Computer Science, Information Technology and Telecommunications

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Derivation of extreme non-gaussian stochastic offshore structural responses using finite memory nonlinear system
(Universiti Teknologi Malaysia, 2020) Mukhlas, Nurul ’Azizah
For offshore structural design, the load due to wind-generated random waves is usually the most important source of loading. A nonlinear wave analysis is recommended to represent a realistic ocean wave for an accurate prediction of extreme offshore structural response. Nevertheless, the contribution of nonlinearity especially due to the wave-wave interaction leads to a complex solution. In fact, the random wave load itself experienced a nonlinearity due to the drag component of Morison’s load, the effect of load intermittency around the member in the splash zone, and the presence of current; which result in a non-Gaussian offshore structural response. The most accurate and versatile method for predicting the statistical properties of extreme responses on a subjected load is the Monte Carlo time simulation method, which can account for all sorts of nonlinearities without introducing any approximations. However, it is computationally very demanding due to its complex procedure in simulating the structural response as reliable results require a very large number of simulations. Therefore, a simple method using finite-memory nonlinear system (FMNS) has been introduced by previous researchers and is proven to improve the efficiency of evaluating offshore structural responses without sacrificing its accuracy. The method is, however, only applicable based on the linear wave analysis. Hence, by taking advantage of the efficiency of FMNS method, a new model needs to be developed by integrating the FMNS method with a nonlinear wave analysis for a more reliable result. It is the derivation of non-Gaussian stochastic offshore structural response using finite-memory nonlinear system, known as FMNSNL (subscript NL indicates nonlinear). In the model development process, the surface elevation is generated first according to a nonlinear wave analysis with at least second-order wave. Then, two components of system are introduced, in which the first component enabled the transformation from a reference surface elevation to a second-order linearized quasi-static responses, while the second component involved the development of nonlinear function based on the relationship of second-order nonlinear and linearized quasi-static responses. Four models have been developed, in which the best model can produce an output of approximate values of second-order nonlinear quasi-static response that is very close to its corresponding values obtained using Monte Carlo time simulation method and will then be used for further examination. Based on the correlation coefficient between those two methods, the best relationship with value of 0.9783 was obtained by model 4 on the drag-induced quasi-static base shear for high significant wave height. The procedure of model development based on those two components is examined for all sea state conditions with Hs = 5, 10 and 15 m, and with the presence of current, U̅= 0 m/sec and ±0.90 m/sec. As a result, the relationship of model 4 fits the data better for all cases. It should be noted that this investigation of in-service analysis is carried out only for quasi-static structure by neglecting the dynamic effect. Based on the result of the short-term analysis, FMNSNL method provided a good accuracy of prediction of 100-year responses compared with the corresponding prediction using Monte Carlo time simulation method for all cases. A comparison has been made according to the ratio of prediction between FMNSNL and Monte Carlo time simulation methods. Overall, the accuracy level achieved by FMNSNL method is in the range of 82% to 99.8%, in which the accuracy level improved with the presence of positive current and vice versa with negative current. The same conclusion is valid for long-term analysis since the accuracy performance of FMNSNL followed exactly as previous analysis for short-term distribution. Without the presence of current along the wave propagation, the accuracy level of FMNSNL method is in the range of 80% to 96%. If there exist a current with the same direction of the wave (positive current), the accuracy improved with an increment of 1% to 7%. However, the opposite direction of current (negative current) provided a severe impact on its prediction with a reduction of 1% to 18% of accuracy. Hence, the method of FMNSNL can then be used with an excellent efficiency and accuracy to determine the extreme offshore structural response. With that, the offshore structure is towards optimization that leads to cost reduction and preservation of safety.
