Miracle-dz/UniFAR-FTUs huggingface dataset:
Resource-Efficient and Robust Distributed Computing

There has been a tremendous growth in the size of distributed systems in the past three decades. Today, distributed systems, such as the Internet, have become so large that they require highly scalable algorithms; algorithms that have asymptotically-small communication, computation, and latency costs with respect to the network size. Moreover, systems with thousands or even millions of parties distributed throughout the world is likely in danger of faults from untrusted parties. In this dissertation, we study scalable distributed algorithms that can tolerate faults from untrusted parties. We consider three different security models: adversarial, rational, and costcompetitive. Throughout this work, we balance two important and often conflicting characteristics of distributed protocols: security and efficiency. Our first contribution is building an asynchronous algorithm for secure Multi-Party Computation (MPC) over n players. MPC is a fundamental problem in distributed computing that allows a set of players to jointly compute an arbitrary function of their inputs, without revealing these inputs to each other. We propose a scalable MPC algorithm assuming strictly less than a 1/8 fraction of the players are controlled by a static adversary. For any function f over a field that can be computed by a circuit with m gates, our algorithm requires each player to send a number of field elements and perform an amount of computation that is Õ( n + √ n). This significantly improves over traditional algorithms, which require each player to both send a number of messages and perform computation that is Ω(nm). To achieve this result, we define and solve a new problem called threshold counting problem in the asynchronous setting. Our solution is load-balanced, with computation, communication, and latency complexity of O(log n), and may be useful for designing other load-balanced applications in the asynchronous communication model. As an important building block of MPC algorithms in the rational setting, we study the classical secret sharing problem in a model where all players are rational. To the best of our knowledge, all known mechanisms for this problem require each player to send O(n) messages in expectation. As our second contribution in this dissertation, we describe mechanisms for rational secret sharing. Our first result is a mechanism for n-out-of-n rational secret sharing that is Nash equilibrium,
Recursion and the competence/performance distinction in AGL tasks

The term “recursion” is used in at least four distinct theoretical senses within cognitive science. Some of these senses in turn relate to the different levels of analysis described by David Marr some 20 years ago; namely, the underlying competence capacity (the computational level), the performance operations used in real-time processing (the algorithmic level), and the neural implementation (the hardware level). It is demonstrated here that the current focus of the artificial grammar learning literature on recursion blurs the different levels, resulting in three main corollaries: (1) the literature cannot tell us anything about the first level, as the explanation for the role of recursion therein lies elsewhere; (2) it has not studied the possible recursive processing of artificial strings properly, as studies have so far focused on the correct processing of the internal hierarchy of recursive structures, but none have attempted to probe the underlying processing operations; and (3) as a consequence, much cannot in fact be known about the neural basis of recursion. It is furthermore argued that, in general, these studies can actually tell us very little about the language faculty, and some programmatic remarks are described and defended towards a more coherent study.
lgcp An R Package for Inference with Spatio-Temporal Log-Gaussian Cox Processes

This paper introduces an R package for spatio-temporal prediction and forecasting for log-Gaussian Cox processes. The main computational tool for these models is Markov chain Monte Carlo and the new package, lgcp, therefore also provides an extensible suite of functions for implementing MCMC algorithms for processes of this type. The modelling framework and details of inferential procedures are rst presented before a tour of lgcp functionality is given via a walk-through data-analysis. Topics covered include reading in and converting data, estimation of the key components and parameters of the model, specifying output and simulation quantities, computation of Monte Carlo expectations, post-processing and simulation of data sets.
Effective Screening and Joint Modeling for High-Throughput Genomic Data Analysis.

RHYNE, JACOB DAVIS. Effective Screening and Joint Modeling for High-Throughput Genomic Data Analysis. (Under the direction of Dr. X. Jessie Jeng). When analyzing genetic data, many current modeling methods are computationally infeasible, due to the size of the data. This dissertation explores two possible solutions to this problem: screening to reduce the number of predictors or making modeling methods more computationally efficient. The first chapter introduces key background information and gives an overview of key developments in relevant statistical methodology. The second chapter presents a screening method–where SNP ranking and screening is based on the Higher Criticism (HC) statistic–to be performed prior to joint modeling of the expression of genes and SNPs. It is shown that the HC-based SNP screening can greatly reduce the computational burden of joint modeling and improve the power for eQTL mapping. The third chapter considers a well-known joint modeling method, LORS, which is computationally infeasible for large data. An alternative method is proposed to solve the LORS optimization problem with less computational time required. The proposed method and LORS are applied to data from the International HapMap Project to illustrate the performance of each. The fourth chapter presents a new joint modeling procedure which extends the debiased lasso (DLasso) to a multivariate response. This method addresses a weakness of LORS in that statistical inference can be performed after joint modeling. It is shown that the proposed procedure can effectively control false discoveries and identify a large proportion of true signals. © Copyright 2019 by Jacob Davis Rhyne
Feature Points Matching Algorithm based on Homography Constraint and Gray Scale Truncation Number

