Emerging Advances in Integrated Technology
The Emerging Advances in Integrated Technology (EmAIT) journal is a peer-reviewed publication released twice annually—in June and December. It focuses on advancements in material science and technology, encompassing areas such as computational, digital, and management technologies. EmAIT encourages submissions that explore experimental research, modelling, simulation, and optimization within both the physical and theoretical domains of cutting-edge developments. Serving as a collaborative platform, the journal invites contributions from students, researchers, and industry professionals to share their findings at both local and international levels. Its goal is to foster innovation and facilitate the exchange of contemporary knowledge and skills that reflect the dynamic evolution of current technologies. More info
Mini Review of RF Magnetron Sputtering for Aluminum Nitride Thin Film Deposition: Scale-Up Challenges and Perspectives
Radio Frequency (RF) magnetron sputtering is a pivotal technique in thin-film deposition, renowned for its versatility and precision in producing high-quality crystalline films. This method excels in delivering uniform film deposition, high reproducibility, and adaptability for both insulating and conductive materials. Among the materials deposited using RF magnetron sputtering, Aluminum Nitride (AlN) has gained attention due to its wide bandgap, high thermal conductivity, and excellent breakdown voltage. Over the years, researchers have successfully deposited c-axis-oriented AlN films with thicknesses ranging from 8 nm to 2.75 µm, typically on small wafers (2–4 inches) at temperatures up to 900 °C. This mini-review explores the fundamentals, working principles, and application of RF magnetron sputtering for AlN thin film deposition. The novelty lies in synthesizing existing literature on RF magnetron sputtering for AlN deposition and systematically linking key sputtering parameters (RF power, working pressure, gas flow ratio, substrate temperature, target-to-substrate distance, and post-annealing) to film properties, while highlighting the challenges of scaling up to larger wafers. These insights offer a practical reference for optimizing AlN deposition at larger scales.
Copyright (c) 2025 Emerging Advances in Integrated Technology https://creativecommons.org/licenses/by-nc-sa/4.0
Development of a Smart Cooling and Fertigation System for Strawberry Cultivation in Tropical Lowland Greenhouses
Strawberry cultivation in tropical lowland regions faces major challenges due to excessive heat, high humidity, and poor root zone temperature regulation, often leading to low fruit quality and inconsistent yields. This project aims to address these limitations by integrating environmental optimization with smart agricultural technology tailored for tropical greenhouse applications. The main objective is to develop a sustainable, IoT-enabled fertigation and microclimate control system for strawberry cultivation in lowland Malaysia, focusing on improving yield, fruit sweetness, and plant resilience. A comprehensive review was conducted on critical environmental parameters like temperature, humidity, light intensity, CO₂ levels, and electrical conductivity combined with a study of recent innovations in precision agriculture. Based on this review, a prototype system is proposed featuring solar-powered chillers, automated misting, root zone cooling, and fertigation component controlled by ESP32 microcontrollers. The system includes real-time sensor feedback and wireless control to maintain optimal growing conditions. The proposed system will be developed at Politeknik Sultan Haji Ahmad Shah (POLISAS) and will be tested in a real-world setting at FELDA Bukit Sagu 2, a rural farming community in Kuantan. Preliminary simulations from review suggest a greenhouse temperature reduction of 4°C–6°C and improved root zone stability, aligning with recommended growth thresholds. These improvements are expected to enhance strawberry size, sweetness (Brix value), and shelf life. The novelty of this project lies in its context-specific combination of smart cooling and fertigation technologies in a modular, scalable design suitable for low-resource farming environments. It bridges academic innovation and practical agriculture, supported by sustainable energy integration and data-driven control. The project idea has gained early recognition in institutional R&D and is positioned for further collaboration with agricultural research bodies (e.g., MARDI), smart farming startups, and rural development agencies. With continued development, the system offers potential as a replicable model for tropical horticulture, supporting Malaysia’s goals for agrotechnology innovation and food security.
