Pub Date : 2023-10-01DOI: 10.2174/266625581608231012101755
{"title":"Patent Selections","authors":"","doi":"10.2174/266625581608231012101755","DOIUrl":"https://doi.org/10.2174/266625581608231012101755","url":null,"abstract":"","PeriodicalId":36514,"journal":{"name":"Recent Advances in Computer Science and Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135762450","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 : 2023-09-14DOI: 10.2174/2666255816666230914085830
Yong Lan, Shaoxiong Huang, Zhenlong Wang, Yong Pan, Yan Zhao, Jianjun Sun
Introduction: Crack is the main bridge disease. The monitoring of the crack width is the key for determining whether the bridge needs to be maintained. The systematic and automatic detection of bridge cracks can be realized using the crack images, which are captured using unmanned aerial vehicles (UAV). Methods: Cracks in the image with a complex background and low contrast ratio are difficult to detect. In order to detect the tiny cracks, the image is preprocessed by homomorphic filtering to enhance the contrast ratio. It is a necessary step that makes the color clustering be used in the detection. An adaptive color clustering method is proposed to detect cracks without additional initialization. Morphological method is also used to obtain clean edges and skeletons. Results: The proposed method can accurately detect the crack areas with an actual width greater than 0.13 mm, and the absolute error is only 0.0013 mm. The relative error for all test images are smaller than 15.6%. Cracks over 0.2 mm need to be filled. Therefore, this error is completely acceptable in practice. Discussion: The proposed method is practical and reproducible for bridge disease automatic inspection based on UAV. In order to verify its advantage, the proposed method is compared with a state-of-the-art method, which is published on Sensors. The proposed method is proven to be better for images with water stains in its complex background. Conclusion: The proposed method can calculate the width of tiny cracks accurately, even if the width is below 0.2 mm.
{"title":"Width Calculation of Tiny Bridge Cracks Based on Unmanned Aerial Vehicle Images","authors":"Yong Lan, Shaoxiong Huang, Zhenlong Wang, Yong Pan, Yan Zhao, Jianjun Sun","doi":"10.2174/2666255816666230914085830","DOIUrl":"https://doi.org/10.2174/2666255816666230914085830","url":null,"abstract":"Introduction: Crack is the main bridge disease. The monitoring of the crack width is the key for determining whether the bridge needs to be maintained. The systematic and automatic detection of bridge cracks can be realized using the crack images, which are captured using unmanned aerial vehicles (UAV). Methods: Cracks in the image with a complex background and low contrast ratio are difficult to detect. In order to detect the tiny cracks, the image is preprocessed by homomorphic filtering to enhance the contrast ratio. It is a necessary step that makes the color clustering be used in the detection. An adaptive color clustering method is proposed to detect cracks without additional initialization. Morphological method is also used to obtain clean edges and skeletons. Results: The proposed method can accurately detect the crack areas with an actual width greater than 0.13 mm, and the absolute error is only 0.0013 mm. The relative error for all test images are smaller than 15.6%. Cracks over 0.2 mm need to be filled. Therefore, this error is completely acceptable in practice. Discussion: The proposed method is practical and reproducible for bridge disease automatic inspection based on UAV. In order to verify its advantage, the proposed method is compared with a state-of-the-art method, which is published on Sensors. The proposed method is proven to be better for images with water stains in its complex background. Conclusion: The proposed method can calculate the width of tiny cracks accurately, even if the width is below 0.2 mm.","PeriodicalId":36514,"journal":{"name":"Recent Advances in Computer Science and Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134972979","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 : 2023-09-11DOI: 10.2174/2666255816666230911151545
Akul Nagchandi, Pradyot Kher, Abhishek Gudipalli, Amit Tiwari
Background: The concept of pill reminders has been discussed and developed throughout the decade. It varies from cascaded plastic pill boxes to complicated robust dispensers. This proposed smart pill reminding system based on IoT is being designed by considering ease-to-use and cost-effectiveness. Method: A smart pill reminding system is a system that will alert the patient to take their respective pill at the desired time. It will also track the motion of the patient’s hand while taking the pill and will also display the pill count on an LCD Screen. In case a patient forgets/ignores the reminder provided by the system, the system will automatically display the status on the application that will be installed in the relative/caretaker’s phone and through an email on the patient's relative/caretaker’s email address to take subsequent action. The system will monitor the real-time using an RTC module, and as and when the current time matches the medicines time, it will activate its mechanism, and the patient will have a buffer time to take their medicine. In case a patient does take the medicine in the buffer time provided by the system, then one mechanism of the system will be activated. In another case, if a patient does not take the medicine in the stipulated time, further actions will be initiated by the