Building design review is the procedure of checking a design against codes and standard provisions to satisfy the accuracy of the design and identify non-compliances before construction begins. The current approaches for conducting the design review...
The rapid growth of smart home technologies, driven by the expansion of the Internet of Things (IoT), has introduced both opportunities and challenges in automating daily routines and orchestrating device interactions. Traditional rule-based automati...
The existence of multiplicative noise in synthetic aperture radar (SAR) images makes SAR segmentation by fuzzy c-means (FCM) a challenging task. To cope with speckle noise, we first propose an unsupervised FCM with embedding log-transformed Bayesian...
Artificial intelligence (AI) has reshaped higher education over six decades, evolving from drill-and-practice programs to adaptive cognitive tutors and, most recently, transformer-based generative models. This article presents a critical review of pu...
Naive Bayes (NB) is one of the essential algorithms in data mining. However, it is rarely used in reality because of the attribute independence assumption. Researchers have proposed many improved NB methods to alleviate this assumption. Among these m...
Industrial image anomaly detection is critical for automated manufacturing. However, most existing methods rely on single-category training paradigms, resulting in poor scalability and limited cross-category generalization. These approaches require s...
Early and reliable diagnosis of inter-turn short-circuit (ITSC) faults is critical to maintaining the reliability, availability, and safe operation of doubly fed induction generators (DFIGs) used in wind energy conversion systems (WECSs). Incipient w...
The teacher–student framework is widely employed for cross-domain object detection. However, it suffers from two problems. One is that large distribution discrepancies will cause critical performance drops. The other is that the samples that de...
Amid growing divergence and confusion in Environmental, Social, and Governance (ESG) rating methodologies and results for assessing corporate sustainability, this study proposes a dual-dimensional framework that conceptualizes ESG rating quality thro...
Building information modelling (BIM) is a revolution in the architectural, engineering, and construction (AEC) industry. In the AEC industry, several interesting innovations are being introduced every day. Most of the code compliance work, which is t...
Gait plays a decisive role in the performance of hexapod robot walking; this paper focuses on adaptive gait generation with reinforcement learning for a hexapod robot. Moreover, the hexapod robot has a high-dimensional action space and therefore it i...
The Retrieval-Augmented Generation (RAG) framework shows great potential in terms of improving the reasoning and knowledge utilization capabilities of language models. However, most existing RAG systems heavily rely on large language models (LLMs) an...
Generating culturally coherent multimodal folktales presents unique challenges, particularly for underrepresented cultures facing data scarcity and cultural bias. Existing approaches predominantly rely on Western-centric corpora, limit outputs to tex...
Many of the next generation of adaptive optics systems on large and extremely large telescopes require tomographic techniques in order to correct for atmospheric turbulence over a large field of view. Multi-object adaptive optics is one such techniqu...
Emerging deep learning-based fault diagnosis methods have advanced in the current industrial scenarios of various working conditions. However, the prerequisite of obtaining target data in advance limits the application of these models to practical en...
Anomalous transaction behaviors in cryptocurrency markets exhibit high concealment, substantial diversity, and strong cross-modal coupling, making traditional rule-based or single-feature analytical methods insufficient for reliable detection in real...
Public Opinion Reports are essential tools for crisis management, yet their evaluation remains a critical bottleneck that often delays response actions. Recently, dominant Large Language Model (LLM)-based evaluators often overlook a critical challeng...
Recent advancements in generative AI have improved process mining, making workflow analysis more accessible and scalable. However, large language models lack structured reasoning and fail to capture sequential dependencies in workflows, limiting thei...
In smart manufacturing, efficient job shop scheduling (JSS) and resource management remain critical challenges, especially in dynamic production environments. Traditional methods often struggle to adapt to real-time changes and unexpected events. To...
High-Mix Low-Volume (HMLV) manufacturing increasingly relies on heterogeneous robot fleets, but automatic generation of vendor-specific robot control code remains difficult due to platform fragmentation and safety-critical feasibility constraints. Al...
We present Liquid Adaptive AI as a theoretical framework and mathematical basis for artificial intelligence systems capable of continuous structural adaptation and autonomous capability development. This work explores the conceptual boundaries of ada...
Translating voxel geometry and connection rules into functional housing organization without binding a method to a single predefined module remains a challenge in computational housing design. This study develops a voxel-based parametric framework li...
With the increasing integration of wind and photovoltaic power, the security and stability of the power system operations are greatly influenced by the intermittency and fluctuation of these renewable sources of energy generation. The accurate and re...
Retrieval-Augmented Generation (RAG) has been observed to encounter challenges in heterogeneous query scenarios characterised by varying evidence requirements and reasoning depths. In order to address this limitation, the present paper puts forward a...
Retrieval-augmented generation (RAG) addresses the problem of knowledge cutoff and overcomes the inherent limitations of pre-trained language models by retrieving relevant information in real time. However, challenges related to efficiency and accura...
