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Optimised Heterogeneous Handover In Mobile Ipv6 Using Enhanced Predictive Fast Proxy With Media Independent Handover (Mih) Support, Aliyu Aminu Abdulhadi, Nura Mukhtar Oct 2025

Optimised Heterogeneous Handover In Mobile Ipv6 Using Enhanced Predictive Fast Proxy With Media Independent Handover (Mih) Support, Aliyu Aminu Abdulhadi, Nura Mukhtar

Journal of Informatics and Web Engineering

In wireless networks, handover performance is essential for enabling real-time traffic applications. Long handover delays make it impossible for a Mobile Node (MN) to send and receive data packets, which is very undesirable for real-time applications like video conferencing and VoIP. Therefore, in order to guarantee better handover performance, decreasing handover duration is crucial. The Internet Engineering Task Force (IETF) has standardized Fast Proxy Mobile IPv6 (FPMIPv6) as an enhancement to the novel Proxy Mobile IPv6 (PMIPv6) to attain better handover performance. FPMIPv6 functions in two modes: predictive and reactive, using a link-layer triggering mechanism. The predictive mode uses link-layer …

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Developing A Predictive Model For Football Players’ Market Value Using Machine Learning, Muhammad Afif Jazimin Idris, Sew Lai Ng Oct 2025

Developing A Predictive Model For Football Players’ Market Value Using Machine Learning, Muhammad Afif Jazimin Idris, Sew Lai Ng

Journal of Informatics and Web Engineering

Football is the world’s most popular sport, and evaluating the market value of players is crucial for clubs and managers in making informed decisions regarding transfers, contracts, and financial planning. This study aims to develop a predictive model to estimate the market value of football players using machine learning (ML) algorithms and real-life statistics performance data from the top five European leagues such as English Premier League, Italian Serie A, Spanish La Liga, German Bundesliga, and French Ligue 1 between the 2017/18 and 2019/20 seasons. By reviewing past research, various ML methods such as Random Forest, LightGBM, XGBoost, and Gradient …

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Deep Learning Approaches To Autocorrelation Function And Signal-To-Noise Ratio Estimation In Noisy Images, Kai Liang Lew, Kok Swee Sim, Shing Chiang Tan Oct 2025

Deep Learning Approaches To Autocorrelation Function And Signal-To-Noise Ratio Estimation In Noisy Images, Kai Liang Lew, Kok Swee Sim, Shing Chiang Tan

Journal of Informatics and Web Engineering

Accurate estimation of signal-to-noise ratio (SNR) in Scanning Electron Microscopy (SEM) is crucial because it evaluates the image quality. SEM images faced a challenge whereby Gaussian noise commonly appears in the images. Thus, researchers have developed several methods to estimate the SNR value. With the introduction of deep learning, most of the limitations in the classical methods can be addressed. This paper proposes a novel deep learning, CNN-based Calibration Map Network (CalibNet) to estimate the SNR value from SEM images using a calibration map between classical SNR and autocorrelation function SNR. The architecture consists of convolutional layers, rectified linear unit …

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Loan Default Prediction Using Machine Learning Algorithms, Zhi Zheng Kang, Sin Yin Teh, Samuel Yong Guang Tan, Wei Chien Ng Oct 2025

Loan Default Prediction Using Machine Learning Algorithms, Zhi Zheng Kang, Sin Yin Teh, Samuel Yong Guang Tan, Wei Chien Ng

Journal of Informatics and Web Engineering

Financial institutions constantly face at the risk of default by borrowers which can result in significant financial losses. It is essential to develop an appropriate predictive model for loan default to reduce these risks and minimise financial losses. The objective of this study is to identify the most suitable machine learning model to predict loan default by comparing four models which are Random Forest, Decision Tree, Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM). Additionally, it also examines the key features influencing loan default prediction. The dataset used in this study is sourced from Kaggle and it consists …

