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Yufan Qian, Limei Tian, Baichen Zhai, Shufan Zhang and Rui Wu
Missing observations in time series will distort the data characteristics, change the dataset expectations, high-order distances, and other statistics, and increase the difficulty of data analysis. Therefore, data imputation needs to be performed first. ...
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Fan Zhang, Melissa Petersen, Leigh Johnson, James Hall, Raymond F. Palmer, Sid E. O?Bryant and on behalf of the Health and Aging Brain Study (HABS?HD) Study Team
The Health and Aging Brain Study?Health Disparities (HABS?HD) project seeks to understand the biological, social, and environmental factors that impact brain aging among diverse communities. A common issue for HABS?HD is missing data. It is impossible to...
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Benjamin Agbo, Hussain Al-Aqrabi, Richard Hill and Tariq Alsboui
The Internet of Things (IoT) has had a tremendous impact on the evolution and adoption of information and communication technology. In the modern world, data are generated by individuals and collected automatically by physical objects that are fitted wit...
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Milad Salem, Shayan Taheri and Jiann-Shiun Yuan
The SECOM dataset contains information about a semiconductor production line, entailing the products that failed the in-house test line and their attributes. This dataset, similar to most semiconductor manufacturing data, contains missing values, imbalan...
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Cong Li, Xupeng Ren and Guohui Zhao
Ground meteorological observation data (GMOD) are the core of research on earth-related disciplines and an important reference for societal production and life. Unfortunately, due to operational issues or equipment failures, missing values may occur in G...
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Luca Cappelletti, Tommaso Fontana, Guido Walter Di Donato, Lorenzo Di Tucci, Elena Casiraghi and Giorgio Valentini
Missing data imputation has been a hot topic in the past decade, and many state-of-the-art works have been presented to propose novel, interesting solutions that have been applied in a variety of fields. In the past decade, the successful results achieve...
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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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Hsin-Yu Chen, Zoran Vojinovic, Weicheng Lo and Jhe-Wei Lee
The development of civilization and the preservation of environmental ecosystems are strongly dependent on water resources. Typically, an insufficient supply of surface water resources for domestic, industrial, and agricultural needs is supplemented with...
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Saul G. Ramirez, Gustavious Paul Williams, Norman L. Jones, Daniel P. Ames and Jani Radebaugh
Obtaining and managing groundwater data is difficult as it is common for time series datasets representing groundwater levels at wells to have large gaps of missing data. To address this issue, many methods have been developed to infill or impute the mis...
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Mara Meggiorin, Giulia Passadore, Silvia Bertoldo, Andrea Sottani and Andrea Rinaldo
This study compares three imputation methods applied to the field observations of hydraulic head in subsurface hydrology. Hydrogeological studies that analyze the timeseries of groundwater elevations often face issues with missing data that may mislead b...
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Menna Ibrahim Gabr, Yehia Mostafa Helmy and Doaa Saad Elzanfaly
Data completeness is one of the most common challenges that hinder the performance of data analytics platforms. Different studies have assessed the effect of missing values on different classification models based on a single evaluation metric, namely, a...
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Edgar Acuna, Roxana Aparicio and Velcy Palomino
In this paper we investigate the effect of two preprocessing techniques, data imputation and smoothing, in the prediction of blood glucose level in type 1 diabetes patients, using a novel deep learning model called Transformer. We train three models: XGB...
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Xing Su, Wenjie Sun, Chenting Song, Zhi Cai and Limin Guo
With the rapid development of the economy, car ownership has grown rapidly, which causes many traffic problems. In recent years, intelligent transportation systems have been used to solve various traffic problems. To achieve effective and efficient traff...
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Francisco R. da S. Pereira, Aliny A. Dos Reis, Rodrigo G. Freitas, Stanley R. de M. Oliveira, Lucas R. do Amaral, Gleyce K. D. A. Figueiredo, João F. G. Antunes, Rubens A. C. Lamparelli, Edemar Moro and Paulo S. G. Magalhães
The recent advances in unmanned aerial vehicle (UAV)-based remote sensing systems have broadened the remote sensing applications for agriculture. Despite the great possibilities of using UAVs to monitor agricultural fields, specific problems related to m...
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Li Cai, Cong Sha, Jing He and Shaowen Yao
Traffic flows (e.g., the traffic of vehicles, passengers, and bikes) aim to reveal traffic flow phenomena generated by traffic participants in traffic activities. Various studies of traffic flows rely heavily on high-quality traffic data. The taxi GPS tr...
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Ashokkumar Palanivinayagam and Robertas Dama?evicius
The existence of missing values reduces the amount of knowledge learned by the machine learning models in the training stage thus affecting the classification accuracy negatively. To address this challenge, we introduce the use of Support Vector Machine ...
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Gaurav Narkhede, Anil Hiwale, Bharat Tidke and Chetan Khadse
Day by day pollution in cities is increasing due to urbanization. One of the biggest challenges posed by the rapid migration of inhabitants into cities is increased air pollution. Sustainable Development Goal 11 indicates that 99 percent of the world?s u...
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Xinxi Lu, Lijuan Yuan, Ruifeng Li, Zhihuan Xing, Ning Yao and Yichun Yu
In recent years, the development of computer technology has promoted the informatization and intelligentization of hospital management systems and thus produced a large amount of medical data. These medical data are valuable resources for research. We ca...
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Kun Kang, Qishen Chen, Kun Wang, Yanfei Zhang, Dehui Zhang, Guodong Zheng, Jiayun Xing, Tao Long, Xin Ren, Chenghong Shang and Bojing Cui
In the context of globalization in the mining industry, assessing the production feasibility of mining projects by smart technology is crucial for the improvement of mining development efficiency. However, evaluating the feasibility of such projects face...
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Tiantian Liu and Yuanyuan Li
Single-cell RNA sequencing (scRNA-seq) has become a powerful technique to investigate cellular heterogeneity and complexity in various fields by revealing the gene expression status of individual cells. Despite the undeniable benefits of scRNA-seq, it is...
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