Search Results

• The seru formation problem considering demand fluctuations is studied.
• Two multi-objective stochastic models are constructed.
• CVaR is utilized to measure the performance of the system in worst-case scenarios.
• An enhanced ...

The increasingly diverse and non-deterministic customer demands have given rise to the seru production system. This study aims to address the multi-objective seru formation problem under demand fluctuations, with the mean and the CVaR or standard ...

Pavement disease is a key factor affecting road safety, and regular inspection and maintenance play an important role in maintaining the performance of asphalt pavement. Manual crack detection is subjective and inefficient. Even with the rapid development ...

Vortical flow animation has attracted considerable attention within the realm of computer graphics. Given that boundaries are the source of vorticity, we introduce a novel approach for the wall-bounded flow simulation in the vortex dynamics ...

Display Omitted

• A boundary treatment method to accurately describe the boundary vorticity generation.
• A computation method for boundary viscosity to capture the boundary layer dynamics.
• A vortex dynamics approach to simulate the complex wall-...

Multi-lead electrocardiogram (ECG) is a fundamental and reliable diagnostic tool for the detection of heart arrhythmias. An increasing number of deep neural network models have been proposed for automatic arrhythmia detection using multi-lead ...

Text-based audio generation models have limitations as they cannot encompass all the information in audio, leading to restricted controllability when relying solely on text. To address this issue, we propose a novel model that enhances the ...

• A novel ECG Diagnosis model for mobile devices is proposed based on dynamic neural network.
• The model has high inference efficiency and device versatility opposed to static models.
• Two multi-classifier collaborative learning ...

Mobile health devices with automatic electrocardiogram diagnosis models facilitate long-term cardiac monitoring and enhance the sensitivity of detecting paroxysmal cardiovascular disease. However, these devices often encounter limitations in ...

Lesion segmentation of ultrasound medical images based on deep learning techniques is a widely used method for diagnosing diseases. Although there is a large amount of ultrasound image data in medical centers and other places, labeled ...

• Transfer learning is used for ultrasound image segmentation across tissues/organs.

Cluster analysis discovers natural structures from different perspectives of data objects and has become an effective method in data mining. The emergence of semi-supervised clustering techniques has improved the performance of ...

• A knowledge augmentation-based semi-supervised clustering method is proposed to deal with the constraint conflict scenario in pairwise constraint semi-...

The interdisciplinary knowledge integration has become a typical feature in the development of modern science, which has promoted the production of original scientific achievements and major breakthroughs. The interdisciplinary network describes ...

Speech enhancement shows an important necessity in many audio applications, particularly in noisy environments, where the speech quality needs to be improved. In this work, we consider the single-channel noise reduction (NR) problem from the conventional ...

Wireless acoustic sensor network (WASN) has shown a superiority over conventional microphone arrays in many aspects. There exists an important tradeoff between the performance and power consumption, as usually the sensors are power driven with a limited ...

This study proposes a novel interpretable framework to forecast the daily tourism volume of Jiuzhaigou Valley, Huangshan Mountain, and Siguniang Mountain in China under the impact of COVID-19 by using multivariate time-series data, particularly ...

We propose a pure Lagrangian vortex particle dynamics framework to simulate the various phenomena of turbulent smoke and two-way coupling between fluid and solid. In the framework, we model the fluid using vorticity and velocity fields ...

Display Omitted

• We present a pure Lagrangian vortex particle dynamics framework for smoke simulation.

In order to solve the problem that corporate financial risks seriously affect the healthy development of enterprises, credit institutions, securities investors, and even the whole of China, the K-means clustering algorithm, the risk screening process, and ...

Many applications need a hierarchical image representation as a tool for unifying formalism. The level line tree model is such a tool, using a two-tree (the positive and negative level line trees) scheme to represent an image. The two trees differ only ...

We propose a novel Lagrangian geometric representation using segment clouds to simulate incompressible fluid exhibiting strong anisotropic vortical features. The central component of our approach is a cloud of discrete segments enhanced by a set of ...

Level set methods are fruitful in computer vision, image coding, image processing, geographic information systems, and many other fields. The connected components of the level sets of an image, ordered by inclusion, are organized into a component ...

Punishment plays an important role in promoting cooperation. In real society, individuals tend to punish other players based on certain conditions rather than punish them directly. Thus, we introduce a conditional neutral punishment ...

Multi-exponentiation is very important in varies cryptographic and digital signatures. In the situation like electronic cash and SNS websites, the server need to answer a mass of requests in a short time. With every request, there are always processes of ...

As positioning technology is an important foundation of the Internet of Things, a dynamic indoor WLAN localization system is proposed in this paper. This paper mainly concentrates on the design and implementation of the WiMap-a dynamic indoor WLAN ...