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2012

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Articles 361 - 390 of 12196

Full-Text Articles in Physical Sciences and Mathematics

Protection Of Solar Electric Car Dc Motor With Pic Controller, Ahmed Haidar, Ramdan Razali, Ahmed Abdalla, Hazizulden Abdul Aziz, Khaled Noman, Rashad Al-Jawfi Dec 2012

Protection Of Solar Electric Car Dc Motor With Pic Controller, Ahmed Haidar, Ramdan Razali, Ahmed Abdalla, Hazizulden Abdul Aziz, Khaled Noman, Rashad Al-Jawfi

Dr Ahmed Mohamed Ahmed Haidar

The electric car may represent new opportunities for any country and its electric utilities. Widespread use of electric cars can reduce the consumption of both imported and domestic oil, substitute abundant fuels such as coal and nuclear power. Since the charging of electric cars DC motor can be accomplished to a large extent during utility off-peak hours, electric cars can contribute to improve the utility load factors, as a result, reducing the average cost of generation. The problem arising when the DC motor does not stop automatically due to the abnormal condition and cause the loss of energy and the …

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Evaluation Of Transformer Magnetizing Core Loss, Ahmed Haidar, S Taib, I Daut, S Uthman Dec 2012

Evaluation Of Transformer Magnetizing Core Loss, Ahmed Haidar, S Taib, I Daut, S Uthman

Dr Ahmed Mohamed Ahmed Haidar

Loss in transformer core is the electrical power lost in terms of heat within the core of transformer, when core is subjected to AC magnetizing force. It is composed of several types of losses such a s Hysterics loss, eddy current loss within individual laminations and inter-laminar losses that may arise if laminations are not sufficiently insulated from each other. To assess the level of no load loss relative to the occurrence of an inaccurate manufacturing of transformer core, a quantitative measure is often considered. The objective of this research is to study the magnetic behaviour of transformer core and …

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Vulnerability Assessment Of A Large Sized Power System Considering A New Index Based On Power System Loss, Ahmed M. Haidar, Azah Mohamed, Aini Hussain Dec 2012

Vulnerability Assessment Of A Large Sized Power System Considering A New Index Based On Power System Loss, Ahmed M. Haidar, Azah Mohamed, Aini Hussain

Dr Ahmed Mohamed Ahmed Haidar

The concept of power system vulnerability assessment combines information on the level of system security as well as information on a wide range of situations, events and contingencies with regards to which a system is vulnerable. This paper attempts to investigate and evaluate the effect of line outage, generation outage and amount of load disconnected on the power transmission network losses of a large size power system. These effects will be investigated and evaluated using new proposed method based on vulnerability index of power system loss. The objectives of this work is to evaluate and compare the efficiency of the …

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Grounding Locations Assessment Of Practical Power System, Nadheer Shalash, Ahmed M. Haidar, Abdul Sattar Dec 2012

Grounding Locations Assessment Of Practical Power System, Nadheer Shalash, Ahmed M. Haidar, Abdul Sattar

Dr Ahmed Mohamed Ahmed Haidar

Grounding Points (GPs) are installed in electrical power system to drive protective devices and accomplish the person- nel safety. The general grounding problem is to find the optimal locations of these points so that the security and reli- ability of power system can be improved. This paper presents a practical approach to find the optimal location of GPs based on the ratios of zero sequence reactance with positive sequence reactance (X0/X1), zero sequence resistance with positive sequence reactance (R0/X1) and Ground Fault Factor (GFF). The optimal values of these indicators were deter- mined by considering several scenarios of fault disturbances …

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Electrical Defect Detection In Thermal Image, Ahmed Haidar, Geoffrey Asiegbu, Kamarul Hawari, Faisal Ibrahim Dec 2012

Electrical Defect Detection In Thermal Image, Ahmed Haidar, Geoffrey Asiegbu, Kamarul Hawari, Faisal Ibrahim

Dr Ahmed Mohamed Ahmed Haidar

Electrical and Electronic objects, which have a temperature of operating condition above absolute zero, emit infrared radiation. This radiation can be measured on the infrared spectral band of the electromagnetic spectrum using thermal imaging. Faults on electrical systems are expensive in terms of plant downtime, damage, loss of production or risk from fire. If the threshold temperature is timely detected, the electrical equipment failures can be avoided. This paper presents a straightforward approach for thermal analysis that examines power loads and large area thermal characteristics. A thermal imaging camera was used to collect thermal pictures of the tested system under …

