With the improvement of living standards, more and more people are pursuing personalized routes. This paper uses personalized mining of interest points of ethnic minority tourism demand groups, extracts customer data features in social networks, and constructs data features of interesting topic factors, geographic location factors, and user access frequency factors, using LDA topic models and matrix decomposition models to perform feature vectorization processing on user sign-in records and build deep learning recommendation model (DLM). Using this model to compare with the traditional recommendation model and the recommendation model of a single data feature module, the experimental results show the following: (1) The fitting error of DLM recommendation results is significantly reduced, and its recommendation accuracy rate is 50% higher than that of traditional recommendation algorithms. The experimental results show that the DLM constructed in this paper has good learning and training performance, and the recommendation effect is good. (2) In this method, the performance of the DLM is significantly higher than other POI recommendation methods in terms of the accuracy or recall rate of the recommendation algorithm. Among them, the accuracy rates of the top five, top ten, and top twenty recommended POIs are increased by 9.9%, 7.4%, and 7%, respectively, and the recall rate is increased by 4.2%, 7.5%, and 14.4%, respectively.
{"title":"Research on Personalized Minority Tourist Route Recommendation Algorithm Based on Deep Learning","authors":"Guang Liu","doi":"10.1155/2022/8063652","DOIUrl":"https://doi.org/10.1155/2022/8063652","url":null,"abstract":"With the improvement of living standards, more and more people are pursuing personalized routes. This paper uses personalized mining of interest points of ethnic minority tourism demand groups, extracts customer data features in social networks, and constructs data features of interesting topic factors, geographic location factors, and user access frequency factors, using LDA topic models and matrix decomposition models to perform feature vectorization processing on user sign-in records and build deep learning recommendation model (DLM). Using this model to compare with the traditional recommendation model and the recommendation model of a single data feature module, the experimental results show the following: (1) The fitting error of DLM recommendation results is significantly reduced, and its recommendation accuracy rate is 50% higher than that of traditional recommendation algorithms. The experimental results show that the DLM constructed in this paper has good learning and training performance, and the recommendation effect is good. (2) In this method, the performance of the DLM is significantly higher than other POI recommendation methods in terms of the accuracy or recall rate of the recommendation algorithm. Among them, the accuracy rates of the top five, top ten, and top twenty recommended POIs are increased by 9.9%, 7.4%, and 7%, respectively, and the recall rate is increased by 4.2%, 7.5%, and 14.4%, respectively.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"20 1","pages":"8063652:1-8063652:9"},"PeriodicalIF":0.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79032800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objective. This study aimed to evaluate the improvement and neurological function changes of patients with ischemic stroke in the posterior circulation before and after interventional therapy using magnetic resonance imaging (MRI) under genetic algorithm and compressed sensing algorithm. Methods. Thirty-six patients with posterior circulation ischemia who visited the interventional cerebrovascular disease area were included in this study. The treatment effect was observed through abnormal signal changes in the lesion area on each sequence of MRI images before and after treatment. The National Institutes of Health Stroke Scale (NIHSS) was used for the evaluation of the changes in neurological function. Results. The real data experiment results suggested that the peak signal-to-noise ratio (PSNR) = 39.33 and structure similarity (SSIM) = 0.96 in the algorithm reconstructed image, which showed no significant difference with the simulation experiment results of PSNR = 35.19 and SSIM = 0.96 ( P < 0.05 ). In addition, the stenosis rate after interventional treatment (13.89%) was substantially lower than that before treatment (91.67%) ( P < 0.05 ). Cerebral blood flow (CBF) of the bilateral occipital lobes and cerebellum after six months of treatment was higher than that before treatment ( P < 0.05 ), and the incidence of postoperative restenosis was 11.11% (4/36). Conclusion. The combination of genetic algorithm and compressed sensing algorithm had a good effect on MRI image processing. The posterior circulation ischemia interventional stent implantation can effectively improve the stenosis of the vertebral artery and vertebral basilar artery as well as the cerebral tissue perfusion in the ischemic area, which improved the clinical symptoms substantially and reduced the probability of restenosis.
