17 accepted papers
The scarcity of parallel corpora for Mongolian and Chinese constrains the performance of Mongolian-Chinese neural machine translation (NMT), particularly manifesting in inadequate accuracy in translating specialized terminology. To address this limitation, this study adopts a lexically constrained a
In emergency response scenarios, rapid acquisition of critical disaster information supports effective decision-making. Traditional geometric coverage-based path planning often struggles to balance efficiency and information value. To address this, we propose a Disaster-Aware Informative Path Planni…
This work presents a flexible and effective micromixer based on optoelectronic tweezers (OET), which leverages both asymmetric induced-charge electro-osmosis (ICEO) and dielectrophoresis (DEP) phenomena on microscale anisotropic NdFeB particles. The asymmetric ICEO phenomenon is generated by symmetr
Biological machines that use biological cells and soft materials in combination to obtain a sense of the environment driven by bioenergy and generate driving force are called biohybrid actuators. With the development of tissue engineering and organoid technology, researchers have applied biohybrid a
The facial expression generation capability of humanoid social robots is critical for achieving natural and human-like interactions, playing a vital role in enhancing the fluidity of human-robot interactions and the accuracy of emotional expression. Currently, facial expression generation in humanoi
Radio maps enrich radio propagation and spectrum occupancy information, which provides fundamental support for the operation and optimization of wireless communication systems. Traditional radio maps are mainly achieved by extensive manual channel measurements, which is time-consuming and inefficien…
Magnetic microswarms have attracted significant attention in medical robotics, owing to their potential for performing complex tasks in challenging environments. However, developing microswarms that can operate effectively in both liquid and air environments remains a substantial challenge. This stu
This study describes a microfluidics experiment with ready classroom applications, designed to enhance students' understanding of fluid dynamics, controlled mixing, and bubble formation. The materials employed are safe and readily accessible, such as vinegar and baking soda, combined with PDMS micro
The regulation of muscle function is very important for tissue engineering and sports science. This paper presents a simple microfluidic chip platform and its control method to investigate the regulation of muscle function. By employing C2C12 cells as the model system for skeletal muscle research, t
Model-based shallow machine-learning methods and data-driven deep-learning (DL) methods have been advanced to address hyperspectral and multispectral image fusion (HS–MS fusion). Nonetheless, model-based approaches, which meticulously craft regularization terms within optimization models using hand-…
Tactile information is the research hotspot of wearable flexible sensors due to its importance and complexity. With the innovation of wearable technology and robotics in healthcare, researchers are increasingly integrating wearable flexible sensors on the front end of robots to reproduce the hand ta…
Precipitation nowcasting based on radar data plays a crucial role in extreme weather prediction and has broad implications for disaster management. Despite progresses have been made based on deep learning, two key challenges of precipitation nowcasting are not well-solved: (i) the modeling of comple…
Improving the spatial resolution of a hyperspectral image (HSI) is of great significance in the remotely sensed field. By fusing a high-spatial-resolution multispectral image (MSI) with an HSI collected from the same scene, hyperspectral and multispectral (HS–MS) fusion has been an emerging techniqu…
Mongolian morphological segmentation is regarded as a crucial preprocessing step in many Mongolian related NLP applications and has received extensive attention. Recently, end-to-end segmentation approaches with long short-term memory networks (LSTM) have achieved excellent results. However, the inn…
Age is an important biometric feature of human face. Estimating the specific age of facial images is challenging, because of face aging's highly nonlinearity and randomness. Commonly age predictors are based on classification or regression method, which may be affected greatly by the category number…
Unsupervised cross-database facial expression recognition (FER) is a challenging problem, in which the training and testing samples belong to different facial expression databases. For this reason, the training (source) and testing (target) facial expression samples would have different feature dist…
In this paper, we investigate an interesting problem, i.e., unsupervised cross-corpus speech emotion recognition (SER), in which the training and testing speech signals come from two different speech emotion corpora. Meanwhile, the training speech signals are labeled, while the label information of…