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An Intelligent Approach For Cost Minimization Of Power Generation, Ahmed M. A. Haidar, Ibrahim A. Ahmed, Norazila Jaalam Dec 2012

An Intelligent Approach For Cost Minimization Of Power Generation, Ahmed M. A. Haidar, Ibrahim A. Ahmed, Norazila Jaalam

Dr Ahmed Mohamed Ahmed Haidar

Cost reduction is one of the main targets in power industry due to economic load dispatch problem and allocating loads to plants for minimum cost. The principal objective in economic dispatch of thermal generators in a power system is to determine the economic loadings of the generators so that the load demand can be met and the loadings are within the feasible operating regions of the generators. This study presents an optimization approach for fuel cost and power loss minimization based on genetic algorithm and particle swarm optimization methods. To demonstrate the global optimization power of the presented techniques, these …

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Neural Network Prediction Of Electromagnetic Field Strength In Hybrid Micro-Grid System, Ahmed Haidar, Ibrahim Ahmed, Ahmed Abdalla Dec 2012

Neural Network Prediction Of Electromagnetic Field Strength In Hybrid Micro-Grid System, Ahmed Haidar, Ibrahim Ahmed, Ahmed Abdalla

Dr Ahmed Mohamed Ahmed Haidar

Location of any Hybrid Micro-Grid System requires efficiently prediction of the electromagnetic field strength. This study proposes a novel Electromagnetic Field Strength (EFS) predication based on Probabilistic Neural Network (PNN). Learning data sets have been generated using Electromagnetic Transients Program EMTP. The PNN model has three input nodes representing the Switching Distance, Busbar Interference Voltage and Current waveforms, the output node representing the EFS. Testing datasets have deliberately been chosen outside the region of the learning datasets so as to check the performance of the neural network. The results indicate that the proposed technique can be used successfully to detect …

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Power Line Enhancement For Data Monitoring Of Neural Electrical Activity In The Human Body, Ahmed M. Haidar, Sridhathan C, Abdulsalam Hazza, Ahmed Saleh Dec 2012

Power Line Enhancement For Data Monitoring Of Neural Electrical Activity In The Human Body, Ahmed M. Haidar, Sridhathan C, Abdulsalam Hazza, Ahmed Saleh

Dr Ahmed Mohamed Ahmed Haidar

Distance and real-time data monitoring are the necessary condition that makes any system in good working order. Recent advancements in micro-electronics and wireless technology enable the application of wireless sensors in both industry and wild environments. However, Long-distance wireless communication has several drawbacks like limited bandwidth, considerable costs and unstable connection quality. Therefore, Power Line Communication (PLC) using pre-established Power Lines (PL) becomes more attractive for high data transmission technology. This paper reviews the existing distance data monitoring systems and presents a case study for data transferring of temperature and heart beat measurement. The simulations were carried out on the …

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A Computational Intelligence-Based Suite For Vulnerability Assessment Of Electrical Power Systems, Ahmed Haidar, Azah Mohamed, Federico Milano Dec 2012

A Computational Intelligence-Based Suite For Vulnerability Assessment Of Electrical Power Systems, Ahmed Haidar, Azah Mohamed, Federico Milano

Dr Ahmed Mohamed Ahmed Haidar

This paper discusses the feasibility of implementing computational intelligence algorithms for power system analysis in an open source environment. The scope is specially oriented to education, training and research. In particular, the paper describes a software package, namely Computational Intelligence Applications to Power System (CIAPS), that implements a variety of heuristic techniques for vulnerability assessment of electrical power systems. CIAPS is based on Matlab and suited for analysis and simulation of small to large size electric power systems. CIAPS is used for solving power flow, optimal power flow, contingency analysis based on artificial neural networks and fuzzy logic techniques. A …

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Vulnerability Control Of Large Scale Interconnected Power System Using Neuro-Fuzzy Load Shedding Approach, Ahmed Haidar, Azah Mohamed, Aini Hussain Dec 2012

Vulnerability Control Of Large Scale Interconnected Power System Using Neuro-Fuzzy Load Shedding Approach, Ahmed Haidar, Azah Mohamed, Aini Hussain

