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7th IET Smart Cities Symposium (SCS 2023)

作者： R. Surendran M. S. Seena Aravind Swaminathan Joel Benjamin Julius Babu Visal Vinod Department of computer science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Science Chennai India Data Science Department of Computer Science Middlesex University Knowledge Park Dubai UAE

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.

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Temporal Pattern Mining from Evolving Networks

arXiv

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arXiv 2017年

作者： Impedovo, Angelo Loglisci, Corrado Ceci, Michelangelo University of Bari Aldo Moro Department of Computer Science Knowledge Discovery and Data Engineering Laboratory Bari70125 Italy

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On the integration of graph exploration and data analysis: The creative exploration toolkit

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2012年 7250卷 301-312页

作者： Haun, Stefan Gossen, Tatiana Nürnberger, Andreas Kötter, Tobias Thiel, Kilian Berthold, Michael R. Data and Knowledge Engineering Group Faculty of Computer Science Otto-von-Guericke-University Germany Department for Bioinformatics and Information Mining University of Konstanz Germany

ISBN: (纸本)9783642318290

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 framework. We present the Creative Exploration Toolkit (CET), which consists of a state-of-the-art user interface for graph visualization designed towards explorative tasks and support tools for integration and communication with external data sources and mining tools, especially the data-mining platform KNIME. All parts of the interface can be customized to fit the requirements of special tasks, including the use of node type dependent icons, highlighting of nodes and clusters. Through an evaluation we have shown the applicability of CET for structure-based analysis tasks. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： User interfaces

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The Computational Complexity of Angry Birds

arXiv

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arXiv 2018年

作者： Stephenson, Matthew Renz, Jochen Ge, Xiaoyu Department of Data Science and Knowledge Engineering Maastricht University Maastricht Netherlands Research School of Computer Science Australian National University Canberra Australia

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 leading AI conference. Developing intelligent agents that can play this game effectively has been an incredibly complex and challenging problem for traditional AI techniques to solve, even though the game is simple enough that any human player could learn and master it within a short time. In this paper we analyse how hard the problem really is, presenting several proofs for the computational complexity of Angry Birds. By using a combination of several gadgets within this game’s environment, we are able to demonstrate that the decision problem of solving general levels for different versions of Angry Birds is either NP-hard, PSPACE-hard, PSPACE-complete or EXPTIME-hard. Proof of NP-hardness is by reduction from 3-SAT, whilst proof of PSPACE-hardness is by reduction from True Quantified Boolean Formula (TQBF). Proof of EXPTIME-hardness is by reduction from G2, a known EXPTIME-complete problem similar to that used for many previous games such as Chess, Go and Checkers. To the best of our knowledge, this is the first time that a single-player game has been proven EXPTIME-hard. This is achieved by using stochastic game engine dynamics to effectively model the real world, or in our case the physics simulator, as the opponent against which we are playing. These proofs can also be extended to other physics-based games with similar mechanics. Copyright © 2018, The Authors. All rights reserved.

关键词： Computational complexity

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Folkrank: A ranking algorithm for folksonomies

Folkrank: A ranking algorithm for folksonomies

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Workshop-Woche on Lernen, Wissen und Adaptivitat, LWA 2006

作者： Hotho, Andreas Jäschke, Robert Schmitz, Christoph Stumme, Gerd Knowledge and Data Engineering Group Department of Mathematics and Computer Science University of Kassel Wilhelmshöher Allee 73 D34121 Kassel Germany Research Center L3S Expo Plaza 1 D30539 Hannover Germany

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].

关键词： Semantic Web

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Mining Maximal Frequent Patterns in a Unidirectional FP-tree

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Journal of Donghua University(English Edition) 2006年第6期000卷 105-109页

作者： SONG Jing-jing LIU Rui-xin WANG Yan JIANG Bao-qing SONG Jing-jing(Institute of Data and Knowledge Engineering Henan University Kaifeng 475001) LIU Rui-xin(Information Engineering Science Department Yellow River Conservancy Technical Institute Kaifeng 475003) WANG Yan(Institute of Data and Knowledge Engineering Henan University Kaifeng 475001 Department of Computer Science and Application Zhengzhou Institute of Aeronautical Industry Management Zhengzhou 450015)

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.

关键词： data mining frequent pattern the maximal frequent pattern Unid _ FP-tree conditional Unid _ FP-tree

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Enhancing Classification of Ecological Momentary Assessment data Using Bagging and Boosting

Enhancing Classification of Ecological Momentary Assessment ...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Gerasimos Spanakis Gerhard Weiss Anne Roefs Department of Data Science and Knowledge Engineering Maastricht University Maastricht Netherlands Faculty of Psychology and Neuroscience Maastricht University Maastricht Netherlands

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.

关键词： Bagging Boosting Decision trees Training data Vegetation Training Biological system modeling

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The Influence of Using a Static Diastolic Geometry in ECG Imaging

The Influence of Using a Static Diastolic Geometry in ECG Im...

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Computers in Cardiology (CinC)

作者： Job Stoks Matthijs J.M. Cluitmans Ralf Peeters Paul G.A. Volders Department of Cardiology Maastricht University Medical Centre Maastricht The Netherlands Data Science and Knowledge Engineering Maastricht University Maastricht The Netherlands

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.

关键词： Geometry Heart Correlation Electric potential Image reconstruction Surface reconstruction Correlation coefficient

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Incremental computation for MEDIAN cubes in what-if analysis

Incremental computation for MEDIAN cubes in what-if analysis

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Joint International Conference on Advances in data and Web Management, APWeb/WAIM 2009

作者： Xiao, Yanqin Zhang, Yansong Wang, Shan Chen, Hong Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE Beijing 100872 China School of Information Renmin University of China Beijing 100872 China Computer Center Hebei University Baoding Hebei 071002 China Department of Computer Science Harbin Finance College Harbin 150030 China

ISBN: (纸本)9783642006715

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 source data must be kept in order to compute the new aggregate value when new tuples are inserted or deleted, in what-if analysis, incrementally computing a data cube for holistic aggregation functions is a difficult problem. In this paper, we adopt delta cube strategy and work area technique to incrementally compute data cube for MEDIAN function. The size of work area has important influence on the efficiency of the incremental computing. This paper optimizes the size of work area based on the number and the cardinality of dimension attributes of the cuboid. Performance study shows that our algorithms are effective over large databases. © Springer-Verlag Berlin Heidelberg 2009.

关键词： Geometry

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Investigating different syntactic context types and context representations for learning word embeddings

Investigating different syntactic context types and context ...

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2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017

作者： Li, Bofang Liu, Tao Zhao, Zhe Tang, Buzhou Drozd, Aleksandr Rogers, Anna Du, Xiaoyong School of Information Renmin University of China China Key Laboratory of Data Engineering and Knowledge Engineering MOE China Shenzhen Graduate School Harbin Institute of Technology China Global Scientific Information and Computing Center Tokyo Institute of Technology China Department of Computer Science University of Massachusetts Lowell United States

ISBN: (纸本)9781945626838

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 context. We provide a systematical investigation of 4 different syntactic context types and context representations for learning word embeddings. Comprehensive experiments are conducted to evaluate their effectiveness on 6 extrinsic and intrinsic tasks. We hope that this paper, along with the published code, would be helpful for choosing the best context type and representation for a given task. © 2017 Association for Computational Linguistics.

关键词： Embeddings

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