A graph signal is a random vector with a partially known statistical description. The observations are usually sufficient to determine marginal distributions of graph node variables and their pairwise correlations representing the graph edges. Howeve...
How does a social venture build multiple partnerships among stakeholders to enable a wide range of social value propositions and alleviate economic inequality? We address this question by developing a new concept on generative partnerships, defined a...
The human brain is approximately a symmetric structure, although the functional brain does not exhibit symmetry. Functional brain aging process modelling is essential for the understanding of hypothesized generative mechanisms for human brain network...
This study explores the application of generative artificial intelligence (AI) in financial risk forecasting, aiming to assess its potential in enhancing both the accuracy and interpretability of predictive models. Traditional methods often struggle...
While Machine Learning has become the holy grail of modern-day computing, it has many security flaws that have yet to be addressed and resolved. Adversarial attacks are one of these security flaws, in which an attacker appends noise to data samples t...
Document-grounded conversation (DGC) is a natural language generation task to generate fluent and informative responses by leveraging dialogue history and document(s). Recently, DGCs have focused on fine-tuning using pretrained language models. Howev...
Simulated data play an important role in SAR target recognition, particularly under zero-shot learning (ZSL) conditions caused by the lack of training samples. The traditional SAR simulation method is based on manually constructing target 3D models f...
Smart contracts are central to blockchain ecosystems, yet their development remains technically demanding, error-prone, and tied to platform-specific programming languages. This paper introduces SCEditor-Web, a web-based modeling environment that com...
We propose a generative model of the legend. The model is elaborated based on two case studies, the first of contemporary storytelling related to vaccination on parenting blogs, and the second of historical storytelling related to witchcraft and folk...
In a wide range of applications, heating or cooling systems provide not only temperature changes, but also small temperature gradients in a sample or industrial facility. Although a conventional proportional-integral-derivative (PID) controller usual...
In the industrial sector, malfunctions of equipment that occur during the production and operation process typically necessitate human intervention to restore normal functionality. However, the question that follows is how to design and optimize the...
This paper proposes a novel hybrid car-following model: the physics-informed conditional generative adversarial network (PICGAN), designed to enhance multi-step car-following modeling in mixed traffic flow scenarios. This hybrid model leverages the s...
This article presents a generative model for the inverse design of dual-band filters based on a type of modified complementary split-ring resonator (CSRR). It consists of a series of convolutional neural networks that incorporate the conditional deep...
In this paper, we study the problem of privacy-preserving data synthesis (PPDS) for tabular data in a distributed multi-party environment. In a decentralized setting, for PPDS, federated generative models with differential privacy are used by the exi...
Generative models for images, audio, text, and other low-dimension data have achieved great success in recent years. Generating artificial human movements can also be useful for many applications, including improvement of data augmentation methods fo...
Wildfires are one of the major disasters among many and are responsible for more than 6 million acres burned in the United States alone every year. Accurate, insightful, and timely wildfire detection is needed to help authorities mitigate and prevent...
A substantial amount of money and time is required to optimize resources in a massive Wi-Fi network in a real-world environment. Therefore, to reduce cost, proposed algorithms are first verified through simulations before implementing them in a real-...
Generative conversational systems consisting of a neural network-based structural model and a linguistic model have always been considered to be an attractive area. However, conversational systems tend to generate single-turn responses with a lack of...
Older adults often face significant challenges in understanding medical information due to cognitive aging and limited health literacy. Existing simplification models, while effective in general domains, cannot adapt content for elderly users, freque...
Body-worn sensors in general and accelerometers in particular have been widely used in order to detect human movements and activities. The execution of each type of movement by each particular individual generates sequences of time series of sensed d...
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In recent years, advanced methods and smart solutions have been investigated for the safe, secure, and environmentally friendly operation of ships. Since data acquisition capabilities have improved, data processing has become of great importance for...
Conventional pattern-recognition algorithms for surface electromyography (sEMG)-based hand-gesture classification have difficulties in capturing the complexity and variability of sEMG. The deep structures of deep learning enable the method to learn h...
Background: Significant progress has been made in the field of machine learning, enabling the development of methods for automatic interpretation of medical images that provide high-quality diagnostics. However, most of these methods require access t...
The perception systems of autonomous vehicles face significant challenges under adverse conditions, with issues such as obscured objects and false detections due to environmental noise. Traditional approaches, which typically focus on noise removal,...
The use of generative learning models in natural language processing (NLP) has significantly contributed to the advancement of natural language applications, such as sentimental analysis, topic modeling, text classification, chatbots, and spam filter...
