Spatiotemporal Dynamics of Drought in the Huai River Basin (2012–2018): Analyzing Patterns Through Hydrological Simulation and Geospatial Methods by Yuanhong You, Yuhao Zhang, Yanyu Lu, Ying Hao, Zhiguang Tang, Haiyan Hou

“…Our results demonstrate that the model showed a correlation coefficient of 0.74, a bias of −0.29, and a root mean square error of 2.66% when compared with reanalysis data in the 0–10 cm soil layer. …”
Get full text

IoT‐Based Elderly Health Monitoring System Using Firebase Cloud Computing by Adhan Efendi, Muhammad Imam Ammarullah, Indra Griha Tofik Isa, Meli Puspita Sari, Jasmine Nurul Izza, Yohanes Sinung Nugroho, Hamid Nasrullah, Denny Alfian

“…Device validation is conducted by involving six participants to measure the real‐time data of heart‐rate, oxygen saturation, and body temperature, then analysed by mean average percentage error (MAPE) to define error rate. …”
Get full text

Deep Learning-Based Rapid Flow Field Reconstruction Model with Limited Monitoring Point Information by Ping Wang, Guangzhong Hu, Wenli Hu, Xiangdong Xue, Jing Tao, Huabin Wen

“…Using POD, the order of the tested temperature field was reduced by 99.75%, and the order of the velocity field was reduced by 99.13%, effectively decreasing the dimensionality of the flow field. Our analysis revealed that the first modal coefficient of the temperature field snapshot data, after modal decomposition, had a higher energy proportion compared to that of the velocity field snapshot data, along with a more pronounced marginal effect. …”
Get full text

Pemodelan Sistem Monitoring Kualitas Udara Pintar Berbasis Internet of Things dengan Pendekatan Machine Learning by Eddy Prasetyo Nugroho, Ani Anisyah, Deva Shofa Al Fathin, Muhammad Nur Yasin Amadudin, Muhammad Satria Ramadhani, Yosafat

“…The system is designed by utilising the Long Short-Term Memory (LSTM) algorithm to predict daily air quality based on historical data. The focus of the research includes the design of the system architecture, data model, and prediction method, which were developed based on previous architecture analysis and literature review. …”
Get full text

Analisis Tren dan Perkiraan Pandemi COVID-19 di Indonesia Menggunakan Peramalan Metode Prophet :Sebelum dan Sesudah Aturan New Normal by Mawaddah Harahap, Ahmad Zaki Andika, Amir Mahmud Husein, Abdi Dharma

“…The Prophet method is used to predict confirmed cases and deaths within the next 30 days. Visual data analysis using the Exploratory Data Analysis (EDA) approach is presented to provide an understanding of the development of the pandemic spread in Indonesia. …”
Get full text

The Impact of Snow Cover on River Discharge Simulation: Insights from the Barandozchay River Basin by Haleh Hashemi, Hossein Rezaie, Keivan Khalili, Amin Amini

“…This study presents a comprehensive analysis aimed at predicting the discharge of the Barandozchay River using machine learning algorithms and meteorological data from both satellite and ground sources over the period from 2002 to 2022. …”
Get full text

An Integrated UAV and Deep Learning Framework With HSB-Based Segmentation for Automated Slope Anomaly Detection in Mountainous Soil and Water Conservation Sites by Nai-Hsin Pan, Bo-Yuan Chang

“…By integrating UAVs for data acquisition and deep learning for automated analysis, the proposed system significantly reduces human labor costs, improves inspection efficiency, and provides a robust and reliable solution for anomaly detection and analysis. …”
Get full text

Integration of HAS with blockchain as halal sustainability in maqashid sharia perspective by Ariza Qanita, Nuril Laila Maghfuroh, Zaydan Muhammad

“…This study used a qualitative approach with the type of library research. The data analysis technique used is PESTELE analysis. …”
Get full text

MODEL SELECTION FOR B-SPLINE REGRESSION USING AKAIKE INFORMATION CRITERION (AIC) METHOD FOR IDR-USD EXCHANGE RATE PREDICTION by Indriani Wahyu Nur Pratiwi, Sri Utami Zuliana

“…Exchange rate data is a collection of information about the exchange rate the foreign currency which collected by time. …”
Get full text

A novel prediction model of grounding resistance based on long short-term memory by Xinghai Pu, Jing Zhang, Fei Wang, Shuai Xue

