In order to meet the requirements of users in terms of speed, capacity, storage efficiency, and security, with the goal of improving data redundancy and reducing data storage space, an unbalanced big data compatible cloud storage method based on redundancy elimination technology is proposed. A new big data acquisition platform is designed based on Hadoop and NoSQL technologies. Through this platform, efficient unbalanced data acquisition is realized. The collected data are classified and processed by classifier. The classified unbalanced big data are compressed by Huffman algorithm, and the data security is improved by data encryption. Based on the data processing results, the big data redundancy processing is carried out by using the data deduplication algorithm. The cloud platform is designed to store redundant data in the cloud. The results show that the method in this paper has high data deduplication rate and data deduplication speed rate and low data storage space and effectively reduces the burden of data storage.
{"title":"Unbalanced Big Data-Compatible Cloud Storage Method Based on Redundancy Elimination Technology","authors":"Tingting Yu","doi":"10.1155/2022/1371778","DOIUrl":"https://doi.org/10.1155/2022/1371778","url":null,"abstract":"In order to meet the requirements of users in terms of speed, capacity, storage efficiency, and security, with the goal of improving data redundancy and reducing data storage space, an unbalanced big data compatible cloud storage method based on redundancy elimination technology is proposed. A new big data acquisition platform is designed based on Hadoop and NoSQL technologies. Through this platform, efficient unbalanced data acquisition is realized. The collected data are classified and processed by classifier. The classified unbalanced big data are compressed by Huffman algorithm, and the data security is improved by data encryption. Based on the data processing results, the big data redundancy processing is carried out by using the data deduplication algorithm. The cloud platform is designed to store redundant data in the cloud. The results show that the method in this paper has high data deduplication rate and data deduplication speed rate and low data storage space and effectively reduces the burden of data storage.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"106 1","pages":"1371778:1-1371778:10"},"PeriodicalIF":0.0,"publicationDate":"2022-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81234034","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 research was to study the application value of real-time shear wave elastography (SWE) quantitative evaluation based on deep learning (DL) in the diagnosis of chronic kidney disease (CKD) in children. Methods. 60 children with pathological diagnoses of CKD were selected as a CKD group. During the same period, 45 healthy children for physical examination were selected as the control group. The application value of real-time shear-wave elastography based on DL in the evaluation of CKD in children was explored by comparing the differences between the two groups. Results. It was found that the elastic modulus values of the middle and lower parenchyma of the left kidney and right kidney in the case group were (22.02 ± 10.98) kPa and (21.99 ± 11.87) kPa, respectively, which were substantially higher compared with (4.61 ± 0.47) kPa and (4.50 ± 0.59) kPa in the control group. Young’s modulus (YM) of the middle and lower parenchyma of the left kidney in patients with CKD stages 3 to 5 was 13.27 ± 0.83, 24.21 ± 5.69, and 31.67 ± 3.82, respectively, and that of the right kidney was 17.26 ± 0.98, 26.76 ± 7.22, and 32.37 ± 4.27, respectively, and the difference was significant ( P < 0.05). In patients with moderate and severe CKD, the YM values of the middle and lower parenchyma of the left kidney were 17.27 ± 0.83, 27.93 ± 6.49, and those of the right kidney were 17.26 ± 0.98, 29.56 ± 6.49, respectively, and the difference was statistically significant ( P < 0.05). The serum creatinine (Scr) of the CKD group was substantially higher than that of the control group, and the estimated glomerular filtration rate (eGFR) level of the former was lower than that of the latter. However, there was no statistical difference between the YM values of the middle and lower parts of the left and right kidneys of the CKD group and the control group. Conclusion. The DL-based SWE is a new noninvasive, real-time, and quantitative detection method, which can effectively evaluate the stiffness of the kidney and help to better detect the progress of CKD as a clinical reference.
