Purpose The purpose of this paper is to report the results an exploratory investigation behavioral factors in relation virtual knowledge sharing among Multimedia University students, Malaysia, based on theory reasoned action (TRA). Design/methodology/approach A search and review existing literature was followed by empirical test proposed model pilot study (number participants: n =50) main ( =250). Findings Trust, anticipated reciprocal relationship willingness share as individual's attitude;...

We frequently hear news about compromised systems, virus attacks, spam emails, stolen bank account numbers, and loss of money. Safeguarding protecting digital assets against these other cyber-attacks are extremely important in our connected world today. Many organizations spend substantial amounts money to protect their assets. One type cyber threat that is rampant days social engineering attacks work on human psychology. These typically persuade, convince, trick threaten naïve innocent...

The capacity for creativity and innovation has become increasingly crucial in today's dynamic world, where adaptability forward-thinking are essential success. Drawing from recent advances neuroscience, quantum physics, consciousness studies, this paper explores a holistic approach to fostering students. Through the integration of cognitive, emotional, interpersonal dimensions, we develop validate machine learning framework that predicts creative capabilities based on physiological...

The aim of this paper is to compare the performances ARIMA, Neural Network and Linear Regression models for prediction Infant Mortality Rate. performance comparison based on Rate data collected in Indonesia during years 1995 – 2008. We using measures such as Mean Absolute Error (MAE), Percentage (MAPE) Root Square (RMSE). results show that model with 6 input neurons, 10 hidden layer neurons hyperbolic tangent activation functions output layers best among different considered.

Medical centers produce a massive amount of sequential medical images for examinations such as CT, MRI and Fluoroscopy, where each examination patient consists series images. This takes up large storage space, in addition to the cost time incurred during transmission. For data, lossless compression is preferred greater gains lossy compression, interest accuracy. paper proposes new method pharynx esophagus fluoroscopy images, using correlation combination Run Length Huffman coding on...

Automated optical inspection (AOI) is a visual defect system. The semiconductor industry has strong dependency on AOI for defects screening. Conventional inadequate some inspections, especially surface like crack, chip and void, the algorithms are inefficient in isolating from product variants. Convolutional Neural Network (CNN) had been broadly studied adopted to replace conventional inspection. There many CNN architectures developed past decade image classification, such as AlexNet,...

This paper proposes new coding schemes based on neural networks for the compression of telemetry data. It is shown that network predictors can be used successfully in a two-stage lossless scheme. Single-layer perceptron, multi-layer perceptron and recurrent models are investigated this purpose. The proposed tested using different data files. For encoder second stage, arithmetic Huffman employed. found performance comparable some cases better than methods linear such as FIR lattice filters.

Image de-noising is a core operation in image processing and computer vision. In this paper, combination of two popular methods bilateral anisotropic-diffusion filtering investigated to reduce the noise medical images, while preserving clarity images. The proposed method experimented on 23 MRI results obtained from gained higher peak signal ratio (PSNR) compression (CR) performance comparison with traditional by more than 8%.

Low-field magnetic resonance imaging (MRI) is vital for sensitive surgery to allow real-time in the operation theatre. In this paper, we demonstrate implementations of denoising algorithms on low-field MR brain images. A major concern images poor quality secondary a worsening signal-to-noise ratio (SNR) compared with high-field MRI scanners. This paper gives some useful insight application pre-processing techniques towards segmenting and labeling Promising results are reported anisotropic...

This paper proposes an efficient way to effectively segment malignant melanoma in color dermoscopy images. A combination of methods are used the proposed technique, including smoothing filters, PSNR, Spline, edge detection, morphological operations and segmentation. The pre-processing step eliminates noise, smoothes image employs spline function improve while lesion from image. Manual boundary selection is as benchmark test accuracy automatic by algorithm. evaluation results show that method...

Liver diseases are a common medical problem, especially amongst the population of developing countries. Magnetic Resonance Cholangio Pancreatography (MRCP) has become popular non-invasive, non-ionizing examination for analysis hepatobiliary structure in liver. Unfortunately, conventional 2D MRCP images can be difficult to analyze biliary tree anomalies, with volume effect, artefacts and noise present these images, whilst good 3D MRI systems costly less affluent nations. This paper proposes...