Bond strength and tension stiffening of fly ash geopolymer concrete
(Universiti Teknologi Malaysia, 2022) Salem, Hamdi Abdulrahman Saif
Fly ash geopolymer concrete has gained attention from concrete industries and researchers in view of its environmental sustainability in construction. This emerging concrete protects the environment by utilizing fly ash wastes and significantly reducing the demand for Ordinary Portland Cement (OPC) concrete that exhibits higher carbon footprints. A proper understanding of mechanical properties and structural behaviour of fly ash geopolymer is crucial at the service and ultimate limit state conditions. Therefore, this study aims to investigate the mechanical properties of high calcium fly ash (HCFA) geopolymer concrete and evaluate the effects of compressive strength and concrete cover-to-bar diameter (Cc/db) ratio on bond strength, tension stiffening, crack spacing, and crack width. The initial step of the experimental program was to develop a concrete design mix based on trial-and-error by varying alkaline activator to binder (AA: B) ratios between 0.30 to 0.40 to achieve concrete compressive strength between 20 MPa and 45 MPa using ambient curing regime. Pullout specimens were cast on 100 mm dimensional cube molds due to their accuracy in obtaining bond strength. Tension stiffening prisms were cast on molds with a square cross-section of 75 mm ×75 mm and a length of 650 mm, in which matrix cracking was allowed to occur. The Cc/db ratio for pullout specimens and tension stiffening prisms varied from 2.63 to 4.5 and 1.84 to 3.25, respectively. The pullout results showed that HCFA geopolymer concrete has a high bond strength and is affected by both compressive strength and Cc/db ratio. Most of the pullout specimens exhibited splitting bond failure characterized by a gradual decay of bond strength. A comparison between the experimental bond strength and that estimated using OPC concrete formulas revealed that the bond strength of HCFA geopolymer concrete is slightly underestimated due to a better interfacial transition zone in the concrete matrix. Significantly, the results of tension stiffening, crack spacing, and crack width showed that HCFA geopolymer concrete exhibited better tension stiffening with smaller crack width and spacing than OPC control specimens. These results were influenced by both compressive strength and the Cc/db ratio. Increasing the reinforcement ratio resulted in a higher crack number due to the smaller concrete cross-sectional area, which required a lower force to generate more cracks. This consequently reduced the average crack spacing and produced a narrower crack width. The results also showed that fly ash geopolymer concrete exhibited a ductile cracking compared to the brittle fracture mechanism observed in OPC concrete. In addition, the experimental crack spacing and crack width were validated against those values estimated using the standard codes of practice, suggesting that the existing provisions developed for OPC concrete underestimate crack spacing and crack width by 15% and 30% respectively. In conclusion, this study developed the empirical models based on the experimental results to estimate the bond-slip performance, crack width and crack spacing of HCFA geopolymer concrete.
A hybrid effort estimation model for change request in ongoing software project
(Universiti Teknologi Malaysia, 2022) Md. Sarkan, Haslina
Frequent requirement changes are challenging in an ongoing software project and have been recognised as one of the main causes of project failures. Many change requests are expected as new requirements would eventually accumulate to meet the stakeholders’ expectations or adapt to new technologies and current circumstances. This circumstance requires the Software Project Manager (SPM) to make good and fast effort estimations. Inaccurate estimations could lead to over-estimate or under-estimate, resulting in wastage of resources or budget excess during an ongoing software project. When the software is under development, the software artefacts are in unstable states. Current estimation models are not very accurate when it comes to estimating effort based on multiple change requests. To address this issue, an estimation model is needed to aid the SPM to estimate the effort taken by the change requested to approve or reject it. In this research, a hybrid effort estimation model was developed to enable the SPM to make a more accurate decision to accept or reject a change request. The design of this model took into consideration algorithmic methods which are Software Change Impact Analysis (SCIA) and Software Change Effort Estimation (SCEE) to deal with artefacts which are either fully developed, under development or not yet being developed, hybridized with expert judgement, to provide SPM with the correct information to decide whether to accept or not a change request. The hybrid effort estimation (HEE) model was successfully developed. A prototype was built to evaluate this model. The results demonstrated improved accuracy for the hybrid model compared to the algorithmic model. Many effort estimation models exist but none works well for different types of projects. This research has demonstrated that a hybrid effort estimation model via the prototype improves estimates; taking advantage of both algorithmic and non-algorithmic model’s benefits. Experimental results showed a 17% accuracy improvement.