{"title":"Quantitative Evaluation of Real-Time Shear-Wave Elastography under Deep Learning in Children with Chronic Kidney Disease","authors":"Jie Zhang, Cuirong Duan, Xingxing Duan, Yuan Hu, Jinqiao Liu, Wenjuan Chen","doi":"10.1155/2022/6051695","DOIUrl":"https://doi.org/10.1155/2022/6051695","url":null,"abstract":"Objective. This research was to study the application value of real-time shear wave elastography (SWE) quantitative evaluation based on deep learning (DL) in the diagnosis of chronic kidney disease (CKD) in children. Methods. 60 children with pathological diagnoses of CKD were selected as a CKD group. During the same period, 45 healthy children for physical examination were selected as the control group. The application value of real-time shear-wave elastography based on DL in the evaluation of CKD in children was explored by comparing the differences between the two groups. Results. It was found that the elastic modulus values of the middle and lower parenchyma of the left kidney and right kidney in the case group were (22.02 ± 10.98) kPa and (21.99 ± 11.87) kPa, respectively, which were substantially higher compared with (4.61 ± 0.47) kPa and (4.50 ± 0.59) kPa in the control group. Young’s modulus (YM) of the middle and lower parenchyma of the left kidney in patients with CKD stages 3 to 5 was 13.27 ± 0.83, 24.21 ± 5.69, and 31.67 ± 3.82, respectively, and that of the right kidney was 17.26 ± 0.98, 26.76 ± 7.22, and 32.37 ± 4.27, respectively, and the difference was significant (\u0000 \u0000 P\u0000 \u0000 < 0.05). In patients with moderate and severe CKD, the YM values of the middle and lower parenchyma of the left kidney were 17.27 ± 0.83, 27.93 ± 6.49, and those of the right kidney were 17.26 ± 0.98, 29.56 ± 6.49, respectively, and the difference was statistically significant (\u0000 \u0000 P\u0000 \u0000 < 0.05). The serum creatinine (Scr) of the CKD group was substantially higher than that of the control group, and the estimated glomerular filtration rate (eGFR) level of the former was lower than that of the latter. However, there was no statistical difference between the YM values of the middle and lower parts of the left and right kidneys of the CKD group and the control group. Conclusion. The DL-based SWE is a new noninvasive, real-time, and quantitative detection method, which can effectively evaluate the stiffness of the kidney and help to better detect the progress of CKD as a clinical reference.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"43 1","pages":"6051695:1-6051695:9"},"PeriodicalIF":0.0,"publicationDate":"2022-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84867670","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}
Yinhua Tian, Xinran Li, Man Qi, Dong Han, Yuyue Du
Several unexpected behaviors may occur during actual treatment of clinical pathways, which will have negative impact on the implementation and the future work. To increase the performance of current deviation detection algorithms, a method is presented according to business alignment, which can effectively detect the anomaly in the implementation of the clinical pathways, provide judgment basis for the intervention in the process of the clinical pathway implementation, and play a crucial role in improving the clinical pathways. Firstly, the noise in diagnosis and treatment logs of clinical pathways will be removed. Then, the synchronous composition model is constructed to embody the deviations between the actual process and the theoretical model. Finally, A ∗ algorithm is selected to search for optimal alignment. A clinical pathway for ST-Elevation Myocardial Infarction (STEMI) under COVID-19 is used as a case study, and the superiority and effectiveness of this method in deviation detection are illustrated in the result of experiments.
{"title":"Deviation Detection in Clinical Pathways Based on Business Alignment","authors":"Yinhua Tian, Xinran Li, Man Qi, Dong Han, Yuyue Du","doi":"10.1155/2022/6993449","DOIUrl":"https://doi.org/10.1155/2022/6993449","url":null,"abstract":"Several unexpected behaviors may occur during actual treatment of clinical pathways, which will have negative impact on the implementation and the future work. To increase the performance of current deviation detection algorithms, a method is presented according to business alignment, which can effectively detect the anomaly in the implementation of the clinical pathways, provide judgment basis for the intervention in the process of the clinical pathway implementation, and play a crucial role in improving the clinical pathways. Firstly, the noise in diagnosis and treatment logs of clinical pathways will be removed. Then, the synchronous composition model is constructed to embody the deviations between the actual process and the theoretical model. Finally, \u0000 \u0000 A\u0000 ∗\u0000 \u0000 algorithm is selected to search for optimal alignment. A clinical pathway for ST-Elevation Myocardial Infarction (STEMI) under COVID-19 is used as a case study, and the superiority and effectiveness of this method in deviation detection are illustrated in the result of experiments.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"84 1","pages":"6993449:1-6993449:13"},"PeriodicalIF":0.0,"publicationDate":"2022-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82733215","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 was to analyze the application value of a reconstruction algorithm in CT images of patients with coronary heart disease and analyze the correlation between epicardial fat volume and coronary heart disease. An optimized reconstruction algorithm was constructed based on compressed sensing theory in this study. Then, the optimized algorithm was applied to the image reconstruction of multislice spiral CT image data after testing its sensitivity, accuracy, and specificity. 