Pub Date : 2023-02-20DOI: 10.38007/ijmc.2023.040106
{"title":"Innovative Application of ERP Sand Table Teaching Method Based on Intelligent Multimedia and Human-computer Interaction Technology","authors":"","doi":"10.38007/ijmc.2023.040106","DOIUrl":"https://doi.org/10.38007/ijmc.2023.040106","url":null,"abstract":"","PeriodicalId":43265,"journal":{"name":"International Journal of Mobile Computing and Multimedia Communications","volume":"43 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88829597","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}
Pub Date : 2023-02-20DOI: 10.38007/ijmc.2023.040104
Xiangru Hou
: In order to reduce the radiation exposure of patients during CT scan, low-dose CT images were produced, but the disadvantage was that the image quality was reduced. The Bayesian maximum posterior probability estimation (Bayesian MAP) method is an applied statistical method that can estimate the original noise-independent coefficients from the noise-contaminated image detail coefficients. This paper aims to study the application of bayesian based improved hidden markov algorithm in low-dose CT images, which has become the focus of CT research in recent years. In this experiment, hmrf-em, eHMRF algorithm and hmrf-msa-em algorithm were firstly analyzed by mathematical statistics within the experimental scope, and the superiority of this algorithm was compared by looking at different coefficients. The classification and statistical analysis of the re-data statistical method were carried out by using the naive bayesian algorithm and the improved hidden markov algorithm based on bayes. And the use of a single variable method to compare the use of bayesian based improved hidden markov algorithm in the low-dose CT image imaging whether there are different changes, and the degree of change. Experimental data show that the improved hidden markov algorithm based on bayes achieves higher values of Jaccard, Dice and CCR at different noise levels. The improved hidden markov algorithm based on bayes is clearer than the low-dose CT images obtained by the naive bayes algorithm. In various medical
{"title":"Improved Hidden Markov Algorithm Based on Bayes in Low Dose CT Images","authors":"Xiangru Hou","doi":"10.38007/ijmc.2023.040104","DOIUrl":"https://doi.org/10.38007/ijmc.2023.040104","url":null,"abstract":": In order to reduce the radiation exposure of patients during CT scan, low-dose CT images were produced, but the disadvantage was that the image quality was reduced. The Bayesian maximum posterior probability estimation (Bayesian MAP) method is an applied statistical method that can estimate the original noise-independent coefficients from the noise-contaminated image detail coefficients. This paper aims to study the application of bayesian based improved hidden markov algorithm in low-dose CT images, which has become the focus of CT research in recent years. In this experiment, hmrf-em, eHMRF algorithm and hmrf-msa-em algorithm were firstly analyzed by mathematical statistics within the experimental scope, and the superiority of this algorithm was compared by looking at different coefficients. The classification and statistical analysis of the re-data statistical method were carried out by using the naive bayesian algorithm and the improved hidden markov algorithm based on bayes. And the use of a single variable method to compare the use of bayesian based improved hidden markov algorithm in the low-dose CT image imaging whether there are different changes, and the degree of change. Experimental data show that the improved hidden markov algorithm based on bayes achieves higher values of Jaccard, Dice and CCR at different noise levels. The improved hidden markov algorithm based on bayes is clearer than the low-dose CT images obtained by the naive bayes algorithm. In various medical","PeriodicalId":43265,"journal":{"name":"International Journal of Mobile Computing and Multimedia Communications","volume":"223 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77011616","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}
Pub Date : 2023-02-20DOI: 10.38007/ijmc.2023.040103
Shengwei Qiu
: In the process of studying the Tang Sancai figurines, some images will be degraded due to optical system, motion, atmospheric turbulence, etc., so the images need to be restored. With the best restoration method, the restored image can meet the requirements. In fact, the purpose of image restoration is to process the degraded image to make the restored image closer to the original image. This paper conducts a comparative experiment on the classical image reconstruction methods, taking the images of Tang Sancai figurines as the experimental objects. The results show that the image reconstruction quality of the least squares method is the best among the methods selected for the experiment in this paper, and the SSIM and PSNR index values of the reconstructed image A are 0.9612 and 31.7612, respectively; in the performance comparison of GAN, GA-GAN, and Dense-GAN models, the image reconstruction algorithm based on the GA-GAN model has the best performance. Among the ten images of Tang Sancai figurines used in the experiment, the highest SIMM value is 0.99, and the highest PSNR value is 27.9345.
