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Journal of Iron and Steel Research(International) 2024年第5期31卷 1139-1152页

作者： Zhi-qiang Peng Zi-bing Hou Kai Yi Kun-hui Guo Dong-wei Guo Guang-hua Wen College of Materials Science and Engineering Chongqing UniversityChongqing400044China Chongqing Key Laboratory of Vanadium-Titanium Metallurgy and New Materials Chongqing UniversityChongqing400044China

The correlation between the longitudinal crack occurrence and integrated heat transfer of the mold with data mining methods was investigated.Firstly,three kinds of support vector machine models based on principal component analysis with different input features were established to explore the effect of integrated heat transfer on the accuracy of the prediction model for the longitudinal crack.The results show that the accuracy was improved while features including mean and standard deviation of integrated heat transfer were added.Then,the difference in integrated heat transfer between defect and normal samples under the same process parameters was quantitatively compared.Compared with normal samples,the temperature difference of cooling water for defect samples decreased by 0.65%,and the temperature difference fluctuation increased by 31.1%.Finally,the literature data were used to provide support for the quantitative correlation according to defect formation mechanism.A new criterion for the prediction of longitudinal crack and a discovering method for correlation between product quality and process parameters in the manufacturing industry have been provided.

关键词： Continuous casting slab Longitudinal surface crack Heat transfer data mining Quantitative correlation

Acupoint Selection Standards of Auricular Therapy in the Treatment of Maintenance Hemodialysis Insomnia Based on data mining

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World Journal of Traditional Chinese Medicine 2024年第1期10卷 53-64页

作者： Jun-Xin Wang Bing-Qian Zou Yu-Feng Chen Cheng-Long Wang Wei-Hong Li Xue-Ling Ma Xiang-Di Liu Department of TCM Nursing School of NursingBeijing University of Chinese MedicineBeijingChina Department of Healthcare Beijing HospitalNational Center of GerontologyInstitute of Geriatric MedicineChinese Academy of Medical SciencesP.R.China Pharmacology of Integrated Chinese and Western Medicine School of Traditional Chinese MedicineBeijing University of Chinese MedicineBeijingChina Beijing Key Laboratory of TCM Syndrome and Formula School of Traditional Chinese MedicineBeijing University of Chinese MedicineBeijingChina Key Laboratory of TCM Syndrome and Formula School of Traditional Chinese MedicineBeijing University of Chinese MedicineMinistry of EducationBeijingChina

Background:Insomnia is a high-incidence complication in patients undergoing maintenance hemodialysis(MHD).Auricular therapy can effectively improve sleep with few adverse effects.Acupoint selection affects the impact of auricular therapy.However,there is currently a lack of analysis on the standards of acupoint selection.Our study used data mining technology to investigate the acupoint selection principles and characteristics of auricular therapy for the treatment of MHD-related insomnia.Objective:The objective of the study is to explore the standards of acupoint selection in auricular therapy for the treatment of MHD-related insomnia through data mining technology.Materials and Methods:We searched three English(PubMed,WOS,and Embase)and four Chinese(CNKI,VIP,Wangfang,and CBM)databases for studies on auricular therapy for MHD-related insomnia from self-establishment to November 14,2022.Results:Eighty-one publications were involved,which included 33 acupoints.The most common auricular points in patients with MHD-related insomnia were the Shenmen,heart,and kidney points.More applications involved the visceral,nervous system,and specific acupoints.Five effective clusters and two clusters were obtained through cluster analysis,including specific auricular points for insomnia,such as the multi-dream area,neurasthenia area,deep sleep point,and anterior ear lobe.Complex network analysis showed that the core auricular acupoint combinations for the intervention of MHD-related insomnia were Shenmen with kidney,Shenmen with heart,heart with kidney,heart with Shenmen,and heart and Shenmen with subcortex.Conclusions:The selection of auricular points for the treatment of MHD-related insomnia was guided by the heart theory of traditional Chinese medicine.Clinical treatment attaches importance to the use of the multi-dream area,neurasthenia area,and other acupoints.