Dr Ahmed Mohamed Ahmed Haidar

Vulnerability control is becoming an essential requirement for security of power systems in the new utility environment. It is a difficult task for system operator who under economic pressure may be reluctant to take preventive action against harmful contingencies in order to guarantee providing continued service. For power systems which are operated closer to their stability limits, it is desirable to use load shedding as a form of vulnerability control strategy. This paper presents a neuro-fuzzy approach for determining the amount of load to be shed in order to avoid a cascading outage. The objective is to develop fast and …

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Utilization Of Pico Hydro Generation In Domestic And Commercial Loads, Ahmed Haidar, Mohod Senan, Abdulhakim Noman, Taha Radman Dec 2012

Utilization Of Pico Hydro Generation In Domestic And Commercial Loads, Ahmed Haidar, Mohod Senan, Abdulhakim Noman, Taha Radman

Dr Ahmed Mohamed Ahmed Haidar

Pico hydro is a term used to distinguish very small-scale hydropower with a maximum electrical output of five kilowatts (5 kW). It is a good technique of providing electricity to the off-grid remote and isolated regions that suffer energy deficit. Typical pico hydro generator is designed and supported by electrical converting system, batteries and safety equipment so that it can be installed at the residential water pipeline. In pico hydro generation, the environmental impact is negligible since large dams are not involved, and the schemes can be managed and maintained by the consumer. This paper is reviewing the application of …

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An Intelligent Load Shedding Scheme Using Neural Networks And Neuro-Fuzzy, Ahmed Haidar, Azah Mohamed, Majid Al-Dabbagh, Aini Hussain, Mohamed Masoum Dec 2012

An Intelligent Load Shedding Scheme Using Neural Networks And Neuro-Fuzzy, Ahmed Haidar, Azah Mohamed, Majid Al-Dabbagh, Aini Hussain, Mohamed Masoum

Dr Ahmed Mohamed Ahmed Haidar

Load shedding is some of the essential requirement for maintaining security of modern power systems, particularly in competitive energy markets. This paper proposes an intelligent scheme for fast and accurate load shedding using neural networks for predicting the possible loss of load at the early stage and neuro-fuzzy for determining the amount of load shed in order to avoid a cascading outage. A large scale electrical power system has been considered to validate the performance of the proposed technique in determining the amount of load shed. The proposed techniques can provide tools for improving the reliability and continuity of power …

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Parameters Evaluation Of Unified Power Quality Conditioner, Ahmed Haidar, C Benachaiba, F Ibrahim, K Hawari Dec 2012

Parameters Evaluation Of Unified Power Quality Conditioner, Ahmed Haidar, C Benachaiba, F Ibrahim, K Hawari

Dr Ahmed Mohamed Ahmed Haidar

The term of “Power Quality” is used to describe the electromagnetic phenomenon in variations of voltage and current in the power system. Most power quality disturbances can come from the facility itself, such as large loads turning on simultaneously, improper wiring and grounding practices, the start-up of large motors and electronic equipments that can be both a source and victim of power quality phenomena or from externally generated, for example, lightning strokes on the power lines. Currently, there are so many industries using a high technology for the manufacturing and requiring a high quality of power supply. Therefore, the paper …

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Vulnerability Assessment Of Power System Using Radial Basis Function Neural Network And A New Feature Extraction Method, Ahmed M. Haidar, Azah Mohamed, Aini Hussain Dec 2012

Vulnerability Assessment Of Power System Using Radial Basis Function Neural Network And A New Feature Extraction Method, Ahmed M. Haidar, Azah Mohamed, Aini Hussain

Dr Ahmed Mohamed Ahmed Haidar

Vulnerability assessment in power systems is important so as to determine how vulnerable a power system in case of any unforeseen catastrophic events. This paper presents the application of Radial Basis Function Neural Network (RBFNN) for vulnerability assessment of power system incorporating a new proposed feature extraction method named as the Neural Network Weight Extraction (NNWE) for dimensionality reduction of input data. The performance of the RBFNN is compared with the Multi Layer Perceptron Neural Network (MLPNN) so as to evaluate the effectiveness of the RBFNN in assessing the vulnerability of a power system based on the indices, power system …

