51 hasil untuk "Guiling Sun"
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Artikel Jurnal Teks lengkap
Real-Time Analysis and Intervention of Classroom Behavior Using Multi-Modal Fusion and Spatiotemporal Context
Analyzing classroom engagement is essential for developing effective smart learning environments. Conventional methods often face challenges in achieving reliable identification of individual students, accurately recognizing their behavioral states, and providing timely support. This paper presents…
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Computational prediction of MoRFs based on protein sequences and minimax probability machine
Abstract Background Molecular recognition features (MoRFs) are one important type of disordered segments that can promote specific protein-protein interactions. They are located within longer intrinsically disordered regions (IDRs), and undergo disorder-to-order transitions upon binding to their…
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SVD++ Recommendation Algorithm Based on Backtracking
Collaborative filtering (CF) has successfully achieved application in personalized recommendation systems. The singular value decomposition (SVD)++ algorithm is employed as an optimized SVD algorithm to enhance the accuracy of prediction by generating implicit feedback. However, the SVD++ algorithm…
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The Prediction of Intrinsically Disordered Proteins Based on Feature Selection
Intrinsically disordered proteins perform a variety of important biological functions, which makes their accurate prediction useful for a wide range of applications. We develop a scheme for predicting intrinsically disordered proteins by employing 35 features including eight structural properties…
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Prediction of MoRFs in Protein Sequences with MLPs Based on Sequence Properties and Evolution Information
Molecular recognition features (MoRFs) are one important type of intrinsically disordered proteins functional regions that can undergo a disorder-to-order transition through binding to their interaction partners. Prediction of MoRFs is crucial, as the functions of MoRFs are associated with many…
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Identification of Key Genes and Pathways in Renal Cell Carcinoma Through Expression Profiling Data
Background/Aims: To isolate key genes and pathways in renal cell carcinoma (RCC), which might reveal more evidences on the regulation network and contribute to pathogenic mechanisms of RCC. Methods: Microarray data of GSE34676, GSE23926 and GSE48008 were downloaded from Gene Expression Omnibus…
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MadgwickFall-Net: A Lightweight Dual-Frame Feature Fusion Network for Pre-Impact Fall Detection Using Wearable IMUs
As global population aging intensifies, fall-related injuries among the elderly have become a critical public health concern. Existing fall detection methods based on wearable IMUs all extract features in the sensor’s body frame, failing to exploit the information embedded in sensor signals. Some…
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Plant Diseases Recognition Based on Image Processing Technology
A new image recognition system based on multiple linear regression is proposed. Particularly, there are a number of innovations in image segmentation and recognition system. In image segmentation, an improved histogram segmentation method which can calculate threshold automatically and accurately…
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Genome-Wide Functional Analysis of the Cotton Transcriptome by Creating an Integrated EST Database
A total of 28,432 unique contigs (25,371 in consensus contigs and 3,061 as singletons) were assembled from all 268,786 cotton ESTs currently available. Several in silico approaches [comparative genomics, Blast, Gene Ontology (GO) analysis, and pathway enrichment by Kyoto Encyclopedia of Genes and…
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MicroRNA Expression Analysis in the Cellulosic Biofuel Crop Switchgrass ( Panicum virgatum ) under Abiotic Stress
Switchgrass has increasingly been recognized as a dedicated biofuel crop for its broad adaptation to marginal lands and high biomass. However, little is known about the basic biology and the regulatory mechanisms of gene expression in switchgrass, particularly under stress conditions. In this…
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Application of RAD Sequencing for Evaluating the Genetic Diversity of Domesticated Panax notoginseng (Araliaceae)
Panax notoginseng, a traditional Chinese medicinal plant, has been cultivated and domesticated for approximately 400 years, mainly in Yunnan and Guangxi, two provinces in southwest China. This species was named according to cultivated rather than wild individuals, and no wild populations had been…
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Multi-Attribute Data Recovery in Wireless Sensor Networks With Joint Sparsity and Low-Rank Constraints Based on Tensor Completion
In wireless sensor networks (WSNs), data recovery is an indispensable operation for data loss or energy constrained WSNs using sparse sampling. However, the recovery accuracy is not satisfying for WSNs with various sensor types due to the neglect of the correlation among multi-attribute data. In…
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Compressive Sparse Data Gathering With Low-Rank and Total Variation in Wireless Sensor Networks
Wireless Sensor Networks (WSNs) have been deeply studied by many researchers and been widely used in many fields. Since a large amount of energy for WSNs is used for sensing and transmitting, researchers come up with many methods to reduce the number of sensed and transmitted data packets…
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Low-Energy Data Collection in Wireless Sensor Networks Based on Matrix Completion
Sparse sensing schemes based on matrix completion for data collection have been proposed to reduce the power consumption of data-sensing and transmission in wireless sensor networks (WSNs). While extensive efforts have been made to improve the recovery accuracy from the sparse samples, it is…
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Extraction and Research of Crop Feature Points Based on Computer Vision
Based on computer vision technology, this paper proposes a method for identifying and locating crops in order to successfully capture crops in the process of automatic crop picking. This method innovatively combines the YOLOv3 algorithm under the DarkNet framework with the point cloud image…
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MRMAFusion: A Multi-Scale Restormer and Multi-Dimensional Attention Network for Infrared and Visible Image Fusion
Infrared and visible image fusion improves the visual representation of scenes. Current deep learning-based fusion methods typically rely on either convolution operations for local feature extraction or Transformers for global feature extraction, often neglecting the contribution of multi-scale…
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Multi-Timeslots Data Collection With Low Rank and Modified Second-Order Horizontal Total Variation for Wireless Sensor Networks
Decreasing the number of data gathered is the most highly effective way to decrease the power consumption for wireless sensor networks. Compressed Data Gathering, as it known to all, is a data collection method in wireless sensor networks, but it cannot achieve sparse sensing as all data need to be…
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Data Recovery in Wireless Sensor Networks Based on Low Rank and Short-Term Stability
The most effective way to reduce the energy consumption of energy-limited wireless sensor networks is to reduce the amount of data collected. However, this will increase the difficulty of data recovery. At the same time, most of the data collection and recovery algorithms based on matrix completion…
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The Sparsity Adaptive Reconstruction Algorithm Based on Simulated Annealing for Compressed Sensing
This paper proposes a novel sparsity adaptive simulated annealing algorithm to solve the issue of sparse recovery. This algorithm combines the advantage of the sparsity adaptive matching pursuit (SAMP) algorithm and the simulated annealing method in global searching for the recovery of the sparse…
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Multi-Sensor Data Fusion Algorithm Based on Trust Degree and Improved Genetics
Aiming at the problems of low data fusion precision and poor stability in greenhouse wireless sensor networks (WSNs), a multi-sensor data fusion algorithm based on trust degree and improved genetics is proposed. The original data collected by the sensor nodes are sent to the gateway through the…