Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Hybrid Symbiotic Organism Search on Flow Shop Scheduling with a New Learning Effect

The present article proposes a hybrid learning effect model which takes into account the previous experience of the operator, separates the machine/manual times and considers truncation. The developed model is fitted to experimental data to investigate its accuracy. The fits are compared with those of four other well-known position based learning models. Next, each learning model is applied to the large scale flow shop problems which makes them strongly NP - hard. Hence, the problems are tackled by a hybrid meta-heuristic named Symbi-otic Organism Search Simulated Annealing ( SOS-SA ). The algorithm combines the fast and easy implementation of SOS with the powerful local search of SA . The proposed algorithm is tested on flowshop benchmark problems and the results show its validation.
Semantic Segmentation of Urban Buildings from VHR Remote Sensing Imagery Using a Deep Convolutional Neural Network

Urban building segmentation is a prevalent research domain for very high resolution (VHR) remote sensing; however, various appearances and complicated background of VHR remote sensing imagery make accurate semantic segmentation of urban buildings a challenge in relevant applications. Following the basic architecture of U-Net, an end-to-end deep convolutional neural network (denoted as DeepResUnet) was proposed, which can effectively perform urban building segmentation at pixel scale from VHR imagery and generate accurate segmentation results. The method contains two sub-networks: One is a cascade down-sampling network for extracting feature maps of buildings from the VHR image, and the other is an up-sampling network for reconstructing those extracted feature maps back to the same size of the input VHR image. The deep residual learning approach was adopted to facilitate training in order to alleviate the degradation problem that often occurred in the model training process. The proposed DeepResUnet was tested with aerial images with a spatial resolution of 0.075 m and was compared in performance under the exact same conditions with six other state-of-the-art networks—FCN-8s, SegNet, DeconvNet, U-Net, ResUNet and DeepUNet. Results of extensive experiments indicated that the proposed DeepResUnet outperformed the other six existing networks in semantic segmentation of urban buildings in terms of visual and quantitative evaluation, especially in labeling irregular-shape and small-size buildings with higher accuracy and entirety. Compared with the U-Net, the F1 score, Kappa coefficient and overall accuracy of DeepResUnet were improved by 3.52%, 4.67% and 1.72%, respectively. Moreover, the proposed DeepResUnet required much fewer parameters than the U-Net, highlighting its significant improvement among U-Net applications. Nevertheless, the inference time of DeepResUnet is slightly longer than that of the U-Net, which is subject to further improvement.
Bias by default ? A means for a priori interface measurement

Systems have biases. Their interfaces naturally guide a user toward specific patterns of action. For example, modern word-processors and spreadsheets are both capable of handling word wrapping, checking spelling, and calculating formulas. You could write a paper in a spreadsheet or could do simple business modeling in a wordprocessor. However, their interfaces naturally communicate which function they are designed for. Visual analytic interfaces also have biases. We outline why simple Markov models are a plausible tool for investigating that bias, even prior to user interactions, and how they might be applied to understand a priori system biases. We also discuss some anticipated difficulties in such modeling and touch briefly on what some Markov model extensions might provide.
WP / 17 / 95 Tax Administration and Firm Performance : New Data and Evidence for Emerging Market and Developing Economies

Tax compliance costs tend to be disproportionately higher for small and young businesses. This paper examines how the quality of tax administration affects firm performance for a large sample of firms in emerging market and developing economies. We construct a novel, internationally comparable, and multidimensional index of tax administration quality (the TAQI) using information from the Tax Administration Diagnostic Assessment Tool. We show that better tax administration attenuates the productivity gap of small and young firms relative to larger and older firms, a result that is robust to controlling for other aspects of tax policy and of economic governance, alternative definitions of small and young firms, and measures of the quality of tax administration. From a policy perspective, we provide evidence that countries can reap growth and productivity dividends from improvements in tax administration that lower compliance costs faced by firms. JEL Classification Numbers: E62; H30; H63
Design and Simulation of Control Technique for Permanent Magnet Synchronous Motor Using Space Vector Pulse Width Modulation

After the rapid advancement in the field of power electronics devices and drives for last few decades, there are different kinds of Pulse Width Modulation techniques which have been brought to the market. The applications ranging from industrial appliances to military equipment including the home appliances. The vey common application for the PWM is three phase voltage source inverter, which is used to convert DC to AC in the homes to supply the power to the house in case electricity failure, usually named as Un-interrupted Power Supply. In this paper Space Vector Pulse Width Modulation techniques is discussed and analysed under the control technique named as Field Oriented Control. The working and implementation of this technique has been studied by implementing on the three phase bridge inverter. The technique is used to control the Permanente Magnet Synchronous Motor. The drive system is successfully implemented in MATLAB/Simulink using the mathematical equation and algorithm to achieve the satisfactory results. PI type of controller is used to tuned ers of the motothe parametr i.e. torque and current.
The Labor Force Effects of Unplanned Childbearing ∗