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Artificial Intelligence Application To Malaysian Electrical Powersystem, Ahmed Haidar, Azah Mohamed, Aini Hussain, Norazila Jaalam Dec 2012

Artificial Intelligence Application To Malaysian Electrical Powersystem, Ahmed Haidar, Azah Mohamed, Aini Hussain, Norazila Jaalam

Dr Ahmed Mohamed Ahmed Haidar

Vulnerability assessment and control of a power system is important to power utilities due to the blackouts in recent years in many countries which indicate that power systems today are vulnerable when exposed to unforeseen catastrophic contingencies. A fast and accurate technique to assess the level of system strength or weakness is some of the essential requirements for maintaining security of modern power systems, particularly in competitive energy markets. This paper presents intelligent artificial techniques for vulnerability assessment of Malaysian power system and recommends preventive control measures. Accurate techniques for vulnerability assessment and control of power systems are developed. In …

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Optimal Configuration Assessment Of Renewable Energy In Malaysia, Ahmed Haidar, Priscilla John, Mohd Shawal Dec 2012

Optimal Configuration Assessment Of Renewable Energy In Malaysia, Ahmed Haidar, Priscilla John, Mohd Shawal

Dr Ahmed Mohamed Ahmed Haidar

This paper proposes the use of a PVewindediesel generator hybrid system in order to determine the optimal configuration of renewable energy in Malaysia and to compare the production cost of solar and wind power with its annual yield relevant to different regions in Malaysia namely, Johor, Sarawak, Penang and Selangor. The configuration of optimal hybrid system is selected based on the best components and sizing with appropriate operating strategy to provide a cheap, efficient, reliable and cost-effective system. The various renewable energy sources and their applicability in terms of cost and performance are analyzed. Moreover, the annual yield and cost …

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New Method Vulnerability Assessment Of Power System, Ahmed Haidar, Azah Mohamed, Aini Hussain Dec 2012

New Method Vulnerability Assessment Of Power System, Ahmed Haidar, Azah Mohamed, Aini Hussain

Dr Ahmed Mohamed Ahmed Haidar

Vulnerability assessment in power systems is to determine a power system`s ability to continue to provide service in case of an unforeseen catastrophic contingency. It combines information on the level of system security as well as information on a wide range of scenarios, events and contingencies. To assess the level of system strength or weakness relative to the occurrence of an undesired event, a quantitative measure based on vulnerability index is often considered. In this study, a new vulnerability assessment method is proposed based on total power system loss which considers power generation loss due to generation outage, power line …

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Transient Stability Evaluation Of Electrical Power System Using Generalized Regression Neural Networks, Ahmed Haidar, M Mustafa, Faisal Ibrahim, Ibrahim Ahmed Dec 2012

Transient Stability Evaluation Of Electrical Power System Using Generalized Regression Neural Networks, Ahmed Haidar, M Mustafa, Faisal Ibrahim, Ibrahim Ahmed

Dr Ahmed Mohamed Ahmed Haidar

Transient stability evaluation (TSE) is part of dynamic security assessment of power systems, which involves the evaluation of the system’s ability to remain in equilibrium under credible contingencies. Neural networks (NN) have been applied to the security assessment of power systems and have shown great potential for predicting the security of power systems. This paper proposes a generalized regression neural networks (GRNN) based classification for transient stability evaluation in power systems. In the proposed method, learning data sets have been generated using time domain simulation (TDS). TheGRNN input nodes representing the voltage magnitude for all buses, real and reactive powers …

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Computational Intelligence Applications To Power Systems (Ciaps), Ahmed Haidar Dec 2012

Computational Intelligence Applications To Power Systems (Ciaps), Ahmed Haidar

Dr Ahmed Mohamed Ahmed Haidar

No abstract provided.

