Pub Date : 2024-01-29DOI: 10.2174/0118722121281570240122065836
Yuan Zhang, Ziqi Liu, Yibing Wang
This paper provides an overview of representative patents related to space docking mechanisms in terms of structural and functional optimization. The working principle and characteristics are explained. By comparing different types of space docking mechanisms, we summarized the main problems of the current space docking mechanism and proposed some improvements. They include electromagnetic docking, modularization and standardization, together with the use of advanced design optimization algorithms and intelligent drive technology.
{"title":"Development and Overview of Space Docking Mechanism","authors":"Yuan Zhang, Ziqi Liu, Yibing Wang","doi":"10.2174/0118722121281570240122065836","DOIUrl":"https://doi.org/10.2174/0118722121281570240122065836","url":null,"abstract":"\u0000\u0000This paper provides an overview of representative patents related to space docking mechanisms\u0000in terms of structural and functional optimization. The working principle and characteristics\u0000are explained. By comparing different types of space docking mechanisms, we summarized the main\u0000problems of the current space docking mechanism and proposed some improvements. They include\u0000electromagnetic docking, modularization and standardization, together with the use of advanced\u0000design optimization algorithms and intelligent drive technology.\u0000","PeriodicalId":40022,"journal":{"name":"Recent Patents on Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140486264","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 : 2024-01-16DOI: 10.2174/0118722121283037231231064521
Beibei He, Shengchao Su, Yiwang Wang
In recent years, with the development of the Internet of Vehicles, a variety of novel in-vehicle application devices have surfaced, exhibiting increasingly stringent requirements for time delay. Vehicular edge networks (VEN) can fully use network edge devices, such as roadside units (RSUs), for collaborative processing, which can effectively reduce latency. In recent years, with the development of the field of internet of vehicles, a variety of novel in-vehicle application devices have surfaced, exhibiting increasingly stringent requirements for time delay. Vehicular edge network (VEN) can make full use of network edge devices, such as road side unit (RSU) for collaborative processing, which can effectively reduce the latency. Most extant studies, including patents, assume that RSU has sufficient computing resources to provide unlimited services. But in fact, its computing resources will be limited with the increase in processing tasks, which will restrict the delay-sensitive vehicular applications. To solve this problem, a vehicle-to-vehicle computing task offloading method based on deep reinforcement learning is proposed in this paper, which fully considers the remaining available computational resources of neighboring vehicles to minimize the total task processing latency and enhance the offloading success rate. A vehicle-to-vehicle computing task offloading method based on deep reinforce-ment learning is proposed in this paper, which fully considers the remaining available computa-tional resources of neighboring vehicles with the objective of minimizing the total task processing latency and enhancing the offloading success rate. In the multi-service vehicle scenario, the analytic hierarchy process (AHP) was first used to prioritize the computing tasks of user vehicles. Next, an improved sequence-to-sequence (Seq2Seq) computing task scheduling model combined with an attention mechanism was designed, and the model was trained by an actor-critic (AC) reinforcement learning algorithm with the optimization goal of reducing the processing delay of computing tasks and improving the success rate of offloading. A task offloading strategy optimization model based on AHP-AC was obtained on this basis. The average latency and execution success rate are used as performance metrics to compare the proposed method with three other task offloading methods: only-local processing, greedy strategy- based algorithm, and random algorithm. In addition, experimental validation in terms of CPU frequency and the number of SVs is carried out to demonstrate the excellent generalization ability of the proposed method. The average latency and execution success rate are used as performance metrics to compare the proposed method with three other task offloading methods: only-local processing, greedy strate-gy-based algorithm and random algorithm. In addition, experimental validation in terms of both CPU frequency and the number of SVs is carried out to d
