Implementation model of the production process control system at a car service enterprise by Evgeniy S. Kozin

“…To simulate the system operation, a simulation model is used that takes into account the gradual increase in the error of performers and its elimination when applying the control action. …”
Get full text

Addressing the challenges of estimating the target population in calculation of routine infant immunization coverage in Kenya. by Christine Karanja-Chege, Ambrose Agweyu, Fred Were, Michael Boele van Hensbroek, William Ogallo

“…We assessed the accuracy of the estimates for 2003-2018 by computing the Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and the Pearson Correlation Coefficient (r), excluding outliers. …”
Get full text

Forecasting Temperature Time Series Data Using Combined Statistical and Deep Learning Methods: A Case Study of Nairobi County Daily Temperature by John Kamwele Mutinda, Amos Kipkorir Langat, Samuel Musili Mwalili

“…Evaluation metrics, including root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and R-squared, highlighted the superiority of hybrid models over individual approaches, particularly those combining VMD with ARIMA, GRU, LSTM, and Transformer. …”
Get full text

What diameter? What height? Influence of measures of average tree size on area-based allometric volume relationships by Yilin Wang, John A. Kershaw, Mark J. Ducey, Yuan Sun, James B. McCarter

“…The overall best equation used quadratic mean diameter, Lorey’s height, and density (root mean square error ​= ​5.26 ​m3⋅ha−1; 1.9 % relative error). The best equation without density used mean diameter of the largest trees needed to calculate a stand density index of 400 and the mean height of the tallest 400 trees per ha (root mean square error ​= ​32.08 ​m3⋅ha−1; 11.8 % relative error). …”
Get full text

Significance of the ARIMA epidemiological modeling to predict the rate of HIV and AIDS in the Kumba Health District of Cameroon by Arrey Emmanuel Besong, Odette Dzemo Kibu, Odette Dzemo Kibu, Odette Dzemo Kibu, Odette Dzemo Kibu, Elvis Asangbeng Tanue, Elvis Asangbeng Tanue, Elvis Asangbeng Tanue, Elvis Asangbeng Tanue, Besong Agbor Obinkem, Ginyu Innocentia Kwalar, Ginyu Innocentia Kwalar, Ginyu Innocentia Kwalar, Ginyu Innocentia Kwalar, Fabrice Chethkwo, Valentine Ndze Ngum, Maurice Marcel Sandeu, Maurice Marcel Sandeu, Maurice Marcel Sandeu, Maurice Marcel Sandeu, Patrick Jolly Ngono Ema, Patrick Jolly Ngono Ema, Patrick Jolly Ngono Ema, Patrick Jolly Ngono Ema, Nkweteyim Denis, Nkweteyim Denis, Nkweteyim Denis, Nkweteyim Denis, Onduo Moise, Onduo Moise, Onduo Moise, Onduo Moise, Ayana Gelan, Ayana Gelan, Ayana Gelan, Ayana Gelan, Jude Dzevela Kong, Jude Dzevela Kong, Jude Dzevela Kong, Dickson Shey Nsagha, Dickson Shey Nsagha, Dickson Shey Nsagha, Dickson Shey Nsagha

“…This disease has significant health and socio-economic implications and is one of the primary causes of illness and death globally (UNAIDS, 2022). …”
Get full text

A comparative analysis of L-moments, maximum likelihood, and maximum product of spacing methods for the four-parameter kappa distribution in extreme value analysis by Muhammad Shafeeq ul Rehman Khan, Zamir Hussain, Sadaf Sher, Muhammad Amjad, Faisal Baig, Ishfaq Ahmad, Hamd Ullah

“…The accuracy of the estimates has been evaluated using root mean square error (RMSE) and bias. The paper also includes an analysis of the effect of the estimation method on the estimated quantiles considering a real-life example of annual maximum peak flows and the Generalized Normal Distribution as the error distribution. …”
Get full text

Agreement of Analytical and Simulation‐Based Estimates of the Required Land Depth in Climate Models by N. J. Steinert, J. F. González‐Rouco, C. A. Melo Aguilar, F. García Pereira, E. García‐Bustamante, P. deVrese, V. Alexeev, J. H. Jungclaus, S. J. Lorenz, S. Hagemann

“…Any depth increase gradually decreases the relative error in the subsurface thermodynamics, and a minimum depth of 170 m is recommended to simulate the ground climate adequately. …”
Get full text

Multilevel Monte Carlo methods for ensemble variational data assimilation by M. Destouches, M. Destouches, M. Destouches, P. Mycek, P. Mycek, S. Gürol, S. Gürol, A. T. Weaver, A. T. Weaver, S. Gratton, E. Simon

“…<p>Ensemble variational data assimilation relies on ensembles of forecasts to estimate the background error covariance matrix <span class="inline-formula"><strong>B</strong></span>. …”
Get full text

ESTIMATION OF THE STANDARD GROWTH REGION OF NATIVE TURKEYS (Meleagris gallopavo L.) CALCULATED USING THE RICHARDS EQUATION by Marco Antonio Camacho-Escobar, Sergio Machorro-Sámano, Serafín Jacobo López-Garrido, Narciso Ysac Ávila-Serrano, Mónica Marcela Galicia-Jiménez, Jorge Alberto Cruz-Torres, Eliud Flores-Morales

