An optimal weighting-based hybrid classifier for Children's congenital heart diseases signal processing by Morteza Ebrahimpour, Mehdi Khashei

“…The main objective of the proposed optimal weighting-based CNN-LSTM-SVM (OCLS) hybrid classifier is to simultaneously leverage the unique advantages of CNN in feature extraction from input signals, LSTM in modeling the sequential patterns of signals, SVM in classifying regular patterns, and especially the proposed weighting algorithm to optimally integrate the outputs of these components. …”
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Incorporating Attention Mechanism Into CNN-BiGRU Classifier for HAR by Ohoud Nafea, Wadood Abdul, Ghulam Muhammad

“…The HAR system is primarily intended to assist healthcare providers and elderly care facilities using other technologies such as the Internet of Things (IoT). Standard pattern recognition techniques have developed significantly, but they continue to depend on heuristic and manual feature extraction, which undermines the generalization performance. …”
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Remote Sensing Identification of Major Crops and Trade-Off of Water and Land Utilization of Oasis in Altay Prefecture by Gaowei Yan, Luguang Jiang, Ye Liu

“…Within this fragile balance lies a critical opportunity: efficient water resource management could pave the way for sustainable development across the entire arid oasis regions. This study uses a decision tree model based on a feature threshold to map the spatial distribution of major crops in the Altay Prefecture oasis, assess their water requirements, and identify the coupling relationships between agricultural water and land resources. …”
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Sql injection detection using Naïve Bayes classifier: A probabilistic approach for web application security by Lu Zhexi

“…Feature extraction is later employed to identify patterns and characteristics commonly associated with SQL injection, such as certain SQL clauses and logical operators. …”
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Spatial–temporal evolution and associated factors of older adult care institutions in Shanghai by Xingxing Yin, Jinghang Cui, Yifan Wu, Mingxuan Cui, Kun Li, Haoxiang Guo

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Characteristics of phase synchronization in electrohysterography and tocodynamometry for preterm birth prediction by Jae-Hwan Kang, Young-Ju Jeon, In-Seon Lee, Junsuk Kim

“…This study suggests the critical role of EHG signals and their intricate spatiotemporal patterns in predicting preterm birth, providing insights for the development of more accurate and efficient prediction models.…”
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Higher-order topology for collective motions by Zijie Sun, Tianjiang Hu

“…In this paper, we propose a specified higher-order topology, rather than the pairwise individual-to-individual pattern, to enable optimal responsiveness-persistence trade-off in collective motion. …”
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Urban Dynamics in Downtown Baghdad: Analyzing Syntactic Properties and Land Use Forms of AlShorja and Bab AlSharqi Areas by Noor Hadi Alsaffar, Dhirgham Alobaydi

“…This study explores how Baghdad’s downtown area incorporates this spatial arrangement into land use patterns to support vitality. Particularly attention is given to AlShorja and Bab AlSharqi (two districts within Downtown Baghdad). …”
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Identification of Tree-Related High-Impedance Earth Faults Based on Long-Term Fluctuations in Zero-Sequence Current by Pengwei Wang, Bingyin Xu, Tony Yip, Dong Liang, Guofeng Zou

“…The analysis of the recorded data from staged tests in a real test network reveals the development patterns of THIEFs and their zero-sequence characteristics during the fault process. …”
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Mining Potential Spammers from Mobile Call Logs by Zhipeng Liu, Dechang Pi, Yunfang Chen

“…With the rapid development of mobile telecommunication, voice call spam has become a growing problem in China. …”
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Fault diagnosis and inference of hoist main bearing based on transfer learning and ontology by Fei DONG, Di ZHANG, Kunpeng GE, Junjie CHEN, Xinyue XU

“…Firstly, the collected bearing vibration signals are processed, and it uses continuous wavelet transform to decompose the original vibration signals and extract two-dimensional time-frequency images; secondly, to adaptively extract deep features from both the source and target domains, the pre-trained and fine-tuning approaches are employed for convolutional neural networks transfer learning, and it constructs a transfer convolutional neural network model to achieve adaptive extraction of deep features from both domains; then, a new supervised domain adaptation method is proposed, integrating dynamic joint distribution adaptation with enhanced separability, to further reduce the distribution differences between deep feature sets of the source and target domains while effectively enhancing the separability of feature data; finally, a patterns recognition classifier is trained based on the source domain features after domain adaptation, which achieves fault patterns recognition in the target domain. ② Hoist main bearing fault knowledge reasoning based on ontology. …”
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Text-mining metadata: What can titles tell us of the history of modern and contemporary art? by Mike Bowman

