Advanced Transdisciplinary Engineering and Technology

Strengthening of TVET institutions is vital toward producing a knowledgeable, skilled and competence workforce for the industry. The heart of TVET education is about practicing psychomotor skills through a direct engagement with the laboratory and workshop facilities. Therefore, it demands an effective maintenance management toward ensuring a 100% availability of those facilities. Nevertheless, the literature portrays that many of TVET institutions worldwide are struggling to maintain their laboratory and workshop facilities. Thus, this review study aimed at revealing the uncovered issue related to maintenance management of laboratory and workshop facilities at technical and vocational education and training (TVET) institution. Secondary data based on previous research was gathered and scrutinized to extract a key critical success factors (CSFs) for managing the maintenance activities of laboratory and workshop facilities at TVET institution. Based on analysis, it was summarized that there are seven CSFs having the most significant impact toward improving the maintenance activities for TVET institution. All those CSFs constructs were then integrated in a simple yet self-explanatory framework to convey the conceptual idea to all stakeholders involved in managing the maintenance activities within TVET institutions. It is believed that the framework developed would benefit as an indicator and guideline in improving the maintenance activities for laboratory and workshop facilities at TVET institution.

Magnetic materials are main components of complex technology in fulfilling the industry’s basic demands. However, there are no effective instruments developed to determine the magnetic property of the material. Hence, this study aimed to develop sensing coils which are used for measuring the magnetic properties of materials. The developed sensing coils are calibrated, and the data is collected by LabVIEW before being used in analyzing the value of box coefficients. The calculated box coefficients, KB and KH, are 0.093314 and 0.005925, respectively. These box coefficients are important to ensure the accuracy of the magnetic properties measurement. To increase the reading accuracy in the future, it is recommended to justify the accuracy and precision of the coils, to increase the magnetic field produced by the solenoid by using the proper solenoid or using an AC converter, and amplify the induced voltage reading. As the conclusion, this study provided the precision measurement of magnetic properties which affects the total core loss. This is an important variable to consider when designing magnetic devices for optimum performance.

Chicken poultry is one of the important economic segments in the agricultural sector in Malaysia today. Chicken production in Malaysia has been increased gradually due to the standardized farming management and good manufacturing practices. There are few parameters that affect the health of a chicken such as temperature, water, and food supplies. These parameters need to be controlled in order to maintain the production and quality of chicken. With the advent of automation, a traditional chicken coop management system can be improved. Therefore, this study focuses on the development of an automated chicken coop management system prototype. Among the main hardware used for the project is the Arduino Mega board and sensors to control and monitor the parameters like temperature, water, and food level in the chicken coop. The parameters can also be monitored through a mobile Blynk application. The results indicate that with a more systematic control of the environmental factors that affect the health of a chicken, an ideal environmental condition can be achieved and maintained in the chicken coop.

Handling manual medical records (MR) in tertiary hospitals can be inefficient, hence may affect patient’s care. At present, patient waiting times at specialized clinics were affected due to the inability of preparing medical records on time. Our study applies the lean technique to examine issues and produce measurement performance indicator metrics in manual record management. This action research was carried out in the Medical Record Department, Hospital Kuala Lumpur. It was conducted over a year-period in 2017 in two main phases which were awareness and coaching of lean thinking and its application. Lean tools that have been utilized were value stream mapping (VSM), affinity diagram, 5S (i.e. sort, set in order, shine, standardize, sustain/self-discipline), Kanban, Kaizen, Heijunka and Poka-yoke. Specific performance project measurement metrics were established to determine the successful application of lean. Based on our case study, four specific performance project measurement metrics were achieved; (1) number of MR available 2 days before clinic appointment improved from 72 to 74%, (2) number of temporary MR made due to unavailable MR on clinic day reduced significantly (mean 8.43 vs. 2.53, p < 0.01), (3) number of MR to be traced on the clinic day for walk in patient and MR available improved significantly (mean 4.19 vs. 0.58, p < 0.01), (4) number of MR to be traced on the clinic day for walk in patient and MR not available reduced significantly (mean 4.24 vs. 1.69, p < 0.01). This study has shown the successful and positive feedback of lean technique application in manual medical record management at a tertiary hospital. Moreover, lean technique also produced the relevant and appropriate performance measurement metrics/indicators in monitoring the competency of medical record processes.

