Deep learning-based time series prediction in multispectral and hyperspectral imaging for cancer detection by Lijun Hao, Changmin Wang, Jinshan Che, Mingming Sun, Yuhong Wang

“…Traditional approaches for cancer detection rely on handcrafted features and conventional machine learning algorithms, which struggle with high-dimensional spectral data, noise interference, and domain adaptation challenges. …”
Get full text

An improved YOLOv5s-based method for detecting rice leaves in the field by Cheng Zhou, Caohang Zhou, Lili Yao, Yagang Du, Xin Fang, Zhangbin Chen, Chengliang Yin

“…Second, we introduced a coordinate attention mechanism (CA) to strengthen focus on leaf tip features under weed interference and leaf occlusion conditions. …”
Get full text

Stable descriptors in image recognition tasks by V. B. Melekhin, V. M. Khachumov

“…In general, the proposed approach allows developing an effective image recognition system in the presence of various types of interference on the recognized images.…”
Get full text

Prediction of Bus Arrival Time Based on Gated Recurrent Unit Neural Networks by LU Juntian;SUN Ling;SHI Quan

“…Furthermore, combining more than 50 million pieces of raw data, the model uses Spark elastic distributed data set in distributed Hadoop cluster to clean data and site matching algorithm to match source data, Lasso algorithm to optimize feature options and remove interference. The simulation results reveal that the R-square fitting degree of the improved GRU model is 94.547% and the prediction efficiency is nearly 14% higher than that of traditional long short-term(LSTM) model. …”
Get full text

Arcing detection method of metro pantograph based on improved yolov4-tiny by AI Shengyong, DING Jianming, ZHANG Qingsong

“…For the problem of strong light interference and variable background in pantograph arcing detection for metro vehicles, an arcing detection method based on an improved yolov4-tiny model is proposed. …”
Get full text

A Stochastic Learning Algorithm for Machine Fault Diagnosis by Zhipeng Dong, Yucheng Liu, Jianshe Kang, Shaohui Zhang

“…The proposed method consists of three steps: firstly, to increase the computational efficiency of the model, the dimension of the high-dimensional data is reduced by establishing a random matrix; secondly, for enhancing the clustering influence of the sample, the input data are enhanced by feature processing; thirdly, to make the clustering effects more pronounced, the noise and interference of the data need to be processed, and the singularity value denoising method is used to denoise training data and test data. …”
Get full text

Wheel Tread Dynamic Detection Benchmark Positioning Method Based on Iterative Reweighted Least-squares Line Fitting by LI Miaocheng, WANG Junping, SHEN Yunbo, YOU Yong, DAI Bowang, LAN Qiangqiang

“…After extracting the point cloud data through structured light calibration, center-line extraction and other algorithms, reference feature points of the inner side are segmented combined with tread features, and an iterative re-weighted least squares line fitting (IRLS-LF) method is used to realize robust positioning of the inner side benchmark. …”
Get full text

Design of Automatic Scoring System for Oral English Test Based on Sequence Matching and Big Data Analysis by Ping Li, Hua Zhang, Sang-Bing Tsai

“…Aiming at the reliability of the automatic scoring system, based on the principle of sequence matching, this paper adopts the spoken speech feature extraction method to extract the features of spoken English test pronunciation and establishes a dynamic optimized spoken English pronunciation signal model based on sequence matching, which could maintain good dynamic selection and clustering ability in a strong interference environment. …”
Get full text

Application of Improved LSTM Model in Runoff Simulation in Arid Region of Northwest China: A Case Study of the Zuli River by SONG Haiping, TANG Yiran, DANG Wentao, WANG Yibo

“…In view of the scarcity of measured data in the Zuli River Basin, the upper reaches of the Yellow River, as well as the difficult hydrological simulation problems caused by the intense interference of human activities, this study focused on the Zuli River Basin in the upper reaches of the Yellow River. …”
Get full text

SE-WiGR: A WiFi Gesture Recognition Approach Incorporating the Squeeze–Excitation Mechanism and VGG16 by Fenfang Li, Chujie Weng, Yongguang Liang

“…This improvement confirms that the SE module effectively enhances gesture feature extraction while suppressing background noise.…”
Get full text

Generative adversarial nets in laser-induced fluorescence spectrum image recognition of mine water inrush by Jing Li, Yong Yang, Hongmei Ge, Yong Wang, Li Zhao

“…The fluorescence spectrum from the water sample is stimulated by 405-nm lasers and improved by recursive mean filtering method to alleviate interference and auto-correlation to enhance the feature difference. …”
Get full text

Time synchronization attack detection for industrial wireless network by Sichao ZHANG, Wei LIANG, Xudong YUAN, Yinlong ZHANG, Meng ZHENG