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Indonesian Language Sign Detection Using Mediapipe With Long Short-Term Memory (Lstm) Algorithm, Wargijono Utomo, Yogasetya Suhanda, Harun Ar-Rasyid, Andy Dharmalau Oct 2025

Indonesian Language Sign Detection Using Mediapipe With Long Short-Term Memory (Lstm) Algorithm, Wargijono Utomo, Yogasetya Suhanda, Harun Ar-Rasyid, Andy Dharmalau

Journal of Informatics and Web Engineering

People with disabilities mostly communicate using sign language, but the public still has little understanding of the Indonesian Sign Language System (ISLS). This causes obstacles in daily interactions. Advances in artificial intelligence technology, especially artificial neural networks, open opportunities in sign language recognition, but are still in the development stage. This study aims to build a ISLS sign language recognition model using the LSTM approach and MediaPipe Hands. The method of collecting hand keypoint data, 25 sequences per gesture, and 36 alphabetic and numeric gestures. The dataset is divided into three categories, namely 80% training, 10% validation, and 10% testing. …

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Mapping Relational Database To Full-Text Xml For Open Journal System Cross-Platform Article Distribution, Chee-Xiang Ling, Kok-Why Ng, Heru Agus Santoso Oct 2025

Mapping Relational Database To Full-Text Xml For Open Journal System Cross-Platform Article Distribution, Chee-Xiang Ling, Kok-Why Ng, Heru Agus Santoso

Journal of Informatics and Web Engineering

In academic publications, the automation of full-text eXtensible Markup Language (XML) is increasingly essential, as generating full-text XML for article distribution is a complex and time-consuming process that requires metadata extraction from a relational database and transformation into hierarchical structures such as Journal Article Tag Suite (JATS). The lack of automation in this transformation process may cause inconsistencies and inaccuracies and may cause errors due to human error. The primary aim is to develop an automation system for transforming metadata from a relational database to full-text XML by reducing errors and speeding the process of generating full-text XML. This is …

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Exploring Generative Ai Recommender Systems In E-Commerce: Model, Evaluation Metric, And Comparative Review, Wan-Er Kong, Tong-Ern Tai, Palanichamy Naveen, Kok-Why Ng, Lucia Dwi Krisnawati Oct 2025

Exploring Generative Ai Recommender Systems In E-Commerce: Model, Evaluation Metric, And Comparative Review, Wan-Er Kong, Tong-Ern Tai, Palanichamy Naveen, Kok-Why Ng, Lucia Dwi Krisnawati

Journal of Informatics and Web Engineering

Generative Artificial Intelligence (GAI) is changing what can be done with Recommender Systems (RS) in e-commerce by allowing much more interactive, situationally aware, and highly tailored experiences for users. The purpose of this paper is to provide overall insight into how GAI, including Large Language Models (LLMs), Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and other emerging methods, is affecting the building and running of modern e-commerce RS. This paper classifies generative models into groups based on the type of models used, data modality, and specific domain of application. Their involvement in tasks such as personalized product ranking, content generation, …

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User Behaviour Prediction In E-Commerce Using Logistic Regression, Wei-Wen Lee, Noramiza Hashim, Shaymaa Al-Juboori Oct 2025

User Behaviour Prediction In E-Commerce Using Logistic Regression, Wei-Wen Lee, Noramiza Hashim, Shaymaa Al-Juboori

Journal of Informatics and Web Engineering

From a psychological perspective, human behaviour reflects underlying thoughts and decision-making patterns, for example, consumer behaviour may correlate with the purchase decisions. In the fast-evolving e-commerce industry, predicting user behaviour is essential for enhancing marketing strategies, improving customer experiences, and increasing sales. However, traditional heuristic (e.g. market basket analysis) approaches to analyse buyer behaviour are often rigid and fail to adapt to complex consumer interactions. This research work develops a predictive model that analyses user behaviour based on data such as historical purchasing patterns and demographic attributes. Based on a review of previous studies, Logistic Regression (LR) is utilized as …