The purpose of this study is to obtain a better understanding of how to create a knowledge discovery database (KDD) and how to use it in maintenance. Frameworks for undertaking knowledge discovery and data mining have changed over time to meet corporate needs, according to the literature. Domain driven data mining is a KDD framework that is often used for this (DDDM). We use DDDM-KDD in this study to design an effective tire maintenance strategy for a Malaysian transportation company. The direction of the study, the utilization of research procedures, and the contribution of research are all factors to consider.

Sensor technology is one of the technology enablers widely used in the manufacturing process to improve efficiency and reliability. However, the sensor technology has attracted little attention in usage and application in the logistics function as compared to RFID, barcoding, and ERP. As such, this research aims to explore various issues related to the lack of sensor adoption in the logistics integration process in the manufacturing environment. The research adopted the qualitative method using the in-depth interview to unveil the themes related to the question in the study. The study identified various issues that hinder the adoption of sensors technology in the logistic area, particularly the failure to understand the logistics boundary in the manufacturing environment. This study contributed the knowledge on the sensor application in the logistics area in the manufacturing environment that can be used for future research.

This research is an assessment study about the effectiveness of machinery in warehouse operation at Armstrong Electronics Sdn Bhd. This research describes the usage of the software in the warehouse to improve the problem regarding inefficiency in warehousing operation of the company. The software that was used to conduct this research was the witness simulation software. The case study was conducted at Armstrong Electronics Sdn Bhd. In this study, the data collected from respondent will be consist of the effectiveness of machinery in their warehouse operation and the data that has been transferred to a software system in the witness simulation software. The interview was conducted with the executive logistics for data collection. Next, several improvement ideas were constructed to increase and improve the level and quality of service for their customer. These improvement ideas were recommended to be implemented for the warehouse operation in the company. In the conclusion, several suggestions have been made to improve the best of quality and recommendation for future research has also been included in the final part of this research.

In recent years, digital media has become pervasive in modern cultures. The number of internet users is at an all-time high, not just because of laptops and PCs, but also because of smartphone penetration, which makes it simpler and more accessible to people of all ages. Digital psychology has recently become an essential tool for organizations and scholars to better understand client psychological behaviour. The current study focuses on the literature on digital psychology since the advent of online goods buying and selling. It's tough to accept abrupt changes in one’s manner of doing things. For this purpose, the Scopus database is selected to extract data on digital psychology. The keywords for this study used are digital psychology, and after a detailed screening process, the final of sixty articles is included in the review. In order to gather data on digital psychology, the Scopus database was used. The study keywords included “digital psychology”, and the final sixty papers are included in the review following a thorough screening procedure. For data selection and rejection, the methodological element adheres to the PRISMA declaration from 2015. Year basis, journal base, and most referenced part are all discussed in the description section. The writers classify the data based on their results, settings, and processes. Digital environment, psychology, and behaviour are three key areas in which the literature is classified.

The damage mechanics concept introduced to assess the deformation and failure process of solder interconnects in electronic assemblies with ball grid array (BGA) assembly during reflow cooling, and subsequent temperature cycles are investigated. The test assembly consists of Sn-4.0Ag-0.5Cu (SAC405) solder arrays that provide an interconnection between an electronic package and the printed circuit board. Anand model of constitutive unified inelastic strain was employed to pronounce the temperature- and strain rate-dependent response of the SAC405 solder joints. The temperature-dependent cohesive model is also used to predict the damage process of the solder and intermetallic compound (IMC) interface fracture of SAC405 solder joints. Temperature loading consists of initial cooling down from the assumed stress-free reflow temperature of 220–25 °C, followed by a temperature cycle ranging from 125 to −40 °C at heating and cooling rates of 11 °C/min. Results showed that the most critical solder joint is located underneath the silicon die corner with the highest equivalent inelastic strain and von Mises stress under reflow cooling. The different straining rates experienced by the solder joints are driven by the temperature and strain rate effects of cohesive zone model parameter values. The highest predicted inelastic strain rate of 4.5 × 10–3 s−1 is found in the solder joint at 25 °C. Throughout the reflow cooling and temperature cycles, the damage propagation at the interface of solder and IMC is minimized. However, damage is initiated at the interface of solder and IMC plane and localized at a small edge region at the side of assembly package.

