Suchergebnisse - an integrated environment for developing and learning Python IDLE

USING THE PYTHON IDLE DEVELOPMENT AND TRAINING ENVIRONMENT FOR STUDENTS TO LEARN PROBABILITYY

Quelle: Вестник МГПУ. Серия Информатика и информатизация образования.

Schlagwörter: методика обучения математике, methodology of teaching mathematics, интегрированная среда для разработки и обучения Python IDLE, interdisciplinary connections between mathematics and informatics, an integrated environment for developing and learning Python IDLE, междисциплинарные связи математики и информатики

The Impact of Digital Learning Competence on the Academic Achievement of Undergraduate Students.

Autoren: Song, Yafeng Lv, Shuqi Wang, Meng et al.

Quelle: Behavioral Sciences (2076-328X); Jul2025, Vol. 15 Issue 7, p840, 25p

Using Ensemble Machine Learning and Feature Engineering to Increase the Accuracy of Predicting Learners' Performance in an Online Educational Environment.

Autoren: Noorani, Seyede Fatemeh Karimi, Maryam Gholijafari, Zahra

Quelle: Interdisciplinary Journal of Virtual Learning in Medical Sciences; Dec2024, Vol. 15 Issue 4, p369-387, 19p

AI-Enabled Membrane Bioreactors: A Review of Control Architectures and Operating-Parameter Optimization for Nitrogen and Phosphorus Removal.

Autoren: Xu, Mingze Liu, Di

Quelle: Water (20734441); Oct2025, Vol. 17 Issue 19, p2899, 29p

Schlagwörter: NITROGEN removal (Sewage purification), PHOSPHATE removal (Sewage purification), BIOLOGICAL nutrient removal, BIOREACTORS, REGULATORY compliance, WASTEWATER treatment, ARTIFICIAL intelligence, FEEDBACK control systems

Iot Based Healing Process For Diabetic Foot Ulcer.

Autoren: S., Keerthana C., Gokulraj N., Sivaram et al.

Quelle: Journal of Advanced Zoology. 2024, Vol. 45 Issue 4, p227-233. 7p.

CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and Forecasting.

Autoren: Koumar, Josef Hynek, Karel Čejka, Tomáš et al.

Quelle: Scientific Data; 2/26/2025, Vol. 12 Issue 1, p1-12, 12p

Schlagwörter: COMPUTER network security, COMPUTER network traffic, ANOMALY detection (Computer security), DETECTION algorithms, ARTIFICIAL intelligence, INTRUSION detection systems (Computer security)

Hybrid approach for suspicious object surveillance using video clips and UAV images in cloud-IoT-based computing environment.

Autoren: Ahamad, Rayees Mishra, Kamta Nath

Quelle: Cluster Computing; Feb2024, Vol. 27 Issue 1, p761-785, 25p

Schlagwörter: VIDEO surveillance, VIDEO excerpts, HYBRID systems, HUMAN facial recognition software, IDENTIFICATION photographs, ERROR rates, AUTOMATED teller machines

Multi-agent deep reinforcement learning for integrated production and maintenance optimisation in shared manufacturing.

Autoren: Peng, Xiaoshuai Wang, Shiyi Wang, Kangzhou

Quelle: International Journal of Production Research; Dec2025, Vol. 63 Issue 23, p8761-8780, 20p

A scalable Deep Q-Learning approach for hot stamping process under dynamic control environment.

Autoren: Nievas, Nuria Pagès-Bernaus, Adela Abio, Albert et al.

Quelle: International Journal of Production Research; Apr2025, Vol. 63 Issue 8, p2831-2852, 22p

Schlagwörter: DEEP reinforcement learning, REINFORCEMENT learning, FOIL stamping, ARTIFICIAL intelligence, MANUFACTURING processes

Dynamic scheduling for flexible job-shop with reconfigurable manufacturing cells considering dynamic job arrivals based on deep reinforcement learning.

Autoren: Zheng, Liang Chen, Xiaodi Zhuang, Cunbo et al.

Quelle: International Journal of Production Research; Oct2025, Vol. 63 Issue 20, p7427-7459, 33p

Schlagwörter: SCHEDULING, REINFORCEMENT learning, MANUFACTURING cells

Strategy for maximizing space utilization in smart libraries based on reinforcement learning.

Autoren: Dai, Ying

Quelle: Scientific Reports; 11/12/2025, Vol. 15 Issue 1, p1-22, 22p

Schlagwörter: REINFORCEMENT learning, RESOURCE allocation, SATISFACTION, INTERNET of things, SPECIAL libraries

Real-Time and Fully Automated Robotic Stacking System with Deep Learning-Based Visual Perception.

