<?xml version='1.0' encoding='UTF-8'?><?xml-stylesheet href="http://www.blogger.com/styles/atom.css" type="text/css"?><feed xmlns='http://www.w3.org/2005/Atom' xmlns:openSearch='http://a9.com/-/spec/opensearchrss/1.0/' xmlns:blogger='http://schemas.google.com/blogger/2008' xmlns:georss='http://www.georss.org/georss' xmlns:gd="http://schemas.google.com/g/2005" xmlns:thr='http://purl.org/syndication/thread/1.0'><id>tag:blogger.com,1999:blog-4694815573867137083</id><updated>2024-12-18T19:31:10.558-08:00</updated><category term="Cursos"/><category term="mestrado"/><category term="Agrupamento de Dados"/><category term="Clustering"/><category term="Escrita Científica"/><category term="Inglês"/><category term="Mineração de Dados"/><category term="Restrições"/><title type='text'>Quase Mestre</title><subtitle type='html'>Saiba o que um aluno de mestrado faz!</subtitle><link rel='http://schemas.google.com/g/2005#feed' type='application/atom+xml' href='http://quasemestre.blogspot.com/feeds/posts/default'/><link rel='self' type='application/atom+xml' href='http://www.blogger.com/feeds/4694815573867137083/posts/default'/><link rel='alternate' type='text/html' href='http://quasemestre.blogspot.com/'/><link rel='hub' href='http://pubsubhubbub.appspot.com/'/><author><name>Anonymous</name><uri>http://www.blogger.com/profile/18365707535183571778</uri><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='16' height='16' src='https://img1.blogblog.com/img/b16-rounded.gif'/></author><generator version='7.00' uri='http://www.blogger.com'>Blogger</generator><openSearch:totalResults>8</openSearch:totalResults><openSearch:startIndex>1</openSearch:startIndex><openSearch:itemsPerPage>25</openSearch:itemsPerPage><entry><id>tag:blogger.com,1999:blog-4694815573867137083.post-1351431979001109519</id><published>2014-02-04T05:07:00.000-08:00</published><updated>2014-02-04T05:07:48.307-08:00</updated><category scheme="http://www.blogger.com/atom/ns#" term="Cursos"/><category scheme="http://www.blogger.com/atom/ns#" term="Escrita Científica"/><category scheme="http://www.blogger.com/atom/ns#" term="mestrado"/><title type='text'>Escrita científica: clareza e objetividade</title><content type='html'>&lt;div style=&quot;text-align: justify;&quot;&gt;
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&lt;a href=&quot;https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjjuseTlraeKSA8zThq_HZOGlbQUqtNKlZt3q9XJIYKexbvQLuKpnZPNPmkvxLvRwpTDCqCB4uzAQYAsVAUHIvNlCUzmJmicYUtiexklBaQHdCgchyx3sxO66Eib8PRrf3zko_6IqKe6E7z/s1600/escrita-cient%C3%ADfica.jpg&quot; imageanchor=&quot;1&quot; style=&quot;margin-left: 1em; margin-right: 1em;&quot;&gt;&lt;img border=&quot;0&quot; src=&quot;https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjjuseTlraeKSA8zThq_HZOGlbQUqtNKlZt3q9XJIYKexbvQLuKpnZPNPmkvxLvRwpTDCqCB4uzAQYAsVAUHIvNlCUzmJmicYUtiexklBaQHdCgchyx3sxO66Eib8PRrf3zko_6IqKe6E7z/s1600/escrita-cient%C3%ADfica.jpg&quot; height=&quot;416&quot; width=&quot;640&quot; /&gt;&lt;/a&gt;&lt;/div&gt;
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A escrita e publicação de um artigo científico são as últimas etapas do processo de pesquisa e têm o intuito de apresentar nossas ideias e resultados à sociedade, porém, do que adianta publicar se ninguém compreender a relevância do seu trabalho?&amp;nbsp;&lt;/div&gt;
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Muitos autores seguem a famosa frase de Harry Truman: “se não puder convencê-los, confunda-os”, porém esse é um péssimo hábito. Uma boa escrita transmite de forma direta a intenção do autor, com clareza e objetividade.&lt;/div&gt;
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Geralmente somos aconselhados a descrever nossas pesquisas utilizando a terceira pessoa e a voz passiva, isso é muito estranho, pois não deixa clara a participação do autor e sugere que as coisas simplesmente aconteceram por si sós. &amp;nbsp;Preste atenção nos seguintes trechos:&lt;/div&gt;
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&lt;span style=&quot;color: red;&quot;&gt;1. Grandes diferenças nos tempos de reação dos dois estudos foram encontradas.&lt;/span&gt;&lt;br /&gt;
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&lt;span style=&quot;color: blue;&quot;&gt;2. Nós observamos grandes diferenças nos tempos de reação dos dois estudos.&lt;/span&gt;&lt;br /&gt;
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Os experimentos e análises não surgem do nada, os autores têm responsabilidade sobre suas pesquisas e devem demonstrar confiança sobre o que publicam. Veja que a utilização da voz ativa na segunda frase deixa o texto mais direto, melhorando a interpretação e clareza de ideias.&lt;/div&gt;
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Um erro comum que cometemos é adicionar palavras ou expressões sem necessidade, principalmente quando estamos escrevendo artigos em inglês. Veja os exemplos a seguir:&lt;/div&gt;
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&lt;span style=&quot;text-align: justify;&quot;&gt;&lt;span style=&quot;color: red;&quot;&gt;1. This paper provides a review of the basic tenets of cancer biology study design, using as examples studies that ilustrate the methodologic challenges or that demonstrate successful solutions to the difficulties inherent in biological research.&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style=&quot;text-align: left;&quot;&gt;
&lt;span style=&quot;text-align: justify;&quot;&gt;&lt;span style=&quot;color: red;&quot;&gt;&lt;br /&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style=&quot;text-align: left;&quot;&gt;
&lt;span style=&quot;text-align: justify;&quot;&gt;&lt;span style=&quot;color: blue;&quot;&gt;2. This paper reviews cancer biology study design, using examples that illustrate specific challenges and solutions.&lt;/span&gt;&lt;/span&gt;&lt;br /&gt;
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&lt;span style=&quot;text-align: justify;&quot;&gt;Observe que a segunda versão da frase ficou muito melhor, simples e direta. Uma frase concisa é sempre preferível à um texto enorme que diz a mesma coisa.&lt;/span&gt;&lt;br /&gt;
&lt;span style=&quot;text-align: justify;&quot;&gt;&lt;br /&gt;&lt;/span&gt;
&lt;span style=&quot;text-align: justify;&quot;&gt;O texto científico geralmente está atrelado a temas complexos — destinados a públicos específicos — que podem conter vários conceitos técnicos e jargões, mas em sua essência um artigo deve ser compreensível para todos que buscam conhecimento.&amp;nbsp;&lt;/span&gt;&lt;br /&gt;
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Escrever qualquer texto extenso demanda tempo e paciência, principalmente quando estamos descrevendo experimentos, metodologias e resultados de pesquisas científicas. A chance de ficar perfeito de primeira é mínima, são necessárias inúmeras revisões e ajustes, portanto não desista e revise quantas vezes for necessário!&lt;/div&gt;
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&lt;div style=&quot;text-align: justify;&quot;&gt;
Para quem se interessou pelo assunto e deseja melhorar suas técnicas de escrita recomendo os cursos online &lt;a href=&quot;https://www.coursera.org/course/sciwrite&quot; target=&quot;_blank&quot;&gt;Writing in the Sciences&lt;/a&gt; — oferecido pela universidade Stanford — e &lt;a href=&quot;http://www.escritacientifica.com/&quot; target=&quot;_blank&quot;&gt;Escrita Científica&lt;/a&gt; – oferecido pela USP.&lt;/div&gt;
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Comente e compartilhe! Contribua para o crescimento do blog e mande sua sugestão de tema para contato.quasemestre@gmail.com.&lt;/div&gt;
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</content><link rel='replies' type='application/atom+xml' href='http://quasemestre.blogspot.com/feeds/1351431979001109519/comments/default' title='Postar comentários'/><link rel='replies' type='text/html' href='http://quasemestre.blogspot.com/2014/02/escrita-cientifica-clareza-e.html#comment-form' title='1 Comentários'/><link rel='edit' type='application/atom+xml' href='http://www.blogger.com/feeds/4694815573867137083/posts/default/1351431979001109519'/><link rel='self' type='application/atom+xml' href='http://www.blogger.com/feeds/4694815573867137083/posts/default/1351431979001109519'/><link rel='alternate' type='text/html' href='http://quasemestre.blogspot.com/2014/02/escrita-cientifica-clareza-e.html' title='Escrita científica: clareza e objetividade'/><author><name>Anonymous</name><uri>http://www.blogger.com/profile/18365707535183571778</uri><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='16' height='16' src='https://img1.blogblog.com/img/b16-rounded.gif'/></author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjjuseTlraeKSA8zThq_HZOGlbQUqtNKlZt3q9XJIYKexbvQLuKpnZPNPmkvxLvRwpTDCqCB4uzAQYAsVAUHIvNlCUzmJmicYUtiexklBaQHdCgchyx3sxO66Eib8PRrf3zko_6IqKe6E7z/s72-c/escrita-cient%C3%ADfica.jpg" height="72" width="72"/><thr:total>1</thr:total></entry><entry><id>tag:blogger.com,1999:blog-4694815573867137083.post-265896564518479632</id><published>2014-01-24T08:21:00.000-08:00</published><updated>2014-01-24T08:27:45.360-08:00</updated><category scheme="http://www.blogger.com/atom/ns#" term="mestrado"/><title type='text'>Qual Sistema Operacional utilizar no mestrado, Linux ou Windows?</title><content type='html'>&lt;div align=&quot;CENTER&quot; style=&quot;margin-bottom: 0cm;&quot;&gt;
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&lt;a href=&quot;https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjADQaRtjQzNDE4eJpYxwv9ry_W7WJIjdotxbom-7GK1O75rKD-ZxCxMaYangdegVstR5D8jeJXou8sVLjkPYXFfcOxJts_im0jF2xobHAh656FI-HdpYuKhWu1SSh-smzJRdvYFXr4RBc/s1600/lw.png&quot; imageanchor=&quot;1&quot; style=&quot;margin-left: 1em; margin-right: 1em;&quot;&gt;&lt;img border=&quot;0&quot; src=&quot;https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjADQaRtjQzNDE4eJpYxwv9ry_W7WJIjdotxbom-7GK1O75rKD-ZxCxMaYangdegVstR5D8jeJXou8sVLjkPYXFfcOxJts_im0jF2xobHAh656FI-HdpYuKhWu1SSh-smzJRdvYFXr4RBc/s1600/lw.png&quot; height=&quot;320&quot; width=&quot;640&quot; /&gt;&lt;/a&gt;&lt;/div&gt;
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Muitos
artigos na internet nos deixam fascinados sobre a descrição das
distribuições Linux e/ou Windows. Mas algumas informações fazem
apenas aumentar a dúvida da qual escolher. Trazendo esse assunto
para o mestrado, pode-se perguntar: O sistema operacional que está
sendo utilizado realmente faz alguma diferença? É uma questão
interessante a ser levantada, pois isso possibilita ou não a ter um
melhor rendimento nos estudos.&lt;br /&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div style=&quot;margin-bottom: 0cm; text-align: center;&quot;&gt;
&lt;/div&gt;
&lt;div style=&quot;margin-bottom: 0cm; text-align: justify;&quot;&gt;
Este
artigo tem o objetivo de comentar um pouco sobre esses dois sistemas
operacionais de forma mais imparcial possível (pois atualmente
utilizo os dois sistemas operacionais, mais especificamente Windows 8
e Ubuntu 13.10), para ajudar o leitor a fazer a escolha certa,
evitando preconceitos que muitos usuários tanto de Windows como de
Linuxs têm.&lt;br /&gt;
&lt;br /&gt;&lt;/div&gt;
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&lt;a href=&quot;https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEif8zklQlWZPvlQSRQ0_bA7xumH6kyg1mFPrTMhYqWuBKbrc6oKGWt4U4vVx7beTAWBEN-3kUSoHKE4BoPnSv67PHzTDgeHzTgFuTAWnykSHKdwfToNJHA1V4pi34rokMsDegWKmRFUaOA/s1600/lw.png&quot; imageanchor=&quot;1&quot; style=&quot;margin-left: 1em; margin-right: 1em;&quot;&gt;&lt;img border=&quot;0&quot; src=&quot;https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEif8zklQlWZPvlQSRQ0_bA7xumH6kyg1mFPrTMhYqWuBKbrc6oKGWt4U4vVx7beTAWBEN-3kUSoHKE4BoPnSv67PHzTDgeHzTgFuTAWnykSHKdwfToNJHA1V4pi34rokMsDegWKmRFUaOA/s1600/lw.png&quot; height=&quot;283&quot; width=&quot;320&quot; /&gt;&lt;/a&gt;&lt;/div&gt;
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&lt;div align=&quot;CENTER&quot; style=&quot;margin-bottom: 0cm;&quot;&gt;
&lt;b&gt;&lt;span style=&quot;font-size: large;&quot;&gt;O sistema operacional
pode influenciar nos estudos?&lt;/span&gt;&lt;/b&gt;&lt;/div&gt;
&lt;div align=&quot;CENTER&quot; style=&quot;margin-bottom: 0cm;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div style=&quot;margin-bottom: 0cm; text-align: justify;&quot;&gt;
Essa
pergunta é muito interessante, pois, de maneira quase imperceptível,
o sistema operacional (SO) pode atrasar vários projetos, trabalhos e
tarefas. Isso ocorre devido ao fato de que a quantidade de tempo
gasto para se instalar uma ferramenta em um determinado sistema
operacional pode fazer uma grande diferença. 
