Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Ensemble of Trees in MLlib

We analyze the implementation of decision tree and random forest in MLlib, a machine learning library built on top of Apache Spark, and investigate parallelization as well as algorithmic improvements. We make contributions on two fronts in this paper. First, we analyze the implementation of decision tree and random forest in MLlib, and propose a parallelized version of calculating split bins, or candidate cut-points, for each feature. Second, we discuss the implementation of a tree learning algorithm extra-trees using the existing structure from the random forest implementation, and test both ensembles on multiple datasets. Our results show that the parallelization improvement scales linearly, and that extra-trees perform better than random forest for deeper trees and dense datasets
7.2: States of Consciousness

No matter what you’re doing–solving homework, playing a video game, simply picking out a shirt–all of your actions and decisions relate to your consciousness. But as frequently as we use it, have you ever stopped to ask yourself: What really is consciousness? In this module, we discuss the different levels of consciousness and how they can affect your behavior in a variety of situations. As well, we explore the role of consciousness in other, “altered” states like hypnosis and sleep.
Current handling capability of the neutral point of a three-phase/switch/level boost-type PWM (VIENNA) rectifier

In this paper the stationary operational behavior of a three-phase/switch/level PWM rectifier is analyzed for asymmetrical loading of the output partial voltages. For the considerations a sinusoidal mains current shape, resistive behavior of the mains current fundamental and constant pulse frequency are assumed. Based on analytical calculations it is shown that the average value of the neutral point current (which has to be formed for asymmetrical load) has an approximately linear dependency on the distribution of the overall relative on-time of the switching states of the system being redundant concerning the voltage formation between begin and end of a pulse half interval. The maximum admissible load of the neutral point (capacitive output voltage center point) is calculated. This load is given as a function of the amplitude of the mains current and the voltage transfer ratio of the system. The calculations are checked by results of a digital simulation of the system behavior. Furthermore, the increase of the rms value of the ripple of the mains current of the rectifier is analyzed as it results in forming of an average value of the neutral point current. As a basis for comparison, the ripple rms value is used which results in harmonic-(sub)optimal control and negligible average value of the neutral point current. Finally, the current stress on the power semiconductors and on the output capacitors of the system are compiled in the form of diagrams which can be applied directly for dimensioning the system.
Realizability conditions and bounds on synthesis of switched-capacitor DC-DC voltage multiplier circuits

A formal study of the theoretical performance of switched-capacitor (SC) dc-dc voltage multiplier circuits is given. A question concerning the necessary number of circuit elements to realize a given conversion ratio is addressed. In response to the question the bound on attainable voltage ratio for a given number of capacitors k and the bound on the number of switches required in any circuit configuration have been established. The maximum step-up or step-down ratio is given by the kth Fibonacci number, while the bound on the number of switches required in any SC circuit is 3k-2. The complete set of attainable DC conversion ratios is found. A canonical circuit realization of the maximum voltage ratio is discussed and illustrative examples are included. Necessary and sufficient conditions for the realizability of a dc conversion ratio are determined and formal proofs are given.
Self-supervised Instance Detection by (and for) Pose Estimation Supplementary Material

Real-time object pose estimation is necessary for many robot manipulation algorithms. However, state-of-the-art methods for object pose estimation are trained for a specific set of objects; these methods thus need to be retrained to estimate the pose of each new object, often requiring tens of GPU-days of training for optimal performance. We propose to leverage a slow zero-shot pose estimator to self-supervise the training of a fast detection algorithm. This fast detector can then be used to filter the input to the pose estimator, drastically improving its inference speed. We show that this self-supervised training exceeds the performance of existing zero-shot detection methods on two widely used object pose estimation and detection datasets, without requiring any human annotations. Further, we show that the resulting method for pose estimation has a significantly faster inference speed, due to the ability to filter out large parts of the image. Thus, our method for self-supervised online learning of a detector (trained using pseudo-labels from a slow pose estimator) leads to accurate pose estimation at real-time speeds, without requiring human annotations. Supplementary materials can be found at https://georgegu1997.github. io/SSOID/
A Fuzzy-based Genetic Algorithm for Social Welfare Maximization by Placement and Sizing of Static Synchronous Series Compensator