{"title":"Curative Effect of Interventional Therapy and Neurological Changes in Ischemic Stroke of Posterior Circulation Evaluated by Magnetic Resonance Imaging under Genetic Algorithm","authors":"Xiaodu Yu, Xingyou Zheng, Daoyou Cheng","doi":"10.1155/2022/2656706","DOIUrl":"https://doi.org/10.1155/2022/2656706","url":null,"abstract":"Objective. This study aimed to evaluate the improvement and neurological function changes of patients with ischemic stroke in the posterior circulation before and after interventional therapy using magnetic resonance imaging (MRI) under genetic algorithm and compressed sensing algorithm. Methods. Thirty-six patients with posterior circulation ischemia who visited the interventional cerebrovascular disease area were included in this study. The treatment effect was observed through abnormal signal changes in the lesion area on each sequence of MRI images before and after treatment. The National Institutes of Health Stroke Scale (NIHSS) was used for the evaluation of the changes in neurological function. Results. The real data experiment results suggested that the peak signal-to-noise ratio (PSNR) = 39.33 and structure similarity (SSIM) = 0.96 in the algorithm reconstructed image, which showed no significant difference with the simulation experiment results of PSNR = 35.19 and SSIM = 0.96 (\u0000 \u0000 P\u0000 <\u0000 0.05\u0000 \u0000 ). In addition, the stenosis rate after interventional treatment (13.89%) was substantially lower than that before treatment (91.67%) (\u0000 \u0000 P\u0000 <\u0000 0.05\u0000 \u0000 ). Cerebral blood flow (CBF) of the bilateral occipital lobes and cerebellum after six months of treatment was higher than that before treatment (\u0000 \u0000 P\u0000 <\u0000 0.05\u0000 \u0000 ), and the incidence of postoperative restenosis was 11.11% (4/36). Conclusion. The combination of genetic algorithm and compressed sensing algorithm had a good effect on MRI image processing. The posterior circulation ischemia interventional stent implantation can effectively improve the stenosis of the vertebral artery and vertebral basilar artery as well as the cerebral tissue perfusion in the ischemic area, which improved the clinical symptoms substantially and reduced the probability of restenosis.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"78 1","pages":"2656706:1-2656706:11"},"PeriodicalIF":0.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83883218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Divakaran, Somashekhar Malipatil, Tareeq Zaid, M. Pushpalatha, Vilaskumar Patil, A. Chakrapani, T. Titus, K. Srihari, M. R. Vignesh, Baswaraj Gadgay, Venkatesa Prabhu Sundramurthy
With increasing advancements in the field of telecommunication, the attainment of a higher data transfer rate is essentially a greater need to meet high-performance communication. The exploitation of the fuzzy system in the wireless telecommunication systems, especially in Fifth Generation Mobile Networks (or) 5G networks is a vital paradigm in telecommunication markets. A comprehensive survey is dealt in the paper, where it initially reviews the basic understanding of fuzzy systems over 5G telecommunication. The literature studies are collected from various repositories that include reference materials, Internet, and other books. The collection of articles is based on empirical or evidence-based from various peer-reviewed journals, conference proceedings, dissertations, and theses. Most of the existing soft computing models are streamlined to certain applications of 5G networking. Firstly, it is hence essential to provide the readers to find research gaps and new innovative models on wide varied applications of 5G. Secondly, it deals with the scenarios in which the fuzzy systems are developed under the 5G platform. Thirdly, it discusses the applicability of fuzzy logic systems on various 5G telecommunication applications. Finally, the paper derives the conclusions associated with various studies on the fuzzy systems that have been utilized for the improvement of 5G telecommunication systems.