Tropical greenhouse, Smart agriculture, IoT-based cooling, Strawberry cultivation, Sustainable farming
The Effect of Kefir Incorporation on the Physicochemical and Sensory Properties of Bread
Kefir, a fermented milk beverage from the Caucasus region, is rich in probiotic microorganisms and bioactive compounds. This study aimed to evaluate the effects of kefir incorporation on sensory properties, physicochemical and microbiological bread. Commercial bread is often produced using synthetic additives such as enzymes, preservatives and chemical leavening agents to improve texture, shelf life and volume. There is growing consumer demand for more natural and functional food products. Kefir, a fermented milk beverage rich in probiotics as a natural alternative that may enhance bread quality without the need for synthetic additives. Its application in bread production is still limited and not widely explored. This study focuses on evaluating the suitability of kefir in bread formulations and its effects on the physical, chemical, microbiological, and sensory qualities of bread. This study used three bread formulations, formulation 1 (2.8% yeast and no kefir), formulation 2 (34% kefir and 1.2% yeast) and formulation 3 (48.5% kefir with no yeast). The sensory evaluation using hedonics and scoring indicated that Formulation 2 received the highest scores for aroma, taste, texture and overall acceptability. Physicochemical analysis revealed that this formulation produced bread with desirable textural attributes, including a mean hardness of 5.91 N and elasticity of 5.39 mm. Additionally, it exhibited the highest bread volume (1690 cm³) and specific volume (3.7 cm³/g), indicating enhanced leavening and crumb structure. The pH value of pH 4, attributed to kefir’s natural acidity, contributed to improved microbial stability, with microbial counts as low as Log 2.74 CFU/mL on day 7 of storage suggesting an extended shelf life. In conclusion, the incorporation of kefir at 34% in bread formulation significantly enhances textural quality, microbial safety and sensory acceptance. Kefir presents a viable alternative to conventional fermentation agents in breadmaking. This study was awarded a Gold Medal at the Research; Innovation & Product Launching held in Politeknik Sultan Haji Ahmad Shah Kuantan in 2023. This recognition highlights the innovative potential of kefir-based bread as a functional food product with high quality and commercial viability.
Biomedical, Health, Pharmaceutical and Food Technology
The automatic chicken coop cleaner is designed to sustain hygiene for small scale poultry breeders. This system is developed using an ESP8266 NodeMCU V3 microcontroller which features both scheduled and trigger remote cleaning via Blynk application supported when needed. Manual cleaning is time-consuming, inconsistent, and frequently neglected, particularly among breeders who balance poultry keeping with full-time employment or other responsibilities. Accumulated waste leads to increased moisture, ammonia buildup, and pathogen growth. Poor hygiene contributes to respiratory infections, reduced growth performance, and increased mortality. The cleaning mechanism is driven by a linear actuator and a scraper blade, programmed to operate on a fixed schedule twice daily. The prototype with dimensions of 2feet by 2feet is optimized for 5 to 10 chicks aged 1 to 4 weeks which crucial period for immune system development. The complete cleaning process involves scraper movement forward and backward and took approximately 160seconds. Execution results demonstrate reliable cleaning performance according to the fixed schedule and consistent remote responsiveness via the Blynk application and notification will be sent. Obstructions able to be detected by the system and failure notifications are sent through both the smartphone and email to facilitate timely intervention. The overall system provides a low cost, energy efficient and smart solution that improves flocks’ health, supports operational efficiency and promotes sustainable management.
A Mini Review on Edge Computing Devices for IoT Systems
Edge computing is a transformational distributed computing paradigm that brings computers and data storage closer to IoT data sources, overcoming critical limitations of cloud-centric approaches such as excessive latency, bandwidth constraints, privacy concerns, and energy inefficiency. This review examines the fundamental requirements of edge computing devices for IoT, exploring essential characteristics including processing capabilities (through microcontrollers, microprocessors, and AI accelerators like GPUs, TPUs, and VPUs), energy efficiency mechanisms, ultra-low latency solutions, connectivity options (LoRa, Wi-Fi, BLE, 5G), and robust security frameworks. Current challenges in designing edge computing for IoT applications include benchmarking difficulties due to a lack of standardized metrics, severe resource constraints, security vulnerabilities in distributed networks, scalability issues in dynamic environments, and limited real-time adaptability with pre-trained models. Emerging technologies such as federated learning, 6G connectivity, TinyML innovations, and sustainable design approaches show significant promise for improving edge computing efficiency. The findings reveal that edge computing has profoundly impacted IoT development by enabling real-time processing and decision-making across industries, enhancing data privacy, improving energy efficiency, and facilitating AI integration into resource-constrained environments, while continuing research focuses on addressing persistent challenges in scalability, security, standardization, and sustainable deployment.
Polymer Mixed Matrix Membrane with Biosynthesized Zinc Oxide/Silver Oxide Additive for Antibacterial Performance
Membrane technology has emerged as one of the most effective approaches for water purification, utilizing pore separation to achieve filtration without the complexities and high energy consumption associated with the traditional methods. Recent advancements have focused on modifying polymeric membranes, particularly polysulfone (PSf), by incorporating inorganic additives such as zinc oxide (ZnO) and silver oxide (AgO) nanoparticles. Thus, in this study, polymer MMMs were fabricated by incorporating biosynthesized ZnO/AgO synthesized from tea leaf extract as a reducing agent with the aim of enhancing membrane characteristics and antibacterial properties. The results showed that the antibacterial properties were enhanced by the addition of additives, particularly at higher concentrations of ZnO along with the presence of AgO. Other characteristics such as morphology, surface roughness, porosity, and hydrophilicity also produced the same increasing trend. These results proved that the addition of additives was able to enhance MMMs capabilities especially in terms of antibacterial properties.
