Miracle-dz/UniFAR-FTUs huggingface dataset:
LOFAR and HDF5: Toward a New Radio Data Standard

For decades now, scientific data volumes have experienced relentless, exponential growth. As a result, legacy astronomical data formats are straining under a burden not conceived when these formats were first introduced. With future astronomical projects ensuring this trend, ASTRON and the LOFAR project are exploring the use of the Hierarchical Data Format, version 5 (HDF5), for LOFAR radio data encapsulation. Most of LOFAR’s standard data products will be stored using the HDF5 format. In addition, HDF5 analogues for traditional radio data structures such as visibility data and spectral image cubes are also being developed. The HDF5 libraries allow for the construction of distributed, entirely unbounded files. The nature of the HDF5 format further provides the ability to custom design a data encapsulation format, specifying hierarchies, content and attributes. The LOFAR project has designed several data formats that will accommodate and house all LOFAR data products, the primary styles and kinds of which are presented in this paper. With proper development and support, it is hoped that these data formats will be adopted by other astronomical projects as they, too, attempt to grapple with a future filled with mountains of data.
Standardized precipitation index‐based approach to predict environmental flow condition

Environmental flow is one of the essential factors required to maintain the health of the river as well as the aquatic ecosystem. The present study describes the environmental flow conditions based on the percentage of average annual flow (%AAF) used in the Tennant method and the drought situations based on Standardized Precipitation Index (SPI) and investigates the existence of %AAF–SPI relationship. The study presents an attempt to correlate hydro‐meteorology of the catchment with the eco‐hydrology. High‐flow season (July–September) rainfall and runoff data of 16 catchments from the Mahanadi, Godavari, Brahmani‐Baitaini, and Tapi river basins were used for the independent derivation of both %AAF and SPI. The %AAF was plotted against the values of SPI (3‐month scale) for the high‐flow season for each of the study catchments. The R2 values of greater than 0.63 for most of the catchments reveal the existence of robust relationship between the %AAF and SPI and enabled EF prediction for even ungauged catchments using SPI (rather than %AAF) derivable from easily available rainfall data only.
ANALYSIS OF PARTIAL FREQUENCY STARTUP PROCESS OF SYNCHRONOUS MACHINE

In this paper the double machines coupling model of partial frequency starting is derived in detail on the basis of the actual partial frequency starting process of synchronous machine. State equations are established on Park equations in order to analyze the partial frequency starting process. The effects during the starting process such as initial speed of the generator, mechanical torque of the generator, field current of the generator and the motor, and impedance of the interconnection cables between the generator and the motor are analyzed in detail. The variation rules of rotation speed and electromagnetic torque of the generator and the motor in starting process are given. The simulation results agree well with the experimental results.
Recent advancements in biochar preparation, feedstocks, modification, characterization and future applications

ABSTRACT Biochar is a stable carbon-rich product synthesized from biological materials through different heating techniques. The main aim of this review is to evaluate various biochar production methods, parameters affecting the production of biochar, facilities to investigate the composition and structure of biochar, mechanism associated with production of biochar as well as various modification procedures to suit biochar for different applications. Various methods used to synthesize biochar include pyrolysis, torrefaction, gasification, hydrothermal and flash carbonization. Several factors such as feedstock composition and type, pyrolysis conditions such as temperature and time strongly influences the property of synthesized biochar. The physico-chemical properties of biochar strongly influence the role of biochar in several applications such as fuel cells, biosorption, agriculture, supercapacitors, catalyst/support and environmental remediation. It was identified through research efforts that the properties of biochar can be altered using various chemical or physical agents to suit various applications. Thus, the present review consolidates recent advancements in biochar research with special attention towards contaminant remediation and agricultural applications. GRAPHICAL ABSTRACT
Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation

Since approval of the EU General Data Protection Regulation (GDPR) in 2016, it has been widely and repeatedly claimed that the GDPR will legally mandate a ‘right to explanation’ of all decisions made by automated or artificially intelligent algorithmic systems. This right to explanation is viewed as an ideal mechanism to enhance the accountability and transparency of automated decision-making. However, there are several reasons to doubt both the legal existence and the feasibility of such a right. In contrast to the right to explanation of specific automated decisions claimed elsewhere, the GDPR only mandates that data subjects receive meaningful, but properly limited, information (Articles 13-15) about the logic involved, as well as the significance and the envisaged consequences of automated decision-making systems, what we term a ‘right to be informed’. Further, the ambiguity and limited scope of the ‘right not to be subject to automated decision-making’ contained in Article 22 (from which the alleged ‘right to explanation’ stems) raises questions over the protection actually afforded to data subjects. These problems show that the GDPR lacks precise language as well as explicit and well-defined rights and safeguards against automated decision-making, and therefore runs the risk of being toothless. We propose a number of legislative and policy steps that, if taken, may improve the transparency and accountability of automated decision-making when the GDPR comes into force in 2018.
Traveltime approximation for converted waves in elastic orthorhombic media