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Smart Control Of Upcq Within Microgrid Energy System, C Benachaiba, Ahmed Haidar, O Habab, O Abdelkhalek Dec 2012

Smart Control Of Upcq Within Microgrid Energy System, C Benachaiba, Ahmed Haidar, O Habab, O Abdelkhalek

Dr Ahmed Mohamed Ahmed Haidar

One of the most popular issues in the future power distribution is the quality improvement of microgrid and the development of smart grid (SG). Many applications operating at the microgrid level can be considered as smart grid functions. This paper proposes the application of Fuzzy Logic (FL) technique within microgrid energy system based on the most modern power conditioning equipment devices such as Unified Power Quality Conditioner (UPQC). This technique is working together with the microgrid to track the disturbance of the smart grid and improve the quality of the system with a high flexibility. Furthermore, a control methodology developed …

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A Self-Organizing Map For Adaptive Processing Of Structured Data, Markus Hagenbuchner, A. Sperduti, Ah Chung Tsoi Dec 2012

A Self-Organizing Map For Adaptive Processing Of Structured Data, Markus Hagenbuchner, A. Sperduti, Ah Chung Tsoi

Dr Markus Hagenbuchner

Recent developments in the area of neural networks produced models capable of dealing with structured data. Here, we propose the first fully unsupervised model, namely an extension of traditional self-organizing maps (SOMs), for the processing of labeled directed acyclic graphs (DAGs). The extension is obtained by using the unfolding procedure adopted in recurrent and recursive neural networks, with the replicated neurons in the unfolded network comprising of a full SOM. This approach enables the discovery of similarities among objects including vectors consisting of numerical data. The capabilities of the model are analyzed in detail by utilizing a relatively large data …

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A Conceptlink Graph For Text Structure Mining, Rowena Chau, Ah Chung Tsoi, Markus Hagenbuchner, Vincent Lee Dec 2012

A Conceptlink Graph For Text Structure Mining, Rowena Chau, Ah Chung Tsoi, Markus Hagenbuchner, Vincent Lee

Dr Markus Hagenbuchner

Most text mining methods are based on representing documents using a vector space model, commonly known as a bag of word model, where each document is modeled as a linear vector representing the occurrence of independent words in the text corpus. It is well known that using this vector-based representation, important information, such as semantic relationship among concepts, is lost. This paper proposes a novel text representation model called ConceptLink graph. The ConceptLink graph does not only represent the content of the document, but also captures some of its underlying semantic structure in terms of the relationships among concepts. The …

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A Supervised Self-Organizing Map For Structures, Markus Hagenbuchner, Ah Chung Tsoi Dec 2012

A Supervised Self-Organizing Map For Structures, Markus Hagenbuchner, Ah Chung Tsoi

Dr Markus Hagenbuchner

This work proposes an improvement of a supervised learning technique for self organizing maps. The ideas presented in This work differ from Kohonen's approach to supervision in that a.) a rejection term is used, and b.) rejection affects the training only locally. This approach produces superior results because it does not affect network weights globally, and hence, prevents the addition of noise to the learning process of remote neurons. We implemented the ideas into self-organizing maps for structured data (SOM-SD) which is a more general form of self-organizing maps capable of processing graphs. The capabilities of the proposed ideas are …

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Self Organizing Maps For The Clustering Of Large Sets Of Labeled Graphs, Shujia Zhang, Markus Hagenbuchner, Ah Chung Tsoi, Milly Kc Dec 2012

Self Organizing Maps For The Clustering Of Large Sets Of Labeled Graphs, Shujia Zhang, Markus Hagenbuchner, Ah Chung Tsoi, Milly Kc

Dr Markus Hagenbuchner

Graph Self-Organizing Maps (GraphSOMs) are a new concept in the processing of structured objects using machine learning methods. The GraphSOM is a generalization of the Self-Organizing Maps for Structured Domain (SOM-SD) which had been shown to be a capable unsupervised machine learning method for some types of graphstructured information. An application of the SOM-SD to document mining tasks as part of an international competition: Initiative for the Evaluation of XML Retrieval (INEX), on the clustering of XML formatted documents was conducted, and the method subsequently won the competition in 2005 and 2006 respectively. This paper applies the GraphSOM to theclustering …

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Computational Capabilities Of Graph Neural Networks, Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, Gabriele Monfardini Dec 2012

Computational Capabilities Of Graph Neural Networks, Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, Gabriele Monfardini

Dr Markus Hagenbuchner

In this paper, we will consider the universal approximation properties of a recently introduced neural network model called graph neural network (GNN) which can be used to process structured data inputs, e.g. acyclic graph, cyclic graph, directed or un-directed graphs. This class of neural networks implements a function (G, n) 2 IRm that maps a graph Gand one of its nodes n onto an m-dimensional Euclidean space. We characterize the functions that can be approximated by GNNs, in probability, up to any prescribed degree of precision. This set contains the maps that satisfy a property, called preservation of the unfolding …