{"title":"Image Reconstruction of Tang Sancai Figurines Based on Artificial Intelligence Image Extraction Technology Based on Ration","authors":"Shengwei Qiu","doi":"10.38007/ijmc.2023.040103","DOIUrl":"https://doi.org/10.38007/ijmc.2023.040103","url":null,"abstract":": In the process of studying the Tang Sancai figurines, some images will be degraded due to optical system, motion, atmospheric turbulence, etc., so the images need to be restored. With the best restoration method, the restored image can meet the requirements. In fact, the purpose of image restoration is to process the degraded image to make the restored image closer to the original image. This paper conducts a comparative experiment on the classical image reconstruction methods, taking the images of Tang Sancai figurines as the experimental objects. The results show that the image reconstruction quality of the least squares method is the best among the methods selected for the experiment in this paper, and the SSIM and PSNR index values of the reconstructed image A are 0.9612 and 31.7612, respectively; in the performance comparison of GAN, GA-GAN, and Dense-GAN models, the image reconstruction algorithm based on the GA-GAN model has the best performance. Among the ten images of Tang Sancai figurines used in the experiment, the highest SIMM value is 0.99, and the highest PSNR value is 27.9345.","PeriodicalId":43265,"journal":{"name":"International Journal of Mobile Computing and Multimedia Communications","volume":"50 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79398053","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}
Pub Date : 2022-10-10DOI: 10.38007/ijmc.2022.030402
Rajite Ragab
: The rapid development of information technology has accelerated the rise of the Internet of Things, and with the application and popularization of the Internet of Things, it has gradually achieved good development momentum in various fields. How to further exert the maximum value of the Internet of Things, and combine the data it monitors with the computer network to form a comprehensive control of the computer monitoring system has become an important issue to be solved in the current related fields. The rapid development of technology, the rise of 5G technology, the application of 5G technology to the Internet of Things technology, the computer monitoring system based on 5G Internet of Things technology is more intelligent in the actual operation. Tunnel lining is a permanent structure that supports and maintains the long-term stability and durability of the tunnel. Its role is to: support and maintain the stability of the tunnel; maintain the space required for the train to run; prevent the weathering of the surrounding rock; remove the impact of groundwater, etc., apply the 5G IOT computer monitoring system to the tunnel lining, which can be effectively used by the monitoring system. Observing the situation of the tunnel helps the relevant personnel to make predictions and maintenance. In this paper, the 5G IOT computer monitoring system is designed to monitor the tunnel lining, and the tunnel lining is analyzed by the data observed by the monitoring system to realize prediction and maintenance. Through system monitoring, we found that the computer monitoring system based on 5G Internet of Things is about 50% higher in data monitoring than the traditional monitoring system, the feedback speed is about 36% higher, and the protection monitoring capability is higher. It will be based on 5G Internet of Things. The monitoring system is applied in the tunnel lining, which helps to collect the actual situation of the tunnel lining faster and more convenient for prediction and maintenance.
