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Om Prakash Sharma, Narayanan Kannan, Scott Cook, Bijay Kumar Pokhrel and Cameron McKenzie
Most of the recent studies on the consequences of extreme weather events on crop yields are focused on droughts and warming climate. The knowledge of the consequences of excess precipitation on the crop yield is lacking. We attempted to fill this gap by ...
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Slavica Stevanovic, Jelena Minovic, Isidora Ljumovic
Research Question: This paper examines the impact of liquidity on the profitability of the Serbian polluting medium sized enterprises. Motivation: We study the impact of traditional liquidity indicators and indicators based on cash flow on the profitabil...
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Maja Jandric
Research Question: The aim of this paper is to construct a numerical measure of EPL which takes into consideration the implementation of legislation and employment structure. Motivation: It is recognized in the literature that in countries with a signifi...
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Álvaro V. Ramírez-Alujas
Pág. pp. 5 / 50
Junto con debatir el concepto, aplicación y desarrollo de la innovación en el sector público, el artículo propone una agenda de transformación de las organizaciones públicas hacia un modelo de gobernanza colaborativa en el marco de las iniciativas de gob...
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Haneul Lee and Seokheon Yun
Accurately predicting construction costs during the initial planning stages is crucial for the successful completion of construction projects. Recent advancements have introduced various machine learning-based methods to enhance cost estimation precision...
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Hyojae Jung and Chanjin Chung
This study estimates consumers? willingness to pay (WTP) for sustainability turfgrass attributes such as low-input and stress-tolerance attributes, while considering potential trade-off relationships between aesthetic attributes and sustainability attrib...
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Xiaoou Li
This paper tackles the challenge of time series forecasting in the presence of missing data. Traditional methods often struggle with such data, which leads to inaccurate predictions. We propose a novel framework that combines the strengths of Generative ...
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Sara Rajaram and Cassie S. Mitchell
The ability to translate Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) into different modalities and data types is essential to improve Deep Learning (DL) for predictive medicine. This work presents DACMVA, a novel framework ...
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Yongbo Liu, Peng He, Yan Cao, Conghua Zhu and Shitao Ding
A critical precondition for realizing mechanized transplantation in rice cultivation is the implementation of seedling tray techniques. To augment the efficacy of seeding, a precise evaluation of the quality of rice seedling cultivation in these trays is...
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Atefe Sedaghat, Homayoon Arbabkhah, Masood Jafari Kang and Maryam Hamidi
This research introduces an online system for monitoring maritime traffic, aimed at tracking vessels in water routes and predicting their subsequent locations in real time. The proposed framework utilizes an Extract, Transform, and Load (ETL) pipeline to...
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