Disleksi bukan satu penyakit

Disleksia bukan satu istilah yang asing dalam masalah pembelajaran. Terdapat banyak sumber yang rancak membincang dan uar-uarkan. maklumat mengenai masalah dan cara menangani disleksia. Merujuk Sheila Devaraj dan Samsilah Roslan (2006), disleksia hanya diperkenalkan secara formal di Malaysia pada tahun 1993 menerusi Seminar Kebangsaan Pengenalan kepada Disleksia yang dianjurkan oleh Rotary Club Gombak. Dalam kajian ini, penyelidik telah mengambil seramai 20 orang kanak-kanak di bawah Persatuan Disleksia Malaysia yang terletak di sekitar Kuala Lumpur sebagai sampel. Dua kaedah digunakan dalam mendapatkan data iaitu secara temu bual dan pemerhatian. Kaedah ini dianggap bersuaian kerana gambaran secara seluruhan dapat dilihat terhadap proses pengajaran dan pembelajaran pelajar-pelajar disleksia. Persoalan kajian ini ialah 1) Apakah ciri-ciri masalah yang ketara yang dihidapi oleh pelajar-pelajar disleksia dalam pembelajaran? dan 2) Apakah langkah-langkah yang belch diambil untuk membantu pelajar-pelajar bagi mengatasi masalah disleksia

Contrast Enhanced Low-light Visible and Infrared Image Fusion

Multi-modal image fusion objective is to combine complementary information obtained from multiple modalities into a single representation with increased reliability and interpretation. The images obtained from low-light visible cameras containing fine details of the scene and infrared cameras with high contrast details are the two modalities considered for fusion. In this paper, the low-light images with low target contrast are enhanced by using the phenomenon of stochastic resonance prior to fusion. Entropy is used as a measure to tune iteratively the coefficients using bistable system parameters. The combined advantage of multi scale decomposition approach and principal component analysis is utilized for the fusion of enhanced low-light visible and infrared images. Experimental results were carried out on different image datasets and analysis of the proposed methods were discussed.

非線形振動を励起させることによる回転するタイヤ内でのエナジーハーべスティング

学位の種別: 課程博士審査委員会委員 : （主査）東京大学准教授 中野 公彦, 東京大学教授 須田 義大, 東京大学准教授 大石 岳史, 東京大学教授 割澤 伸一, 東京大学教授 金 範埈University of Tokyo(東京大学

Automatic detection, sizing and characterisation of weld defects using ultrasonic time-of-flight diffraction

Ultrasonic time-of-flight diffraction (TOFD) is known as a reliable non-destructive testing technique for weld inspection in steel structures, providing accurate aw positioning and sizing. Despite all its good features, TOFD data interpretation and reporting are still performed manually by skilled inspectors and interpretation software operators. This is a cumbersome and error-prone process, leading to inevitable delay and inconsistency. The quality of the collected TOFD data is another issue that may introduce a host of error to the overall interpretation process. Manual interpretation focuses only on the compression waves portion of the collected TOFD data and overlooks the mode-converted waves region and considers it redundant. This region may provide useful and accurate aw sizing and classification information when there is uncertainty or ambiguity due to the nature of the collected data or the type of aw, and can reduce the number of supplementary (parallel) B-scans by utilising the (longitudinal) D-scans only. The automation of data processing in TOFD is required to minimise time and error and towards building a comprehensive computer-aided TOFD interpretation tool that can aid human operators. This project aims at proposing interpretation algorithms to size and characterise flaws automatically and accurately using data acquired from D-scans only. In order to achieve this, a number of novel data manipulation and processing techniques have been specifically developed and adapted to expose the information in the mode-converted waves region. In addition, several multi-resolution approaches employing the Wavelet transform and texture analysis have been used in aw detection and for de-noising and enhancing quality of the collected data. Performance of the developed algorithms and the results of their application have been promising in terms of speed, accuracy and consistency when compared to human interpretation by an expert operator, using the compression waves portion of the acquired data. This is expected to revolutionise the TOFD data interpretation and be in favour of a real-time processing of large volumes of data. It is highly anticipated that the research findings of this project will increase significantly the reliance on D-scans to obtain high sizing accuracy without the need to perform further B-scans. The overall inspection and interpretation time and cost will therefore be reduced significantly