonomous driving and robotics. However, large-scale MLS reference data often have a huge amount of data and many similar scene data; significant differences may exist between MLS and TLS data. To overcome these challenges, this paper presents a novel deep neural network-based localization method in urban environment, divided by place recognition and pose refinement. Firstly, simple, reliable primitives, cylinder-like features were extracted to describe the global features of a local urban scene. Then, a probabilistic framework is applied to estimate a similarity between TLS and MLS data, under a stable decision-making strategy. Based on the results of a place recognition, we design a patch-based convolution neural network (CNN) (point-based CNN is used as kernel) for pose refinement. The input data unit is the batch consisting of several patches. One patch goes through three main blocks: feature extraction block (FEB), the patch correspondence search block and the pose estimation block. Finally, a global refinement was proposed to tune the predicted transformation parameters to realize localization. The research aim is to find the most similar scene of MLS reference data compared with the local TLS scan, and accurately estimate the transformation matrix between them. To evaluate the performance, comprehensive experiments were carried out. The experiments demonstrate that the proposed method has good performance in terms of efficiency, i.e., the runtime of processing a million points is 5 s, robustness, i.e., the success rate of place recognition is 100% in the experiments, accuracy, i.e., the mean rotation and translation error is (0.24 deg, 0.88 m) and (0.03 deg, 0.06 m) on TU Delft campus and Shanghai urban datasets, respectively, and outperformed some commonly used methods (e.g., iterative closest point (ICP), coherent point drift (CPD), random sample consensus (RANSAC)-based method).
Frequency Spectrum of Crystalline Solids

It is generally accepted that a normal crystalline solid can be pictured at absolute zero as an assembly of molecules arranged at periodically placed lattice points. Since at higher temperatures each molecule becomes a harmonic oscillator about its lattice point, in order to calculate thermodynamic properties of the crystal it is necessary to know the distribution of its internal normal modes of vibration. On the basis of the Born‐von Karman model these normal modes of vibration are roots of a secular determinant. In this paper it is shown that the 2nth moment of the distribution function of normal modes is proportional to the trace of the nth power of the matrix of the Born‐von Karman determinant. By expressing the distribution function as a linear combination of Legendre polynomials it is shown that the coefficient of each polynomial is a linear combination of the moments. The frequency distribution function of a two‐dimensional simple cubic lattice is calculated by the above method and turns out to hav.
Fe $_{3}$ O $_{4}$ Incorporated AOT-Alginate Nanoparticles for Drug Delivery

Composite nanoparticles of aerosol OT-alginate hydrogel loaded with Fe3O4 and rhodamine 6G (R6G) in average diameter between 25 nm and 50 nm were synthesized by emulsification-cross-linking process and characterized by transmission electron microscopy (TEM) and SQUID magnetometery measurements. TEM measurements show that the Fe3O4 particles are uniformly distributed within AOT-alginate nanoparticles. The Ca2+ cross-linked AOT-alginate nanoparticles loaded with Fe3O4 and rhodamine showed superparamagnetic behavior at room temperature with saturation magnetization of ~50 emu/g of Fe3 O4. Similar behavior was exhibited by Fe2+ cross-linked AOT-alginate nanoparticles loaded with Fe3O4 and rhodamine except it showed twice the magnetization of Ca2+ crosslinked counterpart. A decrease in the amount of rhodamine loading for the composite nanoparticle systems as compared to the bare AOT-alginate nanoparticles was found.
Investigation of the mechanisms of bacterial inactivation induced by a cold atmospheric pressure plasma jet for burn wound treatment

Biological applications of cold atmospheric pressure plasma sources such as disinfection of human tissue and medical equipment and more recently wound healing have gained increasing interest in recent years. The beneficial effects of plasma treatment are commonly thought to originate from symbiotic effects of the so-called ’plasma cocktail’, consisting of plasma emitted electrons and ions, radicals, (V)UV, heat and electromagnetic fields. This work focuses on the possibilities of cold atmospheric pressure plasma jet treatments of burn wounds, as bacterial infections occur frequently in burn wound patients. Atmospheric pressure plasmas may provide additional means to reduce the bacterial concentration on a burn wound while minimizing the damage inflicted on surrounding tissue. The research presented here is performed in collaboration with the Association of Dutch Burn Centres. The biological part of this work focuses on the in vitro treatment of the bacterium Pseudomonas aeruginosa, but preliminary treatments of Staphylococcus aureus and human cells (keratinocytes and fibroblasts) are also presented. Keratinocytes and fibroblasts need to be submerged in liquid to avoid dehydration. Because of this, for the treatments of both bacteria and human cells to be comparable, the treatments of bacteria are performed in a liquid medium rather than on a surface. The atmospheric pressure plasma jet used for the biological treatments is characterized by measurements of power dissipation, gas temperature, absolute UV-flux as well as mass spectrometry measurements of emitted ions. The effects of plasma treatment of water are studied by performing liquid ion chromatography and hydrogen peroxide concentration measurements on treated samples. Additionally, an estimation is made of the fluid chemistry induced by the radical flux on the surface of the liquid by solution kinetics calculations. The effects of each of the possible active components in the ’plasma cocktail’ is analyzed and compared to similar experiments reported in literature. In the experiments presented in this work the effect of the plasma can be solely ascribed to plasma induced fluid chemistry, leading to the production of stable and transient chemical species. It is shown that HNO2, ONOO− and H2O2 are present in significant quantities which could explain (with inclusion of symbiotic effects) the bacterial inactivation observed in this work. The reasons for neglecting the influences of the other components of the ’plasma cocktail’ are extensively discussed and motivated by a large parameter study of both plasma and treatment conditions.
Quantitative analysis of gibberellins by isotope dilution mass spectrometry: a comparison of the use of calibration curves, an isotope dilution fit program and arithmetical correction of isotope ratios

