Miracle-dz/UniFAR-FTUs huggingface dataset:
Uso del Smartphone y su reflejo en la escritura entre estudiantes de secundaria bilingües gallego – español

A medida que las tecnologias avanzan y se hacen mas presentes entre los escolares, es necesario estudiar el impacto de estas en su manera de escribir. Esta investigacion analiza la influencia en la escritura adolescente de los llamados textismos . Se han llevado a cabo varios estudios sobre el tema, destacando los de Wood et al (2013; 2014) que concluyen que este lenguaje no amenaza los escritos. Debido a que dichos estudios se realizaron entre hablantes monolingues de ingles, era necesario comprobar si estas conclusiones se podian extrapolar a una lengua romance. Para ello, se escogio un grupo de estudiantes de secundaria hablantes nativos tanto de espanol como de gallego para aplicarles un test de redaccion. Los resultados dan en parte razon a las conclusiones de investigadores previos pero tambien anaden un factor olvidado por ellos: la puntuacion. Este articulo invita tambien a la inclusion del Smartphone en el aula para un buen aprovechamiento del mismo.
Automatic Parallelisation of Quantum Circuits Using the Measurement Based Quantum Computing Model

The main focus of this work is to implement a program that can be used to parallelise quantum circuits. This is done by translating the quantum circuits to the Measurement Based Quantum Computing (MBQC) model, applying a number of optimising techniques to the computation in MBQC, and by translating it back to a quantum circuit. As a side result of implementing this method, a new algorithm for creating and optimising an MBQC graph from a quantum circuit is designed. The implemented program is used to investigate quantum circuits known from the literature: the QFT, and a specific type of "staircase" circuits. We show that our program will parallelise the "staircase" circuit to logarithmic depth, and increase the depth of QFT by a logarithmic factor. Finally, three new classes of quantum circuits are presented: the Toffoli staircase circuit, the Toffoli + CNOT staircase circuit, and a circuits consisting of quantum gates ∧Z, CNOT , ω , Z(α), and J(−2 ). In the computational experiments we perform, those classes of circuits will benefit from the parallelisation method implemented in this dissertation.
Managing dynamic medical data in a distributed mode

In telemedicine applications, it is necessary to archive and query some dynamic data of remote objects. Because the data is dynamic and usually of a huge amount, if we use the market available database server directly, it is difficult to archive dynamic data, and the huge amount of data makes communication very crowded. To solve this problem, we present a distributed management method which uses file servers and database servers to manage data objects and database tables respectively, and connect them with links in the records of the tables. Based on this mode, we design an archiving application running on the file server to archive dynamic data. After the dynamic data are archived, they can be queried as static data. To search a data object, an application queries the database server for contents of the data objects, and gets the link of the data object, then the application gets the data object from file server. For other applications, a transforming application protocol to support access of database in HL7 protocol has been designed. The results indicate that the proposed mode can simplify data management and improve communication condition.
Comprehending Structural Priming: A Connectionist Learning Account

Structural priming is a tendency to reuse previously produced sentence structures. It provides good evidence for syntactic representations in language use, and is informative about how experience with other structures influences those representations. A new connectionist model that does language learning is shown to be better able to explain a variety of structural priming results (compared to previous models), suggesting the same language learning mechanism can support syntax acquisition and structural priming.
VENM: An Algorithm to Accurately Calculate Neutral Slopes and Gradients