This paper explores the impact of unplanned births on female labor force participation and income. I estimate the causal effect of birth on a sample of unplanned pregnancies, defined as those that happened while the woman was using contraception. Labor supply and the decision to give birth are jointly determined. Women with high labor force attachment may be more likely to use contraception or to have an induced abortion if contraception fails. I use spontaneous fetal losses as a source of exogenous variation in births. Unplanned births significantly reduce labor force participation, by as much as 25%. This effect is remarkably higher than the estimates traditionally reported in the literature, suggesting that family planning plays a key role in the limited magnitude of previous estimates. The negative impact decreases over the sample period, 1973-2005. There are no significant differences in the effect of an unplanned birth by level of education and its impact on income is small. JEL Classifications: J13, J22, I3
A Nonsingular Elastic Kirchho Formula applied to VSP Data

A two-way elastic Kirchho -type formula is applied to VSP data modelling and imaging for 3-D multi-layered TI media with dipping interfaces and tilted axes of symmetry. It is expressed in terms of causal and advanced ray-theory Green's functions in such a way that both forward and reversetime wave eld extrapolations are invoked and that the result is not singular when the observation point is close to the target. Application to converted-wave near-o set VSP modelling is presented. We compare the 3-D e ects of dip and anisotropy on P-to-S conversions recorded on the horizontal geophones. In migration, we operate directly on the displacement vector, and use both upgoing and downgoing waves together. The migration algorithm is applied to a walkaway VSP data set from the North Sea. The results give us assurance that the technique is su ciently versatile to handle shear wave behavior in complex geological models.
DISADVANTAGED PRIMARY SCHOOL PUPILS REVISITED

In this paper, I evaluate a Dutch area-based subsidy scheme that targets disadvantaged pupils in primary education. In line with the purpose of this subsidy scheme, I hypothesise that the extra funding has a positive impact on pupil performance. The strict eligibility rules of the subsidy scheme allow for a regression discontinuity design, which analyses a select group of observations. I use school-level government data from three school years covering the period 2013 to 2016. Using ordinary least squares models I find no evidence to support the hypothesis. This thesis is submitted in fulfillment of the requirements for the degree of Master of Science in Economics and Business at the Erasmus School of Economics.
A Geometric Approach for Encoding Demonstrations and Learning New Trajectories

We propose a novel learning approach based on differential geometry to extract and encode important characteristics of a set of trajectories captured through demonstrations. The proposed approach represents the trajectories using a surface in Euclidean space called Canal Surface. The surface is formed as the envelope of a family of regular implicit surfaces (e.g. spheres) whose centers lie on a space curve. Canal surfaces extract the essential aspects of the demonstrations and retrieve a generalized form of the trajectories while maintaining the extracted constraints. Given a random initial pose in task space, a new trajectory is reproduced by considering the relative ratio of the initial point with respect to the corresponding crosssection of the obtained canal surface. Our approach produces a continuous representation which is visually perceivable and easily understandable even by non-expert users. Preliminary experimental results using real-world data are presented.
4 INVESTIGATION OF MESOSCALE PRESSURE AND TEMPERATURE TRANSIENTS ASSOCIATED WITH BOW ECHOES

Bow echoes have been an established part of the literature since a 1978 technical report by Fujita– who not only coined the term, but also created a conceptual model showcasing the lifecycle of these systems. The bow echo’s association with severe winds has also been both well-studied and welldocumented, from Fujita’s original work to the present. However, very little work has focused on surface features, such as pressure and temperature, associated with these storms. While the arrangement of these parameters as associated with squall lines has become highly recognizable (including the mesohigh, cold pool, and wake low; Johnson & Hamilton 1988, Loehrer & Johnson 1995), it is still uncertain how strictly these patterns can be applied to the smaller-sized members of the broad class of mesoscale convective systems (MCSs). Utilizing the Oklahoma Mesonet, an observational network of detailed resolution in both time and space, a dataset of surface features associated with 42 different bow echoes in Oklahoma over four years was generated. These systems were examined to determine if there were any common patterns of behavior of the surface pressure and temperature fields associated with bow echoes, and to further determine if there are patterns that are unique to these phenomena. As will be seen, distinctive patterns of behavior were indeed observed, which presents possible opportunities for a more dynamical separation (other than an arbitrary size limit) of bow echoes from typically larger and more commonly occurring squall lines.
A Support Vector Regression-based Approach Towards Decentralized Fault Diagnosis in Wireless Structural Health Monitoring Systems