system to benefit the patient. Results: It was tested and found that out of ten times, the system worked accurately nine times, with calculated accuracy as high as 90%. Initially, the Blynk application will display “Welcome Patient” and “You will be updated”. Once the RTC matches the scheduled time to take medicine, the buzzer starts buzzing. If the IR sensor detects the movement of the user’s hand, the LCD will update the pill count, and the pill count is reduced by one. The LCD will also display the message “Medicine Taken”. If the IR sensor does not detect the movement of the user’s hand, the LCD will display the same pill count. The LCD will also display the message “Med1 not Taken”. The Blynk will also be updated and will display the same messages. The green LED shows the status of the consumption of the pill. The email will sent to the caretaker in this case. Conclusion: In this work, all the problems related to the system are overcome in a systematic manner with the help of IoT and basic electronic applications. Thus, the system will help the user take all the prescribed medicines on time and will also update the user’s caretaker via application and email services. This will largely help the working class as well as the senior citizens. Thus, this proposed system can be commercialised as a handy and cost-effective device.
{"title":"IoT-based Smart Pill Reminding System","authors":"Akul Nagchandi, Pradyot Kher, Abhishek Gudipalli, Amit Tiwari","doi":"10.2174/2666255816666230911151545","DOIUrl":"https://doi.org/10.2174/2666255816666230911151545","url":null,"abstract":"Background: The concept of pill reminders has been discussed and developed throughout the decade. It varies from cascaded plastic pill boxes to complicated robust dispensers. This proposed smart pill reminding system based on IoT is being designed by considering ease-to-use and cost-effectiveness. Method: A smart pill reminding system is a system that will alert the patient to take their respective pill at the desired time. It will also track the motion of the patient’s hand while taking the pill and will also display the pill count on an LCD Screen. In case a patient forgets/ignores the reminder provided by the system, the system will automatically display the status on the application that will be installed in the relative/caretaker’s phone and through an email on the patient's relative/caretaker’s email address to take subsequent action. The system will monitor the real-time using an RTC module, and as and when the current time matches the medicines time, it will activate its mechanism, and the patient will have a buffer time to take their medicine. In case a patient does take the medicine in the buffer time provided by the system, then one mechanism of the system will be activated. In another case, if a patient does not take the medicine in the stipulated time, further actions will be initiated by the system to benefit the patient. Results: It was tested and found that out of ten times, the system worked accurately nine times, with calculated accuracy as high as 90%. Initially, the Blynk application will display “Welcome Patient” and “You will be updated”. Once the RTC matches the scheduled time to take medicine, the buzzer starts buzzing. If the IR sensor detects the movement of the user’s hand, the LCD will update the pill count, and the pill count is reduced by one. The LCD will also display the message “Medicine Taken”. If the IR sensor does not detect the movement of the user’s hand, the LCD will display the same pill count. The LCD will also display the message “Med1 not Taken”. The Blynk will also be updated and will display the same messages. The green LED shows the status of the consumption of the pill. The email will sent to the caretaker in this case. Conclusion: In this work, all the problems related to the system are overcome in a systematic manner with the help of IoT and basic electronic applications. Thus, the system will help the user take all the prescribed medicines on time and will also update the user’s caretaker via application and email services. This will largely help the working class as well as the senior citizens. Thus, this proposed system can be commercialised as a handy and cost-effective device.","PeriodicalId":36514,"journal":{"name":"Recent Advances in Computer Science and Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136023994","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 : 2023-09-08DOI: 10.2174/2666255816666230901145310
Xiaopu Ma, Qinglei Qi, Li Zhao, Fei Ning, He Li
If we rely solely on whether to assign permissions together to determine roles, the roles we generate may not necessarily reflect the needs of the system. Therefore, the role generation process can be done based on user-to-permission dynamic relationships, such as user dynamic operation logs, thus providing the motivation for this work. In our paper, we introduce a special generalization process and a frequent set-based analysis method to generate roles based on the particular data type of user dynamic operation logs so that the time factor of permissions used is considered before the process of role generation to generate the roles such also as auth_perms(r)={p_1,p_2,p_3}. Our algorithm is less time consuming and generates less roles than traditional algorithm. Furthermore, the roles generated by the algorithm can better describe the real needs of the system and have better interpretability. The results show that the algorithm has superior performance and useful role generation compared to traditional algorithm.
