Miracle-dz/UniFAR-FTUs huggingface dataset:
Abundance estimates of Southern Hemisphere Breeding Stock ‘D’ humpback whales from aerial and land-based surveys off Shark Bay, Western Australia, 2008

Single platform aerial line transect and land-based surveys of Southern Hemisphere Breeding Stock ‘D’ humpback whales Megaptera novaeangliaewere undertaken off Shark Bay, Western Australia to provide absolute abundance estimates of animals migrating northward along the westernAustralian coast. The aerial survey flew a total of 28 flights, of which 26 were completed successfully, from 24 June–19 August 2008. The landbased survey was undertaken from Cape Inscription, Dirk Hartog Island, Shark Bay, during the expected peak of the whales’ northward migration,from 8–20 July. During the first week of the land-based survey, some double count effort was undertaken to provide information on the numbersof pods missed from the land station. The assumed period of northward migration was 2 June–7 September. Estimated abundance of northwardmigrating whales during that time is 34,290 (95% CI: (27,340–53,350)), representing an annual rate of increase of 12.9% (CV = 0.20) since anestimate of 11,500 in 1999. This estimate is based on an estimate of relative abundance of surface-available whales of 10,840 (8,640–16,860), andan estimated g(0) of 0.32. There were considerable practical difficulties encountered during the land-based survey which reduced the effectivenessof the dual-survey approach for estimating g(0) for the aerial survey. Furthermore only about 15% of whales were estimated to be within the visualrange of the land-based station. Alternative approaches for estimating g(0) from these data are therefore also presented, resulting in considerablyhigher estimates of around 0.6–0.7, and yielding a conservative abundance estimate of 17,810 (14,210–27,720).
MASHing metadata: Legacy issues in OAI harvesting from three digital libraries

This Note reports on efforts to build a generalizable OAI-PMH workflow to retrieve metadata sets from unrelated digital libraries. This effort is part of a wider effort to build a database to aggregate metadata from different digital libraries, which can then be used as the basis for content analysis and data mining experiments with the metadata records. A pilot metadata harvest from three digital libraries using OAIPMH encountered a number of issues, arising from idiosyncratic legacy characteristics of each of the three metadata sets. In rthe end, the harvests had to be manually tailored to each library. OAI-PMH proved to be a useful approach, but only after communication with each digital library had identified important characteristics of each metadata set, including many legacy characteristics, which had to be acounted for in the harvest.
The Role of Information Sources in Firm R&D Activities – The Case of German Knowledge Intensive Industries

R&D activities affect the ability to create innovation for every firm. Many studies have shown that R&D activities are influenced by a number of determinants and the environment (R&D milieu) in which individual economic entities exist. Due to the nature of firms´ production, it is important to note that not every firm needs the same amount of information and knowledge. This thesis will also affect the efficiency of the use of information sources in R&D activities. In practice, it is necessary to know the dependence of companies and their R&D activities on the available information sources so that public policy makers can better target public policy and possible financial support schemes (grant schemes), because, the one size-fits all principle cannot be assumed. Therefore, the aim of this paper is to analyze the role of information resources in the knowledge intensive industries in the strongest EU economy, i.e. Germany. For the analysis, Eurostat CIS data and own regression model were used. The results show that the knowledge environment has a major impact on the development of R&D in the German knowledge intensive firms. German companies sourced information from the market (especially clients and customers), and all firms acquired information and knowledge from collaborating with universities. The biggest impetus for the realization of R&D activities is for firms to focus on markets outside the EU.
Real-time monitoring of heart rate using wellness belt equipped with electrocardiogram sensors

This paper presents the development of a wellness wear system for monitoring heart rate in real-time. A belt equipped with on-body circuit module and low power sensors enables real-time monitoring of heart situations through wireless syncing between mobile devices and them, and uses digital thread to transmit signals from sensors to the circuit module. The beat detection algorithm using simultaneously electrocardiogram was developed to detect R waves and estimate heart rate. Test of the algorithm was carried out with 8 subjects walking on a treadmill. This study can be extended to the future attempts in implementing a real-time algorithm into the circuit module and developing healthcare services utilizing smart clothes.
Designing for Mobile Empowerment in South African Education

We present empowerment as a problem in contemporary societies. We argue it is a ‘wicked problem’, particularly within the resource-constrained environment of South African public education. We offer capability-sensitive design as a grounded theory-led method for the development of conceptual designs empowering teachers and school managers. The participatory elements of the method are constrained within the data gathering phase, the pluralistic analysis inscribed within the capability approach, and the empathy stage of design thinking. The method is illustrated via the ‘Class Journal’ concept, developed as part of engagement between CSIR and SAP Innovation CenterPretoria.
Computer-aided detection of lung nodules: a review