{"title":"Technical Study on 5G Using Soft Computing Methods","authors":"J. Divakaran, Somashekhar Malipatil, Tareeq Zaid, M. Pushpalatha, Vilaskumar Patil, A. Chakrapani, T. Titus, K. Srihari, M. R. Vignesh, Baswaraj Gadgay, Venkatesa Prabhu Sundramurthy","doi":"10.1155/2022/1570604","DOIUrl":"https://doi.org/10.1155/2022/1570604","url":null,"abstract":"With increasing advancements in the field of telecommunication, the attainment of a higher data transfer rate is essentially a greater need to meet high-performance communication. The exploitation of the fuzzy system in the wireless telecommunication systems, especially in Fifth Generation Mobile Networks (or) 5G networks is a vital paradigm in telecommunication markets. A comprehensive survey is dealt in the paper, where it initially reviews the basic understanding of fuzzy systems over 5G telecommunication. The literature studies are collected from various repositories that include reference materials, Internet, and other books. The collection of articles is based on empirical or evidence-based from various peer-reviewed journals, conference proceedings, dissertations, and theses. Most of the existing soft computing models are streamlined to certain applications of 5G networking. Firstly, it is hence essential to provide the readers to find research gaps and new innovative models on wide varied applications of 5G. Secondly, it deals with the scenarios in which the fuzzy systems are developed under the 5G platform. Thirdly, it discusses the applicability of fuzzy logic systems on various 5G telecommunication applications. Finally, the paper derives the conclusions associated with various studies on the fuzzy systems that have been utilized for the improvement of 5G telecommunication systems.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"1 1","pages":"1570604:1-1570604:7"},"PeriodicalIF":0.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89088688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Due to the rapid development of social economy, general hospital buildings of China are undergoing changes in their models, technology, and medical systems. Changes in the model of hospitals may affect the functional structure, streamline layout, and spatial form of the hospital building. The biological-psychological-social (biopsychosocial) model covers the overall significant factors in healthcare. The model focuses on the hospital public environment. For the advocacy of patient-centered medical concepts, researchers have put forward newer and higher requirements as well. However, there is scarcity of research that targets the psychological impact of general hospital public space environment construction on the patients’ health. Moreover, there is no unanimously recognized standard questionnaire for the public space environment. The purpose of this article is to investigate the needs of inpatients for the space environment, to understand the influencing factors of various space environments, and to explore the law of patient needs. The research intends to provide a theoretical background for the construction of a patient-centered space environment. A dedicated questionnaire was designed to systematically collect the significant features and factors. Using cluster sampling, a total of four medical and surgical wards were investigated. The data obtained from 430 questionnaires were statistically analyzed by SPSS-10.0. Various statistical operations such as descriptive analysis, independent sample t test, one-way analysis of variance, and linear and logistic regressions were performed over the data. The psychological impact was studied from four aspects. The highest score (3-4 points) obtained for the larger number of patients (84.4%) testifies that the public space environment has a significant impact on patients’ mental health. Besides healthcare, outcomes of the paper may be used in various related domains such as psychological well beings, spatial analysis, social interaction, and public space designing.
{"title":"Psychological Impact of the Hospital Indoor Public Spaces on Patients' Health, Assessment, and Analysis","authors":"Zhe Du, Baogang Lin, Zhenyi Chen","doi":"10.1155/2022/4010643","DOIUrl":"https://doi.org/10.1155/2022/4010643","url":null,"abstract":"Due to the rapid development of social economy, general hospital buildings of China are undergoing changes in their models, technology, and medical systems. Changes in the model of hospitals may affect the functional structure, streamline layout, and spatial form of the hospital building. The biological-psychological-social (biopsychosocial) model covers the overall significant factors in healthcare. The model focuses on the hospital public environment. For the advocacy of patient-centered medical concepts, researchers have put forward newer and higher requirements as well. However, there is scarcity of research that targets the psychological impact of general hospital public space environment construction on the patients’ health. Moreover, there is no unanimously recognized standard questionnaire for the public space environment. The purpose of this article is to investigate the needs of inpatients for the space environment, to understand the influencing factors of various space environments, and to explore the law of patient needs. The research intends to provide a theoretical background for the construction of a patient-centered space environment. A dedicated questionnaire was designed to systematically collect the significant features and factors. Using cluster sampling, a total of four medical and surgical wards were investigated. The data obtained from 430 questionnaires were statistically analyzed by SPSS-10.0. Various statistical operations such as descriptive analysis, independent sample t test, one-way analysis of variance, and linear and logistic regressions were performed over the data. The psychological impact was studied from four aspects. The highest score (3-4 points) obtained for the larger number of patients (84.4%) testifies that the public space environment has a significant impact on patients’ mental health. Besides healthcare, outcomes of the paper may be used in various related domains such as psychological well beings, spatial analysis, social interaction, and public space designing.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"34 1","pages":"4010643:1-4010643:8"},"PeriodicalIF":0.