Sparse Planar Array Synthesis Using Matrix Enhancement and Matrix Pencil by Mei-yan Zheng, Ke-song Chen, Hong-gang Wu, Xian-pan Liu

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Cutaneous Manifestation Maple Syrup Urine Disease: Case Report by Gabriel Alejandro Díaz Bernal, Mányeles Brito Vázquez, Magdalena de la Caridad Guirado Espinosa

“…Maple syrup urine disease or leucinosis is caused by an inborn error in the metabolism of three essential branched chain amino acids. …”
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Agenet: Age of Information evaluation in wireless networks by Chathuranga M. Wijerathna Basnayaka, Nuno Fachada

“…The package offers tools to calculate signal-to-noise ratio, block error rate, and both theoretical and simulated AoI. …”
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China–Pakistan Economic Corridor, Logistics Developments and Economic Growth in Pakistan by Zunaira Khadim, Irem Batool, Muhammad Bilal Lodhi

“…The study defined a Cobb–Douglas type of research framework in which the country’s real income level relates to four factor inputs, e.g., employed labor force, logistics development, financial development, and energy consumption in an economy. …”
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Autonomous Navigation onto Autodocking Drone System using Computer Vision by LISA KRISTIANA, KEINDRA BAGAS MAULANA, SHAFIRA KURNIA FASYA, MUHAMMAD ZUFAR DAFY, MUKTIADI AKHMAD JANUAR

“…The abstract contains a summary of backgrounds, methods, and research results, with the maximum number of characters being 150.…”
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ANALYZING UNCONTROLLABLE FACTORS THAT CAUSE DEFECTIVE PRODUCTS BY POISSON AND NEGATIVE BINOMIAL INAR(1) FOR FITTING MODEL by Herry Kartika Gandhi, Ispány Márton

“…The use of the appropriate model is determined by using overdispersion analysis of the Poisson value and Index of Dispersion (ID). This research is based on data of break occurrences in 3 paper machines. …”
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The Dollar and Gold: Which is the Safest Haven? COVID-19 Evidence by Bousbia Salah Rahima, Beggat Hanane, Debbar Abdelkerim

“…This paper examines the dynamic correlation between the US dollar and gold prices during the coronavirus pandemic to determine which of the two assets is a safer haven from an investor’s perspective. The research utilises methods of analysis and synthesis of theoretical knowledge from published articles, literature, and official statistics websites. …”
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Artificial Neural Network Algorithm for Condition Monitoring of DC-link Capacitors Based on Capacitance Estimation by Hammam Abdelaal Hammam Soliman, Huai Wang, Brwene Salah Abdelkarim Gadalla, Frede Blaabjerg

“…The implemented ANN estimated the capacitance of the DC-link capacitor in a back-toback converter. Analysis of the error of the capacitance estimation is also given. …”
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A Mobile LiDAR-Based Deep Learning Approach for Real-Time 3D Body Measurement by Yongho Jeong, Taeuk Noh, Yonghak Lee, Seonjae Lee, Kwangil Choi, Sujin Jeong, Sunghwan Kim

“…Traditional body measurement methods mainly rely on 2D images or manual measurements. This research, however, utilizes 3D depth information to enhance both accuracy and efficiency. …”
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Occupant-Aware Energy Consumption Prediction in Smart Buildings Using a LSTM Model and Time Series Data by Muhammad Anan, Khalid Kanaan, Driss Benhaddou, Nidal Nasser, Basheer Qolomany, Hanaa Talei, Ahmad Sawalmeh

“…The model’s performance is evaluated using the following three metrics: Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE). …”
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Intercept-Resend Attack on SARG04 Protocol: An Extended Work by Ali H. Yousif, Omar S. Mustafa, Dana F. Abdulqadir, Farah S. Khoshaba

“…In 2019, simulation and enhancement of the performance of SARG04 protocol have been done by the same research group in terms of error correction stage using multiparity rather than single parity (Omar, 2019). …”
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An Analytical Approximate Solution for the Quasi-Steady State Michaelis-Menten Problem by U. Filobello-Nino, H. Vazquez-Leal, R. Castaneda-Sheissa, V. M. Jimenez-Fernandez, A. L. Herrera-May, J. Huerta-Chua, L. Gil-Adalid, J. E. Pretelin-Canela

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Enhancing the interpretability of electricity consumption forecasting models for mining enterprises using SHapley Additive exPlanations by Pavel V. Matrenin, Alina I. Stepanova

“…The mean absolute percentage error was 7.84 % with consideration of meteorological factors, 7.41 % with consideration of meteorological factors and a load plan formulated by an expert, and the expert's forecast error was 9.85 %. …”
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Machine learning‐based investigations of the effect of surface texture geometry on the wear behaviour of UHMWPE bearings in hip joint implants by Vipin Kumar, Ravi Prakash Tewari, Anubhav Rawat

“…With a performance evaluation of 0.06 mean absolute error (MAE), 0.17 Root Mean Square Error (RMSE), and 0.96 R2, the Random Forest Regression is found to be the best model. …”
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Practices and Considerations in Wind Data Processing for Accurate and Efficient Wind Farm Energy Calculation by Angel Gaspar Gonzalez-Rodriguez, Jose Manuel Riega-Medina, Ildefonso Ruano-Ruano, Jose Vicente Muñoz-Diez

“…This estimation should be based on historical wind data collected over several years at the site location. However, research articles often rely on data grouped into 12 sectors. …”
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SP-RF-ARIMA: A sparse random forest and ARIMA hybrid model for electric load forecasting by Kamran Hassanpouri Baesmat, Farhad Shokoohi, Zeinab Farrokhi

“…This methodology, termed SP-RF-ARIMA, is evaluated against existing approaches; it demonstrates more than 40% reduction in mean absolute error and root mean square error compared to the second-best method.…”
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Water scarcity in Hebei Province, China: A predictive model and analysis of contributing factors by Wanliang Qian, Shun Wu, Min Fang, Xiaoyan Qian

“…The model demonstrates high predictive accuracy, with Mean Absolute Percentage Error (MAPE) and Mean Squared Percentage Error (MSPE) below 5 %, validating its reliability. …”
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Ray-Tracing method for fields of view simulation in agricultural and forestry vehicles by Lorenzo Landi, Luca Burattini, Maurizio Cutini, Leonardo Vita, Luca Landi

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A machine learning-based framework for predicting metabolic syndrome using serum liver function tests and high-sensitivity C-reactive protein by Bahareh Behkamal, Fatemeh Asgharian Rezae, Amin Mansoori, Rana Kolahi Ahari, Sobhan Mahmoudi Shamsabad, Mohammad Reza Esmaeilian, Gordon Ferns, Mohammad Reza Saberi, Habibollah Esmaily, Majid Ghayour-Mobarhan

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A multi-level, multi-scale comparison of LiDAR- and LANDSAT-based habitat selection models of Mexican spotted owls in a post-fire landscape by Ho Yi Wan, Michael A. Lommler, Samuel A. Cushman, Jamie S. Sanderlin, Joseph L. Ganey, Andrew J. Sánchez Meador, Paul Beier

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