Keywords, morpheme parsing and syntactic trees: features for text complexity assessment by Dmitry A. Morozov, Ivan A. Smal, Timur A. Garipov, Anna V. Glazkova

“…In most situations, morphemic characteristics turned out to be more effective than previously described methods for assessing the lexical complexity of a text: the frequency of words and the occurrence of word-formation patterns. …”
Get full text

Rail Corrugation Detection of High-Speed Railway Using Wheel Dynamic Responses by Jianbo Li, Hongmei Shi

“…Detection of rail corrugation wavelength and depth is absolutely essential for maintenance and safety. A novel method using wheel vibration acceleration is proposed in this paper, in which ensemble empirical mode decomposition (EEMD) is employed to estimate the wavelength, and bispectrum features are extracted to recognize the depth with support vector machine (SVM). …”
Get full text

Integrating structured and unstructured data for livestock price forecasting: a sustainability study from South Korea by Yifan Zhu, Yifan Zhu, Yifan Zhu, Tserenpurev Chuluunsaikhan, Jong-Hyeok Choi, Aziz Nasridinov

“…In terms of price prediction, the proposed AM-LSTM model outperformed traditional statistical methods, as well as machine learning and deep learning baselines, achieving improvements in MAE ranging from 43.0 to 87.4%. …”
Get full text

Exoskeleton-guided passive movement elicits standardized EEG patterns for generalizable BCIs in stroke rehabilitation by Xinyi Zhang, Lanfang Xie, Wanting Liu, Shaoying Liang, Liyao Huang, Mingjun Wang, Lingling Tian, Li Zhang, Zhen Liang, Hai Li, Gan Huang

“…Time and time-frequency domain analyses were performed to examine the event-related potential (ERP), event-related desynchronization (ERD), and synchronization (ERS) patterns. …”
Get full text

Discovery of Characteristic Patterns from Transactions with Their Classes by Shigeaki Sakurai

“…Also, this paper verifies the effect of the method through numerical experiments based on the data registered in the UCI machine learning repository and the RFID (radio frequency identification) data collected from two apparel shops.…”
Get full text

MOIRA-UNIMORE Bearing Data Set for Independent Cart Systems by Abdul Jabbar, Marco Cocconcelli, Gianluca D’Elia, Davide Borghi, Luca Capelli, Jacopo Cavalaglio Camargo Molano, Matteo Strozzi, Riccardo Rubini

Get full text

Vowel classification with combining pitch detection and one‐dimensional convolutional neural network based classifier for gender identification by Chia‐Hung Lin, Hsiang‐Yueh Lai, Ping‐Tzan Huang, Pi‐Yun Chen, Chien‐Ming Li

“…The Yet Another Algorithm for Pitch Tracking (YAAPT)‐based PD method was designed to extract the voice fundamental frequency (F0) from non‐stationary speaker's voice signals, allowing us to achieve gender identification, by distinguishing differences in F0 between adult females and males, and classify voices into adult and children groups. …”
Get full text

Utilizing deep learning for intelligent monitoring and early warning of slope disasters in public space design by Wang Ting, Ying Wang

“…Although machine learning models like decision trees and support vector machines have improved predictions using historical data, their scalability and adaptability remain constrained due to the need for intensive feature engineering and their limited ability to model complex nonlinear dynamics.MethodsThis study introduces a novel framework utilizing Deep Learning techniques to enable intelligent, real-time monitoring and early warning of slope disasters. …”
Get full text

Steganography in IoT: A Comprehensive Survey on Approaches, Challenges, and Future Directions by Maha Driss, Lamia Berriche, Safa Ben Atitallah, Siwar Rekik

“…This study bridges this gap by providing a comprehensive review of steganographic methods for IoT, exploring approaches across many domains such as spatial, frequency, and hybrid methods used in images, videos, audio, text, network traffic, hybrid approaches, and quantum-based methods. …”
Get full text

Impact of occupancy behavior on building energy efficiency: What’s next in detection and monitoring technologies? by Wenjie Song, John Calautit

“…Particular attention is paid to data-driven methods, including probabilistic models such as Hidden Markov Models (HMMs), classical machine learning algorithms such as Support Vector Machines (SVMs) and K-Nearest Neighbors (KNN), and deep learning architectures such as Convolutional Neural Networks (CNNs), all of which have demonstrated high accuracy in both laboratory and real-world settings. …”
Get full text

