Expert systems are AI's greatest commercial success. It is a research-oriented application area of AI. An expert system uses knowledge specific to a problem domain to provide “expert quality” performance. Predic...
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Expert systems are AI's greatest commercial success. It is a research-oriented application area of AI. An expert system uses knowledge specific to a problem domain to provide “expert quality” performance. Predicate logic is being used for knowledge representation which is further programmed using PROLOG inference engine for deriving intelligent conclusions. The current research paper introduces a rule-based expert system that provides a medical diagnosis for determining the health problems and classification of birds and animals. The user has to have some knowledge about these topics so that he can query the system. Three knowledge bases are provided for each domain. The specialized computer language PROLOG embedded into J2SE is used to develop this system.
In this paper the support vector machine is utilized to recognize the object from the given image. The proposed method for object recognition is associated with the reduction of feature vector by Kernel Principal Comp...
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In this paper the support vector machine is utilized to recognize the object from the given image. The proposed method for object recognition is associated with the reduction of feature vector by Kernel Principal Component Analysis (KPCA) and recognition using the Support Vector Machine (SVM) classifier. Also in this paper the feature extraction method extracts features from global descriptors of the image. In the feature extraction process for an image, global features are extracted and formed as feature vector. For the entire training image the feature vector is generated and dimension reduction is done using KPCA. The reduced feature vector is used to train the SVM classifier. Later test images are given as input and tested the performance of the Classifier. To prove the efficiency of the SVM Classifier, Back Propagation Neural Network is used for the object recognition. From the comparison, SVM classifier outperforms.
Recently Wireless Sensor Network Services have potential usage in a wide range of application domain. However due to the solid and mature advancement of SWE standard, there is still one challenge is left that has to b...
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Recently Wireless Sensor Network Services have potential usage in a wide range of application domain. However due to the solid and mature advancement of SWE standard, there is still one challenge is left that has to be addressed within this context i.e. discovery of Sensor Web Registry services throughout heterogeneous environment which raises several concerns like performance, reliability, and robustness. Many approaches and frameworks have been proposed to discover the sensor web registry services. Some of the approaches assume that the requests are placed in SOAP compatible formats while others focus on GUI based parametric query processing. We have formulated an approach that uses the Natural Language Query Processing which is a convenient and easy method of sensor data access in comparison to SQL or XML based Query Language like XQuery and XPath. We propose an architecture based on Multi-layered SOA Framework that organizes the method of sensor web registry service discovery in an efficient and structured manner by adding some new layers like Request Parser & Query Generator(RPQ), Service Verifier and Certifier (SVC) and Service Rank Calculator(SRC). We describe a typical weather sensor web service discovery where RPQ facilitates the processing of plain text request query to a most appropriate weather sensor web service and also an algorithm with implementation for a complete cycle of suitable sensor web registry service discovery according to requester's functional and QoS requirements.
Sensor Web Services has potential usage in a wide range of application domain. However due to advancement of OGC SWE standard, there are still challenges left that has to be addressed within the context of discovery o...
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Sensor Web Services has potential usage in a wide range of application domain. However due to advancement of OGC SWE standard, there are still challenges left that has to be addressed within the context of discovery of Sensor Web Registry services throughout heterogeneous environment which raises several concerns like performance, reliability, and robustness. Many approaches and frameworks have been proposed to discover the sensor web registry services and some of the approaches assume that the requests are placed in SOAP compatible formats while others focus on GUI based parametric query processing. In this paper an approach has been proposed that uses the Natural Language Query Processing which is a convenient and easy method of sensor data access in comparison to SQL or XML based Query Language like XQuery and XPath. An architecture based on Multi-layered SOA Framework that organizes the method of sensor web registry service discovery in an efficient and structured manner has been suggested by adding some new layers like Request Parser & Query Generator (RPQ), Service Verifier and Certifier (SVC) and Service Rank Calculator (SRC). A typical weather sensor web service discovery where RPQ facilitates the processing of plain text request query to a most appropriate weather sensor web service and also an algorithm with implementation for a complete cycle of suitable sensor web registry service discovery according to requester's functional and QoS requirements has been provided.