A measure function is used to judge whether match in boost matching. In this paper, we offer a kind of new measure function called GST. We simply use the relationship between gray differences and threshold of the points of domain tests the matching degree. We use homography and GST to improve the number and precision of correspondences of SIFT matching. Firstly, homography is estimated using the result of SIFT matching by VRANSAC. Then, wrong correspondences are eliminated by homography. Finally, we use GST and homography to boost matching the wrong correspondences. Experiments with the Oxford datasets show that our method can get better performance than the existed methods.
Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC)

It is well established that people with diabetes have an increased risk of cardiovascular disease and cardiovascular death compared to people without diabetes. Until recently there has been a lack of information on cardiovascular risk reduction in people with type 1 diabetes, especially the younger population. Previous studies looking specifically at glycaemic control have been few in number and the results inconsistent. The DCCT trial demonstrated that a period of intensive insulin therapy and improvement in HbA1c% reduced the incidence and progression of microvascular complications, but macrovascular events were not significantly reduced. The DCCT/EDIC study was the long-term observational follow up of patients from DCCT, and was used to evaluate whether intensive therapy reduced cardiovascular events in patients with type 1 diabetes. The patients treated intensively in the original DCCT trial had a 42% reduction in any first cardiovascular event when compared to the conventionally treated group, and the risk of first occurrence of non-fatal myocardial infarction, stroke or death from cardiovascular disease was reduced by 57%. DCCT/EDIC provides us with long-term, objective documentation of glycaemic control and its relationship to cardiovascular complications. However, until we find methods of bringing down HbA1c% without the added problem of frequent hypoglycaemia, we may find it difficult to translate these findings into our everyday practice. Copyright © 2007 John Wiley & Sons.
Clinical Observation of Azelnidipine on Mild to Moderate Hypertension

Objective To explore the effect and safety of Azelnidipine on mild to mederate hypertensive patients.Methods In this double-blind control study,61 patients were randomly divided into two groups the Azelnidipine group(n=40)received Azelnidipine 8-16 mg once every day,Amlodipine group(n=21)once every day with a period of 6 weeks.Results The SBP and DBP decreased significantly in both Azelnidipine group and Amlodipine group 2 weeks,4 weeks,6 weeks,8 weeks after the treatment(P0.05). After 2 weeks,4 weeks,6 weeks,8 weeks' treatment,the SBP and DBP between Azelnidipine group and Amlodipine group had no significant difference(P0.05). Conclusion The treatment with Azelnidipine,5-10 mg once every day can decrease the blood pressure of mild to mederate hypertensive patients,and have a good medication compliance.
Prevalence of Anti thyroid peroxidase (Anti TPO) in type 1 diabetes mellitus

Aims: The aim of our study was to determine the prevalence of anti-thyroid peroxidase (anti-TPO) and tyrosine phosphatase (IA2) antibodies positivity in glutamic acid decarboxylase (GAD65) antibody positive type 1 diabetics. Methods: Seventy five type 1 diabetic patients with GAD65+ve were included in this hospital based study. IA -2 and Anti TPO antibodies were measured in this cohort Results: In GAD65 +ve Type 1 diabetics the TPO antibody positivity was found in 58.7%(44/75) patients, Females had higher prevalence of TPO antibodies positive than the males(73% vs. 44.7%, P = 0.019). Positive IA-2A is present in 68.2 % males and 55.5 % females in Type 1 diabetic patients who were Gad 65 positivity. Conclusions: There is a high prevalence of Anti TPO positivity in our Type 1 diabetic patients who are Gad 65 positive. So thyroid autoimmunity should be screened at diagnosis in all our Type 1 diabetic patients.
An Approach To Graphics Passthrough In Cloud Virtual Machines

Growing need of cloud computing services makes it more challenging field for cloud providers and researchers. After a brief introduction of Xen hypervisor paper discusses the problem of inefficient access to graphics accelerators in cloud. The reason behind such problem is proprietary models and heterogeneity in architecture of graphics processors. This paper focuses on such problem of GPU (Graphical Processing Unit) acceleration by providing a sample GPU passthrough model. At the last we will discuss the advantages of such technique and its future.
Prédiction du mouvement humain pour la robotique collaborative: du geste accompagné au mouvement corps entier.Prediction of human movement for collaborative robotics: from accompanied gesture to whole-body movement.