The moveout approximations are commonly used in seismic data processing such as velocity analysis, modeling, and time migration. The anisotropic effect is very obvious for a converted wave when estimating the physical and processing parameters from the real data. To approximate the traveltime in an elastic orthorhombic (ORT) medium, we defined an explicit rational-form approximation for the traveltime of the converted [Formula: see text]-, [Formula: see text]-, and [Formula: see text]-waves. To obtain the expression of the coefficients, the Taylor-series approximation is applied in the corresponding vertical slowness for three pure-wave modes. By using the effective model parameters for [Formula: see text]-, [Formula: see text]-, and [Formula: see text]-waves, the coefficients in the converted-wave traveltime approximation can be represented by the anisotropy parameters defined in the elastic ORT model. The accuracy in the converted-wave traveltime for three ORT models is illustrated in numerical examples. One can see from the results that, for converted [Formula: see text]- and [Formula: see text]-waves, our rational-form approximation is very accurate regardless of the tested ORT model. For a converted [Formula: see text]-wave, due to the existence of cusps, triplications, and shear singularities, the error is relatively larger compared with PS-waves.
Optimal Portfolios with Parametric Weights∗

We propose a novel approach to optimizing portfolios with large numbers of assets. We model directly the portfolio weight in each asset as a function of the asset’s characteristics. The coefficients of this function are found by optimizing the investor’s average utility of the portfolio’s return over the sample period. Our approach is computationally simple, easily modified and extended, produces sensible portfolio weights, and offers robust performance in and out of sample. In contrast, the traditional approach of first modeling the joint distribution of returns and then solving for the corresponding optimal portfolio weights is not only difficult to implement for a large number of assets but also yields notoriously noisy and unstable results. Our approach also suggests a new test of the portfolio choice implications of equilibrium asset pricing models. We illustrate our portfolio optimization approach through an empirical application to all stocks in the CRSPCompustat universe, exploiting size, value, and momentum effects. ∗We thank Michael Brennan, Rob Engle, Ravi Jagannathan, Larry Harris, Francis Longstaff, and seminar participants at CUNY Baruch, NYU, the Chicago Quantitative Alliance, the Los Angeles Quantitative Investment Association, Mellon Capital, Nomura, the Society of Quantitative Analysis, and Wells Capital Management for their comments and suggestions. †Durham, NC 27708, phone (919)660-1948, e-mail: mbrandt@duke.edu ‡Los Angeles, CA 90095, phone: (310)206-6077, e-mail: pedro.santa-clara@anderson.ucla. edu. §Los Angeles, CA 90095, phone: (310)825-7246, e-mail: rossen.valkanov@anderson.ucla. edu. USC FBE FINANCE SEMINAR presented by Pedro Santa-Clara FRIDAY, October 8, 2004 10:30 am – 12:00 pm, Room: JKP-104
Proactive environmental systems:the next generation of environmental monitoring

In this article we envision factors and trends that shape the next generation of environmental monitoring systems. One key factor in this respect is the combined effect of end-user needs and the general development of IT services and their availability. Currently, an environmental (monitoring) system is assumed to be reactive. It delivers measurement data and computational results only if the user explicitly asks for it either by query or subscription. There is a temptation to automate this by simply pushing data to end-users. This, however, leads easily to an "advertisement strategy", where data is pushed to end-users regardless of users' needs. Under this strategy, the mere amount of received data obfuscates the individual messages; any "automatic" service, regardless of its fitness, overruns a system that requires the user's initiative. The foreseeable problem is that, unless there is no overall management, each new environmental service is going to compete for end-users' attention and, thus, inadvertently hinder the use of existing services. As the main contribution we investigate the nature of proactive environmental systems, and how they should be designed to avoid the aforementioned problem. We also discuss how semantics, participatory sensing, uncertainty management, and situational awareness link to proactive environmental systems. We illustrate our proposals with some real-life examples.
Web 2.0 in the Classroom

This class is for teachers of all grade levels. Come learn how to use the various resources Web 2.0 provides in your classroom. Discussions will evolve on best practices for Web 2.0 in the classroom. Web 2.0 resources can be used in all subject areas. They can be used by students, teachers, administrators and support staff to promote collaboration, creativity and increase productivity. Why you should come: Teachers love free stuff and most of the Web 2.0 is free and too good to be true! It is a lot of fun and you will be a Web 2.0 junkie once you participate in this workshop.
HMM-based feature compensation method: an evaluation using the AURORA2

