Spatial-temporal data modelling and processing for personalised decision support

The purpose of this research is to undertake the modelling of dynamic data without losing any of the temporal relationships, and to be able to predict likelihood of outcome as far in advance of actual occurrence as possible. To this end a novel computational architecture for personalised ( individualised) modelling of spatio-temporal data based on spiking neural network methods (PMeSNNr), with a three dimensional visualisation of relationships between variables is proposed. In brief, the architecture is able to transfer spatio-temporal data patterns from a multidimensional input stream into internal patterns in the spiking neural network reservoir. These patterns are then analysed to produce a personalised model for either classification or prediction dependent on the specific needs of the situation. The architecture described above was constructed using MatLab© in several individual modules linked together to form NeuCube (M1). This methodology has been applied to two real world case studies. Firstly, it has been applied to data for the prediction of stroke occurrences on an individual basis. Secondly, it has been applied to ecological data on aphid pest abundance prediction. Two main objectives for this research when judging outcomes of the modelling are accurate prediction and to have this at the earliest possible time point. The implications of these findings are not insignificant in terms of health care management and environmental control. As the case studies utilised here represent vastly different application fields, it reveals more of the potential and usefulness of NeuCube (M1) for modelling data in an integrated manner. This in turn can identify previously unknown (or less understood) interactions thus both increasing the level of reliance that can be placed on the model created, and enhancing our human understanding of the complexities of the world around us without the need for over simplification. Read less Keywords Personalised modelling; Spiking neural network; Spatial-temporal data modelling; Computational intelligence; Predictive modelling; Stroke risk predictio

Spatial-temporal data modelling and processing for personalised decision support

The purpose of this research is to undertake the modelling of dynamic data without losing any of the temporal relationships, and to be able to predict likelihood of outcome as far in advance of actual occurrence as possible. To this end a novel computational architecture for personalised ( individualised) modelling of spatio-temporal data based on spiking neural network methods (PMeSNNr), with a three dimensional visualisation of relationships between variables is proposed. In brief, the architecture is able to transfer spatio-temporal data patterns from a multidimensional input stream into internal patterns in the spiking neural network reservoir. These patterns are then analysed to produce a personalised model for either classification or prediction dependent on the specific needs of the situation. The architecture described above was constructed using MatLab© in several individual modules linked together to form NeuCube (M1). This methodology has been applied to two real world case studies. Firstly, it has been applied to data for the prediction of stroke occurrences on an individual basis. Secondly, it has been applied to ecological data on aphid pest abundance prediction. Two main objectives for this research when judging outcomes of the modelling are accurate prediction and to have this at the earliest possible time point. The implications of these findings are not insignificant in terms of health care management and environmental control. As the case studies utilised here represent vastly different application fields, it reveals more of the potential and usefulness of NeuCube (M1) for modelling data in an integrated manner. This in turn can identify previously unknown (or less understood) interactions thus both increasing the level of reliance that can be placed on the model created, and enhancing our human understanding of the complexities of the world around us without the need for over simplification. Read less Keywords Personalised modelling; Spiking neural network; Spatial-temporal data modelling; Computational intelligence; Predictive modelling; Stroke risk predictio

Development and characterization of treated kaolin filled polypropylene/kaolin nanocomposites

