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1
Kim, Bowon, Hanyoung Kim, Jeong Eun Sim, and Chanshik Shin. "LG Display's First Module Plant in Europe." Asian Case Research Journal 18, no. 02 (December 2014): 339–70. http://dx.doi.org/10.1142/s0218927514500138.
Повний текст джерелаАнотація:
As of 2012, LG Display was one of the largest LCD manufacturers in the world. Headquartered in Seoul, Korea, LGD had one R&D center, twelve LCD panel plants, and nine LCD module plants in Korea, China, and Poland. As the head of his company's Strategy and Marketing Center, Senior VP Champ Shin was evaluating one of the most important long-term strategic choices he had helped LGD to undertake in 2004. It was the company's decision to build its first module plant in Europe. In fact, it was the first plant LGD had ever built outside Korea and China. Now he had to assess the performance of the module plant in Europe for the last 5 years since it had started manufacturing in 2007 and report the overall evaluation result to the company's executive committee. Mr. Shin was preparing the report in two parts, one about the decision-making processes in 2004 his team had gone through to decide to build the European plant in Poland and the other about the plant's performance since its construction completed in 2007. In the report, he planned to describe the detailed steps taken by his team when making the decision and the plant's various performance outcomes. Shin thought he and his team had made a good choice, which was evidenced by the excellent performance observed from the module plant in Poland. Believing that his experience in making LGD's first European operations successful would be a valuable lesson for the entire company, Shin already started to chart out the company's next strategy.
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Suslyaev, V. G., O. N. Vladimirova, K. K. Shcherbina, A. V. Sokurov, Yu I. Zhdanov, and V. A. Chupryaev. "The role of early prosthetic help in the system of rehabilitation of the military personnel with military trauma: organizational, legal and methodical aspects." Bulletin of the Russian Military Medical Academy 20, no. 2 (December 15, 2018): 40–47. http://dx.doi.org/10.17816/brmma12218.
Повний текст джерелаАнотація:
The role and the place of early use of technical means of rehabilitation in the system of complex rehabilitation of patients and disabled people owing to a military trauma is considered. Need of early providing the needing persons with technical means of rehabilitation is proved during recovery treatment, including before establishment by him of disability and formation of the individual program of rehabilitation and an abilitation of disabled people. The efficiency of the developed non-plaster technology of prosthetics manufacturing techniques of artificial limbs of the lower extremities is proved by express method, options of her execution are offered. The first option of production of products on this technology consists in use of polymeric silicone covers and the water-hardening polymeric bandage directly on the patient’s stump. The second option of prosthetics is applied at some defects and diseases of a stump excluding application of silicone covers and full contact individual reception sleeves. For this purpose at production of medical and training artificial limbs of a shin and hip adjustable demountable reception sleeves from thermolayers for right-and left-side amputating defects are used. These options of prosthetics by express method are innovative, are aimed at early rendering the prosthetic and orthopedic help to patients with amputating defects. At production of artificial limbs on these technology domestic materials, modular and not modular accessories are used. The modular complete set of medical and training artificial limbs provides fast and individual setting up the scheme of construction, the individual choice of combinations of functional elements taking into account group of physical activity of the patient, a possibility of replacement of a reception sleeve and any of product elements without withdrawal of an artificial limb at the user. In need of service of a product, for example repair, replacement of the module (artificial foot, a knee) there is no requirement of urgent production of a similar design. Adjustable reception sleeves for primary artificial limbs of a shin and hip in the form of a standard series and moisture-curing bandage can add the list of products of medical appointment in laying for expansion of medical institutions during the special period.
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Gavrilov, E. V. "Anthropomorphic foot mock-up, to assess the trauma safety of the crew of auto armored vehicles with mine explosion." Izvestiya MGTU MAMI 11, no. 2 (June 15, 2017): 8–15. http://dx.doi.org/10.17816/2074-0530-66879.
