13474 research outputs found
Sort by
A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah
No full textUnderwater wireless sensor networks (UWSNs), which benefit ocean surveillance applications, marine monitoring and underwater target detection, have advanced substantially in recent years. However, existing deployment solutions do not satisfy the deployment of mobile underwater sensor nodes as a stochastic system. Internal and external environmental problems concern maximum coverage in the deployment region while minimising energy consumption. To fill this gap, this research proposes and implements a multi-objective optimisation solution to balance conflicts concerning node deployment objectives. First, this research analyses the existing mobile underwater node deployment algorithms to identify the significant problems in existing solutions. Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. Based on that analysis, this research suggests a hybrid algorithm: the Multi-Objective Optimisation Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy). The method adapts the original Non-Dominated Sorting Genetic Algorithm II (NSGA-II) by introducing a hybridisation of adaptive multi-parent crossover genetic algorithm and fuzzy dominance-based decomposition techniques. The algorithm introduces the fuzzy Pareto dominance concept to compare two solutions and uses the scalar decomposition method when one solution cannot dominate the other in terms of the fuzzy dominance level. The solution also proposes adaptive multi-parent crossover (AMP) to balance exploration and exploitation with new offspring, changing the number of parents involved in the crossover based on the execution of the new generation. The solution is further improved by introducing prospect theory to guarantee convergence through risk evaluation. The results obtained are then analysed to assess the proposed solution’s performance in obtaining each deployment objective’s optimal value. Finally, the proposed algorithm’s effectiveness regarding node coverage, energy consumption, Pareto-optimal value, and algorithm execution time is validated using three Pareto-optimal metrics: including inverted generation distance (IGD), hypervolume, and diversity. Furthermore, this research utilises five commonly used two-objective ZDT test instances as benchmark tests, namely ZDT-1, ZDT-2, ZDT-3, ZDT-4, and ZDT-6. These tests use specific problem characteristics to impose the underlying proposed solution as well as three other systems. Pareto-optimal values obtained indicate that the proposed solution has almost complete coverage involving the actual Pareto front. Furthermore, all analysis and evaluation attributes indicate that the MOGA-AMPazy deployment algorithm can handle the multi-objective underwater sensor deployment problem better than other solutions. Thus, MOGA-AMPazy provides an efficient and comprehensive deployment solution for mobile sensor nodes in UWSNs. This study makes several noteworthy contributions to the body of knowledge concerning UWSNs, and it provides an excellent multi-objective representation to decision-makers or mission planners to monitor the region of interest (RoI)
Time series analysis and improved deep learning model for electricity price forecasting / Md Rashed Iqbal
No full textAccurate electricity price forecasting (EPF) is important for the purpose of bidding strategies and minimizing the risk for market participants in the competitive electricity market. However, accurate prediction is very challenging due to complex nonlinearity in electricity prices. Therefore, forecasting accuracy highly depends on the nature of time series. An improved deep-learning framework is proposed for short and mid-term EPF which consists of four modules: time-series data pre-processing, the deep learning-based prediction methodology, spike prediction module and reliability checking of prediction model. The feature pre-processing module is based on linear trend of the correlated features of electricity price series and test time series for unit root by augmented dickey fuller (ADF). In addition, the time series data is transformed with box-cox transformation method for better training process. Firstly, the prediction module combines linear scaled hyperbolic tangent (LISHT) with the long short-term memory (LSTM) and compared with bidirectional long short-term memory (BiLSTM) which is a recurrent neural network (RNN) to adjust complex nonlinear features and improve the precision of day ahead prediction. The residual autocorrelation determined in the reliability check section. Secondly, an optimized gated recurrent unit (GRU) which incorporates bagged tree ensemble (BTE) is developed in the recurrent neural network (RNN) architecture for the mid-term EPF. A tanh layer is employed to optimize the hyperparameters of the heterogeneous GRU with the aim to improve the model's performance, error reduction and predict the spikes. This study is performed based on the Australian price, load and renewable energy supply data from five major economical states New South Wales (NSW), Queensland (QLD), South Australia (SA), Tasmania (TAS), Victoria (VIC). The experimental results obtained show that the proposed EPF framework performed better compared to previous techniques
The use of swear words among university students / Jayanthi Sinnathamby