This research work focused on producing modified kaolin filler in polypropylene/kaolin (PP/K) nanocomposite by melt compounding process in order to improve its mechanical and thermal properties for industrial applications. The surface treatments of micron sized Malaysian kaolin were conducted to produce nano sized kaolin by acidification of kaolin fillers with sulphuric acid and planetary milling using urea (mechanochemical milling). Testing on both surface treated kaolin were carried out with the aid of Field Scanning Electron Microscopy (FESEM), Fourier Transform Infrared (FTIR), Brunauer–Emmett–Teller (BET), X-ray Diffraction (XRD) and Particle Size Analyser and results of both treated kaolin were compared. However, the surface treated kaolin using acidification was unsuccessful as shown by XRD, FTIR and BET results. A successful delamination of micron sized into nano sized kaolin was achieved by mechanochemical milling. The additional bands at 3624, 3445 and 3388 cm-1 and illite phase at lower 2θ by FTIR and XRD studies respectively, indicated delamination of kaolin. Surface area increased by 400% from BET results. The PP/K nanocomposite was produced by incorporating low weight (1-7%) percentages of organically modified nanokaolin into PP by melt compounding with polypropylene grafted maleic anhydride (PP-g-MA) as coupling agent. The FTIR and XRD analyses on chemical structure showed successful synthesis of PP/K nanocomposites by the vanishing of characteristic of OH bands and peaks of kaolin respectively. The tensile and impact strength, tan δ, loss modulus and melt flow index of PP/K nanocomposite decreases by 17, 27, 36, 32 and 78% respectively. Conversely, the results show that incorporation of nanokaolin clay into PP causes increase in thermal degradation (200%), crystalinity (17%), nucleation effect (17%), storage modulus (10%), surface roughness (87%), and optical (262%). Whereas, TEM of PP/K nanocomposite exhibit nanokaolin dispersion with nanoscale sizes. Therefore, the PP/K nanocomposites formulated shall be a potential candidate for manufacturing novel new materials of attraction in many sectors

IMPROVED PHOTOLITHOGRAPHY SCHEDULING IN SEMICONDUCTOR MANUFACTURING

Photolithography is typically the bottleneck process in semiconductor manufacturing. In this thesis, we present a model for optimizing photolithography job scheduling in the presence of both individual and cluster tools. The combination of individual and cluster tools that process various layers or stages of the semiconductor manufacturing process flow is a special type of flexible flowshop. We seek separately to minimize total weighted completion time and maximize on-time delivery performance. Experimental results suggest that our mathematical- and heuristic-based solution approaches show promise for real world implementation as they can help to improve resource utilization, reduce job completion times, and decrease unnecessary delays in a wafer fab

Pool-based electricity market model for Malaysia electricity supply industry considering minimum generation capacity payment

Malaysia is improving its electricity supply industry to become more transparent, productive and competitive with the introduction of the single buyer market model. However, since the electricity demand is lower than the reserved capacity, the implementation of this market model does not provide transparent competition as Tenaga Nasional Berhad (TNB) has suffered massive profit erosion because of monthly capacity payment that should be paid to Independent Power Producers (IPP) regardless of electricity usage. Since 2005, the Malaysia Electricity Supply Industry (MESI) has planned to change to the pool market model as it is recognized as a model which could overcome the shortcomings of the single buyer market model. However, there are a few issues on introducing the pool model such as price fluctuation and market power exercises which could influence the welfare of generators as well as the consumers. Some researchers have developed pool-based market models with the aim to overcome the aforementioned issues, but the efficiency and the energy price offered from the generators are not considered. Therefore, this research developed a model introducing the minimum generation capacity payment involving the efficiency of the generators and base load sharing approaches. The proposed model was tested using the 2, 16 and 24 generator test systems involving IPPs and Tenaga Nasional Berhad Generation (TNBG) around Peninsular Malaysia for an economic analysis to highlight the merits of the proposed model in terms of generation revenue and demand payment. The results have shown that the proposed market model ensures the intermediate value of total generation revenue which decreased from 1.99% to 4.67% and 3% to 9.62% during the weekday and weekend, respectively. The demand payment decreased as it is proportional to the generation revenue. However, this proposed model did not consider market uncertainties. This findings can be applied for MESI and globally, in assisting and creating a new policy to achieve a better electricity market model

Effects of spent garnet on the compressive and flexural strengths of concrete

Sand is the non-renewable resource which has been over-exploited from rivers in sync with the rapid development of construction industries to produce concrete. This affected the morphology of rivers and interrupted the functionality of riverine ecosystems by pollution. Meanwhile, the unrecyclable spent garnets were disposed of on a large scale and led to waste pollution. Therefore, this study aimed to determine the compressive and flexural strengths of concrete consisting of spent garnet as sand replacement. The specimens were prepared with consisting of spent garnet as sand replacement by weight in 0%, 10%, 20%, 30% and 40%. They were tested under compressive strength test at the age of 7 and 28 days while flexural strength test was conducted on the 28days. The findings revealed that the workability of fresh concrete was enhanced by an incremental amount of spent garnet. However, the compressive and flexural strengths of concrete consisting of spent garnet were discerned to be lower than control samples at all levels of replacement. Overall, the replacement with 20% spent garnet showed the optimum compressive and flexural strengths. It is concluded that the usage of spent garnet is considered as a promising resource for reducing consumption of sand and thus, improving the environmental problems

