A Brief Review on Thermal Behaviour of PANI as Additive in Heat Transfer Fluid

Since a decade ago, investigation on nanofluids has grown significantly owing to its enhanced thermal properties compared to conventional heat transfer fluids. This engineered nanofluid has been widely used in the thermal engineering system to improve their energy consumption by improving the thermal efficiency of the system. The addition of nano-size particles as additives dispersed in the base fluids proved to significantly either improve or diminish the behaviour of the base fluids. The behaviour of the base fluid highly depends on the properties of the additives material, such as morphology, size, and volume fraction. Among the variety of nanoparticles studied, the conducting polymers have been subject of high interest due to its high environmental stability, good electrical conductivity, antimicrobial, anti-corrosion property and significantly cheap compared to other nanoparticles. As such, the main objective of the present review is to provide an overview of the work performed on thermal properties performance of conducting polymers based nanofluids

Immense impact from small particles: Review on stability and thermophysical properties of nanofluids

Nanofluid is a conventional fluid, blended with single or more nano additives with a dimension of less than 100 nm. Early studies revealed that dispersing a small amount of nano additives to base fluids can enhance the effective heat transfer properties of nanofluids by up to 250% relative to the base fluid. However, from a number of studies on nanofluid published, inconsistent thermophysical properties of formulated nanofluids reported due to many factors such as preparation approach, types of base fluids and morphology of nano additives. Selection of accurate parameters during nanofluids formulation can resolve this issue. The discussion on experimental studies by different authors include the stability evaluation of nanofluids and thermophysical measurement including its density, rheological and thermal conductivity studies can provide a guideline to the researchers towards the future development of nanofluids system with optimum thermophysical properties. This review article provided critical comments on biodegradable vegetable oil base fluid as one of the alternatives to non-renewable mineral oil as well it presents an overview of the remarkable research progress on conducting polymers base nanofluids witnessed in recent years. The outcome of this review paper would give an overview of further enhancements in nanofluid systems for industrial

Copper oxide/polyaniline nanocomposites-blended in palm oil hybrid nanofluid: Thermophysical behavior evaluation

In the present work, Copper Oxide-Polyaniline (CuO/PANI) nanocomposites-blended in palm oil hybrid nanofluid have been prepared via a two-step method and investigated as potential heat transfer hybrid nanofluids for the first time. Initially, CuO/PANI nanocomposites are synthesized via oxidative polymerization by varying the weight percentage of CuO nanoparticles (1, 5, and 10 wt%) and characterized using TEM, EDX, XRD, FTIR, and TGA analysis. The findings revealed a successful fusion of nanocomposite composed of spherical CuO nanoparticles embedded in flake-like PANI. The formulated CuO/PANI-palm oil hybrid nanofluids are prepared at a volume concentration between 0.01% and 0.5% and stabilized using an ultrasonication process without any surfactant. UV–vis and sedimentation observation revealed that all nanofluids remain stable for up to a month. FTIR analysis reveals that all formulated nanofluids are chemically stable as no formation of new peaks obtained with the dispersion of nano additives. The TGA analysis affirmed better thermal stability in all nanofluids compared to base fluids. Density evaluation of formulated nanofluids shows a linear relationship between density and volume concentration of nanocomposites but decreased with temperature. Rheology study indicates that palm oil exhibits viscous flow behavior similar to Newtonian behavior. Nanofluid containing 10 wt% CuO/PANI nanocomposites displayed having the highest viscosity and thermal conductivity properties (31.34% enhancement) compared to the rest prepared nanofluids. Mathematical equations were developed at the final stage of the research for future properties prediction

Effect of enterprise resource planning systems and forms of management control on firm’s competitive advantage

In the brick of digitalization industry revolution era, this study signifies the pertinent role of Enterprise Resource Planning Systems (ERPs) towards assisting the organization towards attaining the firm’s mission and goal. This study extends the knowledge by exploring the relationship between ERPs and management control (MC), which in turn enhances firm’s competitive advantage. Realizing the limited empirical work on ERPs from management accounting and control perspective, the discussion would be drawn from business stakeholder’s perspective, instead of from information technology standpoint. The study views ERPs as an important resource in creating the capability to control the business operations and combination of both factors creates the firm’s competitive advantage. Survey questionnaires were administered via email to 972 randomly selected manufacturing firms listed in Federation of Malaysian Manufacturer Directory. Based on the 114 usable responses, the data was analyzed using a structural equation modeling (SEM) approach through partial least square (PLS) software. The findings provide empirical evidence on the significance of ERPs in determining firm’s MC approaches, both technocratic and socio-ideological forms of control. Evidently, these variables do associate positively with competitive advantage. Additionally, the analysis demonstrates that only technocratic form of MC mediates the relationship between ERPs and competitive advantage, but not for socio-ideological control. These findings provide an insight on the relationship among ERPs, form of MC and firm’s competitive advantage, which may be an input for businesses in facing the industrial digitalization era