{"title":"Mining Roles Based on User Dynamic Operation Logs","authors":"Xiaopu Ma, Qinglei Qi, Li Zhao, Fei Ning, He Li","doi":"10.2174/2666255816666230901145310","DOIUrl":"https://doi.org/10.2174/2666255816666230901145310","url":null,"abstract":"\u0000\u0000If we rely solely on whether to assign permissions together to determine roles, the roles we generate may not necessarily reflect the needs of the system. Therefore, the role generation process can be done based on user-to-permission dynamic relationships, such as user dynamic operation logs, thus providing the motivation for this work.\u0000\u0000\u0000\u0000In our paper, we introduce a special generalization process and a frequent set-based analysis method to generate roles based on the particular data type of user dynamic operation logs so that the time factor of permissions used is considered before the process of role generation to generate the roles such also as auth_perms(r)={p_1,p_2,p_3}.\u0000\u0000\u0000\u0000Our algorithm is less time consuming and generates less roles than traditional algorithm. Furthermore, the roles generated by the algorithm can better describe the real needs of the system and have better interpretability.\u0000\u0000\u0000\u0000The results show that the algorithm has superior performance and useful role generation compared to traditional algorithm.\u0000","PeriodicalId":36514,"journal":{"name":"Recent Advances in Computer Science and Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44993298","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 : 2023-09-01DOI: 10.2174/266625581607231012095121
{"title":"Patent Selections","authors":"","doi":"10.2174/266625581607231012095121","DOIUrl":"https://doi.org/10.2174/266625581607231012095121","url":null,"abstract":"","PeriodicalId":36514,"journal":{"name":"Recent Advances in Computer Science and Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135691622","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 : 2023-08-25DOI: 10.2174/2666255816666230825100307
S. S. Birunda, R. Kanniga Devi, M. Muthukannan
Twitter has rapidly become a go-to source for current events coverage. The more people rely on it, the more important it is to provide accurate data. Twitter makes it easy to spread misinformation, which can have a significant impact on how people feel, especially if false information spreads around COVID-19. Unfortunately, twitter was also used to spread myths and misinformation about the illness and its preventative immunization. So, it is crucial to identify false information before its spread gets out of hand. In this research, we look into the efficacy of several different types of deep neural networks in automatically classifying and identifying fake news content posted on social media platforms in relation to the COVID-19 pandemic. These networks include long short-term memory (LSTM), bi-directional LSTM, convolutional-neural-networks (CNN), and a hybrid of CNN-LSTM networks. The "COVID-19 Fake News" dataset includes 42,280, actual and fake news cases for the COVID-19 pandemic and associated vaccines and has been used to train and test these deep neural networks. The proposed models are executed and compared to other deep neural networks, the CNN model was found to have the highest accuracy at 95.6%.