{"title":"Computer Monitoring System Based on 5G Internet of Things in Service Period of Tunnel Lining","authors":"Rajite Ragab","doi":"10.38007/ijmc.2022.030402","DOIUrl":"https://doi.org/10.38007/ijmc.2022.030402","url":null,"abstract":": The rapid development of information technology has accelerated the rise of the Internet of Things, and with the application and popularization of the Internet of Things, it has gradually achieved good development momentum in various fields. How to further exert the maximum value of the Internet of Things, and combine the data it monitors with the computer network to form a comprehensive control of the computer monitoring system has become an important issue to be solved in the current related fields. The rapid development of technology, the rise of 5G technology, the application of 5G technology to the Internet of Things technology, the computer monitoring system based on 5G Internet of Things technology is more intelligent in the actual operation. Tunnel lining is a permanent structure that supports and maintains the long-term stability and durability of the tunnel. Its role is to: support and maintain the stability of the tunnel; maintain the space required for the train to run; prevent the weathering of the surrounding rock; remove the impact of groundwater, etc., apply the 5G IOT computer monitoring system to the tunnel lining, which can be effectively used by the monitoring system. Observing the situation of the tunnel helps the relevant personnel to make predictions and maintenance. In this paper, the 5G IOT computer monitoring system is designed to monitor the tunnel lining, and the tunnel lining is analyzed by the data observed by the monitoring system to realize prediction and maintenance. Through system monitoring, we found that the computer monitoring system based on 5G Internet of Things is about 50% higher in data monitoring than the traditional monitoring system, the feedback speed is about 36% higher, and the protection monitoring capability is higher. It will be based on 5G Internet of Things. The monitoring system is applied in the tunnel lining, which helps to collect the actual situation of the tunnel lining faster and more convenient for prediction and maintenance.","PeriodicalId":43265,"journal":{"name":"International Journal of Mobile Computing and Multimedia Communications","volume":"29 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88039395","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}
Pub Date : 2022-10-10DOI: 10.38007/ijmc.2022.030404
Yu-yan Han
: The purpose of this paper is to propose a hybrid super heuristic genetic algorithm for solving a class of fuzzy flexible job shop scheduling problems of work pieces processing time represented by using triangular fuzzy numbers, to minimize the optimization goal and reduce the fuzzy completion time. At the same time, under the conditions of product customization trend, diversified development of process routes, provide enterprises with a small-scale customized production that can be realized in time and a solution to improve the flexible operation of production systems .This paper first considers the practical problems in the production process of fuzzy flexible job shop and establishes a multi-objective optimization model. Then carried out a lot of research and analysis on traditional genetic algorithm, finding that the standard genetic algorithm is easy to fall into the problems of local optimum, low search efficiency and infeasible solution when solving the problem of shop scheduling. Came up with the hybrid heuristic algorithm for this problem, the algorithm incorporates methods such as hybrid heuristics, making the generated initial population as much as possible in the solution space of the whole problem, and to ensure the diversity of solution. Finally, through a series of improvements to the traditional genetic algorithm, improve the way of coding and genetic operators based on the super heuristic genetic algorithm, combine elite retention strategies and niche technologies to further optimize the convergence and diversity of algorithms. Calculates the fitness of the chromosome by weight coefficient change method. Therefore, the results of experimental analysis show that the proposed algorithm can verify the effectiveness of the proposed sorting criterion and super heuristic genetic algorithm, and can play a good role in the actual production process, it can also fully reflect the target requirements of fuzzy flexible job shop scheduling in production.