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Identifying The Barriers To Digital Financial Inclusion In The Most Financially Excluded Country Using Machine Learning Algorithm, Yin Ting Chin, Hui Shan Lee Oct 2025

Identifying The Barriers To Digital Financial Inclusion In The Most Financially Excluded Country Using Machine Learning Algorithm, Yin Ting Chin, Hui Shan Lee

Journal of Informatics and Web Engineering

Despite the call of digital financial services (DFS) to improve inclusive growth and reduce poverty, the adoption of DFS remains low in Nigeria. The objective of this study is to examine the barriers of ability, access and usage of DFS in Nigeria. This study uses secondary data Global Findex year 2017 and year 2021 to predict the socioeconomic factors on the target variables of DFS (ability, access and usage). Using a machine learning (ML) algorithm, namely the J48 decision tree in the Waikato Environment for Knowledge Analysis (WEKA) software, this study analyses the predictive strength of variables such as gender, …

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Robust Lane Detection Under Varying Lighting Conditions Using Adaptive Vision-Based Techniques, Habibatelrahman Mosaad Abdelfattah Mohamed Abdelaal, Tee Connie, Michael Kah Ong Goh Oct 2025

Robust Lane Detection Under Varying Lighting Conditions Using Adaptive Vision-Based Techniques, Habibatelrahman Mosaad Abdelfattah Mohamed Abdelaal, Tee Connie, Michael Kah Ong Goh

Journal of Informatics and Web Engineering

Reliable lane detection is crucial to autonomous driving but continues to be challenging with varying lighting conditions. Fluctuations in illuminations due to bright sunlight, shadows or low lighting at night can degrade the visual quality and adversely affect the accuracy of the lane detection results. This research proposes an adaptive approach for lane detection under different lighting scenarios. For daytime, a Region of Interest (ROI) masking and line averaging technique help in the stability and visibility of the lane markings. For nighttime conditions, a Probabilistic Hough Transform-based method improves lane detection in low-light environments. An evaluation tool has been developed …

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Real-Time Read And Analysis Of Air Pollution Produced From Private Electrical Generators In Mosul City Using Lorawan, Mahmood Alfathe, Awfa Aladwani, Ali Abduljabbar Oct 2025

Real-Time Read And Analysis Of Air Pollution Produced From Private Electrical Generators In Mosul City Using Lorawan, Mahmood Alfathe, Awfa Aladwani, Ali Abduljabbar

Journal of Informatics and Web Engineering

This study presents a novel, site-specific deployment of a Long Range Wide Area Network (LoRaWAN)-driven air pollution monitoring network specifically for the Iraqi city of Mosul, which is beset by widespread power outages and extensive utilization of decentralized diesel generators. While these generators mitigate electricity shortages, they are enormous contributors to urban air pollution, emitting high levels of CO2 and particulates. As opposed to previous studies, which concentrate on affluent urban areas, this research addresses a very deprived locale using an extensible low-power, low-cost LoRaWAN network and high-precision CO2 sensors (Sensirion SCD30 and MH-Z19) and The Things Network (TTN) for …

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Impact Of Data Quality Types On Computational Time In Data Source Selection Using Ant Colony Optimization, Nor Amalina Mohd Sabri, Abd Samad Hasan Basari, Nurul Akmar Emran Oct 2025

Impact Of Data Quality Types On Computational Time In Data Source Selection Using Ant Colony Optimization, Nor Amalina Mohd Sabri, Abd Samad Hasan Basari, Nurul Akmar Emran

Journal of Informatics and Web Engineering

Data quality varies dramatically from source to source, even within the same domain. Given these challenges, data source selection has emerged as a crucial step in information integration. It demands efficient and scalable approaches that can handle massive data volumes while ensuring the quality of results. Adapting the ACO algorithm to solve the data sources selection problems may lead to inconsistent computational time if the data sources provided are vary in quality. These challenges bring the issues of time consuming in selecting the required data sources. However, how much the computational time needed in solving the data sources selection is …

