E. Lei, Chaobo Wang, Wen Xue Li, Y. Wang, Yong Bing Yang, Huabin Zheng, Qichen Tang
Mechanical grain harvesting is a crop production development direction. However, the residue management methods suitable for mechanical grain harvesting have been not established. In order to study the effect of residue management modes on maize yield formation and explore the best residue management methods for mechanical grain harvesting, four crop field surveys were carried out in Southwest China. Crops were mechanically harvested, and the residues were shredded and returned to the field using various straw application methods including straw deep burial with plowing (SDBP), straw shallow burial with rotary tillage (SSBRT), and straw mulching with minimum tillage (SMMT). The first-season rape residues were returned to the field, and the second-season maize yield under SDBP and SSBRT was significantly higher than that under SMMT. However, with the increase in rounds of residue application, compared with SDBP and SSBRT, SMMT continuously increased the soil moisture content in the 0–30 cm soil layer at the early stage of maize growth, increased the soil alkaline-hydrolyzed nitrogen content in the 0–20 cm and 40–60 cm layers, and reduced the soil compaction under 40 cm layer, which were more conducive to the root system growth. Maize yield with the SMMT increased by 5.4% compared with that of the previous season, while the yields with SDBP and SSBRT decreased by 16.7% and 12.7%, respectively, compared with those of the previous season. In conclusion, it is recommended to employ the SMMT method during crop mechanical harvesting, which is of great significance to improve soil quality and increase maize grain yield.
{"title":"Straw Mulching with Minimum Tillage Is the Best Method Suitable for Straw Application under Mechanical Grain Harvesting","authors":"E. Lei, Chaobo Wang, Wen Xue Li, Y. Wang, Yong Bing Yang, Huabin Zheng, Qichen Tang","doi":"10.1155/2021/6878176","DOIUrl":"https://doi.org/10.1155/2021/6878176","url":null,"abstract":"Mechanical grain harvesting is a crop production development direction. However, the residue management methods suitable for mechanical grain harvesting have been not established. In order to study the effect of residue management modes on maize yield formation and explore the best residue management methods for mechanical grain harvesting, four crop field surveys were carried out in Southwest China. Crops were mechanically harvested, and the residues were shredded and returned to the field using various straw application methods including straw deep burial with plowing (SDBP), straw shallow burial with rotary tillage (SSBRT), and straw mulching with minimum tillage (SMMT). The first-season rape residues were returned to the field, and the second-season maize yield under SDBP and SSBRT was significantly higher than that under SMMT. However, with the increase in rounds of residue application, compared with SDBP and SSBRT, SMMT continuously increased the soil moisture content in the 0–30 cm soil layer at the early stage of maize growth, increased the soil alkaline-hydrolyzed nitrogen content in the 0–20 cm and 40–60 cm layers, and reduced the soil compaction under 40 cm layer, which were more conducive to the root system growth. Maize yield with the SMMT increased by 5.4% compared with that of the previous season, while the yields with SDBP and SSBRT decreased by 16.7% and 12.7%, respectively, compared with those of the previous season. In conclusion, it is recommended to employ the SMMT method during crop mechanical harvesting, which is of great significance to improve soil quality and increase maize grain yield.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"81 1","pages":"6878176:1-6878176:12"},"PeriodicalIF":0.0,"publicationDate":"2021-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80207205","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}
Sports industry cluster refers to the economic phenomenon that sports related enterprises gather in a large number in a specific area. For the sports enterprises in the cluster, they can obtain huge competitive advantages through enterprise agglomeration, thus obtaining better development and rich economic benefits. The optimization of particle swarm optimization is interlinked with the agglomeration of industrial clusters. Therefore, in view of the limitation of the standard particle swarm optimization (PSO) algorithm, an improved particle swarm optimization algorithm-diaphragm particle swarm optimization (D-PSO) was proposed and used to simulate the formation of sports industry clusters. D-PSO introduces the cell membrane processing mechanism of the biological system into the PSO algorithm, which improves the ability of the PSO algorithm to get rid of local extremum points. The competitiveness value of the sports industry cluster is the value of the objective function solved by the D-PSO algorithm. The geographical coordinates of the industrial cluster were the locations in the particle search space of the D-PSO algorithm. The D-PSO algorithm is used to simulate the aggregation process of enterprises in the cluster. Compared with the standard PSO, the D-PSO algorithm has better convergence performance and optimal rate. The results of case analysis show that the proposed method can effectively predict the development trend of sports industrial clusters.
