Air pollution, a major global concern resulting in numerous annual fatalities, has been associated with various health disorders. This study focuses on understanding the impact of residing in heavily polluted cities o...
Air pollution, a major global concern resulting in numerous annual fatalities, has been associated with various health disorders. This study focuses on understanding the impact of residing in heavily polluted cities on mental and behavioral patterns, specifically exploring the potential link between air pollution and autism. Supervised classification algorithms, including logistic regression, random forest, decision tree, and AdaBoost, were employed to predict the risk of autism in individuals residing in severely polluted countries by 2030. The research aims to identify the relationship between genetic variations in adults with Autism Spectrum Disorder (ASD) and harmful air pollutants, investigate gender differences in autism frequency, and determine the neurotoxicant posing the greatest danger for neurodegeneration and its impact on autistic individuals. This study successfully employed supervised classification models to uncover hidden patterns between air pollution and autism risk. The binary prediction model achieved an average accuracy of 70%, with the AdaBoost algorithm demonstrating the highest accuracy at 73% in predicting autism prevalence. Increased PM2.5 concentrations correlated with higher autism risk compared to other neurotoxicants. These findings underscore the importance of sustainable practices and pollution reduction to safeguard human health.
To enable discovery in large, heterogenious information networks a tool is needed that allows exploration in changing graph structures and integrates advanced graph mining methods in an interactive visualization frame...
详细信息
The physics-based simulation game Angry Birds has been heavily researched by the AI community over the past five years, and has been the subject of a popular AI competition that is currently held annually as part of a...
详细信息
In social bookmark tools users are setting up lightweight conceptual structures called folksonomies. Currently, the information retrieval support is limited. We present a formal model and a new search algorithm for fo...
详细信息
In social bookmark tools users are setting up lightweight conceptual structures called folksonomies. Currently, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset. A long version of this paper has been published at the European Semantic Web Conference 2006 [3].
Becausemining complete set of frequent patterns from dense database could be impractical, an interesting alternative has been proposed recently. Instead of mining the complete set of frequent patterns, the new model o...
详细信息
Becausemining complete set of frequent patterns from dense database could be impractical, an interesting alternative has been proposed recently. Instead of mining the complete set of frequent patterns, the new model only finds out the maximal frequent patterns, which can generate all frequent patterns. FP-growth algorithm is one of the most efficient frequent-pattern mining methods published so far. However,because FP-tree and conditional FP-trees must be two-way traversable, a great deal memory is needed in process of mining. This paper proposes an efficient algorithm Unid_FP-Max for mining maximal frequent patterns based on unidirectional FP-tree. Because of generation method of unidirectional FP-tree and conditional unidirectional FP-trees, the algorithm reduces the space consumption to the fullest extent. With the development of two techniques:single path pruning and header table pruning which can cut down many conditional unidirectional FP-trees generated recursively in mining process, Unid_ FP-Max further lowers the expense of time and space.
Ecological Momentary Assessment (EMA) techniques gain more ground in studies and data collection among different disciplines. Decision tree algorithms and their ensemble variants are widely used for classifying this t...
详细信息
ISBN:
(纸本)9781509044603
Ecological Momentary Assessment (EMA) techniques gain more ground in studies and data collection among different disciplines. Decision tree algorithms and their ensemble variants are widely used for classifying this type of data, since they are easy to use and provide satisfactory results. However, most of these algorithms do not take into account the multiple levels (per-subject, per-day, etc.) in which EMA data are organized. In this paper we explore how the EMA data organization can be taken into account when dealing with decision trees and specifically how a combination of bagging and boosting can be utilized in a classification task. A new algorithm called BBT (standing for Bagged Boosted Trees) is proposed which is enhanced by an over/under sampling method leading to better estimates of the conditional class probability function. BBT's necessity and effects are demonstrated using both simulated datasets and real-world EMA data collected using a mobile application following the eating behavior of 100 people. Experimental analysis shows that BBT leads to clear improvements with respect to prediction error reduction and conditional class probability estimation.
One of the common choices when performing electrocardiographic imaging (ECGI) is that the cardiac geometry is in a static, diastolic state. To test the influence of this approximation, we compared epicardial potential...
详细信息
ISBN:
(数字)9781728169361
ISBN:
(纸本)9781728159423
One of the common choices when performing electrocardiographic imaging (ECGI) is that the cardiac geometry is in a static, diastolic state. To test the influence of this approximation, we compared epicardial potential maps and isochrones during systolic and diastolic geometries in four patients. Zero-th order Tikhonov regularization was used to reconstruct ventricular epicardial potentials. A spatiotemporal estimation method was then used to determine the activation and recovery times from the reconstructed epicardial electrograms. Activation times (AT), recovery times (RT) and electrogram correlation coefficients (CC) were compared for both geometries. Furthermore, CC and differences in AT/ RT were correlated against the linear movement and a substitute for rotational movement. Poor correlation was found between linear/rotational movement and reconstruction differences. Overall, agreement between epicardial potential maps and isochrones of both geometries was high when assessed quantitatively, but regional differences might occur for qualitative interpretation. These differences mostly occurred in areas of flat T-waves. This novel, more accurate quantification of the influence of assuming a diastolic geometry in ECGI may further help in interpreting ECGI measurements.
What-if analysis is an important type of DSS analysis processing procedure. It analyzes hypothetical scenarios based on historical data. The data cube view must be updated when the what-if condition is changed. Since ...
详细信息
The number of word embedding models is growing every year. Most of them are based on the co-occurrence information of words and their contexts. However, it is still an open question what is the best definition of cont...
详细信息
暂无评论