{"title":"A Deep Learning Model to Detect Fake News About Covid-19","authors":"S. S. Birunda, R. Kanniga Devi, M. Muthukannan","doi":"10.2174/2666255816666230825100307","DOIUrl":"https://doi.org/10.2174/2666255816666230825100307","url":null,"abstract":"\u0000\u0000Twitter has rapidly become a go-to source for current events coverage. The more people rely on it, the more important it is to provide accurate data. Twitter makes it easy to spread misinformation, which can have a significant impact on how people feel, especially if false information spreads around COVID-19.\u0000\u0000\u0000\u0000Unfortunately, twitter was also used to spread myths and misinformation about the illness and its preventative immunization. So, it is crucial to identify false information before its spread gets out of hand. In this research, we look into the efficacy of several different types of deep neural networks in automatically classifying and identifying fake news content posted on social media platforms in relation to the COVID-19 pandemic. These networks include long short-term memory (LSTM), bi-directional LSTM, convolutional-neural-networks (CNN), and a hybrid of CNN-LSTM networks.\u0000\u0000\u0000\u0000The \"COVID-19 Fake News\" dataset includes 42,280, actual and fake news cases for the COVID-19 pandemic and associated vaccines and has been used to train and test these deep neural networks.\u0000\u0000\u0000\u0000The proposed models are executed and compared to other deep neural networks, the CNN model was found to have the highest accuracy at 95.6%.\u0000","PeriodicalId":36514,"journal":{"name":"Recent Advances in Computer Science and Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41346976","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 : 2023-08-23DOI: 10.2174/2666255816666230823125227
Sajida Mhammedi, Noreddine Gherabi, Hakim El Massari, M. Amnai
With the explosion of data in recent years, recommender systems have become increasingly important for personalized services and enhancing user engagement in various industries, including e-commerce and entertainment. Collaborative filtering (CF) is a widely used approach for generating recommendations, but it has limitations in addressing issues such as sparsity, scalability, and prediction errors. To address these challenges, this study proposes a novel hybrid CF method for movie recommendations that combines an incremental singular value decomposition approach with an item-based ontological semantic filtering approach in both online and offline phases. The ontology-based technique improves the accuracy of predictions and recommendations. The proposed method is evaluated on a real-world movie recommendation dataset using several performance metrics, including precision, F1 scores, and MAE. The results demonstrate that the proposed method outperforms existing methods in terms of accuracy while also addressing sparsity and scalability issues in recommender systems. Additionally, our approach has the advantage of reduced running time, making it a promising solution for practical applications. The proposed method offers a promising solution to the challenges faced by traditional CF methods in recommender systems. By combining incremental SVD and ontological semantic filtering, the proposed method not only improves the accuracy of predictions and recommendations but also addresses issues related to scalability and sparsity. Overall, the proposed method has the potential to contribute to the development of more accurate and efficient recommendation systems in various industries, including e-commerce and entertainment.
{"title":"Enhancing Recommendation System using Ontology-based Similarity and Incremental SVD Prediction","authors":"Sajida Mhammedi, Noreddine Gherabi, Hakim El Massari, M. Amnai","doi":"10.2174/2666255816666230823125227","DOIUrl":"https://doi.org/10.2174/2666255816666230823125227","url":null,"abstract":"\u0000\u0000With the explosion of data in recent years, recommender systems have become increasingly important for personalized services and enhancing user engagement in various industries, including e-commerce and entertainment. Collaborative filtering (CF) is a widely used approach for generating recommendations, but it has limitations in addressing issues such as sparsity, scalability, and prediction errors.\u0000\u0000\u0000\u0000To address these challenges, this study proposes a novel hybrid CF method for movie recommendations that combines an incremental singular value decomposition approach with an item-based ontological semantic filtering approach in both online and offline phases. The ontology-based technique improves the accuracy of predictions and recommendations. The proposed method is evaluated on a real-world movie recommendation dataset using several performance metrics, including precision, F1 scores, and MAE.\u0000\u0000\u0000\u0000The results demonstrate that the proposed method outperforms existing methods in terms of accuracy while also addressing sparsity and scalability issues in recommender systems. Additionally, our approach has the advantage of reduced running time, making it a promising solution for practical applications.\u0000\u0000\u0000\u0000The proposed method offers a promising solution to the challenges faced by traditional CF methods in recommender systems. By combining incremental SVD and ontological semantic filtering, the proposed method not only improves the accuracy of predictions and recommendations but also addresses issues related to scalability and sparsity. Overall, the proposed method has the potential to contribute to the development of more accurate and efficient recommendation systems in various industries, including e-commerce and entertainment.\u0000","PeriodicalId":36514,"journal":{"name":"Recent Advances in Computer Science and Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41430164","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 : 2023-08-17DOI: 10.2174/2666255816666230817101831
Savita Singh, Ankita Verma
This paper aims to provide a comprehensive study of the underlying buffer management issues and challenges in developing an efficient DTN routing protocol. Our aim is to begin with the discussion of buffer management schemes in DTNs in full generality and then dive in-depth, covering aspects of buffer management. Buffer strategies are used to determine which packets need to be forwarded or dropped. This paper will focus on the variety of buffer management strategies available, providing a comprehensive survey and analysis. We have also conducted an empirical analysis using simulator ONE to analyze the buffering time in various primary routing protocols such as Epidemic, Spary-and-wait (SNW), Prophet, Encounter based Routing (EBR) and Inter-Contact Delay and Location Information based Routing (ICDLIR). For these algorithms, it is also observed how varying the buffer size effect the delivery probability and overhead.