This study proposes a neural-augmented Libor Market Model (LMM) for swaption surface calibration that enhances expressive power while maintaining the interpretability, arbitrage-free structure, and numerical stability of the classical framework. Clas...
Generative image models have revolutionized artificial intelligence by enabling the synthesis of high-quality, realistic images. These models utilize deep learning techniques to learn complex data distributions and generate novel images that closely...
The origin–destination (OD) matrix describes traffic flow information between regions. It is a critical input for intelligent transportation systems (ITS). However, obtaining the OD matrix remains challenging due to high costs and privacy conce...
The rapid development of generative artificial intelligence has paved the way for a new approach to reproduce and intelligently generate traditional patterns digitally. This paper focuses on the traditional Chinese phoenix pattern and constructs a &l...
Antimicrobial peptides (AMPs) provide a robust alternative to conventional antibiotics, combating escalating microbial resistance through their diverse functions and broad pathogen-targeting abilities. While current deep learning technologies enhance...
Ambisonic room impulse responses (ARIRs) are recorded to capture the spatial acoustic characteristics of specific rooms, with widespread applications in virtual and augmented reality. While the first-order Ambisonics (FOA) microphone array is commonl...
E-commerce applications have emerged as key drivers of digital transformation, reshaping consumer behavior and driving demand for seamless online transactions. Despite the growth of smart mobile technologies, existing methods rely on fixed UI content...
Nishikigoi are highly valued ornamental fish whose evaluation affects their market price. However, the judging criteria of the exhibitions remain unclear. This study applies a generative artificial intelligence model to explore potential factors behi...
Air pollution is one of the most pressing modern-day issues in cities around the world. However, most cities have adopted air quality measurement devices that only measure the past pollution levels without paying attention to the influencing factors....
This study investigates the factors influencing users’ intention to use generative AI by employing a Bayesian network-based probabilistic structural equation model approach. Recognizing the limitations of traditional models like the technology...
Brain decoding is a process of decoding human cognitive contents from brain activities. However, improving the accuracy of brain decoding remains difficult due to the unique characteristics of the brain, such as the small sample size and high dimensi...
The Building Houses on Rented Land Model (BHRLM) was a pivotal land development model that drove Shanghai’s urbanization in the early modern era. This research examines the spatial generative mechanism of the Prepaid Building Houses on Rented L...
Research on face recognition with masked faces has been increasingly important due to the prolonged COVID-19 pandemic. To make face recognition practical and robust, a large amount of face image data should be acquired for training purposes. However,...
This study addresses the academic gap in the adoption of generative AI systems by investigating the factors influencing technology acceptance and usage behavior in Korean firms. Although recent advancements in AI are accelerating digital transformati...
This paper introduces the Sextuple Helix Innovation Model as an extension of the Quintuple Helix Innovation Model by Carayannis and Campbell. The epistemic perspective considers the understanding of generative AI (GenAI) as a sixth helix of knowledge...
Accurate crude oil price forecasting is essential, considering oil’s critical role in the global economy. However, the crude oil market is significantly influenced by external, transient events, posing challenges in capturing price fluctuations...
In order to minimize the influence of decorrelation noise on multi-temporal interferometric synthetic aperture radar (MT-InSAR) applications, a series of phase reconstruction methods have been proposed in recent years. Unfortunately, current phase re...
The integration of large language models (LLMs) into structural engineering workflows presents both a transformative opportunity and a critical challenge. While LLMs enable intuitive, natural language interactions with complex data, their limited ari...
Blood pressure is a fundamental health metric widely employed to predict cardiac diseases and monitor overall well-being. However, conventional blood pressure measurement methods, such as the cuff method, necessitate additional equipment and can be i...
The rapid diffusion of “(GenAI)” Generative Artificial Intelligence systems has reshaped everyday activities, yet their adoption remains uneven and cognitively demanding for many users. Existing research has largely relied on conventional...
Sensory perception of forests is closely related to human health and well-being. Based on attention recovery theory and stress relief theory, this paper investigates the influence of sensory perception of forests on visitors’ restoration effect...
Current techniques for fault analysis in photovoltaic (PV) systems plants involve either electrical performance measurements or image processing, as well as line infrared thermography for visual inspection. Deep convolutional neural networks (CNNs) a...
The orthogonal frequency-division multiplexing (OFDM) transmission technique is well known to be efficient for data transmission but is susceptible to performance degradation due to factors such as high-order modulation schemes, multipath fading, and...
Generative Artificial Intelligence (GenAI)-assisted Virtual Reality (VR) heritage serious game design constitutes a complex adaptive socio-technical system in which natural language prompts act as control levers shaping designers’ cognition and...
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