Heat Transfer Enhancement in Single Heat Exchanger 2D Pipe Using Rod with Different Angles Based on Computational Fluid Dynamics Study
The current numerical study focuses on the statistical investigation of the airflow and the improvement of the heat transfer rate by forced convection of a single pipe in a heat exchanger by the inclusion of a rod. Using the finite volume method by numerical simulation the flow characteristics of the working fluid with enhanced heat transfer are numerically studied. Homogeneous heat flux is applied to the upper and lower walls of the pipe. More for the Reynolds number range (9000-18000) the effect of inserting a rod inside the tube at different oblique angles (40°,50°, and 60°) was examined. Numerical results revealed that the transfer coefficient rate (Nusselt number) increase in the tube inserted into the rod is higher compared to the normal pipe. In addition, the results also showed that when the angle of inclination of the rod in the single-pipe heat exchanger is gradually increased the Nusselt number increases. The Nusselt number maximum value was shown at the 60° angle of the rod insert. Because of the resistance of a bigger flow, the friction factor was found by using the rod inserts at (60°) and pitch distance (0.04 m). For a minimum slant angle of (40°) and a pitch distance of (0.04 m), the maximum value of the performance evaluation criteria (PEC) was stated. In comparison to the smooth tube, the percentage of fluid velocity distribution rises by (50,57, and 63%) at the angle of inclination of the rod (40°, 50°, and 60°), respectively
Simulation Study of n-type Double-Gate Nano-MOSFET with Arbitrary Wafer Orientations and Any Channel Materials
In this paper, the technique for quantum mechanically simulating a double-gate (DG) nano-MOSFET with arbitrarily oriented wafer directions and various channel materials is presented. The problem with arbitrarily oriented wafer directions and any channel materials is that the misalignment of principal axes of conduction bands ellipsoids and devices axes causes the matrix and so effective mass equation (EME) become cumbersome to solve. This drawback is overcome by transforming the main axes of the conduction band ellipsoids of the nano-MOSFET to align properly with the device axes, that are transport, confinement and width directions. This transformation technique is discussed theoretically, generally and then simulated specifically for a 10 nm n-type DG nano-MOSFET designed using Silicon (Si) wafer orientation of (100) direction. Two current-voltage (I-V) equations are derived and the calculated on-state current value, are compared with theoretically simulated data 2.500x103 µA/µm. The first and second current model produce of 2.182x103 µA/µm and 2.548x103 µA/µm, respectively. The second model is more accurate since it treats the electron flow as ballistic. This transformation technique enables device engineers to use any device simulator with EME model to study the carriers transport properties of MOSFET with any channel materials (Si, Ge and GaAs) and arbitrary wafer orientations ((100), (110) and (111)). This paper focuses specifically on Si with (100) wafer.
Semiconductor Devices Modelling and Simulation
A Comprehensive Review of Network and Communication in IoT Systems
The Internet of Things (IoT) represents a transformative domain in technology, integrating devices equipped with sensors, software, and connectivity to enable data exchange and automation. This paper discusses IoT networks and their communication protocols, highlighting applications across smart homes, industrial settings, and agriculture. It explores core technologies such as Wi-Fi, Bluetooth, Cellular (4G/5G), and LoRa, emphasizing their advantages and limitations. The layered IoT architecture, from perception to application, is reviewed, detailing its impact on system performance. Challenges related to energy consumption, security, and scalability are also addressed. Key findings underscore the importance of tailored communication solutions and integrated protocols for optimized IoT performance.
IoT network and communication, Wi-Fi, Bluetooth, 5G, LoRa.
Gait Analysis for Walking on Flat Footwear and High Heels
Gait analysis has transformed traditional methods of studying human locomotion by enabling precise monitoring and real-time analysis of critical biomechanical parameters. The purpose of this project is to design a portable gait analysis system as a prototype to evaluate the effects of different footwear on walking dynamics. The acceleration sensor was implemented into a wearable device to collect data and analyze gait variations between walking in flat footwear and high heels. The system monitors angular velocity, acceleration, and an-gles across three axes (x, y, and z). Key features of this system in-clude its ability to record motion data in real time using the WitMotion mobile application. The application visualizes gait parameters, enabling users to identify and understand how different footwear impacts balance, posture, and muscle activation. This portable and user-friendly device offers an accessible alternative to traditional gait analysis tools, making it suitable for individuals, clinicians, and researchers. The resulting system is a practical solution and a cost-effective innovation that bridges the gap between advanced gait analysis and real-world applications.