{"title":"Super Heuristic Genetic Algorithm for Fuzzy Flexible Job Shop Scheduling","authors":"Yu-yan Han","doi":"10.38007/ijmc.2022.030404","DOIUrl":"https://doi.org/10.38007/ijmc.2022.030404","url":null,"abstract":": The purpose of this paper is to propose a hybrid super heuristic genetic algorithm for solving a class of fuzzy flexible job shop scheduling problems of work pieces processing time represented by using triangular fuzzy numbers, to minimize the optimization goal and reduce the fuzzy completion time. At the same time, under the conditions of product customization trend, diversified development of process routes, provide enterprises with a small-scale customized production that can be realized in time and a solution to improve the flexible operation of production systems .This paper first considers the practical problems in the production process of fuzzy flexible job shop and establishes a multi-objective optimization model. Then carried out a lot of research and analysis on traditional genetic algorithm, finding that the standard genetic algorithm is easy to fall into the problems of local optimum, low search efficiency and infeasible solution when solving the problem of shop scheduling. Came up with the hybrid heuristic algorithm for this problem, the algorithm incorporates methods such as hybrid heuristics, making the generated initial population as much as possible in the solution space of the whole problem, and to ensure the diversity of solution. Finally, through a series of improvements to the traditional genetic algorithm, improve the way of coding and genetic operators based on the super heuristic genetic algorithm, combine elite retention strategies and niche technologies to further optimize the convergence and diversity of algorithms. Calculates the fitness of the chromosome by weight coefficient change method. Therefore, the results of experimental analysis show that the proposed algorithm can verify the effectiveness of the proposed sorting criterion and super heuristic genetic algorithm, and can play a good role in the actual production process, it can also fully reflect the target requirements of fuzzy flexible job shop scheduling in production.","PeriodicalId":43265,"journal":{"name":"International Journal of Mobile Computing and Multimedia Communications","volume":"16 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88661705","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}
Pub Date : 2022-10-10DOI: 10.38007/ijmc.2022.030403
Khadijaha Mansour
: With the progress of the times, more and more scientific and technological elements have been integrated into people’s daily life, which is manifested in fitting. Virtual fitting technology provides people with a more convenient and interactive fitting mode. The launch of Microsoft Kinect solves the problem of human body spatial information acquisition and facilitates the development of virtual fitting systems. This paper uses modeling software to build a human body 3D clothing model, and focuses on the human body 3D clothing modeling. This paper binds the three-dimensional clothing model with human bones to the user’s three-dimensional information collected through the Kinect camera to achieve the fusion of virtual and virtual clothing. This paper simulates the physical characteristics of clothing fabrics to improve the realism of virtual clothing degree. The iterative nearest point algorithm is improved. First, the voxel grid is down-sampled for the two point clouds, and then the scale-invariant feature points of the source point cloud are found and saved as a point cloud. The saved point cloud is registered with the target point cloud sampled from the voxel grid. In this paper, the human body point cloud data is collected through Kinect, and the point cloud segmentation, point cloud registration and point cloud reconstruction are studied separately, which makes the Kinect-based 3D human body modeling method more efficient and accurate. This paper proposes a method of iteratively deforming the standard model using the mesh deformation migration algorithm. The method is to establish a mapping relationship between models by given a set of corresponding point pairs between the source grid and the target grid, and realize the constrained deformation from the source grid to the target grid. Experiments show that the algorithm proposed in this paper uses a cheap depth camera to scan the human body. The algorithm preprocessing time is only about 1 second, and the average optimization time is about 3.6 seconds. It can overcome the shortcomings of low depth camera data accuracy, and the reconstruction time is short and the result is high accuracy.
{"title":"3D Reconstruction of Human Body in Virtual Fitting Room Based on Kinect","authors":"Khadijaha Mansour","doi":"10.38007/ijmc.2022.030403","DOIUrl":"https://doi.org/10.38007/ijmc.2022.030403","url":null,"abstract":": With the progress of the times, more and more scientific and technological elements have been integrated into people’s daily life, which is manifested in fitting. Virtual fitting technology provides people with a more convenient and interactive fitting mode. The launch of Microsoft Kinect solves the problem of human body spatial information acquisition and facilitates the development of virtual fitting systems. This paper uses modeling software to build a human body 3D clothing model, and focuses on the human body 3D clothing modeling. This paper binds the three-dimensional clothing model with human bones to the user’s three-dimensional information collected through the Kinect camera to achieve the fusion of virtual and virtual clothing. This paper simulates the physical characteristics of clothing fabrics to improve the realism of virtual clothing degree. The iterative nearest point algorithm is improved. First, the voxel grid is down-sampled for the two point clouds, and then the scale-invariant