&lt;br /&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div style=&quot;margin-bottom: 0cm; text-align: justify;&quot;&gt;
Os
programas feitos para os Windows sempre são fáceis de instalar
(pelo menos a maioria deles), apenas apertando o botão &lt;i&gt;next
&lt;/i&gt;muitas vezes instala sem
problema algum, e isso é vantajoso, pois é rápido, fácil e
prático, mas
as vezes é trabalhoso achar um site confiável, já que o maior medo
dos usuários que usam
este sistema operacional é ser infectado por qualquer tipo de &lt;i&gt;vírus&lt;/i&gt;.
O
tempo gasto para encontrar o site e
fazer o download do arquivo é
muito grande, além de que o
arquivo baixado pode não ser
o arquivo certo! Isso quase
mata muitos
de raiva, ou seja, a procura
do programa continua, e pode levar mais muito tempo.&lt;br /&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div style=&quot;margin-bottom: 0cm; text-align: justify;&quot;&gt;
No
Linux, é mais fácil? Isso também varia,
pois dependendo da distribuição Linux, supondo
que seja uma distribuição que não tenha a
central de programas (central
de programas é um &lt;i&gt;software &lt;/i&gt;que
mostra uma lista de todos
os programas disponíveis que podem
ser instalados
no seu Linux, sendo que a instalação e
procura se torna muito mais
fácil do que o próprio Windows),
volta ao caso explicado
anteriormente (de
procurar
a ferramenta na internet),
lógico que não existe
a preocupação do seu computador pegar
&lt;i&gt;vírus&lt;/i&gt;, e
isto é uma grande vantagem
das distribuições Linuxs,
mas após baixar o programa, vêm a grande dificuldade, a instalação.

&lt;br /&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div style=&quot;margin-bottom: 0cm; text-align: justify;&quot;&gt;
&lt;/div&gt;
&lt;div style=&quot;margin-bottom: 0cm; text-align: justify;&quot;&gt;
Muitos
blogs
e fóruns
da internet ensinam
a fazer instalação, mas os tutoriais podem ser bem
complicados para algo que supostamente é simples, e muitos não dão
certo ou foram feitos para &lt;i&gt;experts&lt;/i&gt;
(que conhecem
muito bem o SO),
os quais ocultam detalhes imaginando
que os usuários
que estão
seguindo (a
risca)
o tutorial já saibam.
Isto infelizmente complica a vida de muitos, pois, por não ter dado
certo a primeira tentativa,
correm atrás de outro tutorial, e por ter começado uma instalação
de forma incorreta, a outra também pode não
dar certo.&lt;br /&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div style=&quot;margin-bottom: 0cm; text-align: justify;&quot;&gt;
Um
profundo conselho é, se for seguir um tutorial de um fórum ou um
blog, verifique
primeiro as
experiências dos outros
usuários (&lt;i&gt;cobaias&lt;/i&gt;)
que tentaram,
e certifique se eles conseguiram instalar com êxito ou não, se mais
de uma pessoa comentou que as instruções seguidas deram certo,
se torna confiável o tutorial, caso contrário, procure outro.
Utilize
também, uma
distribuição Linux que tenha uma central de programas
(ex: Ubuntu, Fedora, Mint e
outros), pois as vantagens
são grandes. Na central de programas, se
tem
o que você procura, coloque para instalar e pronto, resta apenas
desfrutar da ferramenta, o
que torna a instalação muito mais fácil do que no
Windows, já que basta apenas um clique.

&lt;br /&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div style=&quot;margin-bottom: 0cm; text-align: justify;&quot;&gt;
Esses
casos mencionados, podem levar horas ou até mesmo dias, quando se
trata do mestrado, pois os &lt;i&gt;softwares &lt;/i&gt;utilizados
são quase todos complicados e com difícil instalação, e ainda
mais, o programa pode ser para um sistema operacional em especifico,
para o Linux como exemplo o banco de dados Hbase, e para o Windows o
ArtoolKit. É interessante você ter um dual-boot (dois sistemas
operacionais na sua máquina) ou máquinas virtuais, pois,
os professores
de disciplinas diferentes podem
pedir
para instalar duas ferramentas especificas
uma para o Linux e outro para o Windows. Então não perca
tempo e já deixe sua máquina pronta, antecipando
e otimizando o seu tempo
para acelerar os seus estudos.&lt;/div&gt;
&lt;div align=&quot;JUSTIFY&quot; style=&quot;margin-bottom: 0cm;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align=&quot;CENTER&quot; style=&quot;margin-bottom: 0cm;&quot;&gt;
&lt;b&gt;&lt;span style=&quot;font-size: large;&quot;&gt;Refletindo
sobre os Linux e Windows&lt;/span&gt;&lt;/b&gt;&lt;/div&gt;
&lt;div align=&quot;JUSTIFY&quot; style=&quot;margin-bottom: 0cm;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align=&quot;JUSTIFY&quot; style=&quot;margin-bottom: 0cm;&quot;&gt;
O
mais sensato a ser feito é aprender o máximo sobre esses sistemas
operacionais, deixando de lado o preconceito, pois existem
muitos programas legais e
úteis no Windows e não têm
no Linux, e o contrário também é verdade. Um exemplo simples é a
gravadora
de CD, a ferramenta Nero é ótima e sem defeito para o Windows,
já no caso do Linux as
ferramentas com essa finalidade deixam muito a desejar.
Enquanto que o editor LateX e
visualizador de PDF no Linux são melhore que no Windows.&lt;br /&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align=&quot;JUSTIFY&quot; style=&quot;margin-bottom: 0cm;&quot;&gt;
O
certo, seria ensinar todas as pessoas a utilizar os dois sistemas
operacionais, já que hoje em dia, pode-se dizer sem medo algum que
o Linux e o Windows estão
praticamente do mesmo nível em questão de qualidade, utilidade e
aparência. 
&lt;br /&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align=&quot;JUSTIFY&quot; style=&quot;margin-bottom: 0cm;&quot;&gt;
Nem
tudo é perfeito, tanto o Windows como o Linux têm sua desvantagem.
A principal desvantagem do Windows é a o perigo de infectar o
computador com qualquer tipo de &lt;i&gt;vírus&lt;/i&gt;,
que estão
em toda parte da internet, CD, &lt;i&gt;pendrives&lt;/i&gt;,
HD externo e dentre outros.  Isso realmente é muito chato, pois além
do &lt;i&gt;vírus &lt;/i&gt;roubar
informações, controlar seu computador, infectar outros dispositivos
(máquinas fotográficas, celulares, MP3, MP4, e etc),
pode danificar o sistema operacional a tal ponto que têm que
reinstalar tudo de novo. Fora o medo que é constante de pegar vírus
de alguma pessoa que não cuida do seu computador. O
Linux, neste ponto é muito bom, mas o seu principal ponto fraco é a
pequena quantidade
de programas bons que faz com que muitos usuários não se interessem
por esse sistema operacional. 