The reliability of sensors in structural health monitoring (SHM) systems is affected by sensor faults that compromise the quality of monitoring, causing erroneous judgment of structural conditions. To ensure reliable operation of SHM systems, techniques for diagnosing sensor faults have been proposed. In wireless SHM systems, embedding techniques for fault diagnosis (FD) into sensor nodes is of increasing importance as sensor nodes process data on board and communicate analysis results instead of large sets of raw data. As a consequence of on-board processing, raw data is frequently unavailable and sensor faults remain undetected. In this paper, a decentralized fault diagnosis approach based on support vector regression (FD-SVR) is proposed. Due to the high accuracy of the support vector regression (SVR), which can be achieved even with relatively small data sets, the FD-SVR approach enables wireless sensor nodes autonomously selfdiagnose sensor faults, enhancing the reliability of wireless SHM systems without a need for large data sets to be used for fault diagnosis. The ability of the embedded FD-SVR approach to detect and isolate sensor faults, increasing the reliability of sensors in wireless SHM systems, is validated in laboratory experiments.
D Dendrite Reconstruction and Spine Identification

In neuron-biology, 3D neuron dendrite reconstruction followed by spine identification is indispensable for the study of neuronal functions and biophysical properties. In this paper, we propose an automatic dendrite reconstruction method to with a surface representation of the neuron on the basis of a novel level set approach. Our novel level set approach can effectively tackle the problem of segmentation under blurring and intensity in-homogeneity. Then spines are detected based on dendrite medial axis and a label-based thinning strategy is proposed to accurately extract the dendrite skeleton for spine identification. Experimental results reveal that our method works well.
Are uncertainty measures powerful predictors of real economic activity in the Euro Area ?

In the paper we propose and collect measures that are related to different aspects of economic uncertainty and examine their predictive power for real economic activity in the Euro Area. The set of uncertainty measures investigated includes: the European News Index, Economic Policy Uncertainty index, uncertainty indices related to the global financial and commodity markets, and the Euro Area industry uncertainty measures calculated using business surveys provided by the European Commission. Macroeconomic activity indicators used in the study describe production, investment and unemployment. The analysis covers quarterly data from 2000 to 2014. The study is based on the rolling scheme and different specifications of VAR models. Two main conclusions can be drawn. First, uncertainty measures are, to a great extent, independent of one another. Second, some uncertainty indices perform well in forecasting economic activity indicators. It seems, however, that the best strategy is to apply forecast averaging techniques and to combine information provided by all uncertainty
Capturing Soot Formation with the Use of Iso-Octane as a Surrogate for Fischer-Tropsch Fuel

The goal of this work is to support the development of surrogate fuel mixtures that replicate the chemistry and flame characteristics of renewable Fischer-Tropsch (FT) fuels. In particular, we focus on capturing soot formation and growth with the use of iso-octane as a surrogate for FT jet fuel. An axisymmetric, co-flow, laminar flame configuration is used to study soot formation for non-premixed and rich-premixed mixtures at atmospheric pressure. A laser extinction technique is used to obtain spatially resolved soot volume fraction results, and thermocouple measurements provide profiles of gas temperatures in both the radial and axial directions. Comparisons of flame temperature measurements from both FT and iso-octane flames indicate that the temperatures are the same in both the axial and radial profiles within the uncertainty of the measurement. The flame temperatures for the non-premixed flame are 50100 degrees Celsius higher throughout the flame than those for the rich-premixed flame. Laser extinction measurements with both fuels show that the soot volume fraction profiles are very similar for FT fuel and iso-octane. Additional analysis shows the impact of premixing air on soot formation and the differences in time-scales of soot formation with and without the presence of oxygen.
Delivery of Cancer-Testis Antigens Using Self-Assembled Dipeptide Nanotubes Inhibits Tumor Growth in Mice Melanoma Model

Delivery of tumor-associated antigens for cancer immunotherapy is generally limited due to poor stability and low cellular uptake. Use of nanoparticles as delivery vehicles has been an exciting development but toxicity associated with nanoparticles has remained a concern. Here, we have used conformationally constraint self-assembling dipeptide nanotubes for the delivery of Cancer-Testis antigens (CTAs). A dipeptide Phenylalanine-α, β-dehydrophenylalanine (F-ΔF) was synthesized and was found to self-assemble into nanotubes. CTAs (NY-ESO-1 and MAGE-3) were also synthesized and loaded onto F-ΔF nanotubes using physical adsorption method for delivery purposes. CTA loaded F-ΔF nanotubes showed higher cellular uptake in macrophages. In animal studies, F-ΔF-CTA nanocomplex elicited much higher immune response compared to CTAs alone and showed an inhibition of ~65-70% tumor growth in mouse melanoma model. Our results indicated that F-ΔF nanotubes are biocompatible and are efficient delivery vehicles for CTAs in vivo and therefore are excellent candidates for further development as delivery agents.
2 J ul 2 01 8 Source Code Optimization using Equivalent Mutants ✩

