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Conference

International Conference on Industrial and Information Systems 

About: International Conference on Industrial and Information Systems is an academic conference. The conference publishes majorly in the area(s): Control theory & Feature extraction. Over the lifetime, 2043 publications have been published by the conference receiving 12163 citations.


Papers
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Proceedings ArticleDOI
01 Dec 2008
TL;DR: This paper presents an algorithm using feed forward neural network for automated diagnosis of localized faults in rolling element bearings, which requires only a few input features, resulting in simple preprocessing and faster training.
Abstract: Rolling element bearings are critical mechanical components in rotating machinery Fault detection and diagnosis in the early stages of damage is necessary to prevent their malfunctioning and failure during operation Vibration monitoring is the most widely used and cost-effective monitoring technique to detect, locate and distinguish faults in rolling element bearings This paper presents an algorithm using feed forward neural network for automated diagnosis of localized faults in rolling element bearings Normal negative log-likelihood value and kurtosis value extracted from time-domain vibration signals are used as input features for the neural network Trained neural networks are able to classify different states of the bearing with 100% accuracy The proposed procedure requires only a few input features, resulting in simple preprocessing and faster training Effectiveness of the proposed method is illustrated using the bearing vibration data obtained experimentally

127 citations

Proceedings ArticleDOI
01 Jan 2009
TL;DR: In this article, a good collection of properly reported literatures on power system stability and reliability including history of blackouts are presented and some critical comments on root causes, lessons learnt from the blackouts and solutions are addressed.
Abstract: Increasing electrical energy demand, modern lifestyles and energy usage patterns have made the world fully dependant on power systems. This instigated mandatory requirements for the operators to maintain high reliability and stability of the power system grid. However, the power system is a highly nonlinear system, which changes its operations continuously. Therefore, it is very challenging and uneconomical to make the system be stable for all disturbances. The system is usually designed to handle a single outage at a time. However, during the last decade several major blackouts were reported and all of them started with single outages. Each major blackout was mandatorily and transparently reported to the public. The properly written blackout reports help to minimize the operational risk, by strengthening the system and its operations based on selected high risk contingencies. In the last decade, several major blackouts were reported separately in many research papers. This paper lists a good collection of properly reported literatures on power system stability and reliability including history of blackouts. Some critical comments on root causes, lessons learnt from the blackouts and solutions are addressed while briefly discussing the blackout events presented in published literatures.

123 citations

Proceedings ArticleDOI
01 Dec 2008
TL;DR: In this paper, the authors used four feature extraction techniques namely, intersection, shadow feature, chain code histogram, and straight line fitting features for handwritten Devnagari characters recognition using weighted majority voting technique.
Abstract: In this paper, we present an OCR for handwritten Devnagari characters. Basic symbols are recognized by neural classifier. We have used four feature extraction techniques namely, intersection, shadow feature, chain code histogram and straight line fitting features. Shadow features are computed globally for character image while intersection features, chain code histogram features and line fitting features are computed by dividing the character image into different segments. Weighted majority voting technique is used for combining the classification decision obtained from four multi layer perceptron(MLP) based classifier. On experimentation with a dataset of 4900 samples the overall recognition rate observed is 92.80% as we considered top five choices results. This method is compared with other recent methods for handwritten Devnagari character recognition and it has been observed that this approach has better success rate than other methods.

110 citations

Proceedings ArticleDOI
10 Oct 2011
TL;DR: A short review of upper extremity robotic exoskeleton systems can be found in this article, where the authors identify the brief history, basic concept, challenges, and future development of the robotic exo-keleton systems.
Abstract: Robotic exoskeleton systems are one of the highly active areas in recent robotic research. These systems have been developed significantly to be used for the human power augmentation, robotic rehabilitation, human power assist, and haptic interaction in virtual reality. Unlike the robots used in industry, the robotic exoskeleton systems should be designed with special consideration since they directly interact with human user. In the mechanical design of these systems, movable ranges, safety, comfort wearing, low inertia, and adaptability should be especially considered. Controllability, responsiveness, flexible and smooth motion generation, and safety should especially be considered in the controllers of exoskeleton systems. Furthermore, the controller should generate the motions in accordance with the human motion intention. This paper briefly reviews the upper extremity robotic exoskeleton systems. In the short review, it is focused to identify the brief history, basic concept, challenges, and future development of the robotic exoskeleton systems. Furthermore, key technologies of upper extremity exoskeleton systems are reviewed by taking state-of-the-art robot as examples.

109 citations

Proceedings ArticleDOI
10 Oct 2011
TL;DR: The aim of this paper is to provide a review of the current state of the research on feature based SLAM, in particular to examine the current understanding of the fundamental properties of the SLAM problem and associated issues with the view to consolidate recent achievements.
Abstract: Simultaneous Localization and Mapping (SLAM) problem has been an active area of research in robotics for more than a decade. Many fundamental and practical aspects of SLAM have been addressed and some impressive practical solutions have been demonstrated. The aim of this paper is to provide a review of the current state of the research on feature based SLAM, in particular to examine the current understanding of the fundamental properties of the SLAM problem and associated issues with the view to consolidate recent achievements.

106 citations

Performance
Metrics
No. of papers from the Conference in previous years
YearPapers
202055
20195
201882
201795
2016176
201595