In civil engineering, crack detection using image processing has gained much attention among researchers and transportation agencies. As the often presents a fuzzy boundary random shape, it is difficult to achieve satisfactory performance. This study proposes method based on fractional differential fractal dimension. achieves enhancement extraction in two stages. First, an algorithm applied solve boundary. can enhance information significantly while simultaneously maintaining texture...

With digital information applied in intelligent transportation system, pavement crack detection with twins has drawn widely attention since the past several years. However, it is still a challenge task to accomplish satisfactory results due complex background. This paper presents method based on 3D edge representation and data communication twins. Firstly, achieved by multiple sensors including video scanning technology, model constructed communication. Secondly, distinguish between feature...

Semantic segmentation of high-resolution remote sensing images based on deep learning has become a hot research topic and been widely applied. At present, the structure convolutional neural network, when extracting target features through multiple layer layers, it is easy to cause loss small fuzzy boundary ground object classification. Therefore, we propose image semantic method P-Net detect enhance edge feature. The proposed network was an Encoder-Decoder structure. decoder included...

With the development of wireless technology, indoor localization has gained wide attention. The fingerprint method is proposed in this paper, which divided into two phases: offline training and online positioning. In phase, Improved Fuzzy C-means (IFCM) algorithm for regional division. Between-Within Proportion (BWP) index selected to divide database, can ensure result division consistent with building plane structure. Moreover, Agglomerative Nesting (AGNES) applied accomplish Access Point...

Human activity recognition (HAR) has vital applications in human–computer interaction, somatosensory games, and motion monitoring, etc. On the basis of human accelerate sensor data, through a nonlinear analysis time series, novel method for HAR that is based on non-linear chaotic features proposed this paper. First, C-C G-P algorithm are used to, respectively, compute optimal delay embedding dimension. Additionally, Reconstructed Phase Space (RPS) formed while using time-delay accelerometer...

With artificial intelligence prevailing in intelligent transportation system, pavement crack detection with deep learning has aroused wide attentions both academia and sector. Nevertheless, it still remains a challenge to accomplish due the complexity background. Motivated by latest advents computer vision research, fractional integral-based filtering method is advocated remove noise, fractal dimension estimation also emerged present shape feature at pixel level, multi-scale architecture....

Large Language Models (LLMs) have achieved remarkable success across various domains, yet deploying them on mobile devices remains an arduous challenge due to their extensive computational and memory demands. While lightweight LLMs been developed fit environments, they suffer from degraded model accuracy. In contrast, sparsity-based techniques minimize DRAM usage by selectively transferring only relevant neurons while retaining the full in external storage, such as flash. However, approaches...

With the wide application of data mining and deep learning in mobile cellular network operation maintenance, measurement report (MR) plays an increasingly important role artificial intelligence for IT operations (AIOps). For integrity MR reported by maintenance (OM) proxy base station, existing collecting methods are typically based on static distributed clustering. Due to lack effective load balancing scheme, nevertheless, these result some issues, e.g., low efficiency, poor scalability,...

The popularity of mesoscopic whole-brain imaging techniques has increased dramatically, but these generate teravoxel-sized volumetric image data. Visualizing or interacting with massive data is both necessary and essential in the bioimage analysis pipeline; however, due to their size, researchers have difficulty using typical computers process them. existing solutions do not consider applying web visualization three-dimensional (3D) volume rendering methods simultaneously reduce number copy...

Glycosidases are essential for the industrial production of functional oligosaccharides and many biotech applications. A novel β-galactosidase/α-L-arabinopyranosidase (PpBGal42A) glycoside hydrolase family 42 (GH42) from Paenibacillus polymyxa KF-1 was identified functionally characterized. Using pNPG as a substrate, recombinant PpBGal42A (77.16 kD) shown to have an optimal temperature pH 30 °C 6.0. pNPαArap were 40 7.0. has good stability. Furthermore, Na+, K+, Li+, Ca2+ (5 mmol/L) enhanced...

With the development of computer vision technology, crack detection based on digital image segmentation method arouses global attentions among researchers and transportation ministries. Since always exhibits random shape complex texture, it is still a challenge to accomplish reliable results. Therefore, novel fractal DBC (differential box counting) introduced in this paper. The proposed can estimate every pixel feature neighborhood information which consider contribution from all possible...

This paper presents a new change detection method based on fractional integral and improved FLICM clustering. Firstly, the log-ratio operator is applied to obtain difference image from two registered corrected remote sensing images; then, introduced de-nosing preserve edge texture information of image; Finally, carried out get areas, which fully considering pixel neighborhood spatial distance objective function. Experimental results show that proposed algorithm has strong ability suppress...