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Suggested Topics within your search.
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361
Circular Animal Protein Hydrolysates: A Comparative Approach of Functional Properties
Published 2025-06-01“…Conversely, SHARK and FISH supported opportunistic bacteria growth, suggesting a potential use as nitrogen sources in microbial media. These findings highlight the nutritional and functional versatility of animal-derived protein hydrolysates and support their integration into sustainable feed strategies within a circular bioeconomy.…”
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362
Review of Fault Detection and Diagnosis Methods in Power Plants: Algorithms, Architectures, and Trends
Published 2025-06-01“…Key findings are summarized in a comparative matrix, highlighting trends, gaps, and inconsistencies across publication sources. This review identifies critical research gaps—including the underuse of hybrid models, lack of benchmark datasets, and limited integration between detection and control layers—and offers concrete recommendations for future research. …”
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363
Multi-Person Fall Detection Using Data Assimilation Method With Kalman Filter
Published 2025-01-01“…Fall detection is an essential technology for ensuring the safety of elderly individuals, as falling accidents are critical and can cause significant functional damage in old age. …”
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364
Detection of Elementary White Mucosal Lesions by an AI System: A Pilot Study
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365
Automatic detection of floating instream large wood in videos using deep learning
Published 2025-02-01“…Therefore, the findings of this paper could be used when designing a custom wood detection network. With the growing availability of flood-related videos featuring wood uploaded to the internet, this methodology facilitates the quantification of wood transport across a wide variety of data sources.…”
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366
Three-Dimensional Real-Scene-Enhanced GNSS/Intelligent Vision Surface Deformation Monitoring System
Published 2025-04-01“…The system integrates GNSS monitoring terminals and multi-source meteorological sensors to accurately capture minute displacements at monitoring points and multi-source Internet of Things (IoT) data, which are then automatically stored in MySQL databases. …”
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367
Joint planning of energy storage site selection and line capacity expansion in distribution networks considering the volatility of new energy
Published 2024-11-01“…This technology uses CHk-means clustering calculations based on actual large-scale operation data of new energy sources to generate typical operating curves. Then, it finely constructs an objective function considering power transmission in the transmission-distribution network, abandonment of new energy, line limits, and energy storage construction. …”
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368
Stimuli Selection Criteria for the Experiment “Visual Perception of Imitative Words in Native and Non-Native Language by the Method Lexical Decision”
Published 2020-11-01“…The authors also use psycho-semantic methods such as the method of lexical decision. The main sources of stimuli selection are The Russia Etymological Dictionary by M. …”
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369
Synthesis of Molecularly Imprinted Polymers for Selective Extraction Followed by Solid Phase Determination of Metformin in Pharmaceutical Preparation and in Human Serum
Published 2024-05-01“…A solid-phase extraction (SPE) syringe packed with molecular imprinted polymers (MIPs) was employed to selectively separate and pre-concentrate the Metformin in multiple pharmaceutical drugs from several sources. …”
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370
New Horizon in Selective Tocols Extraction from Deodorizer Distillates Under Mild Conditions by Using Deep Eutectic Solvents
Published 2025-03-01“…The basic principles of intermolecular interactions (H-bond, van der Walls bond, and misfit interaction) between DESs or their components with tocols are discussed to understand the mechanism by which DESs selectively extract tocols from the mixture. This is mainly observed to be a function of the intrinsic properties of DESs and/or tocols, which could be beneficial for tuning the appropriate DESs for extracting tocols selectively and effectively under mild operation conditions. …”
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371
Failure Law of Sandstone and Identification of Premonitory Deterioration Information Based on Digital Image Correlation–Acoustic Emission Multi-Source Information Fusion
Published 2025-02-01“…Additionally, by introducing the derivative functions of the multi-source information function for quantitative analysis, a comprehensive evaluation method was proposed based on the multi-source information fusion monitoring to forewarn red sandstone failure by levels during loading. …”
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372
A spatial matrix factorization method to characterize ecological assemblages as a mixture of unobserved sources: An application to fish eDNA surveys
