• Title/Summary/Keyword: ship position

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Questions of Social Order in Herman Melville's "Benito Cereno": The Conflict Between Babo's Plot and Delano's Abject Fear

  • Kim, Hyejin
    • Journal of English Language & Literature
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    • v.55 no.6
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    • pp.1123-1137
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    • 2009
  • Revisiting the horror of slave mutiny in nineteenth century America via Julia Kristeva's concept of abject, this essay examines abject fear in Amasa Delano and Babo's subversive act to deceive Delano in Herman Melville's "Benito Cereno." Babo, the slave, exercises subversive power, thereby reversing racial hierarchy aboard the slave ship-the San Dominick. Babo's ability to mimic and control racial stereotypes exposes how nineteenth-century racial hierarchy was only a social fiction, which becomes the very source of Delano's fear. Delano's dread belies upon the possible disruption of social order triggered by Babo'sblack rebellion. In order to repress his fear, Delano consciously and unconsciously attempts to re-inscribe white dominion and reaffirm black inferiority and stereotypes by means of rationalizing the disturbing signs he witnesses on the San Dominick. When Delano discovers the realsituation of the ship, he must relinquish the abject resonance that disturbs the previous racial order. Employing a legal document, Delano re-inscribes the official position of the blacks as slaves, defining them as violent savages, and thereby silences Babo. However, Melville's text is not a testament to white power. "Benito Cereno" actually endorses abject instability to challenge racial hierarchies through the poignant image of Babo's dead gaze in the last scene of the novella. Thus, "Benito Cereno" exemplifies the recurring power of abject as a threat to social hierarchy and as a constant reminder of the falsity and insecurity of a social order.

Shock-Resistance Responses of Frigate Equipments by Underwater Explosion

  • Kim, Hyunwoo;Choung, Joonmo
    • Journal of Ocean Engineering and Technology
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    • v.36 no.3
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    • pp.161-167
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    • 2022
  • Three-dimensional finite element analysis (3D-FEA) models have been used to evaluate the shock-resistance responses of various equipments, including armaments mounted on a warship caused by underwater explosion (UNDEX). This paper aims to check the possibility of using one-dimensional (1D) FEA models for the shock-resistance responses. A frigate was chosen for the evaluation of the shock-resistance responses by the UNDEX. The frigate was divided into the thirteen discrete segments along the length of the ship. The 1D Timoshenko beam elements were used to model the frigate. The explosive charge mass and the stand-off distance were determined based on the ship length and the keel shock factor (KSF), respectively. The UNDEX pressure fields were generated using the Geers-Hunter doubly asymptotic model. The pseudo-velocity shock response spectrum (PVSS) for the 1D-FEA model (1D-PVSS) was calculated using the acceleration history at a concerned equipment position where the digital recursive filtering algorithm was used. The 1D-PVSS was compared with the 3D-PVSS that was taken from a reference, and a relatively good agreement was found. In addition, the 1D-PVSS was compared with the design criteria specified by the German Federal Armed forces, which is called the BV043. The 1D-PVSS was proven to be relatively reasonable, reducing the computing cost dramatically.

Deep Learning based Distress Awareness System for Small Boat (딥러닝 기반 소형선박 승선자 조난 인지 시스템)

  • Chon, Haemyung;Noh, Jackyou
    • IEMEK Journal of Embedded Systems and Applications
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    • v.17 no.5
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    • pp.281-288
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    • 2022
  • According to statistics conducted by the Korea Coast Guard, the number of accidents on small boats under 5 tons is increasing every year. This is because only a small number of people are on board. The previously developed maritime distress and safety systems are not well distributed because passengers must be equipped with additional remote equipment. The purpose of this study is to develop a distress awareness system that recognizes man over-board situations in real time. This study aims to present the part of the passenger tracking system among the small ship's distress awareness situational system that can generate passenger's location information in real time using deep learning based object detection and tracking technologies. The system consisted of the following steps. 1) the passenger location information is generated in the form of Bounding box using its detection model (YOLOv3). 2) Based on the Bounding box data, Deep SORT predicts the Bounding box's position in the next frame of the image with Kalman filter. 3) When the actual Bounding Box is created within the range predicted by Kalman-filter, Deep SORT repeats the process of recognizing it as the same object. 4) If the Bounding box deviates the ship's area or an error occurs in the number of tracking occupant, the system is decided the distress situation and issues an alert. This study is expected to complement the problems of existing technologies and ensure the safety of individuals aboard small boats.