&lt;br /&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div align=&quot;JUSTIFY&quot; style=&quot;margin-bottom: 0cm;&quot;&gt;
&lt;/div&gt;
&lt;div align=&quot;JUSTIFY&quot; style=&quot;margin-bottom: 0cm;&quot;&gt;
Após
experimentar esses dois sistemas você notará que compensa não
apenas experimentar um ou outro, mas ter ambos e usá-los diariamente
em seus estudos, pois
quanto mais tempo você os utilizar, começará
a notar suas vantagens e
consequentemente os preconceitos finalmente desaparecerão.&lt;/div&gt;
</content><link rel='replies' type='application/atom+xml' href='http://quasemestre.blogspot.com/feeds/265896564518479632/comments/default' title='Postar comentários'/><link rel='replies' type='text/html' href='http://quasemestre.blogspot.com/2014/01/qualsistema-operacional-utilizar-no.html#comment-form' title='0 Comentários'/><link rel='edit' type='application/atom+xml' href='http://www.blogger.com/feeds/4694815573867137083/posts/default/265896564518479632'/><link rel='self' type='application/atom+xml' href='http://www.blogger.com/feeds/4694815573867137083/posts/default/265896564518479632'/><link rel='alternate' type='text/html' href='http://quasemestre.blogspot.com/2014/01/qualsistema-operacional-utilizar-no.html' title='Qual Sistema Operacional utilizar no mestrado, Linux ou Windows?'/><author><name>Anonymous</name><uri>http://www.blogger.com/profile/02603191106845298428</uri><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='16' height='16' src='https://img1.blogblog.com/img/b16-rounded.gif'/></author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjADQaRtjQzNDE4eJpYxwv9ry_W7WJIjdotxbom-7GK1O75rKD-ZxCxMaYangdegVstR5D8jeJXou8sVLjkPYXFfcOxJts_im0jF2xobHAh656FI-HdpYuKhWu1SSh-smzJRdvYFXr4RBc/s72-c/lw.png" height="72" width="72"/><thr:total>0</thr:total></entry><entry><id>tag:blogger.com,1999:blog-4694815573867137083.post-1380985187975817531</id><published>2014-01-10T05:03:00.000-08:00</published><updated>2014-01-10T05:17:19.628-08:00</updated><category scheme="http://www.blogger.com/atom/ns#" term="Agrupamento de Dados"/><category scheme="http://www.blogger.com/atom/ns#" term="Clustering"/><category scheme="http://www.blogger.com/atom/ns#" term="Mineração de Dados"/><category scheme="http://www.blogger.com/atom/ns#" term="Restrições"/><title type='text'>Agrupamento Semi-Supervisionado</title><content type='html'>&lt;div class=&quot;separator&quot; style=&quot;clear: both; text-align: center;&quot;&gt;
&lt;a href=&quot;http://3.bp.blogspot.com/-7bdxbN7ILtE/Us_oxcbLNgI/AAAAAAAADC4/Ni2lq7MIDgU/s1600/plot_mean_shift.png&quot; imageanchor=&quot;1&quot; style=&quot;margin-left: 1em; margin-right: 1em;&quot;&gt;&lt;img border=&quot;0&quot; src=&quot;http://3.bp.blogspot.com/-7bdxbN7ILtE/Us_oxcbLNgI/AAAAAAAADC4/Ni2lq7MIDgU/s1600/plot_mean_shift.png&quot; /&gt;&lt;/a&gt;&lt;/div&gt;
&lt;div class=&quot;separator&quot; style=&quot;clear: both; text-align: justify;&quot;&gt;
&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;&lt;br /&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div class=&quot;separator&quot; style=&quot;clear: both; text-align: justify;&quot;&gt;
&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;Na
área de Mineração de Dados o &lt;b&gt;agrupamento&lt;/b&gt;,
ou &lt;b&gt;&lt;i&gt;clustering&lt;/i&gt;&lt;/b&gt;
como é mais conhecido, é a tarefa de agrupar um conjunto de dados em subconjuntos
que possuam algum grau de similaridade, de forma que, os dados pertencentes ao
mesmo grupo tenham características semelhantes. Esse processo pode ser
realizado basicamente de três formas:&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div class=&quot;separator&quot; style=&quot;clear: both; text-align: justify;&quot;&gt;
&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;&lt;br /&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div class=&quot;separator&quot; style=&quot;clear: both; text-align: justify;&quot;&gt;
&lt;/div&gt;
&lt;ol&gt;
&lt;li&gt;&lt;span style=&quot;font-size: 15px; line-height: 16.866666793823242px;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;&lt;b&gt;&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;agrupamento supervisionado&lt;/span&gt;&lt;/b&gt;&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;, em que se conhece os rótulos dos dados a
partir de um conhecimento de domínio, também conhecido como classificação;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/li&gt;
&lt;li&gt;&lt;span style=&quot;font-size: 15px; line-height: 16.866666793823242px;&quot;&gt;&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;&lt;b&gt;&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;agrupamento não-supervisionado&lt;/span&gt;&lt;/b&gt;&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;, no qual não se tem nenhuma ideia sobre o
conjunto de dados, e que o processo agirá sem qualquer conhecimento prévio para
criar uma quantidade &lt;i&gt;x&lt;/i&gt;&amp;nbsp;&lt;/span&gt;&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;de
grupos;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/li&gt;
&lt;li&gt;&lt;span style=&quot;font-size: 15px; line-height: 16.866666793823242px;&quot;&gt;&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;&lt;b&gt;&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;agrupamento semi-supervisionado&lt;/span&gt;&lt;/b&gt;&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt; é o método mais recente entre os três, e tem
sido um tópico bastante abordado nos últimos anos, ele funciona com uma pequena
quantidade de informação a priori sobre os dados.&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/li&gt;
&lt;/ol&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;&lt;br /&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;As
informações utilizadas pelo agrupamento semi-supervisionado podem ser
representadas de duas maneiras: rótulos em parte dos dados ou restrições. Na
primeira, uma pequena quantidade do conjunto de dados é rotulada e servirá como
uma base de treinamento para que posteriormente o resto dos dados do conjunto
sejam agrupados com base nesse pequeno conjunto inicial. Na segunda, a
informação a priori é representada por restrições, a qual funciona
principalmente entre dois tipos: &lt;i&gt;must-link&lt;/i&gt;
– indica que dois elementos do conjunto de dados devem pertencer ao mesmo grupo;
e &lt;i&gt;cannot-link&lt;/i&gt; – indica que dois
elementos do conjunto não podem pertencer ao mesmo grupo.&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;&lt;br /&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;A
figura abaixo mostra um conjunto de dados representado em um espaço euclidiano,
em que a distância entre dois elementos diz o quanto eles são similares, isto é,
quanto mais distantes dois elementos estão no plano, mais diferentes eles são. Os
atributos relevantes dos dados para a representação no espaço são o peso e a
altura. As linhas contínuas entre dois elementos representam uma restrição &lt;i&gt;must-link&lt;/i&gt;, e as linhas pontilhadas entre
dois elementos representam uma restrição &lt;i&gt;cannot-link&lt;/i&gt;.&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style=&quot;font-family: Calibri, sans-serif; text-align: justify;&quot;&gt;
&lt;span style=&quot;font-family: &amp;quot;Calibri&amp;quot;,&amp;quot;sans-serif&amp;quot;; font-size: 11.0pt; line-height: 115%; mso-ansi-language: PT-BR; mso-ascii-theme-font: minor-latin; mso-bidi-font-family: &amp;quot;Times New Roman&amp;quot;; mso-bidi-language: AR-SA; mso-bidi-theme-font: minor-bidi; mso-fareast-font-family: Calibri; mso-fareast-language: EN-US; mso-fareast-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;&quot;&gt;&lt;br /&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div class=&quot;separator&quot; style=&quot;clear: both; font-family: Calibri, sans-serif; text-align: center;&quot;&gt;
&lt;a href=&quot;http://3.bp.blogspot.com/-77vD1DwOXtU/Us_qAbR9BfI/AAAAAAAADDA/ZMNvKl-3_Vg/s1600/Untitled.png&quot; imageanchor=&quot;1&quot; style=&quot;margin-left: 1em; margin-right: 1em;&quot;&gt;&lt;img border=&quot;0&quot; src=&quot;http://3.bp.blogspot.com/-77vD1DwOXtU/Us_qAbR9BfI/AAAAAAAADDA/ZMNvKl-3_Vg/s1600/Untitled.png&quot; height=&quot;228&quot; width=&quot;640&quot; /&gt;&lt;/a&gt;&lt;/div&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;&lt;br /&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;Perceba
que a informação contida nas restrições (lado direito da figura) altera uma
forma intuitiva de agrupamento que seria feita por um processo
não-supervisionado (lado esquerdo da figura).&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;&lt;br /&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;Dentre
os vários exemplos de utilização desse processo de agrupamento
semi-supervisionado, trago aqui um dos mais comuns apresentados em trabalhos
científicos. Suponha uma base de dados com milhares de imagens sobre um
determinado domínio, por exemplo, animais. Agora imagine que nessas imagens possuam
animais de todos os possíveis tipos e você deseja agrupá-las de alguma forma,
mas não tem ideia de quantos grupos possam existir nesse conjunto ou de como
poderá agrupá-las. Uma ideia para resolver esse problema, usada por alguns
autores na literatura, seria dividir esse processo em duas etapas:&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;&lt;br /&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
&lt;ol&gt;
&lt;li&gt;&lt;span style=&quot;font-size: 15px; line-height: 16.866666793823242px;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;Realizar
um processo totalmente não supervisionado, como uma espécie de pré-processamento
dos dados, para que sejam criados uma determinada quantidade &lt;i&gt;x&lt;/i&gt;&lt;/span&gt;&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&amp;nbsp;de grupos preliminares.&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/li&gt;
&lt;li&gt;&lt;span style=&quot;font-size: 15px; line-height: 16.866666793823242px;&quot;&gt;&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;A partir daí, o usuário ou especialista do domínio entra em cena para verificar a corretude
desses grupos, dizendo, por exemplo, se duas imagens devem pertencer a aquele
grupo (&lt;i&gt;must-link&lt;/i&gt;) ou se duas imagens
não podem pertencer ao mesmo grupo (&lt;i&gt;cannot-link&lt;/i&gt;).