Abstract This article presents a fuzzy-based genetic algorithm to maximize total social welfare and alleviate congestion by placement and sizing of one static synchronous series compensator device, considering its investment cost in a double-sided auction market. The generating units cost curves are considered to be quadratic with sine components to show the impacts of valve point loading. By adding the valve point effect, the model presents non-differentiable and convex regions that challenge most gradient-based optimization algorithms. In addition, the impact of distribution companies on the social welfare maximization and congestion management is presented as a quadratic function. The proposed approach makes use of the fuzzy-based genetic algorithm to optimal schedule generating companies and distribution companies and setting the static synchronous series compensator location and its size while the Newton–Raphson algorithm minimizes the mismatch of the power flow equations. Simulation results on the modified IEEE 14- and 30-bus test systems (with/without line flow constraints, before/after compensation) are used to examine the impacts of the static synchronous series compensator on the total system social welfare improvement versus its cost. Several cases are considered to test and validate the consistency of detecting best solutions. Simulation results are compared to solutions obtained by the genetic algorithm and sequential quadratic programming approach, which has been used in MATPOWER (available on-line; see [1]). The aim of this article is the utilization of static synchronous series compensator for the social welfare maximization problem considering the impact of valve point loading effect on the operation point of the generating companies by inclusion of fuzzy rules in the genetic algorithm to guarantee fast convergence for locating/sizing the static synchronous series compensator. The proposed method shows the benefits of the static synchronous series compensator in a deregulated power market and demonstrates how it can be utilized by the independent system operator to improve the total social welfare and prevent congestion.
Teaching Foreign Languages to the Deaf in Poland

Inclusive teaching is strongly emphasised nowadays in European regulations and documents. Educators, teachers, scholars and policy makers are struggling to make education accessible to the widest possible group of learners. One of such groups are the d/Deaf – teaching them foreign languages is still an area that has not been fully explored. Although it is undoubtful that the d/Deaf require adjustments in teaching techniques and content, some researchers claim that there is no special method that could be applied to teaching this group of learners. The article presents the characteristics of teaching foreign languages to the d/Deaf. This theory is combined with the results of a study conducted on a group of foreign language teachers (of English and Polish) working with d/Deaf learners, showing how they manage to teach this peculiar group of students. The data gathered in a form of online interviews and reported in the paper shed light on how teachers approach this particular group of FL learners. The article presents conclusions regarding the conditions and formal regulations of the Polish system. They concern possible changes in the educational programme and the teacher training system. Additionally, the paper presents a wide range of practical suggestions regarding teaching foreign languages to the d/Deaf.
Space MMF Harmonic Rotor Losses under Healthy and Open Circuit Conditions

Rotor eddy current losses of a five phase dual-rotor permanent magnet synchronous machine (DR-PMSM) are investigated in both healthy working condition and open circuit fault conditions in this paper. The studied eddy current losses are induced by harmonics of stator magneto-motive force (MMF). The eddy current losses are calculated by finite element method (FEM) using an improved point current model to generate MMFs for different conditions. The calculation results are analyzed and applied in thermal analysis. Finally, experimental measurements and validations are conducted.
Gradient Boosting Machine for Early Prediction of Sepsis Using Clinical Data

Sepsis is a severe medical condition caused by the body’s extreme response to an infection leading to tissue damage, organ failure, and even death. The emergence of advanced technologies such as Artiﬁcial Intelligence and machine learning allowed faster exploration of advanced ways to recognize sepsis cases. In this paper, we present an efﬁcient model, based on gradient boosting machines, to optimize sepsis risk monitoring and mitigation. Our model can also serve as a general framework to solve survival analysis problems in different domains. We also provide generic techniques for statistical feature extraction, which can drastically increase the aptitudes of detection without speciﬁc domain knowledge. The proposed model is also capable of handling a high rate of missing values of patient records. There are four main components of the model: features engineering, sepsis risk estimation, alert system optimization, and ﬁnally sepsis alarm predictions. Using the utility score metrics provided by PhysioNet/Computing in Cardiology Challenge 2019, the local validation score are 32.9% for utility score and 82.1% for Area Under the ROC Curve. Such results places us among the 10 places in the public leader-board.
A STUDY ON CAPITAL STRUCTURE DETERMINANTS OF INDIAN STEEL COMPANIES

This paper studies the determinants of capital stru ctu e choice of Indian steel companies. The main ob jective of the firm is to explore the most important factors w hich influence most the choice of capital structure of the steel companies in India. The study is basically empirical in natur e. In the present paper 37 Indian steel companies l isted under National Stock Market and Bombay Stock Market constitute the sample of study. Correlation and regression analys is are used to explore the relationship between dependent variable lev rage and other independent variables like tang ibility, size, non-debt tax shield, growth opportunity, profitabil ity and business risk. It is found that tangibility , non-debt tax shield, size and growth opportunity have significant effect of t he leverage of the capital structure of the compani es. The other two variables, profitability and business risk have ins ig ificant effect on the capital structure of the c ompanies.
Adsorption of Hydrogen Sulfide (H2S) from Municipal Solid Waste by Using Biochars