关键词： Acupoint selection standards auricular therapy data mining insomnia maintenance hemodialysis

Generative pre-trained transformers(GPT)-based automated data mining for building energy management:Advantages,limitations and the future

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Energy and Built Environment

Energy and Built Environment 2024年第1期5卷 143-169页

作者： Chaobo Zhang Jie Lu Yang Zhao Institute of Refrigeration and Cryogenics Zhejiang UniversityHangzhouChina Department of the Built Environment Eindhoven University of TechnologyEindhovenThe Netherlands Key Laboratory of Clean Energy and Carbon Neutrality of Zhejiang Province Jiaxing Research InstituteZhejiang UniversityJiaxingChina

Advanced data mining methods have shown a promising capacity in building energy management.However,in the past decade,such methods are rarely applied in practice,since they highly rely on users to customize solutions according to the characteristics of target building energy systems.Hence,the major barrier is that the practical applications of such methods remain laborious.It is necessary to enable computers to have the human-like ability to solve data mining tasks.Generative pre-trained transformers(GPT)might be capable of addressing this issue,as some GPT models such as GPT-3.5 and GPT-4 have shown powerful abilities on interaction with humans,code generation,and inference with common sense and domain knowledge.This study explores the potential of the most advanced GPT model(GPT-4)in three data mining scenarios of building energy management,i.e.,energy load prediction,fault diagnosis,and anomaly detection.A performance evaluation framework is proposed to verify the capabilities of GPT-4 on generating energy load prediction codes,diagnosing device faults,and detecting abnormal system operation patterns.It is demonstrated that GPT-4 can automatically solve most of the data mining tasks in this domain,which overcomes the barrier of practical applications of data mining methods in this domain.In the exploration of GPT-4,its advantages and limitations are also discussed comprehensively for revealing future research directions in this domain.

关键词： ChatGPT GPT-4 Artificial general intelligence data mining Building energy management

A systematic study of Erzhu Erchen decoction against damp-heat internalized type 2 diabetes based on data mining and experimental verification

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Traditional Medicine Research 2024年第2期9卷 27-41页

作者： Peng-Yu Wang Jian-Fen Shen Shuo Zhang Qing Lan Guan-Di Ma Tong Wang You-Zhi Zhang School of Pharmacy Hubei Engineering Research Center of Traditional Chinese Medicine of South Hubei ProvinceXianning Medical CollegeHubei University of Science and TechnologyXianning 437100China Department of Central Laboratory The First Affiliated Hospital of Jiaxing UniversityJiaxing 314000China

Background:Erzhu Erchen decoction(EZECD),which is based on Erchen decoction and enhanced with Atractylodes lancea and Atractylodes macrocephala,is widely used for the treatment of dampness and heat(The clinical manifestations of Western medicine include thirst,inability to drink more,diarrhea,yellow urine,red tongue,et al.)internalized disease.Nevertheless,the mechanism of EZECD on damp-heat internalized Type 2 diabetes(T2D)remains unknown.We employed data mining,pharmacology databases and experimental verification to study how EZECD treats damp-heat internalized T2D.Methods:The main compounds or genes of EZECD and damp-heat internalized T2D were obtained from the pharmacology databases.Succeeding,the overlapped targets of EZECD and damp-heat internalized T2D were performed by the Gene Ontology,kyoto encyclopedia of genes and genomes analysis.And the compound-disease targets-pathway network were constructed to obtain the hub compound.Moreover,the hub genes and core related pathways were mined with weighted gene co-expression network analysis based on Gene Expression Omnibus database,the capability of hub compound and genes was valid in AutoDock 1.5.7.Furthermore,and violin plot and gene set enrichment analysis were performed to explore the role of hub genes in damp-heat internalized T2D.Finally,the interactions of hub compound and genes were explored using Comparative Toxicogenomics database and quantitative polymerase chain reaction.Results:First,herb-compounds-genes-disease network illustrated that the hub compound of EZECD for damp-heat internalized T2D could be quercetin.Consistently,the hub genes were CASP8,CCL2,and AHR according to weighted gene co-expression network analysis.Molecular docking showed that quercetin could bind with the hub genes.Further,gene set enrichment analysis and Gene Ontology represented that CASP8,or CCL2,is negatively involved in insulin secretion response to the TNF or lipopolysaccharide process,and AHR or CCL2 positively regulated lipid and atherosclerosis,and/or including NOD-lik

