The revolution in web world led to increasing users' needs, demands and expectations. By the time, those needs developed starting from ordinary static pages, moving on to fully dynamic ones and reaching the need f...
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The revolution in web world led to increasing users' needs, demands and expectations. By the time, those needs developed starting from ordinary static pages, moving on to fully dynamic ones and reaching the need for services and applications to be available on the web!.. Those demands changed the perspective of our web today to what's said to be a cloud of computing that aims mainly to provide applications as services for web user. As time goes by, applications were just not enough;users needed their applications and data available anytime, anywhere. For these reasons, traditional operating system functionality was needed to be provided as a service that integrates several applications together with user's data. In this paper we present the detailed description, implementation and evaluation of SEWOS [1]- a semantically enhanced web operating system- that provides the feel, look and mimic traditional desktop applications using desktop metaphor.
Least association rules are the association rules that consist of the least item. These rules are very important and critical since they can be used to detect the infrequent events and exceptional cases. However, the ...
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Least association rules are the association rules that consist of the least item. These rules are very important and critical since they can be used to detect the infrequent events and exceptional cases. However, the formulation of measurement to efficiently discover least association rules is quite intricate and not really straight forward. In educational domain, this information is very useful since it can be used as a base for investigating and enhancing the current educational standards and managements. Therefore, this paper proposes a new measurement called Critical Relative Support (CRS) to mine critical least association rules from educational context. Experiment with students’ examination result dataset shows that this approach can be used to reveal the significant rules and also can reduce up to 98% of uninterested association rules.
Switching estimated receiver position (SwERP) scheme is proved to be a promising solution for indoor positioning system, owing to its high achievable accuracy and consistency. The high positioning accuracy is achieved...
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Switching estimated receiver position (SwERP) scheme is proved to be a promising solution for indoor positioning system, owing to its high achievable accuracy and consistency. The high positioning accuracy is achieved from sensitivity (R x ,S) limit, field-of-view (FOV) limit, and assisted azimuth and tilt information from 6-axis sensor. In this paper, we propose a physical simulation model that can predict the latter three factors. The conventional visible light communication (VLC) model uses only geometric optics (GO) to predict light propagation, which is not enough to define the FOV limit. Thus, we propose a novel method using rotation matrix with cone function and support vector machines (SVMs) to classify the boundary of FOV limit. Based on sensitivity and FOV limits, possible azimuth and tilt angulations are mathematically defined. Moreover, by including FOV limit into the simulation, transmitters and their mirrors that are outside FOV limit can be neglected, of which reduce at least 80% of computation during GO calculation.
This paper compared ACF(Auto Correlation Feature) characteristics for ZCD, Kasami and Golay codes. Sequence codes have been used as a spreading sequence in order to overcome ICI(Inter Code Interference) caused by tran...
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This paper compared ACF(Auto Correlation Feature) characteristics for ZCD, Kasami and Golay codes. Sequence codes have been used as a spreading sequence in order to overcome ICI(Inter Code Interference) caused by transmitter and MPI(Multiple Path Interference) in receiver. In this paper, we abstracted characteristics of each spreading code and analyzed the properties of them.
Association Rules Mining is one of the popular techniques used in data mining. Positive association rules are very useful in correlation analysis and decision making processes. In educational context, determine a “ri...
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Association Rules Mining is one of the popular techniques used in data mining. Positive association rules are very useful in correlation analysis and decision making processes. In educational context, determine a “right” program to the students is very unclear especially when their chosen programs are not selected. In this case, normally they will be offered to other programs based on the programs availability and not according to their program's field interests. The main concern is, by assigning inappropriate program which is not reflected their overall interest; it may create serious problems such as poorly in academic commitment and academic achievement. Therefore, Therefore in this paper, we proposed a model which consists of pre-processing, mining patterns and assigning weight to discover highly positive association rules. We examined the previous chosen programs by computerscience students in our university for July 2008/2009 intake. The result shows that the proposed model can mine association rules with high correlation. Moreover, for data analysis, there are existed students that have been offered in computerscience program at our university but not within their program's field interests.
This paper presents a new speed controller based on the theory of adaptive fuzzy inference system based on neural (ANFIS) for a direct torque to twelve sectors controlled of the induction motor. The proposed controlle...
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This paper presents a new speed controller based on the theory of adaptive fuzzy inference system based on neural (ANFIS) for a direct torque to twelve sectors controlled of the induction motor. The proposed controller integrates fuzzy logic algorithm with a structure of artificial neural network (ANN) five-layer in order to reap the benefits of both methods, the learning abilities of the first and readability and flexibility of the second. The controller replaces the conventional PI is the rule fuzzy inference system with the hybrid learning algorithm. This makes learning the fuzzy system. The performance of the proposed neuro-fuzzy control for induction motor speed was studied at different operating conditions. The simulation study shows the robustness and relevance of control for applications in high performance driving.
In this study, a new type of trigonometric neural network is presented by adding frequency and phase to trigonometric activation functions. The proposed trigonometric neural network has more flexibility in comparison ...
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In this study, a new type of trigonometric neural network is presented by adding frequency and phase to trigonometric activation functions. The proposed trigonometric neural network has more flexibility in comparison with conventional trigonometric neural networks and even other types of neural networks. Due to the low convergence rate and high posibility of trapping in a local minimum of backpropagation algorithm, Extended Kalman Filter algorithm is used to train the neural network's parameters which they appear in a nonlinear form. The Simulation of the suggested neural network based on the prediction of Mackey-Glass time series and identification of a nonlinear dynamic ystem reveals the efficiency of the proposed network. To show the efficiency of this method, the results are compared with the results of the others.
As modern software systems operate in a highly dynamic context, they have to adapt their behaviour in response to changes in their operational environment or/and requirements. Triggering adaptation depends on detectin...
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As modern software systems operate in a highly dynamic context, they have to adapt their behaviour in response to changes in their operational environment or/and requirements. Triggering adaptation depends on detecting quality of service (QoS) violations by comparing observed QoS values to predefined thresholds. These threshold-based adaptation approaches result in late adaptations as they wait until violations have occurred. This may lead to undesired consequences such as late response to critical events. In this paper we introduce a statistical approach CREQA - Control Charts for the Runtime Evaluation of QoS Attributes. This approach estimates at runtime capability of a system, and then it monitors and provides early detection of any changes in QoS values allowing timely intervention in order to prevent undesired consequences. We validated our approach using a series of experiments and response time datasets from real world web services.
A model is proposed for selecting the optimal result of contractor selection under multi criteria environment. Fuzzy comparing judgment is used to tackling the vagueness and uncertainty in choosing significant prefere...
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A model is proposed for selecting the optimal result of contractor selection under multi criteria environment. Fuzzy comparing judgment is used to tackling the vagueness and uncertainty in choosing significant preferences by decision maker regarding to the subjective opinion. Finally, the model was tested in tender evaluation processes for awarding the most beneficial contractor to perform the construction project.
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