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Article ; Online: Design of Mobile English Teaching Platform Based on Collaborative Filtering Algorithm

Cong Xu

Computational Intelligence and Neuroscience, Vol

2022 Volume 2022

Abstract: With the rapid development of information technology, today’s talent training mode is no longer limited to traditional school education. At the same time, with the maturity of portable mobile devices, a new learning method—mobile learning has been born. ... ...

Abstract	With the rapid development of information technology, today’s talent training mode is no longer limited to traditional school education. At the same time, with the maturity of portable mobile devices, a new learning method—mobile learning has been born. In this paper, the narrative of data is taken into account in the way of user collaborative filtering recommendation. For prefilling the matrix, the project confidence level also needs to be considered during the whole process. The project confidence level is measured by information entropy model. In the process of correction, it combines with traditional cosine similarity, calculates the user similarity matrix, can budget equalization, and expands the original matrix. After filling the matrix, the user uses the method of similarity calculation, using Pearson similarity and combining with the Euclidean distance correction method. When comparing the particular result prediction with the actual prediction following the completion of the similarity matrix data, all results point to a considerable reduction in MAE and RMSE. The user does not assess the item score to forecast. This demonstrates how this technique may enhance the reliability and consistency of the mobile English system platform.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7 ; Neurosciences. Biological psychiatry. Neuropsychiatry ; RC321-571
Subject code	005
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Hindawi Limited
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: The application of hierarchical perception technology based on deep learning in 3D fashion design.

Cong, Xu / Zhang, Wenjia

Heliyon

2024 Volume 10, Issue 9, Page(s) e29983

Abstract: In recent years, 3D fashion design has been relied on for improving attire fashion, design, and presentation with fewer flaws and better visualization. This aids consumers in providing visualized recommendations on modifications, suggestions, and ... ...

Abstract	In recent years, 3D fashion design has been relied on for improving attire fashion, design, and presentation with fewer flaws and better visualization. This aids consumers in providing visualized recommendations on modifications, suggestions, and customized attire designs. Considering the influence of automation and intelligent processing in the fashion designing industry, it introduces a Flaw Detection Method in 3D Representation (FDM-3DR) to reduce frequent modifications. The proposed method visualizes the design in three dimensions for its completeness and flawless representation. Based on the consumer recommendation, the lack of design flaws in the representation is identified, and multiple detections are presented. This is required to improve consumer satisfaction and the multi-dimensional projection between flaws and complete attire products. The learning is trained using the fixable representation, and therefore, the previous unsuitable designs are repelled by different recommendations. This improves the design adaptability, recommendation ratio, and representation ratio. Besides, it reduces the recommendation time and flaws.
Language	English
Publishing date	2024-04-21
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2024.e29983
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A New Method for False Alarm Suppression in Heterogeneous Change Detection

Cong Xu / Baisen Liu / Zishu He

Remote Sensing, Vol 15, Iss 1745, p

2023 Volume 1745

Abstract: Heterogeneous change detection has a wide range of applications in many fields. However, to date, many existing problems of heterogeneous change detection, such as false alarm suppression, have not been specifically addressed. In this article, we discuss ...

Abstract	Heterogeneous change detection has a wide range of applications in many fields. However, to date, many existing problems of heterogeneous change detection, such as false alarm suppression, have not been specifically addressed. In this article, we discuss the problem of false alarm suppression and propose a new method based on the combination of a convolutional neural network (CNN) and graph convolutional network (GCN). This approach employs a two-channel CNN to learn the feature maps of multitemporal images and then calculates difference maps of different scales, which means that both low-level and high-level features contribute equally to the change detection. The GCN, with a newly built convolution kernel (called the partially absorbing random walk convolution kernel), classifies these difference maps to obtain the inter-feature relationships between true targets and false ones, which can be represented by an adjacent matrix. We use pseudo-label samples to train the whole network, which means our method is unsupervised. Our method is verified on two typical data sets. The experimental results indicate the superiority of our method compared to some state-of-the-art approaches, which proves the efficacy of our method in false alarm suppression.
Keywords	heterogeneous change detection ; CNN ; feature difference ; GCN ; Science ; Q
Subject code	000
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Crop pest detection by three-scale convolutional neural network with attention

Xuqi Wang / Shanwen Zhang / Xianfeng Wang / Cong Xu

PLoS ONE, Vol 18, Iss

2023 Volume 6

Abstract: Crop pests seriously affect the yield and quality of crop. To timely and accurately control crop pests is particularly crucial for crop security, quality of life and a stable agricultural economy. Crop pest detection in field is an essential step to ... ...