Welding is a process of joining two similar and non-similar metals or non-metals with the application of heat and pressure. Depth level of penetration is a key in fillet welded joints because the penetration gives the effects on the strength of the welded joint. The present work investigates the influence of the metal inert gas (MIG) welding process parameters such as welding current, welding voltage, and gas flow rate on bead geometry in EN 10025 low carbon steel material. The objectives are to determine the effect of welding current, welding voltage, and gas flow rate to the bead geometry, as well as to optimize the welding parameters for enhancing the weld penetration and to analyze the welding defects that can be considered and accepted using different welding parameter. The experimental work has been carried out using the MIG welding process. The work pieces were inspected and measured using non-destructive testing (NDT) method and a digital caliper to observe the effects of welding parameters on the weld bead condition. For optimization, the Taguchi method L9 orthogonal array and signal-to-noise ratio were used. Then, the data were analyzed using the main effect of means and analysis of variance (ANOVA). From the results, welding current, welding voltage, and gas flow rate were found to be main limitations which affect the bead geometry. The optimal welding setting for EN 10,025 carbon steel was at 180 A current, 26 V voltage and 16 ℓ/min gas flow rate.

In the case of fire in buildings, fire doors installed prevent the spread of fire and smoke from crossing across the building compartments. Much recently, there is a growing interest in the development of earth materials as an alternative material in building and construction like standard bricklaying and masonry. In the present study, the earth materials performance as an additive to the fire door core material in terms of its fire resistant is evaluated. It was found that an earth materials infiltrated core at 50% has shown significant improvement in terms of its fire resistant time. In conclusion, earth materials can be used as an additive to improve the fire resistant performance of fire doors. Comparable performance to the existing fire doors will have positive impact on the development and labor cost of fire doors especially for utilization in developed countries.

Electrical energy is one of the most important sources of energy in the world, and it powers most of the equipment. However, some methods of generating energy can be damaging to the environment such as water dams which can affect marine life. There are also green systems that provide electricity while causing no harm to the environment, such as solar panels which produce electricity but are inefficient on overcast days. As a result of this challenge, a new way for producing electrical energy that is both efficient and environmentally beneficial has been developed. Thus, the development of a low-cost hydroelectric generation system for application on water pipelines is presented in this study. The project is able to harness the kinetic energy of flowing water to generate electricity that will be stored in batteries and used to power other electronic equipment. Two designs have been proposed in this project to see the effect of the Venturi shape on water flow in pipes. The system is equipped with small-sized pipes (0.5 to 1 inch), G1 turbine flowmeter, microcontroller, 5 V water flow turbine hydroelectric generator, XH-M603 charging control module, and 12 V GP rechargeable battery. Although the recommended system is lightweight and compact, the system can be improved by incorporating larger turbines and connecting to municipal canals with higher water flow to generate more electricity. As a result of the experiment, it was found that an increase in water flow would cause the turbine to rotate faster, which resulted in an increase in energy generation. The project can provide effective and efficient results in addition to features such as green technology, lower construction costs, and reliable energy production.

Driving when being drowsy is one of the leading causes of automobile accidents on the road. Insomnia, some types of drugs, and boredom, such as driving for lengthy periods of time, can all cause drowsiness and exhaustion while driving. Many novel devices to prevent sleepy driving have been developed in recent years. One of them is to use biological indicator techniques by measuring the heart rate, brain waves or pulse rate. This technique can detect the parameters well and accurately but requires a physical contact that needs to be attached to the driver’s body. This will make it uncomfortable while driving and in addition the device cannot connect directly with the vehicle being driven. Therefore, the development of a speed control system using face recognition is proposed in this paper. Using the facial recognition method equipped with several devices such as HD web camera and LabVIEW to process facial recognition in real-time monitoring, the device will monitor the driver’s eyes in real time to see if they are awake or asleep. If the driver is found to be drowsy or sleeping, the system will identify it promptly and display it on the human–machine interface (HMI) to alert the other passengers. In this study, the facial recognition system is connected with a simple prototype to show how the system operates and the overall effectiveness of the system is evaluated. The alarm buzzer will be activated to get the driver’s attention back on the road, and if the condition persists, the system will send a signal to the motor driver to stop the vehicle automatically. Based on the findings of the experiments, a notification will be displayed in the graphical user interface (GUI) anytime the driver’s eyes are discovered to be drowsy or closed, an alarm buzzer will be sounded, and the motor speed will be precisely controlled until it becomes slow using the PWM control method.

