Representation Learning of Multi-Spectral Earth Observation Time Series and Evaluation for Crop Type Classification by Andrea González-Ramírez, Clement Atzberger, Deni Torres-Roman, Josué López

“…This averaged reconstruction difference vector is the base for the representations and the subsequent classification. …”
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Evaluation method of Driver’s olfactory preferences: a machine learning model based on multimodal physiological signals by Bangbei Tang, Bangbei Tang, Mingxin Zhu, Mingxin Zhu, Zhian Hu, Yongfeng Ding, Shengnan Chen, Yan Li

“…Additionally, compared with the dataset without baseline processing, the model’s accuracy increases by 3.50%, and the F1-score increases by 6.33% on the dataset after baseline processing.ConclusionsThe combination of physiological signals and machine learning models can effectively classify drivers' olfactory preferences. …”
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Flexible Baseband-Unit Aggregation Enabled by Reconfigurable Multi-IF Over WDM Fronthaul by Haiyun Xin, Hao He, Kuo Zhang, Syed Baqar Hussain, Weisheng Hu

“…Also, driven by the emerging optical fronthaul, traffic migration is introduced in optical fronthaul to help realize BBU aggregation, based on which traffic exchange within BBU pool can be reduced, thus decreasing corresponding processing latency and energy consumption. However, these traffic migration schemes are operated in a time-division multiplexing way and are not suitable for multi-IF over wavelength-division multiplexing (WDM) fronthaul. …”
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Obstacle Detection and Warning System for Visually Impaired Using IoT Sensors by Sunnia Ikram, Imran Sarwar Bajwa, Amna Ikram, Isabel de la Torre Diez, Carlos Eduardo Uc Rios, Angel Kuc Castilla

“…The system is equipped with ultrasonic sensor, PIR sensor and a buzzer, with data processing managed by an Arduino Uno microcontroller. …”
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Rapid classification of rice according to storage duration via near-infrared spectroscopy and machine learning by Chen Zhai, Wenxiu Wang, Man Gao, Xiaohui Feng, Shengjie Zhang, Chengjing Qian

“…However, existing methods of assessing rice storage time are time-consuming, laborious, and incompatible with modern industrial processing technologies. Therefore, we investigated the ability of near-infrared spectroscopy combined with machine learning algorithms to distinguish rice storage duration. …”
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Starting driving style recognition of electric city bus based on deep learning and CAN data by Dengfeng Zhao, Zhijun Fu, Chaohui Liu, Junjian Hou, Shesen Dong, Yudong Zhong

“…The sample data set of driving style is established by pre-processing the collected in-vehicle CAN bus data including the status of driving and vehicle motion, the data pre-processing method includes data cleaning, normalization and sample segmentation. …”
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Real-Time Intrusion Detection in Power Grids Using Deep Learning: Ensuring DPU Data Security by Maoran Xiao, Qi Zhou, Zhen Zhang, Junjie Yin

“…This paper explores the use of deep learning for real-time intrusion detection in power grids with a primary focus on safeguarding the integrity and security of Data Processing Units (DPUs). An evaluation of various machine learning models, including Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), Decision Trees, and Random Forests, is conducted to detect various types of intrusions, including Fault, Injection, Masquerade, Normal, and Replay. …”
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MSJosSAR Configuration Optimization and Scattering Mechanism Classification Based on Multi-Dimensional Features of Attribute Scattering Centers by Shuo Liu, Fubo Zhang, Longyong Chen, Minan Shi, Tao Jiang, Yuhui Lei

“…This study offers valuable insights and references for MSJosSAR configuration optimization and joint feature information processing.…”
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CPS-LSTM: Privacy-Sensitive Entity Adaptive Recognition Model for Power Systems by Hao Zhang, Jing Wang, Xuanyuan Wang, Xuhui Lü, Zhenzhi Guan, Zhenghua Cai, Hua Zhang

“…We then introduce CPS-LSTM (Character-level Privacy-sensitive Entity Adaptive Recognition Model), which enhances the recognition capability of privacy-sensitive entities in mixed Chinese and English text through character-level embedding and word vector fusion. The model features a streamlined architecture, accelerating convergence and enabling parallel sentence processing. …”
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Mobile Accelerometer Applications in Core Muscle Rehabilitation and Pre-Operative Assessment by Aleš Procházka, Daniel Martynek, Marie Vitujová, Daniela Janáková, Hana Charvátová, Oldřich Vyšata

“…A comprehensive computational methodology is introduced, incorporating traditional digital signal processing, feature extraction in both time and transform domains, and advanced classification techniques. …”
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A Fast Power Market Clearing Method Based on Active Constraints Identification by Deep Learning by Yunliang WU, Jianxin ZHANG, Bao LI, Peng LI, Zhiyong LI, Xin ZHOU, Yan YANG, Xiaowen LAI