Logo após ter inserido uma quantidade satisfatória (ao usuário) de
conhecimento, é realizado o processo de agrupamento novamente, mas agora
levando em consideração as restrições inferidas pelo usuário, e assim
sucessivamente até que se tenha chegado a um resultado satisfatório.&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/li&gt;
&lt;/ol&gt;
&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;&lt;br /&gt;&lt;/span&gt;&lt;/span&gt;
&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;
Além
disso, podem ser criadas restrições em relação aos grupos, por exemplo, o
usuário pode dizer que uma determinada imagem não pode pertencer a um certo
grupo, cria-se então uma restrição entre um elemento e um grupo.&amp;nbsp; Isso só foi mencionado para mostrar que podem
existir vários tipos de restrições com vários conceitos diferentes, mas isso é
um assunto para um próximo &lt;i&gt;post&lt;/i&gt;.&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&lt;span style=&quot;font-family: inherit;&quot;&gt;&lt;br /&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
&lt;span style=&quot;font-family: inherit;&quot;&gt;&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;Espero
que tenham gostado e para finalizar a minha primeira postagem nesse blog peço
que entrem em contato a qualquer dúvida, não deixe de comentar, com dicas,
críticas (construtivas de preferência) ou sugestões.&lt;/span&gt;&lt;span style=&quot;font-size: 11pt; line-height: 115%;&quot;&gt;&amp;nbsp;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
</content><link rel='replies' type='application/atom+xml' href='http://quasemestre.blogspot.com/feeds/1380985187975817531/comments/default' title='Postar comentários'/><link rel='replies' type='text/html' href='http://quasemestre.blogspot.com/2014/01/agrupamento-semi-supervisionado.html#comment-form' title='0 Comentários'/><link rel='edit' type='application/atom+xml' href='http://www.blogger.com/feeds/4694815573867137083/posts/default/1380985187975817531'/><link rel='self' type='application/atom+xml' href='http://www.blogger.com/feeds/4694815573867137083/posts/default/1380985187975817531'/><link rel='alternate' type='text/html' href='http://quasemestre.blogspot.com/2014/01/agrupamento-semi-supervisionado.html' title='Agrupamento Semi-Supervisionado'/><author><name>Unknown</name><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='16' height='16' src='https://img1.blogblog.com/img/b16-rounded.gif'/></author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="http://3.bp.blogspot.com/-7bdxbN7ILtE/Us_oxcbLNgI/AAAAAAAADC4/Ni2lq7MIDgU/s72-c/plot_mean_shift.png" height="72" width="72"/><thr:total>0</thr:total></entry><entry><id>tag:blogger.com,1999:blog-4694815573867137083.post-6439211422048376627</id><published>2013-12-29T05:19:00.000-08:00</published><updated>2013-12-29T05:19:26.412-08:00</updated><category scheme="http://www.blogger.com/atom/ns#" term="Cursos"/><title type='text'>Cursos Online Gratuitos</title><content type='html'>&lt;div class=&quot;MsoNormal&quot;&gt;
&lt;div class=&quot;separator&quot; style=&quot;clear: both; text-align: center;&quot;&gt;
&lt;a href=&quot;https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjPcny6ynRUX6nnuuW5Yteyu1Jnrn5y1rNfs3IKNm68XnRNcqNSDNe03irlbWp8_YweORkRs8xrxznIkJwIb2ufhX8KKjWeZ9BqUw6L14-DkuPVY8p2xZ5IaP3Qdm1YLxlgZss6a5_1wFBx/s1600/estudar.JPG&quot; imageanchor=&quot;1&quot; style=&quot;margin-left: 1em; margin-right: 1em;&quot;&gt;&lt;img border=&quot;0&quot; src=&quot;https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjPcny6ynRUX6nnuuW5Yteyu1Jnrn5y1rNfs3IKNm68XnRNcqNSDNe03irlbWp8_YweORkRs8xrxznIkJwIb2ufhX8KKjWeZ9BqUw6L14-DkuPVY8p2xZ5IaP3Qdm1YLxlgZss6a5_1wFBx/s1600/estudar.JPG&quot; height=&quot;369&quot; width=&quot;640&quot; /&gt;&lt;/a&gt;&lt;/div&gt;
&lt;span id=&quot;goog_220179232&quot;&gt;&lt;/span&gt;&lt;span id=&quot;goog_220179233&quot;&gt;&lt;/span&gt;&lt;br /&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
Muitos profissionais buscam aprender coisas novas e ter um diferencial na formação para melhorar seu currículo com novas habilidades, porém, a rotina de trabalho pode impossibilitar a participação em cursos presenciais. O ambiente de aprendizagem online pode resolver esse problema, fornecendo maior flexibilidade de horários e de conteúdo.&lt;/div&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot;&gt;
A internet é uma fonte inesgotável de &lt;s&gt;coisas inúteis&lt;/s&gt; conhecimento,
existem diversos sites especializados que oferecem cursos online gratuitos. &amp;nbsp;Veja
a lista a abaixo:&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div class=&quot;MsoListParagraphCxSpFirst&quot; style=&quot;mso-list: l0 level1 lfo1; text-indent: -18.0pt;&quot;&gt;
&lt;/div&gt;
&lt;ul&gt;
&lt;li&gt;&lt;span style=&quot;font-family: Symbol; text-indent: -18pt;&quot;&gt;·&lt;span style=&quot;font-family: &#39;Times New Roman&#39;; font-size: 7pt;&quot;&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
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&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;text-indent: -18pt;&quot;&gt;&lt;a href=&quot;http://www.skillshare.com/&quot; target=&quot;_blank&quot;&gt;Skillshare&lt;/a&gt;&lt;/span&gt;&lt;/li&gt;
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&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;text-indent: -18pt;&quot;&gt;&lt;a href=&quot;https://www.coursera.org/&quot; target=&quot;_blank&quot;&gt;Coursera&lt;/a&gt;&lt;/span&gt;&lt;/li&gt;
&lt;li&gt;&lt;span style=&quot;font-family: Symbol; text-indent: -18pt;&quot;&gt;·&lt;span style=&quot;font-family: &#39;Times New Roman&#39;; font-size: 7pt;&quot;&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;text-indent: -18pt;&quot;&gt;&lt;a href=&quot;http://www.veduca.com.br/&quot; target=&quot;_blank&quot;&gt;Veduca&lt;/a&gt;&lt;/span&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;!--[if !supportLists]--&gt;&lt;o:p&gt;&lt;/o:p&gt;&lt;br /&gt;
&lt;div class=&quot;MsoListParagraphCxSpMiddle&quot; style=&quot;mso-list: l0 level1 lfo1; text-indent: -18.0pt;&quot;&gt;
&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoListParagraphCxSpMiddle&quot; style=&quot;mso-list: l0 level1 lfo1; text-indent: -18.0pt;&quot;&gt;
&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoListParagraphCxSpMiddle&quot; style=&quot;mso-list: l0 level1 lfo1; text-indent: -18.0pt;&quot;&gt;
&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoListParagraphCxSpLast&quot; style=&quot;mso-list: l0 level1 lfo1; text-indent: -18.0pt;&quot;&gt;
&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot;&gt;
Em especial para os profissionais de TI:&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot;&gt;
&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div&gt;
&lt;div class=&quot;MsoListParagraphCxSpFirst&quot; style=&quot;mso-list: l0 level1 lfo1; text-indent: -18.0pt;&quot;&gt;
&lt;/div&gt;
&lt;ul&gt;
&lt;li&gt;&lt;span style=&quot;font-family: Symbol; text-indent: -18pt;&quot;&gt;·&lt;span style=&quot;font-family: &#39;Times New Roman&#39;; font-size: 7pt;&quot;&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;text-indent: -18pt;&quot;&gt;&lt;a href=&quot;http://www.codecademy.com/pt&quot; target=&quot;_blank&quot;&gt;Codecademy&lt;/a&gt;&lt;/span&gt;&lt;/li&gt;
&lt;li&gt;&lt;span style=&quot;font-family: Symbol; text-indent: -18pt;&quot;&gt;·&lt;span style=&quot;font-family: &#39;Times New Roman&#39;; font-size: 7pt;&quot;&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;a href=&quot;http://noticias.universia.com.br/ciencia-tecnologia/noticia/2013/06/12/1029980/52-cursos-online-gratuitos-profissionais-ti.html&quot; target=&quot;_blank&quot;&gt;
&lt;/a&gt;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;text-indent: -18pt;&quot;&gt;&lt;a href=&quot;http://noticias.universia.com.br/ciencia-tecnologia/noticia/2013/06/12/1029980/52-cursos-online-gratuitos-profissionais-ti.html&quot; target=&quot;_blank&quot;&gt;Lista de 52 cursos online gratuitos&lt;/a&gt;&lt;/span&gt;&lt;/li&gt;
&lt;li&gt;&lt;span style=&quot;font-family: Symbol; text-indent: -18pt;&quot;&gt;·&lt;span style=&quot;font-family: &#39;Times New Roman&#39;; font-size: 7pt;&quot;&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;text-indent: -18pt;&quot;&gt;&lt;a href=&quot;http://www.caelum.com.br/apostilas/&quot; target=&quot;_blank&quot;&gt;Apostilas&lt;/a&gt;&lt;/span&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;span style=&quot;font-family: Calibri, sans-serif; font-size: 15px; line-height: 16px;&quot;&gt;&lt;br /&gt;&lt;/span&gt;
Bons estudos!&lt;/div&gt;
</content><link rel='replies' type='application/atom+xml' href='http://quasemestre.blogspot.com/feeds/6439211422048376627/comments/default' title='Postar comentários'/><link rel='replies' type='text/html' href='http://quasemestre.blogspot.com/2013/12/cursos-online-gratuitos.html#comment-form' title='2 Comentários'/><link rel='edit' type='application/atom+xml' href='http://www.blogger.com/feeds/4694815573867137083/posts/default/6439211422048376627'/><link rel='self' type='application/atom+xml' href='http://www.blogger.com/feeds/4694815573867137083/posts/default/6439211422048376627'/><link rel='alternate' type='text/html' href='http://quasemestre.blogspot.com/2013/12/cursos-online-gratuitos.html' title='Cursos Online Gratuitos'/><author><name>Anonymous</name><uri>http://www.blogger.com/profile/18365707535183571778</uri><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='16' height='16' src='https://img1.blogblog.com/img/b16-rounded.gif'/></author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjPcny6ynRUX6nnuuW5Yteyu1Jnrn5y1rNfs3IKNm68XnRNcqNSDNe03irlbWp8_YweORkRs8xrxznIkJwIb2ufhX8KKjWeZ9BqUw6L14-DkuPVY8p2xZ5IaP3Qdm1YLxlgZss6a5_1wFBx/s72-c/estudar.JPG" height="72" width="72"/><thr:total>2</thr:total></entry><entry><id>tag:blogger.com,1999:blog-4694815573867137083.post-9196027737372795547</id><published>2013-12-18T10:19:00.001-08:00</published><updated>2014-01-24T08:27:32.361-08:00</updated><category scheme="http://www.blogger.com/atom/ns#" term="mestrado"/><title type='text'>O que fazer depois da graduação?</title><content type='html'>&lt;div class=&quot;separator&quot; style=&quot;clear: both; text-align: center;&quot;&gt;