关键词： data mining damp-heat internalized type 2 diabetes Erzhu Erchen decoction network pharmacology bioinformatics

data mining Based Research of Development Direction of Waist Protection Equipment

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Medicinal Plant 2024年第2期15卷 84-90页

作者： Lingfeng ZHU Zhizhen LU Haijie YU Haifen YING Zheming LI Huashan FAN Zhoushan Hospital of TCM Zhoushan 316000China The Third Clinical School of Zhejiang Chinese Medical University Hangzhou 310053China Shengsi Hospital of TCM Zhoushan 2024502China

[Objectives]To explore the trend of brands towards the design of waist protection products through data mining,and to provide reference for the design concept of the contour of waist protection pillow.[Methods]The structural design information of all waist protection equipment was collected from the national Internet platform,and the data were classified and a database was established.IBM SPSS 26.0 and MATLAB 2018a were used to analyze the data and tabulate them in Tableau 2022.4.After the association rules were clarified,the data were imported into Cinema 4D R21 to create the concept contour of waist protection pillow.[Results]The average and standard deviation of the single airbag design were the highest in all groups,with an average of 0.511 and a standard deviation of 0.502.The average and standard deviation of the upper and lower dual airbags were the lowest in all groups,with an average of 0.015 and a standard deviation of 0.120;the correlation coefficient between single airbag and 120°arc stretching was 0.325,which was positively correlated with each other(P<0.01);the correlation coefficient between multiple airbags and 360°encircling fitting was 0.501,which was positively correlated with each other and had the highest correlation degree(P<0.01).[Conclusions]The single airbag design is well recognized by companies,and has received the highest attention among all brand products.While focusing on single airbag design,most brands will consider the need to add 120°arc stretching elements in product design.At the time of focusing on multiple airbag design,some brands believe that 360°encircling fitting elements need to be added to the product,and the correlation between the two is the highest among all groups.

关键词： Spine Low back pain data mining Airbag Stretching Fitting Steel plate support Bidirectional compression Conceptual contour Design

Detection of Knowledge on Social Media Using data mining Techniques

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Open Journal of Applied Sciences 2024年第2期14卷 472-482页

作者： Aseel Abdullah Alolayan Ahmad A. Alhamed Department of Information Systems King Saud University Riyadh Saudi Arabia

In light of the rapid growth and development of social media, it has become the focus of interest in many different scientific fields. They seek to extract useful information from it, and this is called (knowledge), such as extracting information related to people’s behaviors and interactions to analyze feelings or understand the behavior of users or groups, and many others. This extracted knowledge has a very important role in decision-making, creating and improving marketing objectives and competitive advantage, monitoring events, whether political or economic, and development in all fields. Therefore, to extract this knowledge, we need to analyze the vast amount of data found within social media using the most popular data mining techniques and applications related to social media sites.