{"title":"Prediction of Evolution and Development Trend in Sports Industry Cluster Based on Particle Swarm Optimization","authors":"Rui Cong, Hailong Wang","doi":"10.1155/2021/7607623","DOIUrl":"https://doi.org/10.1155/2021/7607623","url":null,"abstract":"Sports industry cluster refers to the economic phenomenon that sports related enterprises gather in a large number in a specific area. For the sports enterprises in the cluster, they can obtain huge competitive advantages through enterprise agglomeration, thus obtaining better development and rich economic benefits. The optimization of particle swarm optimization is interlinked with the agglomeration of industrial clusters. Therefore, in view of the limitation of the standard particle swarm optimization (PSO) algorithm, an improved particle swarm optimization algorithm-diaphragm particle swarm optimization (D-PSO) was proposed and used to simulate the formation of sports industry clusters. D-PSO introduces the cell membrane processing mechanism of the biological system into the PSO algorithm, which improves the ability of the PSO algorithm to get rid of local extremum points. The competitiveness value of the sports industry cluster is the value of the objective function solved by the D-PSO algorithm. The geographical coordinates of the industrial cluster were the locations in the particle search space of the D-PSO algorithm. The D-PSO algorithm is used to simulate the aggregation process of enterprises in the cluster. Compared with the standard PSO, the D-PSO algorithm has better convergence performance and optimal rate. The results of case analysis show that the proposed method can effectively predict the development trend of sports industrial clusters.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"2 1","pages":"7607623:1-7607623:8"},"PeriodicalIF":0.0,"publicationDate":"2021-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78863349","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 latest technology, smartphone's profound impact may be valuable for the users in different age groups, but the elders always face difficulties while adopting the technology. The usability of a smartphone application is essential when the target audience is elderly users, as the designer did not satisfy the specific requirements. The importance of smartphone application and the issues that the elders are facing in using smartphones have motivated us to provide a list of barriers that could negatively impact the usability of smartphone applications in elderly people. This research focused on identifying the barriers that affect the usability of smartphones, especially among elders. A systematic literature review (SLR) was used to identify and validate the barriers. After that, we apply the analytic hierarchy process (AHP) on identified barriers of all barriers’ groups to find out their relative importance. A total of fifteen barriers were identified through the SLR approach, and the barriers were then classified and assigned to one of the five categories. It is expected that the barriers that have been recognized will help the designers of smartphone applications in the early stages of designing applications. The result of the study will help in dealing with the issues related to the elder community and will make the designers develop smartphone applications accordingly.
{"title":"Usability Barriers for Elderly Users in Smartphone App Usage: An Analytical Hierarchical Process-Based Prioritization","authors":"Mujtaba Awan, Sikandar Ali, Mushtaq Ali, Muhammad Faisal Abrar, Hamid Ullah, Dawar Khan","doi":"10.1155/2021/2780257","DOIUrl":"https://doi.org/10.1155/2021/2780257","url":null,"abstract":"With the latest technology, smartphone's profound impact may be valuable for the users in different age groups, but the elders always face difficulties while adopting the technology. The usability of a smartphone application is essential when the target audience is elderly users, as the designer did not satisfy the specific requirements. The importance of smartphone application and the issues that the elders are facing in using smartphones have motivated us to provide a list of barriers that could negatively impact the usability of smartphone applications in elderly people. This research focused on identifying the barriers that affect the usability of smartphones, especially among elders. A systematic literature review (SLR) was used to identify and validate the barriers. After that, we apply the analytic hierarchy process (AHP) on identified barriers of all barriers’ groups to find out their relative importance. A total of fifteen barriers were identified through the SLR approach, and the barriers were then classified and assigned to one of the five categories. It is expected that the barriers that have been recognized will help the designers of smartphone applications in the early stages of designing applications. The result of the study will help in dealing with the issues related to the elder community and will make the designers develop smartphone applications accordingly.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"4 1","pages":"2780257:1-2780257:14"},"PeriodicalIF":0.0,"publicationDate":"2021-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89980060","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 purpose is to improve the power and innovate the communication mode of mainstream I&P (Ideological and Political) education in C&U (Colleges and Universities). The opportunities and challenges that I&P education is facing or will face in media times are analyzed from three factors: the subjective, the mediator, and the environment, which affect the power of mainstream I&P in C&U. Educational means, carriers, resources, places and times, and the interactions between educators and the educated can bring opportunities for the improvement of the educational power of C&U. However, there are great challenges in all aspects of the mainstream ideology, such as education methods, education ideas, education content, education leadership and discourse power, and network public opinion control. Finally, a series of measures are proposed to improve the power of mainstream I&P education in C&U in media times, and they are updating the concept of media education, strengthening the ideological guidance, ensuring the direction of mainstream I&P education, and optimizing the media environment so that a more perfect innovative mode of I&P education is constructed. The research enriches and develops the theory of mainstream I&P education in C&U, innovates the methods of mainstream I&P education in C&U, and enhances the power of mainstream I&P education.