Moderating effects of cross-cultural dimensions on the relationship between persuasive smartphone application's design and acceptance-loyalty

Applying persuasive system design to different cultures has been a focus of many researchers as the global medium of communication has been centered within Smartphone via applications (apps). This is due to the vast proliferation of the Smartphone and the personal attachment of users to this device in various cultures. This led designers to search for ultimate ways to target users in specific regions of the world. The basic purpose of this study was to determine the relevance of cross-cultural factors to persuasive technologies, and the acceptance and loyalty of Smartphone apps. This was achieved by examining the moderating effects of Hofstede’s six cross-cultural dimensions on the relationship between Oinas-Kukkonen and Harjumaa’s Persuasive System Design (PSD), and acceptance and loyalty. By evaluating elements of persuasive systems design and cross-cultural dimensions, from user’s perspective, against a globally popular application like WhatsApp, an instrument was devised to investigate the cross-cultural adoption and continued use of Smartphone apps. Using this instrument, surveys were conducted for this research study to identify the influencing factors that have motivated the users from Malaysia, Netherlands, Germany, and the Kingdom of Saudi Arabia to adopt and continue using this application on a daily basis. These surveys, which included responses from 488 participants, further investigated if there is one cross-cultural dimension that has more moderating effects per country. The findings indicate an agreement among WhatsApp users from all four countries about their reasons for adopting and using this app, namely: social influence (93.7 percent), reliability (83.4 percent), dialog-support via feedback (76.4 percent), ease of use (90.5 percent) and small cost (87.7 percent). The results put new perspective that the gap among cultures is narrowing. Persuasive design strategies are particularly relevant to cultures across the globe. This study can aid the research community in investing efforts into enhancing the persuasive design framework for Smartphone apps

Abandoned project restoration model (APRM) for residential construction projects

Incompletion of construction projects is a common phenomenon in Malaysia. Project abandonment has given an adverse consequences to the economy, society and environment. In the best interest of the end users and other parties involved in the contract, the best resolution for this abandoned projects is to successfully revive them, which has its’ stages and barriers along the way as well. The main aim of this research is to develop an effective model as a guide towards project restoration which could be used to mitigate the issue of abandoned residential construction projects in Malaysia. Identifying the factors contributing towards the restoration of the abandoned projects are important to have a successful completed project. This research was conducted in the purpose of identifying those significant factors in order to obtain the restoration process for abandoned projects where lastly the Abandoned Project Restoration Model (APRM) was developed. The research focuses on residential construction projects. This research comprises of both quantitative and qualitative approaches and process, where a pilot survey and full survey, and as well as interview analysis were conducted. Factor model was developed using AMOS and lastly the developed model was validated and tested by related officials. The outcome of this research showed that the most significant factor for abandoned project restoration is Management Aspects. A complete restoration process based on the significant factors identified were also obtained. This model is seen as useful in contributing and as well as assisting the restoration of the abandoned projects in Malaysia and could be used as a guideline for that purpose

Survival and disinfection of SARS-Cov-2 in environment and contaminated surface

The detection of SARS-Cov-2 in the sewage and water resources has increased the awareness among the people about the possibility survival of SARS-Cov-2 in the environment and the potential to transmit into the human through food chain or water resources. Moreover, the surface contaminated by the virus need to be disinfected frequently by using an effective disinfectant, the current chapter discussed the efficiency of the most traditional treatment process of the sewage and wastewater, and their role in the elimination of the virus as well as the sterility assurance level concept. Moreover, the chemical disinfectant used currently and their temporary efficiency has been reviewed