Article
Geosciences, Multidisciplinary
Yubin Li, Yujie Wu, Jie Tang, Ping Zhu, Zhiqiu Gao, Yuanjian Yang
Summary: This study evaluates the uncertainties of turbulent flux calculation using eddy covariance (EC) and wavelet analysis (WA) methods. The results show that the Mexhat-wavelet method has high accuracy in calculating turbulent fluxes under non-stationary conditions.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Biodiversity Conservation
Qian Wang, Xin Liu, Zeyuan Wang, Lin Zhao, Qi-peng Zhang
Summary: This study explored the time scale selection and periodic fluctuations of drought monitoring in Inner Mongolia grasslands. It found that SPEI6 is the more applicable time scale for drought monitoring, and identified the primary period of drought evolution in Inner Mongolia grasslands as 17 years.
GLOBAL ECOLOGY AND CONSERVATION
(2022)
Article
Computer Science, Information Systems
Xiaoliang Meng, Fuzhen Sun, Liye Zhang, Chao Fang, Xiaoyu Wang
Summary: In order to accurately reconstruct the three-dimensional surface of dynamic objects, a wrapped phase extraction method based on 3D wavelet transform (WT) for spatiotemporal analysis was proposed. The method combines a 2D spatial fringe image with the time dimension to form a 3D image sequence. By utilizing 3D WT and complex Morlet wavelet, the wrapped phase information of the encoded fringe image sequence was extracted, and the accuracy of wrapped phase extraction was improved through spatiotemporal analysis and multi-scale analysis of 3D WT. The measured object was then reconstructed through wrapped phase unwrapping and phase height transformation. Simulation experiment results showed that the proposed method can effectively filter noise in the time dimension and achieve higher accuracy compared to other methods.
Article
Computer Science, Information Systems
Ahmed Gaber Mabrouk, Alaa Hamdy, Hammam M. Abdelaal, Ahmed Gamal Elkattan, Motasem M. Elshourbagy, Hassan A. Youness Alansary
Summary: This study proposes a non-invasive method for diagnosing liver diseases using ultrasound images, by classifying liver tissue as normal, steatosis, or cirrhosis. The method combines different feature selection methods and three voting-based sub-classifiers to achieve accurate liver tissue classification.
Article
Engineering, Biomedical
Pawel Stasiakiewicz, Andrzej P. Dobrowolski, Tomasz Targowski, Natalia Galazka-Swiderek, Teresa Sadura-Sieklucka, Katarzyna Majka, Agnieszka Skoczylas, Wojciech Lejkowski, Robert Olszewski
Summary: The auscultation of the respiratory system, a key element in the human body, is a complex procedure that requires doctors with good perception skills and extensive experience. This article attempts to develop a classification system using wavelet packets, a genetic algorithm, and a Support Vector Machine to differentiate between healthy patients and those with crackles caused by pneumonia, pulmonary fibrosis, HF, or COPD. The system, tested on a dataset of 62 healthy and 58 sick patients, showed promising results with high sensitivity and specificity.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2021)
Article
Statistics & Probability
Kaijie Xue, Jin Yang, Fang Yao
Summary: Most existing methods for functional data classification focus on one or a few processes. In this work, we address the classification of high-dimensional functional data with a large number of potentially correlated functional processes. The challenge lies in the complex inter-correlation structures among multiple functional processes. We propose a penalized classifier that achieves near-perfect classification for functional data while maintaining discrimination set inclusion consistency. Simulation studies and real data applications demonstrate its favorable performance.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2023)
Review
Geriatrics & Gerontology
Rui Ma, Jin Zhao, Cui Li, Yunlong Qin, Jipeng Yan, Yuwei Wang, Zixian Yu, Yumeng Zhang, Yueru Zhao, Boyong Huang, Shiren Sun, Xiaoxuan Ning
Summary: This study evaluated the diagnostic test accuracy of the 3D-CAM in delirium detection through a systematic review and meta-analysis. The results showed that the 3D-CAM has good diagnostic accuracy for delirium detection in different care settings. Therefore, the use of 3D-CAM is recommended for clinical delirium detection.
Article
Agronomy
Zihan Liu, Lili Zhangzhong, Wengang Zheng, Xin Zhang, Jingxin Yu, Fujie Zhang, Lihong Yang
Summary: This study calculated the reference evapotranspiration (ET0) using meteorological data and analyzed its changing trend and influencing factors. The results showed that ET0 had significant oscillation cycles and was correlated with temperature, wind speed, sunshine hours, and relative humidity. A simplified ET0 calculation algorithm based on seasonal temperature was also established. This study provides a scientific basis for the rational regulation of agricultural production.
IRRIGATION AND DRAINAGE
(2023)
Article
Biochemical Research Methods
Sorin Viorel Parasca, Mihaela Antonina Calin
Summary: This paper presents a new approach that combines hyperspectral imaging with an object-oriented classification method to generate burn depth classification maps, facilitating easier characterization of burns. The approach was evaluated using hyperspectral images of 14 patients with burns, and the results showed high overall accuracy, precision, sensitivity, and specificity in differentiating burn classes. The object-based approach for burns hyperspectral images classification can provide maps that help surgeons identify different depths of burn wounds better.
