|
|
|
Bahareh Kalantar, Husam A. H. Al-Najjar, Biswajeet Pradhan, Vahideh Saeidi, Alfian Abdul Halin, Naonori Ueda and Seyed Amir Naghibi
Assessment of the most appropriate groundwater conditioning factors (GCFs) is essential when performing analyses for groundwater potential mapping. For this reason, in this work, we look at three statistical factor analysis methods?Variance Inflation Fac...
ver más
|
|
|
|
|
|
|
Roberto Scigliano, Valeria De Simone, Roberta Fusaro, Davide Ferretto and Nicole Viola
The design of integrated and highly efficient solutions for thermal management is a key capability for different aerospace products, ranging from civil aircraft using hydrogen on board to miniaturized satellites. In particular, this paper discloses a nov...
ver más
|
|
|
|
|
|
|
Kangshen Xiang, Weijie Chen, Siddiqui Aneeb and Weiyang Qiao
Future UHBR (Ultra-High Bypass-Ratio) engines might cause serious ?turbine noise storms? but, at present, turbine noise prediction capability is lacking. The large turning angle of the turbine blade is the first major factor deserving special attention. ...
ver más
|
|
|
|
|
|
|
Ping Huang and Yafeng Wu
Airborne speech enhancement is always a major challenge for the security of airborne systems. Recently, multi-objective learning technology has become one of the mainstream methods of monaural speech enhancement. In this paper, we propose a novel multi-o...
ver más
|
|
|
|
|
|
|
Mingze Li, Bing Li, Zhigang Qi, Jiashuai Li and Jiawei Wu
Predicting ship trajectories plays a vital role in ensuring navigational safety, preventing collision incidents, and enhancing vessel management efficiency. The integration of advanced machine learning technology for precise trajectory prediction is emer...
ver más
|
|
|
|
|
|
|
José Miguel Rodrigues
The timely and precise prediction of flooding progression and its eventual outcome in ships with breached hulls can lead to dramatic improvements in maritime safety through improved guidance for both emergency response and ship design. The traditional ap...
ver más
|
|
|
|
|
|
|
Milica Colovic, Anna Maria Stellacci, Nada Mzid, Martina Di Venosa, Mladen Todorovic, Vito Cantore and Rossella Albrizio
This study analyzed the capability of aerial RGB (red-green-blue) and hyperspectral-derived vegetation indices to assess the response of sweet maize (Zea mays var. saccharata L.) to different water and nitrogen inputs. A field experiment was carried out ...
ver más
|
|
|
|
|
|
|
Wei Zhuang, Zhiheng Li, Ying Wang, Qingyu Xi and Min Xia
Predicting photovoltaic (PV) power generation is a crucial task in the field of clean energy. Achieving high-accuracy PV power prediction requires addressing two challenges in current deep learning methods: (1) In photovoltaic power generation prediction...
ver más
|
|
|
|
|
|
|
Mahammad Khalid Shaik Vadla, Mahima Agumbe Suresh and Vimal K. Viswanathan
Understanding customer emotions and preferences is paramount for success in the dynamic product design landscape. This paper presents a study to develop a prediction pipeline to detect the aspect and perform sentiment analysis on review data. The pre-tra...
ver más
|
|
|
|
|
|
|
Haojie Wang, Pingqing Fan, Xipei Ma and Yansong Wang
The intelligent identification of coal gangue on industrial conveyor belts is a crucial technology for the precise sorting of coal gangue. To address the issues in coal gangue detection algorithms, such as high false negative rates, complex network struc...
ver más
|
|
|
|