The emission of hydrogen sulfide (H2S) from municipal solid waste is one of the environmental issues that raised the public’s attention and awareness. Exposure to H2S that brings a foul smell of rotten eggs will cause headaches, irritation, dizziness, fatigue, and even death if the concentration of H2S is too high. The study’s goals are to investigate the properties of biochars made from rice hulls, banana peels, and sawdust; to compare the biochars’ physical and chemical properties; and establish the H2S removal efficiency of the three biochars. Biochars derived from rice hull (RHB-500), banana peel (BPB-550), and sawdust (SDB-500) by pyrolysis were used as the adsorbents. The biochar yield, pH, ash content, surface functional group, and morphology of the biochars produced were investigated. In this study, H2S was synthesized by mixing food waste and soil in the experimental column. The H2S produced was reduced by the adsorption method. The removal efficiencies of H2S for each biochar were determined by allowing the synthetic H2S to flow through the two columns that were packed with sand (act as control) and biochars, respectively. All biochars were alkaline, and BPB-550 had the highest pH, followed by SDB-500 and finally RHB-500. The order for removal efficiency of H2S (>94%) is BPB-550 > SDB-500 > RHB-500. Overall, the biochars derived from biomass had a strong ability to act as the adsorbents for H2S removal.
A NEW APPROACH TO ROTOR BLADE PERFORMANCE DESIGN IMPROVEMENT

An optimal rotor always requires better hover and forward flight performance within the entire flight envelope. With recent advancements in composite material manufacturing technology, it is possible for engineers to produce flyable blades with variable chords. A new approach on how to select an optimal blade planform design is presented in this paper. The fundamental concept is to increase the aerodynamically efficient blade loading surface area, making it produce higher lift in a more effective manner. At the same time, it also reduces the aerodynamically inefficient blade air-loading area, making it produce less drag penalty during flight. This approach results in an overall higher blade aerodynamic efficiency with a planform having variable local blade chords along the radial direction. The shape of the blade differs greatly from that of a conventional design. Five blade planforms with good OGE hover performance are chosen to demonstrate the method. It is interesting to note that the results obtained from the best hover performance configuration has the worst forward flight performance. The modified 4:1 taper from 75% radius to the tip has the best forward flight performance among the five selected configurations. NOMENCLATURE
Solving Large-scale Open Pit Mining Production Scheduling Problems by Integer Programming

Since the initial application of mathematical optimisation methods to mine planning in 1965, the Lerchs-Grossmann algorithm for computing the ultimate pit limit, operations researchers have worked on a variety of challenging problems in the area of open pit mining. This thesis focuses on the open pit mining production scheduling problem: Given the discretisation of an orebody as a block model, determine the sequence in which the blocks should be removed from the pit, over the lifespan of the mine, such that the net present value of the mining operation is maximised. In practise, when some material has been removed from the pit, it must be processed further in order to extract the valuable elements contained therein. If the concentration of valuable elements is not sufficiently high, the material is discarded as waste or stockpiled. Realistically-sized block models can contain hundreds of thousands of blocks. A common approach to render these problem instances computationally tractable is the aggregation of blocks to larger scheduling units. The thrust of this thesis is the investigation of a new mixed-integer programming formulation for the open pit mining production scheduling problem, which allows for processing decisions to be made at block level, while the actual mining schedule is still computed at aggregate level. A drawback of this model in its full form is the large number of additional variables needed to model the processing decisions. One main result of this thesis shows how these processing variables can be aggregated efficiently to reduce the problem size significantly, while practically incurring no loss in net present value. The second focus is on the application of lagrangean relaxation to the resource constraints. Using a result of Mohring et al. (2003) for project scheduling, the lagrangean relaxation can be solved efficiently via minimum cut computations in a weighted digraph. Experiments with a bundle algorithm implementation by Helmberg showed how the lagrangean dual can be solved within a small fraction of the time required by standard linear programming algorithms, while yielding practically the same dual bound. Finally, several problem-specific heuristics are presented together with computational results: two greedy sub-MIP start heuristics and a large neighbourhood search heuristic. A combination of a lagrangean-based start heuristic followed by a large neighbourhood search proved to be effective in generating solutions with objective values within a 0.05% gap of the optimum.
Raquel Catarina Saraiva Diaz Methicillin resistant Staphylococcus aureus : mec C gene and vancomycin susceptibility Staphylococcus aureus meticilina resistente : gene mec C e susceptibilidade à vancomicina

