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Hybrid metaheuristics for QOS-aware service composition / Hadi Naghavipour
No full textWith the advent of Service-Oriented Architecture (SOA), services can be registered, invoked, and combined by their identical Quality of Services (QoS) attributes to create a new value-added application that fulfils user requirements. Efficient QoS-aware service composition has been a challenging task in cloud computing. This challenge becomes more formidable in emerging resource-constrained computing paradigms such as the Internet of Things and Fog. Service composition has regarded as a multi-objective combinatorial optimization problem that falls in the category of NP-hard. Historically, the proliferation of
services added to problem complexity and navigated solutions from exact (none-heuristics) approaches to near-optimal heuristics and metaheuristics. Although metaheuristics have fulfilled some expectations, the quest for finding a high-quality, near-optimal solution has led researchers to devise hybrid methods. As a result, research on service composition shifts towards the hybridization of metaheuristics. Hybrid metaheuristics have been promising efforts to transcend the boundaries of metaheuristics by leveraging the strength of complementary methods to overcome base algorithm shortcomings. This thesis core
contribution is manifold. First, a mapping study was conducted to infer a framework for hybridization strategies by analyzing 71 papers selected out of the primary pool of 756 between 2008 and 2020. Moreover, it provided a panoramic view of hybrid methods and their experiment setting in respect to the problem domain as the primary outcome of this mapping study. As a result of this mapping study, five major hybridization strategies were identified in which two-third of solutions have been based on modifying algorithm operators or integration with another metaheuristic. An absolute majority of base algorithms for this problem were nature-inspired and population-based metaheuristics extended to complementary methods in hybrid solutions. Thus, slow convergence, local entrapment and stochastic behaviour were reported as their shortcoming. This thesis advocates incorporation of set theory as mathematical tools to transcend the boundary of metaheuristics. On that basis, the second contribution of this thesis is proposing a fast fuzzy evolutionary algorithm with minimal stochastic behaviour. Furthermore, this thesis contributes to the body of knowledge by introducing a novel method called Fuzzy Rough set Genetic Algorithm (FRGA) that take on efficiency of metaheuristics while reducing search space by leveraging the data mining aspect of rough set theory. Finally, this thesis revealed a parallel hybrid metaheuristic architecture and monitoring mechanism to provide immunity against premature convergence when the composition is performed in a subset of search space as the output of rough set-based heuristics. The experiment was conducted for 25 datasets generated incrementally from the real-world QWS dataset, where results were consistent and statistically significant. Inclusive of this writing, limitations, challenges and future direction are discussed in respect to this study finding, followed by conclusions
Speech emotion recognition using bidirectional echo state network with random projection / Hemin Fatih Ibrahim
No full textSpeech is an effective, quick, and important way of communicating and exchanging
complex information between humans. Emotions have always been a part of the normal
human conversation which makes the speech more attractive and more effective. Because
of this major role of both speech and emotion in human life, many researchers are inspired
by studying Speech Emotion Recognition (SER) and considered as a key effort in Human-
Computer Interaction (HCI). The accurate SER system can have an effective role in several
services, such as call center services, the in-car board, educational systems, and children
in care. The major challenges in SER are, to catch and extract the most relevant emotion
features from the raw speech signal with distinctive information and a robust and cheap
computational model. The main focus of this thesis is to design a model for emotion
recognition from speech signals, which still has plenty of challenges in the area, and adopt
the most relevant features. This thesis tackles these challenges by providing a multivariate
time series classification based on reservoir computing for detecting emotions from speech.
