Journals of Universiti Tun Hussein Onn Malaysia (UTHM)
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Design of High Efficiency Class E Power Amplifier Utilizing 0.18-µm RF CMOS Technology for 5G Network
Get PDFThe design of high-efficiency class E power amplifiers faces challenges due to low transistor breakdown voltages, high parasitic capacitances, and limited quality of on-chip passive components, which reduce power efficiency and linearity. Existing solutions offer moderate efficiencies but often require complex trade-offs that are not ideal for high-frequency applications. This research aims to optimize a class E power amplifier design to achieve higher efficiency and output power for 5G newtork, addressing these limitations while maintaining performance suitable for modern wireless communication systems. This paper proposed a high efficiency class E PA for 5G network. The proposed PA is implemented using the 0.18-µm RF CMOS process technology, and the circuit is designed and simulated using Cadence software. The proposed PA consists of a power stage and a driver stage. The power stage and the driver share a single source. The simulation results show that at input power of 0 dBm and supply voltage of 1.8 V, the proposed PA demonstrates a maximum peak power added efficiency (PAE) of 55 %. Meanwhile, a maximum output power (Pout) of 13.1 dBm is delivered by the proposed PA. Since the PA exhibits a stability factor (K value > 1), it is unconditionally stable. In addition, the PA achieves s-parameter of S11, S22 and S21 performances of -13.8 dB, -29.3 dB and 19.7dB, respectively. Furthermore, the layout of the proposed PA is 1.82 mm2 including the pads.
Performance Evaluation of Different Classification Algorithms Applied for Identifying Maternal Nutritional Status by Anthropometric Measurements
No full textPregnancy significantly influences infant quality and development. Maternal monitoring, indicated by body mass index (BMI) and mid-upper arm circumference (MUAC) measurements, reflects a country\u27s socioeconomic development. Improper measurements heighten the risk of chronic energy deficiency (CED) in pregnant women and low birth weight (LBW) in infants. This study leverages artificial intelligence (AI) to enhance the detection process. Specifically, it evaluates the prediction performance of various classification methods: Decision Tree (DT), K-Nearest Neighbors (KNN), Logistic Regression (LR), Naive Bayes (NB), Random Forest (RF), and Support Vector Machine (SVM). Using interviews in Jombang District, Indonesia, these methods were expected to identify maternal nutritional status. The model design was divided into two stages: MUAC estimation generated binary classes, and BMI estimation generated multiple classes. The evaluation of these methods included various performance metrics: Accuracy (Acc), G-means, Sensitivity (Sens), Specificity (Spec), Positive Predictive Value (PPV), and Negative Predictive Value (NPV). Based on the results, all methods are proposed for both classifications, except KNN on multiple classification. KNN achieved significant scores in all matrices with p<0.01. KNN\u27s performance is impacted by data imbalance. The study revealed a strong correlation (0.92 coefficient) between BMI and MUAC variables. The application of ML algorithms in detecting maternal nutritional status can significantly enhance the effectiveness and efficiency of health facilities, especially in areas with inadequate resources and medical personnel. However, exploring diverse ML algorithms is recommended to find optimal approaches for more varied data and to contribute solutions for sustainable development in the country.
Characterization of Clays from Adamawa State, Nigeria, for 3D Printing Applications
No full textThe Sustainable Development Goal 6 aims to ensure availability and management of sustainable water and sanitation, and this is particularly poignant for rural communities that rely heavily on sources such as streams, rivers, hand dug wells and in rare cases boreholes. In Nigeria, only a fraction of the population use improved drinking water sources and sanitation facilities. This makes access to safe and clean drinking-water in the rural areas of Nigeria practically impossible, leading to several health complications. This plays a significant role in diarrhoea related cases in Nigeria, in both adults and children. This research assessed the viability of locally sourced clay from Adamawa State as candidate material for 3D ceramic printed water filter. The assessment involves testing the physical, microstructural and mineralogical properties of the local materials obtained from different areas of the State. A prototype water filer was developed following geometric designs in Autodesk Fusion 360, and trial mix designs of composite materials using 3D printing extrusion process. The result indicates that the clays satisfied minimum plasticity requirements and exhibited satisfactory extrusion property. Heavy metals were not detected in all the clay materials, and composition displayed high amounts of silica and alumina content. The application of 3D printing technology will go a long way towards improving state-of-the-art and refinining the process as well as provide real time opportunity for correcting and editing flaws detected at each stage of prototype development as oppose to the traditional pottery process.