60 patients with suspected angina pectoris were divided into lesion group (40 cases) and normal group (20 cases) according to whether there were coronary atherosclerotic plaques in cardiac vessels. The results showed that the sensitivity, specificity, and accuracy of the optimized reconstruction algorithm were 91.78%, 84.27%, and 95.32%, and the running time was (12.18 ± 2.49) s. The CT value of the liver and the CT ratio of the liver and spleen in the lesion group were (53.81 ± 5.91) and (3.88 ± 0.67), respectively. There was no significant difference between the two groups ( P > 0.05 ). The body mass index and epicardial fat volume in the lesion group were (31.93 ± 4.54) kg/m2 and (120.09 ± 22.01) cm3, respectively. The body mass index and fat volume in the lesion group were significantly higher than those in the normal group ( P < 0.05 ). The epicardial fat constitution increased with the increase of the number of coronary arteries involved, and there was a positive correlation between them. Among patients with different coronary atherosclerotic plaques, the epicardial fat volume in patients with mixed plaques was the largest ( P < 0.05 ). In summary, optimizing CT images under compressed a sensing reconstruction algorithm could effectively improve the diagnostic accuracy of doctors. Epicardial fat volume was positively correlated with coronary heart disease. Epicardial fat volume could be used as one of the important indexes to predict coronary heart disease.
{"title":"Optimized Reconstruction Algorithm-Processed CT Image in the Diagnosis of Correlation between Epicardial Fat Volume and Coronary Heart Disease","authors":"Enzhong Xue, Qiangqiang Jing","doi":"10.1155/2022/2883175","DOIUrl":"https://doi.org/10.1155/2022/2883175","url":null,"abstract":"This study was to analyze the application value of a reconstruction algorithm in CT images of patients with coronary heart disease and analyze the correlation between epicardial fat volume and coronary heart disease. An optimized reconstruction algorithm was constructed based on compressed sensing theory in this study. Then, the optimized algorithm was applied to the image reconstruction of multislice spiral CT image data after testing its sensitivity, accuracy, and specificity. 60 patients with suspected angina pectoris were divided into lesion group (40 cases) and normal group (20 cases) according to whether there were coronary atherosclerotic plaques in cardiac vessels. The results showed that the sensitivity, specificity, and accuracy of the optimized reconstruction algorithm were 91.78%, 84.27%, and 95.32%, and the running time was (12.18 ± 2.49) s. The CT value of the liver and the CT ratio of the liver and spleen in the lesion group were (53.81 ± 5.91) and (3.88 ± 0.67), respectively. There was no significant difference between the two groups (\u0000 \u0000 P\u0000 >\u0000 0.05\u0000 \u0000 ). The body mass index and epicardial fat volume in the lesion group were (31.93 ± 4.54) kg/m2 and (120.09 ± 22.01) cm3, respectively. The body mass index and fat volume in the lesion group were significantly higher than those in the normal group (\u0000 \u0000 P\u0000 <\u0000 0.05\u0000 \u0000 ). The epicardial fat constitution increased with the increase of the number of coronary arteries involved, and there was a positive correlation between them. Among patients with different coronary atherosclerotic plaques, the epicardial fat volume in patients with mixed plaques was the largest (\u0000 \u0000 P\u0000 <\u0000 0.05\u0000 \u0000 ). In summary, optimizing CT images under compressed a sensing reconstruction algorithm could effectively improve the diagnostic accuracy of doctors. Epicardial fat volume was positively correlated with coronary heart disease. Epicardial fat volume could be used as one of the important indexes to predict coronary heart disease.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"57 1","pages":"2883175:1-2883175:8"},"PeriodicalIF":0.0,"publicationDate":"2022-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78677195","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}
Decision support technology has become a key link in modern information strategy. With the deepening of research, introduced expert systems have been introduced into decision support systems. In this way, decision support systems gradually become more uncertain and capable of handling uncertainties. The development direction of decision support system is typically based on qualitative analysis. Intelligent decision support system is a system that combines decision support system with artificial intelligence technology. This study attempts to assess in an innovative way the relationship between financing constraints, entrepreneurship, and agricultural firms. The most recently proposed intelligent decision support system, AI-assisted Intelligent Decision Support System (AIIDSS), is used to predict the impact of entrepreneurship on corporate performance. The paper constructs an entrepreneurship index from five aspects: innovation, competitiveness, human capital accumulation, management capability, and adventurous spirit. The method intends to construct the Kaplan–Zingales (KZ) index to evaluate financing constraints. Through an empirical study, it was found that entrepreneurship can significantly promote the growth of listed agricultural companies. The study can drastically reduce the difficulties involved in financing constraints normally faced by agricultural companies. The impact paths include increasing agricultural company operating cash flow, improving stock liquidity, and increasing debt financing. The research suggests that if listed agricultural companies are to improve financing constraints, entrepreneurs must improve their own competitiveness and management capabilities. This will help in reasonably controlling research and development investment besides the impulse to take risks. As the growth of an enterprise relies on considering the determinants of financing constraints, this research provides an effective investigation technique. Moreover, the findings of the study will help entrepreneurs, particularly agricultural companies, to bear most of the risks and to avail most of the opportunities.