“…The use of topic modelling, parts-of-speech tagging and word counting allows me to identify large-scale and long-run patterns in the language used in the titles of those artworks. …”
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Key social determinants of the Russian large family by R. M. Sadykov, N. L. Bolshakova

“…The authors analyse the social factors and features of having many children. The large families have undergone significant changes, have been greatly transformed in the process of social development and have a new social significance. …”
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Spatiotemporal Changes and Driving Mechanisms of Cropland Reclamation and Abandonment in Xinjiang by Yuling Fang, Shixin Wu, Guanyu Hou, Weiyi Long

“…The results indicate that cropland reclamation experiences a “slow decrease–rapid increase” trend, forming a “V-shaped” pattern, while abandonment shows a “rapid decrease–slow decrease–slow increase” trend, forming a “U-shaped” pattern. …”
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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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Ripening Study Based on Multi-Structural Inversion of Cherry Tomato qMRI by Yanan Li, Jingfa Yao, Wenhui Yang, Zhao Wei, Peng Luan, Guifa Teng

“…This study introduces a non-destructive, quantitative method using low-field MRI to assess moisture mobility and content distribution in cherry tomatoes. This study developed an advanced 3D non-local mean denoising model to enhance tissue feature analysis and applied an optimized TransUNet model for structural segmentation, obtaining multi-echo data from six tissue types. …”
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Early signs of strong El Niño–Southern Oscillation episodes by Wenxiu Zhong, Arnold Sullivan, Gian Luca Eusebi Borzelli, Ziguang Li

“…Additionally, we find that the spatial standard deviations of the sea surface temperature anomaly in Niño-3 and Niño-4 region, rapidly decrease in the first half of ENSO developing year. This feature is fundamentally distinct from that in neutral years, suggesting that the cycle of ENSO persistence goes beyond the SPB and sea surface temperature anomalies in those two Niño regions are the most predictable.…”
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Machine learning-guided field site selection for river classification by Zhihao Wang, Gregory Brian Pasternack, Yufang Jin, Costanza Rampini, Serena Alexander, Nikhil Kumar, Rune Storesund, K. Martin Perales, Christopher Lim, Stephanie Moreno, Igor Lacan

“…Results revealed clear differences in variable distributions between the 148 high‐certainty sites and the 51 high‐uncertainty sites, a pattern that was validated by our field surveys. Furthermore, the 41 newly identified high‐uncertainty sites were found under-represented in the initial surveyed sites and thus their selection for the next round of field surveys will help fill the important feature gaps left by the initial survey. …”
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Informal Settlements Extraction and Fuzzy Comprehensive Evaluation of Habitat Environment Quality Based on Multi-Source Data by Zanxian Yang, Fei Yang, Yuanjing Xiang, Haiyi Yang, Chunnuan Deng, Liang Hong, Zhongchang Sun

“…The study demonstrates that: (1) texture features from the gray level co-occurrence matrix (GLCM) significantly improved the classification of informal settlements, with the random forest classification model achieving a kappa coefficient above 0.77, an overall accuracy exceeding 0.89, and F1 scores above 0.90; (2) informal settlements exhibited two primary development patterns: gradual expansion near formal residential areas and dependence on natural resources such as farmland, forests, and water bodies; (3) economic vitality emerged as a critical factor in improving the living environment, while social, natural, and residential conditions remained relatively stable; (4) the proportion of highly suitable and moderately suitable areas increased from 65.62% to 65.92%, although the overall improvement in informal settlements remained slow. …”
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Feedback control architecture and the bacterial chemotaxis network. by Abdullah Hamadeh, Mark A J Roberts, Elias August, Patrick E McSharry, Philip K Maini, Judith P Armitage, Antonis Papachristodoulou

“…Bacteria move towards favourable and away from toxic environments by changing their swimming pattern. This response is regulated by the chemotaxis signalling pathway, which has an important feature: it uses feedback to 'reset' (adapt) the bacterial sensing ability, which allows the bacteria to sense a range of background environmental changes. …”
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