Cognitive link adaptation via modulation scheme classification in narrowband networks under AWGN and SUI channel conditions by Fatima Ismail, Sajid Gul Khawaja, Asad Mansoor Khan, Umer Hameed Shah, Muhammad Usman Akram, Arslan Shaukat

“…A hierarchical approach is adopted in place of traditional methods that classify modulation schemes as separate entities. …”
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Estimation of Stresses in a Plate with a Concentrator through Ultrasonic Measurements of Acoustic Anisotropy by D. A. Tretyakov, D. S. Osovik

“…A 510×120×15 mm plate with a central hole of 40 mm in diameter was cut from a sheet of commercial-purity aluminum of the AMc brand (AW-3003 according to ISO) across the rolling direction, and subjected to uniaxial step loading in an Instron-8850 testing machine. For ultrasonic measurements, an acoustic sensor with a carrier frequency of 5 MHz was used. …”
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Research on artificial intelligence-driven container relocation problem for green ports by Sisi Zheng, Jin Sha, Yinying Kong, Yougan Wang

“…IntroductionContainer relocation in port yards represents a canonical NP-hard problem, characterized by high-dimensional nonlinear constraints and stringent real-time decision-making requirements.MethodsThis study proposes a unified framework integrating an Intelligent Decision-Driven Model (IDDM), an Adaptive Data Generator (ADG), and an Optimization–Learning Closed-Loop Framework (OLCF).ResultsThe IDDM leverages heuristic search and machine learning within a multi-stage decision mechanism to mitigate the curse of dimensionality; in two-dimensional scenarios involving 50–100 containers, the model achieves an average response time of 9.83 ± 0.12 µs and reduces relocation operations by 61.68%. …”
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Voice-Evoked Color Prediction Using Deep Neural Networks in Sound–Color Synesthesia by Raminta Bartulienė, Aušra Saudargienė, Karolina Reinytė, Gustavas Davidavičius, Rūta Davidavičienė, Šarūnas Ašmantas, Gailius Raškinis, Saulius Šatkauskas

“…The deep neural network classified previously unseen voice recordings with 0.84 accuracy, 0.81 specificity, 0.86 sensitivity, and 0.85 and 0.81 F1-scores for blue and pink classes, respectively. The machine learning algorithms revealed that voice parameters, such as Mel-frequency cepstral coefficients, Chroma vectors, and sound energy, play the most significant role. …”
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High gamma EEG responses to emotional stimuli in virtual reality: insights from local activation and distributed characteristics by Shasha Xiao, Nadia Youssef, Qingxun Zhang, Xiaoqian Lin, Ziquan Qiu, Wenjie Liu, Xianglian Meng, Minchang Yu

“…IntroductionHigh frequency electroencephalogram (EEG) activity, particularly in the high gamma range, plays an important role in research on human emotions. …”
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Lateral vibration estimation of an elevator rope by sequential modal decomposition of elevator rope displacement observed near the traction sheave by Daisuke TAINAKA, Nanako MIURA, Keito SUMIDA, Arata MASUDA

“…In contrast, this paper proposes the estimation method by a sensor installed near the traction sheave in the machine room. …”
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Ensemble deep learning and anomaly detection framework for automatic audio classification: Insights into deer vocalizations by Salem Ibrahim Salem, Sakae Shirayama, Sho Shimazaki, Kazuo Oki

“…Therefore, we propose a framework that begins with a robust segmentation method for extracting sound clips that potentially contain deer vocalizations. …”
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Spatiospectral dynamics of electroencephalography patterns during propofol-induced alterations of consciousness states by Xuan Li, Dezhao Liu, Zheng Li, Rui Wang, Xiaoli Li, Tianyi Zhou

“…Our methods yielded six dynamical patterns that continuously reflect the neural activity changes in specific brain regions and frequency bands under propofol sedation. …”
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Bidirectional Long Short-Term Memory–Based Detection of Adverse Drug Reaction Posts Using Korean Social Networking Services Data: Deep Learning Approaches by Chung-Chun Lee, Seunghee Lee, Mi-Hwa Song, Jong-Yeup Kim, Suehyun Lee

