Dual-Polarimetric SAR Measurements to Observe Liquefaction Surface Manifestations by Ferdinando Nunziata, Anna Verlanti, Nicola Angelo Famiglietti, Maurizio Migliaccio, Annamaria Vicari

“…Experimental results, obtained processing a time-series of ascending and descending Sentinel-1 SAR scenes acquired during the 2023 Türkiye–Syria earthquake, confirm the soundness of the proposed approach.…”
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Water Quality Variations in the Lower Yangtze River Based on GA-RF Model From GF-1, Landsat-8, and Sentinel-2 Images by Wentao Hu, Shuanggen Jin, Yuanyuan Zhang

“…These models are validated and applied to derive long-term time series of TP and TN in the lower Yangtze River from 2018 to 2023. …”
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Mapping hierarchical wetland characteristics by optical-SAR integration with collaborative spatial-spectral-temporal learning by Linwei Yue, Meiyue Wang, Chengpeng Huang, Qing Cheng, Qiangqiang Yuan, Huanfeng Shen

“…Within the network, two parallel branches are designed to collaboratively learn the spatial, spectral or polarized, and temporal dependencies in the optical image and SAR image time series, respectively. Inspired by the relationships of deep and shallow features, the intra-layer features are fused across the branches to generate the multi-level wetland mapping results (i.e., general wetland land cover, and wetland vegetation types). …”
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Surfacing and diving behavior associated with thermal physiology in oceanic habitats of skipjack tuna (Katsuwonus pelamis) in the western north Pacific Ocean by Yoshinori Aoki, Takashi Kitagawa, Hidetada Kiyofuji

“…We aimed to examine how the thermal physiology of skipjack tuna (Katsuwonus pelamis, SKJ) can explain the differences in their vertical behavior, focusing on surfacing and diving, among various thermal environments during their northward migration in the western North Pacific.MethodsWe analyzed archival tag data collected during 2012–2015, with individual time series (Fork length: 38–49 cm, N = 38) of swimming depth, water temperature, and peritoneal body temperature during northward migration from subtropical areas to temperate regions around Japan. …”
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HiQ-FPAR: A High-Quality and Value-added MODIS Global FPAR Product from 2000 to 2023 by Kai Yan, Xinpei Yu, Jinxiu Liu, Jingrui Wang, Xiuzhi Chen, Jiabin Pu, Marie Weiss, Ranga B. Myneni

“…Additionally, HiQ-FPAR exhibits smoother time series in 52.1% of global areas, compared to 44.2% for MODIS. …”
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A comprehensive evaluation of ai techniques for air quality index prediction: RNNs and transformers by Pablo Andrés Buestán Andrade, Pedro Esteban Carrión Zamora, Anthony Eduardo Chamba Lara, Juan Pablo Pazmiño Piedra

“…Conversely, while Transformer-based models exhibited potential, they were less effective in handling intricate time-series data, resulting in comparatively lower accuracy. …”
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A Stock Closing Price Prediction Model Based on CNN-BiSLSTM by Haiyao Wang, Jianxuan Wang, Lihui Cao, Yifan Li, Qiuhong Sun, Jingyang Wang

“…Many factors affect the trend of the stock market, and the relevant information has the nature of time series. This paper proposes a composite model CNN-BiSLSTM to predict the closing price of the stock. …”
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Development and implementation of EcoDecibel: A low-cost and IoT-based device for noise measurement by Ling-Jyh Chen, Sakshi Saraswat, Fu-Shiang Ching, Chih-Yi Su, Hsin-Lan Huang, Wen-Chi Pan

“…The system was deployed across three environmental sites in Sanzhi District, Taiwan, for one week. Time-series prediction and forecasting models (SARIMA, Prophet, LSTM) were applied to the noise data to predict and forecast noise levels. …”
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Repetitive Control of Robotic Joint With Variable Impedance Utilizing Agonist-Antagonist Muscle Pair Structure Based on Virtual Trajectories by Kaho Umeda, Yinlai Jiang, Hiroshi Yokoi, Shunta Togo

“…The virtual trajectory is modeled by a time series of the equilibrium position of the spring. …”
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Statistical Analysis of Relationships between Monthly Maximum Temperatures in Iran and Global Mean Land-Ocean Temperature Anomalies by Yosouf ghavidel rahimi, Manochehr farajzadeh, Mehdi alijahan

“…Goals, the Pearson correlation method for detecting relationships between data's, linear and polynomial regression for trend analysis time series data , To illustrate the correlation between the spatial distribution of temperature data with global warming stations nationwide Geostatistical model Finally, non-parametric test for detecting significant temperature change Man - Kendall were used. …”
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A Time-Varying Coupling Analysis of Expressway Traffic Volume and Manufacturing PMI by Shuo Sun, Mingchen Gu, Yingping Wang, Rongjie Lin, Lifeng Xing, Zhiyuan Xu

