{"title":"Foreword: Message From the <i>MTS Journal</i> Editor","authors":"Alicia M. Mahon","doi":"10.4031/mtsj.57.3.9","DOIUrl":"https://doi.org/10.4031/mtsj.57.3.9","url":null,"abstract":"","PeriodicalId":49878,"journal":{"name":"Marine Technology Society Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135581827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nicholas Rome, Kristen Yarincik, Jorge Brenner, Debra Hernandez, Jake Kritzer, Gerhard Kuska, Rebecca Pearson, Henry Ruhl
{"title":"Unlocking the Full Potential of Offshore Wind Energy Data With Observing Systems","authors":"Nicholas Rome, Kristen Yarincik, Jorge Brenner, Debra Hernandez, Jake Kritzer, Gerhard Kuska, Rebecca Pearson, Henry Ruhl","doi":"10.4031/mtsj.57.3.6","DOIUrl":"https://doi.org/10.4031/mtsj.57.3.6","url":null,"abstract":"","PeriodicalId":49878,"journal":{"name":"Marine Technology Society Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135579372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Oceanic surface currents are estimated from analysis of short duration video obtained by a nadir facing camera installed on a bridge over a tidal inlet. Data analyzed consisted of 13 two-minute video clips captured approximately every 40 min over a period of 8 hr, covering a significant portion of the tidal cycle. Surface current speed and direction estimates are obtained from each collected video using (i) a method originally developed for analysis of imagery from drones (CopterCurrents) and (ii) a particle tracking method. The horizontal (u, v) surface current velocity components and total horizontal velocity magnitude, obtained from the two methods, were in very good agreement with each other ( R 2 = .96 and Root Mean Square (RMS) differences of 0.12 m/s or less). Our analysis suggests that video cameras from stationary structures can provide surface flow measurements over inland waters and navigational channels where deployment of in-situ sensors is not feasible.
{"title":"Video Based Estimation of Surface Currents in a Tidal Inlet","authors":"Benjamin Middour, George Voulgaris, Douglas Cahl","doi":"10.4031/mtsj.57.3.4","DOIUrl":"https://doi.org/10.4031/mtsj.57.3.4","url":null,"abstract":"Abstract Oceanic surface currents are estimated from analysis of short duration video obtained by a nadir facing camera installed on a bridge over a tidal inlet. Data analyzed consisted of 13 two-minute video clips captured approximately every 40 min over a period of 8 hr, covering a significant portion of the tidal cycle. Surface current speed and direction estimates are obtained from each collected video using (i) a method originally developed for analysis of imagery from drones (CopterCurrents) and (ii) a particle tracking method. The horizontal (u, v) surface current velocity components and total horizontal velocity magnitude, obtained from the two methods, were in very good agreement with each other ( R 2 = .96 and Root Mean Square (RMS) differences of 0.12 m/s or less). Our analysis suggests that video cameras from stationary structures can provide surface flow measurements over inland waters and navigational channels where deployment of in-situ sensors is not feasible.","PeriodicalId":49878,"journal":{"name":"Marine Technology Society Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135581586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract This article considers the methods of capturing deep ocean images with deep manned submersibles Mir-1 and Mir-2 (6,000-m depth) for feature films. The filming of Titanic by IMAX (Stephen Low) and Lightstorm Entertainment (James Cameron) companies with the use of deep ocean technique was pioneering work. The problems, which were solved during filming, as well as the development of special equipment are discussed.
