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ART HISTORY
No full textArt history is an academic discipline that examines artistic and visual cultural production across different cultures and eras. It involves analyzing the formal qualities of art, its social and political contexts, and how artistic styles evolve over tim
Blurring Realities : The fusion of real and Virtual in The Art World
No full textThe emergence of technology has had a significant impact on our everyday lives. The concept of immersive environments has gained much popularity in this rapidly changing technological environment that we live in today. Emerging technologies also provide artists with new approaches to creating and manipulating art, allowing audiences to engage in immersive environments. However, what does it entail -
being in an immersive environment
Optimizing UAV performance in turbulent environments using cascaded model predictive control algorithm and Pixhawk hardware
No full textThe modelling and control of unmanned aerial vehicles (UAVs), especially quadrotors with significant position–orientation coupling, pose considerable challenges in practical applications, such as environmental monitoring in wind-affected mangrove forests. Traditional control methods, such as the PID controller, which are commonly used in simulations owing to their simplicity, often fail to perform optimally under real-world conditions because of their reliance on linear assumptions. This study addresses these challenges through three key innovations: (1) a hierarchical cascaded model predictive control (MPC) framework that decouples translational and rotational dynamics into computationally efficient subsystems, signifcantly reducing the computational load of conventional MPC implementations; (2) a control strategy explicitly optimized for turbulent mangrove ecosystems, where dense vegetation amplifies wind disturbances; and (3) experimental validation
of the framework’s real-world applicability via simulations and hardware-in-the-loop flight tests using Pixhawk autopilots under realistic wind conditions. These tests demonstrated that the proposed controller significantly outperformed the conventional PID controller, particularly in terms of stability and disturbance rejection. These results highlight the potential of this control system for UAV applications in challenging environments, bridging the gap between theoretical control design and field-ready robustness
A Framework for Green Energy Resources Identification and Integration Supported by Real-Time Monitoring, Control, and Automation Applications
No full textSarawak is transitioning to green energy adoption, yet progress is hindered by a lack of comprehensive spatial data to identify optimal locations, inadequate optimization techniques for effective integration of these sites, and insufficient robust Industrial Internet of Things-based real-time monitoring and automation strategies to manage the intermittent nature of green energy resources. To address these challenges, a novel Geographical Information System-based fuzzy Technique for Order Preference by Similarity to Ideal Solution coupled with filtration algorithms was proposed. This two-layered approach effectively filters potential green energy sites. The first layer identified 23 optimal wind energy sites and 138 optimal hydro energy sites. The second layer employed spatial data and the fuzzy Technique for Order Preference by Similarity to Ideal Solution algorithm to refine potential solar energy sites, yielding the top 100 optimal locations. The proposed method demonstrated a 69.01 % alignment when validated against the weighted sum method. Following site identification, an improved Geographical Information System-driven fuzzy Traveling Salesman Problem-Binary Integer Programming algorithm was proposed to integrate these sites into a reliable ring-based system topology, aiming to achieve a zero-carbon footprint. The process involved clustering by divisions and designing optimal electrical power line routing for each cluster, prioritizing minimum total distance, elevation difference, and average ground flash density. Validation against conventional methods and state-of-the-art algorithms confirmed the superior performance of the proposed approach. Additionally, an Industrial Internet of Things-based system utilizing servers, cloud platforms, and Supervisory Control and Data Acquisition systems was developed for real-time monitoring, control, and automation to address green energy intermittency. Hardware prototypes using Raspberry Pi and Industrial Internet of Things components were interfaced with SCADA systems to validate real-world applicability. Experimental results confirmed the effectiveness of the proposed methodologies. In conclusion, the proposed methodologies demonstrate the potential to overcome barriers to green energy implementation, fostering sustainable development in Sarawak. This research offers practical insights for policymakers, energy stakeholders, and researchers advancing green energy initiatives
Investigating Pre-treatment Effects and Optimising Solid-State Fermentation for Cellulase Production by Aspergillus niger MBL using Local Pineapple Leaves