&lt;a href=&quot;https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhou8NFo0Ln38iDxoSaltIOiW19bEFkYYtjBg2ngORw9LkdR1k1twFzMn1LTqudvRUEgdmpXmxkiFDJOqocHd_ZBjrWwMifL4JpuDVZZm6UXO95fUFhOvpnqwWi5I340M9lpYFFbAko27cK/s1600/Romans-6_9-why-did-he-die.jpg&quot; imageanchor=&quot;1&quot; style=&quot;margin-left: 1em; margin-right: 1em;&quot;&gt;&lt;img border=&quot;0&quot; src=&quot;https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhou8NFo0Ln38iDxoSaltIOiW19bEFkYYtjBg2ngORw9LkdR1k1twFzMn1LTqudvRUEgdmpXmxkiFDJOqocHd_ZBjrWwMifL4JpuDVZZm6UXO95fUFhOvpnqwWi5I340M9lpYFFbAko27cK/s1600/Romans-6_9-why-did-he-die.jpg&quot; height=&quot;424&quot; width=&quot;640&quot; /&gt;&lt;/a&gt;&lt;/div&gt;
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&lt;br /&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;text-align: justify;&quot;&gt;
Ao terminar a graduação sentimos
uma mistura de vários sentimentos, entre eles está o de dever cumprido, de
alegria, de saudade e também de desespero, pois o que supostamente era para ser o fim é
apenas o começo.&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;text-align: justify;&quot;&gt;
&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
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&lt;br /&gt;&lt;/div&gt;
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Pode-se dizer que saímos melhor
do que entramos, mas definitivamente não saímos prontos. Nesse momento da vida
é como se estivéssemos em uma encruzilhada com dezenas de caminhos possíveis e
a dúvida é tão grande que acabamos ficando paralisados ou pior, agindo por
impulso (decidindo fazer algo somente pelo fato de que a maioria vai fazer).&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;text-align: justify;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
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&lt;a href=&quot;https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiJlkkrGD3mjWxhPI4GvOcgk4_i65sf3rGlc_rvTKSE5srM8ieHAZRzlsIy5eDcSI7Waf7CoisMtbVcU46i8z8SSprIobPfQCMVHIf9GdeZzP0OGFJ01H1Ae4jIoks2i9T9rHIoK3C4eAhyphenhyphen/s1600/encruzilhada_gradua%C3%A7%C3%A3o.PNG&quot; imageanchor=&quot;1&quot; style=&quot;margin-left: 1em; margin-right: 1em;&quot;&gt;&lt;img border=&quot;0&quot; src=&quot;https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiJlkkrGD3mjWxhPI4GvOcgk4_i65sf3rGlc_rvTKSE5srM8ieHAZRzlsIy5eDcSI7Waf7CoisMtbVcU46i8z8SSprIobPfQCMVHIf9GdeZzP0OGFJ01H1Ae4jIoks2i9T9rHIoK3C4eAhyphenhyphen/s1600/encruzilhada_gradua%C3%A7%C3%A3o.PNG&quot; height=&quot;480&quot; width=&quot;640&quot; /&gt;&lt;/a&gt;&lt;/div&gt;
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&lt;br /&gt;&lt;/div&gt;
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Muitos consideram o término da
graduação como um ponto final, que representa uma transição para o mundo “adulto”
e o mundo do “mercado de trabalho”, no qual não é preciso mais estudar. Esse é
um pensamento ingênuo, pois se você pretende crescer profissionalmente em um
mundo onde o conhecimento e a informação são as maiores formas de poder, ficar
parado não é uma boa opção.&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;text-align: justify;&quot;&gt;
&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
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&lt;br /&gt;&lt;/div&gt;
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Para os que pretendem continuar
estudando existem diversas possibilidades, falaremos algumas delas a seguir:&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;text-align: justify;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
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&lt;/div&gt;
&lt;h3&gt;
&lt;ul&gt;
&lt;li&gt;&lt;span style=&quot;font-family: Symbol; text-indent: -18pt;&quot;&gt;·&lt;span style=&quot;font-family: &#39;Times New Roman&#39;; font-size: 7pt;&quot;&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;text-indent: -18pt;&quot;&gt;Certificação&lt;/span&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;/h3&gt;
&lt;o:p&gt;&lt;/o:p&gt;&lt;br /&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
Geralmente as
certificações surgem como uma demanda de mercado e são formas de suprir áreas do
conhecimento que não foram abordadas na graduação.&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
Podem estar
relacionadas a tecnologias ou metodologias específicas, sendo na maioria das
vezes conferido por empresas ou instituições que requerem profissionais
capacitados.&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
Apesar de ser
uma boa opção como diferencial profissional, as certificações têm caráter
temporário, pois devem ser atualizadas na mesma frequência em que as novas
tecnologias ou produtos são lançados. &lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div class=&quot;MsoListParagraph&quot; style=&quot;mso-list: l0 level1 lfo1; text-align: justify; text-indent: -18.0pt;&quot;&gt;
&lt;/div&gt;
&lt;h3&gt;
&lt;ul&gt;
&lt;li&gt;&lt;span style=&quot;font-family: Symbol; text-indent: -18pt;&quot;&gt;·&lt;span style=&quot;font-family: &#39;Times New Roman&#39;; font-size: 7pt;&quot;&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;text-indent: -18pt;&quot;&gt;Especialização&lt;/span&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;/h3&gt;
&lt;!--[if !supportLists]--&gt;&lt;o:p&gt;&lt;/o:p&gt;&lt;br /&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
O objetivo da
especialização é o de ampliar o conhecimento do aluno em determinadas áreas,
permitindo que ele adquira recursos e ferramentas pra aplicar rapidamente ao
seu dia a dia de trabalho.&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
São cursos
voltados para o aperfeiçoamento e a atualização do profissional, permitindo um
melhor direcionamento na carreira.&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div class=&quot;MsoListParagraph&quot; style=&quot;mso-list: l0 level1 lfo1; text-align: justify; text-indent: -18.0pt;&quot;&gt;
&lt;/div&gt;
&lt;h3&gt;
&lt;ul&gt;
&lt;li&gt;&lt;span style=&quot;font-family: Symbol; text-indent: -18pt;&quot;&gt;·&lt;span style=&quot;font-family: &#39;Times New Roman&#39;; font-size: 7pt;&quot;&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;
&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;text-indent: -18pt;&quot;&gt;Mestrado&lt;/span&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;/h3&gt;
&lt;!--[if !supportLists]--&gt;&lt;o:p&gt;&lt;/o:p&gt;&lt;br /&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
O papel do
mestrado não é te transformar em um professor, mas em um MESTRE!&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
Uma definição
que gosto bastante é a do D.Sc. Bertoldo Schneider
Jr:&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18pt; text-align: center;&quot;&gt;
&lt;span style=&quot;background-color: white;&quot;&gt;&lt;span style=&quot;color: #20124d;&quot;&gt;&lt;span style=&quot;line-height: 107%;&quot;&gt;&quot;Mestre
significa alguém que está preparado para resolver, por si mesmo ou em equipe,
problemas não triviais.&amp;nbsp;&lt;/span&gt;&lt;span style=&quot;line-height: 107%;&quot;&gt;Ser Mestre significa, a partir da necessidade de
resolver um problema, descobrir os objetivos a serem atingidos, os passos a
serem dados, planejar como atingi-los, e publicar seu trabalho para que possa
sofrer a crítica de seus pares e outros especialistas. Resumindo, um Mestre é
alguém capaz de levar a cabo um processo de investigação e conclusão de maneira
apropriada (científica, ética, metodológica e honesta).&quot;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
&lt;span style=&quot;color: #4472c4; font-size: 10.0pt; line-height: 107%; mso-themecolor: accent5;&quot;&gt;&lt;br /&gt;&lt;/span&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
Basicamente o
objetivo do mestrado é o de formar um pesquisador, capaz de desenvolver novas
tecnologias e contribuir para o progresso da &lt;a href=&quot;http://www.youtube.com/watch?v=2uMBbkSMppM&quot; target=&quot;_blank&quot;&gt;ciência&lt;/a&gt;. Para isso é necessário um
aprofundamento teórico sobre a área de pesquisa estudada, com análise de
métodos já existentes e criação de novas abordagens.&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
Apesar de
grande parte dos formados optarem pela carreira como professores, há espaço também
no ambiente corporativo. Atualmente há uma cultura de mestres e doutores no
quadro de funcionários, principalmente em empresas de tecnologia de ponta como Google, IBM, etc.&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
Há também a
modalidade de mestrado profissional, que segundo a CAPES enfatiza estudos e
técnicas diretamente voltadas ao desempenho de um alto nível de qualificação profissional,
ou seja, o curso é voltado para o ensino e a pesquisa, porém com um viés mais
