Research on dust identification and concentration detection method based on machine vision by Luyang TU, Qinghua CHEN, Yingsong CHENG, Bingyou JIANG

“…Firstly, a set of simulation experiment platform for collecting and making dust data set is built, and the dust position information data set and dust concentration data set are made respectively. …”
Get full text

Machine Learning-Based Grasshopper Species Classification using Neutrosophic Completed Local Binary Pattern by Mustafa İlçin, Nuh Alpaslan

Get full text

Analysis of plant metabolomics data using identification‐free approaches by Xinyu Yuan, Nathaniel S. S. Smith, Gaurav D. Moghe

“…Additionally, we explore their practical applications in plant science and highlight a set of useful tools to support researchers in analyzing complex plant metabolomics data. …”
Get full text

Smart home environment data across 4 European countrieszenodo by Stefan Winterberger, Dmitriy An, Martin Biallas, Andrew Paice

“…The strength of the dataset lies in the variety of sensors including sound pressure and the long period (nearly 1 year) of high frequency measurements in different countries.Collecting data in real-world residential settings is challenging, but by making this dataset publicly available, we provide researchers with a valuable resource to explore smart home applications, presence detection, and environmental monitoring in everyday life.…”
Get full text

Improved YOLOv8-Based Algorithm for Citrus Leaf Disease Detection by Zhengbing Zheng, Yibang Zhang, Luchao Sun

“…In order to maintain the randomness of the experimental data, this experiment divided the data set into training set, validation set and test set with a ratio of 7:2:1, which contained 1267 images, 362 images and 181 images respectively. …”
Get full text

Recognition of Human Activities Based on Ambient Audio and Vibration Data by Marcel Koch, Thomas Pfitzinger, Fabian Schlenke, Fabian Kohlmorgen, Roland Groll, Hendrik Wohrle

“…This paper presents a distributed multisensor system for the recognition of human activities based on ambient audio and vibration data. The system comprises multiple ambient multisensor nodes (AMSNs) situated within a smart home setting, in conjunction with a data transfer and analysis subsystem. …”
Get full text

Reversible data hiding scheme based on enhanced image smoothness by Jinghan WANG, Hui ZHU, Helin LI, Hui LI, Xiaopeng YANG

“…With the prosperity of Internet technology and the popularity of social networks, reversible data hiding technology has been widely adopted in concealed information transmission of medical and military fields with its advantages on secret information recovery.Traditional reversible data hiding schemes mainly focus on the enhancement of embedding capacity and the reduction of the distortion rate of stego image, but pay less attention to the understanding of image details with the human eyes.Thus, it is difficult to resist hidden information detection methods.To solve the above challenge, a reversible data hiding algorithm was proposed, which ensured the visual quality of the stego image in the process of data hiding through the image visual smoothness enhancement.Specifically, the original image was divided into reference area and non-reference area.The secret data was embedded through the translation of the difference, which was calculated according to the predicted pixel value and the original pixel value of the non-reference area.To guarantee the visual quality of the image, smoothing mechanism was constructed, in which a Gaussian filter was utilized as a template to filter the predicted value and to add the filter difference into the cover image without loss.The pixel value of the reference region was used as edge information for lossless restoration of the original image.The filtering coefficient in Gaussian function was exploited as the embedded key to ensure the security of secret information.Simulation results regarding a large number of classical image data sets illustrated that the visual smoothness of stego image processed by this scheme was effectively enhanced with lower distortion rate, higher embedding rate, and higher embedding and extraction efficiency.In a typical circumstance, the similarity between the generated stego image and the Gaussian filter image can reach 0.9963.The PSNR and the embedded capacity can be up to 37.346 and 0.3289 BPP, respectively.…”
Get full text

ROASMI: accelerating small molecule identification by repurposing retention data by Fang-Yuan Sun, Ying-Hao Yin, Hui-Jun Liu, Lu-Na Shen, Xiu-Lin Kang, Gui-Zhong Xin, Li-Fang Liu, Jia-Yi Zheng

“…The application of ROASMI to four real-world datasets demonstrates its advantages in distinguishing coexisting isomers with similar fragmentation patterns and in annotating detection peaks without informative spectra. ROASMI is flexible enough to be retrained with user-defined reference sets and is compatible with other MS/MS scorers, making further improvements in small-molecule identification. …”
Get full text

SPINEX-anomaly: similarity-based predictions with explainable neighbors exploration for anomaly and outlier detection by M. Z. Naser, Ahmad Z. Naser

Get full text

Depression Recognition Using Daily Wearable-Derived Physiological Data by Xinyu Shui, Hao Xu, Shuping Tan, Dan Zhang

“…Our results demonstrate the feasibility of using daily wearable-derived physiological data for depression recognition. The achieved classification accuracies suggest that this approach could be integrated into clinical settings for the early detection and monitoring of depressive symptoms. …”
Get full text

