Detecting non-neutral modules in species co-occurrence data: principles and application to plant communities by Fabien Laroche, Bodil Ehlers

“…We tested our framework on virtual data and successfully retrieved pre-defined functional groups without generating false positive detections. …”
Get full text

LMGD: Log-Metric Combined Microservice Anomaly Detection Through Graph-Based Deep Learning by Xu Liu, Yuewen Liu, Miaomiao Wei, Peng Xu

“…Therefore, there is an urgent need for fast and accurate anomaly detection capabilities. However, the existing microservice anomaly detection methods do not pay attention to the multi-source data of the microservice system and thus have low accuracy. …”
Get full text

DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK by N Suganthi, R Meenakshi, A Sairam, M Parvathi

“…The approach integrates a Decision Tree (DT) algorithm for rapid initial classification of Primary User (PU) activity, followed by a Hill Climbing (HC) optimization algorithm that fine-tunes the detection based on a fitness function. Entropy and throughput metrics are employed as decision conditions at each sensing channel, enhancing uncertainty measurement and maintaining detection robustness under low Signal-to-Noise Ratio (SNR) conditions. …”
Get full text

Nanotechnology-based paper microfluidics for rapid point-of-care detection and differentiation of snake venom types by Lakshmi Narashimhan Ramana, Nitin Salvi, M.V. Khadilkar, Tarun Kumar Sharma

“…To address this, the current study focuses on detecting functional enzyme components of venomous snake species, such as phospholipase A2, hyaluronidase, and proteases. …”
Get full text

Evaluation of a coastal acoustic buoy for cetacean detections, bearing accuracy and exclusion zone monitoring by Kaitlin J. Palmer, Sam Tabbutt, Douglas Gillespie, Jesse Turner, Paul King, Dominic Tollit, Jessica Thompson, Jason Wood

“…Field trials indicated maximum detection ranges from 4–7.3 km depending on source and ambient noise levels. …”
Get full text

TCE-YOLOv5: Lightweight Automatic Driving Object Detection Algorithm Based on YOLOv5 by Han Wang, Zhenwei Yang, Qiaoshou Liu, Qiang Zhang, Honggang Wang

“…Finally, the EIOU loss function is introduced to measure the overlap between the predicted box and the real box more accurately and improve the detection accuracy. …”
Get full text

Evaluating machine learning-based intrusion detection systems with explainable AI: enhancing transparency and interpretability by Vincent Zibi Mohale, Ibidun Christiana Obagbuwa

“…Machine Learning (ML)-based Intrusion Detection Systems (IDS) are integral to securing modern IoT networks but often suffer from a lack of transparency, functioning as “black boxes” with opaque decision-making processes. …”
Get full text

DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection by Shaofu Lin, Yang Yang, Xiliang Liu, Li Tian

Get full text

YOLOv8n-DDSW: an efficient fish target detection network for dense underwater scenes by Jinwang Yi, Wei Han, Fangfei Lai

“…Therefore, the YOLOv8n-DDSW fish target detection algorithm was proposed in this article to resolve the detection difficulties resulting from fish occlusion, deformation and detail loss in complex intensive aquaculture scenarios. (1) The C2f-deformable convolutional network (DCN) module is proposed to take the place of the C2f module in the YOLOv8n backbone to raise the detection accuracy of irregular fish targets. (2) The dual-pooling squeeze-and-excitation (DPSE) attention mechanism is put forward and integrated into the YOLOv8n neck network to reinforce the features of the visible parts of the occluded fish target. (3) Small detection is introduced to make the network more capable of sensing small targets and improving recall. (4) Wise intersection over union (IOU) rather than the original loss function is used for improving the bounding box regression performance of the network. …”
Get full text

A Sparse Feature-Based Mixed Signal Frequencies Detecting for Unmanned Aerial Vehicle Communications by Yang Wang, Yongxin Feng, Fan Zhou, Xi Chen, Jian Wang, Peiying Zhang

