Clustering gene expression data using ant-based heuristics
- Authors: Tan, Swee , Ting, Kaiming , Teng, Shyh
- Date: 2011
- Type: Text , Conference paper
- Relation: IEEE Congress on Evolutionary Computation (IEEE CEC) 2011 p. 1-8
- Full Text: false
- Reviewed:
- Description: ABSTRACT We consider the problem of finding the clusters in novel datasets in which the number of clusters is not known a priori; and little or no additional information is available for users to adjust the parameters in a clustering algorithm. We address this problem using a stochastic algorithm named SATTA (Simplified Adaptive Time Dependent Transporter), which attempts to find clusters without requiring users to specify the number of clusters or adjust any parameters. SATTA is then compared with Expectation Maximization Clustering, which is also able to estimate the number clusters using the principle of maximum likelihood and find the underlying clusters without any human interventions. Our results on seven gene expression datasets show that SATTA significantly outperforms Expectation Maximization Clustering in terms of clustering accuracy and efficiency. We discuss the conceptual differences between SATTA and EMC, which suggests that SATTA is a more promising alternative approach than Expectation Maximization Clustering when little or no additional information is available for clustering novel datasets.
- Description: ABSTRACT We consider the problem of finding the clusters in novel datasets in which the number of clusters is not known a priori; and little or no additional information is available for users to adjust the parameters in a clustering algorithm. We address this problem using a stochastic algorithm named SATTA (Simplified Adaptive Time Dependent Transporter), which attempts to find clusters without requiring users to specify the number of clusters or adjust any parameters. SATTA is then compared with Expectation Maximization Clustering, which is also able to estimate the number clusters using the principle of maximum likelihood and find the underlying clusters without any human interventions. Our results on seven gene expression datasets show that SATTA significantly outperforms Expectation Maximization Clustering in terms of clustering accuracy and efficiency. We discuss the conceptual differences between SATTA and EMC, which suggests that SATTA is a more promising alternative approach than Expectation Maximization Clustering when little or no additional information is available for clustering novel datasets. [less] 0 BOOKMARKS · 54 VIEWS
Detection of structural similarity for multimodal microscopic image registration
- Authors: Lv, Guohua , Teng, Shyh , Lu, Guojun , Lackmann, Martin
- Date: 2013
- Type: Text , Conference paper
- Relation: 2013 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2013
- Full Text: false
- Reviewed:
- Description: In this paper we propose a novel method to detect the structural similarity in registering color and confocal microscopic images. Our prior work [1] presented the basic idea of detecting the structural similarity of such images, which utilizes the intensity relationships among red-green-blue color channels. The work in this paper will make the detection of structural similarity automatic and adaptive to each individual color microscopic image. The experimental results will demonstrate the effectiveness of the proposed method in detecting the structural similarity of these images and significant improvements in the registration performance.
Improved power transformer winding fault detection using FRA diagnostics – Part 1 : Axial displacement simulation
- Authors: Hashemnia, Naser , Abu-Siada, Ahmed , Islam, Syed
- Date: 2015
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 22, no. 1 (2015), p. 556-563
- Full Text: false
- Reviewed:
- Description: Frequency response analysis (FRA) has become a widely accepted tool to detect power transformer winding deformation due to the development of FRA test equipment. Because FRA relies on graphical analysis, interpretation of its signature is a very specialized area that calls for skilled personnel, as so far, there is no reliable standard code for FRA signature identification and quantification. Many researchers investigated the impact of various mechanical winding deformations on the transformer FRA signature using simulation analysis by altering particular electrical parameters of the transformer equivalent electrical circuit. None of them however, investigated the impact of various physical fault levels on the corresponding change in the equivalent circuit parameters. In this paper, the physical geometrical dimension of a single-phase transformer is simulated using 3D finite element analysis to emulate the real transformer operation. A physical axial displacement of different fault levels is simulated in both low voltage and high voltage windings. The impact of each fault level on the electrical parameters of the equivalent circuit is investigated. A key contribution of this paper is the charts it introduces to correlate various axial displacement levels with the percentage change of all transformer equivalent circuit parameters due to the axial displacement fault. In contrary with other researchers who only considered mutual inductance between low voltage and high voltage windings, simulation results shown in this paper reveal that other circuit parameters should be changed by a particular percentage to accurately simulate particular fault level of transformer winding axial displacement. Results of this paper aid to precisely simulating winding axial displacement using transformer equivalent circuit that facilitates accurate qualitative and quantitative analysis of transformer FRA signatures.
