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Architect’s perception of factors contributing to construction project delay In planning & design phase: Case studies of private housing projects In Klang Valley, Malaysia / Ong Wee Yeak
Get PDFFor construction projects, a delay occurs when the project is unable to be finished on
time. In Malaysia, delay is an unavoidable issue that occurs in all phases of construction
project. Presently, the majority of past research has concentrated on determining the
reasons of or resolving delays in the building phase; however, only a few studies have
looked into delays in the planning and design phases. Thus, this study aims to to
identify the factors that contributing to construction project delays in the planning and
design phase, specially for the private housing projects. Quantitative research method is
adopted as to meet the research objective. This research was conducted depend on the
literature review and questionnaire survey. A questionnaire survey was conducted and
delivered to respondents from architectural consultancy practice (ACP) registered with
the Board of Architects Malaysia (LAM). Relative importance index (RII) analysis
methods applied to justify the most critical delay factors for data analysis. Changes of
client’s requirements was among the most critical causes of delay in the planning and
design phases. The outcome of this research is good justification to propose some
recommendations to mitigate delays for better performance of Malaysia’s private
housing construction project
An optimal homotopy asymptotic method for finding solutions of non-linear fractional mathematical models / Okundalaye Oluwaseun Olumide
No full textThis research project investigates the optimal solution procedure by constructing a fractional mathematical model with a conformable fractional derivative operator sense. Many real-life problems can be modelled more stably with fractional calculus due to its unique long memory feature and non-locality. An approximate analytical method (AAM) for an approximate analytical solution (AAS) has been employed in providing the solution to the model. One of the primary importance of using an AAS is to provide a solution where the exact solution is not available and had been established as one of the best solutions to address this model by many authors. However, the published studies have failed to establish the convergent criteria that guarantee accurate optimal values for the optimal solution. We addressed this challenge using the new optimal homotopy asymptotic method (OHAM) for optimal values for the accurate optimal solution. In this research, four fractional mathematical models with conformable fractional derivative operator sense have been modernized. We considered a fractional mathematical model of the steepest descent direction for equality non-linear constrained optimization problems in the first model. We considered a fractional mathematical model of the steepest descent direction for equality and inequality non-linear constrained optimization problems in the second model. In the third model, a fractional mathematical model for non-linear constrained optimal control problems is developed. In contrast, in the fourth model, we apply the proposed solution method for the non-linear fractional-order epidemic model (FOEM) of childhood disease prediction. The objective is to find the optimal solution, behaviour, and performance of the proposed fractional mathematical model (FMM) in the models. We produced a mathematical formulation and analysis of the problems inside the framework of the modification. A system of non-linear fractional differential equations with given initial conditions was provided for the proposed problems. Finally, we examined the results and compared them to previous works. Our results show a significant performance in fast convergence, actual optimal results, and provides more information about the complexity of the dynamics of the proposed models
Tissue culture of Orthosiphon stamineus and effects of abiotic stress exposure on somaclonal variation / Hanisah Ali
No full textOrthosiphon stamineus is a medicinal herb that has long been used as a traditional treatment for a variety of ailments and disorders, including cardiovascular disease and
epilepsy. In this study, an efficient mircopropagation technique of this species was developed. The plantlets produced were subjected to various stress factors to elucidate
the effects of these stresses on the occurrence of somaclonal variation in this species. Murashige and Skoog (MS) media supplemented with 2.0 mg/L kinetin plus 0.5 mg/LIAA has been identified as the optimum in vitro regeneration media (OM) for nodal explant, yielding the highest production of shoots (5.57 ± 0.42) and leaves (20.53 ± 1.91) per explant. The clonal plantlets were subjected to an Inter Simple Sequence Repeat (ISSR) analysis to determine the genetic fidelity of the regenerants. Data analysis confirmed the clonal nature of the resulting plantlets, based on very low