Abstract. We present an in-depth review and analysis of salient methods for computer-aided detection of lung nodules. We evaluate the current methods for detecting lung nodules using literature searches with selection criteria based on validation dataset types, nodule sizes, numbers of cases, types of nodules, extracted features in traditional feature-based classifiers, sensitivity, and false positives (FP)/scans. Our review shows that current detection systems are often optimized for particular datasets and can detect only one or two types of nodules. We conclude that, in addition to achieving high sensitivity and reduced FP/scans, strategies for detecting lung nodules must detect a variety of nodules with high precision to improve the performances of the radiologists. To the best of our knowledge, ours is the first review of the effectiveness of feature extraction using traditional feature-based classifiers. Moreover, we discuss deep-learning methods in detail and conclude that features must be appropriately selected to improve the overall accuracy of the system. We present an analysis of current schemes and highlight constraints and future research areas.
Analysis and Building of Trading Platform of Construction 3D Printing Technology and Products

Construction 3D printing technology has been rapidly developed, but in the usual life, there are still many people who have not heard of or used construction 3D printing products, and many people want to buy Construction 3D printing products, but there is no channel. Therefore, through the questionnaire survey of potential customers, from the willingness of potential customers, the influencing factors of construction 3D printing technology product trading platform are analyzed, and the PLD-SEM model is established. The potential customers are analyzed in the 3D printing technology product trading platform, with more attention to factors, including product categories, prices, trading platform customization features, and excellent network capabilities. Finally, the 3D printing technology product trading platform was designed, and the customer management module, construction 3D printing technology product information management module, construction 3D printing technology product retrieval module, and transaction information management were proposed. Building a fully functional 3D printing technology product trading platform that can attract more potential customers provides customers with a channel to understand and purchase 3D printing products and helps solve the current 3D printing technology products difficult to promote and trade problem.
Pressure Drop Analysis of Water and Bottom Ash Mixture Flow Through Straight Pipeline With Additive

All the available coals have some percentage of ash. When the coal is burnt about 10 to 20% of quantity of coal used results in ash. In the modern large steam power plants where huge amounts of coal are used, the amount of ash may be go up to many thousands tonnes of ash per year. A slurry transport system is used to disposal the coal ash away from coal burning unit in thermal power plant. Bottom ash slurry is pumped from the common ash slurry sump to the dyke area which is located near slurry pump house. Water and bottom ash are mixed in slurry tank, after that slurry transportation takes place in slurry pipeline with the help of slurry pump. Computational simulation is performed on the slurry flow through pipeline for the analysis of pressure drop. When fluid flows through a pipe, it is subjected to hydraulic resistances which are of viscous frictional resistance and local resistance. Viscous frictional resistance associated with the fluid flow is called major loss of energy. Pressure drop can be reduced in pipe flow by mixing the additive in slurry. Local resistances are essentially due to change of velocity either in magnitude or direction. Modelling of pipeline is developed in Gambit and Fluent is used for the numerical evaluation. Computational simulation has been performed on various concentrations and flow velocities.
AN INTRODUCTION TO VIRTUAL ELEMENTS IN 3 D

The Virtual Element Method (VEM), is a very recent technology introduced in [1] for the discretization of partial differential equations, that has shared a good success in recent years. The VEM can be interpreted as a generalization of the Finite Element Method that allows to use general polygonal and polyhedral meshes, still keeping the same coding complexity and allowing for arbitrary degree of accuracy. The Virtual Element Method makes use of local functions that are not necessarily polynomials and are defined in an implicit way. Nevertheless, by a wise choice of the degrees of freedom and introducing a novel construction of the associated stiffness matrixes, the VEM avoids the explicit integration of such shape functions. In addition to the possibility to handle general polytopal meshes, the flexibility of the above construction yields other interesting properties with respect to more standard Galerkin methods (for instance, the VEM easily allows to build discrete spaces of arbitrary C regularity, or to satisfy exactly the divergence-free constraint for incompressible fluids). The present talk is an introduction to the VEM, aiming at showing the main ideas of the method. We consider for simplicity a simple elliptic model problem (that is pure diffusion with variable coefficients [2]) but set ourselves in the more involved 3D setting [3]. In the first part we introduce the adopted Virtual Element space and the associated degrees of freedom, first by addressing the faces of the polyhedrons (i.e. polygons) and then building the space in the full volumes. We then describe the construction of the discrete bilinear form and the ensuing discretization of the problem. Furthermore, we show a set of theoretical and numerical results. In the very final part, we will give a glance at more involved problems, such as magnetostatics (mixed problem with more complex spaces interacting) and large deformation elasticity (nonlinear problem).
ALGORITHMS AND SYSTEM FOR CURVED AND CONTINUOUS DESCENT TRAJECTORIES IMPROVING FUEL EFFICIENCY IN TMA