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74083856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aimed at discussing deep learning-based dual-source spiral computed tomography (DSCT) image in the evaluation of the efficacy of statins in the treatment of coronary artery plaque. A convolutional neural network (CNN) algorithm was proposed in this study. On this basis, the model was improved, the Res-Net network was applied to reconstruct the computed tomography (CT) image, and the deep learning network model Mask R-CNN was constructed to enhance the ability of image reconstruction. Then, 80 patients with coronary artery disease who were treated in hospital were selected as the research objects and divided into a control group (n = 40) and an observation group (n = 40). There were 21 male patients and 19 female patients in the control group, with an average age of 52 ± 3.2 years; there were 24 male patients and 16 female patients in the observation group, with an average age of 51 ± 2.4 years. The observation group was reconstructed with the constructed model, and patients in the control group received traditional CT. The interval between two examinations was 6–12 months, with an average interval of 8 ± 1.78 months. During the interval, all patients received conservative treatment mainly with atorvastatin. The general data of the two groups were comparable without statistical significance ( P > 0.05 ). A network model was constructed to measure the coronary plaque and vascular volume of the patients, and the images were reconstructed on the Res-Net network. The loss value of Res-Net network was stable at the lowest level around 0.02, showing a very fast effect in the training process. After statin treatment, the vascular volume and coronary plaque volume of the patients were decreased obviously ( P < 0.05 ). The average time spent in the network model was 1.20 seconds. The average time spent in the measurement of each disc by doctors A, B, and C was 186 seconds, 158 seconds, and 142 seconds, respectively. The construction of network model markedly improved the speed of CT image diagnosis and treatment. In conclusion, the Res-Net network model proposed in this study had certain feasibility and effectiveness for dual-source CT (DSCT) image segmentation and could effectively improve the clinical information evaluation of CT images from patients with coronary artery disease, which had important reference value for the development of intelligent medical equipment. It could provide a new diagnostic method for clinical prediction and diagnosis of coronary artery disease (CAD).
{"title":"Evaluation of the Efficacy of Statins in the Treatment of Coronary Artery Plaque Using Dual-Source Spiral Computed Tomography Image Features under Deep Learning","authors":"Weizhong Yu, Haixia Ji, Qingjun Tan","doi":"10.1155/2022/1810712","DOIUrl":"https://doi.org/10.1155/2022/1810712","url":null,"abstract":"This study aimed at discussing deep learning-based dual-source spiral computed tomography (DSCT) image in the evaluation of the efficacy of statins in the treatment of coronary artery plaque. A convolutional neural network (CNN) algorithm was proposed in this study. On this basis, the model was improved, the Res-Net network was applied to reconstruct the computed tomography (CT) image, and the deep learning network model Mask R-CNN was constructed to enhance the ability of image reconstruction. Then, 80 patients with coronary artery disease who were treated in hospital were selected as the research objects and divided into a control group (n = 40) and an observation group (n = 40). There were 21 male patients and 19 female patients in the control group, with an average age of 52 ± 3.2 years; there were 24 male patients and 16 female patients in the observation group, with an average age of 51 ± 2.4 years. The observation group was reconstructed with the constructed model, and patients in the control group received traditional CT. The interval between two examinations was 6–12 months, with an average interval of 8 ± 1.78 months. During the interval, all patients received conservative treatment mainly with atorvastatin. The general data of the two groups were comparable without statistical significance (\u0000 \u0000 P\u0000 >\u0000 0.05\u0000 \u0000 ). A network model was constructed to measure the coronary plaque and vascular volume of the patients, and the images were reconstructed on the Res-Net network. The loss value of Res-Net network was stable at the lowest level around 0.02, showing a very fast effect in the training process. After statin treatment, the vascular volume and coronary plaque volume of the patients were decreased obviously (\u0000 \u0000 P\u0000 <\u0000 0.05\u0000 \u0000 ). The average time spent in the network model was 1.20 seconds. The average time spent in the measurement of each disc by doctors A, B, and C was 186 seconds, 158 seconds, and 142 seconds, respectively. The construction of network model markedly improved the speed of CT image diagnosis and treatment. In conclusion, the Res-Net network model proposed in this study had certain feasibility and effectiveness for dual-source CT (DSCT) image segmentation and could effectively improve the clinical information evaluation of CT images from patients with coronary artery disease, which had important reference value for the development of intelligent medical equipment. It could provide a new diagnostic method for clinical prediction and diagnosis of coronary artery disease (CAD).","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"39 1","pages":"1810712:1-1810712:9"},"PeriodicalIF":0.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83269690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Weisen Pan, Jian Li, Lisa Gao, Liexiang Yue, Yan Yang, Lingli Deng, Chao Deng
In this study, we propose a method named Semantic Graph Neural Network (SGNN) to address the challenging task of email classification. This method converts the email classification problem into a graph classification problem by projecting email into a graph and applying the SGNN model for classification. The email features are generated from the semantic graph; hence, there is no need of embedding the words into a numerical vector representation. The method performance is tested on the different public datasets. Experiments in the public dataset show that the presented method achieves high accuracy in the email classification test against a few public datasets. The performance is better than the state-of-the-art deep learning-based method in terms of spam classification.
