The noninvasive fetal electrocardiogram (FECG) is helpful for well-being monitoring. However, it difficult to obtain high-quality FECG signals because of the maternal (MECG) and noise in abdominal ECG (AECG). To address this problem, an Adaptive Amplitude-Frequency Attention Network (AAFA-Net) proposed extracting from AECG signals, where Frequency Encoder-Decoder (FED) module developed distinguish frequency components Amplitude (AED) devised extract amplitude while Window (WED) designed...

Electric load forecasting (ELF) is always employed to perform power systems management. However, it difficult predict electric due the following issues: 1) prediction prone external interference, e.g., temperature and weather; 2) user behaviors are random, such as family gatherings business rush orders; 3) consumption varies significantly in different time periods. To solve problems, an adaptive sparse attention network (ASA-Net) proposed for ELF, where spatial (ASSA) module first designed...

<abstract><p>Bone age assessment is of great significance to genetic diagnosis and endocrine diseases. Traditional bone mainly relies on experienced radiologists examine the regions interest in hand radiography, but it time-consuming may even lead a vast error between result reference. The existing computer-aided methods predict based general do not explore specific radiography. This paper aims solve such problems by performing prediction articular surface epiphysis from...

Extracellular matrix (ECM) remodeling and inflammation in the infrapatellar fat pad (IPFP) are associated with cartilage degeneration severity of osteoarthritis (OA). Diabetes is progression OA. However, it still unclear whether diabetes can promote by targeting IPFP. In this study, we established a high-fat diet/streptozotocin (HFD/STZ)-induced mouse model. We found that fibrosis were more severe IPFP diabetic mice. Transcriptomic profiling showed MFAP5 expression was upregulated IPFPs...

Magnetic tile defect segmentation plays a vital role in magnet motor production. However, it is difficult to detect areas from the magnetic because of these issues: 1) There low contrast between defects regions and normal ones on surface; 2) The vary greatly, small are always masked by complex backgrounds. To tackle problems, Multi-View Residual Attention U-Net (MVRA-UNet) proposed for surface, where Gaussian Convolution (GRAC) module designed distinguish similar feature environments...

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Defect detection on magnetic tile surfaces is of great significance for the production monitoring permanent magnet motors. However, it challenging to detect surface defects from due these issues: 1) Defects appear randomly tile; 2) are tiny and often overwhelmed by background. To address such problems, an Adaptive Rotation Attention Network (ARA-Net) proposed defect surface, where Convolution (ARC) module devised capture random learning multi-view feature maps, then Region (RAA) designed...

Musculoskeletal abnormality is routinely presented in tissues and organs of the human locomotor system across life course, it essential to detect musculoskeletal X-rays. However, difficult diagnose from radiographs due following issues: 1) There are other interfering organ complicated backgrounds; 2)The MURA dataset contains seven different radiographs, which makes general convolution neural networks unable model weird relationship between them. To address such problems, a Lesion-Guided...

The indoor localization has attracted great attention in both academia and industry with the growing demands on location-based services. However, existing Wi-Fi fingerprint-based solutions are not sufficient for tracing moving target due to unexpected noises of measurements. In view this, this study is dedicated implementing a robust tracking system via joint fingerprint PDR (pedestrian dead reckoning) techniques. Specifically, we first propose two-steps approach, which K-Nearest-Neighbor...

<title>Abstract</title> To improve the performance of original dwarf mongoose optimization algorithm, this study proposes an elite leader algorithm (EL-DMOA). EL-DMOA adopts two stage structure. The employs differential operator to selected leaders. artificial fitness is introduced for selecting swarm If one individual’s ceasing improve, method will imposes additional punishment relevant individual, thereby newly founded solution encouraged lead swarm. In follower stage, each individual...

Knowledge utilization is a critical aspect of LLMs, and understanding how they adapt to evolving knowledge essential for their effective deployment. However, existing benchmarks are predominantly static, failing capture the nature LLMs knowledge, leading inaccuracies vulnerabilities such as contamination. In this paper, we introduce EvoWiki, an dataset designed reflect evolution by categorizing information into stable, evolved, uncharted states. EvoWiki fully auto-updatable, enabling precise...

Abstract It is very necessary for disease diagnosis, monitoring and treatment planning to locate segment brain tumours from 3D MRI images accurately. segmentation MRIs means classifying each voxel in space, it conducive the relevant biological measurements further analysis of lesion. Until now, tumour biomedical has been a challenging worldwide task due features’ variousness, which varies part U-Net concatenates these features, are upsampled same scale. To grasp channel weight ROIs,...

As with the continuous improvement of workshop automation rate and importance in energy consumption, more enterprises not only need to make scheduling decision on production equipment, but also consider whether transportation equipment supports decisions production. At same time, because both are NP-hard problems, it is necessary design an efficient algorithm improve productivity workshop. In order solve this problem, firstly, based analysis problem structure, environment optimization...

Recently, 3D Gaussian, as an explicit representation method, has demonstrated strong competitiveness over NeRF (Neural Radiance Fields) in terms of expressing complex scenes and training duration. These advantages signal a wide range applications for Gaussians understanding editing. Meanwhile, the segmentation is still its infancy. The existing methods are not only cumbersome but also incapable segmenting multiple objects simultaneously short amount time. In response, this paper introduces...

Social network plays an important role in propagating people's viewpoints, emotions, thoughts, and fears. Notably, following lockdown periods during the COVID-19 pandemic, issue of depression has garnered increasing attention, with a significant portion individuals resorting to social networks as outlet for expressing emotions. Using deep learning techniques discern potential signs from messages facilitates early identification mental health conditions. Current efforts detecting through...