feature points of the source point cloud are found and saved as a point cloud. The saved point cloud is registered with the target point cloud sampled from the voxel grid. In this paper, the human body point cloud data is collected through Kinect, and the point cloud segmentation, point cloud registration and point cloud reconstruction are studied separately, which makes the Kinect-based 3D human body modeling method more efficient and accurate. This paper proposes a method of iteratively deforming the standard model using the mesh deformation migration algorithm. The method is to establish a mapping relationship between models by given a set of corresponding point pairs between the source grid and the target grid, and realize the constrained deformation from the source grid to the target grid. Experiments show that the algorithm proposed in this paper uses a cheap depth camera to scan the human body. The algorithm preprocessing time is only about 1 second, and the average optimization time is about 3.6 seconds. It can overcome the shortcomings of low depth camera data accuracy, and the reconstruction time is short and the result is high accuracy.","PeriodicalId":43265,"journal":{"name":"International Journal of Mobile Computing and Multimedia Communications","volume":"29 21 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77681415","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}
Pub Date : 2022-10-10DOI: 10.38007/ijmc.2022.030401
Ahthasha Khan
: With the rapid development and improvement of optical fibres, mobile communications, sensors and other technologies, the "Internet of Things" has been proposed. With the rapid advances in communication technologies and integrated circuits, the "Internet of Things" has also evolved rapidly over the past decade. With the advancement of IoT devices and communication network technologies, the design of IoT gateway platforms and sensor networks is becoming increasingly important. Although much research on IoT technologies in computing and communication networks exists, detailed system induction is lacking. This paper addresses the current development of sensor networks and IoT, IoT architecture, the relationship between sensor networks and IoT, and the implementation of sensor networks in IoT. In line with the IoT architecture and the role of home gateways, a market study and demand analysis of home gateways has been conducted to establish the deployment environment for home gateways and the deployment environment for sensor network nodes. In this paper, we propose the addition of a gateway data aggregation module to perform real-time data aggregation processing for sensor network data packet data processing. Aggregation processing can increase the payload in information transmission, reduce the number of times the sensor nodes send data in the home gateway, and effectively improve the network transmission efficiency and network throughput. Based on the software and hardware platforms of the built-in IoT home gateway and the software and hardware platforms of the sensor network, this paper gives a demand analysis of the home gateway sensor network access module, and proposes that the serial network is used to access the sensor network convergence node to implement the home gateway Development plan of sensor network access module. According to the needs analysis, design the flow chart of the access module and determine the communication interface between the access module and other modules, and complete the outline design of the access module. By simulating the data aggregation module of the home gateway and simulating the aggregation queue length threshold in the aggregation algorithm, the optimal aggregation queue length is obtained. The results show that the aggregation module reduces the number of calls of the home gateway data sending module by 40% and improves the home gateway network transmission efficiency.
{"title":"Computer Hardware and Communication Network Technology in Internet of Things","authors":"Ahthasha Khan","doi":"10.38007/ijmc.2022.030401","DOIUrl":"https://doi.org/10.38007/ijmc.2022.030401","url":null,"abstract":": With the rapid development and improvement of optical fibres, mobile communications, sensors and other technologies, the \"Internet of Things\" has been proposed. With the rapid advances in communication technologies and integrated circuits, the \"Internet of Things\" has also evolved rapidly over the past decade. With the advancement of IoT devices and communication network technologies, the design of IoT gateway platforms and sensor networks is becoming increasingly important. Although much research on IoT technologies in computing and communication networks exists, detailed system induction is lacking. This paper addresses the current development of sensor networks and IoT, IoT architecture, the relationship between sensor networks and IoT, and the implementation of sensor networks in IoT. In line with the IoT architecture and the role of home gateways, a market study and demand analysis of home gateways has been conducted to establish the deployment environment for home gateways and the deployment environment for sensor network nodes. In this paper, we propose the addition of a gateway data aggregation module to perform real-time data aggregation processing for sensor network data packet data processing. Aggregation processing can increase the payload in information transmission, reduce the number of times the sensor nodes send data in the home gateway, and effectively improve the network transmission efficiency and network throughput. Based on the software and hardware platforms of the built-in IoT home gateway and the software and hardware platforms of the sensor network, this paper gives a demand analysis of the home gateway sensor network access module, and proposes that the serial network is used to access the sensor network convergence node to