Development of a Mobile Application for Building Maintenance by Implementing Augmented Reality Technology
No full textBuilding maintenance procedures are currently inefficient, which emphasizes the need for more creative and efficient solutions. In order to improve maintenance operations, the present study aims to develop a functional testing of a mobile application that combines Building Information Modelling (BIM) and Augmented Reality (AR). The development process was tested using Autodesk Revit to produce 3D models that included comprehensive equipment and building material specifications. Subsequently, the AR component of the application was developed using Unity Hub in conjunction with the Vuforia Software Development Kit (SDK). Alpha and Beta testing were deployed and tested in Android devices comprising two key phases. The application showed 100% operational stability with all features functioning as intended throughout alpha testing, which comprised internal evaluations to confirm functionality, stability, and usability. The System Usability Scale (SUS), which consists of 10 Likert-scale questions assessing user confidence, ease of interaction, and perceived usefulness, was used in beta testing to gather end-user input. Beta testing confirmed the system’s effectiveness, with an average SUS score of 72.5 and 90% of users reporting that the application is easy to learn and use. The study demonstrates that integrating AR with BIM in a mobile application fundamentally enhances building maintenance by streamlining processes. This study offers a solid foundation for further research and development and shows how combining AR and BIM might enhance conventional building maintenance
A Comprehensive Review of Network and Communication in IoT Systems
No full textThe 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
Analysis of MgFeCu-Layered Double Hydroxides with Different Interlamellar Anions for Efficient Removal of Dye in Wastewater Treatment
No full textSynthetic dyes, widely used in industries like textiles, leather, and paper, pose a significant global concern for water pollution due to their resistance to conventional wastewater treatment, causing toxic, carcinogenic, and mutagenic effects, endangering aquatic life and disrupting natural processes like photosynthesis. The study analyzes the adsorption of as-prepared MgFeCu-LDH with varied interlamellar anions (CO₃²⁻, SO₄²⁻, NO₃⁻) on dye wastewater, utilizing advanced techniques like Scanning Electron Microscopy (SEM) and X-ray Diffraction (XRD) to identify LDH morphology and crystal structure, elucidating dye removal mechanisms. The methods and materials used in this study include synthesizing MgFeCu-Layered Double Hydroxides with various interlamellar anions using co-precipitation and involved weighing 50 mg of LDH and 30 ml of dye solution, equilibrating samples, and analyzing UV analysis and storage to determine the amount of adsorbed MO in the supernatants, followed by adsorption kinetic studies to evaluate the efficiency and mechanisms of dye removal from wastewater, focusing on pseudo-second-order kinetic models to determine the dominant adsorption processes. MgFeCu-SO₄ LDH removes dyes from wastewater in 150 minutes using a second-order process, providing a quick, cost-effective, and environmentally friendly solution. The findings provide important insights into the development of novel materials to address the persistent problem of synthetic dye contamination in aquatic systems, highlight the potential of LDH materials for wastewater treatment, as they offer a scalable approach to dye removal via tailored chemical and structural properties
Comparative Analysis of Distance Functions on DBSCAN Algorithm: Mapping Malnourished Toddlers in Medan City, Indonesia
Get PDFMedan City is one of Indonesia\u27s largest cities and faces fundamental challenges in addressing malnourished toddlers. It had a stunting prevalence of 19.9% in 2022. The high rates necessitate a practical approach to identifying and managing high-risk areas. This study aims to map districts in Medan City based on the spatial data of public health center locations and malnutrition data for toddlers, using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. DBSCAN is a popular clustering algorithm because of its ability to group data based on density and detect outliers as noise. However, using the Euclidean distance function in DBSCAN may not be appropriate for all geospatial cases. The novelty lies in comparing five distance functions (Euclidean, Manhattan, Minkowski, Cosine, Chebyshev) within DBSCAN to determine which produces the most meaningful clustering in a geospatial health context. The