One of the most important challenges in Air Traffic Management (ATM) is to increase the efficiency of flights arriving at busy airports. The effects of aircraft noise, fuel consumption and related pollutant atmospheric emissions can impact the quality of life in populated areas near to airports and represent environmental issues resulting in restrictions for air traffic procedures, aircraft manufacturing and airport facilities design. ICAO and EUROCONTROL provide guidance and recommendations on environmental measurements in order to overcome these difficulties, contributing to a sustainable balancing between the positive growing demand in the Aviation sector and the negative consequences of human activities. This paper is focused on the development of arrival trajectories automatic generation algorithms. The implementation of these algorithms is aimed to generate curved and continuous descent approach trajectories, by remodeling or adjusting the arrival procedures, for the future efficient flight operations in Terminal Maneuvering Area (TMA), so increasing environmental efficiency and capacity in proximity of airports. Furthermore, the paper reports and discusses the main concepts and mathematical models needed to implement an overall system, including the algorithms cited above, able to generate descent profiles suitably optimized in terms of fuel consumption with respect to conventional step-down arrival paths.
Comparison of Karnin Sensitivity and Principal Component Analysis in Reducing Input Dimensionality

Reducing the input dimensionality of large datasets for subsequent processing will allow the process to become less computationally complex and expensive. This thesis tests if Karnin sensitivity can be applied to reducing input dimensions of feed forward neural networks as well as comparing the results to the well known principal component analysis (PCA). The resulting error when reducing dimensions of inputs of various scenarios according to PCA and Karnin sensitivities are compared. After testing, Karnin was found to be able to be used to reduce input dimensions and did as well if not better than PCA in most cases. However, Karnin, like PCA, is not without its weaknesses. To cover both techniques’ weaknesses, a combination of the two techniques is introduced. In the end, ”PCA chases variance while Karnin chases good mapping. ”
METHODS TO ANALYSE PSYCHOPHYSIOLOGICAL REACTIONS RELATED TO EMOTIONAL VISUAL STIMULATION

Studying affective response to a stimulus can be utilized e.g. in marketing research, where different kind of products are presented to customers to see how pleasant they appear to the customer. The emotional effect can be measured with subjective evaluation on the valence (pleasure/displeasure) or arousal the product elicits on the subject. Sometimes, however, subjects might not want to, or cannot, give truthful evaluation on their emotions. Instead of using subjective questionnaires, the affective responses can be studied during the stimulus with physiological measurements. In this thesis, the physiological reactions to emotional visual stimulation are studied. In studies I and II, the autonomic nervous system (ANS) responses, facial electromyography (fEMG) and gaze were examined during positive and negative food and non-food picture stimulation. In study IV, the stimulus material was similar, but instead of ANS activity, central nervous system (CNS) was studied by measuring brain activity with functional magnetic resonance imaging (fMRI). Study III is focused on environmental stimulation and the effect of lunchtime walk on night-time ANS activity was studied between nature and urban walks. In study I, the physiological measurements were found to be sensitive to stimulus valence and category. The negative pictures increased corrugator fEMG activity and skin conductance level (SCL), while the positive pictures decreased them. Also, the nonfood pictures increased mean R wave interval (RR) and root mean square of successive differences (RMSSD) parameters more than the food pictures. The study II had same measurement setup than study I, but heart rate variability (HRV) parameters were examined with short-time reactivity right after the stimulus onset. The results of the study showed that positive food pictures induced different reactivity than other picture categories. The positive food pictures did not show similar fast mean RR interval and HRV increase as was seen with the other picture categories. In study IV, the visual food and nonfood stimuli were used to study CNS activity with fMRI. The regions of interest included amygdala, anterior cingulate cortex (ACC) and medial prefrontal cortex (MPFC). Compared to positive pictures, negative pictures induced higher amygdala activation, lower ACC activation, and reciprocal findings at MPFC. In addition, the correlation between brain activity and alexithymic features were examined. Alexithymic features were associated with valence of food pictures in right amygdala and with valence of non-food pictures in left MPFC. In addition to presenting the visual stimulation in controlled laboratory setting as pictures on computer screen, the physiological effects of different environment types were studied. In study III, the night-time vagal activity was observed to be greater following a lunchtime walk in nature compared to a walk in urban environ-
Implementation of PWM regular sampling strategy for AC drives

