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Engineering Proceedings

Engineering Proceedings is an open access journal dedicated to publishing findings resulting from conferences, workshops, and similar events, in all areas of engineering. The conference organizers and proceedings editors are responsible for managing the peer-review process and selecting papers for conference proceedings.

Imprint Information Journal Flyer Open Access ISSN: 2673-4591

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Vol. 92

IEEE ECICE 2024

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Vol. 90

EASN 2024

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Vol. 89

IEEE ICKII 2024

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Vol. 88

ENC 2024

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Vol. 84

MEST 2024

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Vol. 83

CITIIC 2023

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Latest Articles

8 pages, 2203 KiB

Open AccessProceeding Paper

Experimental Investigation on Abrasive Flow Finishing of FDM-Printed Polymeric Y-Shaped Nozzle

by Abdul Wahab Hashmi, Shadab Ahmad, Faiz Iqbal, Mohammad Yusuf and Hussameldin Ibrahim

Eng. Proc. 2024, 76(1), 107; https://doi.org/10.3390/engproc2024076107 - 25 Apr 2025

An experiment examined the impact of 0.2% to 1.0% w/w graphite nanoparticles in 15W40 lubricating oil on tribological and rheological behavior. The analysis, conducted with a Pin on Disc machine and Four-Ball tester, revealed improved tribological properties and a 30% reduction in the [...] Read more.

An experiment examined the impact of 0.2% to 1.0% w/w graphite nanoparticles in 15W40 lubricating oil on tribological and rheological behavior. The analysis, conducted with a Pin on Disc machine and Four-Ball tester, revealed improved tribological properties and a 30% reduction in the friction coefficient compared to fresh 15W40. Wear was negligible, and extreme pressure performance increased by approximately 20%. SEM morphology confirmed the presence of graphite nanoparticles on the tribopair surface, indicating enhanced lubricant performance. Full article

(This article belongs to the Proceedings of 1st International Conference on Industrial, Manufacturing, and Process Engineering (ICIMP-2024))

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10 pages, 2333 KiB

Open AccessProceeding Paper

Assessment of Situational Awareness in Relation to Advanced Navigation Systems Using Ship Handling Simulators

by Hari Sundar Mahadevan, Ashwarya Kumar, Robert Grundmann and Anastasia Schwarze

Eng. Proc. 2025, 88(1), 36; https://doi.org/10.3390/engproc2025088036 - 25 Apr 2025

Digitalization has revolutionized the maritime industry, particularly in navigation systems. The use of advanced tools such as the Electronic Chart Display and Information System (ECDIS) has increased the need for information processing. However, the complexity of these systems can be overwhelming for navigators. [...] Read more.

Digitalization has revolutionized the maritime industry, particularly in navigation systems. The use of advanced tools such as the Electronic Chart Display and Information System (ECDIS) has increased the need for information processing. However, the complexity of these systems can be overwhelming for navigators. To address the concern of usability of these complex navigation systems, training with simulator data allows the crew to familiarize themselves with these systems, handle complex navigation scenarios effectively, support the transition from paper-based systems to digital systems, and help in improving their situational awareness (SA) at sea. We propose a tool that provides optimal conditions for assessing situational awareness and informing the development of intuitive systems and user interfaces. In the maritime safety domain, there is an inverse correlation between situational awareness and scenario/system complexity, highlighting the importance of effective training and assessments to improve SA. The proposed tool utilizes the Situational Awareness Global Assessment Technique (SAGAT) method, widely used in other domains, to calculate an individual’s SA score. It evaluates participants’ situational awareness in different navigational scenarios on Ship Handling Simulators, using dynamic questionnaires and contextual maps. Additionally, it integrates a rule-based system to assess participants’ performance and calculate a situational awareness score in real time, offering possibilities for assessing the SA of navigators. Full article

(This article belongs to the Proceedings of European Navigation Conference 2024)

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7 pages, 3962 KiB

Open AccessProceeding Paper

Assessing Impact of Seasonal Lighting Variation on Visual Positioning of Drones

by Che-Cheng Chang, Bo-Yu Liu, Bo-Ren Chen and Po-Ting Wu

Eng. Proc. 2025, 92(1), 14; https://doi.org/10.3390/engproc2025092014 - 25 Apr 2025

Positioning systems and algorithms are essential for drones. The global positioning system (GPS) is the most common method for drone positioning, but the GPS is not always precise or available. For visual-based positioning, convolutional neural networks (CNNs) are often used to match geometric [...] Read more.