In this paper, we propose an IDML tools which can provide teachers a humanoid robot to help them for engaging teaching activities in a classroom. Teachers can use this humanoid robot as a teaching assistant for provid...
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In this paper, we propose an IDML tools which can provide teachers a humanoid robot to help them for engaging teaching activities in a classroom. Teachers can use this humanoid robot as a teaching assistant for providing an interactive learning experience to students. In order to evaluate the teaching efficacy of humanoid robot, we conducted a trial experiment in the primary education. Formative evaluations of the experiments not only proved that the humanoid robot can promote students' learning interest, but also found that humanoid robots have potential benefits for primary education and the possibility of robot-aided education in the classroom.
In recent years, graph representations have been used extensively for modelling complicated structural information, such as circuits, images, molecular structures, biological networks, weblogs, XML documents and so on...
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In recent years, graph representations have been used extensively for modelling complicated structural information, such as circuits, images, molecular structures, biological networks, weblogs, XML documents and so on. As a result, frequent subgraph mining has become an important subfield of graph mining. This paper presents a novel Frequent Pattern Graph Mining algorithm, FP-GraphMiner, that compactly represents a set of network graphs as a Frequent Pattern Graph (or FP-Graph). This graph can be used to efficiently mine frequent subgraphs including maximal fre- quent subgraphs and maximum common subgraphs. The algorithm is space and time efficient requiring just one scan of the graph database for the construction of the FP-Graph, and the search space is significantly reduced by clustering the subgraphs based on their frequency of occur- rence. A series of experiments performed on sparse, dense and complete graph data sets and a comparison with MARGIN, gSpan and FSMA us- ing real time network data sets confirm the efficiency of the proposed FP-GraphMiner algorithm.
We present a genetic algorithm based network intrusion detection system named IGIDS, where the genetic algorithm is used for pruning best individuals in the rule set database. The process makes the decision faster as ...
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The performance of wireless networks in the applications like transferring video files is subjected to dual constraints. Both minimization of power and other QoS requirements like delay, throughputs are have to be tak...
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The performance of wireless networks in the applications like transferring video files is subjected to dual constraints. Both minimization of power and other QoS requirements like delay, throughputs are have to be take care properly. Mobile Ad Hoc Networks are more perceptive to these issues where each mobile device is active like a router and consequently, routing delay adds considerably to overall end-to-end delay. This paper presents a survey on power efficient routing protocols for Mobile Ad-Hoc Networks. This survey centered on recent progress on power saving algorithms. In addition we suggest one energy efficient technique which will reduce energy consumption as well as increase the lifetime of node and network.
With the rapid growth in the area of wireless networks and mobile applications, Quality of Service (QoS) provision has received the attention of researchers. But unpredictable nature of Mobile Adhoc Networks makes it ...
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With the rapid growth in the area of wireless networks and mobile applications, Quality of Service (QoS) provision has received the attention of researchers. But unpredictable nature of Mobile Adhoc Networks makes it a very difficult task. Various QoS based protocols have been proposed by the researchers. These protocols make use of either proactive (table-driven) or reactive (on-demand) approach. Table driven approach requires a large amount of storage space to store the information regarding whole of the network which is not possible in case of small mobile devices. On the other hand, due to flooding of RREQ packets, on-demand routing protocols consumes a large amount of bandwidth and thus increases the network load. Also, there is a transmission delay for the first data packet. This paper presents an optimized approach for providing QoS in a location aware environment.
This paper presents the evolution and importance of clustering techniques, since clustering is unsupervised learning and there are many clustering methods in practice which results in which clustering scheme to be sel...
This paper presents the evolution and importance of clustering techniques, since clustering is unsupervised learning and there are many clustering methods in practice which results in which clustering scheme to be selected for our purpose .Here we take four clustering methodologies crisp Juzzy rough and rough fuzzy. These clustering methods have been implemented and its importance over one another is explained. And the suitable clustering method over these three has been identified for better perspective. The experiment results with the sample dataset illustrate the importance of clustering schemes.
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