College of Graduate Studies (COGS)

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https://irepository.uniten.edu.my/handle/123456789/10212

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Comparison reliability perfomance of single bit ECC and multi bit ECC for SLC NAND flash
(2025-07-17)
Kong Kah Wai
NAND flash is a semiconductor product that commonly found in embedded system. It is a known as a type of none volatile memory where no power is required to maintain the data in memory. Manufacturer increases the array cell by using small transistor technology in wafer process. As transistor technology is getting smaller, space between each array cell is reduced, which could lead to many interference issues as well as data integrity issue. It is important for developer to understand the effect of transistor shrink technology towards SLC NAND flash development. Problems such as data lost and program malfunction will easily occur in a product, if they are not taken care-off. In this project an analysis on multi ECC bit and single ECC bit reliability performance of SLC NAND flash from two suppliers are carried out. The analysis of array cell reliability after 100K cycle or read write is carried out. More specifically, the "bit flip" effect due to the read and write test nearby cell is evaluated. It is observed that the multi- bit ECC SLC NAND flash suffers from this effect. The number of block errors in multi- bit ECC SLC NAND flash is higher compared with that of single-bit ECC SLC NAND flash. This observation is obtained for both manufacturers NAND flash. The data retention capability in SLC NAND flashes is tested by exposing the NAND flash under high temperature aging. It is observed that the number of block errors started to be occurring when the temperature is increased above the working operation temperature. Similarly the multi bit ECC SLC NAND flash demonstrates worse. performance as a result of aging test. It is worth to note that, the multi-bit ECC NAND flash has smaller size, hence, higher number bit of ECC is employed to protect the data. Bad block amount exist in both type of sample. Therefore, a bad block test is carried out to evaluate the effect of the transistor shrink SLC NAND flash. More specifically, the manufacturer bad block test is performed only on multi-bit NAND flash to capture the bad block that occurs during manufacturing. This result observed is verified by the manufacturer specifications. It is found out that the quality of NAND flash does degrade as advance transistor technology (smaller) is used. More specifically, during the manufacturing process of multi-bit NAND flash, manufacturer T used two block for testing the reliability of the NAND cell. Thus, the manufacturing bad block of each multi-bit NAND flash contains of two block errors. This experimental result drives attention to an embedded system developer to take necessary precaution in selecting related NAND flash as well as selecting related NAND management system in their product.
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Study on the effect of ampacity for medium voltage underground cables using horizontal direct drilling method in distribution division, Tenaga Nasional Berhad
(2025-06-05)
Masliza Binti Md. Noah
Underground distribution cable is a vital part of TNB Distribution system in delivering the required power. Selecting the most suitable cable installation method is important and it has become more difficult nowadays due to the stringent requirement imposed by the passage caretaker. TNB Distribution will have to deliberately consider both requirements from TNB and the passage caretaker. This study analyzed laying cable in ducts which are best known as installation cable using Horizontal Direct Drilling (HDD) method which is widely imposed by local authorities in Malaysia. HDD also was known as the expensive way of cable installation method even though contributing less harm to the aesthetic value of the road. The independent variables of the research consist of three major criteria that influence the cable ampacity when laid in ducts, which are the depth effect of HDD pipes, the formation of the HDD pipes and the sizes of the HDD duct or pipe. The research used a multi-model approach where the effect of the independent variables on the dependent variable, which is the method of HDD cable installation were evaluated by a developed matrix model. The technical effect of the various cable installation method was examined using CYMCAP Simulation Software program which used IEC 287 to calculate medium voltage underground ampacity worldwide. The simulated data was used to analyze the effect of the ampacity and also to determine the optimum ampacity for the MVUG cables installed using HDD method. The study found that in order to achieve the optimum ampacity of the laid cable using HDD installation method, it is best to maintain the six inches pipe size but with minimum one meter spacing between the pipes. And for single core cable, it is recommended to lay one cable per core per pipe in order to achieve the optimum ampacity of the said cable.
