Volume 1 No 4 October 2007
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| 1. |
A Novel Technique for Pattern Extraction in Mixed Data Download PDF |
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Authors |
M. Karthikeyan, Krishnan Nallaperumal, K.Senthamaraikannan and K.Velu |
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Abstract |
- Knowledge discovery in databases or data mining is an important issue in the development of data and knowledge base system. The Self Organizing Map (SOM) is a vector quantization method which places the prototype vectors on a regular lowdimensional grid in an ordered fashion. Clustering data and extracting patterns from the clusters are very important tasks in data mining. An attribute-oriented induction method has been developed for knowledge discovery in databases. Clustering which groups similar objects into a single cluster. The objects in two clusters are dissimilar. On the other hand, pattern extraction, especially class description, generates descriptions for characterizing the data, providing a concise & sufficient summary. The objective of this task is to improve results of luster analysis by attribute-oriented induction. Unsupervised algorithms that solve the clustering problem, algorithm AOI is one of techniques of automatic generalization. We further discuss its implementation techniques, a generalized Self Organizing Map and an extended attribute-oriented induction (EAOI), which not only overcome the drawbacks of their original algorithms, but also provide additional analysis capabilities. GSOM has the capacity to handle categorical data and numerical values. The EAOI is the technique which displays or shows major values in the databases. |
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Keywords |
Attribute-oriented induction, clustering, data mining, pattern discovery and self-organizing map. |
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| 2. |
Design of Intelligent Self-Tuning Temperature Controller for Water Bath Process Download PDF |
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Authors |
Melba Mary.P, Marimuthu N.S Albert Singh. N |
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Abstract |
This paper proposes a novel approach based on self-tuning fuzzy logic control and genetic algorithm optimized fuzzy logic controller, for the design of a temperature control process, capable of providing optimal performance over the entire operating range of the process. The proposed control system combines the advantages of Genetic Algorithm and Fuzzy Logic Control schemes. In order to evaluate the performance of the proposed control system methods, results from simulation of the process are presented |
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Keywords |
Genetic Algorithm (GA), Fuzzy Logic Control (FLC) |
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| 3. |
Enhanced QoS Mechanism using Mobile Agents in Wireless Sensor Networks Download PDF |
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Authors |
Mrs. B. Amutha , S. Arun Kumar , Dr. M. Ponnavaikko |
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Abstract |
Wireless Sensor Networks can be used for a wide range of battlefield applications such as target tracking and emergency response. These networks have some specific types of requirements, such as diverse real time requirements, diverse reliability requirements and mixture of periodic and a periodic data. QoS is a challenging problem due to dynamic topology change, large data transfer and unreliable wireless link in wireless sensor networks. We have introduced a new protocol, which provides enhanced QoS mechanism in terms of high reliability, less latency and reduced power consumption through a probabilistic approach, which improves the lifetime of a wireless sensor as a trust ware. Mobile agents are used for automation and dynamism to the adaptation of software in wireless sensor networks. The novel approach provides enhanced QoS mechanism through dynamic software to guide the system adaptation. Mobile agents are used to form adaptation feedback on to the running system. Thus our approach is a complimentary over all other existing systems in this area |
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Keywords |
Distributed Sensor Networks, Mobile Agents, Processing Element, Dynamic software adaptation |
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| 4. |
A Topology of Specialized Brokers for Computational Grid Download PDF |
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Authors |
K Narmadha, S Thamarai Selvi |
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Abstract |
Computational grid comprises compute resources like PCs, clusters etc. The topology of brokers is very important in order to increase the scalability and fault – tolerance in a grid. The existing broker topologies are designed in such a way that the users and resource providers are bound to a single broker. Hence they have no choice in choosing the broker even if the brokers are biased. Moreover a single broker may not scale well if the number of entities bound to it increases and it also represents a single point failure. Hence a scalable and fault – tolerant topology of specialized brokers for computational grid is proposed in this paper in which the users and resource providers are not bound to any particular broker. So they are free to choose the broker according to their choice. The topology is designed in such a way that each broker is specialized in one type of resource. |
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| 5. |
A Soft Computing Model for Knowledge Mining and Trifle Management Download PDF |
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Authors |
M. Karthikeyan, Krishnan Nallaperumal, K.Senthamaraikannan, K.Velu and B.Bensujin |
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Abstract |
The entire information or the evidence about a terrorist and the inclined behavior of some personalities are stored in an Interactive XML sheet (I XML), which are called as trifles, the piece of information. These trifles plays a vital role in the training the soft computing model and for pattern detection. These trifles in the form of I-XML sheets are given in the network for pattern detection which will be able to justify the hypothesis, or negate the hypothesis. The soft computing model used here was the Competitive neural tree (CNet). The CNet is the type of decision tree in which each node is compared a decision will be take to move to the next .In CNet each node will compete to match its pattern with the input arriving the node. If any node matches with the input, then the pattern is recognized and the hypothesis is justified. In each stage the pattern recognition is done with the contents of the I-XML nodes. |
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Keywords |
CNet, Decision Tree, hypothesis I-XML, pattern recognition, soft computing, and trifles |