No full textSwearing has always been regarded as an expression of negativity. Swear words can be defined as language used offensively and can be sexist, racist, homophobic and masochistic. This study aims to examine the types of swear words used by university students and how they use these words to accustom themselves in a new environment. A mixed method was employed in this study using online questionnaires and semi-structured interviews. Research data were limited to English and Malay languages, with swear words listed out by university students relating to certain contexts. Findings show that swear words used by university students fit into epithets, profanities, vulgarities, and obscenities as outlined in Battistella’s (2007) Model of Taboo words Categorisation. 53.5% of respondents state that they are not affected by this usage either by others or themselves. Respondents also believe that using euphemisms, gestures, grawlixes and emojis during social discourse is not swearing. 99% of respondents were conversant in English and this paved the way to the majority of them using an equal number of English and Malay swear words. They are clear about the context and circumstances in which to use swear words. These findings indicate that usage of swear words among students has become normalised and a part of everyday life and provide a mode to accustom themselves in a new environment
Factors influencing perceived retirement saving adequacy among public university employees in Saudi Arabia / Ahmad Saleh M Ghadwan
No full textThe ultimate aim of this research is to investigate the measurable variables that could influence employees in their perceived retirement saving adequacy. These factors comprise the employee’s capacity (basic and advanced financial literacy, financial selfefficacy), psychological (retirement goal clarity and financial risk tolerance), and economic (assets ownership and debt) factors. To carry out this task, this study employs the Capability, Willingness, and Opportunity (CWO) Model to comprehend the factors that influence retirement saving and planning behavior, which was tested on public university employees in Saudi Arabia. The study also examines the moderating effects of culture and government policies affecting these theoretical factors given the unique Arabs culture as well as the Saudi Arabia 2030 Strategic Vision. The analysis is based on data collected via questionnaires involving 558 staff working at 29 Saudi public universities. The study employs Structural Equation Modelling-Smart-PLS (SEM-PLS) methodology to analyze the relationships among the variables. This methodology is chosen as it is the only quantitative method that can simultaneously process a complex relationship between latent variables, enabling this research to analyze more than one layer of relationships between variables under study. The research contributed significantly to the body of knowledge in relation to retirement saving adequacy by examining two theoretical models: the Life Cycle Hypothesis (LCH) and Intentional Change Theory (ICT), on individuals’ awareness of PRSA practices. LCH provides the conceptual framework to explain, analyze, and predict the interaction and relationships between planning and saving on one side and investing for retirement on the other side among individuals. Meanwhile, ICT explains how employees intentionally start changing their consumption and saving behavior before reaching retirement age. An examination through the LCH and ICT lens gives a better understanding of financial planning processes and related retirement behaviors. The study found that, directly and indirectly, capacity, psychological, and external variables influence perceived retirement saving adequacy behavior. In the Saudi context, this thesis has found that only basic financial literacy, financial self-efficacy, retirement goal clarity, and asset ownership (other asset ownership) influenced perceived retirement saving adequacy among the sample respondents. This result suggests that several variables have assisted the respondents in planning and saving for their future and saving money, particularly for their retirement. Surprisingly, this thesis has found that asset ownership (homeownership) negatively influenced perceived retirement saving adequacy. The culture was found to affect the relationship between retirement goal clarity, asset ownership (homeownership), and perceived retirement saving adequacy. Meanwhile, government policy has affected the relationship between retirement goal clarity and debt (credit card loans). The diverse effects of each variable indicate the multi-throng responsibility of government agencies or policies like the Public Pension Agency (PPA) or Vision 2030 in developing a pension system that is deemed to be in accordance with the best interests of retirees
Media representations of foreign domestic helpers in Malaysia / Sheren Khalid Abdul Razzaq