Повний текст джерелаАнотація:
The article presents the results of development and testing of an anthropomorphic foot mock-up, which allows to determine the leg safety in case of mine explosion. As the statistics show, the legs of the crew of auto armored vehicles, as well as the driver and passengers of special protected civilian vehicles, are subject to a strong dynamic impact with a mine explosion, resulting in an increased level of injuries to this part of the body. When developing a protected technique, special attention is paid to leg injuries. Since the anthropomorphic measuring dummies used in the tests for mine explosion are limited, and it is necessary to determine the trauma safety of a large number of people, it was decided to develop an anthropomorphic foot mock-up. The anthropomorphic mock-up of the leg consists of the M2A-02 carrier module with the M3A-01 bushing adapter, the 723/8 foot, the calf shank spring, and the weight cylinder that replaces the missing shank mass and half the hip mass. To determine the axial force in the shin, a special motion sensor is used. According to the measured compression and the existing spring stiffness, a peak axial force is calculated. The anthropomorphic mock-up of the leg was calibrated on a special coprode stand for discharge. The discharge from various heights from 0.46 m to 2.5 m was made on different surfaces - sand and steel with a thickness of 8 mm. Also, a leg was dropped, shod in a statutory boot. After the calibration, the device was used in full-scale tests by undermining a special civil protected vehicle to determine the trauma safety of the driver's and passengers' legs. According to the results of the work, it was concluded that the foot mock-up can be used for testing special civil protected vehicles, as well as for armored vehicles with mine explosion.
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Zhu, Yongjie, Yi Zuo, and Tieshan Li. "Modeling of Ship Fuel Consumption Based on Multisource and Heterogeneous Data: Case Study of Passenger Ship." Journal of Marine Science and Engineering 9, no. 3 (March 3, 2021): 273. http://dx.doi.org/10.3390/jmse9030273.
Повний текст джерелаАнотація:
In the current shipping industry, quantitative measures of ship fuel consumption (SFC) have become one of the most important research topics in environmental protection and energy management related to shipping operations. In particular, the rapid development of sensor technologies enables multisource data collection to improve the modeling of the SFC problem. To address the features of such heterogeneous data, this paper proposes an integrated model for the estimation of SFC that includes three modules: a multisource data collection module, a heterogeneous data feature fusion module and a fuel consumption estimation module. First, in the data collection module, data related to SFC are collected by multiple sensors installed aboard the ship. Second, the feature fusion module employs a series of moving overlapped frames to merge different frequency data into small frames so that fusion features can be extracted from the heterogeneous data of multiple sources. Finally, in the fuel estimation module, the fusion features provide a novel way to consider the modeling and estimation of SFC as a classical time-series analysis using various machine learning techniques. Experimentally, linear regression (LR), support vector regression (SVR), and artificial neural network (ANN) were employed as the machine learning methods to train SFC models. Compared with the traditional feature extraction method, the accuracy of LR, SVR, and ANN were improved by 8.5, 0.35 and 51.5%, respectively, using the proposed method. The main contribution of this work is to consider the multisource and heterogeneous problem of sensor-based SFC data and propose an integrated model to extract the information of SFC data. Moreover, the experimental results showed that the estimation accuracy can be greatly improved.
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Gunawan, Gunawan, Allessandro Setyo Anggito Utomo, Kunihiro Hamada, Kazetaro Ouchi, Hiroyuki Yamamoto, and Yoichi Sueshige. "Optimization of Module Arrangement in Ship Engine Room." Journal of Ship Production and Design 37, no. 01 (February 17, 2021): 54–66. http://dx.doi.org/10.5957/jspd.12190066.
Повний текст джерелаАнотація:
This article presents a new approach for engine room design based on the modularization concept including the part arrangement optimization. The characteristics of the proposed methods are as follows. First, attention was paid to piping systems of multiple bulk carrier series of different sizes. The cost and length of the piping system as well as the similarity and the commonness of the modules and arrangements were considered. Second, to define an effective module that could be commonly used in different ships, a design structure matrix was adopted. Third, in the arrangement design, an optimization system was developed using a genetic algorithm to obtain a similar pattern for module arrangement in multiple series ships with specific consideration toward cost and similarity. Some examples using the proposed method are shown at the end of article.
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Zhou, Kexue, Min Zhang, Hai Wang, and Jinlin Tan. "Ship Detection in SAR Images Based on Multi-Scale Feature Extraction and Adaptive Feature Fusion." Remote Sensing 14, no. 3 (February 6, 2022): 755. http://dx.doi.org/10.3390/rs14030755.