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Early detection of Newcastle disease virus - Infected broiler chickens using machine learning based on optical chromaticity and morphological features
(2025-05-15)
Mohd Anif Akhmal Abu Bakar
The Newcastle disease (ND) outbreak in chickens has raised significant concerns since the Newcastle disease virus (NDV) is highly contagious in chickens and poses a catastrophic impact on populations which can lead to economic losses. Conventional methods of detecting infected chickens rely on manual observation and laboratory tests for confirmation. This method often suffers from delayed detection, leading to major disease outbreaks. Therefore, this research aims to detect NDV-infected chickens in the early stages of infection using image processing techniques and various machine learning classifier models (ML). The research is divided into two main phases. Phase 1 focuses on developing an innovative technique to detect chickens infected with various types of diseases caused by bacteria or viruses based on the optical chromaticity of the chicken comb. This phase analyses the distinctive features of the chromaticity of the chicken comb represented by parameters x, y, and z using the CIE XYZ color space. Chromaticity features were extracted to classify healthy and infected chickens using ML. Phase 2 involved an experimental chicken trial that was carried out for 50 days using specific pathogen free broiler chickens. Surveillance cameras with online connections were set up inside the chicken cages to capture the chicken images without human intervention, simulating actual farm conditions. This phase focuses specifically on detecting NDV-infected chickens based on the combination of the chromaticity and morphological features. The morphological features of the standing chicken were represented by parameters such as circularity, convexity, eccentricity, roundness, and belongation. Morphological and chromaticity features were extracted at 36 hours post infection (after NDV infection) with a 12-hour time step onwards, indicating the severity of the symptoms. This approach enables the development of ML and neural networks to detect infected chickens with respect to the severity of symptoms. Based on the chromaticity analysis in the first phase, the color of the infected chicken's comb transitions from red to green and yellow to blue. The development of various ML using the chromaticity features showed that Logistic Regression (LR), Support Vector Machine (SVM) with Linear and Polynomial kernels performed the best with 95% accuracy. For the well-structured experimental chicken trial in Phase 2, it was established that within 36 hours of NDV-infection, LR and SVM models with Polynomial kernels predict and detect infected chickens at an accuracy of 78.33% and achieved 82.39% after feature optimization. After 72 hours of infection, the best detection is achieved by SVM with Linear kernel model, achieving an accuracy rate of 91.67%. Overall, Phase 1 of this research has established that the chromaticity of chicken comb features can be utilized to detect infected chickens. The study carried out in Phase 2 is the first report on detecting NDV-infected chicken as early as 36 hours post-infection using image processing and ML with an accuracy rate of >75% based on the combination of chicken's comb chromaticity and morphological features. These significant findings contribute to advancing modern agricultural automation technology for early disease detection, ultimately enhancing food security
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Effect of different arrangements of bolt and thickness and shape of gusset plate on the rigidity of beam-to-column connection of cold-formed steel section
(2025-05-15)
Rahima Ummi Kulsum Nadya
Cold-formed steel (CFS) sections are lightweight materials produced by rolling or pressing thin steel sheets at room temperature. In recent years, there has been a growth in the utilisation of CFS as a structural frame for residential constructions and multi-storey commercial buildings. This growth can be attributed to the cost-effectiveness of the material. Despite its lightweight and sustainability benefits, cold-formed steel (CFS) lacks a standardized design for load bearing connectors, as existing codes primarily address individual fasteners rather than integrated connections, resulting in design uncertainties. CFS members' thinness relative to their width makes them prone to buckling, posing a significant design challenge. Additionally, there is limited research on connection configurations, with most studies focusing on idealized connections and overlooking the semi-rigid behaviour of CFS structures. These uncertainties hinder CFS's wider adoption in major structural applications. To bridge this knowledge gap, this research investigates the load response of CFS beam-to-column connections, focusing