Optimal Service Time Distribution for an <i>M</i>/<i>G</i>/1 Waiting Queue by Mario Lefebvre, Roozbeh Yaghoubi

“…When the service times are exponential random variables, we can appeal to dynamic programming to obtain the optimal solution. …”
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Global Capital Flows, Time Varying Fundamentals and Transitional Exchange Rate Dynamics: An MS-VAR Approach by Süleyman Hilmi Kal, İlhami Gündüz

“…This paper studies whether dynamic relationship between exchange rate and economic and financial fundamentals vary depending on exchange rate is overvalued and undervalued with respect to its fundamental value. To achieve this, we implement two-state Markov Switching Vector Auto Regression (MSVAR) model with time varying transition probabilities to investigate whether the relationship among exchange rate, interest rate and inflation dynamics depend on overvaluation and undervaluation of exchange rates for the pre-crises period between years 1972-2009. …”
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Hybrid machine learning for real-time prediction of edema trajectory in large middle cerebral artery stroke by Ethan Phillips, Odhran O’Donoghue, Yumeng Zhang, Panos Tsimpos, Leigh Ann Mallinger, Stefanos Chatzidakis, Jack Pohlmann, Yili Du, Ivy Kim, Jonathan Song, Benjamin Brush, Stelios Smirnakis, Charlene J. Ong, Agni Orfanoudaki

“…Abstract In treating malignant cerebral edema after a large middle cerebral artery stroke, clinicians need quantitative tools for real-time risk assessment. Existing predictive models typically estimate risk at one, early time point, failing to account for dynamic variables. …”
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Clinical audit of nonoperative anaesthesia time and surgical site infections of canine tibial plateau osteotomy procedures by Amy Mann, Ciara Barr

“…Through anaesthesia record analysis we recognised that nonoperative anaesthesia time was a variable that could be targeted for improvement. …”
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VARIABILIDADE PLUVIOMÉTRICA DE ALGUNS MUNICÍPIOS DA REGIÃO METROPOLITANA DE CAMPINAS (SP) EM DOIS PERÍODOS HOMOGÊNEOS / Rainfall variability in some municipalities of the Metropoli... by Daniel Alves de Aguiar, Lucí Hidalgo Nunes

“…Periods that present lower rainfallamounts have higher values of coefficient of variation, i.e., there is higher variability of rainfalldistribution in the years which have lower totals, and in the winter. …”
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Estimation of pea samples with different leaf types according to adaptability parameter by A. R. Ashiev, K. N. Khabibullin, M. V. Skulova

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Time to recovery and its predictors among neonates undergone phototherapy at Comprehensive Specialized hospitals of the Northwest Ethiopia by Gezahagn Demsu Gedefaw, Abere Gebru Abuhay, Dawit Tesfaye Daka, Wubet Tazeb Wondie, Almaz Tefera Gonete, Fekadeselassie Belege Getaneh, Yaregal Semanew Endeshaw, Astewil Moges Bazezew, Bruck Tesfaye Legesse, Degalem Tilahun Worku, Mulugeta Endalamaw Ayenew, Asnake Tadesse Abate

“…Variables with a p-value less than 0.05 were considered statistically significant. …”
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Clarifying causality and information flows between time series: Particulate air pollution, temperature, and elderly mortality by Louis Anthony Cox, Jr

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Correlation Between Friction Time, Rotational Speed, and Mechanical Properties in Aluminum-Based Friction Welding Processes by Bibit Sugito, Agus Dwi Anggono, Agung Setyo Darmawan, Agus Hariyanto

“…In friction welding, rotational speed is a critical parameter that influences the welding outcomes by interacting with time and temperature variables. This study investigates the effects of varying friction times on the microstructure, hardness, and mechanical properties of friction-welded aluminum alloys. …”
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Effects of environmental factors on dengue incidence in the Central Region, Burkina Faso: A time series analyses. by Jean Claude Romaric Pingdwindé Ouédraogo, Sylvain Ilboudo, Richard Joshua Tetteh, Charles Kyei, Siaka Lougué, Wendlasida Thomas Ouédraogo, Salfo Ouédraogo, David Dosoo, Kwaku Poku Asante, Léon Gueswendé Blaise Savadogo

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TIME SERIES IMPUTATION USING VAR-IM (CASE STUDY: WEATHER DATA IN METEOROLOGICAL STATION OF CITEKO) by Muhammad Edy Rizal, Aji H Wigena, Farit M Afendi