Due to the time series and sparse nature of emotion in speech, the multivariate time series
handcrafted feature has been adopted as input data. The bidirectional Echo State Network
(ESN) which is a type of reservoir computing and as a special case of the Recurrent Neural
Network (RNN) has been adopted to avoid model complexity because of its untrained and
sparse nature when mapping the features into a higher dimensional space. Although the
ESN has advantages, some problems still need to be solved, such as the instability with
initializing fixed weights randomly and selecting the optimal value for hyperparameters
which have a big impact on the ESN performance. Therefore, to address these issues in ESN, the bidirectional ESN with twin reservoirs is adopted to catch additional independent
information from each direction. Additionally, the late fusion of the same direction
from twin reservoirs leads to having a more informative representation and enhances the
memorization capability for SER applications. The truncated normal distribution approach
is exploited to initialize random connection weights for the input weight, in addition to
optimizing the hyperparameters in the ESN model by Bayesian optimization and Population
Based Training (PBT) approaches. Moreover, the high dimensional sparse output from
a reservoir makes feature representation suffer from the curse of dimensionality, for that
reason the Sparse Random Projection (SRP) is adopted for dimensionality reduction since
it offers significant computational advantages because it does not need any training and
removes redundancies with minimal loss of information. Experimental results of this
thesis with a speaker-independent strategy achieved 89.21%, 70.48%, 76.76%, and 46.34%
unweighted average recalls on the Emo-DB, SAVEE, RAVDESS, and FAU Aibo datasets
respectively. The results show the superior performance of our proposed model over a set
of other methods on four publicly available emotional speech datasets
The effectiveness of problem-based serious games on learning and learning motivation in the context of 3D computer graphics / Meisam Moradi
No full textThis study was an attempt to realize the possible effects of a problem-based serious game, named 'Immersivio', on learning 3D computer graphics in order to mitigate the challenges undergraduate students have for learning 3D computer graphics in Malaysia. In addition, this study aimed at understanding the extent to which a problem-based SG can affect undergraduate students' learning motivation. Indeed, the literature shows that 3D computer graphic courses are replete with abstract notions and algorithmic concepts which make learning of it difficult. To this end, the researcher designed a quantitative study with a between subject design and aimed at implementing a treatment course using the problem-based SG. Prior to that, a problem-based SG was designed by considering principles of problem-based learning (i.e., higher order thinking, collaborative learning, and cognitive thinking) and serious games (playing for learning). The problem-based model presented by Hmelo-Silver (2004) was used as the basis of the game design. A non-random sampling procedure (purposive sampling) was used in this quasi-experimental study and the participants formed 2 groups, i.e., the experimental group (n= 24) and the control group (n= 26). The independent samples t-test results indicated that the experimental group's posttest scores in a 3D computer graphics course were significantly affected as a result of using Immersivio. In addition, MANOVA test results indicated that the experimental group participants who had experienced Immersivio were more motivated to learn 3D computer graphics in terms of extrinsic motivation, intrinsic motivation, interest, attainment, cost, identification with academics, self-efficacy, and instrumentality. As the problem-based SG designed used in this study proved to be effective, its main constituents were extracted to design a framework of PBL-SG in learning 3D computer graphics. The main constituents considered were time, distance, number of used tools, and number of attempts. This study and the game design in this study can have pedagogical and practical implications for 3D computer graphics lecturers and those who are interested in designing effective problem-based SGs
Prediction of high cost performance metrics in information retrieval evaluation / Muwanei Sinyinda
No full textThere has been extensive use of the test collections to evaluate the effectiveness of
information retrieval systems in laboratory-based evaluation experimentation. A typical
test collection comprises a corpus of documents, topics, and relevance judgments generated
by human assessors. A long-standing problem has been how to reduce the cost of
performing information retrieval evaluations. Therefore, in the last few decades, several
methods have been proposed to reduce the evaluation costs. Recent research has proposed to
reduce the evaluation costs by predicting performance metrics at the high evaluation depths
of documents using other performance metrics computed at the low evaluation depths. In
the above-mentioned research, the performance metrics computed or predicted at the high
evaluation depths of documents were also referred to as high-cost performance metrics.
By predicting the high-cost performance metrics, the usage of the relevance judgments is
restricted only to the computation of the performance metrics at the low evaluation depths.