Positioning systems and algorithms are essential for drones. The global positioning system (GPS) is the most common method for drone positioning, but the GPS is not always precise or available. For visual-based positioning, convolutional neural networks (CNNs) are often used to match geometric features in drone positioning. However, seasonal lighting is not considered, although its changes can affect the results. Hence, by incorporating critical components into a CNN, a new architecture is designed to position a drone accurately despite seasonal lighting variations. The experimental results show that the developed method solves issues in drone positioning with high accuracy and stability. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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8 pages, 1840 KiB

Open AccessProceeding Paper

Image Descriptions for Visually Impaired Individuals to Locate Restroom Facilities

by Cheng-Si He, Nan-Kai Lo, Yu-Huan Chien and Siao-Si Lin

Eng. Proc. 2025, 92(1), 13; https://doi.org/10.3390/engproc2025092013 - 25 Apr 2025

Since visually impaired individuals cannot observe their surroundings, they face challenges in accurately locating objects. Particularly in restrooms, where various facilities are spread across a limited space, the risk of tripping and being injured significantly increases. To prevent such accidents, individuals with visual [...] Read more.

Since visually impaired individuals cannot observe their surroundings, they face challenges in accurately locating objects. Particularly in restrooms, where various facilities are spread across a limited space, the risk of tripping and being injured significantly increases. To prevent such accidents, individuals with visual impairments need help to navigate these facilities. Therefore, we designed a head-mounted device that utilized artificial intelligence (AI) to enhance its functionality. The ESP32-CAM was implemented to capture and transmit images to a computer. The images were then converted into a model-compatible format for the bootstrapping language-image pre-training (BLIP) model to process and generate English descriptions (i.e., written captions). Then, Google Text-to-Speech (gTTS) was employed to convert these descriptions into speech, which was delivered audibly through a speaker. The SacreBLEU and MOS scores indicated that the developed device produced relatively accurate, natural, and intelligible spoken directions. The device assists visually impaired individuals in navigating and locating the restroom facilities to a satisfactory level. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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8 pages, 2046 KiB

Open AccessProceeding Paper

Classification of Salmon Freshness In Situ Using Convolutional Neural Network

by Juan Miguel L. Valeriano and Carlos C. Hortinela IV

Eng. Proc. 2025, 92(1), 12; https://doi.org/10.3390/engproc2025092012 - 23 Apr 2025

Fish is an important food resource, an economic contributor, and a staple food for Filipinos. For the safety and satisfaction of consumers, fish freshness must be determined. Using the convolutional neural network (CNN) algorithm, we determined salmon fillet freshness in this study. In [...] Read more.

Fish is an important food resource, an economic contributor, and a staple food for Filipinos. For the safety and satisfaction of consumers, fish freshness must be determined. Using the convolutional neural network (CNN) algorithm, we determined salmon fillet freshness in this study. In total, 7000 images were used for training and 40 for testing the CNN model. The deep learning technique, specifically ResNet50 architecture, was used with Raspberry Pi 4B, and Raspberry Pi camera V₂ was employed to take images of fish. The model showed a 92.5% accuracy, highlighting the CNN model’s accurate evaluation of seafood quality. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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7 pages, 891 KiB

Open AccessProceeding Paper

Networked Symphony Orchestra in Internet of Things Courses

by Franklin Parrales-Bravo, Rosangela Caicedo-Quiroz, Julio Barzola-Monteses and Lorenzo Cevallos-Torres

Eng. Proc. 2025, 92(1), 11; https://doi.org/10.3390/engproc2025092011 - 23 Apr 2025

Internet of Things (IoT) education is hindered by a deficiency of dynamic and interactive courses, in addition to a lack of components and difficulty in device configuration. These difficulties diminish students’ enthusiasm for IoT initiatives and reduce their drive and involvement. We designed [...] Read more.