Advanced Evacuation Analysis for Passenger Ship Using Penalty Walking Velocity Algorithm for Obstacle Avoid (장애물 회피에 페널티 보행 속도 알고리즘을 적용한 여객선 승객 탈출 시뮬레이션)

  • Park, Kwang-Phil;Ha, Sol;Cho, Yoon-Ok;Lee, Kyu-Yeul
    • Journal of the Korea Society for Simulation
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    • v.19 no.4
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    • pp.1-9
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    • 2010
  • In this paper, advanced evacuation analysis simulation on a passenger ship is performed. Velocity based model has been implemented and used to calculate the movement of the individual passengers under the evacuation situation. The age and gender of each passenger are considered as the factors of walking speed. Flocking algorithm is applied for the passenger's group behavior. Penalty walking velocity is introduced to avoid collision between the passengers and obstacles, and to prevent the position overlap among passengers. Application of flocking algorithm and penalty walking velocity to evacuation simulation is verified through implementation of the 11 test problems in IMO (International Maritime Organization) MSC (Maritime Safety Committee) Circulation 1238.

Pixel-level prediction of velocity vectors on hull surface based on convolutional neural network (합성곱 신경망 기반 선체 표면 유동 속도의 픽셀 수준 예측)

  • Jeongbeom Seo;Dayeon Kim;Inwon Lee
    • Journal of the Korean Society of Visualization
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    • v.21 no.1
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    • pp.18-25
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    • 2023
  • In these days, high dimensional data prediction technology based on neural network shows compelling results in many different kind of field including engineering. Especially, a lot of variants of convolution neural network are widely utilized to develop pixel level prediction model for high dimensional data such as picture, or physical field value from the sensors. In this study, velocity vector field of ideal flow on ship surface is estimated on pixel level by Unet. First, potential flow analysis was conducted for the set of hull form data which are generated by hull form transformation method. Thereafter, four different neural network with a U-shape structure were conFig.d to train velocity vectors at the node position of pre-processed hull form data. As a result, for the test hull forms, it was confirmed that the network with short skip-connection gives the most accurate prediction results of streamlines and velocity magnitude. And the results also have a good agreement with potential flow analysis results. However, in some cases which don't have nothing in common with training data in terms of speed or shape, the network has relatively high error at the region of large curvature.

Depth tracking of occluded ships based on SIFT feature matching

  • Yadong Liu;Yuesheng Liu;Ziyang Zhong;Yang Chen;Jinfeng Xia;Yunjie Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.4
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    • pp.1066-1079
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    • 2023
  • Multi-target tracking based on the detector is a very hot and important research topic in target tracking. It mainly includes two closely related processes, namely target detection and target tracking. Where target detection is responsible for detecting the exact position of the target, while target tracking monitors the temporal and spatial changes of the target. With the improvement of the detector, the tracking performance has reached a new level. The problem that always exists in the research of target tracking is the problem that occurs again after the target is occluded during tracking. Based on this question, this paper proposes a DeepSORT model based on SIFT features to improve ship tracking. Unlike previous feature extraction networks, SIFT algorithm does not require the characteristics of pre-training learning objectives and can be used in ship tracking quickly. At the same time, we improve and test the matching method of our model to find a balance between tracking accuracy and tracking speed. Experiments show that the model can get more ideal results.

Ship Detection from Satellite Radar Imagery using Stepwise Threshold Determination (단계적 임계치 결정을 통한 위성레이더이미지 내 선박 탐지)

  • Ho-Kun Jeon;Hong Yeon Cho
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2023.05a
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    • pp.152-153
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    • 2023
  • AIS has been widely used for maritime traffic assessment for its convenience. However, AIS has problems with position missing due to radio interference and transmission distance limit. On the other hand, satellite radar determines the location of ships over a wide sea regardless of the problems. This study proposes a noble method of stepwise threshold determination to detect ships from Sentinel-1. The proposed method is up to 25 times faster than the existing moving window-based threshold determination method, and the detection accuracy is similar.