{"title":"The Process and Model Innovation of Ideological Education Network Communication in Colleges and Universities Based on Cloud Computing","authors":"Haiyan Zhan","doi":"10.1155/2021/7302877","DOIUrl":"https://doi.org/10.1155/2021/7302877","url":null,"abstract":"The purpose is to improve the power and innovate the communication mode of mainstream I&P (Ideological and Political) education in C&U (Colleges and Universities). The opportunities and challenges that I&P education is facing or will face in media times are analyzed from three factors: the subjective, the mediator, and the environment, which affect the power of mainstream I&P in C&U. Educational means, carriers, resources, places and times, and the interactions between educators and the educated can bring opportunities for the improvement of the educational power of C&U. However, there are great challenges in all aspects of the mainstream ideology, such as education methods, education ideas, education content, education leadership and discourse power, and network public opinion control. Finally, a series of measures are proposed to improve the power of mainstream I&P education in C&U in media times, and they are updating the concept of media education, strengthening the ideological guidance, ensuring the direction of mainstream I&P education, and optimizing the media environment so that a more perfect innovative mode of I&P education is constructed. The research enriches and develops the theory of mainstream I&P education in C&U, innovates the methods of mainstream I&P education in C&U, and enhances the power of mainstream I&P education.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"50 1","pages":"7302877:1-7302877:7"},"PeriodicalIF":0.0,"publicationDate":"2021-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74749601","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}
Moving target detection is involved in many engineering projects, but it is difficult because of the strong time-varying speed and uncertain path. Goal recognition is the key technology of the basketball goal automatic test. Also, accurate and timely judgment of basketball goals has important practical value. Therefore, a basketball goal recognition method based on an improved lightweight deep learning network model (L-MobileNet) is proposed. First of all, the basket detection is carried out by the Hough circle transform algorithm. Then, in order to further improve the detection speed of basketball goals, based on the lightweight network MobileNet, an improved lightweight network (L-MobileNet) is proposed. First of all, for deeply separable convolution, channel compression and block convolution reduce the parameters and computational complexity of the module. At the same time, because block convolution will hinder the information exchange between characteristic channels, an improved channel shuffling method, IShuffle, is introduced. Then, combined with the residual structure to improve the generalization ability of the network, the RLDWS module is constructed. Finally, a more lightweight network L-MobileNet is constructed by using the RLDWS module. The experimental results show that the proposed method can effectively realize the judgment of basketball goals, and the judgment accuracy is improved by 8.35%. At the same time, the amount of parameters and computation is only 29.7% and 53.2% of the original, and it also has certain advantages compared with other lightweight networks.