Mesoscale eddies stir along the neutral plane, and the resulting neutral diffusion is a fundamental aspect of subgrid‐scale tracer transport in ocean models. Calculating neutral diffusion traditionally involves calculating neutral slopes and three‐dimensional tracer gradients. The calculation of the neutral slope traditionally occurs by computing the ratio of the horizontal to vertical locally referenced potential density derivative. However, this approach is problematic in regions of weak vertical stratification, prompting the use of a variety of ad hoc regularization methods that can lead to rather nonphysical dependencies for the resulting neutral tracer gradients. Here we use a VErtical Non‐local Method “VENM,” a search algorithm that requires no ad hoc regularization and significantly improves the numerical accuracy of calculating neutral slopes, neutral tracer gradients, and associated neutral diffusive fluxes. We compare and contrast VENM against a more traditional method, using an independent objective neutrality condition combined with estimates of spurious diffusion, heat transport, and water mass transformation rates. VENM is more accurate, both physically and numerically, and should form the basis for future efforts involving neutral diffusion calculations from observations and possibly numerical model simulations.
TOWARDS POST-DISASTER DEBRIS IDENTIFICATION FOR PRECISE DAMAGE AND RECOVERY ASSESSMENTS FROM UAV AND SATELLITE IMAGES

Abstract. Often disasters cause structural damages and produce rubble and debris, depending on their magnitude and type. The initial disaster response activity is evaluation of the damages, i.e. creation of a detailed damage estimation for different object types throughout the affected area. First responders and government stakeholders require the damage information to plan rescue operations and later on to guide the recovery process. Remote sensing, due to its agile data acquisition capability, synoptic coverage and low cost, has long been used as a vital tool to collect information after a disaster and conduct damage assessment. To detect damages from remote sensing imagery (both UAV and satellite images) structural rubble/debris has been employed as a proxy to detect damaged buildings/areas. However, disaster debris often includes vegetation, sediments and relocated personal property in addition to structural rubble, i.e. items that are wind- or waterborne and not necessarily associated with the closest building. Traditionally, land cover classification-based damage detection has been categorizing debris as damaged areas. However, in particular in waterborne disaster such as tsunamis or storm surges, vast areas end up being debris covered, effectively hindering actual building damage to be detected, and leading to an overestimation of damaged area. Therefore, to perform a precise damage assessment, and consequently recovery assessment that relies on a clear damage benchmark, it is crucial to separate actual structural rubble from ephemeral debris. In this study two approaches were investigated for two types of data (i.e., UAV images, and multi-temporal satellite images). To do so, three textural analysis, i.e., Gabor filters, Local Binary Pattern (LBP), and Histogram of the Oriented Gradients (HOG), were implemented on mosaic UAV images, and the relation between debris type and their time of removal was investigated using very high-resolution satellite images. The results showed that the HOG features, among other texture features, have the potential to be used for debris identification. In addition, multi-temporal satellite image analysis showed that debris removal time needs to be investigated using daily images, because the removal time of debris may change based on the type of disaster and its location.
Extracellular potentials from action potentials of anatomically realistic neurons and neuronal populations.

Extracellular potentials due to firing of action potentials are computed around cortical neurons and populations of cortical neurons. These extracellular potentials are calculated as a sum of contributions from ionic currents passing through the cell membrane at various locations using Maxwell's equations in the quasi-static limit. These transmembrane currents are found from simulations of anatomically reconstructed cortical neurons implemented as multi-compartmental models in the simulation tool NEURON. Extracellular signatures of action potentials of single neurons are calculated both in the immediate vicinity of the neuron somas and along vertical axes. For the neuronal populations only vertical axis distributions are considered. The vertical-axis calculations were performed to investigate the contributions of action potential firing to laminar-electrode recordings. Results for high-pass (750 3000 Hz) filtered potentials are also given to mimic multi-unit activity (MUA) recordings. Extracellular traces from single neurons and populations (both synchronous and asynchronous) of neurons are shown for three different neuron types: layer 3 pyra-
An Examination of Rural Homestay Operations through the Lens of the Sustainable Livelihood Framework: A Case Study of Phou Khao Khouay National Park Community-Based Tourism (PKK NP CBT), Lao PDR

