Implementation of a web-based logbook system on EAST is introduced, which can store the comments for the experiments into a database and access the documents via various web browsers. The three-tier software architect...Implementation of a web-based logbook system on EAST is introduced, which can store the comments for the experiments into a database and access the documents via various web browsers. The three-tier software architecture and asynchronous access technology are adopted to improve the system effectively. Authorized users can view the information of real-time discharge, comments from others and signal plots; add, delete, or revise their own comments; search signal data or comments under complicated search conditions; and collect relevant information and output it to an excel file. The web pages can be automatically updated after a new discharge is completed and without refreshment.展开更多
On April 28,I had a meeting with the Ammonia group.I stated that I wanted bo be notified when a crate was to beopened so that I could make a visual inspection of the condi-tion of the material.Then I would leave and t...On April 28,I had a meeting with the Ammonia group.I stated that I wanted bo be notified when a crate was to beopened so that I could make a visual inspection of the condi-tion of the material.Then I would leave and they would onlycall me if there was a discrepancy in the count or if there展开更多
Fishing logbook records the fishing behaviors and other information of fishing vessels.However,the accuracy of the recorded information is often difficult to guarantee due to the misreport and concealment.The fishing ...Fishing logbook records the fishing behaviors and other information of fishing vessels.However,the accuracy of the recorded information is often difficult to guarantee due to the misreport and concealment.The fishing vessel monitoring system(VMS)can monitor and record the navigation information of fishing vessels in real time,and it may be used to improve the accuracy of identifying the state of fishing vessels.If the VMS data and fishing logbook are combined to establish their relationships,then the navigation characteristics and fishing behavior of fishing vessels can be more accurately identified.Therefore,first,a method for determining the state of VMS data points using fishing log data was proposed.Secondly,the relationship between VMS data and the different states of fishing vessels was further explored.Thirdly,the state of the fishing vessel was predicted using VMS data by building machine learning models.The speed,heading,longitude,latitude,and time as features from the VMS data were extracted by matching the VMS and logbook data of three single otter trawl vessels from September 2012 to January 2013,and four machine learning models were established,i.e.,Random Forest(RF),Adaptive Boosting(AdaBoost),K-Nearest Neighbor(KNN),and Gradient Boosting Decision Tree(GBDT)to predict the behavior of fishing vessels.The prediction performances of the models were evaluated by using normalized confusion matrix and receiver operator characteristic curve.Results show that the importance rankings of spatial(longitude and latitude)and time features were higher than those of speed and heading.The prediction performances of the RF and AdaBoost models were higher than those of the KNN and GBDT models.RF model showed the highest prediction performance for fishing state.Meanwhile,AdaBoost model exhibited the highest prediction performance for non-fishing state.This study offered a technical basis for judging the navigation characteristics of fishing vessels,which improved the algorithm for judging the behavior of fishing vessels based on VMS data,enhanced the prediction accuracy,and upgraded the fishery management being more scientific and efficient.展开更多
为探究鸢乌贼(Sthenoteuthis oualaniensis)资源变化与海洋环境因子的关系,基于2019—2020年南海围网捕捞鸢乌贼的电子渔捞日志数据,首先分析了鸢乌贼资源的月间变动特征,之后利用结构方程模型解析海洋环境因子对其资源时空分布的影响...为探究鸢乌贼(Sthenoteuthis oualaniensis)资源变化与海洋环境因子的关系,基于2019—2020年南海围网捕捞鸢乌贼的电子渔捞日志数据,首先分析了鸢乌贼资源的月间变动特征,之后利用结构方程模型解析海洋环境因子对其资源时空分布的影响。结果表明:围网月间的平均单位捕捞努力量渔获量(Catch per unit effort,CPUE)变化趋势基本一致,年平均CPUE则为2020年大于2019年。南海鸢乌贼渔汛期为3—4月,高产区域集中在112°E—117°E、8°N—12°N,渔汛期CPUE呈现向东和向北偏移的趋势。海洋环境对鸢乌贼资源分布的综合影响系数为0.38,而海表盐度和光合有效辐射在海洋环境上的载荷量分别为0.87和0.82,两者是影响鸢乌贼资源分布的重要环境因子。所用结构方程模型为量化海洋环境因子与鸢乌贼资源分布之间的复杂关系提供了新的研究思路,可为鸢乌贼资源可持续利用和管理提供参考依据。展开更多
Every industry has its professional terms or particular use of common words.The marine industry is no exception.This paper attempts to give a brief introduction to the elementary vocabularies related to marine industr...Every industry has its professional terms or particular use of common words.The marine industry is no exception.This paper attempts to give a brief introduction to the elementary vocabularies related to marine industry from six aspects:types of ships;ship’s structure and equipment,manning,logbook,safety and organizations concerned.The corresponding Chinese terms is given simultaneously.It concludes that a good master of these vocabularies is useful and necessary for Chinese seafarers whose native language is not English.展开更多
基金supported by National Natural Science Foundation of China (No.10835009)the 973 project from the Chinese Ministry of Sciences and Technology (No.2009GB103000)
文摘Implementation of a web-based logbook system on EAST is introduced, which can store the comments for the experiments into a database and access the documents via various web browsers. The three-tier software architecture and asynchronous access technology are adopted to improve the system effectively. Authorized users can view the information of real-time discharge, comments from others and signal plots; add, delete, or revise their own comments; search signal data or comments under complicated search conditions; and collect relevant information and output it to an excel file. The web pages can be automatically updated after a new discharge is completed and without refreshment.
