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Cheolhyeon Kwon and Donghyun Kang
Recently, the technologies of on-device AI have been accelerated with the development of new hardware and software platforms. Therefore, many researchers and engineers focus on how to enable ML technologies on mobile devices with limited hardware resourc...
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Eleni Vlachou, Aristeidis Karras, Christos Karras, Leonidas Theodorakopoulos, Constantinos Halkiopoulos and Spyros Sioutas
In this work, we present a Distributed Bayesian Inference Classifier for Large-Scale Systems, where we assess its performance and scalability on distributed environments such as PySpark. The presented classifier consistently showcases efficient inference...
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Yang Chao, Chaoning Lin, Tongchun Li, Huijun Qi, Dongming Li and Siyu Chen
Aiming to investigate the problem that dam-monitoring data are difficult to analyze in a timely and accurate automated manner, in this paper, we propose an automated framework for dam health monitoring based on data microservices. The framework consists ...
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Yang Shen, Changjiang Zheng and Fei Wu
Urban highway tunnels are frequent accident locations, and predicting and analyzing road conditions after accidents to avoid traffic congestion is a key measure for tunnel traffic operation management. In this paper, 200 traffic accident data from the Yi...
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Donghyun Kim, Heechan Han, Wonjoon Wang and Hung Soo Kim
Accurate water level prediction is one of the important challenges in various fields such as hydrology, natural disasters, and water resources management studies. In this study, a deep neural network and a long short-term memory model were applied for wa...
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Shengyang Li, Zhen Wang and Wanfeng Zhang
Cloud computing has become one of the key technologies used for big data processing and analytics. User management on cloud platforms is a growing challenge as the number of users and the complexity of systems increase. In light of the user-management sy...
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Zeqin Tian, Dengfeng Chen and Liang Zhao
Accurate building energy consumption prediction is a crucial condition for the sustainable development of building energy management systems. However, the highly nonlinear nature of data and complex influencing factors in the energy consumption of large ...
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Deokhwan Kim, Cheolhee Jang, Jeonghyeon Choi and Jaewon Kwak
As a significant portion of the available water resources in volcanic terrains such as Jeju Island are dependent on groundwater, reliable groundwater level forecasting is one of the important tasks for efficient water resource management. This study aims...
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Siyu Qi, Minxue He, Raymond Hoang, Yu Zhou, Peyman Namadi, Bradley Tom, Prabhjot Sandhu, Zhaojun Bai, Francis Chung, Zhi Ding, Jamie Anderson, Dong Min Roh and Vincent Huynh
Salinity management in estuarine systems is crucial for developing effective water-management strategies to maintain compliance and understand the impact of salt intrusion on water quality and availability. Understanding the temporal and spatial variatio...
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Huseyin Cagan Kilinc
Water, a renewable but limited resource, is vital for all living creatures. Increasing demand makes the sustainability of water resources crucial. River flow management, one of the key drivers of sustainability, will be vital to protect communities from ...
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Yongpeng Wang, Daisuke Watanabe, Enna Hirata and Shigeki Toriumi
In this study, we propose an effective method using deep learning to strengthen real-time vessel carbon dioxide emission management. We propose a method to predict real-time carbon dioxide emissions of the vessel in three steps: (1) convert the trajector...
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Otmane Azeroual
Databases such as research data management systems (RDMS) provide the research data in which information is to be searched for. They provide techniques with which even large amounts of data can be evaluated efficiently. This includes the management of re...
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Fatmaelzahraa Hussein, John Stephens and Reena Tiwari
Globalization is associated with significant transformations in city forms and cultural and social performances. Governments and cultural heritage organisations increasingly appreciate the importance of preserving diverse physical cultural heritage throu...
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Kyoung-Don Kang, Liehuo Chen, Hyungdae Yi, Bin Wang and Mo Sha
In data-intensive real-time applications, e.g., cognitive assistance and mobile health (mHealth), the amount of sensor data is exploding. In these applications, it is desirable to extract value-added information, e.g., mental or physical health condition...
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Kyoung-Don Kang, Liehuo Chen, Hyungdae Yi, Bin Wang and Mo Sha
In data-intensive real-time applications, e.g., cognitive assistance and mobile health (mHealth), the amount of sensor data is exploding. In these applications, it is desirable to extract value-added information, e.g., mental or physical health condition...
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Alberto-Jesús Perea-Moreno, María-Jesús Aguilera-Ureña, José-Emilio Meroño-De Larriva, Francisco Manzano-Agugliaro
Pág. 1 - 19
Golf courses can be considered as precision agriculture, as being a playing surface, their appearance is of vital importance. Areas with good weather tend to have low rainfall. Therefore, the water management of golf courses in these climates is a crucia...
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Alberto-Jesús Perea-Moreno, María-Jesús Aguilera-Ureña, José-Emilio Meroño-De Larriva and Francisco Manzano-Agugliaro
Golf courses can be considered as precision agriculture, as being a playing surface, their appearance is of vital importance. Areas with good weather tend to have low rainfall. Therefore, the water management of golf courses in these climates is a crucia...
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Hyewook Kim and Keumjin Lee
Accurate prediction of future air traffic situations is an essential task in many applications in air traffic management. This paper presents a new framework for predicting air traffic situations as a sequence of images from a deep learning perspective. ...
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Min Yue and Shuhong Ma
A crucial component of multimodal transportation networks and long-distance travel chains is the forecasting of transfer passenger flow between integrated hubs in urban agglomerations, particularly during periods of high passenger flow or unusual weather...
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Shuai Ma, Yafeng Wu, Hua Zheng and Linfeng Gou
Aiming at engine health management, a novel hybrid prediction method is proposed for exhaust gas temperature (EGT) prediction of gas turbine engines. This hybrid model combines a nonlinear autoregressive with exogenous input (NARX) model and a moving ave...
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