“…Determination coefficient of 0.993, standard error of the estimate of 190.5 g, and maximum growth rate of 322.11 g*week-1 at 18.22 weeks of age were obtained. …”
Get full text

Improving Investment Forecasting: A Comparative Analysis of Machine Learning Models as Key GDP Indicators by Cheng-Hong Yang, Tshimologo Molefyane, Borcy Lee, Ting-Jen Hsueh, Yu-da Lin

“…Key performance metrics&#x2014;Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE)&#x2014;demonstrated that the GRU model achieved superior accuracy. …”
Get full text

Fitness of Multi-Resolution Remotely Sensed Data for Cadastral Mapping in Ekiti State, Nigeria by Israel Oluwaseun Taiwo, Matthew Olomolatan Ibitoye, Sunday Olukayode Oladejo, Mila Koeva

“…Using the 0.05 m orthomosaic as a reference, the Horizontal Radial Root Mean Square Error (RMSEr) and Normalized Parcel Area Error (NPAE) were computed. …”
Get full text

Lessons learned from the co-development of operational climate forecast services for vineyards management by N. Pérez-Zanón, V. Agudetse, E. Baulenas, P.A. Bretonnière, C. Delgado-Torres, N. González-Reviriego, A. Manrique-Suñén, A. Nicodemou, M. Olid, Ll. Palma, M. Terrado, B. Basile, F. Carteni, A. Dente, C. Ezquerra, F. Oldani, M. Otero, F. Santos-Alves, M. Torres, J. Valente, A. Soret

“…Because end-users need to navigate, comprehend, and select from various alternative options amidst uncertainty, significant emphasis has been placed on crafting the visual representation of the climate service, incorporating interactive elements, and cognitive considerations, thereby enhancing the overall user experience. Practical implications: Weather and climate conditions affect the development of cultivars: phenological stages, disease risk, or wine quality. …”
Get full text

Machine Learning-Based Image Pattern Recognition Using Histogram of Oriented Gradient for Islanding Detection by Kumaresh Pal, Kumari Namrata, Ashok Kumar Akella, Manoj Gupta, Pannee Suanpang, Aziz Nanthaamornphong

“…The failure to identify unintentional islanding results in significant implications for both the power system and human lives. …”
Get full text

Energy Efficiency in Smart Buildings through Prediction modeling and Optimization Using a Modified Whale Optimization Algorithm by El Assri Nasima, Ennejjar Mohammed, Jallal Mohammed Ali, Chabaa Samira, Zeroual Abdelouhab

“…In the case of ANN, the Root Mean Squared Error (RMSE) is reported at 3.806, demonstrating the model's ability to approximate the true energy consumption values. …”
Get full text

Developing an Innovative Seq2Seq Model to Predict the Remaining Useful Life of Low-Charged Battery Performance Using High-Speed Degradation Data by Yong Seok Bae, Sungwon Lee, Janghyuk Moon

“…The Seq2Seq model demonstrated superior performance with low error and high curve-fitting accuracy for 1C and 1.2C untrained data. …”
Get full text

Designing everyday essentials: a guide for user-friendly accessibility using Quality Function Deployment by Wichapol Chanchiewvichai, Suchada Rianmora, Nanthicha Patmayothin

“…The contributions of this research benefit designers (manufacturers), customers, and researchers. The implications of this research include minimizing time spent on trial-and-error in the design stage, optimizing and reducing waste from the prototyping process. …”
Get full text

Description of a Current Outbreak of <i>Mycoplasma pneumoniae</i> in the United States by Anupama Raghuram, Stephen Furmanek, Thomas Chandler, Salwa Rashid, William Mattingly, Julio Ramirez

“…A c-chart was created by calculating the mean and standard error (SE) of cases during the pre-COVID-19 pandemic period, with the upper control limit (UCL) set at 3 SE above the mean. …”
Get full text

Pyridoxal phosphate binding protein (PLPBP) deficiency mimicking opsoclonus‐myoclonus‐ataxia syndrome by Mrinmayee Takle, Dhwani Sahjwani, Diana Bharucha‐Goebel, Tyler Rapp, Cecilia Bouska, Alexandra Kornbluh, Kuntal Sen

“…This report also highlights the clinical overlap between PLPBP deficiency and OMAS, and the differences in pathophysiology, treatment pathways, and implications.…”
Get full text

Unravelling the Link Between Financialisation and Economic Growth: Evidence from Croatia by Agim Mamuti, Fatbardha Kadiu, Idaver Sherifi, Inna Romānova, Simon Grima

“…While the study is limited to the Croatian context and the specified period, its findings have significant implications for policymakers in Croatia and similar emerging markets. …”
Get full text

Reward-optimizing learning using stochastic release plasticity by Yuhao Sun, Yuhao Sun, Wantong Liao, Wantong Liao, Jinhao Li, Jinhao Li, Xinche Zhang, Xinche Zhang, Guan Wang, Guan Wang, Zhiyuan Ma, Zhiyuan Ma, Zhiyuan Ma, Sen Song, Sen Song

“…However, a question remains: how can plasticity rules achieve robustness and effectiveness comparable to error backpropagation? In this study, we introduce Reward-Optimized Stochastic Release Plasticity (RSRP), a learning framework where synaptic release is modeled as a parameterized distribution. …”
Get full text