“…The detection error and detection accuracy of component frequencies are less than 3.19% and greater than 90.7%, respectively.…”
Get full text

Invasive lobular carcinoma of the breast detected with real-time virtual sonography: a case report by Yukie Ito, Kimihito Fujii, Masayuki Saito, Hirona Banno, Mirai Ido, Manami Goto, Takahito Ando, Yukako Mouri, Junko Kousaka, Tsuneo Imai, Shogo Nakano

“…Biopsy of the primary lesion, which was initially only detected with MRI, was successfully performed with clear visualization during RVS, which is based on the fusion of MRI and US images. …”
Get full text

STIED: a deep learning model for the spatiotemporal detection of focal interictal epileptiform discharges with MEG by Raquel Fernández-Martín, Alfonso Gijón, Odile Feys, Elodie Juvené, Alec Aeby, Charline Urbain, Xavier De Tiège, Vincent Wens

Get full text

Subtypes detection of papillary thyroid cancer from methylation assay via Deep Neural Network by Andrea Colacino, Andrea Soricelli, Michele Ceccarelli, Ornella Affinito, Monica Franzese

Get full text

Deception mechanisms of FDA‒AWACS against passive monopulse angle measurements by Bo Wang, Gang Wang, Yonglin Li, Rennong Yang, Yu Zhao

Get full text

Multimodal imaging analysis and structure-function correlation in patients exposed to pentosan polysulfate sodium by Sandra Hoyek, Eleni Konstantinou, Francesco Romano, Darren Chen, Celine Chaaya, Magdalena G. Krzystolik, Daniel Hu, Rachel Huckfeldt, Demetrios G. Vavvas, Leo A. Kim, Jason Lee, Elise De, John B. Miller, Nimesh A. Patel

“…Purpose: To study the anatomic and functional retinal changes in patients exposed to pentosan polysulfate (PPS) using multimodal imaging and mesopic microperimetry. …”
Get full text

Source Process Estimation for the 2024 Mw 7.1 Hyuganada, Japan, Earthquake and Forward Modeling Using N‐net Ocean Bottom Seismometer Data by R. Shibata, H. Kubo, W. Suzuki, S. Aoi, H. Sekiguchi

“…The N‐net seafloor seismograms of the mainshock with a frequency of ∼0.05 Hz recorded east of the source area were reproduced for several stations using the empirical Green's function approach based on the estimated source process data.…”
Get full text

STATISTICAL DATA AND ANALYSIS OF LITERATURE SOURCES ON PATHOPHYSIOLOGICAL MECHANISMS OF THE CROSSTALK BETWEEN ACUTE KIDNEY AND LIVER INJURY IN PRETERM NEWBORNS DURING THE EARLY NEO... by О. Оболонська, Л. Вакуленко

Get full text

Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction by P. Kumudha, R. Venkatesan

“…Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. …”
Get full text

Trends in the development of the ISO 9001 quality management system – a parameter of the logistic function by Grzegorz Kazimierz Rządkowski, Katarzyna Szczepańska

“…Results Studies and calculations have fully confirmed that the number of ISO 9001 certificates between 1993 and 2022 can be effectively modelled using an appropriate multilogistics function. Using scalograms and CWT analysis, the type and position of successive logistic waves can be identified and their parameters can be estimated. …”
Get full text

Primary study on the expression pattern and function of zinc metalloproteinase NAS-31 in Haemonchus contortus by HUANG Yan, ZHANG Hui, TONG Danni, ZHOU Jingru, WU Fei, CHEN Xueqiu, YANG Yi, MA Guangxu, DU Aifang

“…In order to study the function of zinc metalloproteinase NAS-31 gene (Hc-nas-31) in the free-living period (especially L3) of this kind of worm, real-time quantitative polymerase chain reaction (qRT-PCR) was conducted to detect the transcription level of the target gene in different developmental stages of H. contortus. …”
Get full text