This thesis lies at the intersection between machine learning and humanoid robotics, under the theme of human-robot interaction and within the cobotics (collaborative robotics) field. It focuses on prediction for non-verbal human-robot interactions, with an emphasis on gestural interaction. The prediction of the intention, understanding, and reproduction of gestures are therefore central topics of this thesis. First, the robots learn gestures by demonstration : a user grabs its arm and makes it perform the gestures to be learned several times. The robot must
A NEW FRAMEWORK DESIGNED FOR KNOWLEDGE MANAGEMENT IN DISTRIBUTED SOFTWARE DEVELOPMENT

The software development with distributed teams becomes a critical popular nowadays. Not only for the efficiency and effectiveness the distributed teams provide, but also the distributed teams can supply whole-day works with lower costs. Software development is a kind of knowledge-driven industry which depends on the expertise of employees. Although many scholars have long investigated knowledge management as well as distributed software development, the combination that knowledge management in distributed software development is not a enough explored topic in the past decade’s years. In this paper, a review of relevant extant literature on knowledge management in distributed software development is provided. The relationship between two objects and the factors on knowledge sharing are summarized. By analysis of the characteristics and features of knowledge management, the social media-based framework of knowledge management for distributed software development is proposed.
A spatiotemporal data and indexing

Spatiotemporal databases support historical information as well as spatial management at the same time. However, it is very complex to manage these two dimensions where there exist differences in the inherent properties of temporal and spatial dimensions. Therefore, an efficient data model and access method for the integrated dimension should be studied, and it can be achieved by means of development of efficient indexing technology. We suggest a spatiotemporal data model that supports a bitemporal concept for spatial objects. We also propose a unified spatiotemporal index model as an efficient index for spatiotemporal data to efficiently handle both spatial and temporal data.
Data Flow Analysis Frameworks for Concurrent Programs

Data flow analysis is a well studied family of static program analyses. A rich theoretical basis for data flow analysis has been developed. Central to this theory is the concept of data flow framework. These frameworks are a semantically well-founded formalism for specifying a data flow analysis. A variety of solution algorithms for problems specified as data flow frameworks have been developed. The bulk of the research on data flow analysis has been done in the context of analysis of sequential programs. Unfortunately, a number of important assumptions of this work are violated when we apply data flow analysis results to concurrent programs. In this paper, we extend data flow frameworks for sequential program analysis to accommodate concurrent programs. We present solution algorithms for these extended frameworks and reason about their convergence and complexity.
Marching cubes: a high resolution 3D surface construction algorithm

We present a new algorithm, called marching cubes, that creates triangle models of constant density surfaces from 3D medical data. Using a divide-and-conquer approach to generate inter-slice connectivity, we create a case table that defines triangle topology. The algorithm processes the 3D medical data in scan-line order and calculates triangle vertices using linear interpolation. We find the gradient of the original data, normalize it, and use it as a basis for shading the models. The detail in images produced from the generated surface models is the result of maintaining the inter-slice connectivity, surface data, and gradient information present in the original 3D data. Results from computed tomography (CT), magnetic resonance (MR), and single-photon emission computed tomography (SPECT) illustrate the quality and functionality of marching cubes. We also discuss improvements that decrease processing time and add solid modeling capabilities.
A church-based intervention to promote physical activity in Black adolescent girls

The purpose of this study was to conduct a feasibility test of a 12-week church-based physical activity intervention that was culturally sensitive and age and gender specific that would affect attitudes of black adolescent girls that would increase participation in physical activity. The design for this proposed study was a one-group pre- and post-test design. Black adolescent girls, ages 12-18, were recruited from two predominantly black churches in Durham, North Carolina. Paired t-tests and repeated measures of ANOVA revealed no significant changes in key variables. Positive changes were noted with Odds ratios on attitudes, self-efficacy and intention. BMI, METs, and fitness showed positive trends from pre to post intervention. Family support was significantly correlated with one measure of physical activity level. Although, findings were not statistically significant, the intervention did created an interest in the girls for the need and continuation of physical activity. Conducting culturally tailored physical activity programs in black churches aimed at black adolescent girls are feasible and required to reduce the decline in physical activity during adolescence and the associated increases in obesity, high blood pressure and heart disease among this population.
Herramienta de segmentación semiautomática de imágenes mediante visión por computador

El proyecto propone una herramienta de segmentacion semiautomatica de imagenes usando vision por computador. El objectivo es poder segmentar imagenes que contienen gestos realizados con las manos para su posterior interpretacion como parte de una aplicacion posterior. Para llevar a cabo esta herramienta primeramente se realiza un estudio del estado del arte para poder analitzar las capacidades de las herramientas actuales que ya realizan esta funcion, tratando de aprovechar lo que estas nos oferecen. Posteriormente al estudio se explica el desarrollo de la nueva herramienta, que consta de tres fases: preprocesamiento de la imagen, generacion semiautomatica de marcadores mediante el metodo connected labeled components, y la utilizacion del algoritmo Watershed que finalmente se encarga de hacer la segmentacion final. Los resultados preliminares mostrados en este documento indican un gran potencial de la tecnica desarrollada, ofreciendo resultados prometedores de segmentacion sin requerir del usuario final mas que marcar un punto en la imagen.
Analyzing and Specifying Security Requirements in Early Stages of Software Development Life Cycle