Повний текст джерелаАнотація:
Deep learning has attracted increasing attention across a number of disciplines in recent years. In the field of remote sensing, ship detection based on deep learning for synthetic aperture radar (SAR) imagery is replacing traditional methods as a mainstream research method. The multiple scales of ship objects make the detection of ship targets a challenging task in SAR images. This paper proposes a new methodology for better detection of multi-scale ship objects in SAR images, which is based on YOLOv5 with a small model size (YOLOv5s), namely the multi-scale ship detection network (MSSDNet). We construct two modules in MSSDNet: the CSPMRes2 (Cross Stage Partial network with Modified Res2Net) module for improving feature representation capability and the FC-FPN (Feature Pyramid Network with Fusion Coefficients) module for fusing feature maps adaptively. Firstly, the CSPMRes2 module introduces modified Res2Net (MRes2) with a coordinate attention module (CAM) for multi-scale features extraction in scale dimension, then the CSPMRes2 module will be used as a basic module in the depth dimension of the MSSDNet backbone. Thus, our backbone of MSSDNet has the capabilities of features extraction in both depth and scale dimensions. In the FC-FPN module, we set a learnable fusion coefficient for each feature map participating in fusion, which helps the FC-FPN module choose the best features to fuse for multi-scale objects detection tasks. After the feature fusion, we pass the output through the CSPMRes2 module for better feature representation. The performance evaluation for this study is conducted using an RTX2080Ti GPU, and two different datasets: SSDD and SARShip are used. These experiments on SSDD and SARShip datasets confirm that MSSDNet leads to superior multi-scale ship detection compared with the state-of-the-art methods. Moreover, in comparisons of network model size and inference time, our MSSDNet also has huge advantages with related methods.
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Zhang, Dongdong, Chunping Wang, and Qiang Fu. "CAFC-Net: A Critical and Align Feature Constructing Network for Oriented Ship Detection in Aerial Images." Computational Intelligence and Neuroscience 2022 (February 24, 2022): 1–11. http://dx.doi.org/10.1155/2022/3391391.
Повний текст джерелаАнотація:
Ship detection is one of the fundamental tasks in computer vision. In recent years, the methods based on convolutional neural networks have made great progress. However, improvement of ship detection in aerial images is limited by large-scale variation, aspect ratio, and dense distribution. In this paper, a Critical and Align Feature Constructing Network (CAFC-Net) which is an end-to-end single-stage rotation detector is proposed to improve ship detection accuracy. The framework is formed by three modules: a Biased Attention Module (BAM), a Feature Alignment Module (FAM), and a Distinctive Detection Module (DDM). Specifically, the BAM extracts biased critical features for classification and regression. With the extracted biased regression features, the FAM generates high-quality anchor boxes. Through a novel Alignment Convolution, convolutional features can be aligned according to anchor boxes. The DDM produces orientation-sensitive feature and reconstructs orientation-invariant features to alleviate inconsistency between classification and localization accuracy. Extensive experiments on two remote sensing datasets HRS2016 and self-built ship datasets show the state-of-the-art performance of our detector.
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Zhang, Peipei, Guokun Xie, and Jinsong Zhang. "Gaussian Function Fusing Fully Convolutional Network and Region Proposal-Based Network for Ship Target Detection in SAR Images." International Journal of Antennas and Propagation 2022 (May 27, 2022): 1–20. http://dx.doi.org/10.1155/2022/3063965.
Повний текст джерелаАнотація:
Recently, ship target detection in Synthetic aperture radar (SAR) images has become one of the current research hotspots and plays an important role in the real-time detection of sea regions. The traditional SAR ship detection methods usually consist of two modules, one module named land-sea segmentation for removing the complicated land regions, and one module named ship target detection for realizing fine ship detection. An algorithm combining the Unet-based land-sea segmentation method and improved Faster RCNN-based ship detection method is proposed in this paper. The residual convolution module is introduced into the Unet structure to deepen the network level and improve the feature representation ability. The K-means method is introduced in the Faster RCNN method to cluster the size and aspect ratio of ship targets, to improve the anchor frame design, and make it more suitable for our ship detection task. Meanwhile, a fine detection algorithm uses the Gaussian function to fuse the confidence value of sea-land segmentation results and the coarse detection results. The segmentation and detection results on the established segmentation dataset and detection dataset, respectively, demonstrate the effectiveness of our proposed segmentation methods and detection methods.
