Automatic detection of floating instream large wood in videos using deep learning by J. Aarnink, J. Aarnink, T. Beucler, T. Beucler, M. Vuaridel, V. Ruiz-Villanueva, V. Ruiz-Villanueva

“…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.…”
Get full text

Automatic Recognition of Authors Identity in Persian based on Systemic Functional Grammar by Fatemeh Soltanzadeh, Azadeh Mirzaei, Mohammad Bahrani, Shahram Modarres Khiabani

“…First, a corpus composed of documents written by seven contemporary Iranian authors was collected. Second, a list of function words was extracted from the corpus. Moreover, conjunction, modality and comment adjunct system networks were applied to form a lexicon using linguistics resources. …”
Get full text

Three-Dimensional Real-Scene-Enhanced GNSS/Intelligent Vision Surface Deformation Monitoring System by Yuanrong He, Weijie Yang, Qun Su, Qiuhua He, Hongxin Li, Shuhang Lin, Shaochang Zhu

“…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. …”
Get full text

Joint planning of energy storage site selection and line capacity expansion in distribution networks considering the volatility of new energy by Xu Feifei, Pan Xia, Chen Bowei, Li Xiaoshuang, Nie Zhi, Feng Miaoyong, Feng Miaoyong

“…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. …”
Get full text

Stimuli Selection Criteria for the Experiment “Visual Perception of Imitative Words in Native and Non-Native Language by the Method Lexical Decision” by M. A. Flaksman, Yu. V. Lavitskaya, Yu. G. Sedelkina, L. O. Tkacheva

“…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. …”
Get full text

Synthesis of Molecularly Imprinted Polymers for Selective Extraction Followed by Solid Phase Determination of Metformin in Pharmaceutical Preparation and in Human Serum by Rana A. Kamal Aldeen, Yehya K. Al-Bayati

“…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. …”
Get full text

Lightweight and Accurate YOLOv7-Based Ensembles With Knowledge Distillation for Urinary Sediment Detection by Keita Sasaki, Hiroki Nishikawa, Ittetsu Taniguchi, Takao Onoye

“…Urine sediment analysis plays an important role in evaluating kidney function. In addition to improving detection accuracy, reducing model size is also a key challenge, especially when considering deployment on medical devices where computational resources are limited. …”
Get full text

New Horizon in Selective Tocols Extraction from Deodorizer Distillates Under Mild Conditions by Using Deep Eutectic Solvents by Dian Maria Ulfa, Asep Bayu, Siti Irma Rahmawati, Peni Ahmadi, Masteria Yunovilsa Putra, Surachai Karnjanakom, Guoqing Guan, Abdul Mun’im

“…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. …”
Get full text

A spatial matrix factorization method to characterize ecological assemblages as a mixture of unobserved sources: An application to fish eDNA surveys by Letizia Lamperti, Olivier François, David Mouillot, Laëtitia Mathon, Théophile Sanchez, Camille Albouy, Loïc Pellissier, Stéphanie Manel

“…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. …”
Get full text

Surface Defect Detection for Small Samples of Particleboard Based on Improved Proximal Policy Optimization by Haifei Xia, Haiyan Zhou, Mingao Zhang, Qingyi Zhang, Chenlong Fan, Yutu Yang, Shuang Xi, Ying Liu

“…The method integrates the variable action space and the composite reward function and achieves the balanced optimization of different types of defect detection performance by adjusting the scaling and translation amplitude of the detection region. …”
Get full text

Hybrid Capsule Network for precise and interpretable detection of malaria parasites in blood smear images by Bader Alawfi

Get full text

A Susceptible Cell‐Selective Delivery (SCSD) of mRNA‐Encoded Cas13d Against Influenza Infection by Zhuanli Wu, Chengcheng Zhao, Hui Ai, Zhen Wang, Mingyue Chen, Yanli Lyu, Qi Tong, Litao Liu, Honglei Sun, Juan Pu, Ran Zhang, Xiaoxiang Hu, Jinhua Liu, Xiaowei Ma, Yipeng Sun

“…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. …”
Get full text

DP-YOLO: A Lightweight Real-Time Detection Algorithm for Rail Fastener Defects by Lihua Chen, Qi Sun, Ziyang Han, Fengwen Zhai

“…To enable accurate and efficient real-time detection of rail fastener defects under resource-constrained environments, we propose DP-YOLO, an advanced lightweight algorithm based on YOLOv5s with four key optimizations. …”
Get full text

Deep learning vulnerability detection method based on optimized inter-procedural semantics of programs by Yan LI, Weizhong QIANG, Zhen LI, Deqing ZOU, Hai JIN

“…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.…”
Get full text

MSSA: multi-stage semantic-aware neural network for binary code similarity detection by Bangrui Wan, Jianjun Zhou, Ying Wang, Feng Chen, Ying Qian

“…Binary code similarity detection (BCSD) aims to identify whether a pair of binary code snippets is similar, which is widely used for tasks such as malware analysis, patch analysis, and clone detection. …”
Get full text

A lightweight algorithm for steel surface defect detection using improved YOLOv8 by Shuangbao Ma, Xin Zhao, Li Wan, Yapeng Zhang, Hongliang Gao

“…Finally, the SIoU (Simplified IoU ) is used to replace the traditional CIoU loss function, which can make the anchor frame more fast and accurate in the regression process, to improve the stability and the robustness of detection. …”
Get full text

Network security traffic detection and legal supervision based on adaptive metric learning algorithm by Liu Zhen

Get full text

App-DDoS detection method using partial binary tree based SVM algorithm by Bin ZHANG, Zihao LIU, Shuqin DONG, Lixun LI

“…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.…”
Get full text

SurfaceVision: An Automated Module for Surface Fault Detection in 3D Printed Products by Laukesh Kumar, Manoj Kumar Satyarthi

“…The traditional method currently requires visual information processing devices or continuous monitoring of the process via a camera, which is very resource consuming and costly. Machine learning techniques being used for automatic detection of the faults suffer in real time conditions with inefficient fault detection due to the inability of adaptation to real time changes in the printing process. …”
Get full text

FsDAOD: Few-shot domain adaptation object detection for heterogeneous SAR image by Siyuan Zhao, Yong Kang, Hang Yuan, Guan Wang, Hui Wang, Shichao Xiong, Ying Luo

“…Heterogeneous Synthetic Aperture Radar (SAR) image object detection task with inconsistent joint probability distributions is occurring more and more frequently in practical applications. …”
Get full text