Published 2024-12-01“…Abstract Understanding how ecological assemblages vary in space and time is essential for advancing our knowledge of biodiversity dynamics and ecosystem functioning. Metabarcoding of environmental DNA (eDNA) is an efficient method for documenting biodiversity changes in both marine and terrestrial ecosystems. …”
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373
A Susceptible Cell‐Selective Delivery (SCSD) of mRNA‐Encoded Cas13d Against Influenza Infection
Published 2025-03-01“…Given that the virus targets cells with specific receptors but is not limited to a single organ, a Susceptible Cell Selective Delivery (SCSD) system is developed by modifying a lipid nanoparticle with a peptide mimicking the function of the hemagglutinin of influenza virus to target sialic acid receptors. …”
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374
Detecting and routing of dust event using remote sensing and numerical modeling in Isfahan Province
Published 2020-03-01“…In addition, numerical weather models alone are not capable of storm detection, which requires the use of dust detection methods based on data remote sensing. …”
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375
Deep learning vulnerability detection method based on optimized inter-procedural semantics of programs
Published 2023-12-01“…In recent years, software vulnerabilities have been causing a multitude of security incidents, and the early discovery and patching of vulnerabilities can effectively reduce losses.Traditional rule-based vulnerability detection methods, relying upon rules defined by experts, suffer from a high false negative rate.Deep learning-based methods have the capability to automatically learn potential features of vulnerable programs.However, as software complexity increases, the precision of these methods decreases.On one hand, current methods mostly operate at the function level, thus unable to handle inter-procedural vulnerability samples.On the other hand, models such as BGRU and BLSTM exhibit performance degradation when confronted with long input sequences, and are not adept at capturing long-term dependencies in program statements.To address the aforementioned issues, the existing program slicing method has been optimized, enabling a comprehensive contextual analysis of vulnerabilities triggered across functions through the combination of intra-procedural and inter-procedural slicing.This facilitated the capture of the complete causal relationship of vulnerability triggers.Furthermore, a vulnerability detection task was conducted using a Transformer neural network architecture equipped with a multi-head attention mechanism.This architecture collectively focused on information from different representation subspaces, allowing for the extraction of deep features from nodes.Unlike recurrent neural networks, this approach resolved the issue of information decay and effectively learned the syntax and semantic information of the source program.Experimental results demonstrate that this method achieves an F1 score of 73.4% on a real software dataset.Compared to the comparative methods, it shows an improvement of 13.6% to 40.8%.Furthermore, it successfully detects several vulnerabilities in open-source software, confirming its effectiveness and applicability.…”
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376
Network security traffic detection and legal supervision based on adaptive metric learning algorithm
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377
App-DDoS detection method using partial binary tree based SVM algorithm
Published 2018-03-01“…As it ignored the detection of ramp-up and pulsing type of application layer DDoS (App-DDoS) attacks in existing flow-based App-DDoS detection methods,an effective detection method for multi-type App-DDoS was proposed.Firstly,in order to fast count the number of HTTP GET for users and further support the calculation of feature parameters applied in detection method,the indexes of source IP address in multiple time windows were constructed by the approach of Hash function.Then the feature parameters by combining SVM classifiers with the structure of partial binary tree were trained hierarchically,and the App-DDoS detection method was proposed with the idea of traversing binary tree and feedback learning to distinguish non-burst normal flow,burst normal flow and multi-type App-DDoS flows.The experimental results show that compared with the conventional SVM-based and naïve-Bayes-based detection methods,the proposed method has more excellent detection performance and can distinguish specific App-DDoS types through subdividing attack types and training detection model layer by layer.…”
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378
FsDAOD: Few-shot domain adaptation object detection for heterogeneous SAR image
Published 2025-06-01“…Heterogeneous Synthetic Aperture Radar (SAR) image object detection task with inconsistent joint probability distributions is occurring more and more frequently in practical applications. …”
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Characteristics of soil microbial phospholipid fatty acids in artificial, black-soil mountain degraded, and natural grasslands in the source region of the Three Rivers
Published 2025-08-01“…Background The source region of the Three Rivers is a concentrated distribution area of alpine grassland. …”
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