No full textThis study explores the media representation of foreign domestic helpers working in Malaysia. It aims to provide an insight on the strategies employed by the media to portray the foreign domestic helpers as a social group. So, the study compares the representations offered by the most prominent Malaysian online news agencies and the most prominent online news agencies in Indonesia and the Philippines between 2009-2018. These years witnessed frequent changes in policies that involve temporarily withholding the domestic helpers from working in Malaysia. This unstable situation is believed to have influenced media representation. The analysis was carried out using three theoretical frameworks. Firstly, Discourse Historical Approach DHA developed by Wodak (2001) was selected to analyze the discursive strategies employed in the representation and to offer the socio-historical context surrounding it. DHA offers five discursive strategies: Referential, Predication, Argumentation, Intensification/ Mitigation and Perspectivation. Secondly, Semantic Macrostructures developed by Van Dijk (1980) was employed to assist in locating the discursive strategies within discourse topics. Lastly, Van Dijk’s Ideological Square (2004) was employed to highlight the in\out group polarization. The results showed that the representation in the Malaysian media was highly affected by the changes in the state policies resulting in conflicting representations. So, in crime related discourse, the Malaysian media represented FDHs as victims and as criminals. In recruitment discourse, FDH were represented as a need and as replaceable, also as abusers of the law and as victims of human trafficking. On the other hand, the media in Indonesia and the Philippines was less affected by the policy changes as it predominantly represented the domestic helpers as victims, desperate and vulnerable. Their representation was enhanced by justifications for illegality and demands for international laws’ protection
Administrative reform in the power industry of selected states in Nigeria / Aliyu Ashiru Olayemi
No full textSeveral administrative reforms in the power sector in Nigeria have not improved the electricity supply. The outcomes of reforms undertaken so far sharply contradict citizens’ expectations (stable electricity supply). Worse still, the rate of customers’ complaints about epileptic power supply rose from 47,127 to 109,048 between 2015-2016, while in 2019, 265,984 complaints were recorded. The study adopts the generic government sector reform model to analyse the factors contributing to the poor outcomes of the reforms. The model suggests critical component of the government sector reform is required to be integrated, coordinated to underpinning reform initiatives. For the purpose of this study, a survey questionnaire was used to study the relationship between political, bureaucratic support, communication strategy, willingness to changes, and success in government reforms. The study also investigates the relationship between professional and civil society organisations support and level of successful reforms, and the indirect relationship between reform decision, consultation and communication strategy. The survey research methods adopt a cross-sectional approach, employing a purposive sampling technique. Essentially, four hundred and sixty-three (463) copies of the questionnaires were administered to respondents selected from four states (population) with a yield of 401 responses. WarpPLS software, a variance-based Structural Equation Model (PLS-SEM), has been used to analyse the data. The structural model estimation findings reveal that four paths are statistically significant, which confirm the hypothetical relationship. Furthermore, evidence from the literature and the result of descriptive analysis of each measurement item in the model variables support the remaining three paths of the proposed relationship. However, structural model estimation could not statistically establish proposed relationships in the model. Nevertheless, the research confirmed hypotheses 1, 3 and 4 based on the result of the structural model coupled with pieces of evidence from the literature. The findings contribute to the body of literature by filling the gap in terms of studies investigating why reform initiatives might have failed to produce the desired outcomes and make a significant contribution to improving the theory on service delivery, which is critical to good governance. The findings affirmed that political and bureaucratic supports are necessary prerequisite conditions for result-oriented reform programmes. Also, the study finds that the stakeholders' support required to drive a purposeful reform exercise was conspicuously lacking. The work suggested a strong alignment, collaboration, and cooperation amongst the stakeholders as a sine qua non to intended reform outcomes. For the government to achieve a desirable reform outcome, the study advocated an all-inclusive reform process
Effect of forming speeds on coil-break formation during uncoiling of fully annealed low carbon steel sheets-a 3D finite element simulation study / Kam Weng Joe