Attribute can always be used as a mean to recognize anything because it is a characteristic or inherent part of someone or something. Nevertheless, it may become confusing if there are many attributes to characterize one thing without the attributes being sorted out following their similarities first. Therefore, the understanding toward the attribute is essential in the study of quality tools and techniques (QTT) because nowadays there are abundant of quality tools and techniques that have been developed to be used during the improvement activity or problem-solving. Given that there are various industries that use quality tools and techniques, the establishment of new quality tools and techniques becomes countless. Thus, the selection of QTT becomes difficult. Some practitioner just simply uses any QTT they once heard without prior knowledge about the QTT. Some of the selection of QTT being made without considering the whole situation thus resulting in pointless improvement or dead-end to find the solution to the problem. Apart from that, to compete in industry 4.0, all manufacturing industries should consider adapting all quality tools and techniques and all quality practitioners should have adequate knowledge in QTT or at least have some ‘first-aid’ to use the right QTT. That is when the development of attribute comes in handy. Correspondingly, attributes of quality tools and techniques are compulsory to be known to describe each of them since attributes are used to identify thus distinguish each individual QTT from one another. Therefore, the user or quality practitioner can understand the QTT from different standpoints. Expressly, attributes here are the characteristic of QTT that makes them ‘that’ QTT. That is why, review on attributes of quality tools and techniques is crucial. To collect the attributes from previous studies, researcher uses the integrated literature review where these attributes found are being summarized to establish a freshly new attributes framework but still in the same field which is the development of QTT attributes. In this paper, researcher expresses a detailed overview of various classifications of attributes that describe the quality tools and techniques and successfully exhibit the classification of QTT attributes based on 5 main group which are categorization, input, function, output, and demographic. Consecutively, this classification group of QTT attributes will be used as main items to the development of applications that are equipped with prediction system of QTT selection using a machine learning algorithm.

Work-related musculoskeletal disorders or WMSDs are most often cited in various studies related to the risk factors of repetition, application of excessive force, vibration, contact stress, and awkward postures. Lower back, neck, forearms, wrists, hands, shoulders, and elbow are the most often body areas that are affected from these WMSDs. The scientific literature shows that the best preventions from WMSDs are to reduce the exposure to the risk factors. In other words, risk factors of WMSDs should be assessed especially in the work area to ensure the workers have less interaction with the risk factors of WMSDs. The assessment of WMSDs risk factors can be placed in three categories, subjective judgment, direct measurement, and systematic observation. Based on the review, measurement is the most accurate and reliable methods to identify risk factors of WMSDs, but it required significant investment of resources whereas observation methods are the most commonly method used by the ergonomist. The observation method is easier and less costly compared to the other method in identifying the risk factors. It is also the most flexible method when it comes to collecting data in the actual site. The purpose of the study is to obtain the comparison results between the methods to identify the most effective ergonomics risk assessment in preventing WMSDs. While ergonomics practitioners, occupational therapists, employers, union workers, and health and safety authorities need information on the most effective assessment methods available for preventing WMSDs, the literature still offers little applied research that has tested these methods for comparison and lacks information on which methods are the best at preventing WMSDs. There is also no argument between the ergonomics practitioners as the best method to choose is to develop an experiment related to the task and compare the respective result.