Abstract	Crop pests seriously affect the yield and quality of crop. To timely and accurately control crop pests is particularly crucial for crop security, quality of life and a stable agricultural economy. Crop pest detection in field is an essential step to control the pests. The existing convolutional neural network (CNN) based pest detection methods are not satisfactory for small pest recognition and detection in field because the pests are various with different colors, shapes and poses. A three-scale CNN with attention (TSCNNA) model is constructed for crop pest detection by adding the channel attention and spatial mechanisms are introduced into CNN. TSCNNA can improve the interest of CNN for pest detection with different sizes under complicated background, and enlarge the receptive field of CNN, so as to improve the accuracy of pest detection. Experiments are carried out on the image set of common crop pests, and the precision is 93.16%, which is 5.1% and 3.7% higher than ICNN and VGG16, respectively. The results show that the proposed method can achieve both high speed and high accuracy of crop pest detection. This proposed method has certain practical significance of real-time crop pest control in the field.
Keywords	Medicine ; R ; Science ; Q
Subject code	571
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: IL5RA as an immunogenic cell death-related predictor in progression and therapeutic response of multiple myeloma

Cong Xu / Meng Gao / Junhua Zhang / Yunfeng Fu

Scientific Reports, Vol 13, Iss 1, Pp 1-

2023 Volume 12

Abstract: Abstract Previous studies have shown the potential of immunogenic cell death-related modalities in myeloma. The significance of IL5RA in myeloma and immunogenic cell death remains unknown. We analyzed IL5RA expression, the gene expression profile, and ... ...

Abstract	Abstract Previous studies have shown the potential of immunogenic cell death-related modalities in myeloma. The significance of IL5RA in myeloma and immunogenic cell death remains unknown. We analyzed IL5RA expression, the gene expression profile, and secretory protein genes related to IL5RA level using GEO data. Immunogenic cell death subgroup classification was performed using the ConsensusClusterPlus and pheatmap R package. Enrichment analyses were based on GO/KEGG analysis. After IL5RA-shRNA transfection in myeloma cells, cell proliferation, apoptosis, and drug sensitivity were detected. P < 0.05 was considered statistically significant. IL5RA was upregulated in myeloma and progressed smoldering myeloma. We observed enrichment in pathways such as the PI3K-Akt signaling pathway, and Natural killer cell mediated cytotoxicity in the high-IL5RA group. IL5RA was also closely associated with secretory protein genes such as CST6. We observed the enrichment of cellular apoptosis and hippo signaling pathway on differential genes in the immunogenic cell death cluster. Furthermore, IL5RA was associated with immune infiltration, immunogenic cell death-related genes, immune-checkpoint-related genes, and m6A in myeloma. In vitro and in vivo experiments showed the involvement of IL5RA in apoptosis, proliferation, and drug resistance of myeloma cells. IL5RA shows the potential to be an immunogenic cell death-related predictor for myeloma.
Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2023-05-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Crop pest detection by three-scale convolutional neural network with attention.