prático.&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;margin-left: 18.0pt; text-align: justify;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;text-align: justify;&quot;&gt;
Espero que o texto tenha ajudado
a clarear a mente sobre a dúvida do que fazer depois da graduação. Cada opção
tem suas vantagens e desvantagens, porém alguma delas deve se encaixar no seu
perfil e na sua pretensão para o futuro.&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;text-align: justify;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;br /&gt;
&lt;div class=&quot;MsoNormal&quot; style=&quot;text-align: justify;&quot;&gt;
Têm alguma opinião sobre o
assunto? Deixe um comentário e nos ajude a compartilhar a informação.&lt;o:p&gt;&lt;/o:p&gt;&lt;/div&gt;
</content><link rel='replies' type='application/atom+xml' href='http://quasemestre.blogspot.com/feeds/9196027737372795547/comments/default' title='Postar comentários'/><link rel='replies' type='text/html' href='http://quasemestre.blogspot.com/2013/12/o-que-fazer-depois-da-graduacao.html#comment-form' title='0 Comentários'/><link rel='edit' type='application/atom+xml' href='http://www.blogger.com/feeds/4694815573867137083/posts/default/9196027737372795547'/><link rel='self' type='application/atom+xml' href='http://www.blogger.com/feeds/4694815573867137083/posts/default/9196027737372795547'/><link rel='alternate' type='text/html' href='http://quasemestre.blogspot.com/2013/12/o-que-fazer-depois-da-graduacao.html' title='O que fazer depois da graduação?'/><author><name>Anonymous</name><uri>http://www.blogger.com/profile/18365707535183571778</uri><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='16' height='16' src='https://img1.blogblog.com/img/b16-rounded.gif'/></author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhou8NFo0Ln38iDxoSaltIOiW19bEFkYYtjBg2ngORw9LkdR1k1twFzMn1LTqudvRUEgdmpXmxkiFDJOqocHd_ZBjrWwMifL4JpuDVZZm6UXO95fUFhOvpnqwWi5I340M9lpYFFbAko27cK/s72-c/Romans-6_9-why-did-he-die.jpg" height="72" width="72"/><thr:total>0</thr:total></entry><entry><id>tag:blogger.com,1999:blog-4694815573867137083.post-6207425233339807490</id><published>2013-12-12T08:21:00.000-08:00</published><updated>2013-12-12T08:21:22.569-08:00</updated><category scheme="http://www.blogger.com/atom/ns#" term="Cursos"/><category scheme="http://www.blogger.com/atom/ns#" term="Inglês"/><title type='text'>Inglês Sem Fronteiras</title><content type='html'>&lt;div class=&quot;separator&quot; style=&quot;clear: both; text-align: center;&quot;&gt;
&lt;a href=&quot;https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjVmcm_leCIkHi0kM6wFbkdd_j6xe5wxhpk4yp4scTJmBZafP1Nhz9fSFlZs2pkPlTLAM7Vk1thyphenhyphenJ9l2uLJzCfR-NDf_l9nZsTVttyXmWI4dRkY0x0d-HAt4KYugws-qXJLwmEsw2lgHC8z/s1600/16.08-ingles-sem-fronteiras.jpg&quot; imageanchor=&quot;1&quot; style=&quot;margin-left: 1em; margin-right: 1em;&quot;&gt;&lt;img border=&quot;0&quot; src=&quot;https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjVmcm_leCIkHi0kM6wFbkdd_j6xe5wxhpk4yp4scTJmBZafP1Nhz9fSFlZs2pkPlTLAM7Vk1thyphenhyphenJ9l2uLJzCfR-NDf_l9nZsTVttyXmWI4dRkY0x0d-HAt4KYugws-qXJLwmEsw2lgHC8z/s1600/16.08-ingles-sem-fronteiras.jpg&quot; height=&quot;218&quot; width=&quot;320&quot; /&gt;&lt;/a&gt;&lt;/div&gt;
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The book is on the table? É isso mesmo galera, se vocês não têm muita afinidade com o Inglês é melhor começar a praticar. Hoje em dia as tecnologias mudam muito rapidamente e a maioria das pesquisas são divulgadas em inglês, quem é pesquisador ou apaixonado por inovação não pode ficar pra trás!&lt;/div&gt;
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Pra quem está procurando melhorar suas habilidades o Inglês Sem Fronteiras é uma boa opção, além de diversas atividades realizadas em um ambiente online o programa agora incluirá cursos presenciais.&lt;/div&gt;
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Se interessou? Então visite o site clicando &lt;a href=&quot;http://isf.mec.gov.br/&quot; target=&quot;_blank&quot;&gt;aqui&lt;/a&gt; e saiba mais!&lt;/div&gt;
&lt;br /&gt;</content><link rel='replies' type='application/atom+xml' href='http://quasemestre.blogspot.com/feeds/6207425233339807490/comments/default' title='Postar comentários'/><link rel='replies' type='text/html' href='http://quasemestre.blogspot.com/2013/12/ingles-sem-fronteiras.html#comment-form' title='1 Comentários'/><link rel='edit' type='application/atom+xml' href='http://www.blogger.com/feeds/4694815573867137083/posts/default/6207425233339807490'/><link rel='self' type='application/atom+xml' href='http://www.blogger.com/feeds/4694815573867137083/posts/default/6207425233339807490'/><link rel='alternate' type='text/html' href='http://quasemestre.blogspot.com/2013/12/ingles-sem-fronteiras.html' title='Inglês Sem Fronteiras'/><author><name>Anonymous</name><uri>http://www.blogger.com/profile/18365707535183571778</uri><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='16' height='16' src='https://img1.blogblog.com/img/b16-rounded.gif'/></author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjVmcm_leCIkHi0kM6wFbkdd_j6xe5wxhpk4yp4scTJmBZafP1Nhz9fSFlZs2pkPlTLAM7Vk1thyphenhyphenJ9l2uLJzCfR-NDf_l9nZsTVttyXmWI4dRkY0x0d-HAt4KYugws-qXJLwmEsw2lgHC8z/s72-c/16.08-ingles-sem-fronteiras.jpg" height="72" width="72"/><thr:total>1</thr:total></entry><entry><id>tag:blogger.com,1999:blog-4694815573867137083.post-248367600424283728</id><published>2013-12-10T15:55:00.002-08:00</published><updated>2013-12-12T07:59:04.721-08:00</updated><title type='text'>Distância DTW (Dynamic Time Warping) </title><content type='html'>&lt;div style=&quot;text-align: center;&quot;&gt;
&lt;a href=&quot;https://www.blogger.com/blogger.g?blogID=4694815573867137083&quot; imageanchor=&quot;1&quot; style=&quot;clear: right; float: right; margin-bottom: 1em; margin-left: 1em;&quot;&gt;&lt;/a&gt;&lt;a href=&quot;https://www.blogger.com/blogger.g?blogID=4694815573867137083&quot; imageanchor=&quot;1&quot; style=&quot;clear: right; float: right; margin-bottom: 1em; margin-left: 1em;&quot;&gt;&lt;/a&gt;&lt;a href=&quot;https://www.blogger.com/blogger.g?blogID=4694815573867137083&quot; imageanchor=&quot;1&quot; style=&quot;clear: right; float: right; margin-bottom: 1em; margin-left: 1em;&quot;&gt;&lt;/a&gt;&lt;a href=&quot;https://www.blogger.com/blogger.g?blogID=4694815573867137083&quot; imageanchor=&quot;1&quot; style=&quot;clear: left; float: left; margin-bottom: 1em; margin-right: 1em;&quot;&gt;&lt;/a&gt;&lt;a href=&quot;https://www.blogger.com/blogger.g?blogID=4694815573867137083&quot; imageanchor=&quot;1&quot; style=&quot;clear: left; float: left; margin-bottom: 1em; margin-right: 1em;&quot;&gt;&lt;/a&gt;&lt;a href=&quot;https://www.blogger.com/blogger.g?blogID=4694815573867137083&quot; imageanchor=&quot;1&quot; style=&quot;clear: left; float: left; margin-bottom: 1em; margin-right: 1em;&quot;&gt;&lt;/a&gt;&lt;/div&gt;
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&lt;a href=&quot;https://www.blogger.com/blogger.g?blogID=4694815573867137083&amp;amp;pli=1&quot; imageanchor=&quot;1&quot; style=&quot;margin-left: 1em; margin-right: 1em;&quot;&gt;&lt;img alt=&quot;&quot; border=&quot;0&quot; height=&quot;252&quot; 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&quot; 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&lt;span style=&quot;font-size: small;&quot;&gt;&lt;br /&gt;Inaugurando a minha primeira postagem no Blog Quase Mestre, irei comentar um pouco sobre uma distância bem conhecida na literatura (áreas de banco de dados, imagens, matemática e dentre outras) e também pela comunidade de reconhecimento de voz, chamada de&lt;b&gt; DTW&lt;/b&gt; (&lt;i&gt;Dynamic Time Warping&lt;/i&gt;) que traduzindo ao pé da letra, seria Deformação do Tempo Dinâmico.&amp;nbsp;&lt;/span&gt;&lt;/div&gt;
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Para ficar um texto bastante claro e intuitivo, escreverei de forma um pouco superficial e objetiva, mostrando exemplos e aplicações nais quais podem ser utilizada essa distância, de modo que tanto leitores leigos sobre o assunto como também os profissionais na área possam aproveitar.&lt;br /&gt;
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&lt;span style=&quot;font-size: small;&quot;&gt;&lt;span style=&quot;font-size: large;&quot;&gt;O que é DTW?&lt;/span&gt;&lt;/span&gt;&lt;br /&gt;
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&lt;span style=&quot;font-size: small;&quot;&gt;&lt;span style=&quot;font-size: small;&quot;&gt;Uma técnica que permite o &lt;a href=&quot;http://www.mhnederlof.nl/nlm.html&quot; target=&quot;_blank&quot;&gt;&lt;b&gt;mapeamento não linear&lt;/b&gt;&lt;/a&gt; entre duas &lt;a href=&quot;http://pt.wikipedia.org/wiki/S%C3%A9rie_temporal&quot; target=&quot;_blank&quot;&gt;&lt;b&gt;séries temporais&lt;/b&gt;&lt;/a&gt;, de tal forma que realiza a similaridade entre elas para minimizar sua distância. É bastante utilizada em mineração de dados e várias outras tarefas e/ou problemas que podem envolver algum tipo de classificação, clusterização, detecção de anomalias, indexação de séries temporais, dentre outras.&lt;/span&gt;&lt;span style=&quot;font-size: large;&quot;&gt;&lt;span style=&quot;font-size: small;&quot;&gt; &lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;
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&lt;a href=&quot;https://www.blogger.com/blogger.g?blogID=4694815573867137083&quot; imageanchor=&quot;1&quot; style=&quot;margin-left: 1em; margin-right: 1em;&quot;&gt;&lt;/a&gt;&lt;/div&gt;