Autoren: Ozer, Ali Sait Cinar, Ilkay

Quelle: Sensors (14248220); Nov2025, Vol. 25 Issue 22, p6960, 38p

Schlagwörter: DEEP learning, COMPUTER vision, REAL-time computing, AUTOMATION, OBJECT recognition (Computer vision), MACHINE-to-machine communications, ROBOTICS

Firma/Körperschaft: ABB Ltd.

The impact of virtual reality environments on English language acquisition: Innovative immersive learning technologies for communication skills development.

Autoren: Lou, Yaping

Quelle: Journal of Computational Methods in Sciences & Engineering; Sep2025, Vol. 25 Issue 5, p4616-4632, 17p

Schlagwörter: LINGUISTIC complexity, LANGUAGE acquisition, TRANSFORMATIVE learning, INTERACTIVE learning, COMMUNICATION patterns

A Real-Time Intelligent Acoustic IoT-Enabled Embedded Construction Site Monitoring and Alert System: Integrating Deep Learning–Based Machine-Listening Algorithms, Edge Computing, and Cloud Computing.

Autoren: Poudel, Oscar Assaad, Rayan H.

Quelle: Journal of Construction Engineering & Management; Jul2025, Vol. 151 Issue 7, p1-18, 18p

Schlagwörter: BUILDING sites, MACHINE learning, RECURRENT neural networks, CONSTRUCTION industry safety, EVIDENCE gaps, DEEP learning, EDGE computing

Resource-Constrained and Time-Aware Reinforcement Learning Framework for Sustainable Fertilization Strategies.

Autoren: Alkaff, Muhammad Basuhail, Abdullah Sari, Yuslena et al.

Quelle: Journal of Advanced Computational Intelligence & Intelligent Informatics; Nov2025, Vol. 29 Issue 6, p1342-1357, 16p

Schlagwörter: SUSTAINABLE agriculture, NITROGEN, AGRICULTURAL productivity, SOIL quality, PRECISION farming, RESOURCE management, MATHEMATICAL optimization, REINFORCEMENT learning

An LSTM-Enhanced Deep Q-Learning Framework for Decentralized Cooperative Spectrum Sensing in Dynamic Cognitive Radio Networks.

Autoren: Krishnamurthy, Archana Sudhindra, Kumbhashi Rajgopal

Quelle: International Journal of Intelligent Engineering & Systems; 2025, Vol. 18 Issue 10, p827-843, 17p

Schlagwörter: COGNITIVE radio, REINFORCEMENT learning, DECENTRALIZED control systems, COOPERATIVENESS, SPECTRUM allocation, LONG short-term memory, DYNAMICAL systems

A Survey on Services Placement Algorithms in Integrated Cloud-Fog / Edge Computing.

Autoren: Taleb, Imane Guillaume, Jean-Loup Duthil, Benjamin

Quelle: ACM Computing Surveys; Nov2025, Vol. 57 Issue 11, p1-36, 36p

Schlagwörter: INFORMATION technology, METAHEURISTIC algorithms, SCIENCE conferences, ARTIFICIAL neural networks, ANT algorithms, DEEP learning, VIRTUAL networks

Energy-aware self-adaptive real-time job scheduling in a cloud environment using deep reinforcement learning focused on quality of service.

Autoren: Azari, Hossein Zehtab Jalili, Saeed

Quelle: Cluster Computing; Oct2025, Vol. 28 Issue 6, p1-30, 30p

Schlagwörter: DEEP reinforcement learning, REINFORCEMENT learning, COMMUNICATION infrastructure, QUALITY of service, UNEMPLOYMENT

Heuristic-assisted deep learning for integrated scheduling of multiple equipment in automated container terminals.

Autoren: Roi, Ho Van You, Sam-Sang Kim, Hwan-Seong et al.

Quelle: Maritime Economics & Logistics; Dec2025, Vol. 27 Issue 4, p786-818, 33p

Application of Artificial Intelligence in Glacier Studies: A State-of-the-Art Review.

Autoren: Nurakynov, Serik Merekeyev, Aibek Baygurin, Zhaksybek et al.

Quelle: Water (20734441); Aug2024, Vol. 16 Issue 16, p2272, 39p

Schlagwörter: MACHINE learning, ENVIRONMENTAL protection, SUPERVISED learning, ARTIFICIAL intelligence, WATER supply, DEEP learning