Tracking pygmy blue whale diving behaviour and validation of foraging areas defined from horizontal movement data by Michele Thums, Luciana C. Ferreira, Andrew Davenport, Micheline Jenner, Luciana Möller, Grace Russell, Robert D. McCauley, Curt Jenner

“…Here, nine pygmy blue whales (Balaenoptera musculus brevicauda) were tagged with satellite tracking tags and pop-up archival tags (PATs) providing depth and accelerometry time series to determine where actual foraging occurs during migration. …”
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Understanding Human Papillomavirus Vaccination Hesitancy in Japan Using Social Media: Content Analysis by Junyu Liu, Qian Niu, Momoko Nagai-Tanima, Tomoki Aoyama

“…Natural language processing techniques and large language models (LLMs) were used for stance analysis of the collected data. Time series analysis and latent Dirichlet allocation topic modeling were used to identify shifts in public sentiment and topic trends over the decade. …”
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Enhancing stock index prediction: A hybrid LSTM-PSO model for improved forecasting accuracy. by Xiaohua Zeng, Changzhou Liang, Qian Yang, Fei Wang, Jieping Cai

“…The long short-term memory neural network (LSTM) widely employed in stock price prediction due to its ability to address long-term dependence and transmission of historical time signals in time series data. However, manual tuning of LSTM parameters significantly impacts model performance. …”
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A Semiparametric Approach for Modeling Partially Linear Autoregressive Model with Skew Normal Innovations by Leila Sakhabakhsh, Rahman Farnoosh, Afshin Fallah, Mohammadhassan Behzadi

“…The nonlinear autoregressive models under normal innovations are commonly used for nonlinear time series analysis in various fields. However, using this class of models for modeling skewed data leads to unreliable results due to the disability of these models for modeling skewness. …”
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Analysis of Business Cycles in the Breeding of Pigs, Cattle and Poultry and their Relationship to the Causality of Wheat and Rye Cultivation in Poland by Mateusz Mierzejewski, Magdalena Lampart

“…The study used a cross-spectral analysis, which indicated cyclical relationships and shifts between the studied time series. The methodology of the work was based on a simplified spectral analysis, i.e. the use of the square of coherence, spectral density and phase spectrum. …”
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NON-DAMAGE BUSINESS INTERRUPTION INSURANCE POLICIES DURING THE COVID-19 PANDEMIC by Marina Brogi, Valentina Lagasio, Fabrizio Santoboni

“… Pandemic risks, such as Covid-19, are difficult to insure as they are characterized by multiple factor risks and losses and involve different types of businesses and people simultaneously. The scarcity of time series and statistical data prevents insurers from developing correct pricing. …”
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Unveiling uncertain forces in second-order driven oscillators via internal model: A discrete-time feedback by R. Femat, C. Jiménez-gallegos

“…This contribution deals with recovering of the dynamics of the uncertain forces from measurements (time series). The main idea is to construct an internal model of the nonlinear system and design a discretetime feedback in such way that the model/system differences be stabilized at origin. …”
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Financial Risk Avoidance Based on the Sensor Network and Edge Computing by Yong Yu, Xiaoguo Yin

“…Moreover, this paper divides the sensor data into several sliding windows according to the time series, analyzes the offset between the data object and other data in the sliding window by calculating the offset distance, and uses the abnormal level to indicate the possibility of data abnormality. …”
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Forecasting Volatility with Time-Varying Coefficient Regressions by Qifeng Zhu, Miman You, Shan Wu

“…By capturing and studying the time series of time-varying coefficients of the predictors, we find that the coefficients (predictive ability) of heterogeneous volatilities are negatively correlated and the leverage effect is not significant or inverse during certain periods. …”
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Comparison of Statistical Methods to Graphical Methods in Rainfall Trend Analysis: Case Studies from Tropical Catchments by Upaka Rathnayake

“…Time series analyses for climatic factors are important in climate predictions. …”
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IMPACT OF PANELISTS ON WIBOR RATES – HYBRID APPROACH by Piotr Mielus

“…A solution is a hybrid method which combines declarations of panelists and prices of eligible transactions. Based on historic time series, the article analyses the impact of individual banks on the published index and presents the way the hybrid method can be used for WIBOR 3M. …”
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TESTING THE PURCHASING POWER PARITY HYPOTHESIS FOR BRICS: EVIDENCE FROM THE FOURIER UNIT ROOT AND COINTEGRATION TEST by Tuncer Gövdeli, Serpil Sumer

“…This study is a review of the purchasing power parity hypothesis applied to BRICS countries (Brazil, Russia, India, China, and South Africa). For each country, time series based on a Fourier perspective were applied. …”
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The Optimal Supply Decision Based on Dynamic Multiobjective Optimization and Prediction by Kejia He, Hongyu Cheng, Yuchen Zhou, Cuihua Xie

“…In contrast to traditional approaches that rely on expert opinions, the proposed approach in this study allows the time series analysis (ARIMA) to forecast the trend in manufacturers’ development during the execution of the plan. …”
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Recognizing human activities from smartphone sensors using hierarchical continuous hidden Markov models by Charissa Ann Ronao, Sung-Bae Cho

“…However, most of the existing works focus on discriminative classifiers while neglecting the inherent time-series and continuous characteristics of sensor data. …”
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Deep Neural Network Model Forecasting for Financial and Economic Market by Fan Chen

“…In view of the Internet financial market dynamic (volume and daily trading), it is proposed based on a deep neural network for fusion level time series prediction model. First, the proposed model processes the input of characteristic variables of multiple series (market macrodynamic series and multiseed series) and uses an attention mechanism to fuse the input variables in two dimensions of time and sequence feature. …”
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NON-DAMAGE BUSINESS INTERRUPTION INSURANCE POLICIES DURING THE COVID-19 PANDEMIC by Marina Brogi, Valentina Lagasio, Fabrizio Santoboni

“… Pandemic risks, such as Covid-19, are difficult to insure as they are characterized by multiple factor risks and losses and involve different types of businesses and people simultaneously. The scarcity of time series and statistical data prevents insurers from developing correct pricing. …”
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The Underwater Projectile Launching Process Prediction Based on Reduced Order Method by Ke Deng, Yi Jiang, Huan-Xing Liu

“…In this paper, computational fluid dynamics (CFD) and reduced order method (ROM) are developed for predicting the velocity time series during the initial stage of projectile launching. …”
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A Case Follow-Up Report: Possible Health Benefits of Extra Virgin Olive Oil by Said Shahtahmasebi, Shahnaz Shahtahmasebi

“…We recommend that future studies of this kind ought to include a time series of blood cholesterol based on daily measurements or intervals much shorter than the bimonthly measurements and to include measures of overall well being as covariates.…”
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Efficient Prediction of Network Traffic for Real-Time Applications by Muhammad Faisal Iqbal, Muhammad Zahid, Durdana Habib, Lizy Kurian John

“…Many predictors from three different classes, including classic time series, artificial neural networks, and wavelet transform-based predictors, are compared. …”
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A Missing Sensor Data Estimation Algorithm Based on Temporal and Spatial Correlation by Zhipeng Gao, Weijing Cheng, Xuesong Qiu, Luoming Meng

“…Firstly, it saves all the data sensed at the same time as a time series, and the most relevant series are selected as the analysis sample, which improves efficiency and accuracy of the algorithm significantly. …”
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