ML-Enabled Millimeter-Wave Software-Defined Radio With Programmable Directionality by Marc Jean, Murat Yuksel, Xun Gong

“…The increasing demand for gigabit-per-second speeds and higher wireless node density is driving the need for spatial reuse and the utilization of higher frequencies above the legacy sub-6 GHz bands. Since these super-6 GHz bands experience high path loss, directional beamforming has been the main method of access to the large amount of bandwidth available at these higher frequencies. …”
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Understanding students’ sentiment from feedback with a new feature selection and semantics networks by Tran Anh Tuan, Dao Thi Thanh Loan, Nichnan Kittiphattanabawon

“…Currently, existing systems use frequency-based methods for feature selection (e.g., Term Frequency-Inverse Document Frequency (TF-IDF) and Bag of Words (BoW)) not to capture the subtleties of emotions expressed in student feedback and do not provide insights into the specific concerns of students via topics or themes. …”
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Stability Domain Construction and Tuning for External Loop Controller Parameters Based on Permanent Magnet Wind Power Generation Systems by Hao Liang, Fei He, Guangtao Zhang, Chuan Qin

“…Based on the closed-loop frequency domain model of permanent magnet synchronous generator–based wind power generation system (PMSG-WPGS), the stability domain of the control parameters is constructed through the D-partition method in this paper to acquire the range of machine-side converter (MSC) and grid-side converter (GSC) parameters. …”
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Model Updating of Spindle Systems Based on the Identification of Joint Dynamics by Hongrui Cao, Songtao Xi, Wei Cheng

“…The joint stiffness is identified through the iteration process by minimizing the difference between the simulated FRF and the measured FRF of the assembly. The proposed method is verified with a machine-tool spindle system. …”
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Enhancing the performance of SSVEP-based BCIs by combining task-related component analysis and deep neural network by Qingguo Wei, Chang Li, Yijun Wang, Xiaorong Gao

“…However, an efficient strategy for integrating the two methods has not yet been established. To address this issue, we propose a classification framework named eTRCA + sbCNN that combines an ensemble task-related component analysis (eTRCA) algorithm and a sub-band convolutional neural network (sbCNN) for recognizing the frequency of SSVEP signals. …”
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RF Signal Feature Extraction in Integrated Sensing and Communication by Xiaoya Wang, Songlin Sun, Haiying Zhang, Qiang Liu

“…Whether using machine learning methods or current deep learning-based target fingerprint identification, its performance is based on how well the radio frequency features (RFF) are extracted. …”
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A Novel Fractional Filter Design and Cross-Term Elimination in Wigner Distribution by Jiexiao Yu, Kaihua Liu, Liang Zhang, Peng Luo

“…Without any prior knowledge of signal and noise, this method can meet the reliability and universality simultaneously for filter design and realize the global optimization of filter parameters by machine learning even in the case of strong coupling between signal and noise. …”
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Inner pace: A dynamic exploration and analysis of basketball game pace. by Fei Zhang, Qing Yi, Rui Dong, Jin Yan, Xiao Xu

“…By employing K-means clustering on possession duration, we categorized possessions from 1,141 NBA games in the 2019-2020 season into high-frequency (HFS), low-frequency (LFS), and normal-frequency segments (NFS). …”
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Continuous Head-related Transfer Function Representation Based on Hyperspherical Harmonics by Adam Szwajcowski

“…Expressing head-related transfer functions (HRTFs) in the spherical harmonic (SH) domain has been thoroughly studied as a method of obtaining continuity over space. However, HRTFs are functions not only of direction but also of frequency. …”
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Diagnosis and Model Based Identification of a Coupling Misalignment by P. Pennacchi, A. Vania

“…This paper is focused on the application of two different diagnostic techniques aimed to identify the most important faults in rotating machinery as well as on the simulation and prediction of the frequency response of rotating machines. The application of the two diagnostics techniques, the orbit shape analysis and the model based identification in the frequency domain, is described by means of an experimental case study that concerns a gas turbine-generator unit of a small power plant whose rotor-train was affected by an angular misalignment in a flexible coupling, caused by a wrong machine assembling. …”
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基于MED-SVM的齿轮箱故障诊断方法 by 刘志川, 唐力伟, 曹立军, 张远刚