{"title":"Analyzing Relationship between Financing Constraints, Entrepreneurship, and Agricultural Company Using AI-Based Decision Support System","authors":"Xiaohu Liu, Han Li, Hong Li","doi":"10.1155/2022/1634677","DOIUrl":"https://doi.org/10.1155/2022/1634677","url":null,"abstract":"Decision support technology has become a key link in modern information strategy. With the deepening of research, introduced expert systems have been introduced into decision support systems. In this way, decision support systems gradually become more uncertain and capable of handling uncertainties. The development direction of decision support system is typically based on qualitative analysis. Intelligent decision support system is a system that combines decision support system with artificial intelligence technology. This study attempts to assess in an innovative way the relationship between financing constraints, entrepreneurship, and agricultural firms. The most recently proposed intelligent decision support system, AI-assisted Intelligent Decision Support System (AIIDSS), is used to predict the impact of entrepreneurship on corporate performance. The paper constructs an entrepreneurship index from five aspects: innovation, competitiveness, human capital accumulation, management capability, and adventurous spirit. The method intends to construct the Kaplan–Zingales (KZ) index to evaluate financing constraints. Through an empirical study, it was found that entrepreneurship can significantly promote the growth of listed agricultural companies. The study can drastically reduce the difficulties involved in financing constraints normally faced by agricultural companies. The impact paths include increasing agricultural company operating cash flow, improving stock liquidity, and increasing debt financing. The research suggests that if listed agricultural companies are to improve financing constraints, entrepreneurs must improve their own competitiveness and management capabilities. This will help in reasonably controlling research and development investment besides the impulse to take risks. As the growth of an enterprise relies on considering the determinants of financing constraints, this research provides an effective investigation technique. Moreover, the findings of the study will help entrepreneurs, particularly agricultural companies, to bear most of the risks and to avail most of the opportunities.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"81 1","pages":"1634677:1-1634677:9"},"PeriodicalIF":0.0,"publicationDate":"2022-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86216644","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}
In order to obtain the complete equilibrium state of rural financial market and ensure the stable development of rural financial consumer market, this paper introduces CGE model and analyzes the dynamic trust mechanism of individual consumers in rural financial market. In this paper, the single variable evolutionary fuzzy clustering algorithm is used to analyze the orthogonal eigenvector solutions of individual consumers; the big data of individual consumers under the mode of perceived trust is automatically clustered, so as to obtain the fuzzy analogy function of individual consumers in the rural financial market; and finally the prediction value of consumer trust is obtained. The results show that trust, customer satisfaction, and service quality are positively correlated. Under the same sample expectation constraints, the dynamic CGE model is more robust, and the individual consumer trust mechanism of rural financial market in the study area has higher advantages.