implement the home gateway Development plan of sensor network access module. According to the needs analysis, design the flow chart of the access module and determine the communication interface between the access module and other modules, and complete the outline design of the access module. By simulating the data aggregation module of the home gateway and simulating the aggregation queue length threshold in the aggregation algorithm, the optimal aggregation queue length is obtained. The results show that the aggregation module reduces the number of calls of the home gateway data sending module by 40% and improves the home gateway network transmission efficiency.","PeriodicalId":43265,"journal":{"name":"International Journal of Mobile Computing and Multimedia Communications","volume":"36 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78409852","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}
Pub Date : 2022-10-10DOI: 10.38007/ijmc.2022.030405
Yue Wang
: With the development of artificial intelligence technology, robot technology has become more mature, and human-computer interaction technology has become more widely used. China is a country with frequent earthquakes. The application of robot technology to seismic signal detection is of great significance to solve various problems in earthquake disasters. The research purpose of this paper is to study adaptive endpoint detection of seismic signals based on human-computer interaction technology. Based on the analysis of adaptive noise reduction of signal autocorrelation function, this paper references the concept of autocorrelation similarity distance, and proposes human-machine interaction technology Seismic signal adaptive endpoint detection, discusses the description of noise and noisy signals based on autocorrelation similarity distance, and summarizes the adaptive endpoint detection method of seismic signals based on human-computer interaction technology, and gives the specific implementation of the algorithm Compared with the experimental detection results obtained by this method and the time-domain waveform envelope and the method of manually detecting the time-table seismic signal endpoint detection, the research results in this paper show that the accuracy of this algorithm is as high as 96.11%, Under the condition of noise ratio, the end position of the seismic signal can still be detected more accurately by using this algorithm.
{"title":"Seismic Signal Adaptive Endpoint Detection Based on Human-Computer Interaction","authors":"Yue Wang","doi":"10.38007/ijmc.2022.030405","DOIUrl":"https://doi.org/10.38007/ijmc.2022.030405","url":null,"abstract":": With the development of artificial intelligence technology, robot technology has become more mature, and human-computer interaction technology has become more widely used. China is a country with frequent earthquakes. The application of robot technology to seismic signal detection is of great significance to solve various problems in earthquake disasters. The research purpose of this paper is to study adaptive endpoint detection of seismic signals based on human-computer interaction technology. Based on the analysis of adaptive noise reduction of signal autocorrelation function, this paper references the concept of autocorrelation similarity distance, and proposes human-machine interaction technology Seismic signal adaptive endpoint detection, discusses the description of noise and noisy signals based on autocorrelation similarity distance, and summarizes the adaptive endpoint detection method of seismic signals based on human-computer interaction technology, and gives the specific implementation of the algorithm Compared with the experimental detection results obtained by this method and the time-domain waveform envelope and the method of manually detecting the time-table seismic signal endpoint detection, the research results in this paper show that the accuracy of this algorithm is as high as 96.11%, Under the condition of noise ratio, the end position of the seismic signal can still be detected more accurately by using this algorithm.","PeriodicalId":43265,"journal":{"name":"International Journal of Mobile Computing and Multimedia Communications","volume":"1 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79708884","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}
Pub Date : 2022-09-25DOI: 10.38007/ijmc.2022.030303
Mallik Alassery
: In recent years, children's food safety has many problems, and it is particularly important to detect food quality and quality and safety in a timely and efficient manner. At present, the application of biosensors for food safety testing is becoming more and more extensive. Label-free, real-time, and highly sensitive bioassays are currently important technologies in the analysis of biology. In this paper, the optical waveguide lightmode spectroscopy (OWLS) biosensor is used to propose a biosensing detection method based on MEMS micromirror, and the concentration of glucose solution is directly detected by this method. Through the calculation and simulation, the relationship between the thickness of the waveguide film and the sensitivity is obtained. The refractive index sensitivity is proportional to the inverse ratio of the effective refractive index, and an extreme value appears during the period. The glucose solution was detected in TE mode and TM mode. The experimental results show that the solution concentration has a good linear relationship with the incident angle, and the sensitivity can reach 5 ng/m L, which is more sensitive than the traditional immunological detection method. The dynamic characteristics of the MEMS micromirrors were tested and analyzed. The method has the advantages of small volume, simple structure and no labeling, and can realize in-situ detection and avoid damage to protein activity. It is a protein-free optical detection method with great potential.