Xuqi Wang / Shanwen Zhang / Xianfeng Wang / Cong Xu

PLoS ONE, Vol 18, Iss 6, p e

2023 Volume 0276456

Abstract	Crop pests seriously affect the yield and quality of crop. To timely and accurately control crop pests is particularly crucial for crop security, quality of life and a stable agricultural economy. Crop pest detection in field is an essential step to control the pests. The existing convolutional neural network (CNN) based pest detection methods are not satisfactory for small pest recognition and detection in field because the pests are various with different colors, shapes and poses. A three-scale CNN with attention (TSCNNA) model is constructed for crop pest detection by adding the channel attention and spatial mechanisms are introduced into CNN. TSCNNA can improve the interest of CNN for pest detection with different sizes under complicated background, and enlarge the receptive field of CNN, so as to improve the accuracy of pest detection. Experiments are carried out on the image set of common crop pests, and the precision is 93.16%, which is 5.1% and 3.7% higher than ICNN and VGG16, respectively. The results show that the proposed method can achieve both high speed and high accuracy of crop pest detection. This proposed method has certain practical significance of real-time crop pest control in the field.
Keywords	Medicine ; R ; Science ; Q
Subject code	571
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Editorial

Yanjie Li / Cong Xu / Weiqi Yan

Frontiers in Forests and Global Change, Vol

Forest phenomics: how does developing sensor technology improve the growth of forest plantations?

2023 Volume 6

Keywords	forest management ; high-precision ; high-throughput ; forest phenomics ; sensor-based plant phenomics ; Forestry ; SD1-669.5 ; Environmental sciences ; GE1-350
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Assessing causality between inflammatory bowel diseases with frailty index and sarcopenia

Peng Wang / Wei Tao / Zhiqiang Zhang / Cong Xu / Yuan Qiu / Weidong Xiao

European Journal of Medical Research, Vol 29, Iss 1, Pp 1-

a bidirectional Mendelian randomization study

2024 Volume 15

Abstract: Abstract Background Previous studies have found that frailty and sarcopenia are commonly diagnosed in inflammatory bowel disease (IBD) patients, indicating an association between these conditions. Nonetheless, the cause‒effect connection between IBD, ... ...

Abstract	Abstract Background Previous studies have found that frailty and sarcopenia are commonly diagnosed in inflammatory bowel disease (IBD) patients, indicating an association between these conditions. Nonetheless, the cause‒effect connection between IBD, frailty, and sarcopenia remains unclear. Methods We sourced the genetic variants for the exposures and outcomes from publicly accessible, extensive genome-wide association studies (GWAS). Specifically, we obtained IBD data from the International IBD Genetics Consortium, frailty index (FI) data from the United Kingdom Biobank and Swedish TwinGene, and sarcopenia data from a recent GWAS meta-analysis. Five methods, including inverse variance weighted (IVW), simple mode, MR-Egger, weighted mode, and the weighted median, were used to proceed with MR estimates. We also performed heterogeneity and horizontal pleiotropy tests. Results Our results indicated a positive causal relationship between ulcerative colitis (UC) (IVW: β = 0.014, 95% CI, 0.006 to 0.021, p = 0.001) and Crohn's disease (CD) (IVW: β = 0.012; 95% CI, 0.006 to 0.018, p = 2e−04) with the FI. However, we uncovered no proof of a cause-and-effect relationship between UC (IVW: β = 0.001, 95% CI, −0.015 to 0.017, p = 0.344) or CD (IVW: β = 0.003, 95% CI, −0.009 to 0.015, p = 0.214) and sarcopenia. Additionally, in the inverse order, we also discovered no cause-and-effect connection between FI or sarcopenia on UC or CD in this study. Conclusion The MR analysis showed a positive causal association between IBD and FI, indicating that IBD patients may exhibit aging-related characteristics. Therefore, frailty assessments should be conducted as early as possible in IBD patients.
Keywords	Mendelian randomization ; Inflammatory bowel disease ; Frailty ; Sarcopenia ; Medicine ; R
Subject code	610
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: BIM–GIS Integrated Utilization in Urban Disaster Management

Yu Cao / Cong Xu / Nur Mardhiyah Aziz / Syahrul Nizam Kamaruzzaman

Remote Sensing, Vol 15, Iss 1331, p

The Contributions, Challenges, and Future Directions

2023 Volume 1331

Abstract: In the 21st Century, disasters have severe negative impacts on cities worldwide. Given the significant casualties and property damage caused by disasters, it is necessary for disaster management organizations and the public to enhance urban disaster ... ...