Internet of Things (IoT) education is hindered by a deficiency of dynamic and interactive courses, in addition to a lack of components and difficulty in device configuration. These difficulties diminish students’ enthusiasm for IoT initiatives and reduce their drive and involvement. We designed and constructed a networked symphony orchestra using the Lego Mindstorms EV3 package as a project belonging to the IoT subject. Lego Mindstorms EV3 was selected due to its easy configuration. In this study, the knowledge obtained during the subject was utilized. In IoT courses at the University of Guayaquil, there is strong encouragement to apply the studied material to new initiatives. Through the design, the assessment of multiple technologies, and the final implementation of the project described within this paper, students were motivated for the practical application of concepts related to IoT. Full article

(This article belongs to the Proceedings of 2024 IEEE 6th Eurasia Conference on IoT, Communication and Engineering)

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7 pages, 1581 KiB

Open AccessProceeding Paper

Live Flood Detection System: FloodWatch

by Khairun Nidzam Ramli, Mohd Noh Dalimin, Shipun Anuar Hamzah, Mohamad Md Som, Mohd Shamian Zainal, Mohd Hamim Sanusi@Ikhsan, Azli Yusop, Wahyu Mulyo Utomo, Azmi Sidek, Maizul Ishak, Nor Azizi Yusoff and Muladi Muladi

Eng. Proc. 2025, 84(1), 90; https://doi.org/10.3390/engproc2025084090 - 22 Apr 2025

Flood incidents occur annually in Taman Negara Endau Rompin Selai Bekok due to continuous substantial rains during the rainy period. The absence of a structured flood tracking and detection system limits effective information dissemination regarding flooding to the public; currently, visitors are only [...] Read more.

Flood incidents occur annually in Taman Negara Endau Rompin Selai Bekok due to continuous substantial rains during the rainy period. The absence of a structured flood tracking and detection system limits effective information dissemination regarding flooding to the public; currently, visitors are only informed at office counters. This inefficient conventional method should be upgraded to a real time flood monitoring and alert system utilizing Internet of things (IoT) technology. UTHM personnel have requested the development of an easily accessible flood detection system via tablets or smartphones to efficiently relay flood information to visitors. Consequently, a flood detection system called “Floodwatch” was developed. The prototype provides live water level readings, air temperature, humidity, and flood images to users. The prototype has undergone rigorous testing to ensure stability, consistency, and accuracy, enabling its effective utilization. The Floodwatch system aims to enhance safety and awareness during flood events in the Taman Negara Endau Rompin Selai Bekok area. Full article

(This article belongs to the Proceedings of The 8th Mechanical Engineering, Science and Technology International Conference)

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8 pages, 1090 KiB

Open AccessProceeding Paper

Characterization Aluminum Spot Welding with Mesh Variations of Copper Powder Added on 40, 50, and 60 Meshing

by Pramuko Ilmu Purboputro and Patna Partono

Eng. Proc. 2025, 84(1), 89; https://doi.org/10.3390/engproc2025084089 - 22 Apr 2025

This study aims to determine the effect of adding copper powder with different mesh sizes on the welding point, as well as the resulting tensile strength, micro photo and hardness. The raw material of this research is aluminum type 1100. The tests included [...] Read more.

This study aims to determine the effect of adding copper powder with different mesh sizes on the welding point, as well as the resulting tensile strength, micro photo and hardness. The raw material of this research is aluminum type 1100. The tests included tensile strength tests (ASME QW-4629 standard), micro photo tests with a metallographic microscope, and Vickers tests (AWS D8.9-97 standard). The results of the tensile strength test rank mesh 40 (556.38), mesh 50 (739.13) and mesh 60 (1316.10) in descending order of tensile strength. The highest value of hardness is in the fusion zone (nugget). The last heat affected zone is in the base metal area and the order of hardness is, in descending order, mesh size 60, 50, and lastly, 40. For micro images, all of the results obtained are the same because they use the same material. The widest melted area in the welding area is on the 60 mesh and it decreases proportionally with the larger meshes. Full article