JOURNAL OF BIOPHOTONICS
(2022)
Article
Energy & Fuels
Zijing Yang, Haochen Hua, Junwei Cao
Summary: This paper proposes a novel analysis approach based on multiple impact factors to improve disturbance detection accuracy. Five key factors, including wavelet function, wavelet decomposition level, redundant algorithm, event type and disturbance intensity, and start and end moment of disturbance, are considered. An impact factor based accuracy analysis algorithm is proposed, and three transforms are employed to investigate their superiority on disturbance location accuracy. Simulations are conducted for verification, and the proposed method proves to be effective in accurate detection of power quality disturbance.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2023)
Article
Engineering, Biomedical
Yong Wang, Yang Bai, Xiaoyu Xia, Zikang Niu, Yi Yang, Jianghong He, Xiaoli Li
Summary: The research compared three methods for analyzing TMS-evoked oscillations and found that SST could more accurately detect oscillations in different states of consciousness. The main frequency of TMS-evoked oscillations for DOC patients was lower than that of normal individuals.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2021)
Article
Public, Environmental & Occupational Health
Sashikala Mishra, Kailash Shaw, Debahuti Mishra, Shruti Patil, Ketan Kotecha, Satish Kumar, Simi Bajaj
Summary: Healthcare AI systems mainly use classification models for disease detection, but single models may have limited accuracy. Fusion of multiple classifiers outputs into a single framework has been found to increase accuracy. The proposed bit fusion ensemble algorithm reduces classification error rate and has been tested on various datasets, showing improvement in error rates.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Biology
Asghar Zarei, Babak Mohammadzadeh Asl
Summary: A novel algorithm was developed for automatic seizure detection from EEG signals using DWT and OMP techniques, which improved detection accuracy by extracting signal coefficients, calculating nonlinear features, and statistical features. The proposed OMP-based technique with SVM classifier showed good performance in different classification tasks according to the experimental results.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Computer Science, Information Systems
Ganesh Kumar Komal, Ganesh Kumar Sethi, Rajesh Kumar Bawa
Summary: Automatic rice variety identification or quality analysis is a challenging task in image processing that utilizes emerging computational technologies for advanced insights into agricultural research. This research study provides valuable assistance to novice researchers in the agricultural field by presenting a comprehensive perspective on the recent research studies for developing various identification systems. It highlights the minimal research work on automated variety identification systems in deep learning using a combination of rice features, presenting a future direction.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Environmental Sciences
Jian Feng, Yuqiang Zhang, Shuaihe Gao, Zhuangkai Wang, Xiang Wang, Bo Chen, Yi Liu, Chen Zhou, Zhengyu Zhao
Summary: This study presents a statistical analysis of the ionospheric irregularities known as Spread-F (SF) in the middle and low latitudes of East Asia. Using a naive Bayesian classifier, the researchers were able to automatically identify SF on ionograms with a high accuracy of 97%. The results provide valuable insights into the characteristics and occurrence patterns of SF in this region.
Review
Computer Science, Artificial Intelligence
Wei Gao, Shuangshuang Ge
Summary: This study provides a comprehensive review of slope stability research based on artificial intelligence methods, focusing on slope stability computation and evaluation. The review covers studies using quasi-physical intelligence methods, simulated evolutionary methods, swarm intelligence methods, hybrid intelligence methods, artificial neural network methods, vector machine methods, and other intelligence methods. The merits, demerits, and state-of-the-art research advancement of these studies are analyzed, and possible research directions for slope stability investigation based on artificial intelligence methods are suggested.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Khuong Le Nguyen, Hoa Thi Trinh, Saeed Banihashemi, Thong M. Pham
Summary: This study investigated the influence of input parameters on the shear strength of RC squat walls and found that ensemble learning models, particularly XGBoost, can effectively predict the shear strength. The axial load had a greater influence than reinforcement ratio, and longitudinal reinforcement had a more significant impact compared to horizontal and vertical reinforcement. The performance of XGBoost model outperforms traditional design models and reducing input features still yields reliable predictions.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Bo Hu, Huiyan Zhang, Xiaoyi Wang, Li Wang, Jiping Xu, Qian Sun, Zhiyao Zhao, Lei Zhang
Summary: A deep hierarchical echo state network (DHESN) is proposed to address the limitations of shallow coupled structures. By using transfer entropy, candidate variables with strong causal relationships are selected and a hierarchical reservoir structure is established to improve prediction accuracy. Simulation results demonstrate that DHESN performs well in predicting algal bloom.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Limin Wang, Lingling Li, Qilong Li, Kuo Li