“…This study aims to investigate the use of Long Short-Term Memory (LSTM) models for predicting temporal variations in grounding resistance using time series data. This analysis is the first to apply LSTM models to grounding resistance prediction, utilizing experimental data, including soil resistivity and rainfall. …”
Get full text

Prediction of thermospheric temperature over the South Pole based on two-layer LSTM network by Hao Yang, Yanshi Huang, Pingbing Zuo, Kun Zhang, Mengqi Shao, Huan Shi

“…For the year 2011, the mean absolute error between the MSIS2.0 model and FPI data is 53.460 K, whereas the LSTM model reduces it to 34.024 K. …”
Get full text

CO2 emissions response to GDP and crude oil price shocks: Evidence from India and China using SVAR Model by Matali Mahajan, Dr. Ash Narayan Sah

“…This paper investigates the relationship between WTI prices, Inflation, CO2 emission, and GDP in India and China. Based on annual data spanning 1980–2019 for India and 1990–2019 for China, sourced from the “World Bank and Our World in Data” database, we investigate these interactions via a Structural Vector Autoregression framework, using impulse response functions and forecast error variance decomposition to map the effects. …”
Get full text

Wavelet Estimation of Partial Derivatives in Multivariate Regression Under Discrete-Time Stationary Ergodic Processes by Sultana Didi, Salim Bouzebda

“…This study introduces a wavelet-based framework for estimating derivatives of a general regression function within discrete-time, stationary ergodic processes. The analysis focuses on deriving the integrated mean squared error (IMSE) over compact subsets of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi mathvariant="double-struck">R</mi><mi>d</mi></msup></semantics></math></inline-formula>, while also establishing rates of uniform convergence and the asymptotic normality of the proposed estimators. …”
Get full text

The Role of Topological Parameters in Wavelength Requirements for Survivable Optical Backbone Networks by Filipe Carmo, João Pires

“…The results show that, across a set of 27 real-world networks, the wavelength increment factor, defined as the ratio between the number of wavelengths required with protection and without protection, ranges from 1.49 to 3.07, with a mean value of 2.26. Using synthetic data, formulas were derived to estimate this factor from network parameters, resulting in a mean relative error of 12.7% and errors below 15% in 70% of the real-world cases studied.…”
Get full text

Pengaruh Klientilisme terhadap Perilaku Pemilih Masyarakat Kecamatan Sukatani pada Pilkada Kabupaten Bekasi 2012 by Ainur Rofieq, Rahmat Nuryono

“…The method used is a quantitative study with a questionnaire as a data collector. Data analysis technique uses cross tabulation. …”
Get full text

New Class of Estimators for Finite Population Mean Under Stratified Double Phase Sampling with Simulation and Real-Life Application by Abdulaziz S. Alghamdi, Hleil Alrweili

“…The tendency to remove outliers from sample data is common. However, performing such removal can reduce the accuracy of conventional estimating techniques, particularly with regard to the mean square error (MSE). …”
Get full text

Abalone Muscle Texture Evaluation and Prediction Based on TPA Experiment by Jiaxu Dong, Xiaoyan Fang, Huihui Wang, Xu Zhang, Xueheng Tao

“…Specifically, a back propagation (BP) neural network was introduced to predict the equations of statistically significant sensory hardness, springiness, and smell using the texture data gained through TPA (texture profile analysis) experiments as input and sensory evaluation data as the desired output. …”
Get full text

Effectiveness of Jigsaw Type Learning Model on Mathematics Learning Outcomes by Anissatussa’diyah Anissatussa’diyah, Aan Widiyono

“…The results indicate that the use of the Jigsaw model significantly positively impacts students' learning outcomes. Data analysis using this method shows a mean value of -29.523, with a standard deviation of 9.47428 and a standard error mean of 2.06746. …”
Get full text

Work-based learning as a shift towards improved labour market skills in VET in Latvia by Biruta Sloka, Ilze Buligina

“…For the evaluation and comparison of all stakeholder’s opinions, the same questions were used with the same evaluation scale 1-10, where 1- not important; 10-very important. For data analysis of survey data the following indicators of descriptive statistics were used – indicators of central tendency or location: arithmetic mean, mode, median; indicators of dispersion or variability: range, standard deviation, standard error of mean. …”
Get full text

DETERMINANTS OF CAPITALIZATION AMONG RICE PROCESSING ENTERPRISE IN EBONYI STATE, NIGERIA by Doris Chidiebere ANOLIEFO, Chibuzor, N. NWACHUKWU, Nnanna, M. AGWU

“…Data analysis involved descriptive statistics such as frequency concept and ordinary least square model. …”
Get full text