{"title":"Computing Task Offloading in Vehicular Edge Network via Deep Reinforcement Learning","authors":"Beibei He, Shengchao Su, Yiwang Wang","doi":"10.2174/0118722121283037231231064521","DOIUrl":"https://doi.org/10.2174/0118722121283037231231064521","url":null,"abstract":"\u0000\u0000In recent years, with the development of the Internet of Vehicles, a variety\u0000of novel in-vehicle application devices have surfaced, exhibiting increasingly stringent requirements\u0000for time delay. Vehicular edge networks (VEN) can fully use network edge devices, such as roadside\u0000units (RSUs), for collaborative processing, which can effectively reduce latency.\u0000\u0000\u0000\u0000In recent years, with the development of the field of internet of vehicles, a variety of novel in-vehicle application devices have surfaced, exhibiting increasingly stringent requirements for time delay. Vehicular edge network (VEN) can make full use of network edge devices, such as road side unit (RSU) for collaborative processing, which can effectively reduce the latency.\u0000\u0000\u0000\u0000Most extant studies, including patents, assume that RSU has sufficient computing resources\u0000to provide unlimited services. But in fact, its computing resources will be limited with the\u0000increase in processing tasks, which will restrict the delay-sensitive vehicular applications. To solve\u0000this problem, a vehicle-to-vehicle computing task offloading method based on deep reinforcement\u0000learning is proposed in this paper, which fully considers the remaining available computational resources\u0000of neighboring vehicles to minimize the total task processing latency and enhance the offloading\u0000success rate.\u0000\u0000\u0000\u0000A vehicle-to-vehicle computing task offloading method based on deep reinforce-ment learning is proposed in this paper, which fully considers the remaining available computa-tional resources of neighboring vehicles with the objective of minimizing the total task processing latency and enhancing the offloading success rate.\u0000\u0000\u0000\u0000In the multi-service vehicle scenario, the analytic hierarchy process (AHP) was first used\u0000to prioritize the computing tasks of user vehicles. Next, an improved sequence-to-sequence\u0000(Seq2Seq) computing task scheduling model combined with an attention mechanism was designed,\u0000and the model was trained by an actor-critic (AC) reinforcement learning algorithm with the optimization\u0000goal of reducing the processing delay of computing tasks and improving the success rate of\u0000offloading. A task offloading strategy optimization model based on AHP-AC was obtained on this\u0000basis.\u0000\u0000\u0000\u0000The average latency and execution success rate are used as performance metrics to compare\u0000the proposed method with three other task offloading methods: only-local processing, greedy strategy-\u0000based algorithm, and random algorithm. In addition, experimental validation in terms of CPU\u0000frequency and the number of SVs is carried out to demonstrate the excellent generalization ability of\u0000the proposed method.\u0000\u0000\u0000\u0000The average latency and execution success rate are used as performance metrics to compare the proposed method with three other task offloading methods: only-local processing, greedy strate-gy-based algorithm and random algorithm. In addition, experimental validation in terms of both CPU frequency and the number of SVs is carried out to d","PeriodicalId":40022,"journal":{"name":"Recent Patents on Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140505837","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 : 2024-01-15DOI: 10.2174/0118722121273412231220113727
Meng Xun, Zhaolong Li
Superhydrophobic surfaces have great application prospects due to their unique surface- wetting characteristics. However, superhydrophobic surfaces' micro-nano binary rough structure and low surface energy components are easily damaged or lost by wear and grease, which affects their durability and limits their practical application, so it is of great significance to study the durability of superhydrophobic surfaces. The review first introduces the preparation methods and application fields of superhydrophobic surfaces, then sorts out the test methods for the durability performance of superhydrophobic surfaces, methods to improve the durability of superhydrophobic surfaces are summarized, and finally points out some problems in the current research on the durability of superhydrophobic surfaces, aiming to have a comprehensive understanding of the research progress of durable superhydrophobic surfaces, provide some theoretical guidance for the development of durable superhydrophobic surfaces, and look forward to the development direction and trend of durable superhydrophobic surface research in the future. There have been substantial improvements achieved in the preparation techniques to increase the mechanical durability of superhydrophobic surfaces and widen their applications. This review examines pertinent patents and articles on the fabrication of superhydrophobic surfaces from both domestic and foreign sources. The paper introduces the fundamental preparation methods for superhydrophobic surfaces and examines three common techniques: the template method, the spraying method, and the etching method. Additionally, the study discusses these preparation methods and presents future development trends based on the latest research findings. Aiming at the mechanical durability of superhydrophobic surfaces, the test methods for the durability performance of superhydrophobic surfaces under mechanical action are reviewed. The paper also suggests four key methods for enhancing the durability of superhydrophobic surfaces. The refinement of superhydrophobic surface preparation techniques plays a crucial role in enhancing durability and broadening the applications of these surfaces. Additionally, it holds the potential to unlock new possibilities across various domains. The future holds promising prospects for the invention of additional patents and papers focused on superhydrophobic surfaces.