Performance Comparison of Machine Learning Models for Phishing Website Detection based on Multilayer Perceptron
Phishing is a common cybercriminal activity in which attackers lure people into providing data by posing as genuine websites. Currently, alerts and blacklists are well-used methods of detection though they have been proven less effective in the evolving types of phishing. This paper focuses on the impact of a Multilayer Perceptron (MLP) in minimizing the deficiencies of conventional techniques as a tool of identifying phishing websites. The goal is to improve the identification of new and initially unseen phishing sites by building upon MLP capability to resolve multiple relationships between webpage characteristics including URL, HTML, and HTTP properties. The given experiment is conducted on a total 500 phishing and 500 legitimate websites through different machine learning classifiers such as SVM, k-NN, Decision Trees, Naïve Bayes, and MLP using both 5 and 10-fold cross-validation. The performance of the models is measured using commonly used measures these include accuracy, precision, recall, and F1-score with the MLP having the best performance with 98.1% accuracy. This analysis shows that MLP is the best in improving the detection of phishing threats with the best scalability and adaptability in fighting phishing attacks. Hence, this paper reveals that MLP has a great capacity to enhance real-time phishing detection and minimize false alarm rates to afford a reliable defense against one of the constantly evolving cyber threats.
Forecasting Malaysian Tourist Arrivals in Thailand from 2024 to 2027 using the Holt-Winters Method
This study employs the Holt-Winters method to forecast Malaysian tourist arrivals in Thailand from 2024 to 2027. Two approaches were compared: one utilizing monthly tourist data from 2013 to 2023 and the other excluding figures from 2020 to 2022 due to the COVID-19 pandemic's impact on tourist numbers. Evaluation metrics include Mean Absolute Scaled Error (MASE) and Mean Absolute Percentage Error (MAPE). The findings reveal that the second approach, accounting for the pandemic's effects, yields superior forecasting accuracy compared to the first. By excluding these abnormal years, the forecasting model can offer more accurate estimates by reducing the impact of temporary disturbances caused by the pandemic. This strategy improves the model's capacity to forecast future tourist arrivals with increased accuracy and certainty, aiding in strategic decision-making and resource allocation within the tourism sector.
Holt-Winters, Mean Absolute Scaled Error, Mean Absolute Percentage Error, COVID-19
Navigating Digital Transformation in Rural Banks: A Study of Critical Success Factors in Indonesia
Digital transformation (DT) has become imperative for rural banks in Indonesia to enhance efficiency and customer service in response to evolving market demands and technological advancements. This study investigates the factors that influence successful DT implementation in rural banks, focusing on three banks in Indonesia. Through Structural Equation Modeling (SEM) analysis, leadership emerged as a critical factor significantly impacting DT implementation, emphasizing the need for digital-oriented leadership to drive digital initiatives effectively. Additionally, resource allocation and technology adoption were identified as the key drivers of successful DT implementation. These findings underscore the importance of fostering digitally oriented leadership, enhancing employee skills, and reallocating resources effectively to support DT initiatives in rural banks. Moreover, adapting organizational structures and processes to align with digital transformation goals is crucial for rural banks to thrive in an increasingly digital landscape, ultimately enabling them to enhance competitiveness, improve customer service, and achieve sustainable growth.
Digital transformation, Structural Equation Modeling, Rural banks
An Analysis of Logistic Cost Structure in Corn Commodity Supply Chain (Zea Mays L) in East Java Using Activity Based Costing (ABC) Method
East Java is Indonesia's biggest corn producer in 2022, with a percentage of 26,24. The El Niño phenomenon of 2023 caused a decrease in corn production in Indonesia. El Nino phenomenon in non-farming land can add logistic costs, especially in procurement. The goal of the logistic cost structure analysis is to determine the proportion of logistic costs. This research was conducted in three regencies in East Java, a representative of the corn producer centre. A total of 98 respondents were included in the study. The research sample was selected based on convenience sampling and snowball sampling. The Activity Based Costing (ABC) method calculates the logistic-cost structure. The structural analysis of logistic costs used descriptive statistics. The analysis of the logistic cost structure showed that the most significant proportion of logistic cost was procurement activity, with a percentage of 63,09%. The activity at the farmers' tier with the most significant cost proportion was procurement activity, with a percentage of 69,73%. Transportation was the activity with the most considerable logistic cost proportion in the collector trader and large trader tiers, with proportions amounting to 52,31% and 83,01%. The right supply chain strategy for corn commodities in East Java was push-based.