Cost-aware real-time divisible loads scheduling in cloud computing
(Universiti Teknologi Malaysia, 2022) Abdul Majid, Mimi Liza
Cloud computing has become an indispensable alternative for processing big data in science, engineering and analytics. Today, cloud service providers typically offer users virtual machines with different combinations of configurations and prices. Since each user has different preferences and priorities, the problem of allocating the minimum-cost processors while meeting a deadline becomes increasingly complex. Moreover, most previous research have assumed that processors in cloud computing are homogeneous. However, in reality, it consists of heterogeneous processors with different speeds. This thesis examined user preference adaptation for scheduling divisible workloads in a cloud computing platform with deadline constraint as a quality of service (QoS) criteria. The workload allocation approach used in this research is Real-time Divisible Load Theory (RT-DLT). Two crucial problems were investigated: choosing the minimum cost resource combination when processors are heterogeneous in terms of speed and allowing cloud users to have different preferences in terms of their cost while being able to meet their specified deadline. For the first problem, an algorithm called Cost Aware Real-Time Divisible Load Theory (CARTDLT) was developed and a Worker Selection Strategy (WSS) was introduced into the RT-DLT scheduling framework. The additional strategy is mainly to select the best combination of processing nodes that results in the desired total cost based on user requirements. For the second problem, an algorithm called Market-Oriented Real-time Divisible Load Theory (MORTDLT) was developed to group the resources and optimally distribute the load fragments among the available resources according to the user's preference. The proposed algorithm was evaluated through the experimental evaluation using MATLAB and CloudSim 3.0.3, and compared with Min-Min, Max- Min and Sufferage algorithms. The CARTDLT algorithm showed a cost improvement of 45.06% over the Max-Min algorithm, 42.52% over the Min-Min algorithm and 45.57% over the Sufferage algorithm. For low priority user preference, the MORTDLT algorithm showed a cost improvement of 61.22 % over the Max-Min algorithm, 83.58 % over the Min-min algorithm and 49.76 % over the Sufferage algorithm. For high priority user preference, the MORTDLT algorithm showed a cost improvement of 54.49% over the Max-min algorithm, 43.12% over the Min-Min algorithm and 57.60% over Sufferage algorithm. The results indicate that the proposed algorithms have the lowest computational cost and imbalance, and ensure compliance with the deadline without compromising other performance metrics such as makespan. The CARTDLT and MORTDLT algorithms will help cloud users to have different preferences on their costs while meeting the deadline for their job.
Pengurangan kesesakan lalu lintas melalui kawalan lampu isyarat berasaskan integrasi imej dan logik kabur
(Universiti Teknologi Malaysia, 2020) Hamzah, Amir
Masa lampu isyarat di persimpangan ditentukan oleh pihak berkuasa tempatan berdasarkan kajian kepadatan kenderaan sahaja. Kesesakan lalu lintas biasanya tinggi di persimpangan terutama pada waktu puncak; namun, sistem semasa hanya menggunakan satu waktu purata sepanjang hari tanpa mengira jumlah kenderaan dan lebar jalan. Oleh itu, kajian ini bertujuan untuk meningkatkan aliran lalu lintas dengan mengawal lampu isyarat berdasarkan input pada jumlah kenderaan dan lebar jalan. Kajian ini membangunkan algoritma menggunakan peraturan logik kabur untuk masa lampu hijau. Algoritma ini dibangunkan berdasarkan dua input: jumlah kenderaan dan lebar jalan yang bersumber dari Peta Google, untuk menentukan masa lampu hijau. Kajian ini memberi masukan mengenai jumlah kenderaan dan lebar jalan di persimpangan Sala Benda dan Semplak di Bogor, Indonesia. Peraturan logik kabur yang dicadangkan telah mengetengahkan tiga kelas masa lampu hijau – lama, sederhana dan sebentar – berdasarkan jumlah kenderaan dan lebar jalan. Hasil ujian lapangan menunjukkan penurunan masa lampu hijau dari waktu semasa antara 9% hingga 91% di persimpangan Sala Benda dan antara 2.05% hingga 73.19% di persimpangan Semplak. Ringkasnya, kajian ini telah merumuskan masa lampu hijau yang optimum di setiap persimpangan berdasarkan jumlah kenderaan dan lebar jalan dan juga merumuskan tiga kelas masa lampu hijau. Algoritma dapat digunakan oleh pihak berkuasa tempatan yang lain untuk menentukan masa lampu isyarat hijau dalam meningkatkan aliran lalu lintas.

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