{"title":"Research Progress on Superhydrophobic Surface Preparation Methods and Mechanical Durability","authors":"Meng Xun, Zhaolong Li","doi":"10.2174/0118722121273412231220113727","DOIUrl":"https://doi.org/10.2174/0118722121273412231220113727","url":null,"abstract":"\u0000\u0000Superhydrophobic surfaces have great application prospects due to their unique surface-\u0000wetting characteristics. However, superhydrophobic surfaces' micro-nano binary rough structure\u0000and low surface energy components are easily damaged or lost by wear and grease, which affects\u0000their durability and limits their practical application, so it is of great significance to study the\u0000durability of superhydrophobic surfaces. The review first introduces the preparation methods and\u0000application fields of superhydrophobic surfaces, then sorts out the test methods for the durability\u0000performance of superhydrophobic surfaces, methods to improve the durability of superhydrophobic\u0000surfaces are summarized, and finally points out some problems in the current research on the\u0000durability of superhydrophobic surfaces, aiming to have a comprehensive understanding of the research\u0000progress of durable superhydrophobic surfaces, provide some theoretical guidance for the\u0000development of durable superhydrophobic surfaces, and look forward to the development direction\u0000and trend of durable superhydrophobic surface research in the future.\u0000There have been substantial improvements achieved in the preparation techniques to increase the\u0000mechanical durability of superhydrophobic surfaces and widen their applications.\u0000This review examines pertinent patents and articles on the fabrication of superhydrophobic surfaces\u0000from both domestic and foreign sources.\u0000The paper introduces the fundamental preparation methods for superhydrophobic surfaces and examines\u0000three common techniques: the template method, the spraying method, and the etching\u0000method. Additionally, the study discusses these preparation methods and presents future development\u0000trends based on the latest research findings. Aiming at the mechanical durability of superhydrophobic\u0000surfaces, the test methods for the durability performance of superhydrophobic surfaces\u0000under mechanical action are reviewed. The paper also suggests four key methods for enhancing\u0000the durability of superhydrophobic surfaces.\u0000The refinement of superhydrophobic surface preparation techniques plays a crucial role in enhancing\u0000durability and broadening the applications of these surfaces. Additionally, it holds the potential\u0000to unlock new possibilities across various domains. The future holds promising prospects for\u0000the invention of additional patents and papers focused on superhydrophobic surfaces.\u0000","PeriodicalId":40022,"journal":{"name":"Recent Patents on Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140508475","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 : 2024-01-12DOI: 10.2174/0118722121281062231220044142
Chenhao Xu, Baocheng Xie
With the development of automation technology, various actuators are widely used in fields such as robotics and biomedical equipment. However, traditional mechanical actuators have some problems, such as poor movement flexibility and insufficient movement flexibility, because of the characteristics of the mechanical structure. As a new driving mode, artificial muscle actuators can provide enough power and speed while remaining light and flexible, making them highly adaptable in various applications. As a result, artificial muscle actuators are gaining increasing attention. The purpose of this study is to give an overview of the patents related to artificial muscle actuators and introduce their principles, classifications, latest progress, and future development. This paper reviews the current representative patents related to artificial muscle actuators, such as fluid pressure artificial muscle actuators, thermal deformation artificial muscle actuators, and electrical deformation artificial muscle actuators. The optimization of artificial muscle actuators is beneficial to make the output of artificial mechanical devices more stable and more convenient for human-machine combinations. More related patents will be invented in the future.
{"title":"Recent Patents on Artificial Muscle Actuators","authors":"Chenhao Xu, Baocheng Xie","doi":"10.2174/0118722121281062231220044142","DOIUrl":"https://doi.org/10.2174/0118722121281062231220044142","url":null,"abstract":"\u0000\u0000With the development of automation technology, various actuators are\u0000widely used in fields such as robotics and biomedical equipment. However, traditional mechanical\u0000actuators have some problems, such as poor movement flexibility and insufficient movement flexibility, because of the characteristics of the mechanical structure. As a new driving mode, artificial\u0000muscle actuators can provide enough power and speed while remaining light and flexible, making\u0000them highly adaptable in various applications. As a result, artificial muscle actuators are gaining\u0000increasing attention.\u0000\u0000\u0000\u0000The purpose of this study is to give an overview of the patents related to artificial muscle actuators and introduce their principles, classifications, latest progress, and future development.\u0000\u0000\u0000\u0000This paper reviews the current representative patents related to artificial muscle actuators, such as fluid pressure artificial muscle actuators, thermal deformation artificial muscle actuators, and electrical deformation artificial muscle actuators.\u0000\u0000\u0000\u0000The optimization of artificial muscle actuators is beneficial to make the output of artificial mechanical devices more stable and more convenient for human-machine combinations.\u0000More related patents will be invented in the future.\u0000","PeriodicalId":40022,"journal":{"name":"Recent Patents on Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139624626","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 : 2024-01-11DOI: 10.2174/0118722121274858240102060107
Tongke Fan
To improve the accuracy of Chinese word splitting. With the development of Internet technology, people want to get some effective medical information from the Internet, but there are still technical difficulties for non-specialists. At the same time, the level of medical construction can not keep up with the demand of patients for medical treatment, the phenomenon of doctor-patient conflicts has not been fundamentally solved, and the problem of difficult consultation prevails. With the arrival of the era of big data and artificial intelligence, medical Q&A has been applied. In order to meet the user's need to get the correct answer as soon as possible, medical Q&A needs to have high execution efficiency. The accuracy of Chinese participle directly affects the execution efficiency of Q&A. Improving the accuracy of Chinese participle can fundamentally improve the accuracy of medical Q&A and shorten the answering time. Improvement of the Chinese Segmentation Algorithm based on BI-LSTM-CRF using natural language processing technology. Based on the same medical Q&A dataset, the medical Q&A is trained and tested under three commonly used segmentation algorithms and the segmentation algorithm designed in this paper. The experiments show that the Chinese Segmentation Algorithm studied in this paper improves the accuracy of medical Q&A and can improve the execution efficiency of medical Q&A.