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Surrogate-assisted evolutionary algorithms (SAEAs) have been successfully applied to solve computationally expensive optimization problems. However, most SAEAs struggle to achieve good results in solving complex multimodal problems, especially ...

• A multi-region hierarchical surrogate-assisted quantum-behaved particle swarm optimization is proposed.
• A search behavior selection strategy is proposed to better balance exploration and exploitation.
• Adaptive region adjustments ...

Deep learning (DL) systems have been widely utilized across various domains. However, the evolution of DL systems can result in regression faults. In addition to the evolution of DL systems through the incorporation of new data, feature evolution, such as ...

Recently, the rise of code-centric Large Language Models (LLMs) has reshaped the software engineering world with low-barrier tools like Copilot that can easily generate code. However, there is no correctness guarantee for the code generated by LLMs, ...

The concept of deep learning (DL) compiler was proposed to deploy DL models more efficiently on diverse hardware through optimization techniques. As one of the most popular DL compilers, TVM incorporates three levels (high-level, schedule, and low-level) ...

Text guided image diffusion model has demonstrated remarkable ability in consistent image generation. In this paper, we introduce a training free image composition framework that realizes the non-rigid objects composition based on a pair of source ...

Recent advancements in Multimodal Large Language Models (MLLMs) have enabled to process diverse input modalities, leading to significantly better understanding of multimedia contents. However, understanding videos is still difficult and even the ...

• Uniform policy and option menu strategies are examined for AI-enabled products.
• Heterogeneity of privacy concerns and externality of consumer information are considered.
• Firm profit, privacy transfer scale, consumer surplus and ...

The increasing use of artificial intelligence (AI) to enhance products and services has enabled personalized offerings and smarter functionalities through the analysis of consumer data. However, privacy concerns present significant challenges to ...

The Versatile Video Coding (VVC) standard introduces a quad-tree with a nested multi-type tree (QTMT) partition structure to improve the rate-distortion (RD) performance, but this leads to a substantial increase in encoding complexity. Previous studies ...

Collaborative software development significantly enhances development productivity by enabling multiple contributors to work concurrently on different branches. Despite these advantages, such collaboration often increases the likelihood of causing ...

To explore the feasibility of high‐frequency indoor wireless body area network (WBAN) communications, the propagation characteristics of WBAN in simulated hospital ward scenarios at 11 GHz are studied. Based on the extensive measured data, the ...

To explore the feasibility of high‐frequency indoor wireless body area network (WBAN) communications, the propagation characteristics of WBAN in hospital ward scenarios at 11 GHz are studied. Based on the extensive measured data, the impact of the ...

• Retailers’ channel strategy during normal and pandemics periods are investigated.
• A two-dimensional spatial location model captures consumers’ dual heterogeneity.
• The impact of public health measures on retailers’ channel strategy ...

During COVID-19, public health measures triggered shifts in consumer behavior, disrupting supply chains and challenging physical stores’ viability. To navigate this uncertainty, retailers must adjust their channel strategies. Considering consumer ...

Machine learning models are increasingly used for impactful decisions, such as loan approval, criminal sentencing, and resume filtering, raising concerns about ensuring fairness without sacrificing performance. However, fairness has multiple ...

For a bus driver, the environment outside the bus door contains a serious visual blind spot. When a bus is parking, waiting for passengers boarding, and exiting the bus station, this blind spot requires the driver to maintain a high degree of attention. ...

On the one hand, there has been considerable progress on neural network verification in recent years, which makes certifying neural networks a possibility. On the other hand, neural networks in practice are often re-trained over time to cope with new ...

Quantization plays an important role in deploying neural networks on embedded, real-time systems with limited computing and storage resources (e.g., edge devices). It significantly reduces the model storage cost and improves inference efficiency ...

There are various security-critical decisions routinely made, based on information provided by peers: routing messages, user reports, sensor data, navigational information, blockchain updates, etc. Jury theorems were proposed in sociology to make ...

Knowledge tracking (KT) is a task that predicting the degree of students’ knowledge mastery through their learning interaction records. Although existing works improve predictive capability with well-designed neural network models or hypothetical ...

Accurate localization of apple fruits and recognition of occlusion types in complex orchard environments play an important role in precision agriculture. This work proposes an efficient fruit recognition model called Efficient Spatial and Channel ...

We study the problem of programming knowledge tracing (PKT) where the goal is to track the student’s mastery of programming skills during programming assignment tasks. Previous approaches typically focused on either the structural or contextual ...