Investigation and analysis of crack detection using UAV and CNN: A case study of Hospital Raja Permaisuri Bainun

Crack detection in old buildings has been shown to be inefficient, with many technical challenges such as physical inspection and difficult measurements. It is important to have an automatic, fast visual inspection of these building components to detect cracks by evaluating their conditions (impact) and the level of their risk. Unmanned Aerial Vehicles (UAV) can automate, avoid visual inspection, and avoid other physical check-ups of these buildings. Automated crack detection using Machine Learning Algorithms (MLA), especially a Conventional Neural Network (CNN), along with an Unmanned Aerial Vehicle (UAV), can be effective and both can efficiently work together to detect the cracks in buildings using image processing techniques. The purpose of this research project is to evaluate currently available crack detection systems and to develop an automated crack detection system using Aggregate Channel Features (ACF) that can be used with unmanned aerial vehicles (UAV). Therefore, we conducted a real-world experiment of crack detection at Hospital Raja Permaisuri Bainun using DJI Mavic Air (Drone Hardware) and DJI GO 4(Drone Software) using CNN through MATLAB software with CNN-SVM method with the accuracy rate of 3.0 percent increased from 82.94% to 85.94%. in comparison with other ML algorithms like CNN Random Forest (RF), Support Vector Machine (SVM) and Artificial Neural Network (ANN)

Self-organizing map (SOM) for species distribution modelling of birds species at Kenyir landscape

Identifying which biodiversity species are more dominant than others in any area is a very challenging task. This is because of the abundant of biodiversity species that may become the majority species in any particular region. This situation create a large dataset with a complex variables to be analysed. Moreover, the responds of organisms and environmental factors are occurred in a non-linear correlation. The effort to do so is really important in order to conserve the biodiversity of nature. To understand the complex relationships that exist between species distribution and their habitat, we analysed the interactions among bird diversity, spatial distribution and land use types at Kenyir landscape in Terengganu, Malaysia by using artificial neural network (ANN) method of self-organizing map (SOM) analysis. SOM performs an unsupervised and non-linear analysis on a complex and large dataset. It is capable to handle the non-linear correlation between organism and environmental factors because SOM identifies clusters and relationships between variables without the fixed assumptions of linearity or normality. The result suggested that SOM analysis was suited for understanding the relationships between bird species assemblages and habitat characteristics

“Do we really have to talk about that?”: avoiding covid-19 topics with close contacts

As COVID-19 spread globally in 2020, it caused panic and uncertainty. As of September 2021, there were 1.9 million confirmed cases in Malaysia, with over 20,000 deaths (WHO, 2021). Government officials, front liners and health agencies worked tirelessly to manage the pandemic, by spreading awareness, enforcing SOP, and encouraging vaccination. Paramount during this period was dissemination of accurate and updated information about COIVD-19, whether through mediated or interpersonal platforms. Close contacts have a responsibility in making sure they disclose their health status to others and get tested to ensure that the infection does not spread in their local communities. Avoiding honest disclosures of COVID-19 status could be detrimental to others. Accordingly, this study will examine how individuals interact with close contacts and choose to avoid topics related to COVID-19, from the perspective of Theory of Motivated Information Management (TMIM). TMIM has been applied in various health contexts to understand information avoidance, including avoiding conversations on end-of-life preferences with spouses (Rafferty et al., 2014), or sexual health topics with romantic partners (Tannebaum, 2015). In this study, we explore factors that could influence COVID-19 information avoidance, such as anxiety, uncertainty discrepancy, outcome expectancy, and close contact’s target efficacy. Using a cross-sectional survey among young adults in Malaysia, an online survey was distributed among the respondents (N = 483). Overall, two hypotheses were not supported; anxiety is not significantly related to outcome expectancy or target efficacy. Target efficacy also mediates the relationship between outcome expectancy and information avoidance. The repercussion of these findings on TMIM, as well as factors that may influence health information management will be discussed

A brief review on thermal behaviour of PANI as additive in heat transfer fluid

Since a decade ago, investigation on nanofluids has grown significantly owing to its enhanced thermal properties compared to conventional heat transfer fluids. This engineered nanofluid has been widely used in the thermal engineering system to improve their energy consumption by improving the thermal efficiency of the system. The addition of nano-size particles as additives dispersed in the base fluids proved to significantly either improve or diminish the behaviour of the base fluids. The behaviour of the base fluid highly depends on the properties of the additives material, such as morphology, size, and volume fraction. Among the variety of nanoparticles studied, the conducting polymers have been subject of high interest due to its high environmental stability, good electrical conductivity, antimicrobial, anti-corrosion property and significantly cheap compared to other nanoparticles. As such, the main objective of the present review is to provide an overview of the work performed on thermal properties performance of conducting polymers based nanofluids