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Yunhan Geng, Shaojuan Su, Tianxiang Zhang and Zhaoyu Zhu
Centrifugal pumps are susceptible to various faults, particularly under challenging conditions such as high pressure. Swift and accurate fault diagnosis is crucial for enhancing the reliability and safety of mechanical equipment. However, monitoring data...
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Lukas Wiku Kuswidiyanto, Dong Eok Kim, Teng Fu, Kyoung Su Kim and Xiongzhe Han
The cultivation of kimchi cabbage in South Korea has always faced significant challenges due to the looming presence of Alternaria leaf spot (ALS), which is a fungal disease mainly caused by Alternaria alternata. The emergence of black spots resulting fr...
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Guotai Wang, Xingguang Geng, Lin Huang, Xiaoxiao Kang, Jun Zhang, Yitao Zhang and Haiying Zhang
Radial pulse signals are produced by the periodic ejection of blood from the heart, and physiological and pathological information of the human body can be analyzed by extracting the time-domain characteristics of pulse waves. However, since pulse signal...
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Min Yang, Haoran Huang, Yiqi Zhang and Xiongfeng Yan
Recognizing morphological patterns in lines and segmenting them into homogeneous segments is critical for line generalization and other applications. Due to the excessive dependence on handcrafted features in existing methods and their insufficient consi...
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Mohammed Gamal Ragab, Said Jadid Abdulkadir, Norshakirah Aziz, Hitham Alhussian, Abubakar Bala and Alawi Alqushaibi
With the growth of deep learning in various classification problems, many researchers have used deep learning methods in environmental sound classification tasks. This paper introduces an end-to-end method for environmental sound classification based on ...
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Min Seop Lee, Yun Kyu Lee, Dong Sung Pae, Myo Taeg Lim, Dong Won Kim and Tae Koo Kang
Physiological signals contain considerable information regarding emotions. This paper investigated the ability of photoplethysmogram (PPG) signals to recognize emotion, adopting a two-dimensional emotion model based on valence and arousal to represent hu...
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Fangping Xu, Jun Chen and Jianyong Zhu
Insufficient color feature extraction can lead to poor prediction performance in rare earth element composition estimation. To address this issue, we propose a one-dimensional convolutional method for predicting rare earth element composition. First, ima...
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Min-Jee Kim, Jae-Eun Lee, Insuck Back, Kyoung Jae Lim and Changyeun Mo
Excessive total nitrogen (TN) content in topsoil is a major cause of eutrophication when nitrogen flows into water systems from soil losses. Therefore, TN content prediction is essential for establishing topsoil management systems and protecting aquatic ...
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Na Luo, Yunlong Li, Baohua Yang, Biyun Liu and Qianying Dai
The content of tea polyphenols (TP) is one of the important indicators for judging the quality of tea. Accurate and non-destructive estimation technology for tea polyphenol content has attracted more and more attention, which has become a key technology ...
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Chenyang Wang, Wanlu Jiang, Xukang Yang and Shuqing Zhang
Predicting the remaining useful life (RUL) of mechanical equipment can improve production efficiency while effectively reducing the life cycle cost and failure rate. This paper proposes a method for predicting the remaining service life of equipment thro...
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Zongchen Jiang, Yi Ma and Junfang Yang
In recent years, marine oil spill accidents have occurred frequently, seriously endangering marine ecological security. It is highly important to protect the marine ecological environment by carrying out research on the estimation of sea oil spills based...
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Yue Sun, Sandor Brockhauser and Péter Hegedus
In scientific research, spectroscopy and diffraction experimental techniques are widely used and produce huge amounts of spectral data. Learning patterns from spectra is critical during these experiments. This provides immediate feedback on the actual st...
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Omar Serghini, Hayat Semlali, Asmaa Maali, Abdelilah Ghammaz and Salvatore Serrano
Spectrum sensing is an essential function of cognitive radio technology that can enable the reuse of available radio resources by so-called secondary users without creating harmful interference with licensed users. The application of machine learning tec...
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Yang Hu, Liangliang Gong, Xinyang Li, Hui Li, Ruoxin Zhang and Rentao Gu
When applying 5G network slicing technology, the operator?s network resources in the form of mutually isolated logical network slices provide specific service requirements and quality of service guarantees for smart grid communication services. In the fa...
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Hui Sheng, Min Liu, Jiyong Hu, Ping Li, Yali Peng and Yugen Yi
Time-series data is an appealing study topic in data mining and has a broad range of applications. Many approaches have been employed to handle time series classification (TSC) challenges with promising results, among which deep neural network methods ha...
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Tanvir Islam and Peter Washington
Stress is widely recognized as a major contributor to a variety of health issues. Stress prediction using biosignal data recorded by wearables is a key area of study in mobile sensing research because real-time stress prediction can enable digital interv...
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Dali Liu, Wenhao Shen, Wenjing Cao, Weimin Hou and Baozhu Wang
The acquisition of target data for underwater acoustic target recognition (UATR) is difficult and costly. Although deep neural networks (DNN) have been used in UATR, and some achievements have been made, the performance is not satisfactory when recognizi...
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David Opeoluwa Oyewola, Emmanuel Gbenga Dada, Temidayo Oluwatosin Omotehinwa, Onyeka Emebo and Olugbenga Oluseun Oluwagbemi
From the development and sale of a product through its delivery to the end customer, the supply chain encompasses a network of suppliers, transporters, warehouses, distribution centers, shipping lines, and logistics service providers all working together...
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Changsong Bing, Yirong Wu, Fangmin Dong, Shouzhi Xu, Xiaodi Liu and Shuifa Sun
Social media has become more popular these days due to widely used instant messaging. Nevertheless, rumor propagation on social media has become an increasingly important issue. The purpose of this study is to investigate the impact of various features i...
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Changkyoung Eem, Hyunki Hong and Yoohun Noh
We introduce a deep-learning neural network model that uses electrocardiogram (ECG) data to predict coronary artery calcium scores, which can be useful for reliably detecting cardiovascular risk in patients. In our pre-processing method, each lead of the...
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