{"title":"Buffer Management Techniques in Delay Tolerant Networks: A Comprehensive Survey","authors":"Savita Singh, Ankita Verma","doi":"10.2174/2666255816666230817101831","DOIUrl":"https://doi.org/10.2174/2666255816666230817101831","url":null,"abstract":"\u0000\u0000This paper aims to provide a comprehensive study of the underlying buffer management issues and challenges in developing an efficient DTN routing protocol. Our aim is to begin with the discussion of buffer management schemes in DTNs in full generality and then dive in-depth, covering aspects of buffer management. Buffer strategies are used to determine which packets need to be forwarded or dropped. This paper will focus on the variety of buffer management strategies available, providing a comprehensive survey and analysis. We have also conducted an empirical analysis using simulator ONE to analyze the buffering time in various primary routing protocols such as Epidemic, Spary-and-wait (SNW), Prophet, Encounter based Routing (EBR) and Inter-Contact Delay and Location Information based Routing (ICDLIR). For these algorithms, it is also observed how varying the buffer size effect the delivery probability and overhead.\u0000","PeriodicalId":36514,"journal":{"name":"Recent Advances in Computer Science and Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48660072","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 : 2023-08-15DOI: 10.2174/2666255816666230815121119
K. Kalaiselvi, V. David
A significant problem in economics is stock market prediction. Due to the noise and volatility, however, timely prediction is typically regarded as one of the most difficult challenges. A sentiment-based stock price prediction that takes investors' emotional trends into account to overcome these difficulties is essential. This study aims to enhance the ELM's generalization performance and prediction accuracy. This article presents a new sentiment analysis based-stock prediction method using a modified extreme learning machine (ELM) with deterministic weight modification (DWM) called S-DELM. First, investor sentiment is used in stock prediction, which can considerably increase the model's predictive power. Hence, a convolutional neural network (CNN) is used to classify the user comments. Second, DWM is applied to optimize the weights and biases of ELM. The results of the experiments demonstrate that the S-DELM may not only increase prediction accuracy but also shorten prediction time, and investors' emotional tendencies are proven to help them achieve the expected results. The performance of S-DELM is compared with different variants of ELM and some conventional method.
{"title":"Modified Extreme Learning Machine Algorithm with Deterministic Weight Modification for Investment Decisions based on Sentiment Analysis","authors":"K. Kalaiselvi, V. David","doi":"10.2174/2666255816666230815121119","DOIUrl":"https://doi.org/10.2174/2666255816666230815121119","url":null,"abstract":"\u0000\u0000A significant problem in economics is stock market prediction. Due to the noise and volatility, however, timely prediction is typically regarded as one of the most difficult challenges. A sentiment-based stock price prediction that takes investors' emotional trends into account to overcome these difficulties is essential.\u0000\u0000\u0000\u0000This study aims to enhance the ELM's generalization performance and prediction accuracy.\u0000\u0000\u0000\u0000This article presents a new sentiment analysis based-stock prediction method using a modified extreme learning machine (ELM) with deterministic weight modification (DWM) called S-DELM. First, investor sentiment is used in stock prediction, which can considerably increase the model's predictive power. Hence, a convolutional neural network (CNN) is used to classify the user comments. Second, DWM is applied to optimize the weights and biases of ELM.\u0000\u0000\u0000\u0000The results of the experiments demonstrate that the S-DELM may not only increase prediction accuracy but also shorten prediction time, and investors' emotional tendencies are proven to help them achieve the expected results.\u0000\u0000\u0000\u0000The performance of S-DELM is compared with different variants of ELM and some conventional method.\u0000","PeriodicalId":36514,"journal":{"name":"Recent Advances in Computer Science and Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42844433","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}