In many developing countries, Community-Based Tourism (CBT) is regarded as a sustainable tourism development tool as well as a catalyst for rural community development through the involvement of local people and the improvement of the standard of living. To extend the involvement of the local community in CBT, homestay tourism is a form of operation unit and its concept aims to facilitate individual household social-cultural and economic benefit from CBT directly. Although homestays are widely regarded as providing better livelihoods directly to the homestay operators, it is not clear to what extent homestay operations actually contribute to the sustainable livelihood of homestay operators when considering the wider livelihood implications. This research seeks to explore this gap by analysing homestay operators through the lens of Sustainable Livelihood theory (Scoones, 1998). This research adopts a post-positivist paradigm with qualitative methodology. Taking a case study approach, semi-structured interviews and observations were employed to collect primary data from community leaders, heads and deputy heads of the tourist guides, and homestay operators themselves. Results of the study found that although homestay tourism was initially established by the government. The study also found the main characteristics of the homestay operation are in a small size with a limitation of bedrooms, and a few family members involved in hosting tourists, which are husband, wife, and an adult child. All of these people are unpaid labour but receive benefits from the sharing of food and shelter. The study also uncovered that cash-based income, gender empowerment enhancement, and environmental enhancement were the positive impacts of homestay tourism on the livelihoods of the homestay operators, and these positive livelihood outcomes were in line with the original sustainable livelihood framework. In addition, cultural revitalisation was found as an emerged indicator of the sustainable livelihood outcomes, which was used to extend the revised framework. However, the study discovered that opportunity costs, culture shock, and conflict with villagers were negative implications affecting sustainable livelihood outcomes of the homestay operators. The revised Sustainable Livelihood Framework (SLF) suggests that if these negative implications are mitigated, the overall livelihood outcomes will be even greater. The results of this study are expected to provide a deeper understanding of how the impacts of homestay tourism on the sustainable livelihood of the homestay operators.
A Mixed Method Evaluation of a Culturally Adapted, Brief, Bullying Bystander Intervention for Middle School Students

The purpose of this mixed method study was to examine the appropriateness of a brief, bullying bystander intervention (STAC) adapted for a middle school in a low-income, rural community with a predominantly White and Hispanic student body. We were also interested in understanding the experiences of the students who participated in the intervention. Quantitative analysis suggested that students gained knowledge about bullying, increased their confidence to intervene in bullying situations, and used the STAC strategies to intervene in bullying behavior. Analyzing the qualitative data using Consensual Qualitative Research methodology ([CQR] Hill et al.) revealed four domains in which students (a) reported using the STAC strategies across multiple contexts and settings, (b) spoke about fears related to intervening in bullying, yet intervened despite those fears, (c) described emotional benefits experienced after participating in the intervention and while using the STAC strategies, and (d) reported stronger interpersonal relationship after participating in the STAC intervention. This study extends the literature by providing preliminary support for a brief, bystander intervention adapted to address the need for culturally relevant bullying interventions for low-income, rural, ethnically-blended schools.
Augmented Reality Mapping of Rock Mass Discontinuities and Rockfall Susceptibility Based on Unmanned Aerial Vehicle Photogrammetry

In rockfall hazard management, the investigation and detection of potential rockfall source areas on rock cliffs by remote-sensing-based susceptibility analysis are of primary importance. However, when the rockfall analysis results are used as feedback to the fieldwork, the irregular slope surface morphology makes it difficult to objectively locate the risk zones of hazard maps on the real slopes, and the problem of straightforward on-site visualization of rockfall susceptibility remains a research gap. This paper presents some of the pioneering studies on the augmented reality (AR) mapping of geospatial information from cyberspace within 2D screens to the physical world for on-site visualization, which directly recognizes the rock mass and superimposes corresponding rock discontinuities and rockfall susceptibility onto the real slopes. A novel method of edge-based tracking of the rock mass target for mobile AR is proposed, where the model edges extracted from unmanned aerial vehicle (UAV) structure-from-motion (SfM) 3D reconstructions are aligned with the corresponding actual rock mass to estimate the camera pose accurately. Specifically, the visually prominent edges of dominant structural planes were first explored and discovered to be a robust visual feature of rock mass for AR tracking. The novel approaches of visual-geometric synthetic image (VGSI) and prominent structural plane (Pro-SP) were developed to extract structural planes with identified prominent edges as 3D template models which could provide a pose estimation reference. An experiment verified that the proposed Pro-SP template model could effectively improve the edge tracking performance and quality, and this approach was relatively robust to the changes of sunlight conditions. A case study was carried out on a typical roadcut cliff in the Mentougou District of Beijing, China. The results validate the scalability of the proposed mobile AR strategy, which is applicable and suitable for cliff-scale fieldwork. The results also demonstrate the feasibility, efficiency, and significance of the geoinformation AR mapping methodology for on-site zoning and locating of potential rockfalls, and providing relevant guidance for subsequent detailed site investigation.
Storage Workload Characterization and Performance Prediction for Better I/O Traffic Management