However, this recent research reported low predictions of the normalized-cumulative
discounted gain and precision high-cost performance metrics while using the low-cost
performance metrics computed at the evaluation depths of up to 30 documents. Therefore,
this thesis makes several contributions and focuses on the predictions of the high- cost
normalized-cumulative discounted gain and precision performance metrics while using
other performance metrics computed at the low evaluation depths of up to 30 documents.
First, in every test collection, there are topics with varying levels of difficulty. Therefore,
this research has investigated the effect of the difficulty of topics on the predictions of
the high-cost performance metrics and has shown that more difficult topics have higher predictions of the high-cost performance metrics. Therefore, this research suggests that this
identified trend could be exploited in the methods for predicting the high-cost performance
metrics. Also, what was clear was the evidence of the presence of extreme scores of the
performance metrics that this research suggests should be resolved for improved predictions
of the high-cost performance metrics.
The second contribution concerns the exploration of the predictability of the performance
metrics in information retrieval evaluation. In recent research, machine learning models
were trained using performance metrics computed from a set of test collections, while
predictions were made on performance metrics from completely different sets of test collections.
Therefore, this research also explored how predictable the high-cost performance
metrics are that relate to particular test collections given that the machine learning models
were trained using performance metrics computed from other test collections. Hence, this
research has shown that exists a data set shift in the topic scores of performance metrics of
different test collections and therefore suggests addressing this data set shift for predictions
of the high-cost performance metrics.
The last contribution is the proposal of two methods that predict the normalized-cumulative
discounted gain and precision high-cost performance metrics using the low-cost performance
metrics computed at the evaluation depths of up to 30 documents. This research
has shown that the proposed methods provide better predictions than existing research
Molecular characterisation and functional analyses of Musa acuminata Pathogenesis-related 10 (MaPR10) gene / Arullthevan Rajendram
No full textPlant immunity to pathogen infections is a dynamic response that involves multiple organelles and defence signalling systems such as induced systemic resistance (ISR) and systemic acquired resistance (SAR). The latter is mediated by pathogenesis-related proteins (PR), a common type of plant protein known for its diverse role in plant innate immunity. In this study, two novel PR protein variants were isolated from two Musa acuminata cultivars namely Berangan and Grand Naine (ITC 1256). Sequence characterisation study carried out on 69 genomic and transcript clones of M. acuminata PR (MaPR) gene revealed that the PR1-like gene that was reported to involve in Meloidogyne incognita - Grand Naine (ITC 1256) interaction in Al-Idrus et al. (2017) actually belongs to PR10 gene group despite showing 81–95 % similarity with M. acuminata PR1 sequences in the GenBank and Banana Genome Hub database. This discrepancy was further discussed and linked to miss-curation of the previous sequence data entered in the two sequence databases, hence the isolated clones were denoted as MaPR10 instead. Phylogenetic analysis revealed that the deduced amino acid sequences from 69 genomic and transcript clones of MaPR10 clustered into four distinct groups, while 44 genomic clones clustered into three distinct groups. Southern blot result corroborated that of found in phylogenetic analysis confirming that MaPR10 gene was present in at least three copies in both Berangan and Grand Naine genomes studied. Two sequence variants i.e., MaPR10-BeB5 and MaPR10-GNA5, were chosen for a subcellular localisation study in onion epidermal cells. Meeting the expectation of the in silico prediction, this study confirmed that the two protein variants were localised intracellularly. In addition, functional analyses confirmed that both protein variants function as β-1,3-glucanases and ribonucleases. While the former is novel, the latter is a common function of the members of PR10 gene family in plants. When tested on three economically important fungal species Aspergillus fumigatus, Aspergillus niger, and Fusarium oxysporum f. sp. cubense: Tropical Race 4, both protein variants only significantly (p < 0.05) inhibited the growth of A. fumigatus. This study reports MaPR10 protein variants as the first plant protein to exhibit antagonistic effect towards A. fumigatus and the first member of PR10 protein family to exhibit β-1,3-glucanase function