“…In order to solve the problem of gearbox fault diagnosis,a new method based on minimum entropy deconvolution（MED）and support vector machine（SVM）is proposed.MED is used for gearbox vibration acceleration signal under background noise,then feature parameters extracted on breadth domain,frequency domain and energy domain of decreased signal are carried out,and the feature vector is built.Taking the feature vector as input,the multi-classification support vector machine is established,and the model parameters optimized by cross validation method are used to identify gearbox fault types.The fault diagnosis result of practical gearbox vibration signals shows that the proposed method can effectively identify different fault types of gear and bearing,and the optimizing model parameters can evidently improve fault identification accuracy.…”
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Optimizing Class Imbalance in Facial Expression Recognition Using Dynamic Intra-Class Clustering by Qingdu Li, Keting Fu, Jian Liu, Yishan Li, Qinze Ren, Kang Xu, Junxiu Fu, Na Liu, Ye Yuan

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Uncertainty in vibration energy flow analysis by W. BOCHNIAK, J. CIEŚLIK

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CONTROL OVER PROCESS OF SIMULTANEOUS DOUBLE-SIDED LENS FORMATION AT PRELIMINARY PROCESSING STAGE by I. P. Filonov, A. S. Kozeruk, E. O. Lapteva, M. I. Filonova, V. O. Kuznechik, A. V. Vasilevich

“…The paper contains calculation of friction ways in reference points of lens diametrical cross-section for various combinations of such setting parameters of technological equipment to ensure simultaneous lens processing as length of mark line during tool oscillatory motion, rotation frequency of a lens and an input element in an executing mechanism of a machine tool, tool diameter and ratio of its frequency rotation to lens frequency rotation.The paper shows that if control over the shaping process is executed through regulation of rotation frequency of the lens and the input element in the machine tool executing mechanism then unacceptable accuracy of the machined surface is obtained in case of their equal values. …”
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Interpreting neural decoding models using grouped model reliance. by Simon Valentin, Maximilian Harkotte, Tzvetan Popov

“…As a case study to demonstrate the method, random forest and support vector machine models were trained on within-participant single-trial EEG data from a Sternberg working memory task. …”
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Prediction and optimization of acoustic absorption performance of quasi-Helmholtz acoustic metamaterials based on LightGBM algorithm by Jianxin Xu, Weikang Mao, Xiaoqian Yu, Bingfei Liu

“…The results of this study show that the acoustic performance of quasi-Helmholtz acoustic metamaterials can be predicted and optimized using machine learning methods. The study in this paper combines the method of machine learning with acoustic problems to provide a fast method for predicting the absorption performance of acoustic metamaterials.…”
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Voltage Spectral Structure as a Parameter of System Technical Diagnostics of Ship Diesel Engine-Synchronous Generators by Gasparjans Aleksandrs, Terebkovs Aleksandrs, Zhiravetska Anastasia

“…A method of technical diagnostics of ship diesel engine – generator installation – is proposed. …”
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Research on Submarine Cable Buried Depth Monitoring Technology based on Brillouin Effect by WU Kun, WU Mingnian, CHEN Qingqing, WU Zhengming, XIE Shuhong, WANG Daogen, LI Songlin

“…【Methods】The article proposes an intelligent monitoring method that integrates BOTDA with Backpropagation Neural Network (BPNN). …”
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基于Shannon熵的LCD-SVM方法在齿轮故障分类中的研究 by 李鹏宇, 邵忍平, 汪亚运

“…Local feature scale decomposition（Local characteristic scale decomposition,LCD）is a new adaptive time-frequency analysis method,which can adaptively decompose a complex signal into a number of ISC（Intrinsic scale component,ISC）components.SVM（support vector machine,SVM）is a kind of intelligent classification methods of machine learning,Shannon entropy is a nonlinear statistical learning methods.The LCD and SVM are introduced to the fault classification of mechanical transmission system.The Hilbert demodulation algorithm is used to strike the envelope signal of ISC components,through which the Shannon entropy is structured.After an in-depth analysis on the basis,it is combined with SVM in good relationship.The result is input vectors of SVM classifier,the trained SVM is used to determine the fault location,the type or degree of the test sample.Through the experimental analysis and verification,using this combining method,the recognition rate of four operating states which contains the normal state,the root crack of tooth,the wear of tooth surface,the composite fault is up to 97.5%.…”
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Natural language processing-based approach for automatically coding ship sensor data by Yunhui Kim, Kwangphil Park, Byeongwoo Yoo

“…Accordingly, the characteristics of the IO descriptions were extracted using Term Frequency-Inverse Document Frequency (TF–IDF) and word embedding, and machine learning techniques such as K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) and deep learning models such as Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and bidirectional LSTM (BiLSTM) were used to classify them into codes. …”
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