As of lately, more and more studies show that, at a global level, one of the most important causes of economic loss is unauthorized access to informatics resources. For example, a CSI/FBI Computer Crime and Security report from 2006 states that, in the top identified causes for economic loss in the USA, unauthorized access to informatics resources takes second place (Gordon et. al., 2006). Without a doubt, given the accelerated growth of software industry in the present, this need of security should be taken into account in Romania as a top priority. At the moment, in the requirements extraction phase from the software development life cycle, importance is given only to functional requirements. Thus appears the problem of identifying adequate solutions for treating non-functional requirements, where security requirements are included.
Big Social Data for Social and Information Scientists

This workshop aims to help build Big Social Data collection, management, analysis and visualization research competencies in the iSchool Community. We will share our strategies, methods, and tools using data of interest to participants. We propose three paths to participation. First, participants interested in big data who do not yet have well formed research questions, will be provided with public data sets collected from Twitter. Second, participants may submit research questions and corresponding search terms in advance of the workshop; we will use our existing Twitter data collection infrastructure, TwitterZombie (Black, Mascaro, Gallagher, & Goggins, 2012), to collect public data on their behalf under our existing IRB at Drexel University. Third, participants may submit a structurally representative, anonymized sample of corpora to analyze using one of our published methodological approaches; we will evaluate the structure of the data to determine appropriateness.
Qualidade de mudas de pepino produzidas em substratos à base de esterco ovino

O estudo de residuos agricolas como insumos pode ser uma alternativa para sua reciclagem. Objetivou-se avaliar a qualidade de mudas de pepino cv. Caipira produzidas com substratos a base de esterco ovino. O experimento foi conduzido em viveiro da Universidade Federal Rural de Pernambuco, Serra Talhada. Utilizou-se o delineamento inteiramente casualizado, com quatro repeticoes. Os tratamentos avaliados foram: T1 – substrato comercial; T2 – esterco ovino + areia (1:1); T3 – esterco ovino + areia (2:1); T4 – esterco ovino + areia (3:1); T5 – esterco ovino + solo (1:1); T6 – esterco ovino + solo (2:1); T7 – esterco ovino + solo (3:1); T8 – esterco ovino + areia + solo (1:1:1);T9 – esterco ovino + areia + solo (2:1:1); T10 – esterco ovino + areia + solo (3:1:1). Os indicadores de emergencia avaliados foram: porcentagem, primeira contagem, indice de velocidade e tempo medio de emergencia. Analisaram-se as seguintes caracteristicas de desenvolvimento: numero de folhas, altura de plântula, diâmetro de caule, comprimento de raizes, massa seca da parte aerea e das raizes. O substrato comercial proporcionou melhor vigor de mudas de pepino cv. Caipira. Por outro lado, o uso do esterco ovino mais solo (1:1), para compor substratos alternativos constitui-se opcao viavel para a producao de mudas dessa cultivar.
Be Cordial Hotels & Resorts, una apuesta de un grupo de emprendedores por la expansión en el mercado turístico y por la sostenibilidad

Be Cordial Hotels & Resorts es una cadena hotelera que comenzo su actividad en enero de 2004 en la isla de Gran Canaria (Archipielago Canario, Espana), y que actualmente gestiona integramente mas de 1.735 unidades alojativas ademas de 214 unidades alojativas en gestion comercial. Con todo ello el numero de unidades comercializadas se eleva a 1.949 que, en el ejercicio 2017, aportaron una facturacion neta consolidada de 60 millones de euros. A finales de 2018 el Grupo gestiona 12 establecimientos en Gran Canaria y Lanzarote y gestiona comercialmente un hotel en Republica Dominicana, la primera incursion internacional de una cadena con vocacion de expandirse de forma sosegada e imparable. Los inicios de esta empresa hotelera estan marcados por la colaboracion y el entendimiento de muchos emprendedores canarios del ramo de automocion y alimentacion que aportaron el sentido de profesionalidad y cordialidad que impregna el espiritu de esta empresa desde los anos 80. Su apuesta por la expansion y la diferenciacion, han llevado a la empresa a consolidar una importante posicion en el mercado turistico canario. La empresa, ademas, ha estado guiada por una filosofia de gestion basada en la sostenibilidad medioambiental, el trato amable y cordial a sus huespedes, asi como su compromiso con el entorno social, historico y cultural, valores que le han permitido lograr la certificacion “Oro” de Travelife (organizacion de reconocimiento europeo en auditoria de turismo sostenible).