(This article belongs to the Proceedings of The 8th Mechanical Engineering, Science and Technology International Conference)

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11 pages, 5675 KiB

Open AccessProceeding Paper

Integrated Framework for Manufacturing, Design, and Monitoring of Composite-Bonded Joints: An Overview of the Results of the IDEA Project (MOST)

by Marino Quaresimin, Paolo Andrea Carraro, Federico Lamon, Silvia Giovanna Avataneo, Matteo Basso, Andrea Merulla, Umberto Galietti, Ester D’Accardi, Davide Palumbo, Massimiliano De Agostinis, Mattia Mele, Monica Ferraris, Alessandro Benelli and Koshika Pandey

Eng. Proc. 2025, 85(1), 53; https://doi.org/10.3390/engproc2025085053 - 22 Apr 2025

The IDEA project, developed in the frame of MOST—National Centre for Sustainable Mobility—addressed the growing need for reliable bonded joints in fibre-reinforced polymer composite structures used in transportation. Purely bonded joints are preferred for their lightweight and cost-efficient properties, but contamination and defect [...] Read more.

The IDEA project, developed in the frame of MOST—National Centre for Sustainable Mobility—addressed the growing need for reliable bonded joints in fibre-reinforced polymer composite structures used in transportation. Purely bonded joints are preferred for their lightweight and cost-efficient properties, but contamination and defect detection issues often make them unreliable. To solve this, the project developed innovative surface treatments, a methodology for the safe, optimized design of bonded joints, and structural health monitoring solutions, viable for real-time assessment. These advancements aim to increase the reliability and safety of bonded connections, helping industries adopt lighter, purely bonded joints over heavier, hybrid bonded/bolted options. Full article

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11 pages, 4036 KiB

Open AccessProceeding Paper

Design and Application of an Energy Management System Based on Artificial Intelligence Technology

by Hongye Lin, Xuanying Bai, Chun Li, Shenghan Xu, Haibin Xu, Zne-Jung Lee, Yun Lin, Qunshan Zhou and Jingxun Cai

Eng. Proc. 2025, 91(1), 16; https://doi.org/10.3390/engproc2025091016 - 22 Apr 2025

In response to the increasingly severe energy consumption problem and to promote energy saving and emission reduction, this study aims to design and apply an energy management system platform based on artificial intelligence (AI) technology. The system adopts sensor technology and data acquisition [...] Read more.

In response to the increasingly severe energy consumption problem and to promote energy saving and emission reduction, this study aims to design and apply an energy management system platform based on artificial intelligence (AI) technology. The system adopts sensor technology and data acquisition equipment to monitor various types of energy consumption in buildings in real time, efficiently process and predict these data through machine learning algorithms, and finally visualize the results. The system is functionally complete, completing the process from data collection to visualization, the cloud platform’s construction, and finally a full energy management platform. Various machine learning methods are applied to energy management by predicting the chilled water energy meter return temperature of the central air-conditioning system and comparing its performance. Among the various types of regression algorithms, the mean-square error (MSE) of decision tree regression is 0.36, the MSE of support vector regression (SVR) is 0.09, the MSE of K-nearest neighbor (KNN) regression is 0.57, and the MSE of extreme gradient boosting (XGBoost) regression is 0.32. The SVR, the XGBoost regression, and the decision tree regression perform better in various indices. Full article

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11 pages, 1570 KiB

Open AccessProceeding Paper

Identify Subtle Fall Hazards Using Transfer Learning

by Wen-Ta Hsiao, Wen-Der Yu, Chi-Yung Tang and Alexey Bulgakov

Eng. Proc. 2025, 91(1), 15; https://doi.org/10.3390/engproc2025091015 - 22 Apr 2025

Computer vision is increasingly used for fall safety monitoring, but it struggles in subtle hazard scenarios, causing delays in hazard detection. Therefore, this issue was addressed in this study using transfer learning on pre-trained models that were fine-tuned with target datasets to enhance [...] Read more.