This research studies the development of a comprehensive system that is represented as a sustainable IoT-based environment and industrial monitoring system based on applications of the wireless network. Environment pollution can cause damage to human health and causes global warming. Most pollutants are invisible to the human eye. The system created can detect pollution on early stages and as a precaution step. This system can detect the following quantities via some sensors: temperature, humidity, light of intensity, and gas. The main sensor that is attached to this product is to detect the air quality in the surrounding by giving reading values. This system is using internet of things (IoT) and the result is transferred to a phone by using the Blynk apps. After download the Blynk Apps, the position, functions, and connections must be set. The first steps are collecting data and to keep them save in the memory card. The next step is to transfer the data to a laptop by using internet of things (IoT). From the data shown at the laptop, the user identifies the status of the environment condition. This system is able to detect any pollution that occurred and can take action on early stages. In addition, the system is able to monitor the data statistically for further analysis and predict what is going to happen.

The aim of this research is to study the impact of infill design on product strength. To achieve the aim of the research, the objective of this research is to identify and select several types of infill pattern in printing a product, and to find the best parameter in printing a product for this study. The research experiment was designed using the Taguchi method L9 orthogonal array to find the best parameter on printing a strong product. The factors that were selected by referring to journals and articles to print the specimen in this research are infill pattern, infill density, and extrusion temperature. The specimen was printed and underwent impact test to find the specimen that can absorb highest impact energy to determine the best combination of parameter for this research. Minitab software was used to determine the signal to noise (S/N) ratio, main effect plot, and analysis of variance (ANOVA). S/N ratio analysis shows that the infill pattern of grid, infill density of 80%, and extrusion temperature of 240 °C is the best parameter of printing a strong product. This research concludes that infill design did influence the strength of printed material using fused deposition modelling.

This paper presents a novel approach of deriving and estimating the kinematic model of the generic configuration of a swimming mobile robot inspired by manta ray. Initially, the conventional method of mathematical model of linear and angular velocities are described, considering the kinematic model of the traverse entity on a 2-D plane. These parameters are novelly derived to represent a higher degree of motion on a complex environment. Due to the complexity of the environment, the flight dynamic stability analysis is implemented in the derivation, however, the unwanted portion is eliminated from the equation. As a result, the estimated kinematic model is characterised providing the natural performance in mobile robot applications particularly in ocean exploration. Meanwhile, the overarching concept of the proposed system is implementing the layered-architecture mobile robot control whereby the highest level control layer defines the overall perception of the environment condition. The model of the swimming trajectory within this layer and construction is using the multivariate Gaussian function. Further, the pre-planned path is projected onto the trajectory model providing a complete higher degree of freedom mobile robot kinematic equation. Simulation results are also presented which demonstrate the good performance of the proposed model under randomly generated ocean and seabed conditions.

Compressed air (CdA) has become one of the most costly utilities in a manufacturing facility. Numerous tactics are utilised to minimise energy loss and consumption when creating energy-efficient CdA systems. The systems require a multidimensional approach to energy conservation through the use of efficient compressed air generation, distribution, and application equipment. The research's initial objective is to quantify lost CdA in terms of dollars and cents. The second objective is to examine the compressed air system's performance using the SONAPHONE ultrasonic testing (UT) technology based on its auto-leak analysis. The annual cost and leakage cost of CdA were calculated using data collected from the SONAPHONE equipment.

This work develops and evaluates an Augmented Reality Instructional System for assembly support and its role in improving efficiency on manual, customized, or modular manufacturing. The prototype application is a tool designed to unite real and computer-based scenes and images to deliver a combined view of assembly with a marker-less based tracking system, the “Easy-AR”. Normally, such assembly process is conducted by referring to the manual instruction, often via printed graphics which are inefficient especially for new workers. To overcome, industries need to provide series of training sessions to develop worker skills until necessary performance is obtained. This will likely contribute to an increment of direct and indirect cost towards industries. The development of the “Easy-AR” application for assembly support prototype is hypothesized to help to enhance the efficiency and reduce errors of the manual assembly process with minimum training requirement. The prototype was tested in a controlled environment to minimize unnecessary variables. Time study, efficiency, and error of assembly process was done under assistance of the prototype while assistance of a printed manual is introduced as control. Time taken to assemble each component of a prototype was recorded and analyzed to identify the difference of efficiency and assembly quality under both situations and analyzed statistically. Based on testing on 60 participants, assembly time with the prototype reported to be improved by 38.9% in comparison with control. Furthermore, a 50% reduction of errors has been recorded with the prototype. As conclusion, the problem in industry related to the manual processes in daily tasks can be overcome by the implementation of the prototype app which is scalable, and the assembling process will be more interesting, attractive, and effective, in line with the fourth industrial revolution.