polymorphism (7.32%) and low genetic distance values observed in all samples compared to the mother plant. The plantlets were also exposed to various stress factors in different concentration such as high salinity, abscisic acid (ABA) and high cytokinin, by sub-culturing the plantlets onto OM added with various concentrations of NaCl, ABA and high kinetin levels. The exposure to the various stress factors was observed to result in the occurrence of somaclonal variation in O. stamineus, where incidence of hyperhydricity (vitrification) was found to be the most prominent. The variants were then also subjected to an ISSR analysis to compare their genetic distance with the clonal plantlets produced on OM as well as the mother plant. 70.12% polymorphism was discovered in all variants. The results of this study also showed that the plantlets' photosynthetic ability was reduced when the abiotic stress levels increased (as shown by high MDA levels). It was also discovered that when stress levels increased, the chlorophyll content would decrease, which indicates the potential of manipulating the plantlets’ response to stress as a way to increase the production of certain metabolites. Further research should be conducted on the metabolites that are generated and the metabolic pathways related to somaclonal variation, as a result of the exposure to abiotic stress
Evaluation of outlier filtering algorithms for accurate measurement of travel time reliability incorporating lane-splitting situations / Obada M. A. Asqool
No full textMost developed and developing countries, including Malaysia, experience high traffic congestion, especially in urban areas. When congestion occurs, traffic moves at a lower speed which increases travel time and in consequence, people spend considerable time fulfilling their daily journeys. Measuring Travel Time Reliability (TTR) helps traffic professionals to quantify congestion based on travel time parameter, thus, adopting suitable strategies to mitigate traffic congestion. On the other hand, motorcycles are significantly high in Malaysia and other Association of Southeast Asian Nations (ASEAN) countries. As such, detection of travel time based on the media access control (MAC) address is not straightforward. Raw travel times data does not represent the actual traffic condition of passenger cars since motorcycles travel faster than cars during congestion using the gap between two parallel rows of cars. This situation is called lane-splitting. In the past, many travel time filtration algorithms were established. However, there is a real need to determine which algorithms can produce the most accurate results when considering actual and large datasets from lane-splitting situations. Therefore, this study aims to investigate the best algorithm for data filtration and how to use it to obtain accurate data for measuring TTR. In order to find the best filtration algorithm, two stages were adopted in this study. The first stage was the validation of the performance of the previous algorithms. The assessment was conducted by observing the performance of each algorithm and comparing its performance with other algorithms when lane-splitting data were applied. The second stage was to investigate the sensitivity of the algorithm parameters for different days. To analyse TTR, Travel Time Index (TTI), Planning Time Index (PTI), and Buffer Time Index (BTI) were calculated with respect to the time of day (TOD), day of week (DOW), holidays, and election days. This study used travel time datasets collected from three routes in Kuala Lumpur via Wi-Fi detectors during May 2018. The results showed that the Jang algorithm was found to have the best performance for two of the three routes, whereas the TransGuide algorithm was the best algorithm for one route. The parameters of the Jang algorithm and TransGuide algorithm were sensitive for different days. Thus, the Jang algorithm and TransGuide algorithm could be used after calibrating their parameters for each day. After the filtration, TTR measures were calculated. The analysis of TTR measures showed that on weekdays and weekends, the three routes suffered from high variability in travel time. On election days and holidays, the road network operates near to free-flow condition for most of the time with low variability in travel time. The findings and contribution of this research are beneficial for transportation companies and authorities that depend on MAC addresses to collect travel time data in Malaysia and ASEAN countries. Furthermore, this research introduced the concept of TTR, demonstrating its importance to Malaysian traffic researchers. Accordingly, Malaysian transportation authorities need to adopt TTR measures in their studies, reports, and guidelines to maintain reliable travel time
New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams
No full textMaximum power point tracking (MPPT) is one of the crucial components to ensure the PV system operates optimally. The bypass diodes are added across series-connected PV modules to avoid the hotspot phenomenon on the surface of the solar cells, which resulted in the multiple peaks on the power-voltage curve during partial shading conditions (PSCs). The conventional MPPT algorithms are unable to track the global maximum power point (GMPP) for all the complex PSCs and are often stuck at local maximum power point (LMPP). To deal with PSCs, controller-based and circuit-based solutions have been provided in the literature. In this work, different areas have been identified, considering both approaches, on which further research has been carried out.
