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Konstantinos Gratsos , Stefanos Ougiaroglou and Dionisis Margaris
Partition-based clustering is widely applied over diverse domains. Researchers and practitioners from various scientific disciplines engage with partition-based algorithms relying on specialized software or programming libraries. Addressing the need to b...
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Zhixin Yao, Jianqin Zhang, Taizeng Li and Ying Ding
Trajectory big data is suitable for distributed storage retrieval due to its fast update speed and huge data volume, but currently there are problems such as hot data writing, storage skew, high I/O overhead and slow retrieval speed. In order to solve th...
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Jia Dong and Quan Qian
Many machine learning problem domains, such as the detection of fraud, spam, outliers, and anomalies, tend to involve inherently imbalanced class distributions of samples. However, most classification algorithms assume equivalent sample sizes for each cl...
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Elena Fedorchenko, Evgenia Novikova and Anton Shulepov
In order to provide an accurate and timely response to different types of the attacks, intrusion and anomaly detection systems collect and analyze a lot of data that may include personal and other sensitive data. These systems could be considered a sourc...
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Qurban A Memon
Pág. pp. 222 - 230
As technological advances in smartphone domain increase, so are the issues that pertain to security and privacy. In current literature, multimodal biometric approach is addressed at length for purpose of improving secured access into personal devices. Mo...
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Huaping Guo, Jun Zhou and Chang-An Wu
Classification of data with imbalanced class distribution has encountered a significant drawback by most conventional classification learning methods which assume a relatively balanced class distribution. This paper proposes a novel classification method...
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Huaping Guo, Jun Zhou and Chang-An Wu
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Maria Christoforaki and Oya Deniz Beyan
The use of artificial intelligence (AI) applications in a growing number of domains in recent years has put into focus the ethical, legal, and societal aspects (ELSA) of these technologies and the relevant challenges they pose. In this paper, we propose ...
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Xiangqiang Min, Dieter Pfoser, Andreas Züfle and Yehua Sheng
The range query is one of the most important query types in spatial data processing. Geographic information systems use it to find spatial objects within a user-specified range, and it supports data mining tasks, such as density-based clustering. In many...
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Aleksandar Dimitrijevic, Aleksandar Milosavljevic and Dejan Rancic
The rapid growth in Earth?s global geospatial data necessitates an efficient system for organizing the data, facilitating data fusion from diverse sources, and promoting interoperability. Mapping the spheroidal surface of the planet presents significant ...
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Fan Yang, You Li, Mingliang Che, Shihua Wang, Yingli Wang, Jiyi Zhang, Xinliang Cao and Chi Zhang
An increasing number of applications require the accurate 3D layout reconstruction of indoor environments. Various devices including laser scanners and color and depth (RGB-D) cameras can be used for this purpose and provide abundant and highly precise d...
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Chang Zhou, Huimei Lu, Yong Xiang, Jingbang Wu and Feng Wang
In the development of geographic information-based applications for mobile devices, achieving better access speed and visual effects is the main research aim. In this paper, we propose a new geographic data display method based on Geohash, namely Geohash...
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Fabio Sikansi, Renato R. O. da Silva, Gabriel D. Cantareira, Elham Etemad and Fernando V. Paulovich
Graph visualization has been successfully applied in a wide range of problems and applications. Although different approaches are available to create visual representations, most of them suffer from clutter when faced with many nodes and/or edges. Among ...
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Ignacio Pérez-Messina, Eduardo Graells-Garrido, María Jesús Lobo and Christophe Hurter
Pervasive data have become a key source of information for mobility and transportation analyses. However, as a secondary source, it has a different methodological origin than travel survey data, usually relying on unsupervised algorithms, and so it requi...
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Jiwei Qin, Liangli Ma and Jinghua Niu
The rapid development of distributed technology has made it possible to store and query massive trajectory data. As a result, a variety of schemes for big trajectory data management have been proposed. However, the factor of data transmission is not cons...
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Noriyuki Kushiro, Ami Fukuda, Masatada Kawatsu and Toshihiro Mega
In this study, methods for predicting energy demand on hourly consumption data are established for realizing an energy management system for buildings. The methods consist of an energy prediction algorithm that automatically separates the datasets to par...
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Pwint Phyu Khine and Zhaoshun Wang
The inevitability of the relationship between big data and distributed systems is indicated by the fact that data characteristics cannot be easily handled by a standalone centric approach. Among the different concepts of distributed systems, the CAP theo...
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Kelyn Schenatto, Eduardo Godoy Souza, Claudio Leones Bazzi, Vanderlei Arthur Bier, Nelson Miguel Betzek, Alan Gavioli
Pág. 31 - 40
Precision agriculture (PA) comprises the use of management zones (MZs). Sample data are usually interpolated to define MZs. Current research checks whether there is a need for data interpolation by evaluating the quality of MZs by five indices ? variance...
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Fernando Solano Donado
In this article, we design and evaluate several algorithms for the computation of the optimal Rice coding parameter. We conjecture that the optimal Rice coding parameter can be bounded and verify this conjecture through numerical experiments using real d...
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A K Srivastava,D Singh,A S Pandey,Sanjay Kumar
In this paper, electricity price forecasting using J48, Random forest and Bagging are used to effectively forecast the electricity price. These models are obtained by recursively partitioning the data space and fitting a simple prediction model within ea...
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