Personality typology, emotional needs, and romantic relationship stability in Chinese college students: A cultural perspective on MBTI dynamics by Jiaxin Li, Gu Fang, Yiyang Li

“…Structural equation modeling further indicated that gender and personality interactions influence emotional stability, with distinct patterns observed among NT, SJ, and SP types. A U-shaped pattern of emotional stability across academic years was identified, with freshmen showing the highest levels, declining in juniors, and slightly recovering in seniors. …”
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Classification Modeling Method for Near-Infrared Spectroscopy of Tobacco Based on Multimodal Convolution Neural Networks by Lei Zhang, Xiangqian Ding, Ruichun Hou

“…In order to improve the accuracy of the tobacco origin classification, a near-infrared spectrum (NIRS) identification method based on multimodal convolutional neural networks (CNN) was proposed, taking advantage of the strong feature extraction ability of the CNN. Firstly, the one-dimensional convolutional neural network (1-D CNN) is used to extract and combine the pattern features of one-dimensional NIRS data, and then the extracted features are used for classification. …”
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Graph-informed convolutional autoencoder to classify brain responses during sleep by Sahar Zakeri, Somayeh Makouei, Sebelan Danishvar

“…The accuracy of the SlS-GICA classifier is 99.92% on the significant feature set. This achievement could be considered in real-time and automatic applications to develop new therapeutic strategies for sleep-related disorders.…”
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Révision de l’espèce Homo erectus (Dubois, 1893) by Valéry Zeitoun

“…The reconstruction of this evolutionary pattern should be matched with other data (dating, biogeography) to allow to reconstruct a real evolutionary synopsis.According to several authors (Stringer, 1984; Hublin, 1986; Kennedy, 1991; Brauer and Mbua, 1992) the existence of autapomorphic features for Homo erectus is not proved. …”
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Spatiotemporal Heterogeneity and Zoning Strategies of Multifunctional Trade-Offs and Synergies in Cultivated Land in the Hexi Corridor by Kaichun Zhou, Zixiang Sun, Tingting Ma, Yulin Li, Binggeng Xie

“…Through self-organizing feature map analysis, the cultivated land in the Hexi Corridor is divided into four functional areas: agricultural production-dominant areas, agricultural social security areas, ecological agriculture areas, and balanced development areas, and management objectives are proposed. …”
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Multimodal machine learning for analysing multifactorial causes of disease—The case of childhood overweight and obesity in Mexico by Rosario Silva Sepulveda, Magnus Boman, Magnus Boman

“…Public health interventions have shown only moderate success, possibly from relying on knowledge extracted using limited types of statistical data analysis methods.PurposeTo explore if multimodal machine learning can enhance identifying predictive features from obesogenic environments and investigating complex disease or social patterns, using the Mexican National Health and Nutrition Survey.MethodsWe grouped features into five data modalities corresponding to paediatric population exogenous factors, in two multimodal machine learning pipelines, against a unimodal early fusion baseline. …”
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Dementia Scale Score Classification Based on Daily Activities Using Multiple Sensors by Akira Minamisawa, Shogo Okada, Ken Inoue, Mami Noguchi

“…We analyzed the effects of different types of sensor data, such as time spent in an individual room according to human motion sensors, location in a facility, and sleep patterns, on dementia detection. We then developed a feature extraction method related to daily activity patterns based on a clustering algorithm and analyzed its effectiveness. …”
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Integration of geospatial techniques and machine learning in land parcel prediction by Nekkanti Haripavan, Subhashish Dey, Chimakurthi Harika Mani Chandana

“…By harnessing the temporal and spectral information captured by Earth observation satellites, we aim to identify patterns and trends in land parcel changes. These insights are used to train and fine-tune our machine learning models, which will subsequently forecast future land parcel developments. …”
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Deep Learning for the Early Diagnosis of Candidemia by Daniele Roberto Giacobbe, Sabrina Guastavino, Anna Razzetta, Cristina Marelli, Sara Mora, Chiara Russo, Giorgia Brucci, Alessandro Limongelli, Antonio Vena, Malgorzata Mikulska, Alessio Signori, Antonio Di Biagio, Anna Marchese, Ylenia Murgia, Marco Muccio, Nicola Rosso, Michele Piana, Mauro Giacomini, Cristina Campi, Matteo Bassetti

“…Conclusions A deep learning model trained on nonspecific laboratory features showed some discriminatory ability to differentiate candidemia from bacteremia, highlighting the ability of deep learning to exploit complex patterns within nonspecific laboratory data. …”
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The Space Conceptual Models and Water Vapor Characteristics of Typical Rainstorms during Plum Rain Season by Ying Tian, Rong Yao, Enrong Zhao, Qian Yao, Xiaolong Pan