{"title":"Research on the Basketball Goal Recognition Method Based on Improved MobileNet","authors":"Kejian Yang","doi":"10.1155/2021/5862037","DOIUrl":"https://doi.org/10.1155/2021/5862037","url":null,"abstract":"Moving target detection is involved in many engineering projects, but it is difficult because of the strong time-varying speed and uncertain path. Goal recognition is the key technology of the basketball goal automatic test. Also, accurate and timely judgment of basketball goals has important practical value. Therefore, a basketball goal recognition method based on an improved lightweight deep learning network model (L-MobileNet) is proposed. First of all, the basket detection is carried out by the Hough circle transform algorithm. Then, in order to further improve the detection speed of basketball goals, based on the lightweight network MobileNet, an improved lightweight network (L-MobileNet) is proposed. First of all, for deeply separable convolution, channel compression and block convolution reduce the parameters and computational complexity of the module. At the same time, because block convolution will hinder the information exchange between characteristic channels, an improved channel shuffling method, IShuffle, is introduced. Then, combined with the residual structure to improve the generalization ability of the network, the RLDWS module is constructed. Finally, a more lightweight network L-MobileNet is constructed by using the RLDWS module. The experimental results show that the proposed method can effectively realize the judgment of basketball goals, and the judgment accuracy is improved by 8.35%. At the same time, the amount of parameters and computation is only 29.7% and 53.2% of the original, and it also has certain advantages compared with other lightweight networks.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"72 1","pages":"5862037:1-5862037:10"},"PeriodicalIF":0.0,"publicationDate":"2021-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90577025","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 high-resolution remote sensing images with many features and low classification accuracy using a single feature description, a remote sensing image land classification model based on deep learning from the perspective of ecological resource utilization is proposed. Firstly, the remote sensing image obtained by Gaofen-1 satellite is preprocessed, including multispectral data and panchromatic data. Then, the color, texture, shape, and local features are extracted from the image data, and the feature-level image fusion method is used to associate these features to realize the fusion of remote sensing image features. Finally, the fused image features are input into the trained depth belief network (DBN) for processing, and the land type is obtained by the Softmax classifier. Based on the Keras and TensorFlow platform, the experimental analysis of the proposed model shows that it can clearly classify all land types, and the overall accuracy, F1 value, and reasoning time of the classification results are 97.86%, 87.25%, and 128 ms, respectively, which are better than other comparative models.
{"title":"Remote Sensing Image Land Classification Based on Deep Learning","authors":"Kai Zhang, Chengquan Hu, Hang Yu","doi":"10.1155/2021/6203444","DOIUrl":"https://doi.org/10.1155/2021/6203444","url":null,"abstract":"Aiming at the problems of high-resolution remote sensing images with many features and low classification accuracy using a single feature description, a remote sensing image land classification model based on deep learning from the perspective of ecological resource utilization is proposed. Firstly, the remote sensing image obtained by Gaofen-1 satellite is preprocessed, including multispectral data and panchromatic data. Then, the color, texture, shape, and local features are extracted from the image data, and the feature-level image fusion method is used to associate these features to realize the fusion of remote sensing image features. Finally, the fused image features are input into the trained depth belief network (DBN) for processing, and the land type is obtained by the Softmax classifier. Based on the Keras and TensorFlow platform, the experimental analysis of the proposed model shows that it can clearly classify all land types, and the overall accuracy, F1 value, and reasoning time of the classification results are 97.86%, 87.25%, and 128 ms, respectively, which are better than other comparative models.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"25 1","pages":"6203444:1-6203444:12"},"PeriodicalIF":0.0,"publicationDate":"2021-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88619354","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}
Z. Oralbekova, T. Zhukabayeva, K. Iskakov, M. Zhartybayeva, Nargiz Yessimova, Alma Zakirova, A. Kussainova
In order to ensure optimal operation of the existing environmental monitoring information system, it has become essential to use mathematical modeling based on the data assimilation algorithm. In this paper, a data assimilation algorithm has been designed and implemented. An algorithmic approach was tested for the assimilation of city atmosphere monitoring data from an industrial area. An industrial district of Karaganda city was selected for the investigation of the algorithm. The industrial district of Karaganda was taken as a research object due to the high level of atmospheric air pollution in industrial cities in the Republic of Kazakhstan. The result of our research and testing of the algorithm showed the effectiveness of the data assimilation algorithm for monitoring the atmosphere of the selected city. The practical value of the work lies on the fact that the presented results can be used to assess the state of atmospheric air in real time, to model the state of atmospheric air at each point of the city, and to determine the zone of increased environmental risk in an industrial city.