Context: A mutant is a program obtained by syntactically modifying a program’s source code; an equivalent mutant is a mutant, which is functionally equivalent to the original program. Mutants are primarily used in mutation testing, and when deriving a test suite, obtaining an equivalent mutant is considered to be highly negative, although these equivalent mutants could be used for other purposes. Objective: We present an approach that considers equivalent mutants valuable, and utilizes them for source code optimization. Source code optimization enhances a program’s source code preserving its behavior. Method: We showcase a procedure to achieve source code optimization based on equivalent mutants and discuss proper mutation operators. Results: Experimental evaluation with Java and C programs demonstrates the applicability of the proposed approach. Conclusion: An algorithmic approach for source code optimization using equivalent mutants is proposed. It is showcased that whenever applicable, the approach can outperform traditional compiler optimizations.
Treating a case of the mumbo jumbos What linguistic features characterize Swedish electronic health records ?

As the ability to access one’s own electronic health record online (EHR) becomes more widespread, the need for automatic methods to simplify them in order to aid consumer comprehension becomes more apparent. However, before these tools can be developed, the linguistic features that characterize these types of text must be identified. This study attempts to quantify some of these linguistic features through a comparative register analysis using automatic methods in order to determine how different EHRs are from standard Swedish in terms of word and sentence composition, lexical complexity, sentence structures, as well as through the use of readability measures. Four different types of corpora were used, two of which represent the EHR domain, one consisting of standard Swedish, and the last of biomedical journal text. The results show that EHR’s make more frequent use of technical terms and abbreviations, and are dense with information due to the frequent omission of words which, based the situational characteristics of the texts, are likely considered to not carry enough information to be worth using. These include subjects, verbs, and content words. It was also found that a general purpose measure of text difficulty, LIX, was too simplistic to be able to accurately classify the EHRs. Many of the linguistic features of EHRs also pose problems to computational methods developed for standard language use. The study therefore also investigates how successful traditional tools, e.g. a tokenizer and POS tagger, are on this type of out of domain data. It was found that the tokenizer and tagger must be adapted to the domain to achieve satisfactory results.
Lagrangian Analysis of passive tracers dispersion in a confined convective flow

Lagrangian motion in a quasi-two dimensional time dependent, convective flow is studied at different Rayleigh numbers (Ra). Convective motion is generated in a rectangular tank by a linear heat source placed 0.4 cm above the lower surface of the tank. Lagrangian trajectories (Fig.1) have been evaluated using PTV technique. An intermediate regime characterised by an almost periodic Eulerian flow is observed. The flow consists mainly of two counter-rotating rolls divided by an ascending thermal plume above the heat source. The upper end of the plume oscillates horizontally with a frequency which increases with Ra. It is known that Lagrangian motion of particles in a time-dependent flow can be very complex due to chaotic advection even if the Eulerian flow is laminar and regular in an Eulerian viewpoint (? ). As a matter of fact, the non-autonomous one-degree of freedom Hamiltonian system of the equation of motion can not be trivially integrable. Dispersion phenomena occurring in the tank are investigated in a Lagrangian framework by using different statistics on particle displacements. One particle and two particle approaches have been considered. The classical way of looking at diffusive properties by computing average separation at fixed time is compared with an alternative measure known as Finite Size Lyapunov Exponent (FSLE) consisting in the evaluation of average separation time at fixed scale. The impact of an increasing forcing on the system and the corresponding dependence of Lagrangian statistics on Ra have been investigated varying this parameter by increasing the power supplied to the heat source (Table I). The obtained results can be generalised to many geophysical problems allowing us to discuss about the right way of describing spreading of pollutants in closed basins characterised by a not sharp separation between the scale of the velocity field and the dimension of the domain. Figure1 Recognised trajectories during 100 frames of their evolution Table I Parameters related to the performed runs. ) m W ( Q ) C m ( 3 ° α ) s m ( 2 υ ) s m ( 2 κ ) C s m J ( ° ⋅ ⋅ λ Ra Ra Pr 0.96×10 2.53×10 8.85×10 1.44×10 6,03×10 6.87×10 6.14 1.44×10 2.60×10 8.83×10 1.44×10 6.03×10 1.03×10 6.13 3.36×10 2.58×10 8.87×10 1.44×10 6.02×10 2.39×10 6.16 7.93×10 2.65×10 8.72×10 1.44×10 6.04×10 5.96×10 6.04 1.17×10 2.32×10 9.44×10 1.42×10 5.98×10 7.19×10 6.61 2.15×10 2.81×10 8.38×10 1.42×10 6.06×10 1.74×10 5.77 2.80×10 2.72×10 8.56×10 1.44×10 6,05×10 2.17×10 5.92