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Recently, Malaysia has been reported with dengue epidemic, that could rise up to 120, 000 cases recorded per year. This serious issue needs a vital look to prevent the dengue occurrences as it has no medicine yet to be found. Therefore, studies need to be done in order to prevent the dengue occurrences. This paper presents a high accuracy dengue occurrences prediction model which could forecast the...
With the expanding load on healthcare and consequent strain on budget, the demand for tools to increase efficiency in treatments is rising. The use of prediction models throughout the treatment to identify risk factors might be a solution. In this paper we present a novel implementation of a prediction tool and the first use of a dynamic predictor in vocational rehabilitation practice. The tool is...
Terms in source code have become extremely important in Software Engineering research. These ``important'' terms are typically used as input to research tools. Therefore, the quality of the output of these tools will depend on the quality of the term extraction technique. Currently, there is no definitive best technique for predicting the importance of terms during program comprehension. In my work,...
Dengue fever is one of the major health related issues as reported in World Health Organization (WHO). Therefore, a study is needed on the factors that influencing dengue incidences. This paper presents the influence of dengue incidence with dual climate variable in the 3D form scatter plot. Machine learning techniques such as clustering and regression is done to compare the sum square of residual...
The MoveUs project funded by the European Commission aims to foster sustainable eco-friendly mobility habits in cities. In this context predicting the traffic flow is useful for managers to optimize the configuration of the road network towards reducing the congestions and ultimately, the pollution. With the explosion of the so-called Big Data concept and its application to traffic data, a wide range...
Link prediction is an important issue in Social Network Analysis area. Most of the existing link prediction methods aim to find the missing links or to predict the future links mainly based on a static network, ignoring the evolution of the network over time. This paper proposes a link prediction method that can learn from network dynamics. Using machine learning techniques, the method models the...
In the past decade, we have witnessed an explosive growth of the Web, online communities, and social media. This has led to a substantial increase in the range and scope of electronic communication and distributed collaboration. In distributed teams, social communication is thought to be critical for creating and sustaining relationships, but there is often limited opportunity for team members to...
In this study we investigate the transferability of trained regression models to estimate solo run L2 cache stress of programs running on multi-core processors. We used machine learning to generate the trained regression models. Transferability of a regression model means how useful is a regression model (which is trained on one architecture) to predict the solo run L2 cache stress on another architecture...
Visual tracking of articulated objects in real 3D space is challenging with applications in advanced human–computer interfaces and gesture semantic understanding. In this paper, graphical model, constructing articulated human hand, and NBP algorithm embedded with CAMSHIFT, inferencing hand configuration in 3D space, are applied for visual hand tracking. We also introduce image depth cue captured by...
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