“…Secondly, a deep learning strategy is proposed for identification of active constraint sets, which can provide technical support for deep neural networks to effectively identify the active constraints of SCED from two aspects: feature vector design and efficient processing of the results of deep neural network. …”
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Continuous prediction of human knee joint angle using a sparrow search algorithm optimized random forest model based on sEMG signals by Liuyi Ling, Zhu Lin, Bin Feng, Liyu Wei, Li Jin, Yiwen Wang

“…The sEMG signal and knee angle were recorded during four human motions, namely normal gait, sitting-standing transition, ascending stairs and descending stairs. These signals were processed to remove noise and extract eigenvalues in both time and frequency domains. …”
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Soil Organic Carbon Prediction and Mapping in Morocco Using PRISMA Hyperspectral Imagery and Meta-Learner Model by Yassine Bouslihim, Abdelkrim Bouasria, Budiman Minasny, Fabio Castaldi, Andree Mentho Nenkam, Ali El Battay, Abdelghani Chehbouni

“…This study presents a novel meta-learner framework that combines multiple machine learning algorithms and spectra processing algorithms to optimize SOC prediction using the PRISMA hyperspectral satellite imagery in the Doukkala plain of Morocco. …”
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An Integrated Learning Approach for Municipal Solid Waste Classification by Hieu M. Sondao, Tuan M. Le, Hung V. Pham, Minh T. Vu, Son Vu Truong Dao

“…This integrated approach also demonstrates superior performance (97.45%) compared to previous state-of-the-art models on the same dataset, with the data processing and method integration phases having substantial impacts.…”
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Viral and Viroid Communities in Peach Cultivars Grown in Bulgaria by Mariyana Gozmanova, Vesselin Baev, Rumyana Valkova, Elena Apostolova-Kuzova, Stoyanka Jurac, Galina Yahubyan, Lilyana Nacheva, Snezhana Milusheva

“…Maxim) are economically important stone fruits consumed worldwide, both fresh and processed. Viruses and viroids significantly constrain the cultivation and productivity of peach orchards. …”
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IoT-MFaceNet: Internet-of-Things-Based Face Recognition Using MobileNetV2 and FaceNet Deep-Learning Implementations on a Raspberry Pi-400 by Ahmad Saeed Mohammad, Thoalfeqar G. Jarullah, Musab T. S. Al-Kaltakchi, Jabir Alshehabi Al-Ani, Somdip Dey

“…Additionally, an in-house database is compiled, capturing data from 50 individuals via a web camera and 10 subjects through a smartphone camera. Pre-processing of the in-house database involves face detection using OpenCV’s Haar Cascade, Dlib’s CNN Face Detector, and Mediapipe’s Face. …”
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Genomic selection in pig breeding: comparative analysis of machine learning algorithms by Ruilin Su, Jingbo Lv, Yahui Xue, Sheng Jiang, Lei Zhou, Li Jiang, Junyan Tan, Zhencai Shen, Ping Zhong, Jianfeng Liu

“…Machine learning (ML) methods are usually used to predict phenotypic values since their advantages in processing high dimensional data. While, the existing researches have not indicated which ML methods are suitable for most pig genomic prediction. …”
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Comparative Analysis of Machine Learning Techniques for Fault Diagnosis of Rolling Element Bearing with Wear Defects by Devendra Sahu, Ritesh Kumar Dewangan, Surendra Pal Singh Matharu

“…This research addresses these challenges by employing advanced signal processing techniques and machine learning algorithms. …”
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Automated Parkinson’s Disease Diagnosis Using Decomposition Techniques and Deep Learning for Accurate Gait Analysis by S. Jeba Priya, C. Anand Deva Durai, M. S. P. Subathra, S. Thomas George, Andrew Jeyabose

“…The successful application of these methods highlights the importance of advanced signal processing techniques in improving the detection and management of neurological disorders.…”
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CNN-Based Optimization for Fish Species Classification: Tackling Environmental Variability, Class Imbalance, and Real-Time Constraints by Amirhosein Mohammadisabet, Raza Hasan, Vishal Dattana, Salman Mahmood, Saqib Hussain

“…Eight CNN architectures, including DenseNet121, MobileNetV2, and Xception, were compared alongside traditional classifiers like support vector machines (SVMs) and random forest. DenseNet121 achieved the highest accuracy (90.2%), leveraging its superior feature extraction and generalization capabilities, while MobileNetV2 balanced accuracy (83.57%) with computational efficiency, processing images in 0.07 s, making it ideal for real-time deployment. …”
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