Computer vision is increasingly used for fall safety monitoring, but it struggles in subtle hazard scenarios, causing delays in hazard detection. Therefore, this issue was addressed in this study using transfer learning on pre-trained models that were fine-tuned with target datasets to enhance accuracy. We tested two scenarios—“scaffolding transverse brace installation” and “correct safety lifeline hook-up”—with MobileNet v2, GoogleNet, Inception v3, and ResNet-50. GoogleNet achieved an accuracy of 95.2% in brace installation recognition, while MobileNet v2 and Inception v3 achieved an accuracy of 96% for lifeline hook-up recognition, demonstrating excellent capability in complex hazard detection. Full article

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10 pages, 183 KiB

Open AccessProceeding Paper

Design Factors of Water Mist in the Mystery of Landscapes

by Wu-Po-Cheng Lee and Sheng-Jung Ou

Eng. Proc. 2025, 91(1), 14; https://doi.org/10.3390/engproc2025091014 - 22 Apr 2025

Water mist enhances the sense of mystery with visual and sensory effects, depending on its atmospheric creation and varying mist heights. Key factors influencing this mystery are the combination of mist with plants, increased air humidity, and sound effects. We identified important elements [...] Read more.

Water mist enhances the sense of mystery with visual and sensory effects, depending on its atmospheric creation and varying mist heights. Key factors influencing this mystery are the combination of mist with plants, increased air humidity, and sound effects. We identified important elements in the landscape at different times of day: in the morning, plant combinations and terrain; during the day, humidity and obscuring effects; in the evening, imaginative space; and at night, mist with plants. It is necessary to enhance visual effects and terrain variation in mist design to offer guidelines for future exploration. Full article

11 pages, 3848 KiB

Open AccessProceeding Paper

Human Factors in Bus Accidents: A Bibliometric Analysis

by Eva Nursifa Fauziah Suwandi, Bambang Suhardi and Etika Muslimah

Eng. Proc. 2025, 84(1), 88; https://doi.org/10.3390/engproc2025084088 - 21 Apr 2025

This study examines human factors in bus accidents using bibliometric analysis to identify publications, research trends, and collaborative relationships between authors and institutions. Data from 1.834 publications in the Scopus database during the period 2014–2024 were analyzed using VOS viewer software to display [...] Read more.

This study examines human factors in bus accidents using bibliometric analysis to identify publications, research trends, and collaborative relationships between authors and institutions. Data from 1.834 publications in the Scopus database during the period 2014–2024 were analyzed using VOS viewer software to display network visualization and density. The results show a significant increase in publications since 2018, with a peak in 2022. Research related to human factors in bus accidents is growing, with a focus on fatigue, distraction, and driver behavior. The keyword and density analysis identified that “Human” was the most frequently discussed topic. China is the country with the highest contribution, and the medical field plays a major role in this topic. These findings highlight the importance of understanding human factors in efforts to improve transportation safety. Full article

(This article belongs to the Proceedings of The 8th Mechanical Engineering, Science and Technology International Conference)

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9 pages, 1886 KiB

Open AccessProceeding Paper

Modeling the Quantitative Structure–Activity Relationships of 1,2,4-Triazolo[1,5-a]pyrimidin-7-amine Analogs in the Inhibition of Plasmodium falciparum

by Inalegwu S. Apeh, Thecla O. Ayoka, Charles O. Nnadi and Wilfred O. Obonga

Eng. Proc. 2025, 87(1), 52; https://doi.org/10.3390/engproc2025087052 - 21 Apr 2025

Triazolopyrimidine and its analogs represent an important scaffold in medicinal chemistry research. The heterocycle of 1,2,4-triazolo[1,5-a] pyrimidine (1,2,4-TAP) serves as a bioisostere candidate for purine scaffolds, N-acetylated lysine, and carboxylic acid. This study modeled the quantitative structure–activity relationship (QSAR) of 125 congeners of [...] Read more.