Detection of cardiac amyloidosis using machine learning on routine echocardiographic measurements by I-Min Chiu, David Ouyang, James Zou, Rachel Si-Wen Chang, Phillip Tacon, Michael Abiragi, Louie Cao, Gloria Hong, Jonathan Le, Chathuri Daluwatte, Piero Ricchiuto

“…Data was split by patient into a training data set of 2882 studies from 486 patients and a test data set of 721 studies from 150 patients. …”
Get full text

Compositional epistasis detection using a few prototype disease models. by Lu Cheng, Mu Zhu

“…We study computational approaches for detecting SNP-SNP interactions that are characterized by a set of "two-locus, two-allele, two-phenotype and complete-penetrance" disease models. …”
Get full text

Angus: efficient active learning strategies for provenance based intrusion detection by Lin Wu, Yulai Xie, Jin Li, Dan Feng, Jinyuan Liang, Yafeng Wu

“…Abstract As modern attack methods become more concealed and complex, obtaining many labeled samples in big data streams is difficult. Active learning has long been used to achieve better intrusion detection performance by using only a small number of training samples. …”
Get full text

Solar flares detected by the new narrowband VLF receiver at SANAE IV by Hanna Dahlgren, Torbjörn Sundberg, Andrew Collier, Etienne Koen, Stephen Meyer

Get full text

Offline Detection of Violations in Chinese E-Commerce Live Streaming Content by Xiaohan Liu, Chenyu Liu, Ran Bai, Liu Yuan, Yanquan Zhou, Minjiang Huang, Jipeng Qiang

“…Experimental results show that our two-stage approach achieves superior performance, and that LLM-generated data further boosts the robustness and effectiveness of the violation detection system in offline settings.…”
Get full text

Object Detection Algorithm Based on Feature Enhancement and Anchor-object Matching by LI Cheng-yan, ZHAO Shuai, CHE Zi-xuan

“…The mAP of the A-SSD algorithm on the PASCAL VOC data set reached 80.7, and the missed detection rate of the A-SSD algorithm on the workshop pedestrian data set was 3.5%, and the accuracy rate was 91.5%.…”
Get full text

Malicious code within model detection method based on model similarity by Degang WANG, Yi SUN, Chuanxin ZHOU, Qi GAO, Fan YANG

“…The privacy of user data in federated learning is mainly protected by exchanging model parameters instead of source data.However, federated learning still encounters many security challenges.Extensive research has been conducted to enhance model privacy and detect malicious model attacks.Nevertheless, the issue of risk-spreading through malicious code propagation during the frequent exchange of model data in the federated learning process has received limited attention.To address this issue, a method for detecting malicious code within models, based on model similarity, was proposed.By analyzing the iterative process of local and global models in federated learning, a model distance calculation method was introduced to quantify the similarity between models.Subsequently, the presence of a model carrying malicious code is detected based on the similarity between client models.Experimental results demonstrate the effectiveness of the proposed detection method.For a 178MB model containing 0.375MB embedded malicious code in a training set that is independent and identically distributed, the detection method achieves a true rate of 82.9% and a false positive rate of 1.8%.With 0.75MB of malicious code embedded in the model, the detection method achieves a true rate of 96.6% and a false positive rate of 0.38%.In the case of a non-independent and non-identically distributed training set, the accuracy of the detection method improves as the rate of malicious code embedding and the number of federated learning training rounds increase.Even when the malicious code is encrypted, the accuracy of the proposed detection method still achieves over 90%.In a multi-attacker scenario, the detection method maintains an accuracy of approximately 90% regardless of whether the number of attackers is known or unknown.…”
Get full text

Workshop Staff Detection Method Based on Spatial Domain Attention Mechanism by LI Cheng-yan, MA Jin-tao, ZHAO Shuai

“…It is verified on the test set and VOC data set in this paper, and the results show that the positioning effect and detection rate are better.…”
Get full text

“Evaluation of hepatobiliary disorders using magnetic resonance cholangiopancreatography in a low-resource setting in Kano, Nigeria: a retrospective study” by Nuraddeen Mukhtar Rabiu, Abbas Rabiu Muhammad, Ahmad Bashir Umar, Sambo-Donga Donzomga, Ibrahim Umar Garzali, Suwaid Mohammed Abba, Anas Ismail

Get full text

CHANGES IN PHYSICAL AND CHEMICAL PROPERTIES OF ORAL FLUID IN PATIENTS WITH PERIODONTAL DISEASES IN THE SETTINGS OF CHRONIC HEPATITIS C DURING ANTIVIRAL THERAPY by H.A. Sichkoriz, L.Yu. Minko

“…Introduction. Published data indicate a significant increase in the prevalence of HCV-infection and high incidence of periodontal lesions in the settings of infection with hepatitis C. …”
Get full text