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Lightweight String Similarity Approaches For Duplicate Detection In Academic Titles, Fahrudin Mukti Wibowo, Muhammad Zidny Nafan, Muhamad Azrino Gustalika, Harinda Fernando, Muhammad Hussain, Nur Afiqah Sahadun Oct 2025

Lightweight String Similarity Approaches For Duplicate Detection In Academic Titles, Fahrudin Mukti Wibowo, Muhammad Zidny Nafan, Muhamad Azrino Gustalika, Harinda Fernando, Muhammad Hussain, Nur Afiqah Sahadun

Journal of Informatics and Web Engineering

This study addresses the critical challenge of detecting duplicate final year project (FYP) titles in academic institutions, where minor variations like reordering, synonyms, and paraphrasing often obscure plagiarism. We systematically evaluate four string similarity algorithms - Jaro-Winkler, Levenshtein Edit Distance, TF-IDF with Cosine Similarity, and Jaccard Similarity - using a synthetic dataset of 250 title pairs representing common duplication patterns. Our experiments reveal that character-based methods (Jaro-Winkler and Edit Distance) achieve perfect detection (F1-score=1.0) for literal matches, including typographical variations and phrase reordering. At the same time, TF-IDF demonstrates strong semantic capability (F1-score=0.95), albeit with some false positives. Jaccard Similarity …

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Enhancing Imbalanced Data Augmentation: A Comparative Study Of Ganified-Smote And Latent Factor Integration, Rusma Anieza Ruslan, Nureize Arbaiy, Pei-Chun Lin Oct 2025

Enhancing Imbalanced Data Augmentation: A Comparative Study Of Ganified-Smote And Latent Factor Integration, Rusma Anieza Ruslan, Nureize Arbaiy, Pei-Chun Lin

Journal of Informatics and Web Engineering

One such serious problem in machine learning (ML) is imbalanced datasets. Minority class samples are usually sparse but hold significant meaning. The model can become biased toward the majority class due to unbalanced class distribution. This results in fraudulently high accuracy without being able to detect minority cases. This bias is also most perilous in critical applications, where ignoring minority cases can be highly destructive. To overcome this problem, the Synthetic Minority Oversampling Technique (SMOTE) is one of the most widely used. SMOTE creates balanced class distribution by interpolating between existing minority samples. It creates samples that are too close …

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Re: Comments On The Draft Final Butte Mine Waste Repository Geotechnical Investigation Work Plan (Dated September 23, 2025), Emma Rott Oct 2025

Re: Comments On The Draft Final Butte Mine Waste Repository Geotechnical Investigation Work Plan (Dated September 23, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Generative Modeling For Interpretable Anomaly Detection In Medical Imaging: Applications In Failure Detection And Data Curation, Mckell E Woodland, Mais Altaie, Caleb S O'Connor, Austin H Castelo, Olubunmi C Lebimoyo, Aashish C Gupta, Joshua P Yung, Paul E Kinahan, Clifton D Fuller, Eugene J Koay, Bruno C Odisio, Ankit B Patel, Kristy K Brock Oct 2025

Generative Modeling For Interpretable Anomaly Detection In Medical Imaging: Applications In Failure Detection And Data Curation, Mckell E Woodland, Mais Altaie, Caleb S O'Connor, Austin H Castelo, Olubunmi C Lebimoyo, Aashish C Gupta, Joshua P Yung, Paul E Kinahan, Clifton D Fuller, Eugene J Koay, Bruno C Odisio, Ankit B Patel, Kristy K Brock

Faculty, Staff and Students Publications

This work aims to leverage generative modeling-based anomaly detection to enhance interpretability in AI failure detection systems and to aid data curation for large repositories. For failure detection interpretability, this retrospective study utilized 3339 CT scans (525 patients), divided patient-wise into training, baseline test, and anomaly (having failure-causing attributes—e.g., needles, ascites) test datasets. For data curation, 112,120 ChestX-ray14 radiographs were used for training and 2036 radiographs from the Medical Imaging and Data Resource Center for testing, categorized as baseline or anomalous based on attribute alignment with ChestX-ray14. StyleGAN2 networks modeled the training distributions. Test images were reconstructed with backpropagation and …