{"title":"A New Approach to Solving the Problem of Atmospheric Air Pollution in the Industrial City","authors":"Z. Oralbekova, T. Zhukabayeva, K. Iskakov, M. Zhartybayeva, Nargiz Yessimova, Alma Zakirova, A. Kussainova","doi":"10.1155/2021/8970949","DOIUrl":"https://doi.org/10.1155/2021/8970949","url":null,"abstract":"In order to ensure optimal operation of the existing environmental monitoring information system, it has become essential to use mathematical modeling based on the data assimilation algorithm. In this paper, a data assimilation algorithm has been designed and implemented. An algorithmic approach was tested for the assimilation of city atmosphere monitoring data from an industrial area. An industrial district of Karaganda city was selected for the investigation of the algorithm. The industrial district of Karaganda was taken as a research object due to the high level of atmospheric air pollution in industrial cities in the Republic of Kazakhstan. The result of our research and testing of the algorithm showed the effectiveness of the data assimilation algorithm for monitoring the atmosphere of the selected city. The practical value of the work lies on the fact that the presented results can be used to assess the state of atmospheric air in real time, to model the state of atmospheric air at each point of the city, and to determine the zone of increased environmental risk in an industrial city.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"71 1","pages":"8970949:1-8970949:12"},"PeriodicalIF":0.0,"publicationDate":"2021-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86909147","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 constant developments in Internet communication and the rise of the Internet of Things (IoT), technologies incorporating intelligent manufacturing have given birth to the growing industry and production lines. The network of IoT is generally interconnected with different devices through the Internet. The interactions of the IoT devices form smooth and functional communication require the connectivity of billions of objects. The devices of IoT can preserve, capture, share, and analyze data with nodes connected to the world. Various issues of the IoT such as monitoring the data, stealing the data, privacy of the data, tracking of the data, and many other aspects of the data are becoming challenges for the modern-day industry. The role of computational intelligence in proper analysis, managing, and many different perspectives of the IoT is prominent. Such computational intelligence can solve real-time problems with low cost and time. The IoT has provided solutions for poor scalability, system integration, and difficulties in coordinated operation across the emerging systems. The influence of the proposed study is to offer a wide-ranging overview of the current literature related to the Internet of Things based on intelligent techniques in workable computing. The study has considered the search process in the most popular libraries and presented an analysis of the research work done so far. The analysis and results of the study support the progress in the field, which will help researchers come up with new solutions.
{"title":"Internet of Things Based Intelligent Techniques in Workable Computing: An Overview","authors":"Jiayi Guo, S. Nazir","doi":"10.1155/2021/6805104","DOIUrl":"https://doi.org/10.1155/2021/6805104","url":null,"abstract":"With the constant developments in Internet communication and the rise of the Internet of Things (IoT), technologies incorporating intelligent manufacturing have given birth to the growing industry and production lines. The network of IoT is generally interconnected with different devices through the Internet. The interactions of the IoT devices form smooth and functional communication require the connectivity of billions of objects. The devices of IoT can preserve, capture, share, and analyze data with nodes connected to the world. Various issues of the IoT such as monitoring the data, stealing the data, privacy of the data, tracking of the data, and many other aspects of the data are becoming challenges for the modern-day industry. The role of computational intelligence in proper analysis, managing, and many different perspectives of the IoT is prominent. Such computational intelligence can solve real-time problems with low cost and time. The IoT has provided solutions for poor scalability, system integration, and difficulties in coordinated operation across the emerging systems. The influence of the proposed study is to offer a wide-ranging overview of the current literature related to the Internet of Things based on intelligent techniques in workable computing. The study has considered the search process in the most popular libraries and presented an analysis of the research work done so far. The analysis and results of the study support the progress in the field, which will help researchers come up with new solutions.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"140 1","pages":"6805104:1-6805104:15"},"PeriodicalIF":0.0,"publicationDate":"2021-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86622450","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 to explore the application value of computed tomography (CT) imaging radiomics based on a sinogram-affirmed iterative reconstruction algorithm (SAFIRE) in the diagnosis of gastric cancer. 59 patients who were clinically diagnosed with gastric cancer were selected as research objects and arranged CT examinations. The images obtained were optimized by the SAFIRE for the staging of gastric cancer. The pathological biopsy results were used as the gold standard to evaluate its diagnostic effect and compared with the filtered back-projection (FBP) method. The results showed that the carrier-to-noise ratio (CNR) (0.979) and signal-to-noise ratio (SNR) (0.967) of the CT image after the algorithm processing were significantly higher than those (0.781, 0.744) before ( P < 0.05 ). There was no significant difference in CT values between the FBP algorithm and S1, S2, and S3 ( P > 0.05 ); the area under the curve (AUC) (0.999) and sensitivity (0.98) of the CT training group under the SAFIRE algorithm for gastric cancer classification were higher than those of the verification group (0.958, 0.92). The preoperative CT staging kappa value was consistent with the postoperative pathological diagnosis of 0.882. CT images guided by SAFIRE can objectively and noninvasively assess the tumor asymmetry, discover additional information from subjective evaluation beyond the naked eye, and perform reasonable staging diagnosis of gastric cancer, which was useful for clinicians to develop high-quality individualized treatment plans.