Red gypsum (RG) was used as a cement replacement material for brick in order to evaluate the performance of this waste material as a filler. A constant quantity of cement (10%) and w/c ratio of 0.45 was used in order to study the effect of replacement of sand by RG. The increase of compressive strength with replacement of sand by RG up to 25% and later showing a decreasing trend of compressive strength when further increase of replacement percentage was related to the particle size modification of the solid mix. Sieve analysis showed between 0 to 25% replacement, the percentage of fineness increases in the same grading zone. Within this region, the hardness value of the solid mix was altered, resulting in an increase in the compression and consolidation index. The increase in the compression and consolidation index is reflected from the thickness of the bricks produced from the solid mix pressing, in which the thickness of the 25% onwards sand replacement showed slightly thinner bricks with denser appearance. The findings were further strengthened with the results from the UPV analysis showing a higher velocity of doppler wave passing through the dense RG cement bricks.

Two different synthesis processes, in-situ polymerization and ex-situ polymerization process, were implied to identify the impact of these processes on the properties of the graphene oxide (GO) doped conductive polyaniline (PANi)-based electrode materials. This study focused on the improvement of various properties of PANi/GO composite materials produced through the in-situ polymerization process instead of the ex-situ polymerization process. To compare the performance of electrochemical and physical properties PANi/GO electrode materials produced via in-situ and ex-situ polymerization process, several characterization techniques were used. Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD) were performed to observe structural properties. Cyclic voltammetry and galvanostatic Charge–Discharge analysis were conducted to investigate the electrochemical properties of electrodes. Specific capacitance of PANi/GO electrodes was found 63.6% higher for in-situ polymerization compared to the electrodes prepared using ex-situ polymerization process. This high performance was governed by the proper alignment of GO into polyaniline. In the in-situ polymerization process, the interaction of polyaniline is strong with the surface functional groups of GO sheets which results in a good physical mixture between polyaniline and GO particles. In-situ polymerization technique can be effective to develop polymer-based electrode materials for high performance supercapacitors.

This research work aims to study the rheological and mechanical behavior of the natural rubber (NR)-based blends in presence of different fillers like nanosilica, zinc oxide (ZnO) and titanium oxide (TiO2). A rheometer and Mooney viscometer were used to characterize the rheology and Mooney viscosity of the blends. The tensile properties of the cured films were evaluated. Results indicated that the loading of the fillers in the NR increased the Mooney viscosity. The tensile strength of the NR was altered and varied due to the loading of the nanosilica, TiO2 and ZnO. The storage modulus and loss modulus were improved significantly due to the addition of different fillers. The effective individual and combined role of nanosilica, titanium oxide and zinc oxide as a filler were discussed elaborately highlighting the possible interaction and inter-phase relation between the NR and the fillers.

The main aim of the current study is to investigate the energy absorption response of natural fiber/epoxy composite tubes with different shapes. Three different circular lengths, i.e., 50, 100, and 150 mm were investigated experimentally subjected to axial compression tests. Hand lay-up methods were used to prepare the composite shapes. The results showed that the length factor is significantly affected on the energy carrying capacity of circular tubes reinforced by natural kenaf fiber. Furthermore, the composite tube with a length equal to 100 mm showed higher energy absorption capability with the value of 27.42 J/kg as well as average crashing load and crash force efficiency compared to other tubes.

Atmospheric plasma spraying was employed to spray agglomerated aerogel-soda lime glass powders onto Inconel 625 substrate. This paper describes the development of statistical models to predict the optimum atmospheric plasma spray (APS) operating parameters such as current (200–800 A), powder feed rate (2.5 and 5 rpm), and spray distance (8, 10, 12, and 14 cm) on adhesion strength and thermal conductivity of as-sprayed Aerogel-soda lime glass/NiCoCrAlYTa coating using historical data design of response surface methodology (RSM) from Design Expert 11. RSM is a well-organized statistical technique in forecasting variables in order to obtain the optimum operating conditions. The statistical approach used provides a high level of confidence and improves the processing. Significant effects of the process parameters on the microstructure were also observed. Optimum process conditions favourable for the formation of coating layers with the best coverage of agglomerated aerogel were statistically predicted at the current of 800 A, the powder feed rate of 5 rpm, and the spray distance of 13.54 cm with the maximum adhesion strength and minimum thermal conductivity predicted by RSM were 11.60 MPa and 10.30 W/mK respectively.