Evaluation of selected tropical marine microalgal cultures for use in biophotovoltaic platforms / Tay Hui Yee Zoe
No full textMicroalgal-Biophotovoltaic (BPV) research is an emerging discipline in the field of renewable solar energy technology. When exposed to light, microalgae in BPV platforms will use their photosynthetic apparatus to carry out a water splitting reaction which forms oxygen, protons and electrons. The electrons will then be harvested through the anode of a BPV platform to generate electricity. At the same time, carbon dioxide is also consumed by the microalgae which presents the BPV platform as a means to deliver carbon-neutral or carbon-negative energy. In this study, the bioelectrical power generation potential of four tropical marine microalgal strains were investigated through the use of BPV platforms since no known study has investigated on this particular group of marine microalgae to date. Using controlled laboratory experiments, the bioelectrical power outputs of the chlorophytes Parachlorella UMACC 245 and Chlorella UMACC 258, diatom Halamphora subtropica UMACC 370, and cyanobacterium Synechococcus UMACC 371 were determined. Chlorella UMACC 258 was able to produce the highest power density (0.108 mW m-2), followed by Halamphora subtropica UMACC 370 (0.090 mW m-2), Synechococcus UMACC 371 (0.065 mW m-2) and Parachlorella UMACC 245 (0.017 mW m-2). The chlorophyll-a content was examined to have a linear positive relationship with the power density (p < 0.05). Using the Pulse-Amplitude Modulation (PAM) fluorometer, the photosynthetic performance (maximum quantum efficiency, Fv/Fm) of the algal cultures was studied by exposure to a range of actinic irradiances in order to determine their cell physiological stress from photosynthesis. Other parameters of the photosynthetic performance including the alpha (α), maximum relative electron transport rate (rETRmax), photo-adaptive index (Ek) and non-photochemical quenching (NPQ) were also investigated. The Fv/Fm values of all strains, with the exception of Synechococcus UMACC 371, were within a relatively healthy range of 0.37 to 0.50 on the day when power output was greatest before declining by the end of the experiment likely due to nutrient depletion. Synechococcus UMACC 371 produced Fv/Fm values less than 0.30 and this was possibly caused by the presence of background fluorescence from phycobilisomes or phycobiliproteins. The NPQ, which measures the ability of the microalgae to dissipate excess energy as heat in order to induce photoprotection, was strongest in Halamphora subtropica UMACC 370 and weakest in Synechococcus UMACC 371. NPQ activity in Halamphora subtropica UMACC 370 was mediated by its light-harvesting stress-related complex (LHSCR) proteins and extensive de-epoxidation of carotenoids, whereas Synechococcus UMACC 371 employed the Orange Carotenoid Protein (OCP) associated with phycobilisomes. Electrochemical studies via cyclic voltammetry suggest the presence of electro-active proteins on the cellular surface of strains on the carbon anode of the BPV platform, while morphological studies via FESEM imaging verifies the biocompatibility of the biofilms on the carbon anode
Petrology and geochemistry of host rock and gold mineralization at southern part of Ulu Sokor gold deposit, Kelantan, Malaysia / Ahmad Fauzan Yusoff
No full textThe petrology and geochemistry of host rock and gold mineralization at southern part of
Ulu Sokor gold deposit, Kelantan, Malaysia is poorly understood. This study area is
located at the Central Belt of Peninsular Malaysia and hosted as an orogenic gold
deposit from previous study. Particular deposits in this study area are New Found and
New Discovery loads which located at the southern part of the whole Ulu Sokor gold
deposit boundary. Two types of host rocks were identified such as phyllite as a
metasedimentary rock unit and rhyolite as a volcanic rock unit. Based on the
petrological and geochemical data presented, phyllite have been derived from shale and
classified as pelitic and felsic source. It was undergone little heavy mineral fractionation