on how bolt arrangements, gusset plate thickness, and shape impact the behaviour and rigidity of the beam-to-column connection. The research goal was achieved through three key stages:physical testing of a reference connection, numerical analysis of diverse bolt and gusset plate configurations, and evaluation of the connection's failure behaviour, stress distribution, and buckling resistance. Testing on the laboratory model specimen has been carried out until the model has achieved its failure mode. The failure mode of the beam was identified as local buckling, with the specimen (DCC203) failing at a load of 6.9 kN with deformation of 42.17 mm on LVDT. Non-linear load-deformation behaviour was observed on the laboratory test,indicating material yield beyond a certain load threshold. The stiffness (Sj,ini) for the laboratory testing was recorded as 3235.92 kNm/rad. The laboratory-tested model served as the Base Model (BM) for our finite element analysis (FEM), confirming the experimental data's accuracy with a negligible 1.45% peak load difference. This validated the BM in FEM, allowing further investigation on twelve additional models, each with different bolt configurations on the beam to-column sections, gusset plate thicknesses, and shapes. This study examined the influence of bolt configuration, gusset plate thickness, and shape on the behaviour of CFS beam-to-column bolted connections. It was found that increasing the number of bolts on the beam section significantly enhanced connection stiffness, while additional bolts on the column section had a negligible effect on rigidity. While thicker gusset plates marginally improve stiffness, they also introduce a higher risk of buckling due to increased weight. In this study, thicker gusset plates did not significantly reduce z-axis deformation. NBB8 emerged as the model with the highest rigidity (3949.22 kNm/rad), an 18% increase over the baseline BM (3235.92 kNm/rad). However, SGP2 with stiffener plates exhibited the lowest rigidity and significant lateral torsional buckling. Therefore, while NBB8 offers impressive stiffness, considering factors like buckling behaviour is crucial for choosing the optimal model for specific applications. These findings provide valuable insights for optimizing CFS connection design, leading to a more efficient structure.
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Examining factors influencing the adoption of healthcare services in smart cities: A case study on data privacy in Oman
(2025-05-16)
Abdullah Aslam Alzawamri
Adopting Healthcare Services in Smart Cities can enhance healthcare delivery, minimise costs, and improve the quality of life for individuals. However, despite the benefits, the adoption of these services is still relatively low in many regions, including Oman, because serious concern of the smart city is how data and information protection and privacy is managed. One of the biggest challenges is privacy breaches, so, user privacy is a major concern in smart healthcare services in smart cities. Therefore, this research investigates the factors influencing healthcare services adoption in smart cities and tests the validity of the model, focusing on data and information privacy in Oman. A survey questionnaire was distributed to 341 participants, including employees who have undergone Digital Foundations for Public Services program in Oman. Data were analysed using Statistical Package for the Social Sciences (SPSS), and the Structural Equation Modelling (SEM) method was executed using AMOS 20. The research findings suggest that several factors significantly influence the intention to adopt and the actual adoption of healthcare services in smart cities in Oman. Perceived security, perceived usefulness, and perceived ease of use are the main determinants of an individuals’ intentions to adopt healthcare services. Social influence and trust in healthcare providers also significantly impacts the likelihood of adoption. On the other hand, privacy risk and information sensitivity are significant barriers to adoption, as the potential misuse of private data is a serious concern. It is found that privacy concerns is a mediating variable in the intention and adoption of healthcare services in smart cities in Oman. These results provide important insights into the adoption of healthcare services in smart cities, particularly in Oman. These findings can guide healthcare providers and other stakeholders to develop measures that will effectively address the barriers to adoption and promoting the uptake of healthcare services in smart cities, meet consumers’ demands, and provide satisfactory strategies when privacy is violated. For future studies would also be good to use qualitative methodology to closely engage with users and take their opinions, who may be experts in the field of smart cities and healthcare.
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