Publications by authors named "Mohd Shahrizal Sunar"

The dataset presents raw data on the egocentric (first-person view) and exocentric (third-person view) perspectives, including 47166 frame images. Egocentric and exocentric frame images are recorded from original iPhone videos simultaneously. The egocentric view captures the details of proximity hand gestures and attentiveness of the iPhone wearer, while the exocentric view captures the hand gestures in the top-down view of all participants.

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Spontaneous prediction of malignant ventricular arrhythmia (MVA) is useful to avoid delay in rescue operations. Recently, researchers have developed several algorithms to predict MVA using various features derived from electrocardiogram (ECG). However, there are several unresolved issues regarding MVA prediction such as the effect of number of ECG features on a prediction remaining unclear, possibility that an alert for occurring MVA may arrive very late and uncertainty in the performance of the algorithm predicting MVA minutes before onset.

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Cardiovascular application of nanomaterial's is of increasing demand and its usage is limited by its mechanical and blood compatible properties. In this work, an attempt is made to develop an electrospun novel nanocomposite loaded with basil oil and titanium dioxide (TiO) particles. The composite material displayed increase in hydrophobic and reduced fiber diameter compared to the pristine polymer.

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Volumetric shadows often increase the realism of rendered scenes in computer graphics. Typical volumetric shadows techniques do not provide a smooth transition effect in real-time with conservation on crispness of boundaries. This research presents a new technique for generating high quality volumetric shadows by sampling and interpolation.

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To achieve realistic Augmented Reality (AR), shadows play an important role in creating a 3D impression of a scene. Casting virtual shadows on real and virtual objects is one of the topics of research being conducted in this area. In this paper, we propose a new method for creating complex AR indoor scenes using real time depth detection to exert virtual shadows on virtual and real environments.

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Metabolic pathways have become increasingly available for various microorganisms. Such pathways have spurred the development of a wide array of computational tools, in particular, mathematical pathfinding approaches. This article can facilitate the understanding of computational analysis of metabolic pathways in genomics.

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Realistic rendering techniques of outdoor Augmented Reality (AR) has been an attractive topic since the last two decades considering the sizeable amount of publications in computer graphics. Realistic virtual objects in outdoor rendering AR systems require sophisticated effects such as: shadows, daylight and interactions between sky colours and virtual as well as real objects. A few realistic rendering techniques have been designed to overcome this obstacle, most of which are related to non real-time rendering.

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Article Synopsis
  • Neuron cells are complex structures consisting of axons and dendrites that transmit signals between the brain and nervous system, and improving 3D visualization models can enhance understanding and diagnosis of brain functions.
  • Existing neuron models lack realism, as they depict neurons as disjointed segments rather than representing their continuous growth and connections.
  • A new reconstruction model using methods like Bounding Cylinder, Curve Interpolation, and Gouraud Shading has shown promising results, achieving an 82% acceptance and satisfaction rate from bioinformatics analysts in terms of realism and effectiveness.
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