and sediment recycling since these samples slightly enriched with Light Rare Earth
Elements (LREEs). Some of these samples studied have elevated K2O content that
indicate K-metasomatism, which reflects secondary addition of potassium. According to
the Chemical Index Alteration (CIA) and Index Compositional Variability (ICV)
calculation, it shows that the phyllite are intensely weathered with matured sources. The
classifications of depositional conditions are plotted as continental island arc and
oceanic island arc. Continental island arc and oceanic island arc are dominated by the
development of the subduction process, which synchronic with the tectonic evolution of
the Bentong-Raub suture zone. The other type of host rock is rhyolite, which is a typical
type of rock that exists in the volcanic arc environment based on the relationship
between the collision of Sibumasu and East Malaya blocks. The geochemical features
including the enrichment in Large Ion Lithophile Elements (LILEs) relative to High
Field Strength Elements (HFSEs), and the restricted calc-alkaline to shoshonitic rocks are indicative of volcanic arc type. The trace and major geochemical elements of
volcanic rocks support the evidence of volcanic arc setting. Gold mineralization is
primarily hosted in structurally controlled quartz vein, which occurs in various degrees
of ductile-brittle environment. Based on the field relationships, ore microscopy, and
geochemical data analysis, the main gold mineralization type in the southern part of Ulu
Sokor gold deposit is gold (Au)-bismuth (Bi). In terms of mineral exploration and gold
prospecting, the significant enrichment in this study area is bismuth. However, some
other metals can also be considered as a significant value in this area such as Pb, As, Cu
and Zn. From the bulk ore chemistry, the geometric mean values of Au and Bi are
1.8972 ppm (n=23) and 96.3 ppm (n=22) respectively
Synthesis, characterization and biological activities of photocorms derived from cyclopentadienyl iron dimer with organosulfur and organoselenium ligands / Gan Chun Hau
No full textCarbon monoxide releasing molecule (CORM) are well known for various biological
activities but the efficacy and mode of activities are not fully understood. The objective
of this research is to synthesize and evaluate the biological of diiron dimer photoCORMs.
In this research, the conventional Schlenk techniques under an inert atmosphere of argon
is used to synthesize and isolate the products. The reactions of [CpFe(CO)2]2 (1) with 2
moles equivalents of R2E2 (R= C6H11, C4H3S, CH2C6H5; E= S, Se) have yielded dinuclear
products of [CpFe(CO)(μ-L)]2 (L= C6H11S (2), C4H3S2 (3) and CH2C6H5Se (4)),
respectively. An additional trinuclear compound, C24H22O2Se2Fe3 (5) was isolated only
from the reaction with dibenzyl diselenide. It was postulated that the formation of 2, 3, 4
and 5 proceeded via the radical pathway which involved the formation of CpFe(CO)2 •
radical and S-S bond or Se-Se bond cleavages of the ligands. All the products have been
fully characterized by FT-IR, 1H and 13C NMR, CHN elemental analysis, GCMS and
structurally elucidated by single crystal X-ray diffraction. Since 5 was a minor product,
it was not involved in any further study. The stability of 2-4 both under dark and UV
conditions were investigated by monitoring the changes in their respective UV-Vis
spectra in phosphate buffered saline (PBS) solution. Their potential application as
photoCORMs were also evaluated by standard myoglobin assay. 3 showed the shortest
half-life and highest equivalent of CO-released. The anticancer studies of 2-4 were
evaluated in-vitro on breast cancer cell lines (MCF-7, MDA-MB-231 and MDA-MB-468)
and the cytotoxicity of 3 had increased approximately 4 times against MDA-MB-468 cell
line upon UV irradiation, which was 11.5 ± 2.7 μM. All complexes exhibited cytotoxic effect on specific sub-types of breast cancer cells. Antimalarial activities of 2-4 had also
been studied and reported in this work. Unfortunately, these complexes did not display
any significant effect on the Plasmodium falciparum 3D7 strains. The physicochemical,
pharmacokinetics and drug like parameters of 2-4 were determined by using SwissADME
tool
Environmentally friendly epoxy and alkyd coatings derived from natural rubber / Yong Ming Yee
