Pusat Pengajian Sains Komputer - Tesis

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Real-Time Capable Multi-Hop Media Access Control Protocol For Smart Home Environment
(2017-11)
M.Shukeri, Nurulfaizal
The Wireless Sensor Network (WSN) is a technology that is now often highlighted and various studies have been done to apply in life such as environmental monitoring, security and military applications. These include the study of the Internet of Things (loT) and Smart Home, where it is now gaining popularity in the research environment. The combination of home appliances such as lights, gates and closed circuit, would be able to make the future home not just smart, but smarter in energy consumption and secure. Nevertheless, to apply WSN in the Smart Home Environment, WSN protocols need to support real-time characteristics. This protocol must also be capable of transmitting time-sensitive data such as audio and video at low bit rates through a multi-hop network where coverage can be expanded.
Compute Language Interface: A Transparent Wrapper Library For Multi Cpu-Gpu
(2013-03)
Ooi, Keng Siang
The Graphics Processing Unit (GPU) processing capability is getting more powerful than before. Compute intensive and data parallelism applications are proven to perform better on the GPU than on the Central Processing Unit (CPU). However, available General-Purpose Computing on Graphics Processing Unit (GPGPU) programming frameworks which are available publicly are unable to reach beyond the single computer limitation to utilize multiple CPUs and GPUs at different computers in a distributed computing system easily. This study presents the Compute Language Interface (CLI) which is a wrapper library that enables the existing OpenCL applications access to all available CPUs and GPUs in a distributed computing system through Message Passing Interface (MPI) transparently. It is designed to improve the scalability of the OpenCL applications on a distributed computing system while maintaining the same set of application programming interface (API) in the original OpenCL library. The applications can access all available CPUs and GPUs in different computers in a distributed computing system as ifall the CPUs and GPUs are in the same computer.
Social Sciences, Arts And Humanities Research Collaboration: The Malaysian Coverage
(2014)
Hussain, Husriati
As a developing country, Malaysia emphasizes the need for university researchers to be more socially oriented and highly encourages them to seek collaboration with other organizations. Collaboration is used as the main requirement and indicator in almost Malaysian grant scheme and Malaysian research assessment, such as Higher Institutions Centre of Excellence (HICoE) Grant, Long Term Research Grant Scheme (LRGS), Malaysian Research Assessment (MyRA), National Higher Education Strategic Plan, etc. The main reasons behind this are because collaboration may contribute to creative, wealth and innovative ideas, unique experiences, and great exposures, which consequently will give a high impact on the nation's research productivity and development. In this regard, this study employed bibliometric methods of co-authorship analysis to measure the patterns of collaboration in Social Sciences, Arts and Humanities in Malaysia from 2007 to 2011. Based on the 2,280 publications, patterns of collaboration were analyzed with respect to 7 relevant areas: co-authorship patterns, national and international collaboration, country collaboration, institutional collaboration, sectoral collaboration, intra-disciplinary and interdisciplinary collaboration, and extent of collaboration. The results may help the government and universities to plan an appropriate Malaysia Research Policy and manage the R&D funding and resources effectively and efficiently. The
Multi-fish Detection And Tracking Using Track-mask Region Convolutional Neural Network
(2023-09)
Alshdaifat, Nawaf Farhan Fankur
Deep learning has become more common in recent years due to its excellent results in many areas. This thesis primarily focuses on multi-fish detection and tracking methods in underwater videos. The existing multi-fish detection methods for underwater videos have a low detection rate and consumes time in the training and testing process due to the underwater conditions and the overfitting during training. Many multi-fish detection and tracking methods for underwater videos (based on deep learning) where low accuracy for multi-fish tracking and occlusion instances during multi-fish tracking leads to inability to distinguish edges, and inability to handle each detected object over time. Therefore, this research aims to improve and enhance methods for multi-fish detection and tracking in underwater videos based on the latest deep learning algorithms. The proposed improved multi-fish detection method involves three main steps: 1) Improving ResNet-101 backbone for better fish detection, 2) Enhancing the Region Proposal Network (RPN) method based on Faster R-CNN for multi-fish detection and 3) An improved multi-fish detection method in terms of accuracy and with a lower training and testing times by utilising the aforementioned methods. The proposed multi-fish tracking method (Track-Mask R-CNN) also exhibits similar enhanced characteristics compared to the state-of-art methods (using fish dataset). An accuracy of 86.7% and 78.9% have been achieved for the proposed multi-fish detection and tracking respectively.
Partial Verification Bias Correction In Diagnostic Accuracy Studies Using Propensity Score-Based Methods
(2023-06)
Wan Nor Arifin Bin Wan Mansor
This research objective was to design PS-based methods with weighted regression and resampling approaches to improve and extend PVB correction under MAR and MNAR assumptions. Three MAR PS-based methods of PVB correction were proposed: 1) Inverse probability weighted logistic regression (IPWLogReg), 2) Scaled inverse probability weighted resampling (SIPW-Resamp) and 3) Scaled inverse probability weighted balanced resampling (SIPW-BalResamp).

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