In terms of controller-based, in this work, a new global maximum power point tracking (GMPPT) algorithm based on a modified butterfly optimization algorithm (MBOA) has been proposed. The proposed method differentiates between different PSCs, uniform shading conditions (USCs), solar intensity, and load variation conditions with fast convergence speed (CS). Only one dynamic variable is used as a tuning parameter reducing the complexity of the algorithm. The search space skipping method has been proposed to improve the CS. The proposed method is hybridized with a constant impedance method to improve the system's response time for fast varying load variations. The proposed method has been validated experimentally on SEPIC converter topology with a sampling time of 0.05 s. The experimental validation proved the average tracking time for different shading patterns is less than 1 s with a steady-state efficiency of 99.74% on average. The CS for USCs is improved by 40.35%. The response to load variation is also improved by 86.15% and becomes eligible for fast varying load variations. Lastly, the comparison table based on the MPPT rating has been presented to determine the effectiveness of the proposed method among other popular metaheuristic approaches used for GMPPT. Despite the effective proposed GMPPT algorithm, the PSCs reduce the maximum power extraction capability of the PV system heavily due to the activation of bypass diodes. To enhance the energy yield during PSCs, in this work, a hybridized switched inductor and switched capacitor converter (SCC-SIC) based voltage equalizer (VE) topology has also been proposed to prevent the multiple peaks during PSCs and increase the energy yield. MPPT controller with PSC detection, which uses only one voltage and one current sensor, is proposed so that the VE can only operate when the MPPT controller senses the PSC to avoid the undesired loss of MOSFET and diode due to switching and conduction. The performance evaluation determined the efficacy of the proposed system with the other state-of-the-art modular PV equalizers for ten modules in series with the reduction in switch count. The experimental results showed an increase in energy yield of 30.42% on average. In addition, the proposed controller tracks the MPP for USCs at 0.10 s while for PSCs at 0.692 s with an MPPT efficiency of 99.67% on average.
Lastly, the MBOA-MPPT controller for GMPPT and the proposed controller for VE have been compared under the same test conditions. It has been observed that the proposed controller for VE topology enhanced the energy yield by 30.03% and tracking time less than 1 s with less oscillation of power during the tracking state. Still, the cost of the system is higher in comparison with the conventional system for GMPPT
Production of glycerol carbonate from industrial grade crude glycerol via microwave-assisted transesterification / Teng Wai Keng
No full textThis research aims to produce glycerol carbonate (GC) from industrial-grade crude glycerol originating from a biodiesel plant via microwave-assisted transesterification (MAT). Aspects including a feasibility study of transforming industrial-grade crude glycerol into GC via MAT, the study of the effect of impurities in the crude glycerol, process optimization, and kinetic study were investigated. Three types of glycerol, the pure form, crude glycerol at 70% and 86%, were transesterified with dimethyl carbonate
(DMC) using CaO as a catalyst. A comparison study was made between conventional transesterification and MAT. The research found that crude glycerol of 70% purity produced higher GC yield in both conventional and MAT processes with the latter showing better energy efficiency. The highest GC yield of 93.4% was obtained from glycerol with a purity of 70% under MAT with 1 wt.% of CaO, 2:1 molar ratio of DMC/glycerol at 65 °C and 5 min reaction time. The yield of GC was observed to increase with temperature, time, and molar ratio but independent from the catalyst loading. The impact of single and multiple impurities in crude glycerol was investigated by adding impurities to pure glycerol. Methanol, sodium methylate, and soap were found to give a positive effect whereas water and fatty acid inhibited GC synthesis. The addition of impurities of 20 wt.% methanol and 1 wt.% sodium methylate increased GC yield by four times, from 7.62% to 30.56%. At its optimized reaction conditions, the GC yield can be further increased to 80.43% through the addition of 5 wt.% sodium methylate and 0.01 wt.% of soap. This shows the impurities which might otherwise be undesirable for the transesterification process under normal circumstances have unusually demonstrated positive effects on the performance of The MAT process was optimized to yield 99.5% GC from 70% purity crude glycerol at 65 °C with 1 wt.