No full textCoil breaks are narrow, irregularly changing deformation lines that causes difficulties in many steel industries as it is considered as a serious surface defect which leads to esthetical problems on the final product. A 3D explicit finite element model was developed to evaluate the coil break formations during uncoiling of full annealed low carbon steel sheets at different speeds. The 3D model consists of 2 lap coils measuring 600 mm in the inner core diameter and 300 mm width with a sheet thickness of 1.5 mm. The line speed was increased from 1 mpm to 1000 mpm and the change in true (LE11) strains and stress distributions (S11) along the longitudinal direction on top surface of the sheet were recorded. The simulation results show that there are 7 interruption zones with Zone A consists of narrow band of compressive strain and Zone B which consists of islands of tensile strain or coil breaks. The strain rate of the uninterrupted element increased the highest from 0.0007 to 1.1920 /s when the uncoiling speed increased from 1 mpm to 1000 mpm. The higher strain rate will cause the LE11 to reduce which minimizes the peak height. Hence, coil break was able to minimize with 1000 mpm as it subjected to a higher strain rate. Coil tensions were varied from 36 N/mm to 176 N/mm to further reduced the coil break with 1000 mpm line speed. 1000 mpm with coil tension of 146 N/mm was selected as the optimum profile as the severity of the coil breaks are the lowest. In the mesh analysis using higher integration points, the formation of coil break in Zone B1 were eliminated and the severity of coil breaks were increased as more accurate results were obtained. The total computational time recorded for 1000 mpm with coil tension of 146 N/mm with 7 integration points was 0.38 hours (22.8 minutes)
Development of visual odometry based machinery motion assessment system / Low Shee Teng
No full textMonitoring the vibrations of a machine's mechanical components is critical to its proper operation as for performing preventive maintenance. Recently, a sizable number of the study approaches in vibration analysis are based on non-contacting vibration measuring equipment that offering various advantages than the conventional sensors. New methods for gathering information about the vibration of the machine have evolved simultaneously with the constant improvement of the visual odometry (VO) systems due to the rapid development of computer vision (CV) field. Digital image analysis, video analysis, and other visual inputs are all examples of CV, which is a branch of artificial intelligence (AI) that empowers computers or systems to obtain significant information from digital images, videos, as well as other visual inputs and to take actions or make recommendations based on this information. Research laboratories to actual industrial installations were made possible because of their actual effectiveness. The use of visualization tools can often be a useful addition to vibration analysis or even a complete replacement for more traditional approaches. The non-contacting attributes and the ability to simultaneously observe several spots in the defined region are the most important factors. Motion magnification (MM), an image processing technique that provides the visual observation of vibration processes that are not visible in their native state, is an image processing technology. Four types of methodologies involving optical flow (OF), motion amplification and MM have been implemented and linear based Eulerian Video Magnification (EVM) have been implemented as a benchmark. Method 1 include the calculation of OF follow by motion amplification on the video. Method 2 would be the same as Method 1 but including the insertion of the cut-off frequency. Method 3 would be combining Method 2 with linear based EVM, and Method 4 would be purely linear based EVM. These algorithms are implemented in terms of their computational complexity and visual quality as well as how they provide the amplified motion of video output. Machine diagnostics can be improved by using visual methods that magnify motion. Motion amplification aids in the visualization of complex vibration problems that are otherwise inaccessible to the human eye. When used in conjunction with other tools, this instrument can save time and money in the areas of routine condition monitoring programs, troubleshooting, vibration analysis and root cause analysis. In this research, the output of the video amplifying and magnifying algorithm have been compared. According to the findings, EVM is the most appropriate VO for a machinery motion assessment system because it has performed the best magnification work in this project. The EVM technique has the best magnification when comparing the data acquired from these approaches; nonetheless, the EVM method exhibits superior noise characteristics than Method 3. Method 2 outperforms Method 1 in terms of edge distortions, but the results are foggy at the end of the system because of the blurring that occurs at the end of the system
Microcalcification detection in mammography for early breast cancer diagnosis using deep learning technique / Leong Yew Sum
No full textBreast Cancer is one of the common cancers in women and may cause lives to be lost if
they were misdiagnosed and left untreated. Existence of breast microcalcifications are
common in breast cancer patients and they are an effective indicator of early breast
cancer. This project will incorporate the use of machine learning in segmenting breast
mammogram images with calcifications of either benign or malignant cases for early
breast cancer diagnosis. ROI images of breast microcalcification will be utilized to train
several pretrained models from fastai library in Google Colaboratory platform using
supervised learning with a ratio of 0.80 for training dataset and 0.20 for validation
dataset. Image processing of ROI images were conducted to remove possible artifacts
and noises in order to enhance the quality of the images before training. The pretrained
models that were included in this study are Resnet34, Resnet50, VGG16 and Alexnet.