Activity Based Costing, Corn, Logistic Cost, Supply chain
Formulation of B2B Strategies for Steel Structure Product at a Construction Company in Domestic Market
The company that will be discussed is one of those engaged in Indonesia’s construction industry. Because demand in foreign markets has decreased, this construction company is currently moving its target market to the domestic market with its main product in the form of steel structures. Based on sales data, the profit margin tends to be very small when compared to the increase in sales volume. The purpose of this study is to identify the main causes of the low annual profit of steel structure products in the domestic market and to formulate appropriate alternative strategies based on the company’s condition. The methods used in this study were Porter’s five forces, paired comparison, IFE, EFE, IE, SWOT, and QSPM. The results of the analysis show that the cause of the low annual profit of steel structure products is intense competition in the industry and the strong bargaining power of buyers. The SWOT matrix produces five alternative strategies, which are synthesized into three strategies, and in order of priority based on the QSPM matrix, the price adjustment strategy, the expanding market share strategy, and lastly, the maintaining loyalty strategy.
Steel, Porter’s five forces, construction
Comparative Evaluation of Diabetic Retinopathy Detection Using VGG-16 and ResNet-50 Models: Insights from Matthew’s Correlation Coefficient and Cohen’s Kappa Metrics
The diagnosis of diabetic retinopathy utilizing artificial intelligence is a subject of debate, particularly involvement of convolutional neural networks (CNN). This article employs VGG-16 and ResNet-50 models for the diagnosis of degrees of diabetic retinopathy by analyzing the common retinal features of diabetic retinopathy, which are microaneurysms, hemorrhages, macula oedema, and exudates. The datasets from the APTOS 2019 Blindness Detection fundus images, which were resized to 224×224 pixels, are used for model training to prevent overfitting and processed via yCbCr color filter to emphasis on the image brightness for ease of diagnosis and evaluation. The evaluation results were determined by the metrics of Matthew’s Correlation Coefficient (MCC) and Cohen’s Kappa, both capable of handling imbalanced data, ensure reliable agreement with true labels, and provide balanced insights into the model’s predictive accuracy. The findings revealed that the VGG-16 performed better than ResNet-50 via measurement of Matthew’s Correlation Coefficient in classifying images in a balanced manner, while ResNet-50 performs better than VGG-16 according to values of Cohen’s Kappa thanks to the deep layers of the model.
Vending Machine for Enhancing Healthcare Access
This project addresses challenges in pharmacy access and feedback mechanisms for vending machine utilization by developing an advanced healthcare vending system. The system integrates RFID technology and an Arduino Mega microcontroller to enable secure dispensing and a conceptual RFID-based payment system. Additionally, an MIT App was developed to provide customer assistance. The methodology involved designing and assembling the vending machine's mechanical and electrical components, programming the Arduino Mega, and testing the system. Results demonstrated robust RFID tag detection at 100% within 1.0 cm, declining accuracy at greater distances, and product vending accuracy ranging from 70% to 90% across slots. These findings highlight the potential of the system to enhance healthcare accessibility through reliable dispensing technology. Future improvements include IoT-based real-time inventory tracking for stock and expiration monitoring and implementing a Telegram bot for intelligent inventory management.
Wind Energy Control Technologies for Power Quality Improvement on a Microgrid-A Review
This paper focuses on the development of wind energy control technologies in hybrid energy systems, highlighting their crucial role in integrating renewable energy sources on a microgrid. It examines the wind turbine curve, a fundamental framework for wind turbine operation, and the challenges and possibilities of integrating wind power into renewable energy systems, various methods to improve the efficiency and stability of wind turbines, with wind turbine control methods as the cornerstone. The study also examines the qualities of advanced wind turbine controllers, highlighting their efficiency in using wind energy resources and investigates wind energy conversion systems (WECSs) electrical generators, highlighting current developments that promise increased energy production and system dependability. The aim is to contribute to the ongoing discussion on wind energy control technologies by utilizing various cutting-edge studies. The study aims to provide valuable insights and views that can guide the energy industry toward a sustainable and environmentally friendly future through a comprehensive assessment of these crucial components.
Wind energy control, Hybrid energy system, Wind turbine controllers, Efficiency, Energy industries
Comparative Study Infused Mechanism Among Absorbance Materials to Improve Plant Growth
Agriculture is the practice of cultivating land, growing crops, and raising livestock for human consumption. The purpose of this experiment is to assess how successful zeolite, charcoal, and kaolin are as slow-release fertilizers by investigating the adsorption performance of zeolite as a nutrient-uptake agent using various samples. This paper discussed the three absorbents when infused with the fertilizer towards plant growth potentially for soil quality, conservation of water, and nutrient consumption. Since the infused absorbent shows the best quality in the retention of water and nutrients, it enables it to collect hazardous substances quickly and efficiently from environmental pollution. The mixture of the sample contains 80 grams of soil and 5 grams of infused zeolite, charcoal, and kaolin for planting green beans. Absorption and fertilizer testing were performed to see the physical properties of infused absorbent samples. In conclusion, the ability of zeolite and kaolin to retain nutrients was performed the best while charcoal slightly displayed growth of the plants as shown by the result of the height, length of leaf, pH level, and humidity of the soil.