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Feng, Chengxu, Bing Fu, Yasong Luo, and Houpu Li. "The Design and Development of a Ship Trajectory Data Management and Analysis System Based on AIS." Sensors 22, no. 1 (December 31, 2021): 310. http://dx.doi.org/10.3390/s22010310.
Повний текст джерелаАнотація:
To address the data storage, management, analysis, and mining of ship targets, the object-oriented method was employed to design the overall structure and functional modules of a ship trajectory data management and analysis system (STDMAS). This paper elaborates the detailed design and technical information of the system’s logical structure, module composition, physical deployment, and main functional modules such as database management, trajectory analysis, trajectory mining, and situation analysis. A ship identification method based on the motion features was put forward. With the method, ship trajectory was first partitioned into sub-trajectories in various behavioral patterns, and effective motion features were then extracted. Machine learning algorithms were utilized for training and testing to identify many types of ships. STDMAS implements such functions as database management, trajectory analysis, historical situation review, and ship identification and outlier detection based on trajectory classification. STDMAS can satisfy the practical needs for the data management, analysis, and mining of maritime targets because it is easy to apply, maintain, and expand.
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Mohapatra, Tapas Kumar, Asim Kumar Dey, Krushna Keshab Mohapatra, and Binod Sahu. "A novel non-isolated positive output voltage buck-boost converter." World Journal of Engineering 16, no. 1 (February 11, 2019): 201–11. http://dx.doi.org/10.1108/wje-06-2018-0214.
Повний текст джерелаАнотація:
Purpose A two switches non-isolated DC-DC novel buck-boost converter for charging the battery of electric vehicle is projected in this paper. The performance of the converter is compared with conventional buck-boost and transformer-less P/O buck-boost converter by Shan and Faqiang. The detail operation and performance analysis of the proposed converter is described both in continuous conduction mode and discontinuous conduction mode. A state space model and simulation model is designed in MATLAB. The PID controller parameters are tuned using Single-objective Salp swarm optimization algorithm using MATLAB. The controller is implemented using DSP board. The hardware and simulation results are projected in the paper to validate the effectiveness of the proposed buck-boost converter. A comparison analysis is projected among conventional converter and Shan & Faqiang converter. Design/methodology/approach The converter state space model is designed and simulation model is also developed in MATALAB. The controller is implemented using DSP board. The parameters are obtained using optimization technique using SSA algorithm. The hardware design is also implemented, and the result is compared with the Shan and Faqiang converter. The efficiency of the converter is also tested. Findings The converter is providing a higher efficiency. The inductor current is also positive in both buck and boost mode. The robustness of the controller is better for a wide range of variation of input voltage because the output voltage remains almost constant. Therefore, this is very suitable for battery charging and PV module application. Practical implications For battery charging from PV module where voltage fluctuation is frequent. Social implications The authors can use household applications to charge the battery using PV module. Originality/value The converter design concept is new. Optimization is used to find the parameters of the controllers and is implemented in hardware design. The parameters obtained provide robustness in the converter performance.
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Han, Huimin, Wenjuan Dai, Han Zhou, and Xinchun Sun. "Research on Ship Fire Monitoring and Alarm System." Journal of Physics: Conference Series 2029, no. 1 (September 1, 2021): 012142. http://dx.doi.org/10.1088/1742-6596/2029/1/012142.
Повний текст джерелаАнотація:
Abstract This paper analyzed the application status of land fire protection system and the characteristics of ship fire protection, and analyzed the functional requirements of ship fire protection system according to the ship special environment with crowded escape routes and complex structure. Using distributed intelligent control mode and modular structure design, a monitoring and alarm system composed of sensor acquisition module, microprocessor, central server, audible and visual alarm module, liquid crystal display module and CAN bus communication is constructed. The designed system has simple structure, stable performance and high cost performance, and has certain application and promotion value.
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Zhao, Danpei, Chunbo Zhu, Jing Qi, Xinhu Qi, Zhenhua Su, and Zhenwei Shi. "Synergistic Attention for Ship Instance Segmentation in SAR Images." Remote Sensing 13, no. 21 (October 30, 2021): 4384. http://dx.doi.org/10.3390/rs13214384.
