Kajian motivasi ekstrinsik di antara Pelajar Lepasan Sijil dan Diploma Politeknik Jabatan Kejuruteraan Awam KUiTTHO

Kajian ini dijalankan untuk menyelidiki pengaruh dorongan keluarga, cara pengajaran pensyarah, pengaruh rakan sebaya dan kemudahan infrastruktur terhadap motivasi ekstrinsik bagi pelajar tahun tiga dan tahun empat lepasan sijil dan diploma politeknik Jabatan Kejuruteraan Awain Kolej Universiti Teknologi Tun Hussein Onn. Sampel kajian ini beijumlah 87 orang bagi pelajar lepasan sijil politeknik dan 38 orang bagi lepasan diploma politeknik. Data kajian telah diperolehi melalui borang soal selidik dan telah dianalisis menggunakan perisian SPSS (Statical Package For Sciences). Hasil kajian telah dipersembahkan dalam bentuk jadual dan histohgrapi. Analisis kajian mendapati bahawa kedua-dua kumpulan setuju bahawa faktor-faktor di atas memberi kesan kepada motivasi ekstrinsik mereka. Dengan kata lain faktpr-faktor tersebut penting dalam membentuk pelajar mencapai kecemerlangan akademik

Speckle Noise Reduction in Medical Ultrasound Images

Ultrasound imaging is an incontestable vital tool for diagnosis, it provides in non-invasive manner the internal structure of the body to detect eventually diseases or abnormalities tissues. Unfortunately, the presence of speckle noise in these images affects edges and fine details which limit the contrast resolution and make diagnostic more difficult. In this paper, we propose a denoising approach which combines logarithmic transformation and a non linear diffusion tensor. Since speckle noise is multiplicative and nonwhite process, the logarithmic transformation is a reasonable choice to convert signaldependent or pure multiplicative noise to an additive one. The key idea from using diffusion tensor is to adapt the flow diffusion towards the local orientation by applying anisotropic diffusion along the coherent structure direction of interesting features in the image. To illustrate the effective performance of our algorithm, we present some experimental results on synthetically and real echographic images

Evaluation of Digital Speckle Filters for Ultrasound Images

Ultrasound (US) images are inherently corrupted by speckle noise causing inaccuracy of medical diagnosis using this technique. Hence, numerous despeckling filters are used to denoise US images. However most of the despeckling techniques cause blurring to the US images. In this work, four filters namely Lee, Wavelet Linear Minimum Mean Square Error (LMMSE), Speckle-reduction Anisotropic Diffusion (SRAD) and Non-local-means (NLM) filters are evaluated in terms of their ability in noise removal and capability to preserve the image contrast. This is done through calculating four performance metrics Peak Signal to Noise Ratio (PSNR), Ultrasound Despeckling Assessment Index (USDSAI), Normalized Variance and Mean Preservation. The experiments were conducted on three different types of images which is simulated noise images, computer generated image and real US images. The evaluation in terms of PSNR, USDSAI, Normalized Variance and Mean Preservation shows that NLM filter is the best filter in all scenarios considering both speckle noise suppression and image restoration however with quite slow processing time. It may not be the best option of filter if speed is the priority during the image processing. Wavelet LMMSE filter is the next best performing filter after NLM filter with faster speed