Staphylococcus aureus is a major cause of infection and vancomycin the gold standard for its treatment. In 2011, mecC gene was discovered in methicillinresistant Staphylococcus aureus, this gene shares 69% nucleotide homology with mecA gene. Also in recent years it has been described a phenomenon called "MIC creep", which describes the increase of the minimum inhibitory concentration of vancomycin within susceptibility range. The aims of this work included the evaluation of the overall prevalence of mecC gene and the worldwide phenomenon of “MIC creep” using meta-analysis techniques. Since that in Portugal this investigation is still residual and because this is a phenomenon with regional characteristics, it was also assessed the presence of “MIC creep” in Staphylococcus aureus strains of Centro Hospitalar Baixo Vouga, Aveiro. For the evaluation of mecC gene it was obtained an overall prevalence of 0.009 (95% CI = 0005-0013). Despite the rare prevalence of this gene and absence of suspected strains, it is of utmost importance in clinical and epidemiological terms to screen this new form of methicillin-resistant Staphylococcus aureus. For the evaluation of global evidence of vancomycin “MIC creep”, our results do not suggest the presence of this phenomenon. The results obtained showed that mean values of vancomycin Minimum Inhibitory Concentration, of all methicillin-resistant Staphylococcus aureus isolates reported, were 1.19 mg/L and 1.20 mg/L determined by Etest and Broth Microdilution method, respectively. At the regional level, our results showed no evidence of “MIC creep” but described differences in methodologies applied to determine vancomycin Minimum Inhibitory Concentration. Either with the evaluation of the Minimum Inhibitory Concentration of vancomycin values or with research of the mecC gene in Staphylococcus aureus, this work highlights the need to better understand the resistance of nosocomial infections to antibiotics and to alert clinicians to the possibility of resistance to vancomycin scenario and the microbiology laboratories for the risk of new strains carrying the resistance gene.
Manure Handling System Attributes Impact on Manure Management Investment Decisions: A Random Utility Model Approach

A random utility model framework was used to estimate the probability that a farmer chooses one of three mutually exclusive manure handling systems (daily haul, short term, and long-term storage) based on manure handling system attributes as well as individual farmer/farm characteristics. Results demonstrate that costs of manure handling systems, as well as compliance with environmental programs, play the largest role in determining the decisions made by producers and should be considered when designing these programs in the future.
Differentiating between partial discharge sources using envelope comparison of ultra-high-frequency signals

Partial discharges (PD) in high-voltage equipment cause damage to insulation. One method for detecting them is the ultra-high-frequency (UHF) method. Subsequent analysis using phase-resolved patterns or time-of-flight measurements can identify PD type or locate the defect. This study presents a method for comparing UHF signal envelopes to differentiate between multiple PD sources. Experimental investigations are conducted to identify an approach that strikes a compromise between competing aims of minimising signal sampling rates while retaining sufficient ability to discriminate between PD sources in different locations. The envelope comparison method is efficient and has potential for incorporation within automated systems. Results clearly demonstrate the ability to distinguish between PD sources in different positions, which offers a means to determine the number of PD sources present. Since each PD pulse can then be associated with a particular subset of data, subsequent PD interpretation could be applied to separate PD date streams, rather than to mixed data. An radio frequency (RF) detector circuit was designed and used to validate the approach by means of experiments carried out in a model transformer tank. The technique should be applicable to other condition monitoring systems that are required to distinguish between complex transient signals.
Compact, harmonic suppressed power divider using open complementary split‐ring resonator

An open complementary split‐ring resonator (OCSRR) based T‐junction power divider working at 900 MHz frequency is proposed in this paper. By embedding the OCSRR in the microstrip transmission line, slow wave effect is introduced to achieve size reduction. The proposed power divider size is 47% smaller than the conventional power divider. Besides, the proposed power divider provides better third harmonic suppression. The simulated results are verified with the experimental results. © 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett 53:2897–2899, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26393
Improving teenage driver perceptions regarding the impact of distracted driving in the Pacific Northwest

ABSTRACT The goal of this educational outreach project was to examine perceptions of driver distraction among teenagers in the Pacific Northwest. Specifically, to identify secondary tasks this group may consider distracting and determine their self-reported engagement in those same secondary tasks while driving. An interactive presentation was developed and administered to 1,400 teenage drivers. Teenagers from age 14 to 18 years were recruited from high schools in Washington, Idaho, and Oregon with an approximately equal sample in each State. Of these participants, 1,006 teenage drivers responded to a pre- and postknowledge survey administered immediately before and 2 weeks after the interactive presentation. The purpose of the survey was to measure the degree to which the interactive presentation improved teenage driver perspectives regarding the hazards of distracted driving. Results indicated that the interactive presentation positively influenced teenage driver perspectives, meaning that after the interactive presentation, teenage drivers were more likely to correctly identify different types of distracted driving.