Nanotechnology can help conserve renewable resources and future ecosystems. They may help tackle various energy and environmental challenges. They will be used in bioengineering, electrical gadgets, and energy storage. This research describes novel fibrous freeze-shaping procedures for 1D polymer nanofiber cellulose fibrous, isotropically linked elastic nanofibers. This is a summary of the review. In the first part, electrospinning may significantly enhance aerogel reinforcing. Our focus will be on nanofiber network aerogels and their possible energy storage. Applicability of nanocellulose fiber aerogels follows. 3D nanocellulose aerogels will improve research chances.

Cloud computing is becoming more apparent in the realm of network technology to ensure the availability and sharing of resources through virtualization. Despite its attractiveness and benefits, the higher education institutions (HEIs) are still hesitant to implement cloud computing services due to insufficient details on issues and priorities in implementing cloud computing services. Therefore, this study aims to evaluate the factors of cloud computing implementation in HEIs, propose the cloud computing implementation model, and encourage the research community to explore more research in cloud computing implementation. By synthesizing the literature from various industries, this study proposes a conceptual model-based cloud computing implementation for HEIs and integrates it into the technological, organizational, and environmental (TOE) framework. The research methodology consists of rigorous data collection and analysis that allows for more substantive conclusions to enable viable CC-LMS operation. The Delphi technique was adapted in the data collection and judgment process. The two-round Delphi survey has been conducted with 18 (1st round) and 13 (2nd round) cloud computing technology and LMS experts from local HEIs and service vendors to assist in the judgment process. This analysis resulted in a consensus after the second round of the Delphi survey with suggestions on the high importance of several factors in implementing a cloud computing system for LMS in HEIs. Finally, the study is expected to provide HEIs decision-makers with a better understanding and guidelines of cloud computing implementation characteristics with the relevant perception of current services.

The Internet of Things (IoT) is one of the most recently emerging supply chain processes in the manufacturing industry. To receive the benefits of the IoT, the organization must be ready to adopt this new technology. Several studies have looked into the perspective of the IoT in the industrial sectors. However, IoT is still in its early stages of adoption across various industries, including manufacturing. Thus, this study aims to identify factors influencing the IoT adoption in the manufacturing industry. By using a systematic literature review on several databases incorporated with summative content analysis, we explore the important factors and propose the research model of IoT adoption for the Malaysian manufacturing industry. These articles will assist businesses in the manufacturing value chain operation in understanding the user experiences of the IoT adoption and will motivate the research community to conduct additional research in IoT adoption.

Using several types of nanofluids, such as aluminium oxide (Al2O3) and copper, this study proposes to explore the heat and mass transfer phenomena through a cylinder. To demonstrate the flow, the viscoelastic nanofluid model is combined with the energy equation. The modified main equations with specific conditions were used in this work, and model of Tiwari and Das was used. The acquired findings are numerically computed using the Keller-box approach and graphically shown to investigate the physics of relevant flow parameters. In comparison to aluminium oxide, the highest nanofluid performance was reported at copper, which significantly improved thermal conductivity and heat transfer.