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Comparative Responsiveness Of Preference-Based Health-Related Quality Of Life, Social Care, And Well-Being Measures In The Context Of Multiple Sclerosis, Elizabeth Goodwin, Amy Heather, Nia Morrish, Jenny Freeman, Kate Boddy, Sarah Thomas, Jeremy Chataway, Rod Middleton, Annie Hawton Oct 2025

Comparative Responsiveness Of Preference-Based Health-Related Quality Of Life, Social Care, And Well-Being Measures In The Context Of Multiple Sclerosis, Elizabeth Goodwin, Amy Heather, Nia Morrish, Jenny Freeman, Kate Boddy, Sarah Thomas, Jeremy Chataway, Rod Middleton, Annie Hawton

School of Health Professions

Objectives: To provide evidence on the responsiveness of social care and well-being preference-based measures (PBMs) compared with health-related quality of life PBMs in the context of multiple sclerosis (MS). Methods: The ICEpop CAPability measure for Adults (ICECAP-A) and Adult Social Care Outcomes Toolkit (ASCOT) were completed online in September 2019, March 2020, September 2020, via the UK MS Register. Responses were linked to EQ-5D-3L and MS Impact Scale-8 Dimensions (MSIS-8D) values, and to MS Walking Scale-12, Hospital Anxiety and Depression Scale (HADS), and Fatigue Severity Scale scores. Responsiveness was assessed in relation to minimal important differences on MS Walking Scale-12, …

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Efficacy Of Teaching At The Right Level Approach Combined With The Problem-Based Learning Model On Science Learning Outcomes At Middle School, Heri Syahputra Azhar Panjaitan, Ryan Dwi Puspita Oct 2025

Efficacy Of Teaching At The Right Level Approach Combined With The Problem-Based Learning Model On Science Learning Outcomes At Middle School, Heri Syahputra Azhar Panjaitan, Ryan Dwi Puspita

Jurnal Pendidikan Sains

This research seeks to evaluate the efficacy of the Teaching at the Right Level (TaRL) strategy in conjunction with the Problem-Based Learning (PBL) model on the scientific learning outcomes of eighth-grade students at middle school Islam Terpadu Khairul Imam. This research addresses the inadequate scientific problem-solving abilities and science learning outcomes of Indonesian students, necessitating a more interactive and individualized instructional technique. The methodology used is a quasi-experimental design with a nonequivalent control group. The sample included two purposively chosen eighth-grade classes: one experimental class (n=25) underwent the TaRL–PBL intervention, whereas the control class (n=25) simply used the lecture approach. …

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Durability Assessment Of Low-Carbon Concrete Using Electrical Resistivity And Derived Transport Parameters, Elo Merit Imitini, Benny Suryanto, Bhaskar Sen Gupta Oct 2025

Durability Assessment Of Low-Carbon Concrete Using Electrical Resistivity And Derived Transport Parameters, Elo Merit Imitini, Benny Suryanto, Bhaskar Sen Gupta

International Conference on Durability of Concrete Structures

Effective assessment of reinforced concrete durability necessitates monitoring of concrete performance using straightforward yet robust technique over an extended period of time. This study investigates six low-carbon concrete mixes incorporating up to 70% Portland cement replacement using binary and ternary combinations of ground granulated blast furnace slag (GGBS), fly ash (FA), and limestone powder (LP). Electrical resistivity measurements were undertaken over a 360-day period and used to derive formation factors and instantaneous diffusion coefficients, offering insight into the evolving pore structure and ionic transport. The results showed that all mixes exhibited a progressive increase in resistivity, indicative of continued hydration …

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Assessment Of Ggbs-Blended-Concrete Durability With Modified Water Permeability Method, Soumyaranjan Panda, Supratic Gupta, Saubhagya Kumar Panigrahi Oct 2025