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The Graph Neural Network Model, Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, Gabriele Monfardini Dec 2012

The Graph Neural Network Model, Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, Gabriele Monfardini

Dr Markus Hagenbuchner

Many underlying relationships among data in several areas of science and engineering, e.g. computer vision, molecular chemistry, molecular biology, pattern recognition, data mining, can be represented in terms of graphs. In this paper, we propose a new neural network model, called graph neural network (GNN) model, that extends existing neural network methods for processing the data represented in the graph domain. This GNN model, which can directly process most of the practically useful types of graphs, e.g. acyclic, cyclic, directed, un-directed, implements a transduction function $\tau(\BG,n)\in\R^m$ that maps a graph $\BG$ and one of its nodes $n$ into an m-dimensional …

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"Kernalized" Self-Organizing Maps For Structured Data, F. Aiolli, G. Da San Martino, A. Sperduti, M. Hagenbuchner Dec 2012

"Kernalized" Self-Organizing Maps For Structured Data, F. Aiolli, G. Da San Martino, A. Sperduti, M. Hagenbuchner

Dr Markus Hagenbuchner

The suitability of the well known kernels for trees, and the lesser known Self- Organizing Map for Structures for categorization tasks on structured data is investigated in this paper. It is shown that a suitable combination of the two approaches, by defining new kernels on the activation map of a Self-Organizing Map for Structures, can result in a system that is significantly more accurate for categorization tasks on structured data. The effectiveness of the proposed approach is demonstrated experimentally on a relatively large corpus of XML formatted data.

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Building Mlp Networks By Construction, Ah Chung Tsoi, M. Hagenbuchner, A. Micheli Dec 2012

Building Mlp Networks By Construction, Ah Chung Tsoi, M. Hagenbuchner, A. Micheli

Dr Markus Hagenbuchner

We introduce two new models which are obtained through the modification of the well known methods MLP and cascade correlation. These two methods differ fundamentally as they employ learning techniques and produce network architectures that are not directly comparable. We extended the MLP architecture, and reduced the constructive method to obtain very comparable network architectures. The greatest benefit of these new models is that we can obtain an MLP-structured network through a constructive method based on the cascade correlation algorithm, and that we can train a cascade correlation structured network using the standard MLP learning technique. Additionally, we show that …

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Sparsity Issues In Self-Organizing-Maps For Structures, Markus Hagenbuchner, Giovanni Da San Martino, Ah Chung Tsoi, Alessandro Sperduti Dec 2012

Sparsity Issues In Self-Organizing-Maps For Structures, Markus Hagenbuchner, Giovanni Da San Martino, Ah Chung Tsoi, Alessandro Sperduti

Dr Markus Hagenbuchner

Recent developments with Self-Organizing Maps (SOMs) produced methods capable of clustering graph structured data onto a fixed dimensional display space. These methods have been applied successfully to a number of benchmark problems and produced state-of-the-art results. This paper discusses a limitation of the most powerful version of these SOMs, known as probability measure graph SOMs (PMGraphSOMs), viz., the sparsity induced by processing a large number of small graphs, which prevents a successful application of PMGraphSOM to such problems. An approach using the idea of compactifying the generated state space to address this sparsity problem is proposed. An application to an …

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Ranking Attack Graphs With Graph Neural Networks, Liang Lu, Rei Safavi-Naini, Markus Hagenbuchner, Willy Susilo, Jeffrey Horton, Sweah Liang Yong, Ah Chung Tsoi Dec 2012

Ranking Attack Graphs With Graph Neural Networks, Liang Lu, Rei Safavi-Naini, Markus Hagenbuchner, Willy Susilo, Jeffrey Horton, Sweah Liang Yong, Ah Chung Tsoi

Dr Markus Hagenbuchner

Network security analysis based on attack graphs has been applied extensively in recent years. The ranking of nodes in an attack graph is an important step towards analyzing network security. This paper proposes an alternative attack graph ranking scheme based on a recent approach to machine learning in a structured graph domain, namely, Graph Neural Networks (GNNs). Evidence is presented in this paper that the GNN is suitable for the task of ranking attack graphs by learning a ranking function from examples and generalizes the function to unseen possibly noisy data, thus showing that the GNN provides an effective alternative …

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