Online transformer internal fault detection based on instantaneous voltage and current measurements considering impact of harmonics
- Authors: Masoum, Ali , Hashemnia, Seyednaser , Abu-Siada, Ahmed , Masoum, Mohammad Sherkat , Islam, Syed
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Transactions on Power Delivery Vol. 32, no. 2 (2017), p. 587-598
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- Description: This paper investigates the performance of a recently proposed online transformer internal fault detection technique and examines impact of harmonics through detailed nonlinear simulation of a transformer using three-dimensional finite element modelling. The proposed online technique is based on considering the correlation between the instantaneous input and output voltage difference (ΔV) and the input current of a particular phase as a finger print of the transformer that could be measured every cycle to identify any incipient mechanical deformation within power transformers. To precisely emulate real transformer operation under various winding mechanical deformations, a detailed three-dimensional finite-element model is developed. Detailed simulations with (non)sinusoidal excitation are performed and analysed to demonstrate the unique impact of each fault on the ΔV-I locus. Impact of harmonic order, magnitude and phase angle is also investigated. Furthermore, practical measurements have been performed to validate the effect of winding short circuit fault on the proposed ΔV-I locus without and with the impact of system harmonics.
Detection of power transformer bushing faults and oil degradation using frequency response analysis
- Authors: Hashemnia, Naser , Abu-Siada, Ahmed , Islam, Syed
- Date: 2015
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 23, no. 1 (2015), p. 222-229
- Full Text: false
- Reviewed:
- Description: Frequency response analysis (FRA) has been globally accepted as a reliable tool to detect mechanical deformation within power transformers. However, because of its reliance on graphical analysis, interpretation of FRA signature is still a challenging area that calls for skilled personnel, as so far, there is no widely accepted reliable standard code for FRA signature identification and quantification. While several papers investigating the impact of various mechanical winding deformations on the transformer FRA signature can be found in the literature, no attention was given to investigate the impact of various bushing faults and transformer oil degradation on the FRA signature. This paper introduces a detailed simulation and practical analyses to elaborate the impact of bushing faults as well as transformer oil degradation on the transformer FRA signature. In this regard, the physical geometrical dimension of a three phase power transformer is simulated using 3D finite element analysis to emulate the real transformer operation. Various bushing faults have been emulated on the studied model and oil degradation is implemented through changing oil permittivity. Practical FRA test is conducted on a three phase 132kV, 35MVA power transformer to validate the simulation results. Results show that bushing faults and oil degradation can be visibly detected through FRA signature.
Determination of nanosecond pulse parameters on transfer function measurement for power transformer winding deformation
- Authors: Zhao, Zhongyong , Yao, Chenguo , Hashemnia, Naser , Islam, Syed
- Date: 2016
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 23, no. 6 (2016), p. 3761-3770
- Full Text: false
- Reviewed:
- Description: Transfer function method is now a widely acceptable tool to diagnose transformer winding deformations. A sweep frequency sine wave generator is often used to excite the different modes of resonance and anti-resonances. However, it is time consuming. Nanosecond square wave pulse signal offers an alternative that can serve the same objective. However, as so far, there is no certain criterion for selecting pulse parameters. This paper provides a comprehensive method for the determination of nanosecond square wave pulse parameters for transfer function evaluation of power transformer for winding deformation studies.
