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In view of the problems existing in the ESG classification task of Chinese financial texts, such as feature loss caused by excessively long texts, this paper proposes an interactive multi-task model AmultiESG for ESG classification of Chinese ...

In this paper we study the online over-time scheduling on an unbounded parallel-batch machine to minimize the weighted makespan. First, we show that the general problem has a low bound 2 and then design a 4-competitive online algorithm. ...$\frac{\sqrt{\mathrm{}}\mathrm{}}{\mathrm{}}\mathrm{}$$\frac{\sqrt{\mathrm{}}\mathrm{}}{\mathrm{}}\mathrm{}$$\frac{\mathrm{}}{\mathrm{}}\mathrm{}$

Sequential recommendation aims at mining user interests through modeling sequential behaviors. Most existing sequential recommendation methods overlook the direct transition relationship among items, and only encode a user sequence as a whole, ...

The accurate segmentation of retinal vessels (RV) and Foveal Avascular Zone (FAZ) is crucial for the retina health assessment. However, fusing OCT and OCTA images while projecting these 3D data for segmentation is a challenge. In this paper, we ...

• Propose a novel multi-modal fusion enhancement network for RV and FAZ joint segmentation based on OCT and OCTA.
• Design an end-to-end kernel adaptive projection (KAPM) for 3D to 2D and volume fusion (VFM) for data reuse.
• Achieve ...

Road inspection and cleaning are crucial to securing driving safety. Deploying a fleet of robots that run through a city can inspect and clean pavements without causing road closure. To achieve high coverage, one has to prevent robots from going through ...

Enzyme design plays a crucial role in both industrial production and biology. However, this field faces challenges due to the lack of comprehensive benchmarks and the complexity of enzyme design tasks, leading to a dearth of systematic research. ...

In this paper, we consider the problem of joint delay-Doppler estimation in an automotive radar based on orthogonal time frequency space (OTFS) modulation. We propose a super-resolution estimation approach that operates in the continuous domain ...

• A super-resolution approach is proposed to estimate delay and Doppler parameters for OTFS-based automotive radar.
• An ADMM-based fast algorithm is proposed to accelerate computation.
• Numerical studies are conducted to validate the ...

Structural magnetic resonance imaging characterizes the morphology and anatomical features of the brain and has been widely utilized in the diagnosis of developmental disorders. Given the dynamic nature of developmental disorder progression with ...

In diffusion MRI (dMRI), a uniform single or multiple shell sampling scheme is typically required for data acquisition in $\mathbf{q}$-space, because uniform spherical sampling offers the advantage of capturing more information using fewer samples, leading ...

The infant brain undergoes rapid development in the first few years after birth. Compared to cross-sectional studies, longitudinal studies can depict the trajectories of infants’ brain development with higher accuracy, statistical power and ...

How can we ensure that Ubiquitous Computing (UbiComp) research outcomes are ethical, fair, and robust? While fairness in machine learning (ML) has gained traction in recent years, it remains unexplored, or sometimes an afterthought, in the context of ...

Mental health and well-being influence overall health: suffering from a mental illness can create severe impairment and reduce quality of life. Ubiquitous computing technologies are beginning to play a central role in collecting clinically relevant ...

Deep learning models are highly vulnerable to adversarial examples, leading to significant attention on techniques for detecting them. However, current methods primarily rely on detecting image features for identifying adversarial examples, often ...

This figure abstract illustrates a method for identifying adversarial samples through noise injection and denoising. A benign sample, such as an image of a bird, is first transformed into an adversarial sample by adding perturbations. ...

• A new method for detecting adversarial samples with higher performance.
• Balances preserving original information and removing adversarial perturbations.
• Ability to reconstruct adversarial samples as benign samples.
• No threshold ...

The acoustic levitation technology expands the possibility of non-contact mass measurements, avoiding contact contamination and loss, particularly for tiny objects. Current acoustic levitated object mass estimation methods focus on the mechanism ...

We propose the Topology-Preserving Segmentation Network, a deformation-based model that can extract objects in an image while maintaining their topological properties. This network generates segmentation masks that have the same topology as the ...

Recent works have demonstrated that using reinforcement learning (RL) with multiple quality rewards can improve the quality of generated images in text-to-image (T2I) generation. However, manually adjusting reward weights poses challenges and may ...

Prior research has suggested that participation in peer feedback activities, specifically the giving and receiving of comments, and the implementation of suggested ideas helps to improve writing quality. However, it is not always the case that ...

• No correlation between implemented comments and student writing performance.
• Total comments moderates relationship between implementation and performance.
• The fewer comments received, the more impact implementation of them has.

In modern society, power communication networks play a crucial role, and their stable operation is essential for the safety and efficiency of power grids. In this paper, a distributed simulation system for power communication networks is proposed, aiming ...

The split delivery vehicle routing problem with three-dimensional loading constraints (3L-SDVRP) intertwines complex routing and packing challenges. The current study addresses 3L-SDVRP using intelligent optimization algorithms, which iteratively ...

In the finance domain, nested named entities recognition has become a hot topic in named entity recognition tasks. Traditional nested entity recognition methods easily ignore the dependency relationships between entities, and these methods are ...