Triazolopyrimidine and its analogs represent an important scaffold in medicinal chemistry research. The heterocycle of 1,2,4-triazolo[1,5-a] pyrimidine (1,2,4-TAP) serves as a bioisostere candidate for purine scaffolds, N-acetylated lysine, and carboxylic acid. This study modeled the quantitative structure–activity relationship (QSAR) of 125 congeners of 1,2,4-TAP from the ChEMBL database in the inhibition of Plasmodium falciparum using six machine learning algorithms. The most significant features among 306 molecular descriptors, including one molecular outlier, were selected using recursive feature elimination. A ratio of 20% was used to split the x- and y-matrices into 99 training and 24 test compounds. The regression models were built using machine learning sci-kit-learn algorithms (multiple linear regression (MLR), k-nearest neighbours (kNN), support vector regressor (SVR), random forest regressor (RFR) RIDGE regression, and LASSO). Model performance was evaluated using the coefficient of determination (R²), mean squared error (MSE), mean absolute error (MAE), root mean squared error (RMSE), p-values, F-statistic, and variance inflation factor (VIF). Five significant variables were considered in constructing the model (p < 0.05) with the following regression equation: pIC₅₀ = 5.90 − 0.71npr1 − 1.52pmi3 + 0.88slogP − 0.57vsurf-CW2 + 1.11vsurf-W2. On five-fold cross-validation, three algorithms—kNN (MSE = 0.46, R² = 0.54, MAE = 0.54, RMSE = 0.68), SVR (MSE = 0.33, R² = 0.67, MAE = 0.46, RMSE = 0.57), and RFR (MSE = 0.43, R² = 0.58, MAE = 0.51, RMSE = 0.66)—showed strong robustness, efficiency, and reliability in predicting the pIC₅₀ of 1,2,4-triazolo[1,5-a]pyrimidine. The models provided useful data on the functionalities necessary for developing more potent 1,2,4-TAP analogs as anti-malarial agents. Full article

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12 pages, 707 KiB

Open AccessProceeding Paper

A Rule-Based Model for Stemming Hausa Words

by Mustapha Ashiru Bari, Hadiza Ali Umar, Bello Shehu Bello and Ibrahim Said Ahmed

Eng. Proc. 2025, 87(1), 51; https://doi.org/10.3390/engproc2025087051 - 21 Apr 2025

The increasing number of online communities has led to the significant growth in digital data in multiple languages on the Internet. Consequently, language processing and information retrieval have become important fields in the era of the Internet. Stemming, a crucial preprocessing tool in [...] Read more.

The increasing number of online communities has led to the significant growth in digital data in multiple languages on the Internet. Consequently, language processing and information retrieval have become important fields in the era of the Internet. Stemming, a crucial preprocessing tool in natural language processing and information retrieval, has been extensively explored for high-resource languages like English, German, and French. However, more extensive studies regarding stemming in the context of the Hausa language, an international language that is widely spoken in West Africa and one of the fastest-growing languages globally, are required. This paper presents a rule-based model for stemming Hausa words. The proposed model relies on a set of rules derived from the analysis of Hausa word morphology and the rules for extracting stem forms. The rules consider the syntactic constraints, e.g., affixation rules, and performs a morphological analysis of the properties of the Hausa language, such as word formation and distribution. The proposed model’s performance is evaluated against existing models using standard evaluation metrics. The evaluation method employed Sirstat’s approach, and a language expert assessed the system’s results. The model is evaluated using the manual annotation of a set of 5077 total words used in the algorithm, including 2630 unique words and 3766 correctly stemmed Hausa words. The model achieves an overall accuracy of 98.66%, demonstrating its suitability for use in applications such as natural language processing and information retrieval. Full article

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9 pages, 1118 KiB

Open AccessProceeding Paper

Color Stability of PET-G in Clear Aligners: Impact of Prolonged Exposure to Everyday Substances and Its Psychological and Social Implications

by Fabiana Nicita, Joseph Lipari, Frank Lipari and Arianna Nicita

Eng. Proc. 2025, 87(1), 50; https://doi.org/10.3390/engproc2025087050 - 21 Apr 2025

The aesthetics of clear aligners is a critical factor that can influence patient satisfaction and psychological and social well-being. However, their transparency can be compromised by exposure to staining agents. This study aimed to evaluate the color stability of PET-G aligners following prolonged [...] Read more.