{"title":"Semantic Graph Neural Network: A Conversion from Spam Email Classification to Graph Classification","authors":"Weisen Pan, Jian Li, Lisa Gao, Liexiang Yue, Yan Yang, Lingli Deng, Chao Deng","doi":"10.1155/2022/6737080","DOIUrl":"https://doi.org/10.1155/2022/6737080","url":null,"abstract":"In this study, we propose a method named Semantic Graph Neural Network (SGNN) to address the challenging task of email classification. This method converts the email classification problem into a graph classification problem by projecting email into a graph and applying the SGNN model for classification. The email features are generated from the semantic graph; hence, there is no need of embedding the words into a numerical vector representation. The method performance is tested on the different public datasets. Experiments in the public dataset show that the presented method achieves high accuracy in the email classification test against a few public datasets. The performance is better than the state-of-the-art deep learning-based method in terms of spam classification.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"20 1","pages":"6737080:1-6737080:8"},"PeriodicalIF":0.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86267469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tao Zheng, Guofeng Shao, Qingyun Zhou, Qinning Wang, Mengmeng Ye
This study was to analyze the impacts of the image segmentation model and computed tomography angiography (CTA) on the clinical diagnosis of aortic constriction under the background of artificial intelligence. In this study, 126 patients with congenital aortic constriction (CAC) diagnosed by surgery were selected as the research objects and routine digital subtraction angiography (DSA) and CTA were performed. Then, the traditional active contour model (AC model) was optimized based on the local area information to construct a new image segmentation model for intelligent segmentation and reconstruction of the CTA images of patients. The results revealed that compared with the AC model and the image segmentation model based on region growth (RG model) obtained from angiography segmentation, the algorithm constructed in this study showed a smaller segmentation range for angiography images and more accurate segmentation results. The quantitative data results suggested that the evolution times and running time of the constructed model were less than those of the AC and RG models P < 0.05 . Based on the gold standard of DSA examination results, there were 122 correctly diagnosed cases, 3 missed diagnosed cases, and 1 misdiagnosed by CTA, so the diagnosis coincidence rate was 96.83%. Compared with DSA, the average inner diameter and average pressure difference of patients with precatheter, paracatheter, and postcatheter type were not greatly different in CTA P > 0.05 . The CTA examination suggested there were 154 cases with intracardiac structural abnormalities, with a detection rate of 86.52%; there were 32 cases of cardiac-vascular connection abnormalities, with a detection rate of 100%; and there were 79 extracardiac vascular abnormalities, with the detection rate of 95.18%. It indicated that the optimized image segmentation model based on local area information proposed in this paper has excellent segmentation performance for CT angiography images and has good segmentation effect and efficiency. The CTA based on the artificial intelligence image segmentation model showed a better diagnostic effect on abnormal heart-vascular connection and abnormal extracardiac blood vessels and can be used as an effective examination method for clinical diagnosis of CAC.
