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Mihai Crengani?, Radu-Eugen Breaz, Sever-Gabriel Racz, Claudia-Emilia Gîrjob, Cristina-Maria Biri?, Adrian Maro?an and Alexandru Bârsan
This scientific paper presents the development and validation process of a dynamic model in Simulink used for decision-making regarding the locomotion and driving type of autonomous omnidirectional mobile platforms. Unlike traditional approaches relying ...
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Ramachandra Canumalla and Tanjore V. Jayaraman
Titanium alloys, with their low density, exceptional mechanical properties, and outstanding corrosion resistance, play a vital role in various aerospace applications. Our decision science-driven assessment focused on metastable ß, near-ß, a + ß, and near...
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Shweta More, Moad Idrissi, Haitham Mahmoud and A. Taufiq Asyhari
The rapid proliferation of new technologies such as Internet of Things (IoT), cloud computing, virtualization, and smart devices has led to a massive annual production of over 400 zettabytes of network traffic data. As a result, it is crucial for compani...
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Xuyuan Zhang, Yingqing Guo, Haoran Luo, Tao Liu and Yijun Bao
The rapid identification of the amount and characteristics of chemical oxygen demand (COD) in influent water is critical to the operation of wastewater treatment plants (WWTPs), especially for WWTPs in the face of influent water with a low carbon/nitroge...
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Wei Chen, Yishuai Tian, Yanhua Wang, Hang Yan and Yong Wang
As the size and complexity of cities around the world increase, various types of urban problems are emerging. These problems are caused by multiple factors that have complex relationships with each other. Addressing a single cause blindly may result in a...
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Liming Li and Zeang Zhao
To effectively enhance the adaptability of earthquake rescue robots in dynamic environments and complex tasks, there is an urgent need for an evaluation method that quantifies their performance and facilitates the selection of rescue robots with optimal ...
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Jean-Sébastien Dessureault, Félix Clément, Seydou Ba, François Meunier and Daniel Massicotte
The field of interior home design has witnessed a growing utilization of machine learning. However, the subjective nature of aesthetics poses a significant challenge due to its variability among individuals and cultures. This paper proposes an applied ma...
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Nguyet-Minh Nguyen, Reza Bahramloo, Jalal Sadeghian, Mehdi Sepehri, Hadi Nazaripouya, Vuong Nguyen Dinh, Afshin Ghahramani, Ali Talebi, Ismail Elkhrachy, Chaitanya B. Pande and Sarita Gajbhiye Meshram
The aim of this paper is to assess the extent to which the Sad-Kalan watershed in Iran participates in floods and rank the Sad-Kalan sub-watersheds in terms of flooding potential by utilizing multi-criteria decision-making approaches. We employed the ent...
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Mohammed Abaker, Hatim Dafaalla, Taiseer Abdalla Elfadil Eisa, Heba Abdelgader, Ahmed Mohammed, Mohammed Burhanur, Aiman Hasabelrsoul, Mohammed Ibrahim Alfakey and Mohammed Abdelghader Morsi
In recent years, several strategies have been introduced to enhance early warning systems and lower the risk of rock-falls. In this regard, this paper introduces a deep learning- and IoT-based framework for rock-fall early warning, devoted to reducing ro...
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Pascal Harth, Orlando Jähde, Sophia Schneider, Nils Horn and Rüdiger Buchkremer
In this research, we present an algorithm that leverages language-transformer technologies to automate the generation of product requirements, utilizing E-Shop consumer reviews as a data source. Our methodology combines classical natural language process...
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