In distributed high-performance computing storage systems, contention is a problem that usually occurs when the volume of client I/O requests exceeds the capability of storage servers; it degrades the whole system’s performance. The Storage Traffic Control System (STCS) is a critical component of a large system, which reduces the contention between clients, alleviates congestions in the system, and improves network and storage system efficiency. In a rule-based STCS, the building process for an optimal Storage Traffic Control Rule Set (STCRS) usually requires repetitious and lengthy benchmarking and tweaking cycles. Furthermore, most STCRSs are workload-specific and the established rule sets only matches to a limited subset of the actual workloads a storage system needs to handle. To add adaptiveness to the rule-based STCS, we present a performance prediction approach to help choosing existing STCRS for new workloads. This approach simplifies the traffic management for large-scale systems: instead of redesigning traffic control rules for each new workload the system receives, the proposed method extracts and measures the features of new workload and uses a regression tree pipeline to predict the performance improvement each control rule set bring to the new workload. The rule set that can best improve the performance of a workload will be chosen and applied to the new workload. Evaluation results show that most of the regression models we build have a high correlation coefficient (0.87) and low mean absolute error (3.8%). Using these performance prediction models, the suggested approach added adaptability to a rule based STCS by greatly increasing the amount of workloads that STCRSs can deal with.
Estimating High-Resolution Groundwater Storage from GRACE: A Random Forest Approach

Gravity Recovery and Climate Experiment (GRACE) data have become a widely used global dataset for evaluating the variability in groundwater storage for the different major aquifers. Moreover, the application of GRACE has been constrained to the local scale due to lower spatial resolution. The current study proposes Random Forest (RF), a recently developed unsupervised machine learning method, to downscale a GRACE-derived groundwater storage anomaly (GWSA) from 1° × 1° to 0.25° × 0.25° in the Northern High Plains aquifer. The RF algorithm integrated GRACE to other satellite-based geospatial and hydro-climatological variables, obtained from the Noah land surface model, to generate a high-resolution GWSA map for the period 2009 to 2016. This RF approach replicates local groundwater variability (the combined effect of climatic and human impacts) with acceptable Pearson correlation (0.58 ~ 0.84), percentage bias (−14.67 ~ 2.85), root mean square error (15.53 ~ 46.69 mm), and Nash-Sutcliffe efficiency (0.58 ~ 0.84). This developed RF model has significant potential to generate finer scale GWSA maps for managing groundwater at both local and regional scales, especially for areas with sparse groundwater monitoring wells.
Expression and localization of object invariants

One of the most difficult things in determining correctness of programs is the checking of cross-object invariants. Often, it is very simple to check whether or not an invariant is upheld inside of one object, but it is no trivial task to check these same constrains when then need to be upheld across objects. In this project, I have developed a tool, Hawk, that will help a user determine whether or not an invariant is upheld by isolating the section of Java code that is needed for the user to look at in order to determine whether or not the invariant is upheld. It does this by first building an object model of the compiled Java code, and the allowing the user to input the invariant based upon this object model. Thesis Supervisor: Daniel Jackson Title: Ross Professor of Software Technology
Supereigenvalue Problem to Addition-Min Fuzzy Matrix With Application in P2P File Sharing System