Improved power transformer winding fault detection using FRA diagnostics – Part 2 : Radial deformation simulation
- Authors: Hashemnia, Naser , Abu-Siada, Ahmed , Islam, Syed
- Date: 2015
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 22, no. 1 (2015), p. 564-570
- Full Text: false
- Reviewed:
- Description: Frequency response analysis (FRA) is proven to be a powerful tool to detect winding deformation within power transformers. Although the FRA test along with the equipment are well developed, interpretation of FRA signature is still a challenge and it needs skilled personnel to identify and quantify the fault type if exists as at this stage, there is no reliable standard code for FRA signature classification and quantification. As it is very hard to implement faults on physical transformer without damaging it, researchers investigated the impact of various mechanical winding deformations on the transformer FRA signature by randomly changing the value of particular electrical parameters of the transformer equivalent electrical circuit. None of them however, precisely investigated the correlation between physical fault level and the percentage change in each parameter. In this paper, the physical geometrical dimension of a single-phase transformer is simulated using 3D finite element analysis to emulate the real transformer operation. A physical radial deformation of different fault levels is simulated on both low voltage and high voltage windings. The impact of each fault level on the electrical parameters of the equivalent circuit is investigated and the correlation between the fault level and the percentage change in each parameter of the equivalent circuit is provided. This will facilitate precise fault simulation using transformer equivalent electrical circuit and ease the quantification analysis of FRA signature.
Consistency driven opinion formation modelling in presence of external sources
- Authors: Das, Rajkumar , Kamruzzaman, Joarder , Karmakar, Gour
- Date: 2015
- Type: Text , Conference proceedings
- Relation: International Joint Conference on Neural Networks, IJCNN 2015; Killarney, Ireland; 12th-17th July 2015
- Full Text: false
- Description: Opinion formation in social networks has changed in a more rigorous way due to the inception of Online Social Networks (OSNs) as a platform of generating and sharing huge amount of contents as well as easy and ubiquitous access to varied information sources. Our opinions are not only updated through interactions with our neighbours in OSNs, but also shaped by the opinions received from information sources external to the native OSNs. Current models only consider the neighbours' influence in opinion evolution, thus lack the impact of other information sources, e.g., news media, web search, bulletin board, discussion forum on opinion formation. They consider individual opinion distances to model the influence among interactive neighbours, but fail to capture the influence of majority supported opinions and its possible impact in opinion evolution. Our model explicitly captures the effect of external sources on opinion formation in an OSN. We combine the implication of most perceived opinions in terms of consistency along with opinion distance to emulate the influence of different opinion sources. Consistency is measured by the entropy of opinions derived from a particular source type. Simulation results show that our model properly captures the consensus, polarization and fragmentation properties of opinion evolution. Finally, we investigate the influence of stubborn agents on opinion formation and compare it with a contemporary model. © 2015 IEEE.
Impact of capacitive coupling circuit on online impulse frequency response of a power transformer
- Authors: Zhao, Zhongyong , Yao, Chenguo , Zhao, Xiaozhen , Hashemnia, Naser , Islam, Syed
- Date: 2016
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 23, no. 3 (2016), p. 1285-1293
- Full Text: false
- Reviewed:
- Description: Detecting the early signs of mechanical failures of power transformer winding is necessary and is possible with online monitoring techniques. Online impulse frequency response analysis (IFRA) is a promising diagnostic method when a transformer is in service. This paper examines the unrevealed problem existing in the method, namely, the impact of bushing capacitive coupling circuit on online impulse frequency response. An equivalent electrical model of capacitive coupling circuit and transformer winding is established. The frequency response of the capacitive coupling circuit is obtained to study its influence on online impulse frequency response. The parameter variations of capacitive coupling circuit caused by coupling capacitance variation and bushing dielectric breakdown are simulated to investigate their influence on online impulse frequency response signatures. A few experiments are eventually performed to verify the theoretical analysis and simulation results. This paper contributes to the application of online IFRA.