Zeolite, Charcoal, Kaolin, Absorbent, Infused, Absorption, Hydrochloric Acid (HCL), (NaOH) Sodium Hydroxide
Zeolite Synthesis from Natural Kaolin: The Effect of Metakaolin Heating and Transformation
In this study, the effect of kaolin heating and metakaolin transformation on zeolite synthesis was investigated. Two different metakaolin temperatures at the early stage of transformation were chosen in determining the lowest temperature that was capable of synthesizing the zeolite structure from natural kaolin. The synthesis of zeolite materials from the transformation of natural kaolin to metakoalin was conducted through the hydrothermal method. Natural kaolin obtained from Ipoh, Perak, was calcined at two different calcination temperatures of 600°C and 650°C. Metakaolin was obtained after 2 hours of exposure at 600°C and 650°C, respectively, with slightly different FTIR peaks of quartz at both temperatures. The incomplete metakaolin formation at a slightly lower temperature revealed the unsuccessful zeolite formation. At slightly higher calcination temperatures, the metakoalin peak obviously existed and led to the formation of the complete zeolite phase. This experiment also proved the importance of accurate calcination temperature in converting to zeolite synthesis. Furthermore, this current work also revealed that the complete transformation of metakoalin that can be conducted slightly lower temperature as compared to the common metakoalin phase will minimize energy consumption during the zeolite synthesis as well as the metakoalin transformation.
Zeolite, Synthesis, Acidic plant extract, Hydrothermal method
Copyright (c) 2024 Emerging Advances in Integrated Technology https://creativecommons.org/licenses/by-nc-sa/4.0
The Extraction of Organic Silica from Agricultural Waste: A Mini Review
Inorganic silica precursors, also known as alkoxysilanes, have been used commercially in many applications and synthetizations. However, it has been reported that these inorganic silicas can harm human health, causing stomach, bladder, and kidney failure, as well as death in the case of an acute inhalation. Due to this reason, organic silica from agricultural waste such as coconut husks, corncobs, sugarcane bagasse, rice husks, and bamboo leaves is being reviewed as an alternative source to replace the risky inorganic silica. This work discussed the extraction method, silica percentage obtained, and applications involving the use of organic silica, demonstrating that green waste can replace inorganic silica and provide good value to society. Inorganic silica precursors, also known as alkoxysilanes, have been used commercially in many applications and synthetizations. However, it has been reported that these inorganic silicas can harm human health, causing stomach, bladder, and kidney failure, as well as death in the case of an acute inhalation. Due to this reason, organic silica from agricultural waste such as coconut husks, corncobs, sugarcane bagasse, rice husks, and bamboo leaves is being reviewed as an alternative source to replace the risky inorganic silica. This work discussed the extraction method, silica percentage obtained, and applications involving the use of organic silica, demonstrating that green waste can replace inorganic silica and provide good value to society.
Agricultural waste, Organic silica, Extraction, Thermal treatment, Chemical Treatment, Sol-gel
The Smart Aquaponic System Integrated with Internet of Things Technology
Aquaponics is a sustainable plant method that combines aquaculture (fish life) and hydroponics (soilless plants) in a closed cycle. To achieve optimal results, aquaponics requires a robust water cycle and meticulous maintenance, including monitoring temperature, environmental air humidity, and plant media humidity, among other factors. The current aquaponics system still relies on manual methods for monitoring, lacking an integrated system to handle this care function. Therefore, we developed this product to address these issues by concentrating on creating intelligent aquaponic systems that integrate the Internet of Things, enabling users to track necessary parameters. Additionally, the system automates tasks like irrigation and fish feeding schedules. In this development, the researcher employed the 7-phase Engineering Design Process (EDP) model, which includes the following stages: (1) defining the problem, (2) conducting research, (3) developing a solution concept, (4) constructing a prototype, (5) constructing a product, (6) conducting a product analysis, and (7) improving the product. he BBC micro:bit microcontroller as the main controller and the ESP01s WiFi module as the component that allows interaction with ThingSpeak. Next, the researcher used several types of sensors, such as DHT11, HC-SR04, capacitive soil moisture sensor v1.2, DS18B20, and actuators such as a DC water pump motor and a FS90 180-degree servo motor. As a result, the researcher successfully met the set objectives, including the design, development, and testing of the product's functionality, and the product performed as expected. Finally, according to experts, this product's weakness is that it requires the addition of a humidity sensor installed on each plant pot, which is recommended for further study due to limitations on the microcontroller's I/O pins.
