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Mariana Lourenço, Teresa Arrufat, Elena Satorres, Sara Maderuelo, Blanca Novillo-Del Álamo, Stefano Guerriero, Rodrigo Orozco and Juan Luis Alcázar
(1) Background: Accurate preoperative diagnosis of ovarian masses is crucial for optimal treatment and postoperative outcomes. Transvaginal ultrasound is the gold standard, but its accuracy depends on operator skill and technology. In the absence of expe...
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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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Anas A. Makki and Ammar Y. Alqahtani
This study analyzes the barriers to developing smart cities (SCs) using the decision-making trial and evaluation laboratory (DEMATEL) approach. The primary objective is to identify, classify, and assess the main barriers hindering the progress of SCs. Th...
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Svetlana S. Uvarova, Svetlana V. Belyaeva, Alexandr K. Orlov and Vadim S. Kankhva
Most large construction projects face the problem of cost overruns and failures to meet deadlines mainly due to changes in the cost of building materials. A lot of studies proved the high importance of the cost of building materials for the project budge...
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Mohammad Mahbubur Rahman Khan Mamun and Tarek Elfouly
Contemporary methods used to interpret the electrocardiogram (ECG) signal for diagnosis or monitoring are based on expert knowledge and rule-centered algorithms. In recent years, with the advancement of artificial intelligence, more and more researchers ...
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Meron Teferi Taye, Fasikaw Atanaw Zimale, Tekalegn Ayele Woldesenbet, Mulugeta Genanu Kebede, Selamawit Damtew Amare, Getachew Tegegne, Kirubel Mekonnen and Alemseged Tamiru Haile
Lack of consistent streamflow data has been an increasing challenge reported by many studies in developing countries. This study aims to understand the current challenges in streamflow monitoring in Ethiopia to prioritize research topics that can support...
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Fazlul Karim, Mohammed Ali Armin, David Ahmedt-Aristizabal, Lachlan Tychsen-Smith and Lars Petersson
Machine learning (also called data-driven) methods have become popular in modeling flood inundations across river basins. Among data-driven methods, traditional machine learning (ML) approaches are widely used to model flood events, and recently deep lea...
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Yasunari Matsuzaka and Ryu Yashiro
Computer vision is a branch of computer science that studies how computers can ?see?. It is a field that provides significant value for advancements in academia and artificial intelligence by processing images captured with a camera. In other words, the ...
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Benjamin Ruch, Margita Hefner and André Sradnick
Market gardening is a widespread practice of bio-intensive vegetable production characterized by direct marketing, small-scale farming structures, high crop densities, and innovative cultivation approaches. Currently, deep compost mulch (DCM) is a popula...
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Mohammed Taha Alqershy and Qian Shi
Social responsibility strategies are indispensable for the sustainable development of the Belt and Road Initiative (BRI). Nonetheless, the application of social responsibility (SR) policies in such mega infrastructure projects remains a pressing concern ...
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