In this paper, supereigenvalue and constrained supereigenvalue problems of an addition-min fuzzy matrix are investigated. In a peer-to-peer file sharing system, the download requirement of the terminals could be described by a constant constraint system with addition-min fuzzy relation inequalities. Without considering the constant constraint system, we first study the supereigenvalue problem. While considering the constant constraint system, the so-called constrained supereigenvalue is further proposed and investigated. A constrained supereigenvalue represents the ratio of the data-download quality to the data-sending quality under a constant constraint. In order to arouse the enthusiasm of the terminals to share their local file data, we aim to maximize the constrained supereigenvalue. A nonlinear programming approach is developed to find the unique maximum constrained supereigenvalue, with some illustrative examples.
Acoplamiento en la Estimación de la Orientación y la Altura Mediante Filtro Extendido de Kalman

Los multicopteros han ganado gran popularidad en los ultimos anos por su capacidad de suspenderse en el aire manteniendo la posicion, y de esta manera realizar tareas que antes requerian costosa infraestructura o simplemente no eran posibles, como la captura de imagenes desde grandes alturas, inspecciones de lugares peligrosos como los interiores de torres de centrales termicas, represas, puentes, lineas de transmision de energia electrica, etc. La posicion del multicoptero en general es determinada por GPS o con algoritmos visuales. Sin embargo, el GPS tiene grandes errores en la estimacion de la altura, y la estimacion de posicion relativa mediante odometria visual necesita asistencia de un sensor de altura para resolver el problema de escala. Para determinar la altura de un vehiculo mediante un sonar o cualquier sensor de rango, es importante tener en cuenta la orientacion del vehiculo ya que al estar rigidamente vinculados, los cambios en la orientacion hacen que el eje de sensibilidad del sensor detecte una distancia mayor de la que se encuentra al suelo realmente. Este error en la estimacion de la altura no solo provocaria un error en la escala sino ademas produciria una posible perdida de sustentacion. Esto es muy comun en multicopteros ya que para cambiar de posicion, deben perder balance en el sentido que se espera el movimiento. En general, la orientacion es tenida en cuenta en la estimacion de altura con sonar, pero de una manera desacoplada, por un lado se determina la orientacion y por otro la altura teniendo en cuenta la orientacion ya calculada. En este trabajo se presenta un ﬁltro de Kalman que acopla la orientacion del vehiculo con la medicion de la distancia al suelo medida por un sensor de rango para determinar la altura. Se demuestra que utilizando el ﬁltro acoplado se atenua el ruido del sensor al mismo tiempo que se disminuye el error en la estimacion de la altura. Se muestran resultados obtenidos en simulaciones y con data-sets publicos.
Progressive Evolution of Designing Internet Maps on the example of Google Maps

In this article the author follows progressive evolution in web design that has been observed in Google Maps over the last 13 years (2005–2018). The analysis includes the graphic presentation of buttons, their layout and the changes in the functionality of the website. The results of the analysis corroborate the argument that it is possible to adapt the existing concept of progressive evolution, to the needs of Internet cartography. In the process of the analysis several crucial changes were spotted, such as the fact that as a result of the technological advancement the need to scroll the map with up, down, left and down buttons disappeared, being supplanted by the dragging function. In article all the discussed changes in Google Maps as an application for desktop computers and laptops, as well as a mobile application, prove that the product has been constantly improved. In the author’s opinion, the crucial aspect is to enrich the web map in the non-invasive way to make it as user-friendly and easy to use as possible. The synthetic juxtaposition allowed one to highlight the evolution, considered by the author an important feature of the non-invasive way of introducing changes. The author notes that progressive evolution on Google Maps and other internet maps will continue. It is important that the user’s needs are noticed during these changes.