Assessment Of Ggbs-Blended-Concrete Durability With Modified Water Permeability Method, Soumyaranjan Panda, Supratic Gupta, Saubhagya Kumar Panigrahi

International Conference on Durability of Concrete Structures

The construction industry is increasingly embracing sustainable materials to mitigate environmental concerns and reduce the carbon footprint of conventional practices. Concrete, a vital material in modern infrastructure, is valued for its versatility and durability. However, Ordinary Portland Cement (OPC), the primary binder in conventional concrete, presents significant environmental challenges, including high carbon dioxide emissions and substantial energy consumption. With an annual growth rate of 2.5%, cement production exacerbates these issues, necessitating sustainable alternatives. Ground granulated blast-furnace slag (GGBS), a byproduct of the iron industry, is a promising supplementary material. Its use reduces cement consumption, enhances sustainability, and promotes eco-friendly construction …

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Relationship Between Water Contents And Electrical Conductivity In Concrete, Ki-Tae Park, Jaehwan Kim, Dong-Woo Seo, Sangki Park Oct 2025

Relationship Between Water Contents And Electrical Conductivity In Concrete, Ki-Tae Park, Jaehwan Kim, Dong-Woo Seo, Sangki Park

International Conference on Durability of Concrete Structures

This study investigates the relationship between moisture absorption and electrical conductivity in concrete, aiming to evaluate the feasibility of using electrical impedance as a non-destructive indicator of moisture transport behaviour. Concrete specimens with varying water-to-cement (w/c) ratios were prepared and conditioned for 150 days under controlled air-drying conditions. Moisture absorption tests were conducted in accordance with ASTM C1585-20, and both weight change and impedance were measured over time. Impedance data were collected across a wide frequency range (10 Hz to 1 MHz) using a two-point measurement configuration, and direct current (DC) electrical conductivity was derived through nonlinear regression analysis based …

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Life Cycle Assessment Of Semi-Submerged Offshore Wind Turbines’ Foundation Materials: Concrete Versus Steel, Isabel C L Castellanos, Andrew Whyte, Stephen M. Urquhart Oct 2025

Life Cycle Assessment Of Semi-Submerged Offshore Wind Turbines’ Foundation Materials: Concrete Versus Steel, Isabel C L Castellanos, Andrew Whyte, Stephen M. Urquhart

International Conference on Durability of Concrete Structures

The offshore wind-generation energy sector in Australia has been growing steadily in lieu of non-renewable energy sources, towards addressing national calls for greenhouse gas emission reductions. However, the industry in Australia is still somewhat fledgling, hence localised studies on environmental impact are scarce. In this context, the work here analyses greenhouse gas emissions by comparing like-for-like steel versus concrete materials as the main components in the foundation element of an offshore wind turbine throughout its lifecycle, using an adapted Life Cycle Assessment (LCA) method. This paper details a cradle-to-cradle LCA of the two alternative specifications for semi-submerged foundations supporting a …

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Use Fibre Optic Sensor Systems For Structural Integrity Monitoring In Ageing Sewer Concrete Structures And Pipelines, Matthas Fabian, Joanna Coote, Richard Harry Scott, Heriberto Bustamante, Tong Sun, Kenneth Thomas Victor Grattan Oct 2025

Use Fibre Optic Sensor Systems For Structural Integrity Monitoring In Ageing Sewer Concrete Structures And Pipelines, Matthas Fabian, Joanna Coote, Richard Harry Scott, Heriberto Bustamante, Tong Sun, Kenneth Thomas Victor Grattan

International Conference on Durability of Concrete Structures

Fibre Bragg Gratings (FBGs) form the basis of a valuable class of sensors that have a number of applications in industry and are formed as a periodic variation in the refractive index of an optical fibre that reflects light at a specific wavelength depending on the strain applied to the fibre – this effect can be related to and then calibrated against the parameter to be measured. A number of different types of sensors have been developed for monitoring sewer structures, detecting strain and potential leaks in sewer pipelines by embedding fibres along the pipeline route and for monitoring the …