The quantitative analysis of gibberellin A1 (GA1) in apices of 19-day-old seedlings of Pisum sativum L. cultivar Alaska is described using isotope dilution mass spectrometry. Three methods are compared for determining the dilution of isotope in the internal standards, [17-H-2(2)]GA1 and [2beta-H-2(1)]GA1. Similar results were obtained with each method. The use of calibration curves gave the most precise determination with [H-2(2)]GA1 as internal standard irrespective of the amount added. The use of an isotope dilution fit program was more precise using [H-2(1)]GA1 as internal standard. A simpler arithmetical correction procedure gave consistently higher estimates with both internal standards. The relative merits of the methods are discussed and the requirements for reliable quantification by isotope dilution gas chromatography-mass spectrometry are presented.
The impact of FDI on firms’ survival in Italy: evi dence on horizontal and vertical spillovers

The aim of this paper is to explore a new issue in the literature on the “indirect effects” of FDI: th e impact on firm survival. This is done by checking b oth within industry (horizontal) and between industry (vertical) spillovers through forward and backward linkages and also testing whether there is a difference in the patterns of FDI spillovers e xp rienced in high and low technology industries. The empirical analysis is conducted using a firm le ve database for the period 2002-2009 resulting from the intersection of three different sources: I X Survey 2001-2003 on Manufacturing Firms, by Capitalia/Unicredit, AIDA (Analisi Informatizzata d elle Aziende) and Mint-Italy, by Bureau Van Dyck. This original database provides a rich micro evidence on a stratified and randomly selected sample of more than 4,000 Italian manufacturing fir ms. The econometric analysis relies on Probit and Cox proportional hazard estimates of the relati onship between firm survival and horizontal and vertical FDI, measured respectively as output share of sales of foreign firms in the market and as a share of foreign firms sales in supplier (upstream) and buyer (downstream) industries, and controlling for a rich set of firm and industry spe cific variables following the survival literature. The study contributes to a very restricted and recent s trand of research which estimates the role of horizontal and vertical FDI spillovers on survival (Girma and Gong, 2008; Wang, 2010). Our findings reveal that within the same industry survival of firms in Italy is unaffected by the increased presence of oreign-owned firms . On the other hand, at intraindustry level, firms experience less exits if they benefit from more intense upstream in ter-industry linkages with foreign firms (positive vertical upstream spillovers) while tend to have sh orter lives if affected by affiliates operating in downstream industries (negative vertical downstream spillovers). Furthermore, a different impact is observed in high and low technology sectors and the technology gap between local and foreign firms matters for spillover effects. These results are broadly consistent with the evidence that competition from sectoral FDI does not help firm su rvival while this is affected positively by interindustry spillovers (Wang, 2010). The result is als o in line with the analyses of spillover effects of FDI on productivity of Italian manufacturing firms which also found no evidence of intra-industry FDI spillovers but consistent positive vertical spi llovers. JEL classification: F21, F23, F29, O3, L25, C41, J31
Comparing and Evaluating GPU Platforms with a Single Point

We have seen from the literature that it’s not immediate to compare performance results from different published research papers. We propose a methodology to summarize typical curves used to indicate the performance of a given computing platform. We present performance of matrix multiplication on a GPU platform using a single point. We form clusters of points with similar performance values. We have found three clusters for the SGEMM, SGEMM & DGEMM, and DGEMM. We compare and evaluate platforms in these clusters based on the underlying hardware platform, precision, algorithm, library, etc.
Model-Based Fuzzing Using Symbolic Transition Systems