% catalyst loading in 5 min at a DMC/glycerol molar ratio of 2.5. As a comparison, MAT of pure glycerol was also carried out and the findings showed that merely 66.6% GC yield can be achieved at its longer reaction time of 60 min and higher catalyst loading of 6 wt.%. The reaction time is the most significant factor for MAT of both types of glycerol. MAT reaction fitted well to an irreversible second-order kinetic model. The values of rate constants between 45 °C to 65 °C were in the range of 2.34 - 2.59 x 10-2 L/mol.min, which is one order of magnitude higher than that of conventional heating. Furthermore, a relatively lower activation energy of 4.53 kJ/mol is needed for GC production via MAT of crude glycerol in comparison to the conventional transesterification process. The research demonstrated the feasibility of direct utilization of industrial-grade crude glycerol from biodiesel plants to produce GC. The microwaveassisted process effectively transformed crude glycerol into value-added GC, in addition to its cost-effectiveness in using biodiesel waste as raw material. Hence, compared to other reported transformation techniques, MAT of crude glycerol was shown to be an economically viable, sustainable, robust, and energy-efficient synthesis process of GC
The reality of Awqaf and its investment in the Republic of Gambia: An applied jurisprudence study / Karamo Ibrahima Saidykhan
No full textThe legitimate aim of the institution of waqf in Islam is for the religious and social interest. Failing which in performing its duty a waqf will not be able to achieve this aim. This is the case in the Republic of the Gambia in which the waqf face many obstacles and problems due to many factors such as lack of real estate registration and documentation of endowment properties, leasing for less than the customary rate, no proper lease contract, late payment of lease, absence of the official administrative staff and lack of religious understanding among the people in dealing with waqf property. These have led the waqf in The Republic of the Gambia going in to ruin and unproductive .
This study aimed to get acquainted closely with these problems and to propose solutions from fiqh point of view. In this study, the researcher took (a) the inductive method by referring to the literatures on waqf to get acquainted with the law of waqf, (b) the historical approach to trace back the history of waqf in Gambia, and (c) the descriptive analytical approach to analyze the problems and issues at hand and to come out with the solutions. The study found that waqfs in the Republic of The Gambia have not been optimally exploited, vulnerable to mismanagement and corrupted, the limited mode of generating incomes to renting and below market rate, adhering to the clasiccal fiqh with the absence of a supervisory role and the mechanisms of investment. The researcher suggest in this study of honouring the sanctity of waqf and setting up investment and administrative control mechanisms, taking into account the fiqh point of views, so as to capable of overcoming problems
A translation model using hybrid approaches to improve Arabizi dialect sentiment analysis in business tweet’s / Mohamed Elhag Mohamed Abo
No full textThe most popular electronic communication mediums are microblogs and social media platforms. For social media platforms such as Twitter, important papers representing users' thoughts and viewpoints are produced and traded on a daily basis. Recently, sentiment analysis has brought great opportunities to businesses and services’ providers who are interested in tracking and monitoring reputations of their brands and to policymakers whose supports are needed for assessment for public opinions about their brands, services, and/or policy issues. Various sentiment analysis tools for Twitter and other similar microblogging networks have lately been developed. Most of these models rely mainly on the presence of effect words or syntactic structures that explicitly and unambiguously reflect sentiment. However, these models are weak; they do not work accurately for the Arabizi text, emojis, ambiguity of Arabic, and they ignore emotional words that are less than three letters, when detecting their sentiments in a text. This research investigates the Arabic dialect text in sentiment analysis of microblogs, which is aimed at addressing the problem in the service domains such as hotels, restaurants, and transportation. Twitter data is used as a study dataset of microblogging platforms to investigate whether capturing the sentiment of words concerning Arabizi, emojis, less than three letters of the emotional word has any effect, and that disambiguating leads to more accurate sentiment analysis models on Twitter. A hybrid translation model is proposed to address these issues for extracting, detecting, annotating, and translating language types of sentence semantics for sentiment analysis.