study shows that DBSCAN with the Chebyshev distance function cannot effectively map the malnutrition problem in toddlers, as indicated by a Silhouette index (SI) value below 0.25. The clustering quality using Minkowski and Cosine distance functions in DBSCAN is not superior to that of the classical DBSCAN, with all three producing weak and unclear structures. The most effective mapping results come from using the Manhattan distance function in DBSCAN, which yields an SI value of 0.51045, two clusters, and optimal parameters of Minpts = 6–9 and ε = 6.98–7.8. The first cluster includes two districts (Medan Labuhan and Marelan), while the remaining districts form the second cluster. The analysis of different distance functions provides new insights into how selecting the appropriate distance measure can influence clustering quality in a geospatial context with DBSCAN. The similarity of the clusters is expected to inform decision-making in addressing toddler malnutrition issues in Medan City
Use of Tyre Pyrolysis Products as Recycled Raw Materials for the Production of Composite Suspension Fuel
Get PDFComposite suspension fuel (CSF) is a viable alternative not only to solid coal but also to fuel oil and diesel fuel. The issue with combined systems is the low stability and heterogeneity of the distribution of solid particles, which causes an increase in the viscosity of dispersed systems. Studies have shown that it is possible to use pyrocarbon, which is made from used car tyres, as a fuel for boats. Systems based on pyrocarbon without additives have high viscosity values. To regulate the rheological properties and stabilize the CSF, additives such as dispersants, plasticisers, and stabilisers are used. Research has been done into how dispersants affect the properties of composite suspension fuel (CSF). They used additives like carboxymethylcellulose (CMC), sodium lignosulfonate (LSTNa), naphthalene formaldehyde (NF), the condensation product of β-naphthalene sulfonic acid and formaldehyde (C-3), and humic acids. Studies of the flow of CSF based on pyrocarbon are in line with studies of the surface of pyrocarbon using electrokinetic methods. It is estimated that the surface of unmodified pyrocarbon has a positive charge at a pH of 2-10. The addition of reagents causes a change in the surface charge of the pyrocarbon and surface recharging. The best results have been obtained in CSF formulations with additives containing a sulfur group, such as C-3, NF, and LSTNa in a mass concentration of 2%. The resulting suspensions have an apparent viscosity of no more than 0.8 Pa·s, which makes it possible to use the obtained CSF as a liquid fuel suspension with a solid phase concentration of up to 60% by mass
An Analysis of Logistic Cost Structure in Corn Commodity Supply Chain (Zea Mays L) in East Java Using Activity Based Costing (ABC) Method
Get PDFEast Java is Indonesia\u27s 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\u27 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
Human-Metaverse Interaction in TVET: Research Trends and Future Directions
Get PDFTechnical and Vocational Education and Training (TVET) is swiftly advancing to integrate digital and immersive technologies, equipping learners for prospective employment markets. The metaverse, a shared virtual environment facilitating real-time interactions between individuals and digital entities, is an emerging technology impacting TVET. As Metaverse applications proliferate, they are anticipated to transform training techniques, skill acquisition, and workforce preparedness in Technical and Vocational Education and Training (TVET). A comprehensive analysis of prior studies on Human-Metaverse Interaction (HMI) is essential for grasping these implications. This study performs a bibliometric analysis of HMI, pinpointing essential topics, authors, publications, and trends within this domain. Primary bibliographic data is obtained from the Scopus database using keyword searches and quantitatively examined using bibliometric approaches in VOSviewer software. The analysis examines publication volume, thematic content, national connections, and keyword frequencies to delineate the intellectual framework of HMI research. Research findings reveal an increasing emphasis on virtual reality, augmented reality, and metaverse-related classifications, while highlighting deficiencies in domains like human-robot interaction and social virtual reality. This study offers significant insights for TVET educators and professionals, emphasizing how breakthroughs in HMI research might influence curriculum design, pedagogical approaches, and workforce readiness for a metaverse-oriented future