{"title":"Research on the Trust Mechanism of Individual Consumers in Rural Financial Markets Based on the Dynamic CGE Model","authors":"Fangbin Lin, Wenxiang Chen","doi":"10.1155/2022/2167874","DOIUrl":"https://doi.org/10.1155/2022/2167874","url":null,"abstract":"In order to obtain the complete equilibrium state of rural financial market and ensure the stable development of rural financial consumer market, this paper introduces CGE model and analyzes the dynamic trust mechanism of individual consumers in rural financial market. In this paper, the single variable evolutionary fuzzy clustering algorithm is used to analyze the orthogonal eigenvector solutions of individual consumers; the big data of individual consumers under the mode of perceived trust is automatically clustered, so as to obtain the fuzzy analogy function of individual consumers in the rural financial market; and finally the prediction value of consumer trust is obtained. The results show that trust, customer satisfaction, and service quality are positively correlated. Under the same sample expectation constraints, the dynamic CGE model is more robust, and the individual consumer trust mechanism of rural financial market in the study area has higher advantages.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"12 1","pages":"2167874:1-2167874:10"},"PeriodicalIF":0.0,"publicationDate":"2022-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75770303","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 traditional centralized storage of traditional electronic medical records (EMRs) faces problems like data leakage, data loss, and EMR misplacement. The current protection measures for patients’ privacy in EMRs cannot withstand the fast-developing password cracking technologies and frequency cyberattacks. This paper intends to innovate the information sharing and privacy protection of electronic nursing records (ENRs) management system. Specifically, the signature interception technology was introduced to EMRs, the different phases of certificateless signature interception scheme were depicted, and the validation procedures of the scheme were designed. Then, the six phases of ENR information sharing protocol based on alliance blockchain were described in detail. Finally, an end-to-end memory neural network was constructed for ENR classification. The proposed management scheme was proved effective through experiments.
{"title":"Information Sharing and Privacy Protection of Electronic Nursing Record Management System","authors":"Qiong Li, Hui Yu, Wei Li","doi":"10.1155/2022/4169340","DOIUrl":"https://doi.org/10.1155/2022/4169340","url":null,"abstract":"The traditional centralized storage of traditional electronic medical records (EMRs) faces problems like data leakage, data loss, and EMR misplacement. The current protection measures for patients’ privacy in EMRs cannot withstand the fast-developing password cracking technologies and frequency cyberattacks. This paper intends to innovate the information sharing and privacy protection of electronic nursing records (ENRs) management system. Specifically, the signature interception technology was introduced to EMRs, the different phases of certificateless signature interception scheme were depicted, and the validation procedures of the scheme were designed. Then, the six phases of ENR information sharing protocol based on alliance blockchain were described in detail. Finally, an end-to-end memory neural network was constructed for ENR classification. The proposed management scheme was proved effective through experiments.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"54 1","pages":"4169340:1-4169340:12"},"PeriodicalIF":0.0,"publicationDate":"2022-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85679837","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 world is undergoing great changes that have not been seen at present; colleges and universities can only adapt to social development with a more active and open attitude. Meanwhile, colleges and universities strive to obtain more social resources during the process of gradually embedding social funds into the operation system of universities. In such a backdrop, we establish an optimization model for university running efficiency under limited funds, where the objective function is quadratic and restraint condition is linear. With the help of optimization theory, we have obtained the optimal solution of this optimization model and put forward corresponding suggestions to improve the running efficiency of higher education.
{"title":"Big Data Optimization and Applications in Running Efficiency of Higher Education","authors":"Mingxia Lu","doi":"10.1155/2022/1044800","DOIUrl":"https://doi.org/10.1155/2022/1044800","url":null,"abstract":"The world is undergoing great changes that have not been seen at present; colleges and universities can only adapt to social development with a more active and open attitude. Meanwhile, colleges and universities strive to obtain more social resources during the process of gradually embedding social funds into the operation system of universities. In such a backdrop, we establish an optimization model for university running efficiency under limited funds, where the objective function is quadratic and restraint condition is linear. With the help of optimization theory, we have obtained the optimal solution of this optimization model and put forward corresponding suggestions to improve the running efficiency of higher education.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"3 1","pages":"1044800:1-1044800:10"},"PeriodicalIF":0.0,"publicationDate":"2022-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73061427","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}
N. Arivazhagan, K. Somasundaram, D. Babu, M. Nayagam, R. Bommi, Gouse Baig Mohammad, P. R. Kumar, Yuvaraj Natarajan, V. J. Arulkarthick, V. Shanmuganathan, K. Srihari, M. R. Vignesh, Venkatesa Prabhu Sundramurthy
Considering task dependencies, the balancing of the Internet of Health Things (IoHT) scheduling is considered important to reduce the make span rate. In this paper, we developed a smart model approach for the best task schedule of Hybrid Moth Flame Optimization (HMFO) for cloud computing integrated in the IoHT environment over e-healthcare systems. The HMFO guarantees uniform resource assignment and enhanced quality of services (QoS). The model is trained with the Google cluster dataset such that it learns the instances of how a job is scheduled in cloud and the trained HMFO model is used to schedule the jobs in real time. The simulation is conducted on a CloudSim environment to test the scheduling efficacy of the model in hybrid cloud environment. The parameters used by this method for the performance assessment include the use of resources, response time, and energy utilization. In terms of response time, average run time, and lower costs, the hybrid HMFO approach has offered increased response rate with reduced cost and run time than other methods.
