Article
Computer Science, Artificial Intelligence
Debamita Kumar, Pradipta Maji
Summary: Multimodal data analysis is used for identifying sample categories by incorporating supervised information and capturing the nonlinear correlated structures across different views. The proposed architecture, discriminative deep canonical correlation analysis (D2CCA), combines generative models with the learning objective to improve discriminative ability. The joint representation of multi-view data is learned from maximally correlated subspaces.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Yinsong Wang, Shahin Shahrampour
Summary: This article proposes a task-specific scoring rule for selecting random features, which can be applied to different applications. The proposed ORCCA method improves upon other approximation techniques in the CCA task by optimizing the scoring function.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Xianchao Xiu, Lili Pan, Ying Yang, Wanquan Liu
Summary: This study proposes a new joint sparse constrained CCA model that integrates l(2,0)-norm joint sparse constraints into classical CCA for improved fault detection performance. The proposed approach fully exploits the joint sparse structure to determine the number of extracted variables and utilizes an efficient algorithm for computation. Extensive numerical studies demonstrate the efficiency and speed of the proposed method.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Jianqin Sun, Xianchao Xiu, Ziyan Luo, Wanquan Liu
Summary: This study introduces a novel tensor CCA method (TCCA-O) to preserve orthogonality and improve feature representation. By incorporating a structured sparse regularization term (TCCA-OS), the performance of the method is further improved. Experimental results demonstrate that TCCA-O and TCCA-OS outperform other CCA methods in various evaluation metrics.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Rencheng Song, Jiji Li, Juan Cheng, Chang Li, Yu Liu, Xun Chen
Summary: This article proposes a novel method called robust iBCG (RiBCG) to suppress motion artifacts and an improved version RiBCG-C to reduce HR outliers. Through evaluation on public databases, RiBCG-C method achieves overall the best performance, providing a promising scheme for RiBCG measurements in realistic application scenarios.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Biotechnology & Applied Microbiology
Zishan Wang, Ruqiang Huang, Ye Yan, Zhiguo Luo, Shaokai Zhao, Bei Wang, Jing Jin, Liang Xie, Erwei Yin
Summary: Our study proposed a new method for emotion recognition by exploring the interactions between EEG rhythms under different emotional expressions. The effectiveness of more correlated EEG frequency band features for emotion classification accuracy was verified through experiments. By fusing these correlated features with traditional features at the decision level, we significantly improved the accuracy of emotion recognition.
BIOENGINEERING-BASEL
(2023)
Article
Automation & Control Systems
Hongchao Cheng, Jing Wu, Daoping Huang, Yiqi Liu, Qilin Wang
Summary: A novel method called Rab-CCA is proposed for monitoring wastewater treatment processes, which includes a robust decomposition method and an adaptive statistical control limit to improve the performance of standard process monitoring methods, reducing missed alarms and false alarms simultaneously.
Article
Chemistry, Analytical
Victor Javier Kartsch, Velu Prabhakar Kumaravel, Simone Benatti, Giorgio Vallortigara, Luca Benini, Elisabetta Farella, Marco Buiatti
Summary: Recent studies have shown that the integrity of core perceptual and cognitive functions can be tested with low stimulation frequencies using Steady-State Visual Evoked Potentials (SSVEP) and wearable EEG systems. The results demonstrate that Normalized Canonical Correlation Analysis (NCCA) is an effective method for rapid and accurate detection of SSVEP without the need for preliminary artifact correction or channel selection.
Article
Computer Science, Information Systems
Kai-fa Hui, Ernest Domanaanmwi Ganaa, Yong-zhao Zhan, Xiang-jun Shen
Summary: The paper proposes a method of robust deflated canonical correlation analysis via feature factoring for multi-view image classification, which introduces a feature factoring matrix to evaluate the contribution of each feature to the whole feature space and assign specific weights to different features to suppress noisy data. Multiple factoring matrices are built with respect to multiple projection vectors to weigh the degree of importance of each feature in each projection for better feature representation in multi-view images.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Xiang-Jun Shen, Zhaorui Xu, Liangjun Wang, Zechao Li, Guangcan Liu, Jianping Fan, ZhengJun Zha
Summary: This article presents a novel CCA method that carries out analysis on the dataset in the Fourier domain, which can significantly improve the computation speed and memory efficiency. By applying Fourier transform on the data, the traditional eigenvector computation of CCA is converted into finding discriminative Fourier bases. The proposed method achieves satisfactory accuracy and extremely fast training time consumption in large-scale correlation datasets.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Automation & Control Systems
Hongtian Chen, Zhiwen Chen, Zheng Chai, Bin Jiang, Biao Huang
Summary: This study introduces a new nonlinear fault detection method called SsCCA with the help of neural networks to enhance FD performance, by reformulating the objective function and designing a specific solution. Experimental results demonstrate that this method can effectively improve fault detection capability in nonlinear systems.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Xianchao Xiu, Zhonghua Miao, Ying Yang, Wanquan Liu
Summary: This article proposes an efficient nonlinear process monitoring method by integrating DAENNs, CCA, and SCO. The method is demonstrated on the TE process and the diesel generator process, achieving an increased fault detection rate of 8.00% for the fault IDV(11) compared to classical CCA.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Nutrition & Dietetics
Sven H. Rouschop, Agnieszka Smolinska, Marij Gielen, Renate H. M. de Groot, Maurice P. Zeegers, Antoon Opperhuizen, Frederik J. van Schooten, Roger W. Godschalk
Summary: Maternal fatty acid intake during pregnancy is related to the development of inflammatory lung disorders in children. The study found that maternal fatty acid levels during pregnancy are significantly associated with child inflammatory markers at age 7, with Mead acid being the most important factor in this correlation. Furthermore, the maternal Mead acid levels at birth are related to the development of inflammatory lung disorders in children at age 7.