Abstract	In the 21st Century, disasters have severe negative impacts on cities worldwide. Given the significant casualties and property damage caused by disasters, it is necessary for disaster management organizations and the public to enhance urban disaster management. As an effective method, BIM (Building Information Modeling)–GIS (Geographic Information System) integration can significantly improve urban disaster management. Despite the significance of BIM–GIS integration, there is rarely the adoption of BIM–GIS integration in urban disaster management, which significantly hinders the development of the quality and efficiency of urban disaster management. To enhance urban disaster management and reduce the negative impact caused by disasters, this study is developed to perform a systematic review of the utilization of BIM–GIS integration in urban disaster management. Through the systematic review, the capabilities of BIM–GIS integration in disaster prevention and mitigation, disaster response, and post-disaster recovery are reviewed and analyzed. Moreover, the data acquisition approaches, interoperability, data utilization and analysis methods, and future directions of BIM–GIS integrated utilization in the disaster management process are also discussed and analyzed. Through this study, the public and urban disaster managers can effectively familiarize themselves with and utilize the capabilities of BIM–GIS integration in urban disaster management, thereby improving the urban disaster management efficiency and the survival rate of disaster victims worldwide. For BIM and GIS software developers, this study can support them to familiarize themselves with the methods and trends of BIM–GIS integrated utilization in urban disaster management and thus optimize the development of software for BIM and GIS.
Keywords	building information modeling ; geographic information system ; urban disaster management ; urban hazard management ; Science ; Q
Subject code	710 ; 720
Language	English
Publishing date	2023-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Omicron subvariant BA.5 is highly contagious but containable

Cong Xu / Jue Wang / Lili Yu / Xinbing Sui / Qibiao Wu

Frontiers in Public Health, Vol

Successful experience from Macau

2023 Volume 10

Abstract: IntroductionDue to its high transmissibility and immune escape, Omicron subvariant BA.5 has become the dominant strain of the SARS-CoV-2 virus and led to escalating COVID-19 cases, how to cope with it becomes an urgent issue. A BA.5 infection surge burst ...

Abstract	IntroductionDue to its high transmissibility and immune escape, Omicron subvariant BA.5 has become the dominant strain of the SARS-CoV-2 virus and led to escalating COVID-19 cases, how to cope with it becomes an urgent issue. A BA.5 infection surge burst out on 18 June 2022 and brought an unprecedented challenge to Macau, the most densely populated region worldwide. This study aimed to analyze the characteristics of this outbreak and summarize the useful anti-epidemic measures and experiences during this outbreak.MethodsAll data were obtained from the Government Portal of Macao SAR (https://www.gov.mo), and the Special Webpage Against Epidemics, the Macao Health Bureau (www.ssm.gov.mo). An epidemiologic study was performed to analyze epidemic outcomes, including the infection rate, the proportion of symptomatic cases, the case fatality ratio (CFR), etc. Data were analyzed using SPSS Version 20. A p-value <0.05 was considered statistically significant. The anti-epidemic measures and experience were reviewed and summarized.ResultsThe BA.5 outbreak resulted in 1,821 new cases, which was significantly more than the cumulative cases of the previous variants of COVID-19 in Macau. The symptomatic cases accounted for 38.71% of the total cases, which was higher than that of the previous variants. After 6-week concerted efforts, Macau effectively controlled the outbreak, with an infection rate of 0.27%, which was much lower than many BA.5-attacked regions. The CFR was approximately 0.86%, which was not statistically different from that of previous variants. Six victims were chronically ill senior elders and their vaccination rate was much lower than the average level. Macau took a comprehensive anti-epidemic strategy to win a quick victory against BA.5, especially the “relatively static” strategy that was first formulated and applied by Macau for the management of the COVID-19 pandemic. Successful experience showed that although BA.5 was highly contagious, it could be contained by comprehensive anti-epidemic measures, ...
Keywords	successful experience ; Macau ; Omicron subvariant BA.5 ; “relatively static” strategy ; anti-COVID-19 ; containable ; Public aspects of medicine ; RA1-1270
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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