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&lt;span style=&quot;font-size: large;&quot;&gt;Conhecendo mais sobre o DTW&lt;/span&gt;&lt;br /&gt;
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O DTW tem uma pequena vantagem comparado com outra distância bastante disseminada na literatura, a distância Euclidiana.&lt;br /&gt;
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&lt;b&gt;Distância Euclidiana:&lt;/b&gt; Para fazer o cálculo utilizando a distância Euclidiana é bastante simples, imagine dois pontos em um plano cartesiano, ponto z1 e o ponto z2, cada ponto tem as coordenadas (x1, y1) e (x2, y2), respectivamente, ou seja, z1 = (x1, y1) e z2 = (x2, y2). A formula Euclidiana é dada a seguir:&lt;br /&gt;
&lt;br /&gt;
&lt;img alt=&quot;&quot; height=&quot;42&quot; src=&quot;data:image/png;base64,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&quot; width=&quot;200&quot; /&gt;&lt;br /&gt;
&lt;br /&gt;
Vamos um exemplo bem simples: x1 = 4, y1 = 3 e x2 = 5 e y2 = 7, então o resultado seria:&lt;br /&gt;
&lt;br /&gt;
&lt;img alt=&quot;&quot; height=&quot;32&quot; src=&quot;data:image/png;base64,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&quot; width=&quot;400&quot; /&gt;&lt;span style=&quot;color: red;&quot;&gt;&lt;/span&gt;&lt;br /&gt;
&lt;br /&gt;
Claro que pode haver mais valores do que duas coordenadas para cada ponto, então podemos generalizar a formula Euclidiana entre os pontos P=(p1,p2, ..., pn) e Q = (q1, q2, ..., qn)para:&amp;nbsp; &lt;br /&gt;
&lt;br /&gt;
&lt;img alt=&quot;&quot; height=&quot;44&quot; src=&quot;data:image/png;base64,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&quot; width=&quot;320&quot; /&gt;&lt;span style=&quot;color: red;&quot;&gt;&lt;/span&gt;&lt;br /&gt;
&lt;br /&gt;
&lt;b&gt;Vantagem de usar DTW em vez da distância Euclidiana:&lt;/b&gt; Como pode ser percebido, a distância Euclidiana deve utilizar vetores do mesmo tamanho, ou seja, deve ter a mesma quantidade de &lt;i&gt;p&lt;/i&gt;&#39;s e &lt;i&gt;q&lt;/i&gt;&#39;s, enquanto a DTW não têm essa restrição.&lt;br /&gt;
&lt;br /&gt;
Para facilitar imagine como fazer o cálculo entre vetores de tamanhos diferentes utilizando a distância Euclidiana, uma solução seria completar o vetor de menor tamanho com valores 0&#39;s até alcançar e igualar ao tamanho do maior vetor. É uma das abordagens que pode ser realizada, mas será que é a mais eficiente?&lt;br /&gt;
&lt;br /&gt;
Vamos dar uma olhada na distância DTW a seguir.&lt;br /&gt;
&lt;br /&gt;
&lt;span style=&quot;font-size: large;&quot;&gt;Como calcular a distância DTW&lt;/span&gt;&lt;br /&gt;
&lt;br /&gt;
Suponha que exista duas séries temporais, uma sequência &lt;i&gt;W&lt;/i&gt; de tamanho &lt;i&gt;n&lt;/i&gt;, e uma sequência&amp;nbsp;&lt;i&gt;Q &lt;/i&gt;de tamanho &lt;i&gt;m&lt;/i&gt;, onde:&lt;br /&gt;
&lt;br /&gt;
&lt;i&gt;W &lt;/i&gt;= &lt;i&gt;w1, w2, ..., wi, ... , wn&lt;/i&gt;&lt;br /&gt;
&lt;i&gt;Q = q1, q2, ..., qi, ..., qm&lt;/i&gt;&lt;br /&gt;
&lt;br /&gt;
Exemplo prático:&lt;br /&gt;
&lt;br /&gt;
&lt;i&gt;W = [1,2,3,4]&amp;nbsp; e n =4&lt;/i&gt;&lt;br /&gt;
&lt;i&gt;Q =&amp;nbsp; [4,5,6] e m =3&lt;/i&gt;&lt;br /&gt;
&lt;i&gt;&lt;br /&gt;&lt;/i&gt;
Para&lt;i&gt;&amp;nbsp; &lt;/i&gt;computar a matriz de&amp;nbsp; distância, é computada a distância ao quadrado de todos os valores de &lt;i&gt;W&lt;/i&gt; com todos os valores de &lt;i&gt;Q&lt;/i&gt;. Então a matriz de distância &lt;i&gt;d &lt;/i&gt;recebe (wi - qj)², ou seja, d(wi, qj) = (wi - qj)²,onde &lt;i&gt;i&lt;/i&gt; inicia em 1 e vai até &lt;i&gt;n&lt;/i&gt;, e &lt;i&gt;j &lt;/i&gt;inicia em 1 e vai até &lt;i&gt;m.&lt;/i&gt;&lt;br /&gt;
&lt;br /&gt;
Exemplo prático seria:&lt;br /&gt;
formula dij = (wi - qj)²&lt;br /&gt;
d11 = (1 - 4)² = 3² = 9&lt;br /&gt;
d12 = (1 - 5)² = 4² = 16&lt;br /&gt;
d13 = (1 - 6)² = 5² = 25&lt;br /&gt;
d21 = (2 - 4)² = (-2)² = 4&lt;br /&gt;
d22 = (2 - 5)² = (-3)² = 9&lt;br /&gt;
d23 = (2 - 6)² = (-4)² = 16&lt;br /&gt;
d31 = (3 - 4)² = (-1)² = 1&lt;br /&gt;
d32 = (3 - 5)² = (-2)² = 4&lt;br /&gt;
d33 = (3 - 6)² = (-3)² = 9&lt;br /&gt;
d41 = (4 - 4)² = (0)² = 0&lt;br /&gt;
d42 = (4 - 5)² = (-1)² = 1&lt;br /&gt;
d43 = (4 - 6)² = (-2)² = 4&lt;br /&gt;
&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp; &amp;nbsp; &amp;nbsp;&amp;nbsp; |9&amp;nbsp; 16&amp;nbsp;&amp;nbsp; 25|&lt;br /&gt;
dij = |4&amp;nbsp;&amp;nbsp; 9&amp;nbsp;&amp;nbsp;&amp;nbsp; 16 |&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &amp;nbsp; &amp;nbsp; |1 &amp;nbsp; 4 &amp;nbsp;&amp;nbsp;&amp;nbsp; 9 |&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; |0&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp; 4&amp;nbsp; |&lt;br /&gt;
&lt;br /&gt;
Após criar a matriz &lt;i&gt;d&lt;/i&gt;, devemos encontrar o&lt;i&gt; &lt;/i&gt;mapeamento entre W e Q, para encontrar o caminho chamado de &lt;b&gt;caminho deformado&lt;/b&gt; (caminho na matriz &lt;i&gt;d&lt;/i&gt; que determinar o menor custo total ao somar os elementos (i,j)) utiliza-se &lt;b&gt;programação dinâmica&lt;/b&gt; para avaliar a seguinte recorrência:&lt;br /&gt;
&lt;br /&gt;
Caminho deformado Y(i,j) = d(qi, wi) + min {Y( i - 1, j - 1), Y(i - 1, j), Y(i, j - 1)}&lt;br /&gt;
&lt;br /&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
A &lt;b&gt;programação dinâmica&lt;/b&gt; é baseada em algoritmos que tomam a melhor decisão a cada passo, ou seja, a partir de um determinado elemento da matriz, para encontrar a melhor decisão (no caso, o melhor elemento), devemos procurar o elemento mínimo (que é o menor elemento considerando as três posições Y(i-1, j - 1), Y(i - 1, j) e Y(i, j - 1)). Talvez não tenha ficado muito lógico ou até mesmo claro, então para resolver isso, nada melhor que um exemplo prático para terminar de sanar as dúvidas.&lt;/div&gt;
&lt;br /&gt;
Ex: Seja a matriz dij&lt;br /&gt;
&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp; &amp;nbsp; &amp;nbsp;&amp;nbsp; |9&amp;nbsp; 16&amp;nbsp;&amp;nbsp; 25|&lt;br /&gt;
dij = |4&amp;nbsp;&amp;nbsp; 9&amp;nbsp;&amp;nbsp;&amp;nbsp; 16 |&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &amp;nbsp; &amp;nbsp; |1 &amp;nbsp; 4 &amp;nbsp;&amp;nbsp;&amp;nbsp; 9 |&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; |0&amp;nbsp;&amp;nbsp; 1&amp;nbsp;&amp;nbsp;&amp;nbsp; 4&amp;nbsp; |&lt;br /&gt;
&lt;br /&gt;
Inicialmente o i = n e j = m ou seja i = 4 e j = 3 então d(qi, wj) + min {Y( i - 1, j - 1), Y(i - 1, j), Y(i, j - 1)} = 4 + min(4, 9, 1) = 4 + 1 = 5&lt;br /&gt;
&lt;br /&gt;
O valor 5 que acabou de ser calculado é a soma acumulada do caminho deformado. Seguindo com a explicação do exemplo, na matriz o nosso d(qi, wi) está de azul, e o min {Y( i - 1, j - 1), Y(i - 1, j), Y(i, j - 1) está de vermelho&lt;br /&gt;
&lt;br /&gt;
&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; |9&amp;nbsp; 16&amp;nbsp;&amp;nbsp; 25|&lt;br /&gt;
dij = |4&amp;nbsp;&amp;nbsp; 9&amp;nbsp;&amp;nbsp;&amp;nbsp; 16 |&amp;nbsp;&amp;nbsp; caminho deformado: 4&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &amp;nbsp; &amp;nbsp; |1 &amp;nbsp; &lt;span style=&quot;color: red;&quot;&gt;4&lt;/span&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp;&lt;span style=&quot;color: red;&quot;&gt; 9&lt;/span&gt; |&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; |0&amp;nbsp;&amp;nbsp; &lt;span style=&quot;color: red;&quot;&gt;1&lt;/span&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;span style=&quot;color: blue;&quot;&gt;4&lt;/span&gt;&amp;nbsp; |&lt;br /&gt;
&lt;br /&gt;
e nossa soma acumulada é 5, pois somamos os d(qi, wi) + min {Y( i - 1, j - 1), Y(i - 1, j), Y(i, j - 1)}.&lt;br /&gt;
&lt;br /&gt;
Continuando os passos, refazemos novamente o passo anterior, mudando o i e o j:&lt;br /&gt;
d(qi, wj) + min {Y( i - 1, j - 1), Y(i - 1, j), Y(i, j - 1)} = 1 + min(1, 4, 0) = 1 + 0 = 1&lt;br /&gt;
&lt;br /&gt;
Seguindo com a explicação do exemplo, na matriz o nosso d(qi, wi) está de azul, e o min {Y( i - 1, j - 1), Y(i - 1, j), Y(i, j - 1) está de vermelho, com a diferença agora que foi colocado com a cor verde, a representação do caminho deformado&lt;br /&gt;
&lt;br /&gt;
&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; |9&amp;nbsp; 16&amp;nbsp;&amp;nbsp; 25|&lt;br /&gt;
dij = |4&amp;nbsp;&amp;nbsp; 9&amp;nbsp;&amp;nbsp;&amp;nbsp; 16 |&amp;nbsp;&amp;nbsp; caminho deformado: 4-1&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &amp;nbsp; &amp;nbsp; |&lt;span style=&quot;color: red;&quot;&gt;1 &amp;nbsp; 4&lt;/span&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp; 9 |&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; |&lt;span style=&quot;color: red;&quot;&gt;0&lt;/span&gt;&amp;nbsp;&amp;nbsp;&lt;span style=&quot;color: blue;&quot;&gt; 1&lt;/span&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;span style=&quot;color: lime;&quot;&gt;4&lt;/span&gt;&amp;nbsp; |&lt;br /&gt;
&lt;br /&gt;
fazemos isso repetidas vezes até que i = 1 e j = 1, então:&lt;br /&gt;
&lt;br /&gt;
&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; |9&amp;nbsp; 16&amp;nbsp;&amp;nbsp; 25|&lt;br /&gt;
dij = |4&amp;nbsp;&amp;nbsp; 9&amp;nbsp;&amp;nbsp;&amp;nbsp; 16 |&amp;nbsp;&amp;nbsp; caminho deformado: 4-1-0&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &amp;nbsp; &amp;nbsp; |&lt;span style=&quot;color: red;&quot;&gt;1 &amp;nbsp; &lt;span style=&quot;color: black;&quot;&gt;4&lt;/span&gt;&lt;/span&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp; 9 |&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; |&lt;span style=&quot;color: blue;&quot;&gt;0&lt;/span&gt;&amp;nbsp;&amp;nbsp;&lt;span style=&quot;color: blue;&quot;&gt; &lt;span style=&quot;color: lime;&quot;&gt;1&lt;/span&gt;&lt;/span&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;span style=&quot;color: lime;&quot;&gt;4&lt;/span&gt;&amp;nbsp; |&lt;br /&gt;
