Avaliação do entendimento da cartilha educativa sobre TDAH em formato de revista em quadrinhos com educadores

O presente estudo teve como objetivo realizar a avaliação do entendimento da cartilha educativa em formato de revista em quadrinhos com educadores. A metodologia utilizada na pesquisa de campo foi descritiva, com abordagem qualitativa, participaram do estudo 64 docentes, a coleta de dados aconteceu por meio dos aplicativos WhatsApp e Messenger com o envio da cartilha educativa em Portable Document Format – PDF e o questionário com 13 perguntas com posterior análise discursiva. Os dados serviram como suporte para a elaboração de uma cartilha educativa quadrinizada sobre o Transtorno de Déficit de Atenção e Hiperatividade - TDAH, a ser utilizado pelos educadores. Os resultados obtidos reforçaram a importância de compreender os aspectos do comportamento da criança com TDAH, por meio do entendimento do transtorno. Acredita-se que a cartilha educativa poderá contribuir para o conhecimento dos educadores acerca do Transtorno de Déficit de Atenção e Hiperatividade, fornecendo-lhes subsídios para lidarem com os estudantes portadores do transtorno.

Document management. Portable document format

10.3403/30167699 ◽

2008 ◽

Keyword(s):

Document Management ◽

Proceedings of the Sixth International Conference on Technological Ecosystems for Enhancing Multiculturality - TEEM'18 ◽

Use of 3D PDF (portable document format) in radiological models

10.1145/3284179.3284239 ◽

2018 ◽

Author(s):

Roberto D. Tabernero Rico ◽

Juan A. Juanes Méndez ◽

Alberto Prats-Galino

Keyword(s):

Review: The Portable Document Format (PDF)

Journal of the Society of Architectural Historians ◽

10.1525/jsah.2011.70.4.532.a ◽

2011 ◽

Vol 70 (4) ◽

pp. 532-535

Author(s):

Ana María León

Keyword(s):

Portable Document Format File Containing the Surface Models to Learn the Stereoscopic Shape of Foot Muscles

International Journal of Morphology ◽

10.4067/s0717-95022015000400016 ◽

2015 ◽

Vol 33 (4) ◽

pp. 1287-1292 ◽

Cited By ~ 2

Author(s):

Hae Gwon Jang ◽

Min Suk Chung ◽

Dong Sun Shin

Keyword(s):

Surface Models ◽

Peer Review #1 of "Towards an easier creation of three-dimensional data for embedding into scholarly 3D PDF (Portable Document Format) files (v0.1)"

10.7287/peerj.794v0.1/reviews/1 ◽

2015 ◽

Author(s):

S Pettifer

Keyword(s):

Peer Review ◽

Three Dimensional ◽

PDF: The "P" Stands for Problematic

Weave Journal of Library User Experience ◽

10.3998/weaveux.279 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Julia Caffrey-Hill ◽

Nathan Clark ◽

Brent Davis ◽

William Helman

Keyword(s):

Higher Education ◽

Visually Impaired ◽

Limited Budget ◽

File Formats ◽

Level Of Effort ◽

The Portable Document Format (PDF) is one of the most common document file types in academia, both in the library and the classroom. Unfortunately, PDF poses unique barriers to accessibility, particularly for the visually impaired. Ensuring that all people can read PDF content can be complex and expensive. There are alternative formats that can be made accessible with a lower level of effort, providing a better experience for both the end reader and the document author. This article serves as a call to arms for higher education to migrate away from PDF and to urge the tech community to develop new file formats that lend themselves to enhanced accessibility on a limited budget.

Implementation of Pattern Matching Algorithm for Portable Document Format

International Journal of Advanced Computer Science and Applications ◽

10.14569/ijacsa.2017.081162 ◽

2017 ◽

Vol 8 (11) ◽

Cited By ~ 1

Author(s):

Anton Yudhana ◽

Sunardi ◽

Abdul Djalil

Keyword(s):

Pattern Matching ◽

Matching Algorithm ◽

Pattern Matching Algorithm ◽

Detect Malware in Portable Document Format Files (PDF) Using Support Vector Machine and Random Decision Forest

Jurnal Online Informatika ◽

10.15575/join.v3i2.196 ◽

2019 ◽

Vol 3 (2) ◽

pp. 99 ◽

Cited By ~ 1

Author(s):

Abdachul Charim ◽

Setio Basuki ◽

Denar Regata Akbi

Keyword(s):

Support Vector Machine ◽

Support Vector ◽

Random Decision Forest ◽

Decision Forest ◽

Ensemble Classification System for Scientific Chart Recognition from PDF Files

International Journal of Computer Vision and Image Processing ◽

10.4018/ijcvip.2012100101 ◽

2012 ◽

Vol 2 (4) ◽

pp. 1-10 ◽

Cited By ~ 3

Author(s):

S. Nagarajan ◽

V. Karthikeyani

Keyword(s):

Feature Extraction ◽

Classification System ◽

Texture Features ◽

Ensemble Classification ◽

3 Dimensional ◽

Feature Based ◽

Separation Feature ◽

Object Features ◽

Portable Document Format (PDF) is the most frequently used universal document format on the Internet and E-Publishing. Wide usage of PDF files has increased the need of conversion tools that convert PDF file content to text or HTML formats. A PDF converter can be categorized into two domains, namely, text recognition and graphics recognition. This paper focus on graphic recognition, especially chart type identification, which is concerned with developing algorithms that has the ability to determine the type of a given chart image from a PDF file. In the proposed system, initially an enhanced connected component and statistical feature based method is used to separate the chart region from other regions. The chart region is then analyzed and grouped as either 2-dimensional or 3-dimensional chart. After separating the graphic component from the text components, feature extraction is performed. The features can be grouped as object features, texture features and shape features. The combined feature vector is then classified using ensemble classification system. Experimental results show that the chart separation, feature extraction and ensemble classification models significantly improve the quality of chart identification.