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Toward Durable 3d Printed Structures, David A. Lange, Chenyue Shen Oct 2025

Toward Durable 3d Printed Structures, David A. Lange, Chenyue Shen

International Conference on Durability of Concrete Structures

Durability of 3-D printable concrete begins with control of flow and consolidation of the fresh material. 3D printed concrete needs to be fluid-like for pumping and extrusion but solid-like during placement to support the printed structure. High quality 3D printed materials must have excellent consolidation and a low volume of trapped voids. In practice, achieving this balance is challenging. This research addresses these challenges by leveraging machine learning and numerical simulation to model the fresh behavior of cement-based materials for 3-D printing. It begins with rheological characterisation to understand how mixture design factors influence rheological properties, laying the foundation for …

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Chloride Transport In Low Clinker Content Concretes And Modeling, Pu Yang, Narayanan Neithalath, Manu Santhanam, Yuvaraj Dhandapani Oct 2025

Chloride Transport In Low Clinker Content Concretes And Modeling, Pu Yang, Narayanan Neithalath, Manu Santhanam, Yuvaraj Dhandapani

International Conference on Durability of Concrete Structures

Chloride ion transport behaviour has been reported to be significantly influenced by the use of supplementary cementing materials in concrete, both due to physical effects such as pore structure refinement and chemical effects including chloride binding. This paper provides experimental results on diffusion of chloride ions through concretes containing limestone calcined clay as a cement replacement material at ~50% replacement level, demonstrating the beneficial effects of high-volume replacement of cement with calcined clay. A numerical simulation framework that considers the pore structure of concrete, the concentration-dependence of diffusion coefficient, and Freundlich binding is also presented. The diffusion model is augmented …

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Challenges And Opportunities In Concrete Precast Sector And Its Transition To A Net-Zero Future, Sreejith Nanukuttan, Rory Doherty, Daniel Mcpolin, Marios Soutsos, Mark Russell Oct 2025

Challenges And Opportunities In Concrete Precast Sector And Its Transition To A Net-Zero Future, Sreejith Nanukuttan, Rory Doherty, Daniel Mcpolin, Marios Soutsos, Mark Russell

International Conference on Durability of Concrete Structures

This article explores key factors shaping the transition of the precast concrete sector toward net-zero carbon. While not exhaustive, it highlights areas of scientific and technical interest for a specialist audience. The discussion is structured around priority themes: beginning with cement and clinker replacement, followed by production efficiency improvements, rethinking steel usage, carbon sequestration strategies, and, finally, structural optimisation or volume reduction. These areas are often interdependent: for instance, clinker replacement, production efficiency, and structural optimisation are all influenced by the 16 – 18 hour production cycle typical of precast manufacturing. Unlike the readymix sector, precast operates on a fast-paced, …

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Enhancing Concrete Circularity In Construction: The Recyclebim Framework In Closing Material Loops, Miguel Azenha, Artur Kuzminykh, José Granja, Manuel Parente, M. Albadri, P. González-Cabaleiro, R. Túñez-Alcalde, Lucía Díaz-Vilariño, C. Cao, N. Ukrainczyk, E. Koenders, A. J. Babafemi, M. Colyn, W. De Villiers, A. Ditlhokwa, H. Els, K. Timm, G. Van Zijl, E. Ameh, J. Immelman, V. Ndjate, L. Petrik, E. Ciampi, G. Nisivoccia, M. G. Orecchio, E. Sandonis, V. Garcia, D. Garcia, A. Delaplace Oct 2025

Enhancing Concrete Circularity In Construction: The Recyclebim Framework In Closing Material Loops, Miguel Azenha, Artur Kuzminykh, José Granja, Manuel Parente, M. Albadri, P. González-Cabaleiro, R. Túñez-Alcalde, Lucía Díaz-Vilariño, C. Cao, N. Ukrainczyk, E. Koenders, A. J. Babafemi, M. Colyn, W. De Villiers, A. Ditlhokwa, H. Els, K. Timm, G. Van Zijl, E. Ameh, J. Immelman, V. Ndjate, L. Petrik, E. Ciampi, G. Nisivoccia, M. G. Orecchio, E. Sandonis, V. Garcia, D. Garcia, A. Delaplace

