Tidak Diketahui Pusat Pengajian - Tesis

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Investigation Of Influencing Factors On Dioxins Formation From Combustion Of Peat In Malaysia In The Presence Of Different Precursors And Catalysts
(2025-09)
Mohamed, Khairulmazidah
Polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs), collectively referred to as dioxins, are toxic compounds generated as unintentional byproducts of organic material combustion. While industrial emissions have significantly decreased since 2000, contributions from forest fires, domestic combustion, and vehicular sources remain concerning. Frequent peat fires in Southeast Asia may have leadingly contributed to the dioxins level in the environment. Peat, having high amount of organic material and possible precursor and catalysts for dioxins formation, is highly susceptible to dioxin production during combustion. This study aims to determine the physico-chemical properties, precursor compounds, catalysts, and congener profiles of dioxins of Peninsular Malaysian tropical peats at different depths and eventually determine the congener of emissions resulting from the combustion of selected peat samples.
Elucidation Of Indoor Air Microbial Air Quality And Occurrence Of Mycotoxin In Old Building
(2025-09)
Hamdan, Anis Syuhada Omar
Mycotoxins are secondary metabolites released by filamentous fungi and moulds that may negatively impact the building occupant’s health. Most of the building occupants tend to spend their time in an indoor environment, which might be a health risk due to the presence of mycotoxins, by-products of fungi. In addition, older buildings often experience significant issues due to material and physical deterioration, which can lead to the presence of harmful biological contaminants in the occupants' environment. In malaysia, at this point, there has been limited study on the occurrence of mycotoxins in indoor air, especially in old buildings. The present study investigated and identified the fungi and mycotoxins that occurred in selected old buildings, together with the potential health risks among the building occupants. Two old buildings, the institute for medical research (imr) and universiti sains malaysia (usm), were selected for this study. There were 18 sampling locations, and each building had nine locations that were identified with the fungus problem and moisture damage.
High Figure Of Merit (Fom) Versatile 5g C Band New Radio Iq Receiver System
(2025-04)
Shasidharan, Pravinah Nair
The evolution of 5g technology for the upcoming generation of high-speed applications demands a substantial drive for innovation to develop a more extensive wireless communication system. This dissertation aims to address the challenges associated with high speeds and overcome trade-offs to enhance coverage performance for the 5g new radio c band receiver. It introduces a high figure of merit (fom) 5g new radio wideband receiver system, designed for sub-6 ghz c band applications and implemented using the 130 nm cmos silterra process. The receiver system incorporates a dual-stage low noise amplifier (lna) configuration to achieve a high and consistent gain across the target bandwidth of 3 to 5 ghz, without sacrificing linearity, noise figure, and stability. The lnas are integrated with an innovative iq generator circuit to ensure rf quadrature generation at four phases: 0°, 180°, 90°, and 270°. The double balance mixer, integrated with the iq generator circuit, is supported by 3 to 5 ghz free-running tailless hybrid vcos to form i and q intermediate frequency (if) of 100-200mhz, further enhanced with stacked transimpedance amplifier (tia) stages. Consequently, the entire proposed receiver system achieves key parameters of 35.6 db gain, linearity of 16.1 dbm, and a noise figure (nf) of 4.2 db under 12mw power consumption.
An Adaptive Dropout Artificial Neural Network-Based Approach For Detecting Version Number Attacks In Rpl-Based IOT Network
(2025-07)
Alfriehat, Nadia Adnan Abdallah
This study introduces an adaptive dropout artificial neural network-based approach, ADAN2_VN, for the detection of VN attacks in RPL-based IoT environments. The proposed framework is structured into four phases: (1) extraction of novel features using statistical analysis of IoT traffic data; (2) data preprocessing encompassing cleansing, balancing, and normalizati on; (3) ensemble feature selection to isolate the most significant attributes; and (4) implementation of an adaptive dropout strategy within an artificial neural network to enhance detection performance.
High Efficiency And High Psrr Cmos Multi-Voltage Domain Buck Integrated Low Dropout Regulator
(2025-02)
Poongan, Balamahesn
Power regulators are essential in ensuring stable output for electronic systems by controlling voltage levels. Linear regulators, such as low dropout (ldo) regulators, fixed linear regulators, and shunt regulators, adjust resistance to maintain stable voltages, commonly used in rf applications, audio circuits, and precision analog systems. Switching regulators, including buck and boost converters, efficiently convert voltage by rapidly switching a transistor, typically used in power supplies where noise sensitivity is lower. In this work, a high-efficiency multi-voltage domain (mvd) integrated buck-ldo regulator with a combined compensation scheme is proposed. The mvd buck-ldo operates with a 4.0 v supply headroom and regulates four voltage domains (1.8 v to 3.0 v) with an efficiency of 85.24%. An integrated demultiplexer controller consumes just 42 nw. The design minimizes external components, requiring only a single inductor and capacitor, with a 500 khz clock generator. A single 1.25 v bandgap reference supports both buck and ldo functions.

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