“…The daily precipitation of LLVSP cases has extremity feature. The occurrence and development of rainstorms are well coordinated with the systems on lower levels. …”
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Application of Deep Learning Algorithm for Web Shell Detection in Web Application Security System by Rezky Yuranda, Edi Surya Negara

“…Through preprocessing techniques such as opcode extraction and feature selection, useful pattern recognition for web shell detection is achieved. …”
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Differential gray matter correlates and machine learning prediction of abuse and internalizing psychopathology in adolescent females by Sara A. Heyn, Taylor J. Keding, Josh Cisler, Katie McLaughlin, Ryan J. Herringa

“…Shapley values were aggregated across the entire cohort, and the top 1% of feature clusters with the highest importance are reported. …”
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Fluid Equation-Based and Data-Driven Simulation of Special Effects Animation by Yujuan Deng

“…Finally, the 3D motion trajectory of the point feature object and the motion pattern at a certain moment are shown, and the method in this paper obtains more ideal results, which proves the effectiveness of the method.…”
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Improving automated scoring of prosody in oral reading fluency using deep learning algorithm by Kuo Wang, Xin Qiao, George Sammit, Eric C. Larson, Joseph Nese, Akihito Kamata

“…Our findings also indicate that students’ reading patterns influence cross-domain performance more than specific text passage patterns. …”
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Evolution and driving factors of “Production-living-ecological spaces” in mountainous counties: a case study of Tongdao County, Hunan Province by Hengyuan Cao, Weidong Liu, Minjie Liu

“…Third, PLES are significantly affected by water sources and roads, and the production and living spaces are typically located adjacent to these features. Finally, the development and evolution of PLES patterns are primarily influenced by natural geographical factors, with socioeconomic factors acting as the primary driving force. …”
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Low-hit frequency-hopping communication systems for power Internet of things random access by Shu DU, Mei MA, Bo ZHAO, Qi ZENG, Xing LIU

“…The communication network is an essential component of the data acquisition and information transmission in power Internet of things (IoT).To meet the development requirements of multiple power service in the future, the wireless communication technique with flexible-access and high scalability is one of the development directions for power IoT.Due to the features of large-scale access, random access time, high security and reliability for information transmission of power IoT, a frequency-hopping (FH) technique with low-hit rate for random access was proposed.The construction algorithm of such FH pattern was based upon the combination and shift operation of conventional FH sequences.By the theoretical arithmetic and numerical simulation, the properties of the proposed FH pattern and the error-rate of the FH-based power IoT were evaluated.The analysis reveals that the new class of FH sequences and the system can meet the requirements of large-scale access and highly reliable communication for the power IoT, which has good application prospects.…”
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Unsupervised machine learning-based multi-attributes analysis for enhancing gas channel detection and facies classification in the serpent field, offshore Nile Delta, Egypt by Shaimaa A. El-Dabaa, Farouk I. Metwalli, Ali Maher, Amir Ismail

“…Seismic attribute analysis can enhance the tracking of subtle stratigraphic features. It is challenging to investigate these subtle features, including channel systems, with conventional-amplitude seismic data. …”
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Multi-tissue transcriptomic characterization of endogenous retrovirus-derived transcripts in Capra hircus by Ming-Di Li, Ming-Di Li, Hu-Rong Li, Shao-Hui Ye

“…However, the expression pattern of TEs in those less studied species, like goat (Capra hircus), remains unclear. …”
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Modeling Visual Fatigue in Remote Tower Air Traffic Controllers: A Multimodal Physiological Data-Based Approach by Ruihan Liang, Weijun Pan, Qinghai Zuo, Chen Zhang, Shenhao Chen, Sheng Chen, Leilei Deng

“…The model achieved an average balanced accuracy of 0.92 and an F1 score of 0.90 under 12-fold cross-validation, demonstrating excellent predictive performance. The high-ranking features spanned four modalities, revealing typical physiological patterns of visual fatigue across ocular behavior, cortical activity, autonomic regulation, and arousal level. …”
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Real-time Diagnosis and Prediction of Grounding Insulation Fault inTrain Power Supply System by QIN Fangfang, ZHENG Caihui, LI Xueming, LI Peng

“…In order to solve the problem of fault location and real-time evaluation of fault development trend, it proposed a real-time diagnosis and prediction method based on signal feature pattern recognition. …”
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