No full textAgricultural wastes are the by-products generated as the result of cultivation and processing of raw agricultural products, in which accumulation of these wastes in the landfills without proper waste management can be a concerning issue to the society and environment. Pineapple leaves which are wastes produced from pineapple farming, have the potential to be utilised as raw materials in various biochemical processes such as solid-state fermentation in producing industrial important enzymes, particularly, cellulase. The applications of cellulases in various industries are enormous, however, high production cost of the chemically-produced cellulases has been a major concern among the researchers in order to produce cheaper resource with improved sustainability for the industries. Production of cellulases by microorganisms such as filamentous fungi through solid-state fermentation has been broadly studied and showing a great potential as an alternative approach in producing enzymes with cheaper production cost. In this present study, pineapple leaves from a local cultivar known as ‘Nanas Paun’ were utilised as the substrate used in solid-state fermentation for the production of cellulase by Aspergillus niger MBL. The focus of the study was to evaluate the impacts of different pre-treatments on the morphological changes and lignocellulosic contents of the leaves, as well as, to identify the optimum conditions of the solid-state fermentation for cellulase production with high activity from the fungus mentioned using local pineapple leaves. Due to the complex physicochemical structure and compositional make-up of the biomass, the ‘Nanas Paun’ leaves were subjected to various pre-treatment methods such as chemical treatments with different concentration of dilute acid and alkaline solutions, as well as thermal treatment by autoclave. The effects of different pre-treatments on the compositional contents and morphological properties of the ‘Nanas Paun’ leaves were evaluated through a compositional analysis by gravimetric method and Scanning Electron Microscopy. It was suggested that pre-treatment of local pineapple leaves with 1.5% (v/v) hydrochloric solution revealed to be the most effective pre-treatment method as highest amount of cellulose (51.5% w/w) and lowest lignin content (10.3% w/w) were recorded, as well as showing the most notable changes and severe alteration on its morphological surface structure, in comparison with other pre-treatment methods. The ‘Nanas Paun’ leaves treated with 1.5% (v/v) hydrochloric acid solution was then utilised as the substrate for further evaluation on optimal conditions required for maximum cellulase production of high enzyme activity by Aspergillus niger MBL. Few parameters influencing solid-state fermentation such as incubation period, initial moisture content, pH, and temperature were optimised. Filter paper assay method was used to determine the total enzyme activity of cellulase, and reducing sugars released was assessed through dinitrosalicylic acid method. In this research study, it is concluded that the highest total cellulase activity was recorded at 5.1773 ± 1.2756 U, with treated ‘Nanas Paun’ leaves as the substrate, an incubation period of 8 days (192 hours), an initial moisture content of 70% (v/w), a pH of 5.0, and an incubation temperature at 35 °C. The findings of this study show the potential of local pineapple leaves to be employed as raw materials in bioconversion process such as fermentation to produce cellulase efficiently, with promising benefits for sustainable waste management.
Keywords: Cellulase, pre-treatments, Aspergillus niger MBL, solid-state fermentation, local pineapple leave
The Effect of Climate on Thermal Loads in Living Walls
No full textThis study analysed the impact of living walls on energy-efficient residential buildings in major Australian cities with varying climates. The aim was to identify and
quantify the shading and evapotranspiration benefits of living walls using calibrated thermal simulation software. Empirical correlations were applied to replicate the evapotranspiration effect in the simulation. Building dynamic thermal modelling was undertaken with the widely-used AccuRate Sustainability energy rating software. Two house designs were used in the simulation, applying various scenarios to assess the benefits of living walls in various Australian cities. The results showed that living walls provided the most cooling in warm and dry climates such as Perth and Adelaide, with minimal benefits in tropical regions such as Darwin. In temperate climates, living walls had little impact on heating, but in colder climates, they increased heating demand. Homes with insulated walls are common in modern residential construction. For such homes, the evapotranspiration effect rather than the shading or insulation characteristics of the living wall became
the primary mechanism for reducing cooling loads, particularly in drier climates. When applying a single living wall for idealized models a potential cooling savings in cooling energy of 10–16% was determined, whereas for typical home designs this saving reduced to below 1%. It was found that the benefits of living walls are comparable to or lower than simpler, more cost-effective passive strategies such as adjusting building orientation or using light-coloured walls
Love knows no boundaries : Exploring the challenges in interracial marriages among Sarawakian women