The aesthetics of clear aligners is a critical factor that can influence patient satisfaction and psychological and social well-being. However, their transparency can be compromised by exposure to staining agents. This study aimed to evaluate the color stability of PET-G aligners following prolonged exposure to common daily substances, including food, tobacco products, and cleaning agents. Flat samples of PET-G (n = 220) were immersed in various solutions, including coffee, tea, Coca-Cola, red wine, a colloidal silver-based disinfectant, nicotine, artificial saliva, cigarette smoke, and mixtures of saliva with smooth, coffee, and nicotine. Immersion times of 10 (n = 110) and 15 days (n = 110) were randomly assigned. Colorimetric assessments were conducted by measuring L*a*b* parameters before and after immersion, and total color change (ΔE) was calculated. Non-parametric statistical tests revealed significant color changes in PET-G samples after both immersion durations, with pairwise comparisons indicating notable differences in ΔE values among groups exposed to different substances, particularly coffee, tea, and Coca-Cola. The findings highlight the psychological and social impact of aligner staining on patient confidence and compliance. Understanding these effects highlights the need for enhanced patient education to improve aligner aesthetics and satisfaction. Full article

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11 pages, 4122 KiB

Open AccessProceeding Paper

UKSBAS Testbed Performance Assessment of Two Years of Operations

by Javier González Merino, Fernando Bravo Llano, Michael Pattinson, Madeleine Easom, Juan Ramón Campano Hernández, Ignacio Sanz Palomar, María Isabel Romero Llapa, Sangeetha Priya Ilamparithi, David Hill and George Newton

Eng. Proc. 2025, 88(1), 35; https://doi.org/10.3390/engproc2025088035 - 21 Apr 2025

Current Satellite-Based Augmentation Systems (SBASs) improve the positioning accuracy and integrity of GPS satellites and provide safe civil aviation navigation services for procedures from en-route to LPV-200 precision approach over specific regions. SBAS systems, such as WAAS, EGNOS, GAGAN, and MSAS, already operate. [...] Read more.

Current Satellite-Based Augmentation Systems (SBASs) improve the positioning accuracy and integrity of GPS satellites and provide safe civil aviation navigation services for procedures from en-route to LPV-200 precision approach over specific regions. SBAS systems, such as WAAS, EGNOS, GAGAN, and MSAS, already operate. The development of operational SBAS systems is in transition due to the extension of L1 SBAS services to new regions and the improvements expected by the introduction of dual frequency multi-constellation (DFMC) services, which allow the use of more core constellations such as Galileo and the use of ionosphere-free L1/L5 signal combination. The UKSBAS Testbed is a demonstration and feasibility project in the framework of ESA’s Navigation Innovation Support Programme (NAVISP), which is sponsored by the UK’s HMG with the participation of the Department for Transport and the UK Space Agency. UKSBAS Testbed’s main objective is to deliver a new L1 SBAS signal in space (SIS) from May 2022 in the UK region using Viasat’s Inmarsat-3F5 geostationary (GEO) satellite and Goonhilly Earth Station as signal uplink over PRN 158, as well as L1 SBAS and DFMC SBAS services through the Internet. SBAS messages are generated by GMV’s magicSBAS software and fed with data from the Ordnance Survey’s station network. This paper provides an assessment of the performance achieved by the UKSBAS Testbed during the last two years of operations at the SIS and user level, including a number of experimentation campaigns performed in the aviation and maritime domains, comprising ground tests at airports, flight tests on aircraft and sea trials on a vessel. This assessment includes, among others, service availability (e.g., APV-I, LPV-200), protection levels (PL), and position errors (PE) statistics over the service area and in a network of receivers. Full article

(This article belongs to the Proceedings of European Navigation Conference 2024)

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8 pages, 1424 KiB

Open AccessProceeding Paper

Eco-Friendly and Sustainable Remediation of Copper- and Zinc-Contaminated Farmland

by Chang-Chao Chen, Pei-Cheng Cheng, Chin-Yuan Huang, Min-Siou Lin and Shu-Fen Cheng

Eng. Proc. 2025, 91(1), 13; https://doi.org/10.3390/engproc2025091013 - 21 Apr 2025

Copper and zinc are metals commonly used in industry. However, improperly disposed copper and zinc pollute soil seriously. In farmland where the concentrations of copper and zinc exceeded regulatory standards and farming has been banned for many years, we measured the copper and [...] Read more.