International Conference on Durability of Concrete Structures

Despite significant progress in digitalisation across various sectors, the development of data-driven applications in the built environment remains ongoing, with a focus on improving labour productivity and addressing global sustainability challenges. The circular economy framework for reusing and recycling construction materials is still underexplored. Metrics on the amount and impact of construction and demolition waste (CDW) highlight the need for more effective circularity strategies. Although the circular economy seeks to minimise waste, maximise material reuse, and reduce environmental impacts, practical implementation within the construction sector requires further development—an area where digital technologies can offer substantial support. This study introduces the …

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Decalcification Of Calcium Silicate Hydrate By Sulfate Attack: Material Degradation By Heterogeneous Charges, Muhan Wang, Xiangming Zhou, Chengbo Liu, Pan Wang, Dongshuai Hou Oct 2025

Decalcification Of Calcium Silicate Hydrate By Sulfate Attack: Material Degradation By Heterogeneous Charges, Muhan Wang, Xiangming Zhou, Chengbo Liu, Pan Wang, Dongshuai Hou

International Conference on Durability of Concrete Structures

Sulfate attack is a key factor limiting the durability of concrete in aggressive environments, primarily through the degradation of calcium silicate hydrate (C–S–H), the main binding phase of cement. This study investigates the molecular mechanisms of C–S–H decalcification under sulfate exposure by combining semi-empirical Born–Oppenheimer molecular dynamics (BOMD) with density functional theory (DFT). A C–S–H model with a Ca/Si ratio of 1.5 was simulated in aqueous environments with and without sulfate ions. BOMD trajectories revealed that while C–S–H remained largely stable in pure water, sulfate ions rapidly promoted Ca²⁺ desorption, leading to silicate chain fragmentation and Q²→Q¹ transitions. Electronic structure …

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Fractal Characterisation Of Crack Tortuosity And Its Correlation With Permeability In Concrete, Yuan Shen, Tamon Ueda Oct 2025

Fractal Characterisation Of Crack Tortuosity And Its Correlation With Permeability In Concrete, Yuan Shen, Tamon Ueda

International Conference on Durability of Concrete Structures

This study investigated fracture behaviour in four concrete grades (C40-C70) through controlled splitting tests. Using high-resolution 3D profilometry, we quantitatively characterised crack surface morphology and proposed a novel fractal dimension metric for tortuosity D_T. Post-repair permeability tests on 12 specimens (24 fracture surfaces) revealed: (1) conventional tortuosity showed weak permeability correlation (R²<0.350), while (2) D_T demonstrated superior predictive capability (R²=0.430). The developed fractal tortuosity index provides a robust multiscale quantification method for crack flow mechanism analysis.

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Utilisation Of Semi-Naturally Carbonated Steelmaking Slag As Concrete Aggregate, Sumire Nakamura, Yuichiro Kawabata Oct 2025

Utilisation Of Semi-Naturally Carbonated Steelmaking Slag As Concrete Aggregate, Sumire Nakamura, Yuichiro Kawabata

International Conference on Durability of Concrete Structures

Steelmaking slag has emerged as a promising material for low-carbon concrete, owing to its ability to sequester CO₂ through carbonation. However, CO2 sequestration by steelmaking slag and its utilisation is still far from practical application due to the high energy consumption and cost of the accelerated carbonation process. Anticipating that optimising the pre-natural carbonation during storage would reduce the energy and cost for accelerated carbonation, this study focused on the natural carbonation potential of steelmaking slag. In addition, the applicability of naturally carbonated steelmaking slag as aggregate for concrete was investigated. The long-term exposure experiment simulating outdoor storage demonstrated that …

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