Summary: This paper discusses the urgency of learning complex multivariate probability distributions due to the increase in data variability and quantity. It introduces a highly scalable classifier called TAN, which utilizes maximum weighted spanning tree (MWST) for graphical modeling. The paper theoretically proves the feasibility of extending one-dependence MWST to model high-dependence relationships and proposes a heuristic search strategy to improve the fitness of the extended topology to data. Experimental results demonstrate that this algorithm achieves a good bias-variance tradeoff and competitive classification performance compared to other high-dependence or ensemble learning algorithms.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhejing Hu, Gong Chen, Yan Liu, Xiao Ma, Nianhong Guan, Xiaoying Wang
Summary: Anxiety is a prevalent issue and music therapy has been found effective in reducing anxiety. To meet the diverse needs of individuals, a novel model called the spatio-temporal therapeutic music transfer model (StTMTM) is proposed.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Nur Ezlin Zamri, Mohd. Asyraf Mansor, Mohd Shareduwan Mohd Kasihmuddin, Siti Syatirah Sidik, Alyaa Alway, Nurul Atiqah Romli, Yueling Guo, Siti Zulaikha Mohd Jamaludin
Summary: In this study, a hybrid logic mining model was proposed by combining the logic mining approach with the Modified Niche Genetic Algorithm. This model improves the generalizability and storage capacity of the retrieved induced logic. Various modifications were made to address other issues. Experimental results demonstrate that the proposed model outperforms baseline methods in terms of accuracy, precision, specificity, and correlation coefficient.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
David Jacob Kedziora, Tien-Dung Nguyen, Katarzyna Musial, Bogdan Gabrys
Summary: The paper addresses the problem of efficiently optimizing machine learning solutions by reducing the configuration space of ML pipelines and leveraging historical performance. The experiments conducted show that opportunistic/systematic meta-knowledge can improve ML outcomes, and configuration-space culling is optimal when balanced. The utility and impact of meta-knowledge depend on various factors and are crucial for generating informative meta-knowledge bases.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
G. Sophia Jasmine, Rajasekaran Stanislaus, N. Manoj Kumar, Thangamuthu Logeswaran
Summary: In the context of a rapidly expanding electric vehicle market, this research investigates the ideal locations for EV charging stations and capacitors in power grids to enhance voltage stability and reduce power losses. A hybrid approach combining the Fire Hawk Optimizer and Spiking Neural Network is proposed, which shows promising results in improving system performance. The optimization approach has the potential to enhance the stability and efficiency of electric grids.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhijiang Wu, Guofeng Ma
Summary: This study proposes a natural language processing-based framework for requirement retrieval and document association, which can help to mine and retrieve documents related to project managers' requirements. The framework analyzes the ontology relevance and emotional preference of requirements. The results show that the framework performs well in terms of iterations and threshold, and there is a significant matching between the retrieved documents and the requirements, which has significant managerial implications for construction safety management.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Yung-Kuan Chan, Chuen-Horng Lin, Yuan-Rong Ben, Ching-Lin Wang, Shu-Chun Yang, Meng-Hsiun Tsai, Shyr-Shen Yu
Summary: This study proposes a novel method for dog identification using nose-print recognition, which can be applied to controlling stray dogs, locating lost pets, and pet insurance verification. The method achieves high recognition accuracy through two-stage segmentation and feature extraction using a genetic algorithm.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Shaohua Song, Elena Tappia, Guang Song, Xianliang Shi, T. C. E. Cheng
Summary: This study aims to optimize supplier selection and demand allocation decisions for omni-channel retailers in order to achieve supply chain resilience. It proposes a two-phase approach that takes into account various factors such as supplier evaluation and demand allocation.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jinyan Hu, Yanping Jiang
Summary: This paper examines the allocation problem of shared parking spaces considering parking unpunctuality and no-shows. It proposes an effective approach using sample average approximation (SAA) combined with an accelerating Benders decomposition (ABD) algorithm to solve the problem. The numerical experiments demonstrate the significance of supply-demand balance for the operation and user satisfaction of the shared parking system.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Soroor Motie, Bijan Raahemi
Summary: Financial fraud is a persistent problem in the finance industry, but Graph Neural Networks (GNNs) have emerged as a powerful tool for detecting fraudulent activities. This systematic review provides a comprehensive overview of the current state-of-the-art technologies in using GNNs for financial fraud detection, identifies gaps and limitations in existing research, and suggests potential directions for future research.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Enhao Ning, Changshuo Wang, Huang Zhang, Xin Ning, Prayag Tiwari
Summary: This review provides a detailed overview of occluded person re-identification methods and conducts a systematic analysis and comparison of existing deep learning-based approaches. It offers important theoretical and practical references for future research in the field.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jiajun Ma, Songyu Hu, Jianzhong Fu, Gui Chen
Summary: The article presents a novel visual hierarchical attention detector for multi-scale defect location and classification, utilizing texture, semantic, and instance features of defects through a hierarchical attention mechanism, achieving multi-scale defect detection in bearing images with complex backgrounds.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)