关键词： data mining Knowledge data mining Techniques Social Media

Forecasting the Academic Performance by Leveraging Educational data mining

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Intelligent Automation & Soft Computing 2024年第2期39卷 213-231页

作者： Mozamel M.Saeed Department of Computer Science Prince Sattam bin Abdulaziz UniversityAl Kharj11912Saudi Arabia

The study aims to recognize how efficiently Educational datamining(EDM)integrates into Artificial Intelligence(AI)to develop skills for predicting students’performance.The study used a survey questionnaire and collected data from 300 undergraduate students of Al Neelain University.The first step’s initial population placements were created using Particle Swarm Optimization(PSO).Then,using adaptive feature space search,Educational Grey Wolf Optimization(EGWO)was employed to choose the optimal attribute combination.The second stage uses the SVMclassifier to forecast classification accuracy.Different classifiers were utilized to evaluate the performance of students.According to the results,it was revealed that AI could forecast the final grades of students with an accuracy rate of 97%on the test dataset.Furthermore,the present study showed that successful students could be selected by the Decision Tree model with an efficiency rate of 87.50%and could be categorized as having equal information ratio gain after the semester.While the random forest provided an accuracy of 28%.These findings indicate the higher accuracy rate in the results when these models were implemented on the data set which provides significantly accurate results as compared to a linear regression model with accuracy(12%).The study concluded that the methodology used in this study can prove to be helpful for students and teachers in upgrading academic performance,reducing chances of failure,and taking appropriate steps at the right time to raise the standards of education.The study also motivates academics to assess and discover EDM at several other universities.

关键词： Academic achievement AI algorithms classifiers data mining deep learning

Exploring the medication pattern and mechanism of action of traditional Chinese medicine in treating polycystic ovary syndrome with kidney deficiency and blood stasis based on data mining and network pharmacology

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Medical data mining 2024年第1期7卷 40-52页

作者： Li-Jun Zhou Yi-Ling Liu Department of Gynaecology and Obstetrics Chongqing Ba’nan District Traditional Chinese Medicine HospitalChongqing 401320China Department of Nephropathy Endocrinology Suzhou Hospital of Integrated Traditional Chinese and Western MedicineSuzhou 215000China.

Background:Using network pharmacology to explore the potential molecular mechanism of traditional Chinese medicine in treating polycystic ovary syndrome(PCOS)with kidney deficiency and blood stasis syndrome.Method:Collect the related literature materials of PCOS with kidney deficiency and blood stasis syndrome treated by traditional Chinese medicine in four databases in recent ten years,extract the information of prescriptions and complete the frequency analysis.Traditional Chinese Medicine Systems Pharmacology database was used to screen out the effective components.Use Online Mendelian Inheritance in Man and other databases to screen PCOS disease targets.The intersection targets obtained by clustering prescription and PCOS disease targets were submitted to STRING database for protein-protein interaction network analysis,and Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes pathways were analysed by Metascape.Result:There are 155 kinds of traditional Chinese medicines used in the literature.The most commonly utilized ones are Cuscutae Semen,Angelicae Sinensis Radix,and Rehmanniae Radix Praeparata.The results of the cluster analysis indicated that the plants most commonly found throughout the prescription were Leonuri Herba,Lycopi Herba,Dipsaci Radix,etc.GO results show that biological processes include cell reaction to organic nitrogen compounds and cell reaction to nitrogen compounds.The functional display of GO molecule includes cytokine receptor binding,signal receptor regulator activity and so on.Kyoto Encyclopedia of Genes and Genomes results show that the possible mechanisms of action are cancer pathway,an endocrine resistance signal pathway.Conclusion:Through data mining,the cluster prescription for PCOS with kidney deficiency and blood stasis syndrome is Leonuri Herba,Lycopi Herba,Dipsaci Radix,etc.The network pharmacology research of cluster prescription shows that the main drug components for treating PCOS with kidney deficiency and blood stasis syndrome are quercetin,kaempferol,luteolin,tan

关键词： polycystic ovary syndrome data mining syndrome of kidney deficiency and blood stasis network pharmacology

Integrated data mining and network pharmacology to discover a novel traditional Chinese medicine prescription against diabetic retinopathy and reveal its mechanism

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TMR Modern Herbal Medicine 2024年第2期7卷 41-55页

