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Dhaka, Bangladesh

United International University or UIU is a private university located in Dhaka, Bangladesh, The government of Bangladesh approved the establishment of United International University in 2003 under the Private University Act 1992 . Financial support came from the United Group, a business conglomerate. Wikipedia.


Harun-Owr-Roshid M.,United International University | Majumder S.P.,Bangladesh University of Engineering and Technology
ICECE 2010 - 6th International Conference on Electrical and Computer Engineering | Year: 2010

The focus of this paper is on the performance of an orthogonal frequency division multiplexing (OFDM) transmission system considering the combined influence of receiver noise, Rayleigh fading and the timing error due to imperfect slot synchronization at the receiver. Performance results are presented in terms of BER, BER improvement and BER-floor in presence of inter-channel interference (ICI) and inter-symbol interference (ISI) and additive white Gaussian noise for single input multiple output(SIMO) OFDM system using maximal ratio combining (MRC) technique. The results show that there is a significant degradation in system BER due to timing error but can be improved by applying diversity at the receiver. ©2010 IEEE. Source


Monzurur Rahman S.M.,United International University | Yu X.,RMIT University | Siddiky F.A.,United International University
International Journal of Data Mining, Modelling and Management | Year: 2011

Rule mining is one of the popular data mining (DM) methods since rules provide concise statements of potentially important information that is easily understood by end users and are also useful patterns for predictive data mining (PDM). This paper proposes rule mining methods using an unsupervised neural network approach. Two methods are adopted based on the way of unsupervised neural networks are applied in rule mining models. In the first method, the unsupervised neural network is used for clustering, which provides class information to the rule mining process. In the second method, automated rule mining takes the place of trained neurons as it grows in a hierarchical structure of unsupervised neural network. Copyright © 2011 Inderscience Enterprises Ltd. Source


Islam M.L.,United International University | Shatabda S.,United International University | Rahman M.S.,Bangladesh University of Engineering and Technology
Proceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014 | Year: 2014

Nuclear Magnetic Resonance (NMR) Spectroscopy is a widely used technique to predict the native structure of proteins. However, NMR machines are only able to report approximate and partial distances between pair of atoms. To build the protein structure one has to solve the Euclidean distance geometry problem given the incomplete interval distance data produced by NMR machines. In this paper, we propose a new genetic algorithm for solving the Euclidean distance geometry problem for protein structure prediction given sparse NMR data. Our genetic algorithm uses a greedy mutation operator to intensify the search, a twin removal technique for diversification in the population and a random restart method to recover stagnation. On a standard set of benchmark dataset, our algorithm significantly outperforms standard genetic algorithms. © 2014 IEEE. Source


Saha S.,United International University | Ahmed K.I.,United International University
8th International Conference on Electrical and Computer Engineering: Advancing Technology for a Better Tomorrow, ICECE 2014 | Year: 2015

This paper features the spatial characteristics of the brain towards brain-computer interface (BCI) research. A study on motor imagery (MI) based BCI has been carried out and important implications are identified. Common Spatial Pattern (CSP) is applied to the EEG signals before proceeding to the classification. The primary focus of this research is to utilize the spatial dynamics of the brain to develop BCI with reduced number of electrodes which contribute to the motor imagery tasks with optimal impact. It is observed that computational cost can be reduced drastically by selecting channels from specific regions of interests (ROIs) of the brain without compromising the classification accuracy making BCI efficient. Here, we have reported the best classification accuracies 72.5% and 97.1% which are achieved for two subjects ('av' and 'ay', respectively, in the dataset IVa in the BCI competition III) using less number of electrodes. © 2014 IEEE. Source


Rahman M.M.,United International University | Maksud-Ul-Alam,United International University | Monzurur Rahman S.M.,United International University
International Journal of Data Mining, Modelling and Management | Year: 2015

Building scalable, extensible, interoperable, distributed and easy-to-use large-scale data mining applications has proved to be challenging. Service-oriented architecture (SOA) is a flexible set of design principles used for solving such challenges. Many studies try to leverage it in building data mining applications. Our paper aims to propose an open multi-tier software architecture using SOA open standards in a homogeneous and distributed environment that goes beyond traditional n-tier software architecture efforts. This architecture uses enterprise service bus (ESB) model by utilising Windows Communication Foundation (WCF) to offer a number of endpoints for published services. All the tiers are independent to convey its functionality through this ESB. As a result, in the context of data mining, this framework relies on web services to achieve extensibility and interoperability, offers simple abstractions for users, and supports computationally intensive processing on large amounts of data. Copyright © 2015 Inderscience Enterprises Ltd. Source

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