{"title":"Artificial Intelligence Segmentation Model-Based Computed Tomography Angiography Image in the Diagnosis of Congenital Aortic Constriction","authors":"Tao Zheng, Guofeng Shao, Qingyun Zhou, Qinning Wang, Mengmeng Ye","doi":"10.1155/2022/9057901","DOIUrl":"https://doi.org/10.1155/2022/9057901","url":null,"abstract":"This study was to analyze the impacts of the image segmentation model and computed tomography angiography (CTA) on the clinical diagnosis of aortic constriction under the background of artificial intelligence. In this study, 126 patients with congenital aortic constriction (CAC) diagnosed by surgery were selected as the research objects and routine digital subtraction angiography (DSA) and CTA were performed. Then, the traditional active contour model (AC model) was optimized based on the local area information to construct a new image segmentation model for intelligent segmentation and reconstruction of the CTA images of patients. The results revealed that compared with the AC model and the image segmentation model based on region growth (RG model) obtained from angiography segmentation, the algorithm constructed in this study showed a smaller segmentation range for angiography images and more accurate segmentation results. The quantitative data results suggested that the evolution times and running time of the constructed model were less than those of the AC and RG models \u0000 \u0000 \u0000 \u0000 P\u0000 <\u0000 0.05\u0000 \u0000 \u0000 \u0000 . Based on the gold standard of DSA examination results, there were 122 correctly diagnosed cases, 3 missed diagnosed cases, and 1 misdiagnosed by CTA, so the diagnosis coincidence rate was 96.83%. Compared with DSA, the average inner diameter and average pressure difference of patients with precatheter, paracatheter, and postcatheter type were not greatly different in CTA \u0000 \u0000 \u0000 \u0000 P\u0000 >\u0000 0.05\u0000 \u0000 \u0000 \u0000 . The CTA examination suggested there were 154 cases with intracardiac structural abnormalities, with a detection rate of 86.52%; there were 32 cases of cardiac-vascular connection abnormalities, with a detection rate of 100%; and there were 79 extracardiac vascular abnormalities, with the detection rate of 95.18%. It indicated that the optimized image segmentation model based on local area information proposed in this paper has excellent segmentation performance for CT angiography images and has good segmentation effect and efficiency. The CTA based on the artificial intelligence image segmentation model showed a better diagnostic effect on abnormal heart-vascular connection and abnormal extracardiac blood vessels and can be used as an effective examination method for clinical diagnosis of CAC.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"35 1","pages":"9057901:1-9057901:10"},"PeriodicalIF":0.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77814025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the frequent occurrence of international trade communication, in order to improve the quality of communication, this paper proposes a study on the translation of international trade English phrases and grammar. First, with the help of a rectangular window function, the composition principle of international trade English phrases is determined. Then, the horizontal feature aggregation point method is introduced to build a mathematical model of the characteristic identification of the English phrases. Finally, the sparse matrix representation of the source phrase is constructed to complete the extraction and preprocessing of the English phrase features. The input English sentence is converted into the output sentence, the form and POS factors of the English semantic translation are extracted, and a lemma is introduced to obtain the surface form of international trade English language factors. According to the international trade grammar analysis method, this paper decomposes the translation model, decomposes English sentences into small phrases for translation, and completes the research on international trade English phrase and grammar translation. The experimental results show that this method has high accuracy in the feature extraction of international trade English phrases, and the error rate is low, which is feasible.
{"title":"International Trade English Phrases and Grammar Translation","authors":"Xinxin Wang","doi":"10.1155/2022/3726492","DOIUrl":"https://doi.org/10.1155/2022/3726492","url":null,"abstract":"With the frequent occurrence of international trade communication, in order to improve the quality of communication, this paper proposes a study on the translation of international trade English phrases and grammar. First, with the help of a rectangular window function, the composition principle of international trade English phrases is determined. Then, the horizontal feature aggregation point method is introduced to build a mathematical model of the characteristic identification of the English phrases. Finally, the sparse matrix representation of the source phrase is constructed to complete the extraction and preprocessing of the English phrase features. The input English sentence is converted into the output sentence, the form and POS factors of the English semantic translation are extracted, and a lemma is introduced to obtain the surface form of international trade English language factors. According to the international trade grammar analysis method, this paper decomposes the translation model, decomposes English sentences into small phrases for translation, and completes the research on international trade English phrase and grammar translation. The experimental results show that this method has high accuracy in the feature extraction of international trade English phrases, and the error rate is low, which is feasible.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"2 1","pages":"3726492:1-3726492:6"},"PeriodicalIF":0.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78675235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The artificial intelligence education system promotes the rooting of artificial intelligence in the education field and accelerates its entry into the era of intelligent education. This article focuses on the development of the artificial intelligence education system and proposes an artificial intelligence education system based on differential evolution algorithm optimization support vector machine. First, the processing of educational demand information data is automated, then a differential evolution algorithm is built to optimize the support vector machine model, and the model is used to implement various educational tasks to achieve automated education. The test results show that the model classification accuracy, classification recall rate, classification accuracy rate, and F1-score value are 4 items. Performances have been improved to improve the efficiency of education work and provide a reference for exploring the application and practice of artificial intelligence in education.