FRONTIERS IN NUTRITION
(2023)
Article
Computer Science, Artificial Intelligence
Paris A. Karakasis, Athanasios P. Liavas, Nicholas D. Sidiropoulos, Panagiotis G. Simos, Efrosini Papadaki
Summary: Functional magnetic resonance imaging (fMRI) is widely used for studying the human brain. This study proposes a new fMRI data generating model that takes into account both task-related and resting-state components. Experimental tests show that our method can accurately estimate temporal and spatial components even at low Signal to Noise Ratio (SNR), and outperforms standard procedures based on General Linear Models (GLMs).
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2022)
Article
Computer Science, Information Systems
Zia Ullah, Lin Qi, D. Binu, B. R. Rajakumar, B. Mohammed Ismail
Summary: In this research work, a new Image super-resolution-based Face Emotion Recognition Model has been introduced. The proposed work includes facial image super-resolution and facial emotion recognition. The model uses various techniques such as 2D CCA, Viola-Jones facial detection, GM-WLBP, GLCM, GLRM, PCA, LSTM, and CNN to extract relevant features and classify emotions. The performance of the proposed work is evaluated and compared to existing models.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Editorial Material
Environmental Sciences
Naicheng Wu, Yixia Wang, Yaochun Wang, Qinghua Cai, Wei Ouyang
Article
Environmental Sciences
Xiaonuo Chen, Xiaojun Wang, Yuying Li, Yinlei Yao, Yun Zhang, Yeqing Jiang, Xiaohui Lei, Han Liu, Naicheng Wu, Nicola Fohrer
Summary: This study investigated the changes in periphyton community and environmental factors in an artificial canal, and found that seasonal variability was more significant, with Bacillariophyta being the dominant phylum and water temperature and nutrient concentration being the key factors.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Article
Agriculture, Dairy & Animal Science
Naicheng Wu, Guohao Liu, Min Zhang, Yixia Wang, Wenqi Peng, Xiaodong Qu
Summary: This study compared the correlation and relative contribution of multiple abiotic factors to the different aspects of beta-diversity in macroinvertebrates from 179 stream sampling sites in the Hun-Tai River Basin in Northeastern China. The results showed that functional beta-diversity provides important complementary information to taxonomic and phylogenetic beta-diversity. Spatial factors were found to be more influential than local environmental and geo-climatic variables in shaping the beta-diversity of stream macroinvertebrates.
Article
Environmental Sciences
Caiqin Hu, Kun Guo, Naicheng Wu, Qingfu Liu, Qianfu Liu, Wanling Yang, Chao Wang
Summary: Trait-based approaches are increasingly used in ecology to understand the influence of individual-level trait variation on communities and species. This study examined the responses of individual trait variation of the diatom genus Aulacoseira to environmental changes in the Pearl River Delta. The results showed that different factors regulated the trait richness, trait evenness, and trait dispersion of Aulacoseira, with abiotic factors having a stronger direct influence than biotic factors. This study highlights the potential of multidimensional trait variation as an effective indicator for tracking environmental changes.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2023)
Article
Education & Educational Research
Paula Farina Grosser, Zhongxin Xia, Jannik Alt, Uwe Rueppel, Britta Schmalz
Summary: With the development of the VR4Hydro tool, virtual field trips have been proven to be a valuable supplement to physical field trips in hydrological engineering education. The study showed that the majority of students found virtual excursions to be interesting and valuable, especially when real field trips were not possible due to external circumstances. This research highlights the importance of incorporating virtual field trips into hydrological education to enhance students' interest and learning outcomes.
