Expert Systems With Applications
Papers 14001
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Last.Amir H. Gandomi (UTS: University of Technology, Sydney)H-Index: 50
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Abstract The web contains a huge volume of data, and it's populating every moment to the point that human beings cannot deal with the vast amount of data manually or via traditional tools. Hence an advanced tool is required to filter such massive data and mine the valuable information. Recommender systems are among the most excellent tools for such a purpose in which collaborative filtering is widely used. Collaborative filtering (CF) has been extensively utilized to offer personalized recommend...
#1Mohammad Shahverdy (IUST: Iran University of Science and Technology)
#2Mahmood Fathy (IUST: Iran University of Science and Technology)H-Index: 25
Last.Mohammad SabokrouH-Index: 10
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Abstract Driver behavior monitoring system as Intelligent Transportation Systems (ITS) have been widely exploited to reduce the traffic accidents risk. Most previous methods for monitoring the driver behavior are rely on computer vision techniques. Such methods suffer from violation of privacy and the possibility of spoofing. This paper presents a novel yet efficient deep learning method for analyzing the driver behavior. We have used the driving signals, including acceleration, gravity, throttl...
#1Partha Pratim Banik (Kookmin University)H-Index: 2
#2Rappy Saha (Kookmin University)H-Index: 2
Last.Ki-Doo Kim (Kookmin University)H-Index: 12
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Abstract White blood cells (WBCs) play a remarkable role in the human immune system. To diagnose blood-related diseases, pathologists need to consider the characteristics of WBC. The characteristics of WBC can be defined based on the morphological properties of WBC nucleus. Therefore, nucleus segmentation plays a vital role to classify the WBC image and it is an important part of the medical diagnosis system. In this study, color space conversion and k-means algorithm based new WBC nucleus segme...
Abstract In this study, we developed a novel scheme for the blind watermarking of color images. The proposed scheme incorporates extreme pixel adjustment (EPA), multi-bit partly sign-altered mean modulation (MPSAM), mixed modulation (MM), and particle swarm optimization (PSO) within a scheme based on crisscross inter-block quaternion discrete Fourier transform (QDFT). Accordingly, the proposed scheme employing EPA, MPSAM, MM, and QDFT is referred to as EMMQ. The image is separated into non-overl...
#1Ali Mohtashami (IAU: Islamic Azad University)H-Index: 6
#2Bahram Mohammadkhani Ghiasvand (IAU: Islamic Azad University)
Abstract The purpose of this study is to evaluate efficiency and effectiveness of banks, financial and credit institutes active in stock and super-stock exchange organizations using new Fuzzy DEA model which is the modified, improved and enhanced version of Russell's measurement model. In order to make it more efficient, we used the Z-numbers theory through which the calculations of uncertainty in the decision-making process can be showed more accurately. To do so, the literature of this industr...
Abstract Sensor drift, which is a critical issue in the field of sensor measurements, has plagued the sensor community in the past several decades. How to tackle the sensor drift problem using expert and intelligent systems has gained increasing attention. Most sensor drift compensation methods ignore the sparse and low-rank characteristics of sensor signals. In this paper, we propose a discriminative dimensionality reduction method for sensor drift compensation in the electronic nose. The propo...
#1Isabelle Duran Martins (UFRJ: Federal University of Rio de Janeiro)H-Index: 1
#2Laura Bahiense (UFRJ: Federal University of Rio de Janeiro)H-Index: 8
Last.Edilson F. Arruda (Cardiff University)
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Abstract This paper is motivated by decommissioning studies in the field of oil and gas, which comprise a very large number of installations and are of interest to a large number of stakeholders. Generally, the problem gives rise to complicated multi-criteria decision aid tools that rely upon the costly evaluation of multiple criteria for every piece of equipment. We propose the use of machine learning techniques to reduce the number of criteria by feature selection, thereby reducing the number ...
#1Somayyeh Sadegh Moghaddasi (IAU: Islamic Azad University)
#2Neda Faraji (IKIU: Imam Khomeini International University)H-Index: 3
Abstract The particle filter (PF) is an influential instrument for visual tracking; it relies on the Monte Carlo Chain Framework and Bayesian probability that is of tremendous importance for smart monitoring systems. The current study introduces a particle filter according to genetic resampling to decrease the size of image and marking for tracking moving objects. In the suggested method called Reduced Particle Filter Genetic Algorithm (RPFGA), particles with the highest weights are chosen and g...
#1Qianmu LiH-Index: 11
#2Yanjun Song (Nanjing University of Science and Technology)
Last.Victor S. Sheng (TTU: Texas Tech University)
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Abstract In many real-world applications, an algorithm needs to learn multiclass classification models from data with imbalanced class distributions. Multiclass imbalanced learning is currently receiving increased attention from researchers. In contrast to traditional imbalanced learning on binary datasets, multiclass imbalanced learning faces great challenges from the variety of changes in the class distributions as well as the inadequate performance of multiclass classification algorithms. In ...
Abstract Natural Language Interfaces allow human-computer interaction through the translation of human intention into devices’ control commands, analyzing the user’s speech or gestures. This novel interaction mode arises from advancements of artificial intelligence, expert systems, speech recognition, semantic web, dialog systems, and natural language processing, bringing the concept of Intelligent Personal Assistant (IPA). There is currently a vast literature on this subject. However, in the be...
Top fields of study
Machine learning
Data mining
Pattern recognition
Computer science
Artificial neural network
Fuzzy logic