{"title":"Artificial Intelligence Education System Based on Differential Evolution Algorithm to Optimize SVM","authors":"Weilin Long, Yifang Gao","doi":"10.1155/2022/5379646","DOIUrl":"https://doi.org/10.1155/2022/5379646","url":null,"abstract":"The artificial intelligence education system promotes the rooting of artificial intelligence in the education field and accelerates its entry into the era of intelligent education. This article focuses on the development of the artificial intelligence education system and proposes an artificial intelligence education system based on differential evolution algorithm optimization support vector machine. First, the processing of educational demand information data is automated, then a differential evolution algorithm is built to optimize the support vector machine model, and the model is used to implement various educational tasks to achieve automated education. The test results show that the model classification accuracy, classification recall rate, classification accuracy rate, and F1-score value are 4 items. Performances have been improved to improve the efficiency of education work and provide a reference for exploring the application and practice of artificial intelligence in education.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"20 1","pages":"5379646:1-5379646:7"},"PeriodicalIF":0.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80259300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aiming at the problems of poor functionality, high occupancy, and low real-time performance of the currently designed performance appraisal management system for university administrators, a performance appraisal management system for university administrators based on hybrid cloud is designed. According to the characteristics of hybrid cloud technology, the overall functional requirements and feasibility of the system are analyzed, and the assessment scheme of administrative personnel according to the provisions of relevant documents is analyzed. The performance appraisal index system is designed using an analytic hierarchy process. Using the hybrid cloud architecture and B/S mode based on each component as a service model and J2EE development framework, the basic information management subsystem of administrative personnel, performance appraisal information management subsystem, information analysis and data mining subsystem, and platform system management subsystem are developed. Using XML technology and database technology, the system is integrated with the performance appraisal management system of administrators in colleges and universities. Through the design of data flow diagram and E-R diagram, the design of performance appraisal management system for university administrators based on hybrid cloud is realized. The experimental results show that the proposed method has good functionality, can effectively reduce the system occupancy, and can improve the real-time performance of the system.
{"title":"Performance Appraisal Management System of University Administrators Based on Hybrid Cloud","authors":"X. Wu","doi":"10.1155/2022/9326563","DOIUrl":"https://doi.org/10.1155/2022/9326563","url":null,"abstract":"Aiming at the problems of poor functionality, high occupancy, and low real-time performance of the currently designed performance appraisal management system for university administrators, a performance appraisal management system for university administrators based on hybrid cloud is designed. According to the characteristics of hybrid cloud technology, the overall functional requirements and feasibility of the system are analyzed, and the assessment scheme of administrative personnel according to the provisions of relevant documents is analyzed. The performance appraisal index system is designed using an analytic hierarchy process. Using the hybrid cloud architecture and B/S mode based on each component as a service model and J2EE development framework, the basic information management subsystem of administrative personnel, performance appraisal information management subsystem, information analysis and data mining subsystem, and platform system management subsystem are developed. Using XML technology and database technology, the system is integrated with the performance appraisal management system of administrators in colleges and universities. Through the design of data flow diagram and E-R diagram, the design of performance appraisal management system for university administrators based on hybrid cloud is realized. The experimental results show that the proposed method has good functionality, can effectively reduce the system occupancy, and can improve the real-time performance of the system.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"33 1","pages":"9326563:1-9326563:12"},"PeriodicalIF":0.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80419218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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