Revolutionizing Infrastructure: A Review of Self-Healing Concrete for Longevity and Resilience
A number of characteristics of autogenous and autonomous healing concrete are examined in this review, including their characterization, processes, and performances. It has been discovered that mineral admixtures, fibers, and self-contained methods including shape memory alloys, capsules, and microbial technologies are effective at repairing fractures. This review posits that autonomous procedures exhibit superior efficacy in fracture repair compared to autogenous methods. Furthermore, the selection of self-healing methodologies and agents is significantly influenced by crack geometry and size. Also under investigation are the effectiveness of biomimetic materials, including capsules, shape memory alloys, and self-healing concrete derived from microorganisms. Finally, current research gaps and the scope of prospective research are identified and discussed.
Seismic Performance Assessment for Serviceability of Geosynthetic Reinforced Embankments
Embankments in the field of civil engineering were historically not given much attention in terms of their ability to withstand seismic activity, as they were considered to be non-critical structures. However, in recent years, the seismic stability of embankments has gained increasing importance in the field of geotechnical engineering. This increased significance is due to the need to quickly restore functional infrastructure after earthquakes. The occurrence of lateral spreading, resulting from foundation liquefaction, is the primary factor leading to embankment distress in geotechnical engineering during seismic events. To address this issue, this study presents a novel approach that employs geosynthetic basal reinforcement. The research paper presents a technique that uses geosynthetic basal reinforcement to manage the lateral spreading of embankments both pre and post earthquakes, guaranteeing their ongoing effectiveness. The proposed approach utilizes a pseudo-static limit equilibrium method for determining the tensile load produced in the basal reinforcement. The serviceability criteria establishes the maximum strain permitted in the basal reinforcement by imposing a restriction on the horizontal movement of the embankment toe. By taking into account the tensile load of the reinforcement and the maximum allowable strain, it is feasible to establish an appropriate geosynthetic reinforcement that considers various factors including tensile strength, strain, design life, installation, and durability impacts.
Experiencing In-Vivo Dosimetry Verification in Malaysia: A Patient-Specific EPID-Based Approach
Real-time dosimetry is crucial for patient-specific quality assurance in radiotherapy facilities across Europe, and the same demand extends to advanced countries like Malaysia. Our study aimed to assess the need for in vitro diagnostic (IVD) testing in Malaysia, exploring the use of Electronic Portal Imaging Device (EPID)-based dose verification to simplify complex methods. In this research, we assessed the accuracy of in-vivo dose reconstruction using EPIgrayTM (DOSIsoft, Cachan, France) for 20 cohorts of patients who underwent breast and prostate Intensity-Modulated Radiation Therapy (IMRT) and Volumetric Modulated Arc Therapy (VMAT), and compared the results with the dose calculated by the Treatment Planning System (TPS). Initially, we set a default tolerance level of 7-10% for dose acceptance. Our study found that the majority of patients in the cohort met the 10% tolerance level when validated with EPIgrayTM in vivo dosimetry. Specifically, 12 out of 15 patients who underwent VMAT treatment were within this tolerance range. Additionally, for IMRT treatment, 4 out of 6 patients achieved the 10% tolerance level. These initial findings demonstrate the potential of EPIgrayTM as a valuable tool for verifying in vivo dosimetry for advanced treatment techniques. For VMAT plans, more than 85% of the points were in agreement with the 10% tolerance level for 11 out of 15 patients. For IMRT plans, more than 90% of the points met the set tolerance level for 4 out of 15 patients. By understanding the agreement and variability of EPID-based IVD, we can further refine the utilization of EPID-based IVD as a relevant tool in ensuring accurate and reliable dose delivery during radiotherapy treatments.
The Potential of Gold Nanobipyramids as Anti-Fungal for Dermatophytes Fungi at Living Animals
Dermatophytes are a group of fungi that cause dermatophytosis, a type of skin infection affecting both humans and animals. While dermatophytosis is typically self-limiting, it can pose significant challenges for individuals with weakened immune systems. Additionally, current treatment options for dermatophytosis have their limitations, including issues of toxicity, inefficacy, and the emergence of drug-resistant strains. Recently, nanotechnology-based approaches have emerged as a promising strategy to overcome the drawbacks of conventional antifungal medications. Gold Nanoparticles (GNPs) have demonstrated substantial antifungal activity against various fungal species, including dermatophytes. Among these, Gold Nanobipyramids (GNBPs) exhibit unique physicochemical properties that enhance their effectiveness against dermatophytes. Gold Nanobipyramids (GNBPs) were synthesized using the Seed-Mediated Growth Method (SMGM) due to its simplicity. Optically, GNBPs displayed plasmonic peaks at 1.548 (wavelength 561 nm) and 2.372 (wavelength 807 nm). Structurally, intensity peaks at 38.15° (plane 111) and 44.49° (plane 200) were identified. GNBPs has surface density ~70.227±0.530. In the dermatophyte treatment process, GNBPs exhibited varying inhibitory effects. At 40% concentration, fungal growth persisted, with surface density similar to the no control area. At 60%, inhibition occurred, though less efficiently. The most effective inhibition was observed at 80%, and complete inhibition was achieved at 100% concentration. GNBPs proved successful in inhibiting fungal growth, attributed to their curvature and sharp edges interacting with microbial cell membranes, leading to membrane damage and cellular content leakage.
