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Paulo Vitor de Campos Souza, Augusto Junio Guimarães, Thiago Silva Rezende, Vinicius Jonathan Silva Araujo and Vanessa Souza Araujo
The fuzzy neural networks are hybrid structures that can act in several contexts of the pattern classification, including the detection of failures and anomalous behaviors. This paper discusses the use of an artificial intelligence model based on the ass...
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Sachin Gowda, Vaishakh Kunjar, Aakash Gupta, Govindaswamy Kavitha, Bishnu Kant Shukla and Parveen Sihag
In the realm of urban geotechnical infrastructure development, accurate estimation of the California Bearing Ratio (CBR), a key indicator of the strength of unbound granular material and subgrade soil, is paramount for pavement design. Traditional labora...
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Maryam Alzaid and Fethi Fkih
It is crucial to analyze opinions about the significant shift in education systems around the world, because of the widespread use of e-learning, to gain insight into the state of education today. A particular focus should be placed on the feedback from ...
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Imane Zaimi, Abdelali Boushaba, Mohammed Oumsis, Brahim Jabir, Moulay Hafid Aabidi and Adil EL Makrani
Reducing transmission traffic delay is one of the most important issues that need to be considered for routing protocols, especially in the case of multimedia applications over vehicular ad hoc networks (VANET). To this end, we propose an extension of th...
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Muhsen Alkhalidy, Atalla Fahed Al-Serhan, Ayoub Alsarhan and Bashar Igried
Vehicular ad hoc networks have played a key role in intelligent transportation systems that considerably improve road safety and management. This new technology allows vehicles to communicate and share road information. However, malicious users may injec...
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Ioannis Kosmopoulos, Emmanouil Skondras, Angelos Michalas, Emmanouel T. Michailidis and Dimitrios D. Vergados
Fifth-Generation (5G) vehicular networks support novel services with increased Quality of Service (QoS) requirements. Vehicular users need to be continuously connected to networks that fulfil the constraints of their services. Thus, the implementation of...
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Mohammed Madiafi, Jamal Ezzahar, Kamal Baraka and Abdelaziz Bouroumi
In this paper, we propose a new neural architecture for object classification, made up from a set of competitive layers whose number and size are dynamically learned from training data using a two-step process that combines unsupervised and supervised le...
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Cheng-Jian Lin, Min-Su Huang and Chin-Ling Lee
The applications of computer networks are increasingly extensive, and networks can be remotely controlled and monitored. Cyber hackers can exploit vulnerabilities and steal crucial data or conduct remote surveillance through malicious programs. The frequ...
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Hind R. Mohammed and Zahir M. Hussain
Accurate, fast, and automatic detection and classification of animal images is challenging, but it is much needed for many real-life applications. This paper presents a hybrid model of Mamdani Type-2 fuzzy rules and convolutional neural networks (CNNs) a...
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Deepaa Selva, Balakrishnan Nagaraj, Danil Pelusi, Rajendran Arunkumar and Ajay Nair
Rapid Internet use growth and applications of diverse military have managed researchers to develop smart systems to help applications and users achieve the facilities through the provision of required service quality in networks. Any smart technologies o...
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Mona Abouhamad and Tarek Zayed
The 2019 Canadian Infrastructure report card identified 60% of the subway system to be in a very poor to a poor condition. With multiple assets competing for the limited fund, new methodologies are required to prioritize assets for rehabilitation. The re...
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Ann Nosseir,Yahia Fathy
Pág. pp. 4 - 18
Identifying students at risk or potentials excellent students is increasingly important for higher education institutions to meet the needs of the students and develop efficient learning strategy. Early stage prediction can give an indication of the stud...
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Johanna Guth, Sven Wursthorn and Sina Keller
Average speed is crucial for calculating link travel time to find the fastest path in a road network. However, readily available data sources like OpenStreetMap (OSM) often lack information about the average speed of a road. However, OSM contains other r...
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Jae Hyuk Cho and Hayoun Lee
Low-Energy Adaptive Clustering Hierarchy (LEACH) is a typical routing protocol that effectively reduces transmission energy consumption by forming a hierarchical structure between nodes. LEACH on Wireless Sensor Network (WSN) has been widely studied in t...
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Chidentree Treesatayapun
Robotic systems equipped with a task-multiplexer unit are considered as a class of unknown non-linear discrete-time systems, where the input is a command voltage of the driver unit and the output is the feedback signal obtained by the multiplexer unit. W...
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Shengping Lv, Rongheng Xian, Denghui Li, Binbin Zheng and Hong Jin
The application of the work is to optimize the material feeding of a printed circuit board (PCB) template and therefore reduce the comprehensive cost caused by surplus and supplemental feeding.
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Xiaojie Cui, Jiayao Wang, Fang Wu, Jinghan Li, Xianyong Gong, Yao Zhao and Ruoxin Zhu
The spatial pattern is a kind of typical structural knowledge that reflects the distribution characteristics of object groups. As an important semantic pattern of road networks, the city center is significant to urban analysis, cartographic generalizatio...
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Konstantinos I. Papageorgiou, Katarzyna Poczeta, Elpiniki Papageorgiou, Vassilis C. Gerogiannis and George Stamoulis
This paper introduced a new ensemble learning approach, based on evolutionary fuzzy cognitive maps (FCMs), artificial neural networks (ANNs), and their hybrid structure (FCM-ANN), for time series prediction. The main aim of time series forecasting is to ...
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Mohammad Hemmat Esfe
Pág. 202 - 208
In this article, thermal conductivity data of aqueous nanofluids of CuO have been modeled through one of the instruments of empirical data modeling. The input data of 5 different volume fractions of nanofluid obtained in four temperatures through experim...
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Pág. 42 - 49
The subject matter of the study is data clustering based on the ensemble of neural networks. The goal of the work is to create a new approach to solving the tasks of clustering in data streams when information is fed observation-by-observation in online ...
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