Automatic Extraction and Analysis of Visual Objects Information

2005 ◽  
pp. 203-221 ◽  
Author(s):  
Xavier Giró ◽  
Verónica Vilaplana ◽  
Ferran Marqués ◽  
Philippe Salembier
Keyword(s):  
Automatic Extraction ◽  
Visual Objects

Deskripsi Kesulitan Belajar Siswa Berdasarkan Karakteristik Lerner dalam Menyelesaikan Soal Geometri

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Nazom Murio ◽  
Roseli Theis
Keyword(s):  
Qualitative Research ◽  
Visual Perception ◽  
Learning Difficulties ◽  
Research Subjects ◽  
Visual Objects ◽  
Almost All ◽  
Personality Classification ◽  
The Given ◽  
Classification Test ◽  
Descriptive Qualitative

Geometri adalah bagian matematika yang sangat dekat dari siswa, karena hampir semua objek visual yang ada di sekitar siswa adalah objek geometri, tetapi tidak semua siswa menyukai pembelajaran yang menyertakan gambar, sehingga memungkinkan siswa mengalami kesulitan dalam belajar geometri. Tujuan dari penelitian ini adalah untuk menggambarkan kesulitan belajar siswa berdasarkan karakteristik Lerner dalam menyelesaikan pertanyaan geometri. Jenis penelitian ini adalah penelitian deskriptif kualitatif. Subjek penelitian adalah siswa dengan kepribadian wali yang mengalami kesulitan belajar di kelas IX A SMP N 30 Muaro Jambi. Instrumen yang digunakan dalam penelitian ini adalah penulis sendiri, lembar tes klasifikasi kepribadian, lembar tes kesulitan belajar, dan pedoman wawancara. Hasil penelitian menunjukkan siswa dengan kepribadian wali yang mengalami kesulitan belajar, 100% mengalami kelainan persepsi visual, di mana siswa mengalami kesulitan dalam menentukan seperti apa bangun datar pada masalah tersebut. 60% mengalami kesulitan mengenali dan memahami simbol, di mana siswa melihat simbol "//" sebagai simbol untuk kesesuaian. Serta 40% mengalami kesulitan dalam bahasa dan membaca, di mana siswa kesulitan dalam memahami pertanyaan yang diberikan.   Geometry is a very close mathematical part of the student, because almost all visual objects that exist around the students are objects of geometry, but not all students like learning that includes images, thus allowing students to have difficulty in learning geometry. The purpose of this research is to describe students' learning difficulties based on Lerner's characteristic in solving the geometry question. This type of research is descriptive qualitative research. Research subjects were students with guardian personality who had difficulty studying in class IX A SMP N 30 Muaro Jambi. Instruments used in this study are the authors themselves, personality classification test sheets, learning difficulties test sheets, and interview guidelines. The results showed students with guardian personality who experienced learning difficulties, 100% experienced visual perception abnormalities, where students have difficulty in determining what kind of flat wake on the matter. 60% have difficulty recognizing and understanding symbols, where students see the symbol "//" as a symbol for conformity. As well as 40% have difficulty in language and reading, where students difficulty in understanding the given question.

Automatic Extraction of Acronyms from Text

2020 ◽  
Author(s):  
Stuart Yeates
Keyword(s):  
Digital Library ◽  
False Positives ◽  
Automatic Extraction ◽  
False Negatives ◽  
Library Research ◽  
Communications Theory ◽  
Textual Content

A brief introduction to acronyms is given and motivation for extracting them in a digital library environment is discussed. A technique for extracting acronyms is given with an analysis of the results. The technique is found to have a low number of false negatives and a high number of false positives. Introduction Digital library research seeks to build tools to enable access of content, while making as few as possible assumptions about the content, since assumptions limit the range of applicability of the tools. Generally, the broader the assumptions the more widely applicable the tools. For example, keyword based indexing [5] is based on communications theory and applies to all natural human textual languages (allowances for differences in character sets and similar localisation issues not withstanding) . The algorithm described in this paper makes much stronger assumptions about the content. It assumes textual content that contains acronyms, an assumption which is known to hold for...

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