intelligent models
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2022 ◽  
pp. 971-986
Author(s):  
Pardeep Kumar Sharma ◽  
Cherry Bhargava

Electronic systems have become an integral part of our daily lives. From toy to radar, system is dependent on electronics. The health conditions of humidity sensor need to be monitored regularly. Temperature can be taken as a quality parameter for electronics systems, which work under variable conditions. Using various environmental testing techniques, the performance of DHT11 has been analysed. The failure of humidity sensor has been detected using accelerated life testing, and an expert system is modelled using various artificial intelligence techniques (i.e., Artificial Neural Network, Fuzzy Inference System, and Adaptive Neuro-Fuzzy Inference System). A comparison has been made between the response of actual and prediction techniques, which enable us to choose the best technique on the basis of minimum error and maximum accuracy. ANFIS is proven to be the best technique with minimum error for developing intelligent models.


2021 ◽  
Vol 12 (5-2021) ◽  
pp. 171-176
Author(s):  
Boris A. Kulik ◽  
◽  
Alexander Ya. Fridman ◽  

A paradox is understood as reasoning (knowledge base), from which follows the incompatibility of properties for some objects participating in it. Some methods to analyze and eliminate such paradoxes in intelligent systems based on E-structures and n-tuple algebra are considered and illustrated by examples.


Author(s):  
Sanaa Elyassami ◽  
Sultan Albloushi ◽  
Mohamed Ammar Alnuaimi ◽  
Omran Alhosani ◽  
Hassan Al Ali ◽  
...  

Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2666
Author(s):  
Ahmad Alzu’bi ◽  
Firas Albalas ◽  
Tawfik AL-Hadhrami ◽  
Lojin Bani Bani Younis ◽  
Amjad Bashayreh

A large number of intelligent models for masked face recognition (MFR) has been recently presented and applied in various fields, such as masked face tracking for people safety or secure authentication. Exceptional hazards such as pandemics and frauds have noticeably accelerated the abundance of relevant algorithm creation and sharing, which has introduced new challenges. Therefore, recognizing and authenticating people wearing masks will be a long-established research area, and more efficient methods are needed for real-time MFR. Machine learning has made progress in MFR and has significantly facilitated the intelligent process of detecting and authenticating persons with occluded faces. This survey organizes and reviews the recent works developed for MFR based on deep learning techniques, providing insights and thorough discussion on the development pipeline of MFR systems. State-of-the-art techniques are introduced according to the characteristics of deep network architectures and deep feature extraction strategies. The common benchmarking datasets and evaluation metrics used in the field of MFR are also discussed. Many challenges and promising research directions are highlighted. This comprehensive study considers a wide variety of recent approaches and achievements, aiming to shape a global view of the field of MFR.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
M. A. Moradkhani ◽  
Seyyed Hossein Hosseini ◽  
M. Mansouri ◽  
G. Ahmadi ◽  
Mengjie Song

AbstractThere is a lack of well-verified models in the literature for the prediction of the frictional pressure drop (FPD) in the helically coiled tubes at different conditions/orientations. In this study, the robust and universal models for estimating two-phase FPD in smooth coiled tubes with different orientations were developed using several intelligent approaches. For this reason, a databank comprising 1267 experimental data samples was collected from 12 independent studies, which covers a broad range of fluids, tube diameters, coil diameters, coil axis inclinations, mass fluxes, saturation temperatures, and vapor qualities. The earlier models for straight and coiled tubes were examined using the collected database, which showed absolute average relative error (AARE) higher than 21%. The most relevant dimensionless groups were used as models’ inputs, and the neural network approach of multilayer perceptron and radial basis functions (RBF) were developed based on the homogenous equilibrium method. Although both intelligent models exhibited excellent accuracy, the RBF model predicted the best results with AARE 4.73% for the testing process. In addition, an explicit FPD model was developed by the genetic programming (GP), which showed the AARE of 14.97% for all data points. Capabilities of the proposed models under different conditions were described and, the sensitivity analyses were performed.


2021 ◽  
Vol 01 (01) ◽  
pp. 04-06
Author(s):  
Chapa Sirithunga ◽  
◽  
Buddhika Jayasekara ◽  

This research explores how a robot should gather knowledge upon a scenario between a robot and its user and then generate appropriate intelligent responses towards its user. Therefore, cognitive models were developed to act as a robot’s intelligence or the brain to make situation-specific decisions. Such insightful decisions will help the robot act in a social environment without disturbing its user or other humans around.


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