{"title":"Biosensors in Testing Children's Food Quality and Quality Safety","authors":"Mallik Alassery","doi":"10.38007/ijmc.2022.030303","DOIUrl":"https://doi.org/10.38007/ijmc.2022.030303","url":null,"abstract":": In recent years, children's food safety has many problems, and it is particularly important to detect food quality and quality and safety in a timely and efficient manner. At present, the application of biosensors for food safety testing is becoming more and more extensive. Label-free, real-time, and highly sensitive bioassays are currently important technologies in the analysis of biology. In this paper, the optical waveguide lightmode spectroscopy (OWLS) biosensor is used to propose a biosensing detection method based on MEMS micromirror, and the concentration of glucose solution is directly detected by this method. Through the calculation and simulation, the relationship between the thickness of the waveguide film and the sensitivity is obtained. The refractive index sensitivity is proportional to the inverse ratio of the effective refractive index, and an extreme value appears during the period. The glucose solution was detected in TE mode and TM mode. The experimental results show that the solution concentration has a good linear relationship with the incident angle, and the sensitivity can reach 5 ng/m L, which is more sensitive than the traditional immunological detection method. The dynamic characteristics of the MEMS micromirrors were tested and analyzed. The method has the advantages of small volume, simple structure and no labeling, and can realize in-situ detection and avoid damage to protein activity. It is a protein-free optical detection method with great potential.","PeriodicalId":43265,"journal":{"name":"International Journal of Mobile Computing and Multimedia Communications","volume":"3 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2022-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73258257","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}
Pub Date : 2022-09-25DOI: 10.38007/ijmc.2022.030304
Fawan Almulihi
: Traditional smoke measurement methods for diesel vehicles mainly include Lingman blackness telescope and smoke meter. The Lingman Blackness Telescope uses a binocular prism telescope system. On the telescope partition board, a gray scale step block with corresponding Lingman smoke concentration of 1-5 level is made, and the transparent part is O level. The observer compares the smoke target with the gray gradient block through the left eyepiece of the telescope to determine the standard grade of smoke blackness. Smoke is divided into sampling part and measuring part. In the sampling part, the sampling cylinder extracts a certain volume of smoke from the exhaust pipe so that it passes through a certain area of white filter paper, so the particulate matter in the exhaust gas adheres to the filter paper and makes the filter paper black. Then, the smoke traces on the filter paper are measured by photoelectric detection device to evaluate the exhaust smoke of diesel engine. The above method can measure the smoke level of diesel vehicle exhaust to a certain extent, but it has great application limitations in practice, or cannot be applied in practice. For example, (I) Although the level of diesel vehicle exhaust smoke can be measured with the Lingman blackness telescope, it cannot record the level of diesel vehicle exhaust smoke and the relevant information of the vehicle; (2) The Lingman blackness telescope must be measured manually. It is time-consuming and laborious, and it is impossible for traffic police to observe every vehicle 24 hours with Lingman blackness telescope; (3) Smokemeter can only measure static diesel vehicles, but cannot measure driving vehicles. In view of the above problems, this paper introduces digital image processing technology, through the analysis of digital image of diesel vehicle exhaust, realizes the dynamic detection of diesel vehicle exhaust.
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