The experiments were conducted in two stages. The first stage was about language detection, Arabizi, and emoji translation, by evaluating their impacts on popular sentiment analysis tasks on Twitter. The second stage was about ambiguity-sensitive sentiment of a dictionary adaptation. Three sentiment dictionaries and up to five Twitter datasets of various features were evaluated under each sentiment analysis task, and comparisons to numerous state-of-the-art sentiment analysis were made, using machine- learning classifiers, which were extensively discussed in the literature. The findings of this body of work demonstrate the importance of using the detection of language and translated Arabizi, emoji, and emotional words that are less than three letters of sentiment analysis on business Twitter. The proposed model focuses on the Saudi’s Arabic dialect for sentiment analysis at sentence levels. It surpasses other Arabic dialect and modern standard Arabic models in most datasets. However, the evaluation showed that the results of proposed framework has better result than the five-dataset results that were applied in the same environment. Furthermore, the Naïve Bayes performed the best result, with 94%, 94%, 89%, and 91% for accuracy, precision, recall, and f-measure, respectively
The impact of error-tolerance using customized DIJKSTRA on large scale parallel crowd simulations / Luuk Sterke
No full textThis Dissertation aims at exploring and quantifying the errors that occur in parallel crowd
simulation when not implementing measures to prevent these errors. Consequently, the
simulation should run faster, as less code needs to be executed. A fully functional crowd
simulator has been developed and various features for measuring accuracy and performance
have been implemented. Part of the research was identifying the right metrics for measuring
these quantities. It turns out that a heat map in combination with waiting times, walking
times and local flow measuring entities together create a bijection between this data and
the simulation producing it. The impact of allowing errors on the simulator’s accuracy can
be measured quite well by comparing these statistics. The performance is then measured
using different internal stopwatches keeping track of the time needed to simulate a fixed
amount of agents. From many simulation environments and settings, it becomes clear
that significant speedups can be achieved using the proposed techniques. These speedups
of up to 15% are achieved at the expense of the simulator’s accuracy, where flow and
waiting times are off by single-digit percentages. Heat maps deviate more percentage-wise
because they are more sensitive to small changes. In one case, error tolerance was not
faster and less accurate since error tolerance was not applied on the scale of all agents
but on reducing internal overhead time. Allowing errors to examine many simulations
quickly and then perform precise simulations on just the promising ones are recommended.
Whether the errors observed are large or small is not conclusive as that depends on the
simulated event and because such conclusions are outside of this dissertation’s scope
Self-organizing kernel-based convolutional echo state network for human action recognition / Lee Gin Chong
No full textThe research works on three-dimensional (3D)-skeleton-joints-based human action recognition (HAR) remains demanding. Among the approaches, Echo State Networks (ESNs) are a reservoir computing method that considers skeleton joints human actions as multivariate time series and attempts to identify and model the dynamical temporal features in 3D space. Despite the random initialization of the ESN's input and reservoir weights may reduce the computational cost, this may raise instability and variance in generalization and hence diminish reproducibility. Moreover, ESN remains a black-box algorithm. Notably, it lacks explainability consideration to understand the input-dependent reservoir dynamics, specifically while configuring the optimal hyperparameters for HAR. Besides, following the body of Convolutional Echo State Network (ConvESN) work to incorporate modeling dynamics and multiscale temporal feature in handling HAR problem, the model may be very sensitive to the selection of hyperparameters in Convolutional Neural Network (CNN). This work addresses these issues by proposing a novel approach known as Self-Organizing Convolutional Echo State Network (SO-ConvESN) for HAR. Specifically, this work proposes an unsupervised self-organizing network for learning node centroids and interconnectivity maps compatible with the deterministic initialization of ESN reservoir weights. To ensure stability and echo state property (ESP) in the self-organizing reservoir, this work further exploits the Recurrent Plots (RPs) and Recurrence Quantification Analysis (RQA) techniques for explainability and characterization of the dynamics of the self-organizing reservoir and hence tuning two critical ESN hyperparameters: input scaling