As software is getting more complex, the need for thorough testing increases at the same rate. Model-Based Testing (MBT) is a technique for thorough functional testing. However, MBT cannot perform non-functional security testing. Fuzzing is a technique for automatically detecting vulnerabilities in software. Many diﬀerent fuzzing approaches have been developed in the last years, ranging from random black-box to grammar-based white-box with structured input. In this research, we conduct a systematic review of state-of-the-art fuzzers and perform experiments where we combine multiple fuzzing approaches with MBT. Ultimately, we will choose the fuzzer that performs best, and integrate it into an MBT toolset. We reviewed state-of-the-art fuzzing techniques and implementations and composed a list of candidate fuzzers that can be used in combination with MBT. We developed a generic wrapper that enables a model-based System Under Test (SUT) to be fuzzed with American Fuzzy Lop (AFL), a popular general-purpose fuzzer. Additionally, we developed a dictionary generator, that extracts basic model information and supplies it to AFL.
AFFORDANCES THEORY IN INFORMATION AND COMMUNICATION TECHNOLOGY FOR DEVELOPMENT (ICT4D) RESEARCH

Information and Communication Technology for Development (ICT4D) is argued to have high potential value across all sectors, both public and private; and at multiple levels, be it fighting poverty; improving healthcare; providing better education; fostering gender equality or extending global partnerships for development. Despite this significance and huge potential, it is still not clear, to what extent ICTs are contributing to development, especially that of the relatively poor members of the society. Affordances Theory which has roots in ecological psychology has in the recent past been used in Information Systems (IS) research. This paper explores how affordances theory has been used in ICT4D research. A review of literature was conducted and recommendations made
Factor Screening Techniques for Combat Simulation Models

A stochastic simulation model can be viewed as a system that takes a series of input variables, and then processes them to produce a realisation of the required simulation scenario output. This model will contain a set of parameters, known as factors, that characterise the simulation process. There may in fact be significant complexity with the underlying simulation architecture, and additionally there may be a very large number of factors. The cost of this is slow performance in simulation run times. In many cases there may be factors in the underlying model that are insignificant statistically in the scenario of interest. This phenomenon is referred to as the parsimony principle, or the Pareto 80-20 rule. Hence there is much interest in the scientific literature on the screening of factors in the underlying meta-model applied to the dynamical system. This report thus investigates the subject of factor screening, for stochastic simulation models, and overviews several solutions to this problem. In particular, sequential bifurcation will be shown to provide a very efficient approach to the problem of factor screening, in comparison to standard one factor at a time classification methods. Several variations of sequential bifurcation will be examined, and their performance in several factor screening examples will be investigated. Directions for possible future research will also be discussed. RELEASE LIMITATION Approved for Public Release UNCLASSIFIED
Non-Newtonian fluid flow and heat transfer in an inclined channel with discrete Heat sources

In this paper, the mixed convection in an inclined square channel with seven discrete heat sources has been studied numerically. The heat sources have been constructed flush mounted with channel bottom wall. The working fluid is non-Newtonian, power-law fluid. A FORTRAN program has been written for solution of governing equations by finite difference method. The effect of power-law index, Pe number, Ri number and inclination angle on heat transfer and flow characteristics have been studies using the numerical results.
A NEW ASSOCIATION CLASSIFICATION BASED METHOD FOR DETECTING PHISHING WEBSITES

Impacting businesses across the world, phishing remains today to be a serious problem: due to anonymous access to personal details, businesses and their consumers deal with the problems materialised out of fishing attacks, huge financial loss being one of these problems. Because of this, phishing needs to be identified and dealt with efficiently using intrusion detection techniques; such mechanisms are yet to be used. It is within this paper that, with the use of a newly-arisen method (Phishing Multi-Class, founded on the grounds of Association Rule) we will study the issue of predicting phishing websites. So as to weigh up the successful use of data mining algorithms using a publicly available dataset involving 10,068 incidents of legitimate and phishing websites, two experimental studies were conducted, in which the classifier model was built. In the first of these two studies, the capability of PMCAR (Phishing Multi-Class Association Rule) compared to three associative classification algorithms (CBA, MCAR, and FACA) was examined; additionally, five benchmark algorithms (SVM, LR, DT, and ANN) were assessed in the second experiment, so as to generalise the competence of utilising data mining for resolving the phishing websites detection issue. As a result of conducting these experiments, all data mining algorithms that were evaluated predict phishing websites with decent classification rate; and so we can conclude that, when looking to tackle the issue of predicting phishing websites, these can be successful methods.
Eric C

This report summarizes surveys conducted during August and September of 2017 to assess the presence of giant gartersnakes (GGS) on the Natomas Basin Conservancy’s (TNBC) Cummings Tract (tract) in Sacramento County, California. Methods included a mixed approach of visual encounter surveys (VES) and aquatic trapping surveys, the latter utilizing adaptive Bayesian protocols intended to address low detection probabilities associated with the species’ cryptic and wary nature. However, because even rigorous trapping has failed to detect GGS occurring at low or diminishing densities in other parts of its range, we also applied recently-developed environmental DNA (eDNA) sampling techniques in the hope of increasing survey sensitivity.