Establishment Method of Knowledge Graphs for Public Security Cases
With the continuous improvement of the informatization level of the police, how to make accurate intelligence analysis based on the modeling of massive multimodal data has always been a real intricate problem during the applications of public ...
Improved Sliding Mode Output Control of Mine Filling Slurry Concentration Based on Proportional-Integral Observer
The accuracy of slurry concentration is an important guarantee for the quality of mine filling, and enhancing the robustness of the control system is an effective way to improve the accuracy. Based on sliding mode control, this study proposes a ...
Evaluation of Optimized Inner and Outer Loop Controllers for 4X Flyer under Faulty Actuators
- Nasri Boualem,
- Guessoum Abderrezak,
- Mostefai Lotfi,
- Bensikaddour El habib,
- Hamdadou Nabil,
- Ghoul Abdelhamid,
- Adnane Akram
Metaheuristic optimization techniques are a powerful tool to decide the optimal gains for underactuated systems such as quadrotors, considering the multiple controllers involved in the inner and outer loops of the system. This paper deals with the ...
Flexible Nodes Exclusion and Inclusion Capability Migration Model for Hybrid Software-Defined Network
Software-defined networking (SDN) is a popular network technology that enables flexible programmed network setup for optimizing network performance. However, the high cost of migrating existing devices to SDN leads to slow deployment particularly ...
Classification of Services through Feature Selection and Machine Learning in 5G Networks
Network slicing (Ns) is a key enabling technology to support the concurrent provisioning of better quality of service (QoS) in 5G networks. These services have become essential for a telecom service provider (SP) to offer better QoS and QoE (...
Air Pollutants Classification Using Optimized Neural Network Based on War Strategy Optimization Algorithm
Air quality prediction is considered one of complex problems. This is due to volatility, dynamic nature, and high variability in space and time of particulates and pollutants. Meanwhile, designing an automated model for monitoring and predicting ...
QAM Modulation Based on Lowest Energy Consumption in Passive CRFID
Energy consumption and lacking of spectrum resources have become the bottleneck in the development of the Internet of Things. Reducing energy consumption in RFID tags is an important issue that needs to be studied in the communication links. The ...
Radio-Frequency Energy Harvesting Technology for Future Communication Systems
The research of the sixth generation (6G) cellular network aims at much higher spectral efficiency (SE) and energy efficiency (EE) and would lead to both architectural and component design changes. Over the last decade, simultaneous wireless ...
Color Models Aware Dynamic Feature Extraction for Forest Fire Detection Using Machine Learning Classifiers
The earth’s ecology is well balanced and protected by forests. On the other hand, forest fires affect forest resources, thus causing both economical and ecological losses. Hence, preserving forest resources from fires is very essential to reduce ...
Study of an Automatic Marking Algorithm for Subjective Questions in College English Exams Based on Deep Learning
Computer-assisted marking can reduce the work pressure on teachers. This paper briefly introduced the automatic English subjective question marking algorithm combined with the convolutional neural network + long short-term memory (CLSTM) ...
BC-Net: Early Diagnostics of Breast Cancer Using Nested Ensemble Technique of Machine Learning
Breast cancer is a divergent and prominent cancer that is responsible for the morbidity and mortality of women throughout the world. This paper aims at early detection and accurate diagnosis of this fatal disease, which is one of the most ...