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Block-based Self-organizing TDMA for Reliable VDES in SANETs

  • Sol-Bee Lee;Jung-Hyok Kwon;Bu-Young Kim;Woo-Seong Shim;Dongwan Kim;Eui-Jik Kim
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.2
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    • pp.511-527
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    • 2024
  • This paper proposes a block-based self-organizing time-division multiple access (BSO-TDMA) protocol for very high frequency (VHF) data exchange system (VDES) in shipborne ad-hoc networks (SANETs). The BSO-TDMA reduces the collisions caused by the simultaneous transmission of automatic identification system (AIS) messages by uniformly allocating channel resources using a block-wise frame. For this purpose, the BSO-TDMA includes two functional operations: (1) frame configuration and (2) slot allocation. The first operation consists of block division and block selection. A frame is divided into multiple blocks, each consisting of fixed-size subblocks, by using the reporting interval (RI) of the ship. Then, the ship selects one of the subblocks within a block by considering the number of occupied slots for each subblock. The second operation allocates the slots within the selected subblock for transmitting AIS messages. First, one of the unoccupied slots within the selected subblock is allocated for the periodic transmission of position reports. Next, to transmit various types of AIS messages, an unoccupied slot is randomly selected from candidate slots located around the previously allocated slot. Experimental simulations are conducted to evaluate the performance of BSO-TDMA. The results show that BSO-TDMA has better performance than that of the existing SOTDMA.

A Study for Improving Naval Vessels's Position Calculation and Reporting Requirements for Safe Sailing in Narrow Channels (해군함정 협수로 연안 항해시 함위산출 및 보고사항 개선에 관한 연구)

  • Ko, Jae-Woo;Lim, Bong-Taek
    • Journal of Navigation and Port Research
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    • v.39 no.6
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    • pp.451-456
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    • 2015
  • This research examines the use of Cross Bearing in the Republic of Korea Navy. Specifically, this study focuses on the degrees of errors caused by the order of measuring targets and suggests a new method to determine Advice Course. It then reviews the appropriateness of the contents of Location Report that is regularly to the duty officer during a voyage in a narrow channel. Whenever a naval vessel passes through a narrow channel, many number of sailors are assigned to diverse positions in order to enhance navigational safety. Even though it is possible to easily recognize the location of a ship with helps of various kinds of navigational equipments using state-of-the-art technology, there are still several situations where sailors' efforts are indispensible for calculating the position of their ship : when the ship is damaged during an engagement with enemies and when the enemies interfere (GPS) signals. In addition, the particularity of naval vessels in which many number of crew members can be assigned to various positions supports for the suitability of the use of Cross Bearing in the Navy. This study will contribute to navigational safety of the ROK Navy and fostering junior naval officers' seamanship.

Horizontal Distance Correction of Single Channel Marine Seismic Data (단일 채널 해양 탄성파탐사 자료의 수평거리 보정)

  • Kim Hyun-Do;Kim Jin-Hoo
    • Geophysics and Geophysical Exploration
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    • v.7 no.4
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    • pp.245-250
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    • 2004
  • Horizontal-axes on the seismic section have been represented in a distance unit by applying horizontal-distance correction transformation on a 2-D seismic section of single channel marine seismic data. By drawing horizontal-axes in a distance unit, distortion of horizontal distances shown on the seismic section when the ship speed varies during a survey can be diminished considerably. Position information obtained by GPS and stored in each trace of seismic data as well as data collection windows were used for horizontal distance correction. The minimum window length was decided by considering ship speed and shot interval, and the maximum window length wat determined by reflecting radius of the 1st Fresnel zone. In choosing an optimum window length, horizontal resolution and stacking effect were considered simultaneously. By applying horizontal distance correction we could get a 2-D seismic section which is considered at reflecting the real subsurface structure analogously.