{"title":"Computerized Tomography Imaging Omics under Iterative Reconstruction Algorithm in Diagnosis of Gastric Cancer","authors":"Chunfang Zhou, Shufang Tian, Fei Lv, Rui Shang, Xue-ting Zheng","doi":"10.1155/2021/2987080","DOIUrl":"https://doi.org/10.1155/2021/2987080","url":null,"abstract":"This study aimed to explore the application value of computed tomography (CT) imaging radiomics based on a sinogram-affirmed iterative reconstruction algorithm (SAFIRE) in the diagnosis of gastric cancer. 59 patients who were clinically diagnosed with gastric cancer were selected as research objects and arranged CT examinations. The images obtained were optimized by the SAFIRE for the staging of gastric cancer. The pathological biopsy results were used as the gold standard to evaluate its diagnostic effect and compared with the filtered back-projection (FBP) method. The results showed that the carrier-to-noise ratio (CNR) (0.979) and signal-to-noise ratio (SNR) (0.967) of the CT image after the algorithm processing were significantly higher than those (0.781, 0.744) before (\u0000 \u0000 P\u0000 <\u0000 0.05\u0000 \u0000 ). There was no significant difference in CT values between the FBP algorithm and S1, S2, and S3 (\u0000 \u0000 P\u0000 >\u0000 0.05\u0000 \u0000 ); the area under the curve (AUC) (0.999) and sensitivity (0.98) of the CT training group under the SAFIRE algorithm for gastric cancer classification were higher than those of the verification group (0.958, 0.92). The preoperative CT staging kappa value was consistent with the postoperative pathological diagnosis of 0.882. CT images guided by SAFIRE can objectively and noninvasively assess the tumor asymmetry, discover additional information from subjective evaluation beyond the naked eye, and perform reasonable staging diagnosis of gastric cancer, which was useful for clinicians to develop high-quality individualized treatment plans.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"48 1","pages":"2987080:1-2987080:8"},"PeriodicalIF":0.0,"publicationDate":"2021-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87980364","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 quickly and accurately retrieve a required part from massive multimedia educational resources and improve the utilization of educational resources, a multimedia assisted legal classroom teaching model based on data mining algorithm is designed. Firstly, the attributes of multimedia assisted legal classroom teaching resources are judged, and the numerical resources are standardized and discretized. Then, the B+ tree is used to establish the model’s indexes and index library, and the corresponding retrieval algorithm is designed to complete the resource search, establish the data distribution structure model of the multimedia assisted legal classroom teaching system, mine the data, reconstruct the phase space of the fused data information flow, extract the high-order moment features of the specific data in the multimedia assisted legal classroom teaching system in the reconstructed high-dimensional phase space, and realize the accurate mining of the feature data. The experimental results show that the teaching effect of the designed model has more advantages and can promote the improvement of students’ performance.
{"title":"Construction of Multimedia Assisted Legal Classroom Teaching Model Based on Data Mining Algorithm","authors":"Yu Lu, Wang Lizhi","doi":"10.1155/2021/9948800","DOIUrl":"https://doi.org/10.1155/2021/9948800","url":null,"abstract":"In order to quickly and accurately retrieve a required part from massive multimedia educational resources and improve the utilization of educational resources, a multimedia assisted legal classroom teaching model based on data mining algorithm is designed. Firstly, the attributes of multimedia assisted legal classroom teaching resources are judged, and the numerical resources are standardized and discretized. Then, the B+ tree is used to establish the model’s indexes and index library, and the corresponding retrieval algorithm is designed to complete the resource search, establish the data distribution structure model of the multimedia assisted legal classroom teaching system, mine the data, reconstruct the phase space of the fused data information flow, extract the high-order moment features of the specific data in the multimedia assisted legal classroom teaching system in the reconstructed high-dimensional phase space, and realize the accurate mining of the feature data. The experimental results show that the teaching effect of the designed model has more advantages and can promote the improvement of students’ performance.","PeriodicalId":21628,"journal":{"name":"Sci. Program.","volume":"1 1","pages":"9948800:1-9948800:11"},"PeriodicalIF":0.0,"publicationDate":"2021-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89727110","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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