Kongzhi yu Juece/Control and Decision (ISSN:1001-0920) is a monthly peer-reviewed scopus indexed journal originally founded in 1986. It is sponsored by the Ministry of Education, china and Northeastern University, china. Kongzhi yu Juece/Control and Decision (ISSN:1001-0920) has always adhered to the correct purpose of running the journal, and has been committed to gathering and disseminating excellent academic achievements, inspiring technological innovation, and promoting the development of disciplines in my country.Aiming at major national needs and international frontiers, this journal has published a large number of original and high-level research result. The journal was selected into the "China Science and Technology Journal Excellence Action Plan Project" in December 2019.In the future, it will strive to build an open innovation, collaborative integration.
This study numerically investigates the effect of an aluminum (AA6063) heat sink on the thermal and electrical performance of a solar photovoltaic (PV) panel using a finite-volume-based software. Heat sinks with 2, 4, and 23-finned configurations were analyzed under natural convection and validated against experimental data. Results show strong agreement between simulation and experiment. Increasing the number of fins significantly reduced surface temperature and improved power output. The 23-fin (F23) configuration achieved the best performance, lowering temperature and increasing peak power
The article presents the development of an intelligent wearable system for continuous monitoring of physiological parameters and early detection of stress conditions using modern microcontrollers and machine learning algorithms. The system implements a multisensor approach that includes the registration of electrodermal activity (EDA), heart rate (HR), body temperature, and accelerometer data. For automatic stress level classification, several machine learning models were compared using the main metrics (accuracy, precision, recall, F1-score). The best accuracy was achieved using the Random Fo
Mathematics in Indonesian secondary schools is often taught as a set of procedures, leaving little room for understanding or creativity. This study explores how integrating STEAM pedagogy with the Next Generation Science Standards (NGSS) can bring mathematics to life as a core way of thinking rather than a mere tool. Using a systematic review of 85 studies and expert validation through a modified Delphi method, a framework was developed linking NGSS dimensions with algebraic learning. The findings reveal that while STEAM encourages engagement, mathematics is often sidelined. The proposed frame
Infant Mortality Rate (IMR) remains a vital indicator of a nation’s socioeconomic development and health system performance, particularly in developing countries such as Bangladesh. This study applies hybrid feature selection techniques to identify key environmental and demographic factors influencing IMR. Advanced machine learning models including Gradient Boosting, Random Forest, AdaBoost, K Nearest Neighbors (KNN) Regressor, Linear Regression, and XGBoost were used to forecast future IMR trends. Using data from 1970 to 2022 obtained from the World Development Indicators 2025 (WDI 2025), m
The article proposes a digital twin architecture for an Internet of Things (IoT) environment, focused on stable operation under increasing load and degradation of telemetry quality. The architecture includes a data collection loop from devices and gateways, a message broker with redelivery and loss/duplicate control functions, streaming event processing, a digital twin core, and services for diagnostics, visualization, and (optionally) control. To formalize reliability, an aggregated data quality metric Q∈[0,1] is introduced, taking into account completeness, outliers, drift, distribution sk