Copper and zinc are metals commonly used in industry. However, improperly disposed copper and zinc pollute soil seriously. In farmland where the concentrations of copper and zinc exceeded regulatory standards and farming has been banned for many years, we measured the copper and zinc concentrations in soil. The copper concentration ranged from 30.2 to 1082.3 mg/kg, while the zinc concentration was between 200.2 and 3335.3 mg/kg. To explore the correlation between the concentration of copper and zinc in soil and plants and plant growth, Pennisetum was chosen as the test crop. The economic and carbon reduction benefits of planting Pennisetum in copper- and zinc-polluted farmland were also investigated. The results indicated that the concentration levels of copper and zinc were not significantly impacted, and neither was the growth of Pennisetum. Farming Pennisetum produces a total of about 1100 tons of biomass per hectare per year. The income per hectare was about USD 48,000 per year. Pennisetum captures 578.8 tons of carbon every year, equivalent to 2124.2 ton-CO₂e. When used as fuel, it provides 23,649 GJ of bioenergy. Therefore, Pennisetum is an appropriate plant for the green and sustainable remediation of polluted soil. Full article

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10 pages, 2109 KiB

Open AccessProceeding Paper

Immobilization of Heavy Metals Using Biochar and Manganese Dioxide for Preventing Pollution

by Shui-Wen Chang Chien and Pei-Qi Lu

Eng. Proc. 2025, 91(1), 12; https://doi.org/10.3390/engproc2025091012 - 21 Apr 2025

Using biochar/δ-MnO₂ as an adsorbent, heavy metals in soil were immobilized to prevent further pollution. When biochar/δ-MnO₂ was thoroughly mixed with contaminated soil in a ratio of 2:8, the residual fractions of As, Cu, Pb, and Zn increased by 9.78, 39.0, [...] Read more.

Using biochar/δ-MnO₂ as an adsorbent, heavy metals in soil were immobilized to prevent further pollution. When biochar/δ-MnO₂ was thoroughly mixed with contaminated soil in a ratio of 2:8, the residual fractions of As, Cu, Pb, and Zn increased by 9.78, 39.0, 61.6, and 15.7%. The addition of biochar/δ-MnO₂ significantly immobilized Cu and Pb. Since biochar/δ-MnO₂ fixed As, Cu, Pb, and Zn in the soil, soil contamination was prevented effectively. Full article

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9 pages, 4060 KiB

Open AccessProceeding Paper

Development of Quasi-Direct Drive Motor for Walking Robots in Extraterrestrial Environments

by Jonas Eisenmenger, Zhongqian Zhao and Frank Kirchner

Eng. Proc. 2025, 90(1), 99; https://doi.org/10.3390/engproc2025090099 - 19 Apr 2025

This paper presents the development of a quasi-direct drive motor for space applications, which offers opportunities for dynamic applications, such as in walking robots. The use of such a motor in a space environment presents new challenges that make it necessary to go [...] Read more.

This paper presents the development of a quasi-direct drive motor for space applications, which offers opportunities for dynamic applications, such as in walking robots. The use of such a motor in a space environment presents new challenges that make it necessary to go beyond the conventional design for terrestrial applications. To achieve this, the DFKI-X2D joint was developed as part of the MODKOM project. As an approach, an in-runner and an out-runner motor are developed as prototypes and subjected to several functional tests, including tests on a motor test bench, in a climate chamber, and via vibration tests. During these tests, the in-runner approach showed advantages, especially in thermal terms, and based on the findings, a final iteration was designed as the space version, which will undergo additional environmental testing in the future to move towards TRL 5. Full article

(This article belongs to the Proceedings of The 14th EASN International Conference on “Innovation in Aviation & Space Towards Sustainability Today & Tomorrow”)

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