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NOMBRE CÓDIGO - CATEGORIZACIÓN
NOMBRE CÓDIGO - CATEGORIZACIÓN
PROYECTO AMAZON
Kiara Lucas
Machine Teaching for Information Extraction
Machine Teaching for Information Extraction
Recent work on information extraction has suggested that fast, interactive tools can be highly effective; however, creating a usable system is challenging, and few publically available tools exist. In this paper we present IKE, a new extraction tool that performs fast, interactive bootstrapping to develop high-quality extraction patterns for targeted relations, and provides novel solutions to these usability concerns. In particular, it uses a novel query language that is expressive, easy to understand, and fast to execute - essential requirements for a practical system - and is the first interactive extraction tool to seamlessly integrate symbolic and distributional methods for search. An initial evaluation suggests that relation tables can be populated substantially faster than by manual pattern authoring or using fully automated tools, while retaining accuracy, an important step towards practical knowledge-base construction.
sumithra
Why it's good that Soulstealer Vayne is so hard to get - a statistical Analysis
Why it's good that Soulstealer Vayne is so hard to get - a statistical Analysis
I analyzed the Hextech-Crafting in a Stochastic Simulation with 10 Million Players and found that you're going to make more Riot Points than you spend (in value) and thats without counting Champs. I've made some assumptions, which can be found down in the paper itself for those interested. For everyone else: If you're trying to maximize your RP-Net-Worth stack up on Hextech Chests.
WORST BRUISER EU
Analysis Of Using Social Network On Higher Education
Analysis Of Using Social Network On Higher Education
The Internet has become the broadest area in which to exchange information and communicate.Some use this function in a positive way, whilst others do so negatively. With the growth of the Internet, social networks have also grown. Social networks are used in different fields and for different proposes. They are used in higher education to enhance training and collaborative learning and exchange knowledge in an interaction environment. This paper aims at finding the 10 best universities by measuring the use of social networks in education.Universities are selected for this experiment from the Academic Influence Ranking website for the domain of computer science overall (type A) (for more information about the selected universities please visit this link: http://pubstat.org/).
fatimah
HPCSYSPROS18 Paper/Description Template
HPCSYSPROS18 Paper/Description Template
This document is a combination of the SC18 IEEE proceedings format and a modified SC18 artifact descriptor to be used for the HPCSYSPROS18 CFP. More information here: https://github.com/HPCSYSPROS/CFP18
Stephen Harrell
The Noscuk
The Noscuk
Let's take a look into the dynamic history of the Noscuk valley and its people.
Eugenia Anane-Wae
WebLab1
WebLab1
本次Lab设计一个家庭(宿舍、实验室)网络。说明用户需求(功能及服务),采用的技术(802.11/802.3)及主要设备的型号、传输介质及其特性,给出网络结构的描述(可用Visio工具绘图),所需费用;提出一些与技术与应用相关的问题。ISP提供的接口:有线电视、移动、联通、电信 用户计算机数:台式机、笔记本、智能手机使用方式及性能:固定、移动;带宽需求典型设备:AP路由器、交换机、专用服务器网络安装与测试费用:设备购置、使用费、维护费。
DrLC
Household daily-peak electricity load forecasting with statistical models
Household daily-peak electricity load forecasting with statistical models
This article proposes to obtain a statistical model of the daily peak electricity load of a household located in Austin-TX,USA. The Box-Jenkins methodology was followed to obtain the best fit for the time-series. Four models provided a good fit: ARIMA(0,1,2), ARIMA(1,1,2), SARIMA(0,1,2)(0,1,1) and SARIMA(1,1,2)(0,1,1). The model with the highest Akaike Information Criteria was the ARIMA(1,2,2). However, the model with the highest forecast accuracy was the SARIMA(1,1,2)(0,1,1), which obtained an RMSE of 0.296 and a MAPE Of 15.00.
Luciano Viola
Deployment and topology of a wireless sensor network for precision viticulture
Deployment and topology of a wireless sensor network for precision viticulture
Precision viticulture is a specialization of precision agriculture techniques applied to viticulture. Precision agriculture is the use of information system technologies applied to agricultural production. Some of the applicable technologies are; Wireless Sensor Networks (WSN), Global Positioning Systems (GPS), spectroscopy analysis of Near-Infrared (NIR), Geographic Information Systems (GIS). These systems provide means of observation, evaluation and control of agricultural activities. The farmers demand assistant systems to perform actions for saving time and avoiding risks. There are studies of maps crops and mesh-sampling techniques to predict the harvest volume in a vineyard with a certain varieties of grapes. The prediction is based on a previous study of crops over a period of three to four years. Along these three or four years a large volume of samples is taken to study several parameters. In this application area is where the wireless sensor networks technologies would have high incidence. In this context we intend to analyse, at first place, the specific characteristics of the operational environment of a vineyard. Second, we will analyse the most appropriate architecture for a sensor network in this environment. Application of wireless sensor networks technology can take many forms depending of environment, and implementation objectives. In this paper we discuss about the best procedure for deployment and the optimal topology of a wireless sensor network for viticulture.
Gregorio Corral

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