No full textEnvironmentally friendly coatings are gaining more attention following the growing concern on the threat of environmental pollutions, as well as the depleting fossil resources that have been exploited to produce surface coating resins and additives for the coating industry. One of the approaches to produce environmentally friendly products is to reduce the dependency on petroleum-derived resources in the coating production. In this work, epoxidized natural rubber was utilised to produce epoxy coatings and alkyd coatings. The epoxidized natural rubber was subjected to UV treatment to reduce molecular weight and subsequently improve its solubility in a wide range of solvents. UV-degraded epoxidized natural rubber (UV-ENR25) was characterized with spectroscopies (FTIR and NMR) and gel permeation chromatography, GPC to confirm the reduction in molecular weight, while retaining its epoxide content. Rubber-based epoxy coatings were produced using two different types of hardeners. The first hardener was pentaerythritol tetra (3-mercaptopropionate) which is a common crosslinking agent used in epoxy coating. The second hardener utilised was naturally-sourced tannic acid. The film properties and thermal stability of both epoxy coatings were investigated using series of test methods comprising of physical, chemical, and thermal analyses. Both coatings, UV-ENR25/PETMP and UV-ENR25/tannic acid showed satisfactory coating properties, comparable to some of the reported petroleum derived epoxy coatings. One of the highlights is the focus on the biodegradability of UV-ENR25/tannic acid coating. Owing to the high natural content in UV-ENR25/tannic acid coatings, the coatings exhibited improved extent of biodegradation compared to the commercially available petroleum-derived epoxy coatings. Liquid epoxidized natural rubber was also utilized in alkyd resin synthesis. It served as a polyol in the synthesis and the effect of incorporating the rubber in alkyd synthesis was thoroughly evaluated. The liquid epoxidized rubber was introduced into the alkyd cook during the polyesterification step, for it to serve as polyol and react with polycarboxylic acid. The film properties and thermal stability of the resultant alkyd coatings were investigated using series of standard test methods, as well as chemical and thermal analyses. The results obtained suggest that the properties of alkyd coatings derived using rubber in the formulation was comparable to the control alkyd which was produced purely from the conventional polyol such as glycerol. The integration of rubber into the synthesis offered equivalent in majority and even improvement in some of the coating properties such as film hardness and film adhesion. In summary, natural rubber derivatives could be used as a sustainable raw material in the synthesis of surface coating resin, and the properties of the coatings could match those produced from petrochemical derivatives
Spatio-temporal analysis of land environment changes in Klang, Malaysia / Cai Changqing
No full textLand environment changes can truly reflect the regional ecological environment and an
important indicator for judging the regional ecological environment. Under the combined
influence of natural factors and human activities, the land environment in Klang has
undergone major changes. The analysis of land environment changes and their driving
forces in the study area has a positive impact on optimizing the urban development space,
enhancing the overall functions of the area and the carrying capacity of resources and the
environment. This research takes Klang as the study area, because Klang is a coastal city
and there are a lot of environmental dimensions to be observed. Studding from two
dimensions of shoreline and land use, from the edge to the interior, to study the land
environment of Klang as a whole. This research includes: shoreline change analysis, land
use/cover change analysis, change driving force analysis, and policy recommendations
are made based on the analysis results. Over the past 31 years, the total length of the
shoreline has increased. The artificial shoreline has increased from 21.13km to 39.99km,
and the proportion has increased from 13.52% to 24.71%. The proportion of biological
shorelines dropped from 81.65% to 70.83%. The impact of human activities on the
changes of shorelines is becoming more and more significant. Under the influence of
development, the shoreline expands towards the sea as a whole. In terms of land use,
agricultural land still dominates, but from 1990 to 2021, a large amount of agricultural
land was converted into construction land. Although wetlands are declining, several
wetland islands in the Klang area remain undeveloped in 31 years. Reserve land is
sufficient, and the overall land environment is relatively stable