A Comprehensive Model Incorporating Multiple Spatial Relations in 3D Space. At present, the research on two-dimensional spatial relation expression and inference models is relatively mature, but these models cannot be used to deal with three-dimensional spatial orientation relations. With the application of spatial orientation relations, three-dimensional spatial orientation relations are involved in many fields such as urban architectural design, robotics, image processing, etc. Two-dimensional spatial orientation relations models cannot satisfy the needs of three-dimensional spatial applications, so there is an urgent need to research three-dimensional spatial object orientation relations expression and inference models. This work aims to provide a comprehensive model incorporating multiple spatial relations in 3D space. The joint representation of direction, distance, and topological relations describes more complex spatial position relations among objects. Based on this comprehensive model, the computational properties of interval algebra are used to combine the directional and topological relations. The study lays a good foundation for the formal representation and reasoning of spatial relations between regions, enhances the analyzability of spatial relations between objects, and improves the accuracy of spatial analysis. The main novel contribution of this paper is that we propose a comprehensive orientation relation model, called 3D-TRD, which considers three spatial orientation relations simultaneously. The paper gives examples to represent the position relations of two spatial objects by comparing the RCC8 model, the 3DR46 model, and the comprehensive model to highlight the advantages of our proposed model. Based on the model, the bidirectional mapping association method is also used to represent the location of the spatial objects. The first advantage of the 3D-TRD model is that it represents spatial location relations more accurately than 3DR46, RCC8, and five qualitative distances. The second advantage of the 3D-TRD model is that it proposes a bidirectional mapping representation in three-dimensional space. The third advantage of the 3D-TRD model is that it provides a good basis for the formal representation and inference study of the spatial relations between regions.
{"title":"A Comprehensive Model Incorporating Multiple Spatial Relations in 3D Space","authors":"Mengmeng Li, Weiguang Liu, Yuanyuan Zhao, Jixun Gao, Miao Wang, Zhenxi Fang","doi":"10.2174/2666255816666230815094558","DOIUrl":"https://doi.org/10.2174/2666255816666230815094558","url":null,"abstract":"\u0000\u0000A Comprehensive Model Incorporating Multiple Spatial Relations in 3D Space.\u0000\u0000\u0000\u0000At present, the research on two-dimensional spatial relation expression and inference models is relatively mature, but these models cannot be used to deal with three-dimensional spatial orientation relations. With the application of spatial orientation relations, three-dimensional spatial orientation relations are involved in many fields such as urban architectural design, robotics, image processing, etc. Two-dimensional spatial orientation relations models cannot satisfy the needs of three-dimensional spatial applications, so there is an urgent need to research three-dimensional spatial object orientation relations expression and inference models.\u0000\u0000\u0000\u0000This work aims to provide a comprehensive model incorporating multiple spatial relations in 3D space. The joint representation of direction, distance, and topological relations describes more complex spatial position relations among objects.\u0000\u0000\u0000\u0000Based on this comprehensive model, the computational properties of interval algebra are used to combine the directional and topological relations.\u0000\u0000\u0000\u0000The study lays a good foundation for the formal representation and reasoning of spatial relations between regions, enhances the analyzability of spatial relations between objects, and improves the accuracy of spatial analysis.\u0000\u0000\u0000\u0000The main novel contribution of this paper is that we propose a comprehensive orientation relation model, called 3D-TRD, which considers three spatial orientation relations simultaneously. The paper gives examples to represent the position relations of two spatial objects by comparing the RCC8 model, the 3DR46 model, and the comprehensive model to highlight the advantages of our proposed model. Based on the model, the bidirectional mapping association method is also used to represent the location of the spatial objects. The first advantage of the 3D-TRD model is that it represents spatial location relations more accurately than 3DR46, RCC8, and five qualitative distances. The second advantage of the 3D-TRD model is that it proposes a bidirectional mapping representation in three-dimensional space. The third advantage of the 3D-TRD model is that it provides a good basis for the formal representation and inference study of the spatial relations between regions.\u0000","PeriodicalId":36514,"journal":{"name":"Recent Advances in Computer Science and Communications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46376815","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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