|
|
|
|
|
Juan Murillo-Morera, Carlos Castro-Herrera, Javier Arroyo, Ruben Fuentes-Fernandez
Pág. 114 - 137
Today, it is common for software projects to collect measurement data through development processes. With these data, defect prediction software can try to estimate the defect proneness of a software module, with the objective of assisting and guiding so...
ver más
|
|
|
|
|
|
|
|
|
|
|
Dongkeun Lee, Chaeog Lim, Sang-jin Oh, Minjoon Kim, Jun Soo Park and Sung-chul Shin
Capsizing accidents are regarded as marine accidents with a high rate of casualties per accident. Approximately 89% of all such accidents involve small ships (vessels with gross tonnage of less than 10 tons). Stability calculations are critical for asses...
ver más
|
|
|
|
|
|
|
|
|
|
|
Marcin Aftowicz, Ievgen Kabin, Zoya Dyka and Peter Langendörfer
While IoT technology makes industries, cities, and homes smarter, it also opens the door to security risks. With the right equipment and physical access to the devices, the attacker can leverage side-channel information, like timing, power consumption, o...
ver más
|
|
|
|
|
|
|
|
|
|
|
Donghyuk Kum, Jichul Ryu, Yongchul Shin, Jihong Jeon, Jeongho Han, Kyoung Jae Lim and Jonggun Kim
This study accounted for the importance of daily expansion flow data in compensating for insufficient flow data in a watershed. In particular, the 8-day interval flow measurement data (intermittent monitoring data) could cause uncertainty in the high- or...
ver más
|
|
|
|
|
|
|
|
|
|
|
Santiago Moreno-Carbonell and Eugenio F. Sánchez-Úbeda
The Linear Hinges Model (LHM) is an efficient approach to flexible and robust one-dimensional curve fitting under stringent high-noise conditions. However, it was initially designed to run in a single-core processor, accessing the whole input dataset. Th...
ver más
|
|
|
|
|
|
|
|
|
|
|
Syed As-Sadeq Tahfim and Yan Chen
Severe and fatal crashes involving large trucks result in significant social and economic losses for human society. Unfortunately, the notably low proportion of severe and fatal injury crashes involving large trucks creates an imbalance in crash data. Mo...
ver más
|
|
|
|
|
|
|
|
|
|
|
Juan Ma, Qiang Yang, Mingzhi Zhang, Yao Chen, Wenyi Zhao, Chengyu Ouyang and Dongping Ming
Accurately predicting landslide deformation based on monitoring data is key to successful early warning of landslide disasters. Landslide displacement?time curves offer an intuitive reflection of the landslide motion process and deformation predictions o...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chunru Cheng, Linbing Wang, Xingye Zhou and Xudong Wang
As the main cause of asphalt pavement distress, rutting severely affects pavement safety. Establishing an accurate rutting prediction model is crucial for asphalt pavement maintenance, pavement structure design, and pavement repair. This study explores f...
ver más
|
|
|
|
|
|
|
|
|
|
|
Rejath Jose, Faiz Syed, Anvin Thomas and Milan Toma
The advancement of machine learning in healthcare offers significant potential for enhancing disease prediction and management. This study harnesses the PyCaret library?a Python-based machine learning toolkit?to construct and refine predictive models for...
ver más
|
|
|
|
|
|
|
|
|
|
|
Juyao Wei, Zhenggang Lu, Zheng Yin and Zhipeng Jing
This paper presents a novel data-driven multiagent reinforcement learning (MARL) controller for enhancing the running stability of independently rotating wheels (IRW) and reducing wheel?rail wear. We base our active guidance controller on the multiagent ...
ver más
|
|
|
|
|
|