“…Univariate imputation methods are defined as imputation methods that only use the information of the target variable to estimate missing values. While univariate imputation methods are convenient and flexible since no other variable is required, multivariate imputation methods can potentially improve imputation accuracy given that the other variables are relevant to the target variable. …”
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TemDeep: a self-supervised framework for temporal downscaling of atmospheric fields at arbitrary time resolutions by L. Wang, Q. Li, Q. Li, Q. Lv, Q. Lv, X. Peng, X. Peng, W. You

“…In this paper, we present a self-supervised framework for downscaling atmospheric variables at arbitrary time resolutions by imposing a temporal coherence constraint. …”
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Performance and variability analysis of ALD-grown wafer scale HfO2/Ta2O5-based memristive devices for neuromorphic computing by Sanjay Kumar, Sanjay Kumar, Deepika Yadav, Spyros Stathopoulos, Themis Prodromakis

“…Furthermore, the least values of coefficient of variability (CV) in the device switching voltages are 6.09% (VSET) and 3.22% (VRESET) in the case of device-to-device (D2D) while 1.76% (VSET) and 2.14% (VRESET) in the case of cycle-to-cycle (C2C). …”
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Acoustic behavior and time prediction method for water inrush of tunnel floor under osmotic water pressure by J.G. Wang, Z. Ma, Y.R. Cong, S. Yang

“…Through the monitoring of multiple physical information during the experimental process, the distribution of AE results in space and time was obtained, and the fracture sources were further categorized by the AF-RA values of the AE data. …”
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Decoding the Risk: Heart Rate Variability as a Powerful Predictor of Sudden Cardiac Death in Chronic Hemodialysis Patients—A 36-Month Prospective Study by Petar Avramovski, Maja Avramovska, Zorica Nikleski, Liljana Todorovska, Kosta Sotiroski, Vesna Siklovska, Irena Trajcevska, Saso Vasilevski

“…Among CHPs, SDNN was significantly lower in deceased patients (79.20 ± 14.84 ms) compared to survivors (106.91 ± 23.09 ms, P = 0.0097). The mean survival time for SCD was 34.8 ± 5.3 months. Cox regression coefficients b (-0.1146, 0.1224, 0.0781, and 0.0934), hazard ratio (HR) (0.8917, 1.1303, 1.0812, and 1.0979), and p-value (0.042, 0.203, 0.680 and 0.378) for SDNN, hs-CRP, albumin and hemodialysis (HD) duration, respectively, showed strongest predictive impact for SCD of HRV (SDNN) covariate, with hazard rate rising by 1.12145 (12.45%) for every single unit decrease of SDNN. …”
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High facility-level serum potassium variability associated with mortality in hemodialysis patients: results from Chinese Dialysis Outcomes and Practice Patterns Study (DOPPS) by Xinju Zhao, Fan Fan Hou, Xinling Liang, Zhaohui Ni, Xiaonong Chen, Yuqing Chen, Liangying Gan, Li Zuo

“…The role of facility-level serum potassium (sK+) variability (FL-SPV) in dialysis patients has not been extensively studied. …”
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Thermal characteristics of Falkner-Skan flow of time-dependent Maxwell material with varying viscosity and thermal conductivity by S. Bilal, Muhammad Yasir, Muhammad Bilal Riaz

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Time trend of Brazilian hospital admissions and deaths due to asthma among children and teenagers, 1998-2019. by Luiza Gabriela de Araújo Fonseca, Rêncio Bento Florêncio, Illia Nadinne Dantas Florentino Lima, Lucien Peroni Gualdi

“…The following variables were collected: number and place of hospital admissions classified by the ICD-10, absolute values and frequency by age group, gender and lethality. …”
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Finite and Infinte Time Blow Up of Solutions to Wave Equations with Combined Logarithmic and Power-Type Nonlinearities by Milena Dimova, Natalia Kolkovska, Nikolai Kutev

“…In this paper, we investigate the global behavior of the weak solutions to the initial boundary value problem for the nonlinear wave equation in a bounded domain. …”
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Interval Forecasting Using GEV Regression With Stochastic Search Variable Selection: A Simulation Study and Its Application to Forecast Imported Meat Price Range by Dedy Dwi Prastyo, Ike Yuniarti, Setiawan, Santi Puteri Rahayu

“…However, predicting this price range is challenging due to the asymmetric distribution of import prices, non-stationary trends, and time-varying covariates. Numerous covariates, including lags of response variables, increase computational complexity and multicollinearity issues, requiring variable selection to identify the most impactful covariates. …”
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