The regular sampling technique offers a feasible basis for the microprocessor control of inverters in pulse-width-modulated (PWM) AC drives. An implementation of this technique is presented for the speed control of an induction motor in the frequency range 5-105 Hz. Hardware and software design principles are outlined and discussed for an 8-bit microprocessor. Spectral analyses of the sampling technique with sinusoidal modulating function and with third harmonic distortion added to this function are derived, with emphasis on the fundamental and dominant harmonic components. Experimental and computed results are presented for the motor control in steady state, and for transient current and speed in closed-loop operation, with excellent correlation. <<ETX>>
Music Education as Transformative Practice: Creating New Frameworks for LearningMusic through a Freirian Perspective

The educational perspectives presented by Paulo Freire have been thoroughly analyzed and linked to the general education of children in urban America. Additional studies have focused on Freire’s pedagogy in higher education. Nevertheless, the number of studies that have examined music education and the pedagogy of music teaching and learning as a kind of pedagogy of emancipation are far more restricted, have become available only recently and are still not widely dispersed or read. In this article, Freirian concepts serve to develop frameworks that define the philosophy of a Critical Pedagogy for Music Education. This new conception borrows from Freire’s texts, and delineates practices believing that real learning to take place only if students and teachers alike are changed in and by the process of education. 1 Schmidt: Music Education as Transformative Practice Published by OpenCommons@UConn, 2005
2017-08 A Study of PSF Models for ACS / WFC

This study compares PSFs generated with Tiny Tim against an empirically-derived, effective PSF (Anderson & King, 2006) for the Hubble Space Telescope Advanced Camera for Surveys/Wide Field Channel imaging. We manipulate the Tiny Tim PSF FITS files into a format that can be utilized by the effective PSF FORTRAN photometry code. Then we perform PSF photometry on globular cluster NGC 6397 and analyze the photometry and astrometry results. We measure a value of 0.227± 0.032 for a quality-of-fit metric of the Tiny Tim PSF and a corresponding 0.117± 0.021 for the effective PSFs, an improvement of a factor of approximately two. We find that the effective PSF models outperform the Tiny Tim PSFs in every measurement of stellar sources in this field.
Aerosols and their seasonal variability-Are aerosols important for seasonal prediction ?

This paper provides a short overview of aerosol particles in the atmosphere and their potential effects on weather and climate. Atmospheric aerosol particles display a large spatial and temporal variability and the aerosol concentration is also strongly dependent on meteorological parameters such as clouds, precipitation and wind. In seasonal forecasting, aerosol particles have so far not been treated in great detail, and the importance of including temporal and spatial variations in the aerosol concentration is therefore not known. Some examples of the influence of changes in the atmospheric aerosol particle concentration on largescale circulation, precipitation and surface temperature from climate-related applications are given here. It is shown that aerosol particles may affect tropical precipitation and thereby also extratropcial stationary waves and the surface temperature distribution. The atmospheric aerosol concentration may also influence large-scale circulation systems such as the Indian Monsoon, the Hadley circulation and the Walker circulation.
End-to-end Prediction of Driver Intention using 3D Convolutional Neural Networks

Despite extraordinary progress of Advanced Driver Assistance Systems (ADAS), an alarming number of over 1,2 million people are still fatally injured in traffic accidents every year1. Human error is mostly responsible for such casualties, as by the time the ADAS system has alarmed the driver, it is often too late. We present a vision-based system based on deep neural networks with 3D convolutions and residual learning for anticipating the future maneuver based on driver observation. While previous work focuses on hand-crafted features (e.g. head pose), our model predicts the intention directly from video in an end-to-end fashion. Our architecture consists of three components: a neural network for extraction of optical flow, a 3D residual network for maneuver classification and a Long Short-Term Memory network (LSTM) for handling temporal data of varying length. To evaluate our idea, we conduct thorough experiments on the publicly available Brain4Cars benchmark, which covers both inside and outside views for future maneuver anticipation. Our model is able to predict driver intention with an accuracy of 83,12% and 4,07s before the beginning of the maneuver, outperforming state-of-the-art approaches, while considering the inside view only.