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The Journal of Intelligence Learning Systems and Applications (JILSA) is a peer reviewed international journal with a key objective to provide the academic and industrial community a medium for presenting original cutting-edge research related to intelligent learning systems and their applications. JILSA invites autho…
Guangwu Liu, Jing Long, Lingzhi Yang, Zhaoyi Su, Dechen Yao, Xiangli Zhong
This study concerns with fault diagnosis of urban rail vehicle auxiliary inverter using wavelet packet and RBF neural network. Four statistical features are selected: standard voltage signal, voltage fluctuation signal, impulsive transient signal and frequenc…
Ting Yun, Gang Chen, Fangjun Zhou, Yong Lu, Haiyu Li, Qian Li
The monitoring and warning of urban rail transit is the core of operation management, and the breadth and depth of the monitoring range directly affect the quality of urban rail transit operation. For the current domestic monitoring system, most of the critic…
Jianlong Ding, Yong Qin, Limin Jia, Shiyou Zhu, Bo Yu
This paper aims to propose a modeling framework for subway operation and maintenance system (SOMS), which analyzes the train condition data based on both train sensor network data and basis train maintenance plan. The system is formulated into five function m…
Sharareh R. Niakan Kalhori, Xiao-Jun Zeng
Tuberculosis treatment course completion is crucial to protect patients against prolonged infectiousness, relapse, lengthened and more expensive therapy due to multidrug resistance TB. Up to 50% of all patients do not complete treatment course. To solve this…
Sameh Ghwanmeh, Adel Mohammad, Ali Al-Ibrahim
Heart diagnosis is not always possible at every medical center, especially in the rural areas where less support and care, due to lack of advanced heart diagnosis equipment. Also, physician intuition and experience are not always sufficient to achieve high qu…
Sunday Olusanya Olatunji, Lahouari Cheded, Wasfi G. Al-Khatib, Omair Khan
In this paper, we extend our previous study of addressing the important problem of automatically identifying question and non-question segments in Arabic monologues using prosodic features. We propose here two novel classification approaches to this problem:…
Qing-Guo Wang, Xian Li, Qin Qin
In machine learning, selecting useful features and rejecting redundant features is the prerequisite for better modeling and prediction. In this paper, we first study representative feature selection methods based on correlation analysis, and demonstrate that…
Mahmoud Z. Iskandarani
A novel approach to damage detection in composite structures using hyperspectral image index analysis algorithm with neural network modeling employing Weight Elimination Algorithm (WEA) is presented and discussed. The matrix band based technique allows the mo…
R. F. Mansour, E. Md. Abdelrahim, Amna S. Al-Johani
Support vector machine (SVM) has become an increasingly popular tool for machine learning tasks involving classification. In this paper, we present a simple and effective method of detect and classify hard exudates. Automatic detection of hard exudates from r…
Masayasu Atsumi
This paper proposes a probabilistic model of object category learning in conjunction with attention-guided organized perception. This model consists of a model of attention-guided organized perception of object segments on Markov random fields and a model of…
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The Journal of Intelligence Learning Systems and Applications (JILSA) is a peer reviewed international journal with a key objective to provide the academic and industrial community a medium for presenting original cutting-edge research related to intelligent learning systems and their applications. JILSA invites autho… All articles are open access under a CC BY 4.0 licence, with authors retaining copyright.
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