The objective of this study is to propose a model for planning course registration by using a data mining technique: Bayesian network. The proposed model can be used to predict the sequences of courses to be registere...
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ISBN:
(纸本)9781424414895
The objective of this study is to propose a model for planning course registration by using a data mining technique: Bayesian network. The proposed model can be used to predict the sequences of courses to be registered by undergraduate students whose majors are computerscience or engineering. The data set was obtained from student enrollments and include GPA and grades in each subject for first and second year students from a private university in Thailand. Evaluations show that the predictive power of this model is acceptable. The implications from this studypsilas findings suggest that the model can be applied for advising students in planning courses to be registered in each semester. Further, the model appears to be useful for improving curriculum development in order to fit both studentspsila and university requirements.
Nanoscale porous silicon waveguides, both on silicon substrates and free-standing membranes, are explored for biosensing applications. Measured detection limits in the nanomolar range are reported for DNA sensing. ...
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In this paper, we present a parallelization of a filtering algorithm related to non-linear anisotropic diffusion, used to enhance the performance of an application in a parallel distributed system. The anisotropic dif...
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ISBN:
(纸本)9780769532578
In this paper, we present a parallelization of a filtering algorithm related to non-linear anisotropic diffusion, used to enhance the performance of an application in a parallel distributed system. The anisotropic diffusion is a well-established technique for image enhancement by means of diffusivity functions, which act as border attenuators. However, it requires a high computational cost when a large amount of data is used. The proposed implementation was parallelized considering both point-to-point and collective communications, adopting the MPI paradigm. Results from both approaches indicate that the proposed algorithm has reached interesting levels of performance (81% and 93% of efficiency, respectively) when compared to the execution of one process in a single computer node. In addition, our results indicate an enhancement of around 21% utilizing the collective communication strategy when compared to point-to-point communication.
Given a percentage-threshold and readings from a pair of consecutive upstream and downstream sensors, flow anomaly discovery identifies dominant time intervals where the fraction of time instants of significantly mis-...
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Given a percentage-threshold and readings from a pair of consecutive upstream and downstream sensors, flow anomaly discovery identifies dominant time intervals where the fraction of time instants of significantly mis-matched sensor readings exceed the given percentage-threshold. Discovering flow anomalies (FA) is an important problem in environmental flow monitoring networks and early warning detection systems for water quality problems. However, mining FAs is computationally expensive because of the large (potentially infinite) number of time instants of measurement and potentially long delays due to stagnant (e.g. lakes) or slow moving (e.g. wetland) water bodies between consecutive sensors. Traditional outlier detection methods (e.g. t-test) are suited for detecting transient FAs (i.e., time instants of significant mis-matches across consecutive sensors) and cannot detect persistent FAs (i.e., long variable time-windows with a high fraction of time instant transient FAs) due to a lack of a pre-defined window size. In contrast, we propose a Smart Window Enumeration and Evaluation of persistence-Thresholds (SWEET) method to efficiently explore the search space of all possible window lengths. Computation overhead is brought down significantly by restricting the start and end points of a window to coincide with transient FAs, using a smart counter and efficient pruning techniques. Experimental evaluation using a real dataset shows our proposed approach outperforms Nainodotve alternatives.
This article presents the use of the Project-based Learning approach focused on knowledge exchange to improve the learning process. To reach this goal, we elaborate a learning project to teachs software design, suppor...
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In this paper we present the architecture for the Personal Autonomic Desktop Manager, a self managing application designed to act on behalf of the user in several aspects: protection, healing, optimization and configu...
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In this paper we present the architecture for the Personal Autonomic Desktop Manager, a self managing application designed to act on behalf of the user in several aspects: protection, healing, optimization and configuration. The overall goal of this research is to improve the correlation of the autonomic self{sup}* properties and doing so also enhance the overall self-management capacity of the desktop (autonomicity). We introduce the Circulatory Computing (CC) model, a self-managing system initiative based on the biological metaphor of the cardiovascular system, and use its concepts in the design and implementation of the architecture.
In this paper, a method of estimating both the position and the rotation angle of an object on a measurement stage was proposed. The system utilizes the radio communication technology and the directivity of an antenna...
In this paper, a method of estimating both the position and the rotation angle of an object on a measurement stage was proposed. The system utilizes the radio communication technology and the directivity of an antenna. As a prototype system, a measurement stage (a circle 240mm in diameter) with 36 antennas that placed in each 10 degrees was developed. Two transmitter antennas are settled in a right angle on the stage as the target object, and the position and the rotation angle is estimated by measuring efficiency of the radio communication of each 36 antennas. The experimental result revealed that even when the estimated location is not so accurate (about a 30 mm error), the rotation angle is accurately estimated (about 2.33 degree error on average). The result suggests that the proposed method will be useful for estimating the location and the direction of an object.
In this paper, a handle-electrode system is proposed for obtaining the heart rate of a user while riding a bicycle. The system was designed to measure the user's heart rate by only gripping the handle of a bicycle...
In this paper, a handle-electrode system is proposed for obtaining the heart rate of a user while riding a bicycle. The system was designed to measure the user's heart rate by only gripping the handle of a bicycle. Three electrodes made from conductive cloth were adhered to the handle. A method detecting heart-rate from the obtained electrocardiogram was also proposed. To assess the applicability of the proposed system, a simple experiment was performed. The experiment was performed in four conditions of road surfaces; lawn, asphalt, a tiled, and an uneven road. Experimental result suggests that the proposed system can be useful for obtaining R waves while riding a bicycle.
In this work we address two important issues of off-line signature verification. The first one regards feature extraction. We introduce a new graphometric feature set that considers the curvature of the main strokes o...
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In this work we address two important issues of off-line signature verification. The first one regards feature extraction. We introduce a new graphometric feature set that considers the curvature of the main strokes of the signature. The idea is to simulate the shape of the signature by using Bezier curves and then extract features from these curves. The second important aspect is the use of an ensemble of classifiers based on graphometric features to improve the reliability of the classification, hence reducing the false acceptance. The ensemble was built using a standard genetic algorithm and different fitness functions were assessed to drive the search. Thorough experiments were conduct on a database composed of 100 writers and the results compare favorably.
Decision-making involves choosing between one ore more alternatives, to achieve one or more goals. To support this process, there are decision support systems that employ different approaches, supporting groups or not...
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ISBN:
(纸本)9781424416509
Decision-making involves choosing between one ore more alternatives, to achieve one or more goals. To support this process, there are decision support systems that employ different approaches, supporting groups or not. Generally, however, these systems do not have great flexibility; their users have to follow pre- established decision methods. This paper, after exposing some decision-making processes, describes a system, LaSca (from Large Scale), to support decisions in large-scale groups. This system, besides allowing effective achievement of the benefits of deciding in large groups through the proper structuring of the group, also allows its users to define themselves how this structuring will happen, based or not in the existing theories on the subject. So, in addition to facilitate the decision-making process, LaSca also allows its users to decide how to decide.
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