Different hyperparameters such as epoch, batch size etc were tuned in order to obtain
the best possible result in this study. Confusion matrices were utilized in order to
measure the output parameters of the models for comparison in terms of performance.
The result from this study shows that Resnet50 achieves the highest accuracy with a
value of 97.58%, followed by Resnet34 of 97.35%, VGG16 of 96.97% and finally
Alexnet of 83.06%
Prototype development and performance analysis of latent heat thermal battery integrated with solar collector / Farhood Sarrafzadeh Javadi
No full textThermal battery is one of the challenging topics due to its low thermal storage
capability and independency from the energy sources. This study aims designing,
modeling and performing the experimental analysis of a standalone latent heat thermal
battery (LHTB) integrated with a solar collector as the main source of heat. The LHTB
consists of a plate-fin and tube heat exchanger located inside the battery casing and
paraffin wax which is used as a latent heat storage material. Solar thermal energy is
absorbed by solar collector and transferred to the LHTB using water as heat transfer fluid
(HTF). As a result, the paraffin transforms from the solid to liquid and the heat is stored
in the form of latent heat. Then, the heat can be released in a reverse process. The
significances of this design are the compatibility with different types of solar collectors
which makes it a cheaper solution compared to replacement of solar collector, adaption
with different kinds of heat source such as solar heat and industry heat waste, and mobility
which allows the user to recover the heat in a place other than charging location.
The charging and discharging tests have been conducted in three different operating
temperature of 68, 88, and 108 °C and each test was repeated for HTF flow rates of 30,
60 and 120 l/h. The highest amount of stored thermal energy was 13,210 kJ versus the
highest recovered amount of 5,825 kJ at maximum recovery efficiency of 35%. However,
the highest charging efficiency of 29% achieved in the test using 30 l/h of HTF at 108 °C
with stored thermal energy of 11,189 kJ. The recovery efficiency of the LHTB is varies
between 18% and 35%. It is highlighted that around two third of the paraffin remained at
the temperature above 58 °C at the end of the discharging tests. This is a considerable
amount of unused heat trapped inside the paraffin.
Thermodynamic analysis confirmed that the highest charging and recovery exergy
efficiency of 93.4% and 35.9% are achieved in the tests using 30 l/h of HTF at 68 °C and
120 l/h of HTF at operating temperature of 108 °C, respectively. However, the highest overall exergy efficiency of 25% achieved in the test using 120 l/h of HTF at operating
temperature of 68 °C. In the improved LHTB design, the best performance achieved by
absorbing 12,647 kJ thermal energy at efficiency of 11% using 120 l/h of HTF at 88 °C.
But, highest efficiency of 37% recorded in the test using 30 l/h of HTF.
The highest efficiency of 34%-42% in different tests was reported for the HPSC-LHS,
as the most advanced design in this field. The similar range of charging and recovery
efficiency of 34% and 37% were respectively calculated for the improved LHTB design.
The significant result shows that the charging rate advancement is from 2.07 MJ/h in
HPSC-LHS to 3.16 MJ/h in LHTB design. Therefore, an increase of 52.3% in charging
rate is proven