&lt;br /&gt;
&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; |9&amp;nbsp; 16&amp;nbsp;&amp;nbsp; 25|&lt;br /&gt;
dij = |&lt;span style=&quot;color: red;&quot;&gt;4&amp;nbsp;&amp;nbsp;&lt;span style=&quot;color: black;&quot;&gt; 9&lt;/span&gt;&lt;/span&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp; 16 |&amp;nbsp;&amp;nbsp; caminho deformado: 4-1-0-1&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &amp;nbsp; &amp;nbsp; |&lt;span style=&quot;color: red;&quot;&gt;&lt;span style=&quot;color: blue;&quot;&gt;1&lt;/span&gt; &amp;nbsp; &lt;span style=&quot;color: black;&quot;&gt;4&lt;/span&gt;&lt;/span&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp; 9 |&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; |&lt;span style=&quot;color: lime;&quot;&gt;0&lt;/span&gt;&amp;nbsp;&amp;nbsp;&lt;span style=&quot;color: blue;&quot;&gt; &lt;span style=&quot;color: lime;&quot;&gt;1&lt;/span&gt;&lt;/span&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;span style=&quot;color: lime;&quot;&gt;4&lt;/span&gt;&amp;nbsp; |&lt;br /&gt;
&lt;br /&gt;
&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; |&lt;span style=&quot;color: red;&quot;&gt;9&lt;/span&gt;&amp;nbsp; 16&amp;nbsp;&amp;nbsp; 25|&lt;br /&gt;
dij = |&lt;span style=&quot;color: red;&quot;&gt;&lt;span style=&quot;color: blue;&quot;&gt;4&lt;/span&gt;&amp;nbsp;&amp;nbsp; &lt;span style=&quot;color: black;&quot;&gt;9&lt;/span&gt;&lt;/span&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp; 16 |&amp;nbsp;&amp;nbsp; caminho deformado: 4-1-0-1-4&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &amp;nbsp; &amp;nbsp; |&lt;span style=&quot;color: red;&quot;&gt;&lt;span style=&quot;color: lime;&quot;&gt;1&lt;/span&gt; &amp;nbsp; &lt;span style=&quot;color: black;&quot;&gt;4&lt;/span&gt;&lt;/span&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp; 9 |&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; |&lt;span style=&quot;color: lime;&quot;&gt;0&lt;/span&gt;&amp;nbsp;&amp;nbsp;&lt;span style=&quot;color: blue;&quot;&gt; &lt;span style=&quot;color: lime;&quot;&gt;1&lt;/span&gt;&lt;/span&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;span style=&quot;color: lime;&quot;&gt;4&lt;/span&gt;&amp;nbsp; |&lt;br /&gt;
&lt;br /&gt;
&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; |&lt;span style=&quot;color: blue;&quot;&gt;9&lt;/span&gt;&amp;nbsp; 16&amp;nbsp;&amp;nbsp; 25|&lt;br /&gt;
dij = |&lt;span style=&quot;color: red;&quot;&gt;&lt;span style=&quot;color: lime;&quot;&gt;4&lt;/span&gt;&amp;nbsp;&amp;nbsp; &lt;span style=&quot;color: black;&quot;&gt;9&lt;/span&gt;&lt;/span&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp; 16 |&amp;nbsp;&amp;nbsp; caminho deformado: 4-1-0-1-4-9&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &amp;nbsp; &amp;nbsp; |&lt;span style=&quot;color: red;&quot;&gt;&lt;span style=&quot;color: lime;&quot;&gt;1&lt;/span&gt; &amp;nbsp; &lt;span style=&quot;color: black;&quot;&gt;4&lt;/span&gt;&lt;/span&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp; 9 |&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; |&lt;span style=&quot;color: lime;&quot;&gt;0&lt;/span&gt;&amp;nbsp;&amp;nbsp;&lt;span style=&quot;color: blue;&quot;&gt; &lt;span style=&quot;color: lime;&quot;&gt;1&lt;/span&gt;&lt;/span&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;span style=&quot;color: lime;&quot;&gt;4&lt;/span&gt;&amp;nbsp; |&lt;br /&gt;
&amp;nbsp; &lt;br /&gt;
&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; |&lt;span style=&quot;color: lime;&quot;&gt;9&lt;/span&gt;&amp;nbsp; 16&amp;nbsp;&amp;nbsp; 25|&lt;br /&gt;
dij = |&lt;span style=&quot;color: red;&quot;&gt;&lt;span style=&quot;color: lime;&quot;&gt;4&lt;/span&gt;&amp;nbsp;&amp;nbsp; &lt;span style=&quot;color: black;&quot;&gt;9&lt;/span&gt;&lt;/span&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp; 16 |&amp;nbsp;&amp;nbsp; caminho deformado: 4-1-0-1-4-9&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; &amp;nbsp; &amp;nbsp; |&lt;span style=&quot;color: red;&quot;&gt;&lt;span style=&quot;color: lime;&quot;&gt;1&lt;/span&gt; &amp;nbsp; &lt;span style=&quot;color: black;&quot;&gt;4&lt;/span&gt;&lt;/span&gt; &amp;nbsp;&amp;nbsp;&amp;nbsp; 9 |&lt;br /&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; |&lt;span style=&quot;color: lime;&quot;&gt;0&lt;/span&gt;&amp;nbsp;&amp;nbsp;&lt;span style=&quot;color: blue;&quot;&gt; &lt;span style=&quot;color: lime;&quot;&gt;1&lt;/span&gt;&lt;/span&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;span style=&quot;color: lime;&quot;&gt;4&lt;/span&gt;&amp;nbsp; |&lt;br /&gt;
&lt;br /&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
&lt;b&gt;Obs:&lt;/b&gt;&lt;i&gt; Não foi feita a soma acumulada para ser simples e didático, mas com o exemplo dado é possível entender o processo para o cálculo parcial do DTW, ressaltando que o resultado final será o mesmo que se fizesse a matriz acumulada, a diferença é que o elemento i = 1 e j =1 teria o valor 19.&lt;/i&gt;&lt;/div&gt;
&lt;br /&gt;
Após ter achado o caminho deformado é necessário somar os elementos:&lt;br /&gt;
4 + 1+ 0 + 1+ 4 + 9 =19&lt;br /&gt;
&lt;br /&gt;
O valor 19 é nossa distância entre as séries temporais&lt;br /&gt;
&lt;br /&gt;
&lt;i&gt;W &lt;/i&gt;= &lt;i&gt;w1, w2, ..., wi, ... , wn&lt;/i&gt;&lt;br /&gt;
&lt;i&gt;Q = q1, q2, ..., qi, ..., qm&lt;/i&gt;&lt;br /&gt;
&lt;br /&gt;
&lt;span style=&quot;font-size: large;&quot;&gt;Conclusão&lt;/span&gt;&lt;span style=&quot;font-size: large;&quot;&gt;&amp;nbsp;&lt;/span&gt;&lt;br /&gt;
&lt;br /&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
&lt;span style=&quot;font-size: small;&quot;&gt;Este artigo apresenta somente uma visão geral sobre a distância DTW, sendo aconselhável&amp;nbsp;um aprofundamento maior por parte do leitor que gostou do assunto, porém, agora vocês já tem uma noção sobre o tema, sua importância e aplicabilidade. Esperamos que isso possa te ajudar a resolver algum problema. &lt;/span&gt;&lt;/div&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;</content><link rel='replies' type='application/atom+xml' href='http://quasemestre.blogspot.com/feeds/248367600424283728/comments/default' title='Postar comentários'/><link rel='replies' type='text/html' href='http://quasemestre.blogspot.com/2013/12/distancia-dtw-dynamic-time-warping.html#comment-form' title='0 Comentários'/><link rel='edit' type='application/atom+xml' href='http://www.blogger.com/feeds/4694815573867137083/posts/default/248367600424283728'/><link rel='self' type='application/atom+xml' href='http://www.blogger.com/feeds/4694815573867137083/posts/default/248367600424283728'/><link rel='alternate' type='text/html' href='http://quasemestre.blogspot.com/2013/12/distancia-dtw-dynamic-time-warping.html' title='Distância DTW (Dynamic Time Warping) '/><author><name>Anonymous</name><uri>http://www.blogger.com/profile/02603191106845298428</uri><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='16' height='16' src='https://img1.blogblog.com/img/b16-rounded.gif'/></author><thr:total>0</thr:total></entry><entry><id>tag:blogger.com,1999:blog-4694815573867137083.post-2982464262661777059</id><published>2013-11-06T09:39:00.000-08:00</published><updated>2013-11-06T09:39:07.263-08:00</updated><title type='text'>Bem Vindo ao Blog!</title><content type='html'>&lt;div style=&quot;text-align: justify;&quot;&gt;
A partir de hoje você saberá um pouco mais da rotina e pesquisas de um aluno de mestrado!&amp;nbsp;&lt;/div&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
&lt;br /&gt;&lt;/div&gt;
&lt;div style=&quot;text-align: justify;&quot;&gt;
As postagens terão como foco o curso em Ciência da Computação, com apresentação de linhas de pesquisa como Inteligência Artificial e Banco de Dados.&lt;/div&gt;
&lt;br /&gt;
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Você ainda está em dúvida em fazer mestrado ou não? Fique atento ao blog, pois levantaremos discussões e mostraremos alguns aspectos que podem te ajudar nesse dilema!&lt;br /&gt;
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&lt;br /&gt;</content><link rel='replies' type='application/atom+xml' href='http://quasemestre.blogspot.com/feeds/2982464262661777059/comments/default' title='Postar comentários'/><link rel='replies' type='text/html' href='http://quasemestre.blogspot.com/2013/11/bem-vindo-ao-blog.html#comment-form' title='0 Comentários'/><link rel='edit' type='application/atom+xml' href='http://www.blogger.com/feeds/4694815573867137083/posts/default/2982464262661777059'/><link rel='self' type='application/atom+xml' href='http://www.blogger.com/feeds/4694815573867137083/posts/default/2982464262661777059'/><link rel='alternate' type='text/html' href='http://quasemestre.blogspot.com/2013/11/bem-vindo-ao-blog.html' title='Bem Vindo ao Blog!'/><author><name>Anonymous</name><uri>http://www.blogger.com/profile/18365707535183571778</uri><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='16' height='16' src='https://img1.blogblog.com/img/b16-rounded.gif'/></author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi_cd7_sgzAR36ogocs1xziPq97K2iYHGRj-Jc50on0BqcA3k29cPWZyKgvJwUmfroVgSRVKjp2H3yhtafSvgsb6HLU9EO1xH5lUK0pTIj9p28GM6bCExm_4StV2SJi_QuLENueVAHCEUQ_/s72-c/IA+e+BD.jpg" height="72" width="72"/><thr:total>0</thr:total></entry></feed>