“…Based on this information, we aimed to develop a deep learning model that classifies drug ADR posts based on a recurrent neural network. MethodsIn previous studies, ketoprofen, which has a high prescription frequency and, thus, was referred to the most in posts secured from SNS data, was selected as the target drug. …”
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Pediatric Long COVID Subphenotypes: An EHR-based study from the RECOVER program. by Vitaly Lorman, L Charles Bailey, Xing Song, Suchitra Rao, Mady Hornig, Levon Utidjian, Hanieh Razzaghi, Asuncion Mejias, John Erik Leikauf, Seuli Bose Brill, Andrea Allen, H Timothy Bunnell, Cara Reedy, Abu Saleh Mohammad Mosa, Benjamin D Horne, Carol Reynolds Geary, Cynthia H Chuang, David A Williams, Dimitri A Christakis, Elizabeth A Chrischilles, Eneida A Mendonca, Lindsay G Cowell, Lisa McCorkell, Mei Liu, Mollie R Cummins, Ravi Jhaveri, Saul Blecker, Christopher B Forrest, RECOVER Consortium

“…Our method, an extension of the Phe2Vec algorithm, uses tens of thousands of clinical concepts from multiple domains to represent patients' clinical histories to then identify groups of patients with similar presentations. …”
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Identification of Voltage Sag Source in Distribution Network Based on BAS-SVM by Haitao LIU, Xiaoyi YE, Ganyun LÜ, Huajun YUAN, Zongpu GENG

“…In order to improve the identification accuracy of different voltage sag disturbance sources, a voltage sag source identification method based on beetle antennae search (BAS) and support vector machine (SVM) is proposed. …”
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Determination of the Bentonite Content in Molding Sands Using AI-Enhanced Electrical Impedance Spectroscopy by Xiaohu Ma, Alice Fischerauer, Sebastian Haacke, Gerhard Fischerauer

“…Optimizing the control of these mixtures and the recycling of used sand after casting requires an efficient in-line monitoring method, which is currently unavailable. This study explores the potential of an AI-enhanced electrical impedance spectroscopy (EIS) system as a solution. …”
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Energy Evolution and AE Failure Precursory Characteristics of Rocks with Different Rockburst Proneness by Feng Pei, Hongguang Ji, Jiwei Zhao, Jingming Geng

“…The intensity of AE signals generated in the failure process of strong rockburst rock (granite) is significantly higher than that of moderate rockburst rock (metagabbro). However, the peak frequency bands and amplitude all increase obviously before failure. …”
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Monthly Runoff Prediction Based on STL-CEEMDAN-LSTM Model by WANG Hai, SHEN Yanqing, QI Shansheng, PAN Hongzhong, HUO Jianzhen, WANG Zhance

“…According to the nonlinear and non-stationary characteristics of monthly runoff sequences, the quadratic decomposition method was combined with machine learning to construct a model for predicting monthly runoff. …”
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Documenting the Production Process of Faba bean (Vicia faba L.) in Gorgan, Ali Abadkatol and Aqqola Regions by Mohammad Reza Mansouri Vajari, Ebrahim Zeinali, Afshin Soltani, Benjamin Torabi, Alireza Nehbandani

“…In order to analyze the data, absolute and cumulative frequency distribution was used. In these investigations, the scope of changes and the method of performing each management operation performed in the bean farms and also the proportion of farmers who used different methods of each of these management operations were determined. …”
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A Novel Multiscale Deep Health Indicator with Bidirectional LSTM Network for Bearing Performance Degradation Trend Prognosis by Han Wang, Gang Tang, Youguang Zhou, Yujing Huang

“…This paper proposes a novel strategy for bearing performance degradation trend prognosis, including health indicator construction techniques and a performance degradation trend prediction method. To more accurately represent the degradation trend, the multiscale deep bottleneck health indicator is proposed as a new synthesized health indicator to remove high-frequency detail signals from features, which can reduce possible fluctuations in conventional synthetic health indicators. …”
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Road Event Detection and Classification Algorithm Using Vibration and Acceleration Data by Abiel Aguilar-González, Alejandro Medina Santiago

“…Traditional approaches often require complex feature engineering or the use of machine learning models, which can be computationally intensive, especially when dealing with real-time data from high-frequency vibration and acceleration sensors. …”
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LightGBM-Based Human Action Recognition Using Sensors by Yinuo Liu, Ziwei Chen

“…First, a feature extraction method for sensor data from both the time domain and frequency domain is designed to obtain more than 300 features, aiming to enhance the accuracy and stability of recognition. …”
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Noise research under flat parts processing through ball-and-rod reinforcement by Alexander G Isaev, Mikhail A Tamarkin, Sergey A. Razdorskiy

“…It is found that noise under processing far exceeds the allowable range. Materials and Methods. The investigation was conducted on a universal milling machine. …”
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Characterising Payload Entropy in Packet Flows—Baseline Entropy Analysis for Network Anomaly Detection by Anthony Kenyon, Lipika Deka, David Elizondo

“…A key technique in early detection is the classification of unusual patterns of network behaviour, often hidden as low-frequency events within complex time-series packet flows. …”
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