文摘On April 28,I had a meeting with the Ammonia group.I stated that I wanted bo be notified when a crate was to beopened so that I could make a visual inspection of the condi-tion of the material.Then I would leave and they would onlycall me if there was a discrepancy in the count or if there
基金Supported by the Public Welfare Technology Application Research Project of China(No.LGN21C190009)the Science and Technology Project of Zhoushan Municipality,Zhejiang Province(No.2022C41003)。
文摘Fishing logbook records the fishing behaviors and other information of fishing vessels.However,the accuracy of the recorded information is often difficult to guarantee due to the misreport and concealment.The fishing vessel monitoring system(VMS)can monitor and record the navigation information of fishing vessels in real time,and it may be used to improve the accuracy of identifying the state of fishing vessels.If the VMS data and fishing logbook are combined to establish their relationships,then the navigation characteristics and fishing behavior of fishing vessels can be more accurately identified.Therefore,first,a method for determining the state of VMS data points using fishing log data was proposed.Secondly,the relationship between VMS data and the different states of fishing vessels was further explored.Thirdly,the state of the fishing vessel was predicted using VMS data by building machine learning models.The speed,heading,longitude,latitude,and time as features from the VMS data were extracted by matching the VMS and logbook data of three single otter trawl vessels from September 2012 to January 2013,and four machine learning models were established,i.e.,Random Forest(RF),Adaptive Boosting(AdaBoost),K-Nearest Neighbor(KNN),and Gradient Boosting Decision Tree(GBDT)to predict the behavior of fishing vessels.The prediction performances of the models were evaluated by using normalized confusion matrix and receiver operator characteristic curve.Results show that the importance rankings of spatial(longitude and latitude)and time features were higher than those of speed and heading.The prediction performances of the RF and AdaBoost models were higher than those of the KNN and GBDT models.RF model showed the highest prediction performance for fishing state.Meanwhile,AdaBoost model exhibited the highest prediction performance for non-fishing state.This study offered a technical basis for judging the navigation characteristics of fishing vessels,which improved the algorithm for judging the behavior of fishing vessels based on VMS data,enhanced the prediction accuracy,and upgraded the fishery management being more scientific and efficient.
文摘为探究鸢乌贼(Sthenoteuthis oualaniensis)资源变化与海洋环境因子的关系,基于2019—2020年南海围网捕捞鸢乌贼的电子渔捞日志数据,首先分析了鸢乌贼资源的月间变动特征,之后利用结构方程模型解析海洋环境因子对其资源时空分布的影响。结果表明:围网月间的平均单位捕捞努力量渔获量(Catch per unit effort,CPUE)变化趋势基本一致,年平均CPUE则为2020年大于2019年。南海鸢乌贼渔汛期为3—4月,高产区域集中在112°E—117°E、8°N—12°N,渔汛期CPUE呈现向东和向北偏移的趋势。海洋环境对鸢乌贼资源分布的综合影响系数为0.38,而海表盐度和光合有效辐射在海洋环境上的载荷量分别为0.87和0.82,两者是影响鸢乌贼资源分布的重要环境因子。所用结构方程模型为量化海洋环境因子与鸢乌贼资源分布之间的复杂关系提供了新的研究思路,可为鸢乌贼资源可持续利用和管理提供参考依据。
文摘Every industry has its professional terms or particular use of common words.The marine industry is no exception.This paper attempts to give a brief introduction to the elementary vocabularies related to marine industry from six aspects:types of ships;ship’s structure and equipment,manning,logbook,safety and organizations concerned.The corresponding Chinese terms is given simultaneously.It concludes that a good master of these vocabularies is useful and necessary for Chinese seafarers whose native language is not English.