IoT Based Irrigation and Fertigation System for Smart Smallholder Farming Application
Integrating Internet of Things (IoT) technology with irrigation and fertigation systems has transformed traditional farming methods by enabling reliable monitoring and control of critical environmental parameters. This project aims to design an automated irrigation and fertigation system as a prototype to reduce water waste and monitor the pH level in the soil, temperature, soil dryness, and detection of intruders. Sensors strategically placed throughout the system monitor and control these elements. This system has several important features, including the ability to automatically control water pumps to maintain proper hydration levels, detect intruders within a range of one to six meters of the plant by using the Blynk app, and monitor pH levels through the same app to ensure appropriate neutral levels. Automation and control features are also assessed to confirm that sensors, pumps, and other components precisely respond in line with predetermined requirements. This evaluation helps to determine the overall health of the farmed plants as well as the effectiveness of the system. Finally, the irrigation and fertilizing system for the targeted smallholder farming area has been developed. The resulting smart irrigation and fertigation system is not only a practical solution but also an effective alternative to modern agricultural methods.
Lightweight rPPU Eco-block Using Recycled Plastic (rP) and Polyurethane (PU) for Soft Subgrade Soil Stabilisation
The stability of soil plays a crucial role in the safety and longevity of various civil engineering structures. However, problematic soil conditions, such as clay soil and peat soil, often pose challenges due to their high-water content, poor strength, low bearing capacity, and high compressibility. This research focuses on addressing these challenges by utilizing lightweight fill materials as an effective solution for backfilling applications. The study aims to investigate the characteristics and performance of a novel lightweight fill material using recycled plastic (rP) and polyurethane (PU) known as rPPU ecoblock. The eco-block is mainly fabricated using recycled plastic bottles, recycled plastic packaging, and polyurethane, offering a sustainable approach to waste management and construction materials. To achieve the research objectives, a series of experiments will be conducted. The strength and density of plastic bottles filled with recycled plastic packaging will be analyzed, providing insight into their mechanical properties. Furthermore, the water absorption and buoyancy of the lightweight rPPU eco-block are evaluated, considering its suitability for various construction scenarios. The research findings contribute to the understanding of the physical and mechanical characteristics of the rPPU eco-block, providing valuable information for its potential application as a backfill material. The compressive strength, water absorption, and buoyancy test conducted per ASTM standards provide quantitative data on the eco-block's performance. The use of lightweight fill materials, particularly the rPPU eco-block, offers benefits such as reduced embankment self-weight, improved stability, and minimized environmental impact. Moreover, the recycling of plastic waste contributes to the circular economy and aligns with sustainable development goals (SDG): SDG9 and SDG11. The results of this research provide valuable insights for engineers, construction professionals, and stakeholders involved in geotechnical and civil engineering projects.
Robotic Bartender Control Using DC and Servo Motor with The Aid of Rectifier as Power Source
The project builds a design and implement of robotic bartender prototype using rectifier as power source embedded with digital voltammeter display to monitor supply voltage and current of load used. The usage of robotic bartender in the market make ease to the worker staff in food and beverage industries so that they can prepare drinks to customer in short amount of time. For this paper, the design of robotic bartender is implement using 3D printed components and use Arduino UNO as microcontroller to control input signal of rotary encoder and switches to commodore DC motor rotation and servo motor deflection. The prototype of robotic bartender will be constructed, programmed with C language, circuit tested with Proteus simulation software and hardware will be tested by using tachometer laboratory equipment for speed testing. Lastly the overall system is powered by rectifier with embedded digital voltammeter display for convenient use.
Enhancing Heart Disease Classification: Performance Evaluation of the Machine Learning Model
Heart disease, mainly caused by coronary artery disease, poses a significant health challenge by impeding oxygen-rich blood flow to the heart muscle. Addressing this, our study utilizes a dataset of 1,026 cases from Kaggle, focusing on the application of MultiLayer Perceptron (MLP) in diagnosing heart conditions. This dataset, rich in attributes indicative of heart disease, comprises 14 variables with the class variable determined by 13 attributes acting as the focal point for disease classification. Our methodology involved applying various machine learning algorithms, with a particular emphasis on the MLP model, to categorize cases into diseased or non-diseased. The MLP model demonstrated superior performance, achieving an accuracy of 92.39% (AUC = 0.923), and outperforming several comparative techniques in terms of precision, recall, and mean squared error (MSE). The analysis of the dataset under this model revealed insightful patterns and trends, underscoring the effectiveness of MLP in heart disease diagnosis and potentially guiding future research in medical diagnostics.