{"title":"Cloud-Internet of Health Things (IOHT) Task Scheduling Using Hybrid Moth Flame Optimization with Deep Neural Network Algorithm for E Healthcare Systems","authors":"N. Arivazhagan, K. Somasundaram, D. Babu, M. Nayagam, R. Bommi, Gouse Baig Mohammad, P. R. Kumar, Yuvaraj Natarajan, V. J. Arulkarthick, V. Shanmuganathan, K. Srihari, M. R. Vignesh, Venkatesa Prabhu Sundramurthy","doi":"10.1155/2022/4100352","DOIUrl":"https://doi.org/10.1155/2022/4100352","url":null,"abstract":"Considering task dependencies, the balancing of the Internet of Health Things (IoHT) scheduling is considered important to reduce the make span rate. In this paper, we developed a smart model approach for the best task schedule of Hybrid Moth Flame Optimization (HMFO) for cloud computing integrated in the IoHT environment over e-healthcare systems. The HMFO guarantees uniform resource assignment and enhanced quality of services (QoS). The model is trained with the Google cluster dataset such that it learns the instances of how a job is scheduled in cloud and the trained HMFO model is used to schedule the jobs in real time. The simulation is conducted on a CloudSim environment to test the scheduling efficacy of the model in hybrid cloud environment. The parameters used by this method for the performance assessment include the use of resources, response time, and energy utilization. In terms of response time, average run time, and lower costs, the hybrid HMFO approach has offered increased response rate with reduced cost and run time than other methods.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"1 1","pages":"4100352:1-4100352:12"},"PeriodicalIF":0.0,"publicationDate":"2022-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72843368","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 depth synthesis of image texture is neglected in the current image visual communication technology, which leads to the poor visual effect. Therefore, the design method of film and TV animation based on 3D visual communication technology is proposed. Collect film and television animation videos through 3D visual communication content production, server processing, and client processing. Through stitching, projection mapping, and animation video image frame texture synthesis, 3D vision conveys animation video image projection. In order to ensure the continuous variation of scaling factors between adjacent triangles of animation and video images, the scaling factor field is constructed. Deep learning is used to extract the deep features and to reconstruct the multiframe animated and animated video images based on visual communication. Based on this, the frame feature of video image under gray projection is identified and extracted, and the animation design based on 3D visual communication technology is completed. Experimental results show that the proposed method can enhance the visual transmission of animation video images significantly and can achieve high-precision reconstruction of video images in a short time.
{"title":"Animation Design Based on 3D Visual Communication Technology","authors":"Feng Shan, Youya Wang","doi":"10.1155/2022/6461538","DOIUrl":"https://doi.org/10.1155/2022/6461538","url":null,"abstract":"The depth synthesis of image texture is neglected in the current image visual communication technology, which leads to the poor visual effect. Therefore, the design method of film and TV animation based on 3D visual communication technology is proposed. Collect film and television animation videos through 3D visual communication content production, server processing, and client processing. Through stitching, projection mapping, and animation video image frame texture synthesis, 3D vision conveys animation video image projection. In order to ensure the continuous variation of scaling factors between adjacent triangles of animation and video images, the scaling factor field is constructed. Deep learning is used to extract the deep features and to reconstruct the multiframe animated and animated video images based on visual communication. Based on this, the frame feature of video image under gray projection is identified and extracted, and the animation design based on 3D visual communication technology is completed. Experimental results show that the proposed method can enhance the visual transmission of animation video images significantly and can achieve high-precision reconstruction of video images in a short time.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"1989 1","pages":"6461538:1-6461538:11"},"PeriodicalIF":0.0,"publicationDate":"2022-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82305371","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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