EDUCATION AND INFORMATION TECHNOLOGIES
(2023)
Article
Environmental Sciences
Amrei David, Ernesto Ruiz Rodriguez, Britta Schmalz
Summary: In recent years, many 2D hydrodynamic models have incorporated the direct rainfall method (DRM) to serve as hydrological-hydrodynamic models for floodplain determination. However, the role of catchment hydrological processes (CaHyPro) and its interaction with the calibration process have not been thoroughly investigated. In this case study, the spatiotemporal distribution of precipitation and runoff formation processes, combined with the 2D model HEC-RAS, is examined. A conceptual approach for event-based interflow is also integrated. The results demonstrate the improvement in model accuracy through the integration of CaHyPro and its interplay with calibrated model parameters.
JOURNAL OF FLOOD RISK MANAGEMENT
(2023)
Article
Ecology
Naicheng Wu, Kun Guo, Yi Zou, Fengzhi He, Tenna Riis
Summary: Environmental regimes refer to the dynamics of environmental characteristics over time. An R package called SER is introduced for estimating environmental regimes for various variables. The inclusion of environmental regimes enhances the understanding of environment-community relationships and can be applied in other disciplines such as social science and epidemiology.
ECOLOGY AND EVOLUTION
(2023)
Editorial Material
Forestry
Xiao-Dong Yang, Nai-Cheng Wu, Xue-Wei Gong
Article
Environmental Sciences
Zhenyu Zhang, Georg Hoermann, Jinliang Huang, Nicola Fohrer
Summary: Understanding land use/cover change (LUCC) in watersheds is crucial for sustainable development. The machine learning-based CA-Markov model comprehensively evaluates the factors influencing LUCC, identifies patterns under different scenarios, and can serve as a helpful tool for watershed management.
Review
Environmental Sciences
Yaochun Wang, Guohao Liu, Yixia Wang, Hongli Mu, Xiaoli Shi, Chao Wang, Naicheng Wu
Summary: This paper analyzes the study of microplastics and their impact on aquatic ecosystems, focusing on trends, focal points, and national collaborations in freshwater microplastics research. The findings reveal three stages of microplastics research and a shift in research focus. International cooperation has increased, but the scope of collaboration is still limited. Future research should consider the bi-directional relationship between microplastics and watershed ecosystems and incorporate chemical and toxicological approaches.
Article
Environmental Studies
Mehdi Aalipour, Naicheng Wu, Nicola Fohrer, Yusef Kianpoor Kalkhajeh, Bahman Jabbarian Amiri
Summary: Changes in land use and land cover significantly influence river water quality. This study utilized spatial data from 39 catchments in the southern basin of the Caspian Sea to investigate the impact of landscape structure on water quality. The findings reveal that landscape structure metrics, particularly the shape index, contiguity index, and fractal metric, can predict variations in total dissolved solids (TDS) and magnesium (Mg) concentrations. Optimizing landscape structure metrics in land use planning can help reduce river pollution and improve water quality.
Article
Biodiversity Conservation
Yixia Wang, Naicheng Wu, Guohao Liu, Hongli Mu, Chao Gao, Yaochun Wang, Yanjuan Wu, Yu Zeng, Yunzhi Yan
Summary: Incorporating functional metrics into the development of a diatom-based index of biotic integrity (D-IBI) is conducive to a more comprehensive assessment of water quality and the degree of external impact on ecosystem function.
ECOLOGICAL INDICATORS
(2023)
Article
Environmental Sciences
Mohsen Dehghani Darmian, Britta Schmalz
Summary: This study utilizes genetic programming (GP) to analyze the longitudinal dispersion coefficient (LDC) of rivers and proposes new LDC equations. The sensitivity analysis reveals the most influential parameter and a new efficiency indicator is introduced. The accurately presented LDC is used to simulate the assimilation capacity of the Kashafrud River and shows significant improvement compared to the current pollution entrance.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2023)
Article
Environmental Sciences
Yu Ma, Zongling Yu, Shiqi Jia, Naicheng Wu, Kun Yin, Yeyao Wang, John P. Giesy, Xiaowei Jin
Summary: Biodiversity loss caused by human activities poses a threat to human well-being, but the combined effects of multiple stressors on community diversity, both alpha and beta, are not well understood. A long-term experiment on the Songhua River in China from 2012 to 2019 revealed a decline in alpha and beta diversity indices, particularly in impacted river sections. Despite improved water quality, human-caused stressors have led to biotic homogenization of macroinvertebrate communities, with land use being a significant factor. Different facets of diversity have distinct response mechanisms to stressors, providing complementary information in assessing ecological changes. This study highlights the importance of long-term monitoring and the need for timely control of nutrient input and land use expansion to protect river ecosystems.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2023)