No full textInterracial marriages remain a taboo in Malaysian society, with couples facing distinct challenges compared to same-race couples, including discrimination, lack of support, and the adjustment to different cultural norms. This research aimed to explore the challenges faced by women in interracial marriages, their coping strategies, and their expectations for the future of such unions. A qualitative approach was employed, with interviews conducted with eight Sarawakian women. The data were analysed using Thematic Analysis. The challenges these women encountered included cultural differences, lack of marital support, religious differences, and the specific experiences of being a wife in an interracial marriage. Coping strategies identified included communication, distractions, and the integration of both spouses' cultures. These findings highlight the need for increased awareness of the challenges faced by women in interracial marriages, underscoring the importance of policymaking, enhanced counselling practices that account for cultural differences, and community-based programmes that address their needs
Polymer nanocomposite membranes for heavy metals removal
No full textWater scarcity is an escalating global issue affecting billions and is projected to intensify in the coming decades. The increasing demand for clean water, coupled with the proliferation of wastewater from residential, industrial, and agricultural activities, is leading to the need for efficient and sustainable wastewater treatment technologies development, which is escalating. This chapter focuses on the significant threat posed by industrial wastewater, particularly due to toxic heavy metals such as lead, chromium, arsenic, cadmium, and mercury, which are persistent, bioaccumulative, and pose severe risks to human health and the environment. Recent advancements in polymer nanocomposite membrane technology offer promising solutions compared to traditional treatment methods. Polymer nanocomposite membranes, developed by incorporating nanoscale materials such as nanoparticles, nanofibers, and nanotubes into polymeric matrices, exhibit superior characteristics, including increased hydrophilicity, mechanical strength, and chemical stability. These membranes leverage the unique properties of both organic and inorganic materials, enhancing their functional properties such as permeability, selectivity, and chemical resistance, and proving extremely effective in the removal of heavy metals from wastewater. This chapter explores the latest developments in polymer nanocomposite membranes, emphasizing their design, operational dynamics, and efficacy in treating industrial effluents. It compares these innovative approaches to traditional methods, highlighting their potential to replace older, less effective technologies. This chapter demonstrates the crucial role of polymer nanocomposite membranes in future industrial applications, considering both their capabilities and developmental constraints. This advancement represents a substantial step toward achieving sustainable environmental management, offering a reliable solution to one of the most pressing environmental challenges of our time
Enhancing leptospirosis screening using a deep convolutional neural network with microscopic agglutination test images
No full textLeptospirosis poses substantial challenges to global public health. In Malaysia, leptospirosis is endemic, with annual cases peaking during the monsoon season. The microscopic agglutination test (MAT) is the gold-standard serological method for confirmation of leptospirosis. However, it is labor-intensive and time-consuming, as it relies on the subjective interpretation of medical lab technicians. This study describes the development of a semiautomated workflow for Leptospira screening by integrating a TensorFlow and custom-designed Keras-based Deep Convolutional Neural Network (DCNN) with conventional MAT. We used a dataset of 442 positive and 442 negative MAT images, which consisted of a mixture of Leptospira serovars from Malaysia to train the model. The model was subjected to hyperparameter tuning, which modulated the number of convolutional layers, filters, kernel sizes, units in dense layers, activation functions, and learning rate. Verification of our tested model compared to the verified patient MAT results achieved the following metrics: a Precision score of 0.8125, a Recall of 0.9286, and an F1-Score of 0.8667. Combining our model with the current Malaysia Leptospira workflow can significantly speed up, reduce inaccuracies, and improve the management of leptospirosis. Furthermore, the application of this model is practical and adaptable, making it suitable for other labs that observe MAT as their Leptospira diagnosis. To our knowledge, this approach is Malaysia’s first hybrid diagnostic approach for Leptospira diagnosis. Scaling up the dataset would enhance the model’s accuracy, making it adaptable in other regions where leptospirosis is endemic
An Optimized Load Shedding Approach in Power Grids to Mitigate Cascading Failure
No full textPower grid security has always been a key issue in power industry development. The paper presents an optimal approach to mitigate power blackouts by applying steady-state load shedding. The particle swarm optimization algorithm is employed in cloud computing and monitoring environments to minimize the amount of power to be shed and its location. The standard IEEE test systems have been used as a benchmark to validate the proposed approach. The preliminary results show that the system’s parameters are constrained within the safety limit. Thus, reserve generation remains connected to the power grid for additional service during grid faults. The proposed modeling and control can be used to develop planning and operational strategies for a practical power system. Features related to integrating advanced digital solutions to enhance the power grid operation and reduce downtime by improving real-time monitoring and data-driven approaches are also presented