“…First, for the traffic volume and manufacturing PMI time-series data, unit root stability test and Johansen cointegration test are applied to determine the stability of single sequence and the long-term stable correlation between variables, respectively. …”
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A Reinforcement Learning Model for Optimal Treatment Strategies in Intensive Care: Assessment of the Role of Cardiorespiratory Features by Cristian Drudi, Maximiliano Mollura, Li-wei H. Lehman, Riccardo Barbieri

“…A Markov Decision Process (MDP) was built on the extracted discrete time-series. A policy iteration algorithm was used to obtain the optimal AI policy for the MDP. …”
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Transcriptome-based insights into the calcium transport mechanism of chick chorioallantoic membrane by Qun Huang, Ran Yang, Qia Wang, Hui Teng, Hongbo Song, Fang Geng, Peng Luo

“…Functional enrichment analysis of DEGs showed that CAM DEGs were mainly involved in biological processes such as “ion transport regulation”, “immune response” and “cell cycle”. Time series analysis of the differential genes showed that the functional cells of CAM began to proliferate and differentiate at E9 and the calcium content of egg embryo increased significantly at E13. …”
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Groundwater Level Forecasting in the Jakarta Groundwater Basin by Andi Agus Nur, Dani Ruswandi

“…Changes in well GWL serve as a direct indicator of the effects of groundwater evolution, and GWL time series usually contain important information about aquifer dynamics. …”
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Effect of a closed-loop medication order executive system on safe medication administration at a tertiary hospital: a quasi-experimental study by Xuwen Yin, Haiyan Song, Jieyu Lu, Jing Yang, Rong Wang, Zheng Lin, Shudi Jiang, Hui Yuan, Xumei Wang, Dongmei Xu, Chunhong Gao, Yuan Zhou, Jiayi Xu, Chen Chen, Chenyu Gu, Qingqing Diao, Fang Li, Zejuan Gu

“…The autoregressive integrated moving average (ARIMA) model in time-series analysis was used to evaluate the level and trend changes in ME rates using SPSS 25.0 before and after system implementation. …”
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The growth–environment nexus amid geopolitical risks: cointegration and machine learning algorithm approaches by Md. Idris Ali, Md. Atikur Rahaman, Mohammed Julfikar Ali, Md. Ferdausur Rahman

“…To bridge this gap, this study examines the role of per capita income on environmental outcomes under the Environmental Kuznets Curve (EKC) framework, explicitly incorporating geopolitical risks as a critical determinant. Using Canadian time series data spanning from 1980 to 2022, this research employs the autoregressive distributed lag (ARDL) estimation technique to explore short- and long-term cointegrating relationships among key variables, including economic growth, energy consumption, trade openness, foreign direct investment (FDI), ICT development, and financial development. …”
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Rapid Emulation of Spatially Resolved Temperature Response to Effective Radiative Forcing by Christopher B. Womack, Paolo Giani, Sebastian D. Eastham, Noelle E. Selin

“…We derive impulse response functions by directly deconvolving effective radiative forcing and near‐surface air temperature time series. This enables rapid emulation of new scenarios through convolution and derivation of other impulse response functions from any forcing to its response. …”
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Amalgamation and Local Finance: A Case Study of Ukraine by Glendal Wright, Sergii Slukhai, Bohdan Yakymchuk

“…The decentralization reform was based on three pillars: (1) voluntary amalgamation of the territorial units, (2) enhanced financial resources through own source revenues and infrastructure grants, and (3) utilization of inter-municipal cooperation to support improved service delivery. Methodology: A time series of fiscal data from amalgamated territorial communities in selected regions of Ukraine have been analysed to measure the impact of the amalgamation policy on the amalgamated territorial units. …”
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A Novel Long Short-Term Memory Predicted Algorithm for BDS Short-Term Satellite Clock Offsets by Tailai Wen, Gang Ou, Xiaomei Tang, Pengyu Zhang, Pengcheng Wang

“…To deal with this problem, we proposed a deep learning-based approach for BDS short-term satellite clock offset modeling which utilizes the superiority of Long Short-Term Memory (LSTM) derived from Recurrent Neural Networks (RNN) in time series modeling, and we call it QPLSTM. The ultrarapid predicted clock products provided by IGS (IGU-P) and four widely used prediction methods (the linear polynomial, quadratic polynomial, gray system (GM (1,1)), and Autoregressive Integrated Moving Average (ARIMA) model) are selected to compare with the QPLSTM. …”
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Machine Learning Model for Imbalanced Cholera Dataset in Tanzania by Judith Leo, Edith Luhanga, Kisangiri Michael

“…However, the study could not be treated as a time series problem due to the data collection bias. …”
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