In this paper, we describe an HMM-based featurecompensation method. The proposed method compensates for noise-corrupted features in the MFCC domain using the output probability density functions (pdf) of the Hidden Markov Models (HMM). In compensating the features, the output pdfs are adaptively weighted according to forward path probabilities. Because of this, the proposed method can minimize degradation of featurecompensation accuracy due to temporally changing noise environment. We evaluated the proposed method based on the AURORA2 database. All the experiments were conducted in a clean condition. The experiment results indicate that the proposed method, combined with cepstral mean subtraction, can achieve a word accuracy of 87.64%. We also show that the proposed method is useful in a transient pulse noise environment.
Écologie spatiale des tortues marines dans le Sud-ouest de l’océan Indien : apport de la géomatique et de la modélisation pour la conservation

Le deplacement animal joue un role determinant dans la structuration spatiale et la dynamique des populations biologiques, en particulier des especes fortement mobiles. L’espace et l’environnement font ainsi partie integrante du cycle de vie des tortues marines. Ce travail de these propose de caracteriser l’ecologie spatiale des tortues marines, du stade juvenile au stade adulte, dans le Sud-ouest de l’ocean Indien, principalement par l’usage de deux methodes : la telemetrie satellitaire et la modelisation individu-centree. Il montre en premier lieu que la phenologie de la reproduction de la tortue verte a travers la region est principalement liee a la temperature de surface de la mer au voisinage des sites de reproduction. Sont ensuite etudies les patrons de derive des nouveau-nes generes par les courants oceaniques qui impacteraient inegalement leurs traits d’histoire de vie selon l’emplacement du site de naissance. Concernant le stade immature, les resultats suggerent un cycle de developpement trans-equatorial pour la tortue caouanne dans l’ocean Indien. Pour le stade adulte, cette etude caracterise les couloirs et la connectivite migratoires de la tortue verte dans la region. Enfin, l’integration de ces resultats permet de comprendre la structuration des patrons migratoires regionaux et leur influence sur la dynamique des populations. L’ensemble des connaissances acquises fournit un support concret d’aide a la decision pour la mise en place de plans de gestion et de conservation des tortues marines dans le Sud-ouest de l’ocean Indien. Cela souligne l’importance d’une approche a grande echelle pour la protection d’un patrimoine biologique partage par plusieurs nations.
Impacts of reactive power and harmonics on LV network losses

Reactive power and harmonics have been proposed as key factors contributing to losses on LV networks. This paper describes measurements of reactive power phase displacement and harmonic distortion over a large number of LV feeders, demonstrating that low power factors mostly arise when the demand is lowest. Loss calculations for a set of eleven feeders show that distortion has a low impact, less than 10% of the loss power and near zero for feeders with higher losses. Phase displacement can significantly increase losses, particularly for commercial LV feeders. In one example, power factor correction would reduce losses by up to 36%.
Cattle detection and counting in UAV images based on convolutional neural networks

ABSTRACT For assistance with grazing cattle management, we propose a cattle detection and counting system based on Convolutional Neural Networks (CNNs) using aerial images taken by an Unmanned Aerial Vehicle (UAV). To improve detection performance, we take advantage of the fact that, with UAV images, the approximate size of the objects can be predicted when the UAV’s height from the ground can be assumed to be roughly constant. We resize an image to be fed into the CNN to an optimum resolution determined by the object size and the down-sampling rate of the network, both in training and testing. To avoid repetition of counting in images that have large overlaps to adjacent ones and to obtain the accurate number of cattle in an entire area, we utilize a three-dimensional model reconstructed by the UAV images for merging the detection results of the same target. Experiments show that detection performance is greatly improved when using the optimum input resolution with an F-measure of 0.952, and counting results are close to the ground truths when the movement of cattle is approximately stationary compared to that of the UAV’s.
SPCF: A Memory Based Collaborative Filtering Algorithm via Propagation

Memory based Collaborative Filtering(CF) plays an important role in current Internet recommendation engines.However,this technology suffers from serious data sparsity of user-item rating matrix.This paper proposes a kind of improved model called SPCF,which is based on the state-of-the-art methods.The key property of the proposed model is that it finds more reliable users through similarity propagation and recommends items from both user and item information.Our experimental results on the two datasets — Movie Lens and Yahoo Music show that the proposed model achieves at least 3% lift in MAE relative to traditional collaborative filtering algorithms.
Object-Based Mapping of Coral Reef Habitats Using Planet Dove Satellites

