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Camille Champion, Anne-Claire Brunet, Rémy Burcelin, Jean-Michel Loubes and Laurent Risser
In this paper, we present a new framework dedicated to the robust detection of representative variables in high dimensional spaces with a potentially limited number of observations. Representative variables are selected by using an original regularizatio...
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Marian B. Gorzalczany and Filip Rudzinski
In this paper, we briefly present several modifications and generalizations of the concept of self-organizing neural networks?usually referred to as self-organizing maps (SOMs)?to illustrate their advantages in applications that range from high-dimension...
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Jeongseon Kim, Soohwan Jeong and Sungsu Lim
Attempts to discover knowledge through data are gradually becoming diversified to understand complex aspects of social phenomena. Graph data analysis, which models and analyzes complex data as graphs, draws much attention as it combines the latest machin...
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Yunus Dogan, Feristah Dalkiliç, Alp Kut, Kemal Can Kara and Uygar Takazoglu
Large numbers of job postings with complex content can be found on the Internet at present. Therefore, analysis through natural language processing and machine learning techniques plays an important role in the evaluation of job postings. In this study, ...
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Irina Bazhenova,Tokhir Umarov
Pág. 81 - 89
The article is devoted to the study of methods of extracting causal relationships from unstructured text in a natural language. Automatic extraction of causal relationships from natural language texts is a complex open problem in artificial intelligence....
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Daiwei Zhang, Chunyang Ying, Lei Wu, Zhongqiu Meng, Xiaofei Wang and Youhua Ma
Timely and accurate extraction of crop planting structure information is of great importance for food security and sustainable agricultural development. However, long time series data with high spatial resolution have a much larger data volume, which ser...
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Luca Cappelletti, Tommaso Fontana, Guido Walter Di Donato, Lorenzo Di Tucci, Elena Casiraghi and Giorgio Valentini
Missing data imputation has been a hot topic in the past decade, and many state-of-the-art works have been presented to propose novel, interesting solutions that have been applied in a variety of fields. In the past decade, the successful results achieve...
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Jae Yun Lee, Young Geun Yoon, Tae Keun Oh, Seunghee Park and Sang Il Ryu
In the construction industry, it is difficult to predict occupational accidents because various accident characteristics arise simultaneously and organically in different types of work. Furthermore, even when analyzing occupational accident data, it is d...
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Jixiang Zhu, Miao Gao, Anmin Zhang, Yingjun Hu and Xi Zeng
In order to detect multi-ship encounter situations and improve the safety of navigation, this paper proposed a model which was able to mine multi-ship encounter situations from Automatic identification system (AIS) data and analyze the encounter spatial-...
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Danny D?Agostino, Matteo Diez, Mario Felli and Andrea Serani
This study investigates the underlying mechanisms governing the evolution of tip vortices in the far field of a naval propeller wake. To achieve this, a novel approach utilizing data clustering applied to particle image velocimetry snapshots is employed....
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Yuko Terada, Kenjiro Tanaka, Minami Matsuyama, Masaya Fujitani, Masatoshi Shibuya, Yoshihiko Yamamoto, Ryuji Kato and Keisuke Ito
Because transient receptor potential ankyrin 1 (TRPA1) is involved in various physiological functions, TRPA1-targeting drugs have been energetically developed. Although TRPA1 is considered a multimodal receptor, the structural diversity of TRPA1 agonists...
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Yufeng Huang, Jun Tao, Gang Sun, Hao Zhang and Yan Hu
In this study, a prognostics and health management (PHM) framework is proposed for aero-engines, which combines a dynamic probability (DP) model and a long short-term memory neural network (LSTM). A DP model based on Gaussian mixture model-adaptive densi...
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Yuchang Sun, Jingsong Ma, Jiangfeng She, Qiang Zhao and Lixia He
Complex 3D building models, because of their huge data volume, almost always result in transmission congestion, which leads to poor user experience. To reduce the real-time transmission pressure, a novel view-dependent progressive transmission method was...
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Changlock Choi and Seong-Yun Hong
The increasing use of mobile devices and the growing popularity of location-based ser-vices have generated massive spatiotemporal data over the last several years. While it provides new opportunities to enhance our understanding of various urban dynamics...
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Amgad Agoub and Martin Kada
Understanding how cities evolve through time and how humans interact with their surroundings is a complex but essential task that is necessary for designing better urban environments. Recent developments in artificial intelligence can give researchers an...
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Lianhui Wang, Pengfei Chen, Linying Chen and Junmin Mou
The Automatic Identification System (AIS) of ships provides massive data for maritime transportation management and related researches. Trajectory clustering has been widely used in recent years as a fundamental method of maritime traffic analysis to pro...
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Konstantinos Kapadais, Iraklis Varlamis, Christos Sardianos and Konstantinos Tserpes
The problem of unmanned supervision of maritime areas has attracted the interest of researchers for the last few years, mainly thanks to the advances in vessel monitoring that the Automatic Identification System (AIS) has brought. Several frameworks and ...
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Salaheddin Hosseinzadeh, Hadi Larijani, Krystyna Curtis and Andrew Wixted
This article proposes an adaptive-network-based fuzzy inference system (ANFIS) model for accurate estimation of signal propagation using LoRaWAN. By using ANFIS, the basic knowledge of propagation is embedded into the proposed model. This reduces the tra...
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Elena Kourti, Christina Christodoulou, Loukas Dimitriou, Symeon Christodoulou, Constantinos Antoniou
Pág. 675 - 684
In recent years, mobility patterns have reasonably attracted scientific interest, especially concerning Mega-Cities. The technological advances, especially concerning sensors, facilitates the collection and access on a massive amount of empirical data ca...
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Fang Wang, Xueliang Fu, Weijun Duan, Buyu Wang and Honghui Li
The utilization of ear tags for identifying breeding pigs is a widely used technique in the field of animal production. Ear tag dropout can lead to the loss of pig identity information, resulting in missing data and ambiguity in production management and...
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