作者： Kai-Lun Zhang Xu Wang Xiang-Wei Chang Jun-Fei Gu Bo-Yang Zhu Shi-Bing Wei Bo Wu Can Peng Jiu-Sheng Nie De-Ling Wu College of Pharmacy Anhui University of Chinese MedicineHefei 230012China School of Traditional Chinese Medicine and School of Integrated Chinese and Western Medicine Nanjing University of Chinese MedicineNanjing 210023China MOE-Anhui Joint Collaborative Innovation Center for Quality Improvement of Anhui Genuine Chinese Medicinal Materials Anhui University of Chinese MedicineHefei 230012China Institute of Pharmaceutics Anhui Academy of Chinese MedicineHefei 230012China Anhui Province Key Laboratory of Pharmaceutical Preparation Technology and Application Anhui University of Chinese MedicineHefei 230012China Engineering Technology Research Center of Modernized Pharmaceutics Anhui Education Department(AUCM)Hefei 230012China The First Clinical Medical College Anhui University of Chinese MedicineHefei 230012China

Background:Diabetic retinopathy(DR)is currently the leading cause of blindness in elderly individuals with diabetes.Traditional Chinese medicine(TCM)prescriptions have shown remarkable effectiveness for treating DR.This study aimed to screen a novel TCM prescription against DR from patents and elucidate its medication rule and molecular mechanism using data mining,network pharmacology,molecular docking and molecular dynamics(MD)simulation.Method:TCM prescriptions for treating DR was collected from patents and a novel TCM prescription was identified using data mining.Subsequently,the mechanism of the novel TCM prescription against DR was explored by constructing a network of core TCMs-core active ingredients-core targets-core pathways.Finally,molecular docking and MD simulation were employed to validate the findings from network pharmacology.Result:The TCMs of the collected prescriptions primarily possessed bitter and cold properties with heat-clearing and supplementing effects,attributed to the liver,lung and kidney channels.Notably,a novel TCM prescription for treating DR was identified,composed of Lycii Fructus,Chrysanthemi Flos,Astragali Radix and Angelicae Sinensis Radix.Twenty core active ingredients and ten core targets of the novel TCM prescription for treating DR were screened.Moreover,the novel TCM prescription played a crucial role for treating DR by inhibiting inflammatory response,oxidative stress,retinal pigment epithelium cell apoptosis and retinal neovascularization through various pathways,such as the AGE-RAGE signaling pathway in diabetic complications and the MAPK signaling pathway.Finally,molecular docking and MD simulation demonstrated that almost all core active ingredients exhibited satisfactory binding energies to core targets.Conclusions:This study identified a novel TCM prescription and unveiled its multi-component,multi-target and multi-pathway characteristics for treating DR.These findings provide a scientific basis and novel insights into the development of drugs for DR prevention and

关键词： TCM prescriptions diabetic retinopathy medication rule molecular mechanism data mining network pharmacology molecular docking

An Advanced Image Processing Technique for Backscatter-Electron data by Scanning Electron Microscopy for Microscale Rock Exploration

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Journal of Earth Science 2024年第1期35卷 301-305页

作者： Zhaoliang Hou Kunfeng Qiu Tong Zhou Yiwei Cai Frontiers Science Center for Deep-time Digital Earth China University of GeosciencesBeijing 100083China Department of Geology University of ViennaVienna 1090Austria State Key Laboratory of Geological Processes and Mineral Resources School of Earth Sciences and ResourcesChinaUniversity of GeosciencesBeijing 100083China

Backscatter electron analysis from scanning electron microscopes(BSE-SEM)produces high-resolution image data of both rock samples and thin-sections,showing detailed structural and geochemical(mineralogical)information.This allows an in-depth exploration of the rock microstructures and the coupled chemical characteristics in the BSE-SEM image to be made using image processing techniques.Although image processing is a powerful tool for revealing the more subtle data“hidden”in a picture,it is not a commonly employed method in geoscientific microstructural analysis.Here,we briefly introduce the general principles of image processing,and further discuss its application in studying rock microstructures using BSE-SEM image data.

关键词： Image processing rock microstructures electron-based imaging data mining