{"title":"The <i>Mir-1</i> and <i>Mir-2</i> Submersibles in Feature Films","authors":"Anatoly M. Sagalevich","doi":"10.4031/mtsj.57.3.7","DOIUrl":"https://doi.org/10.4031/mtsj.57.3.7","url":null,"abstract":"Abstract This article considers the methods of capturing deep ocean images with deep manned submersibles Mir-1 and Mir-2 (6,000-m depth) for feature films. The filming of Titanic by IMAX (Stephen Low) and Lightstorm Entertainment (James Cameron) companies with the use of deep ocean technique was pioneering work. The problems, which were solved during filming, as well as the development of special equipment are discussed.","PeriodicalId":49878,"journal":{"name":"Marine Technology Society Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135581834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Direction of arrival (DOA) estimation is a fundamental problem in underwater acoustic vector sensor array signal processing. Because of the advantages of deep learning technology, this paper proposes two categories of data-driven DOA estimation methods for underwater acoustic vector sensor array, which transform the DOA estimation problem into a neural network classification problem. Specifically, one is the DOA estimation method of convolutional neural network based on teacher-student noise reduction (TS-CNN), which considers the covariance matrix as the training data set; the other is a DOA estimation method based on long-short term memory network and attention mechanism (LSTM-ATT), which applies the time-domain signal as the training data set. The experimental simulation results show that: 1) when the number of array elements is small, the accuracy of the DOA estimation method based on TS-CNN is equivalent to that of traditional methods, and it can effectively suppress the influence of noise when the signal-to-noise ratio (SNR) is low; 2) the accuracy of DOA estimation method based on LSTM-ATT is much higher than that of traditional Multiple Signal Classification method, especially in the case of low SNR, which also proves the importance of temporal characteristics for DOA estimation in a real environment.
{"title":"Data-Driven DOA Estimation Methods Based on Deep Learning for Underwater Acoustic Vector Sensor Array","authors":"Yangyang Xie, Biao Wang","doi":"10.4031/mtsj.57.3.3","DOIUrl":"https://doi.org/10.4031/mtsj.57.3.3","url":null,"abstract":"Abstract Direction of arrival (DOA) estimation is a fundamental problem in underwater acoustic vector sensor array signal processing. Because of the advantages of deep learning technology, this paper proposes two categories of data-driven DOA estimation methods for underwater acoustic vector sensor array, which transform the DOA estimation problem into a neural network classification problem. Specifically, one is the DOA estimation method of convolutional neural network based on teacher-student noise reduction (TS-CNN), which considers the covariance matrix as the training data set; the other is a DOA estimation method based on long-short term memory network and attention mechanism (LSTM-ATT), which applies the time-domain signal as the training data set. The experimental simulation results show that: 1) when the number of array elements is small, the accuracy of the DOA estimation method based on TS-CNN is equivalent to that of traditional methods, and it can effectively suppress the influence of noise when the signal-to-noise ratio (SNR) is low; 2) the accuracy of DOA estimation method based on LSTM-ATT is much higher than that of traditional Multiple Signal Classification method, especially in the case of low SNR, which also proves the importance of temporal characteristics for DOA estimation in a real environment.","PeriodicalId":49878,"journal":{"name":"Marine Technology Society Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135579367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"MTS India Section Engages Children With an Essay Contest","authors":"","doi":"10.4031/mtsj.57.2.10","DOIUrl":"https://doi.org/10.4031/mtsj.57.2.10","url":null,"abstract":"","PeriodicalId":49878,"journal":{"name":"Marine Technology Society Journal","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47613858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An ECOP's perspective on the UN Ocean Decade","authors":"","doi":"10.4031/mtsj.57.2.12","DOIUrl":"https://doi.org/10.4031/mtsj.57.2.12","url":null,"abstract":"","PeriodicalId":49878,"journal":{"name":"Marine Technology Society Journal","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48347562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Part 5: Ocean Decade Expands Global Coordination Network to Strengthen Impact of Initiatives","authors":"","doi":"10.4031/mtsj.57.2.5","DOIUrl":"https://doi.org/10.4031/mtsj.57.2.5","url":null,"abstract":"","PeriodicalId":49878,"journal":{"name":"Marine Technology Society Journal","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45914480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Part 2: Engagement and Support in the Ocean Decade","authors":"","doi":"10.4031/mtsj.57.2.2","DOIUrl":"https://doi.org/10.4031/mtsj.57.2.2","url":null,"abstract":"","PeriodicalId":49878,"journal":{"name":"Marine Technology Society Journal","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46913085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Part 4: A Year in Review: Global and Regional Conferences Shine a Spotlight on Ocean Science for Sustainable Development","authors":"","doi":"10.4031/mtsj.57.2.4","DOIUrl":"https://doi.org/10.4031/mtsj.57.2.4","url":null,"abstract":"","PeriodicalId":49878,"journal":{"name":"Marine Technology Society Journal","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42621645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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