scholarly journals Kesan Kaedah Pembelajaran Berasaskan Multiple Document-Based Lessons Terhadap Pengekalan Penguasaan Kemahiran Pemikiran Sejarah dalam kalangan Murid Tingkatan Satu

2021 ◽  
Vol 6 (3) ◽  
pp. 17-29
Author(s):  
M. Kaviza
Keyword(s):  
Multiple Document

Kajian eksperimen dengan reka bentuk faktorial 3 X 3 ini bertujuan mengkaji kesan kaedah pembelajaran berasaskan Multiple Document-Based Lessons terhadap pengekalan penguasaan kemahiran pemikiran sejarah dalam kalangan murid. Seramai 102 orang murid Tingkatan Satu melalui teknik persampelan berkelompok terlibat dalam kajian ini. Instrumen kajian ini merupakan ujian kemahiran pemikiran sejarah yang telah dibina oleh pengkaji yang telah disahkan oleh pakar-pakar penilai serta mempunyai nilai kebolehpercayaan yang baik. Data kuantitatif dalam kajian ini telah dianalisis secara statistic deskriptif dan statistic inferensi iaitu melalui ujian SPANOVA dengan menggunakan perisian IBM SPSS versi 24. Dapatan kajian ini telah menunjukkan bahawa kaedah pembelajaran berasaskan Multiple Document-based Lessons adalah lebih berkesan berbanding dengan kaedah pembelajaran berasaskan Document-based Lessons dan kaedah pengajaran konvensional terhadap pengekalan penguasaan kemahiran pemikiran sejarah dalam kalangan murid. Implikasi kajian ini telah menyediakan sumber maklumat kepada para guru sejarah bahawa kaedah pembelajaran berasaskan Multiple Document-Based Lessons telah dibuktikan adalah lebih berpotensi dilaksanakan dalam pendidikan Sejarah selaras dengan inovasi dalam kaedah pengajaran sejarah sedia ada.

From Image to XML

2015 ◽  
pp. 1295-1318
Author(s):  
Robert Keefer ◽  
Nikolaos Bourbakis
Keyword(s):  
Body Text ◽  
Visually Impaired ◽  
Document Image ◽  
The Body ◽  
Image Process ◽  
Document Images ◽  
Xml Document ◽  
Print Materials ◽  
The Creation ◽  
Multiple Document

Page layout analysis and the creation of an XML document from a document image are useful for many applications including the preservation of archived documents, robust electronic access to printed documents, and access to print materials by the visually impaired. In this paper, the authors describe a document image process pipeline comprised of techniques for the identification of article headings and the related body text, the aggregation of the body text with the headings, and the creation of an XML document. The pipeline was developed to support multiple document images captured by the head-mounted cameras of a reading device for the visually impaired. Both automatic and manual adaptations of the pipeline processed a sample of 25 newspaper document images. By comparing the automatic and manual processes, we show that overall our approach generates high-quality XML encoded documents for use in further processing, such as a text-to-speech for the visually impaired.

Multiple Document Interface Forms

2000 ◽  
pp. 207-227
Author(s):  
Hank Marquis ◽  
Eric A. Smith
Keyword(s):  
Multiple Document

Pc-Based Imaging System for Color Cell Identification and Scoring

1999 ◽  
Vol 5 (S2) ◽  
pp. 942-943
Author(s):  
Jasjit S. Suri ◽  
Kumar Satyender
Keyword(s):  
High Speed ◽  
Imaging System ◽  
Color Image ◽  
Diagnostic System ◽  
Cellular Level ◽  
Connected Components ◽  
Color Image Processing ◽  
Data Sets ◽  
Multiple Document ◽  
Detection And Quantification

Pathologists, microbiologists and cytologists are very interested to automatically identify and quantify the sperms, cells or nucleus in the cellular level images. Complexities like voluminous data sets, variability in data sets, millions of colors, and different kinds of artifacts make the detection and quantification process very difficult. This paper is an attempt to design a sophisticated cellular diagnostic system based on color image processing, mathematical morphology and connected components based on run length encoding. This system runs on Windows ‘98/NT PC platform, in Visual C++, 6.0 environment using three different architectures: Single document interface, multiple document interface and dialog based applications. The system takes around 1.5 seconds per image of 512 x 484 square pixels using high speed threading architecture written on the on 400 MHz Pentiumll processor. The system has an accuracy of 95%. The software has been validated tested on NASA and machine vision real world images.

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