High spatial resolution benthic habitat information is essential for coral reef protection and coastal environmental management. Satellite-based shallow benthic composition mapping offers a more efficient approach than traditional field measurements, especially given the advancements in high spatial and temporal resolution satellite imagery. The Planet Dove satellite constellation now has more than 150 instruments in orbit that offer daily coverage at high spatial resolution (3.7 m). The Dove constellation provides regularly updated imagery that can minimize cloud in tropical oceans where dense cloud cover persists. Daily image acquisition also provides an opportunity to detect time-sensitive changes in shallow benthic habitats following coral bleaching events, storms, and other disturbances. We developed an object-based coral reef habitat mapping approach for Dove and similar multispectral satellites that provides bathymetry estimation, bottom reflectance retrieval, and object-based classification to identify different benthic compositions in shallow coastal environments. We tested our approach in three study sites in the Dominican Republic using 18 Dove images. Benthic composition classification results were validated by field measurements (overall accuracy = 82%). Bathymetry and bottom reflectance significantly contributed to identifying benthic habitat classes with similar surface reflectance. This new object-based approach can be effectively applied to map and manage coral reef habitats.
Multitemporal Surface Deformation Analysis of Amyntaio Slide (Greece) using Remotely Piloted Airborne System and Structure-from-Motion photogrammetry

The results of Structure‐from‐Motion photogrammetry for the quantification of the ground surface deformation due to the massive landslide that occurred at the lignite open pit in Amyntaio, Greece on 10th June 2017, is presented in this paper. This unexpected slide damaged the entire westernmost marginal area of the pit, significant number of buildings and infrastructures (incl. road network, powerlines, biological treatment, houses etc.) of the nearby village of Anargiri, as well as agricultural land at the head of the landslide. We generated a very high‐resolution surface topography and corresponding co‐registered ortho‐rectified images covering a total area of 2 km2 by analyzing images acquired from Remotely Piloted Airborne Systems (RPASs). A high resolution (0.13 m) Digital Surface Model (DSM) was produced after photogrammetric processing, serving as a reference dataset for comparison with other surveys realized on December 2017 and September 2018. We compared the high‐resolution DSMs acquired during the post landslide periods, quantified the overall ground deformation and finally delineated regions of potential risk.
Feature selection in word spotting technology for retrieving historical Mongolian document images

A systematic frame for retrieving Mongolian Kanjur images by word spotting technology was designed.Some features including profile feature,projection feature and back-to-ink transition were adopted to represent Mongolian word images by deeply analyzing characteristics of handwritten Mongolian word images.By doing a lot of comparison experiments on the dataset with 5 500 word images,the best combination of features was determined.Meanwhile,the Mean Average Precision(MAP) of about 78.79% was achieved and the R-Precision 73.01%. The experimental results show that the selective features are valid and effective.
Vertical profiles of dust and other aerosol types above a coastal site

Monthly mean vertical profiles of aerosol type occurrences are determined from multiwavelength Raman and polarization lidar measurements above Haifa, Israel, in 2017. This contribution presents the applied methods and threshold values. The results are discussed for one example, May 2017. This month shows more often large, non-spherical particles in lofted layers than within the planetary boundary layer. Small particles are observed at higher altitudes only when they are observed in lower altitudes, too.
Comparison and implementation of image edge detection algorithm

The purpose of edge detection is to mark the image points that change significantly in intensity. Since derivative could reflect the significant degree of image intensity changes, derivative is used to solve the problem of edge detection in many researched. Three typical edge detection algorithms based on derivatives (Sobel, Log, Canny) are analyzed thoroughly in aspects of idea and flow. Experiments are performed using MATLAB to evaluate these edge detection algorithms. The performance results are analyzed and compared with the scope of application respectively.
Voedselinname van volstruise in die Namib-Naukluftpark, Suidwes- Afrika

The food intake of eight ostriches in the Namib-Naukluft Park, South West Africa, was determined through the analysis of stomach contents. Additional data were obtained by direct field observation of two hand-reared individuals. According to this the ostrich is an opportunistic feeder which utilises a wide variety of plant species.
A Social Recommendation Mechanism for Social Fundraising

In recent years, the world incurs many social issue and environmental disaster, so charity giving is become popular. Nowadays, the crowdfunding also become popular and the charity usually use specific type of crowdfunding called Peer-to-Peer fundraising. Many donor relationship management software and solutions have appeared. But they rarely utilize power of social network and majority of them focus on the aspect of fundraiser not on the aspect of donors. In this research, we will propose a social supported recommendation mechanism for non-profit fundraising. We will examine the donor preference, relationship between donor and fundraiser, and the characteristic fundraising dynamics to enhance the success rate of fundraising project and satisfaction rate of the donor.
An Incremental Grid Density-Based Clustering Algorithm

Although many clustering algorithms have been proposed so far, seldom was focused on high-dimensional and incremental databases. This paper introduces a grid density-based clustering algorithm——GDCA, which discovers clusters with arbitrary shape in spatial databases. It first partitions the data space into a number of units, and then deals with units instead of points. Only those units with the density no less than a given minimum density threshold are useful in extending clusters. An incremental clustering algorithm——IGDCA is also presented, applicable in periodically incremental environment.