Improvement of the dynamic properties of a column with step-variable flexural stiffness in terms of structural mounting damping and internal damping by Jurczyńska Anna

“…The problem was formulated on the basis of the Bernoulli-Euler’s theory and then solved using the variational method (Hamilton’s principle). Determination of differential equations o motion of individual segments of the column and their solutions, taking into account the boundary conditions, made it possible to determine the transcendental equation giving the vibration frequency values. …”
Get full text

Motor Bearing Failure Identification Using Multiple Long Short-Term Memory Training Strategies by Youcef ATMANI, Ammar Mesloub, Said Rechak

“…In the context of condition-based maintenance of rotating machines in manufacturing systems, the early diagnosis of possible faults related to rolling elements of the bearing is mainly based on techniques from artificial intelligence, namely, Machine Learning (ML) and Deep Learning (DL). …”
Get full text

Proactive Detection and Mitigation Strategies for Advanced Persistent Threats by Raghav MITTAL, Ivan CVITIĆ, Dragan PERAKOVIĆ, Soosaimarian Peter RAJA

“…The focus of this paper is on addressing the rising frequency and complexity of APT attacks, aiming to provide a detailed analysis of their evolving tactics and the need for proactive security measures. …”
Get full text

Music genre classification with parallel convolutional neural networks and capuchin search algorithm by Yuxin Zhang, Teng Li

“…The method makes use of discrete wavelet transform (DWT), mel frequency cepstral coefficients (MFCC), and short-time fourier transform (STFT) characteristics to provide a comprehensive framework for expressing stylistic qualities in music. …”
Get full text

Age Estimation Based on Children’s Voice: A Fuzzy-Based Decision Fusion Strategy by Seyed Mostafa Mirhassani, Alireza Zourmand, Hua-Nong Ting

“…Second, different vowel classes contain complementary information for age estimation. Mel-frequency cepstral coefficients are computed for each group and single layer feed-forward neural networks based on self-adaptive extreme learning machine are applied to the features to make a primary decision. …”
Get full text

Emerging Trends in AI-Based Soil Contamination Monitoring and Prevention by Cosmina-Mihaela Rosca, Adrian Stancu

“…The first study examines the distribution of articles over the years to assess researchers’ interest in soil health, and subsequently, the same analysis is conducted regarding artificial intelligence (AI) methods. Additionally, the productivity of authors, the distribution of articles by country, relevant publications, and the frequency of keywords are analyzed to identify areas of interest associated with soil health. …”
Get full text

Application of Minimum Entropy Deconvolution in the Rolling Element Bearing Fault Diagnosis by Leng Junfa, Yang Xin, Jing Shuangxi

“…When rolling element bearing occurred incipient fault,its vibration signal from bearing seat is usually very weak,and the hidden impulse components may be masked by machine noise or background noise,making it difficult to extract the fault features by frequency spectrum or envelope spectrum analysis. …”
Get full text

基于改进阈值小波和支持向量机的低速重载滚动轴承故障诊断的研究 by 雷加鹏, 潘紫微, 戚晓利, 王俊洪, 黄苹

“…A method combining wavelet analysis and support vector machine which used in low-speed bearing fault diagnosis is presented.Firstly,every kind of bearing faults sample signal are collected from the experimental equipment and these signals are denoised by improved wavelet threshold.Then wavelet packet is used to decompose the denoised vibration signals,so the frequency band energy can be obtained and can be seen as eigenvector.Then the eigenvector can be taken as training sample of SVM multi-fault classifier for the intelligent trouble diagnosis.The result shows that there is a better efficiency by this combining method compared to traditional wavelet method.…”
Get full text

Algorithm for Identification Electromagnetic Parameters of an Induction Motor When Running on a Three-Phase Power Plant by D. S. Odnolko

“…Results of simulation demonstrated how effective of the proposed method of identification. The flexible structure of the algorithm allows it to be used for preliminary identification of an induction motor, and in the process operative work induction motor in the frequency-controlled electric drive with vector control.…”
Get full text

Effect of Stiffness of Bearings and Gearbox Housing on the Dynamic characteristic of Drive System by Xu Liang, Shi Chunbao, Long Wei

“…The dynamic characteristic simulation analysis model of a directional drilling machine power head gearbox for different levels of complex is established based on the detailed introduction of the modeling method of main components in gearbox,the influence of the stiffness of bearings and housing on dynamic characteristic of gear drive system is discussed. …”
Get full text