The effectiveness of probiotic adaptation in delivering higher benefits effects toward users can be measured by their efficiency during the immobilization process. The immobilization process that combines between probiotic strains and its matrix that act as support system are highly highlighted area as the best combination during immobilization resulting in higher efficiency. In this research, the study was conducted to determine the ability of different microbial volumes (7.5, 12.5, and 18.75 ml) and particle size of fiber (<150, 150–250, and 250–355 µm), in effecting the immobilization efficiency between Lactobacillus plantarum ATCC8014 and palm kernel cake (PKC). The immobilization efficiency and probiotic viability of 96 ±3.21% and 9.47 ±1.00 log CFU/ml, respectively, was obtained by the volume of 12.5 ml. For 7.5 ml and 18.75 ml, the results obtained were 95 ± 4.72%, and 9.26 ± 1.09 log CFU/ml, and 97 ± 0.57%, and 9.34 ± 0.52 log CFU/ml, respectively. Increment of volume used has caused the beads produced to be inconsistent. The particle size of 150–250 µm, with immobilization efficiency and probiotic viability of 99 ± 1.73%, 9.14 ± 0.22 log CFU/ml, respectively. For <150 µm and 250–355 µm, the results obtained were 98 ± 2.31% and 9.09 ± 0.23 log CFU/ml, respectively and 9.10 ± 0.12 log CFU/ml, respectively. High immobilization efficiency range (95–99%) was obtained by the samples. High immobilization efficiency would further impact the application of immobilized microbe in many beneficial purposes and processes.

Agriculture sectors, especially maize plant farming have been widely used in our country for decades due to revolution of agriculture technologies which evolved aggressively. Thus, the production of maize plants is continuously increased in recent years. In line with the current state of technology, the internet of things (IoT) is one of the pillars outlined in the industrial revolution (IR 4.0) which potentially could be used to enhance the quality and volume of corn’s production. This technology can offer various improvements and minimize the labor’s work and to make it easier for farmers to monitor their crops online besides it could increase the corn production in each season. Thus, the purpose of this study is to develop an automated system that can monitor and control the maize plant's essential needs using the IoT application. Parameters such as soil moisture, temperature, humidity, and the environmental issues are rigorously investigated to monitor the condition of the plant. For the prototype, hardware such as Arduino has been used as the main controller to monitor the condition of the plants and interfaced with sensors. The system is designed based on a real-time monitoring where the data sensed by the sensors will produce a feedback to the controller which is known as feedback control. The controller displays the data received from the sensors using a software known as the Blynk application that is available in smartphones. Besides, the system also enables automated features such as irrigation and roofing to protect the plants from an excessive humidity and water drop. From the hardware and software testing, it is found that the prototype operated smoothly for irrigation and roofing systems.

Lights are command sources in our lives at all times and in all places. Alternative sources are vital to increase satisfaction on customer requirements as demand trends. Saving energy is another factor to consider when choosing a lighting system. As a result, this study explains the implementation of a smart lamp with a controlled light system based on Arduino and the use of a mobile application to save energy. A smart bulb is the best approach to save and conserve light by using a remote system to monitor and manage the intensity. This study developed a design for an energy-saving smart light system that works with mobile apps and devices. It is a little prototype that runs on an Arduino board and is entirely automated. The identification of the LDR sensor, PIR sensor, and circuit configuration is the first step in the design. Following that, the Arduino program, mobile application, and gadgets are integrated with hardware and software. Finally, the testing procedure is carried out, and the data is gathered and analyzed. With the scenario as a setup, the complete system has been empirically proven. By monitoring and adjusting light in such a way that it is always an exact match to the real requirement, it is possible to conserve energy and money while also improving human comfort and efficiency.

Pipelines in thermoelectric power plants run under extreme mechanical and chemical conditions that can result in catastrophic failure. Electroless nickel-phosphorus (Ni-P) coatings surpass other commercially available coatings in terms of corrosion resistance and hardness for power plant pipelines. Electroless coating deposition does not require any electricity for its operation and having a uniform coating. In the present work, Ni-P was successfully deposited on carbon steel using the electroless deposition method. Effect of coating parameters on microstructure evolution and mechanical properties were investigated by scanning electron microscope (SEM) and micro Vickers hardness test. The corrosion behavior was evaluated by hot corrosion test in Na2SO4. The results showed a noticeable improvement in the workability of the coated sample immersed in 80 °C temperature electroless deposition and 5.0 pH of Ni-P with a constant of speed, 200 rpm throughout the experiment. These findings confirm that Ni-P coating successfully coated on carbon steel, could significantly reduce the porosity percentage, increased the hardness, and lead to improvement in corrosion resistance of Ni-P coatings as compared to uncoated samples.