“…High-precision time synchronization is the basis for ensuring the secure and reliable transmission of industrial wireless network (IWN).Delay attacks, as a class of time synchronization attacks which cannot be solved by cryptographic techniques, seriously threaten the secure operation of IWN.Firstly, based on the in-depth analysis on the time synchronization mechanisms of IWN, three-time synchronization attack models were proposed, including the one-way full life cycle delay attack, two-way full life cycle delay attack, and one-way non-full-life cycle delay attack.Stealthier delay attacks could be realized by the attack models under the premise that target nodes were not captured.Secondly, considering the problem that existing detection algorithms are difficult to detect stealthier delay attacks without obvious changes in time features, an attack detection algorithm based on a Bayesian model was proposed that extracts four representative features, including transmission rate, transmission delay, transmission success rate and time synchronization interval.In addition, in order to ensure the accuracy of the attack detection and classification in the presence of noise interference, the noise model of wireless channel was introduced to the Bayesian feature information matrix.Experimental results show that the proposed algorithm can effectively detect three kinds of attacks in the presence of noise.…”
Get full text

Research on the Application of Variational Mode Decomposition Optimized by Snake Optimization Algorithm in Rolling Bearing Fault Diagnosis by Houxin Ji, Ke Huang, Chaoquan Mo

“…However, the fault signal of rolling bearing is susceptible to noise interference, which makes it difficult to extract the fault characteristics of the rolling bearing and thus affects the accuracy of the diagnosis results. …”
Get full text

VARIOUS HISTORICAL CONNOTATIONS OF THE CONCEPT OF SOVEREIGNTY by Emilian CIONGARU

“…Sovereignty as a feature of state power, shall be expressed in terms of organizing and exercising, determining and resolving internal and external problems, freely and according to its will, without any interference, respecting the sovereignty of other states, as well as European and international law norms. …”
Get full text

Research on deception jamming of chaotic composite short-range detection system based on bispectral analysis and genetic algorithm–back propagation by Dongxu Wei, Shuning Zhang, Si Chen, Huichang Zhao, Linzhi Zhu

“…In order to analyze and extract the different characteristics between deceptive jamming and target echo signal, so as to realize the anti-deceptive jamming of chaotic compound short-range detection system, this article analyzes and simulates the mathematical model of deceptive jamming and target echo, and analyzes the bispectral characteristics of the simulated echo and jamming signal, and a set of anti-deception jamming feature parameters has been constructed. The identification of deceptive interference is realized by genetic algorithm–back propagation neural network, and the recognition accuracy is high and the real-time performance is good.…”
Get full text

Enhanced object detection in low-visibility haze conditions with YOLOv9s. by Yang Zhang, Bin Zhou, Xue Zhao, Xiaomeng Song

“…Specifically, the framework incorporates Patchwise Contrastive Learning to fortify the correlation among positive samples within image patches, effectively reducing negative sample interference and enhancing the model's capability to discern subtle local features of haze-impacted images. …”
Get full text

Survey on Context-Aware Radio Frequency-Based Sensing by Eugene Casmin, Rodolfo Oliveira

“…Challenges like environmental interference, scalability, and regulatory constraints are addressed, with insights into real-world mitigation strategies. …”
Get full text

A Method of Abnormal Behavior Detection for Safety Site Surveillance by Wenjing Wang, Yangyang Zhang, QingE Wu

“…For the complex background in the image, a multiframe differential superposition algorithm is proposed to denoise the target image; a feature extraction method is given to extract features for the target image, and then a more complete image with target features is obtained after filtering; a normal behavior model is established to extract the motion information of the target from a single frame of the image; an abnormal detection method is proposed to determine whether it belongs to abnormal behavior. …”
Get full text

Phrasal Verbs in Learner English: A Corpus-based Study of Lithuanian and Polish Learners of English by Božena Garbatovič, Jonė Grigaliūnienė

“…Furthermore, it is noticed that learners face similar stylistic, semantic and syntactic difficulties in the use of this language feature. In particular, the analysis shows that such errors might be caused by native language interference, as well as the inherent complexity of phrasal verbs. …”
Get full text

Robust Model Predictive Control for AFE-Inverter Drives With Common Mode Voltage Elimination by S.M. Muslem Uddin, Galina Mirzaeva, Graham C. Goodwin

“…This paper proposes a novel and robust version of Model Predictive Control scheme for AC drives based on Voltage Source Inverter (VSI) with Active Front End (AFE). The main feature of the proposed MPC is elimination of Common Mode Voltage (CMV) without imposing a penalty on the corresponding term in the cost function, but rather by a smart utilisation of the restricted set of switching states in a computationally efficient algorithm. …”
Get full text