This study proposes a generalized framework for the assessment of flood risk and potential strategies to mitigate flood under various vulnerability and adaptation scenarios. The possible causes of hazard, exposure and vulnerability in flood disaster...
The coal cost of coal-fired units accounts for more than 70% of the total power generation cost. In addition to determining coal costs, coal blending strategies (CBS) significantly impact various types of costs, such as pollutant removal and emission...
In this paper, we present a Unified Framework for cross-domain Space drone Pose Estimation (UF-SPE), addressing the simulation-to-reality gap that limits the deployment of deep learning models in real space missions. The proposed UF-SPE framework int...
Cloud services offer doctors and data scientists access to medical data from multiple locations using different devices (laptops, desktops, tablets, smartphones, etc.). Therefore, cyber threats to medical data at rest, in transit and when used by app...
The flexible and precise design of photovoltaic (PV) skin morphologies for building facades constitutes a critical element for optimizing building energy efficiency and enhancing indoor spatial performance. However, the complex interrelationships amo...
The industrial manufacturing model is undergoing a transformation from a product-centric model to a customer-centric one. Driven by customized requirements, the complexity of products and the requirements for quality have increased, which pose a chal...
Retrieval-augmented generation (RAG) is promising for long-document question answering, but its performance is often limited by fixed-window chunking, query-document mismatch, and static context truncation. This study proposes SES-RAG, a lightweight...
Elderly patients often experience multimorbidity and long-term polypharmacy, making medication safety a critical challenge in disease management. In China, the concurrent use of Western medicines and proprietary Chinese medicines (PCMs) further compl...
With the rapid expansion of AR/VR-based digital platforms, there is an increasing demand for the automated generation of size-varied 3D shoe assets. However, conventional CAD-based linear scaling and PCA-based global statistical shape models are limi...
The compelling visualization of Digital Elevation Models (DEMs) constitutes a vital intersection between Geographic Information Science (GIS) and the digital humanities. Nevertheless, traditional Generative Adversarial Networks (GANs) frequently demo...
Water is the primary medium through which climate change influences the Earth’s ecosystems and therefore people’s livelihoods and wellbeing. Besides climatic change, current demographic trends, economic development and related land use changes have d...
Peri-implant marginal bone stability remains a major determinant of long-term implant success, yet clinical studies report early marginal bone changes ranging from near-stable conditions in some protocols to approximately 1–2 mm during the firs...
Climate change is transforming energy use at the residential level by increasing temperature fluctuations and sustaining extreme weather events. This study proposes a climate-reactive, multi-objective approach to integrate the demand response (DR) wi...
This study aims to investigate the integration of generative artificial intelligence (GAI) and advanced large language models (LLMs) in financial sentiment research, focusing on improving the accuracy and robustness of financial sentiment classificat...
Rapidly evolving family structures have intensified the demand for residential layouts that can flexibly adapt to diverse spatial and functional needs. Conventional design approaches, whether manual or computer-aided, often fail to maintain user-cent...
This paper integrates Adaptive Information Processing (AIP), the Window of Tolerance (WoT), and Hobfoll’s Conservation of Resources (COR) theory into a unified framework for understanding trauma and therapeutic change. We propose that COR, whic...
Design practitioners and academics have increasingly recognised the potential value of design for behaviour change. On the one hand, while existing studies address product or communication design as main interventions, there is a growing interest in...
Industrial visual inspection relies heavily on unsupervised anomaly detection due to the scarcity of annotated defect samples. However, existing methods struggle to balance global structural consistency and local defect sensitivity, leading to limite...
Inthispaper, adirectuncertaintyminimizationframeworkisdevelopedanddemonstrated for model reference adaptive control laws. The proposed framework consists of a novel architecture involvingmodificationtermsintheadaptivecontrollawandtheupdatelaw. Inparti...
Generating mobile apps represents a big challenge in several areas, such as considering audience needs, adapting their user interfaces to such needs, dealing with design constraints or using different development technologies. The present work seeks...
To address the issue that distributed renewable energy grid-connected Virtual Synchronous Generator (VSG) systems are prone to significant power and frequency fluctuations under changing operating conditions, this paper proposes a multi-parameter coo...
This paper introduces a novel framework for addressing domain adaptation challenges in large language models (LLMs), emphasising privacy-preserving synthetic data generation and efficient fine-tuning. The proposed framework employs a multi-stage appr...
Indian mythological narratives contain long event chains, recurring characters, moral conflicts, interactions between human and divine agents, and source-specific narrative styles. General-purpose large language models can generate fluent text while...
Automatic pavement distress detection using deep learning has revolutionized maintenance efficiency, but deploying models in new, unseen scenarios presents significant challenges due to shifts in data distribution. Traditional transfer learning requi...
Recent advances in bioinspired robotics highlight the growing demand for dexterous, adaptive control strategies that allow robots to interact naturally, safely, and efficiently with dynamic, contact-rich environments. Yet, achieving robust adaptabili...
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