A new technique to measure interfacial tension of transformer oil using UV-Vis spectroscopy
- Authors: Abu Bakar, Norazhar , Abu-Siada, Ahmed , Islam, Syed , El-Naggar, Mohammed
- Date: 2015
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 22, no. 2 (2015), p. 1275-1282
- Full Text:
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- Description: Interfacial tension (IFT) and acid numbers of insulating oil are correlated with the number of years that a transformer has been in service and are used as a signal for transformer oil reclamation. Oil sampling for IFT measurement calls for extra precautions due to its high sensitivity to various oil parameters and environmental conditions. The current used technique to measure IFT of transformer oil is relatively expensive, requires an expert to conduct the test and it takes long time since the extraction of oil sample, sending it to external laboratory and getting the results back. This paper introduces a new technique to estimate the IFT of transformer oil using ultraviolet-to-visible (UV-Vis) spectroscopy. UV-Vis spectral response of transformer oil can be measured instantly with relatively cheap equipment, does not need an expert person to conduct the test and has the potential to be implemented online. Results show that there is a good correlation between oil spectral response and its IFT value. Artificial neural network (ANN) approach is proposed to model this correlation.
A review of dissolved gas analysis measurement and interpretation techniques
- Authors: Abu Bakar, Norazhar , Abu-Siada, Ahmed , Islam, Syed
- Date: 2014
- Type: Text , Journal article
- Relation: IEEE Electrical Insulation Magazine Vol. 30, no. 3 (2014), p. 39-49
- Full Text: false
- Reviewed:
- Description: Dissolved gas analysis (DGA) is used to assess the condition of power transformers. It uses the concentrations of various gases dissolved in the transformer oil due to decomposition of the oil and paper insulation. DGA has gained worldwide acceptance as a method for the detection of incipient faults in transformers.
Yen's algorithm-based charging facility planning considering congestion in coupled transportation and power systems
- Authors: Zhang, Xian , Li, Peiling , Hu, Jiefeng , Liu, Ming , Wang, Guibin , Qiu, Jing , Chan, Ka
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Transactions on Transportation Electrification Vol. 5, no. 4 (Dec 2019), p. 1134-1144
- Full Text: false
- Reviewed:
- Description: To promote the penetration of electric vehicles (EVs), a charging facility (CF) planning model based on Yen's algorithm is proposed for coupled transportation and distribution systems (DSs) considering traffic congestion. This model not only takes into account the influence of new CFs on the power system but also considers the impact of CF locations on traffic flow distribution and congestion level in the transportation system (TS). Yen's algorithm is innovatively employed to offer multiple possible choices for EV drivers' route selection considering CF locations determined in the traffic flow assignment model. Overall, the total cost of both distribution and TSs is minimized to obtain the optimal CF planning results. For the DS, generation cost, energy loss, and penalty cost for voltage deviation are included. For the TS, the main objective is to ensure EVs can reach their destinations at the lowest cost, while the travel time due to different path selections and the delay time caused by congestion can be minimized. Finally, a comprehensive case study on the integrated IEEE 30-bus and a 25-node TS is conducted to validate our approach.
Cloud service description model : an extension of USDL for cloud services
- Authors: Sun, Le , Ma, Jiangan , Wang, Hua , Zhang, Yanchun , Yong, Jianming
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Transactions on Services Computing Vol. 11, no. 2 (2018), p. 354-368
- Full Text: false
- Reviewed:
- Description: There are a variety of well-designed specification-modelling-languages serving Internet services, however, none of them is capable of describing the special features of cloud services, from both technical and business points of view. The Unified Service Description Language (USDL) provides a new way to describe Internet services from business, operational, and technical perspectives. Nevertheless, there are various issues with USDL: it lacks a comprehensive specification model, particularly for cloud services, lacks a user-centric specification modeling paradigm, lacks a mechanism to measure cloud service attributes and to present the association relationship and re-usability of the attributes, and lacks semantic representation of cloud services. Based on the above issues, we propose a unified semantic Cloud Service Description Model (CSDM) in this paper. The proposed model will be extended from the basic structure of USDL, by defining cloud-service-specific attributes. Furthermore, an additional module, named transaction module, will be defined, which models the rating system of cloud services from several aspects, such as risk, trust, and reputation. The transaction module facilitates the capability of CSDM with regard to service ranking, and enhances its flexibility and extensibility by providing an extensible sub-module. In addition, we design an OWL-based annotation system to enrich the semantic expressivity of this model. Finally, a case study is provided to explain the application of this model in actual cloud services. © 2008-2012 IEEE.