Повний текст джерелаАнотація:
This paper takes account of the fact that there is a lack of consideration for imaging methods and target characteristics of synthetic aperture radar (SAR) images among existing instance segmentation methods designed for optical images. Thus, we propose a method for SAR ship instance segmentation based on the synergistic attention mechanism which not only improves the performance of ship detection with multi-task branches but also provides pixel-level contours for subsequent applications such as orientation or category determination. The proposed method—SA R-CNN—presents a synergistic attention strategy at the image, semantic, and target level with the following module corresponding to the different stages in the whole process of the instance segmentation framework. The global attention module (GAM), semantic attention module (SAM), and anchor attention module (AAM) were constructed for feature extraction, feature fusion, and target location, respectively, for multi-scale ship targets under complex background conditions. Compared with several state-of-the-art methods, our method reached 68.7 AP in detection and 56.5 AP in segmentation on the HRSID dataset, and showed 91.5 AP in the detection task on the SSDD dataset.
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He, Bokun, Qingyi Zhang, Ming Tong, and Chu He. "An Anchor-Free Method Based on Adaptive Feature Encoding and Gaussian-Guided Sampling Optimization for Ship Detection in SAR Imagery." Remote Sensing 14, no. 7 (April 4, 2022): 1738. http://dx.doi.org/10.3390/rs14071738.
Повний текст джерелаАнотація:
Recently, deep-learning methods have yielded rapid progress for object detection in synthetic aperture radar (SAR) imagery. It is still a great challenge to detect ships in SAR imagery due to ships’ small size and confusable detail feature. This article proposes a novel anchor-free detection method composed of two modules to deal with these problems. First, for the lack of detailed information on small ships, we suggest an adaptive feature-encoding module (AFE), which gradually fuses deep semantic features into shallow layers and realizes the adaptive learning of the spatial fusion weights. Thus, it can effectively enhance the external semantics and improve the representation ability of small targets. Next, for the foreground–background imbalance, the Gaussian-guided detection head (GDH) is introduced according to the idea of soft sampling and exploits Gaussian prior to assigning different weights to the detected bounding boxes at different locations in the training optimization. Moreover, the proposed Gauss-ness can down-weight the predicted scores of bounding boxes far from the object center. Finally, the effect of the detector composed of the two modules is verified on the two SAR ship datasets. The results demonstrate that our method can effectively improve the detection performance of small ships in datasets.
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Ross, Jonathan M. "Integrated Ship Design and Its Role in Enhancing Ship Production." Journal of Ship Production 11, no. 01 (February 1, 1995): 56–62. http://dx.doi.org/10.5957/jsp.1995.11.1.56.
Повний текст джерелаАнотація:
This paper focuses on an important trend that is increasing shipbuilding productivity: integrating the computer-aided ship design process. The ship design process increasingly is being performed with the help of computer programs, either individual programs that address single aspects of the design or integrated programs composed of modules that address a range of ship design aspects. In the case of integrated computer programs, the ship design process is enhanced through individual program modules sharing their results with each other, preferably from a common database. Modern integrated ship design programs not only improve the efficiency of ship design, they also improve the efficiency and ease of ship production, from lofting and numerical cutting to providing workshop drawings and production information.
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Zhou, Fan, Jing Gu, Wei Chen, and Xunpeng Ni. "Measurement of SO2 and NO2 in Ship Plumes Using Rotary Unmanned Aerial System." Atmosphere 10, no. 11 (October 29, 2019): 657. http://dx.doi.org/10.3390/atmos10110657.
Повний текст джерелаАнотація:
A key research problem in the field of ship emissions is how to perform efficient, accurate, and timely measurements of pollutant gases in a ship’s plume. To address this, we have designed and implemented an unmanned aerial system (UAS) that consists of a rotary unmanned aerial vehicle (UAV), a lightweight pod for exhaust monitoring, and a mobile control terminal. The UAV carries the pod and a camera and can fly into a plume at close range. The pod is equipped with a gas acquisition module, SO2 and NO2 sensors, and communication modules to measure the gases in real time. The mobile control terminal is convenient for operators and receives real-time video and measured gas concentrations. We measured SO2 and NO2 in six ship plumes in 2018 to verify the effectiveness and accuracy of the UAS. The SO2/NO2 ratios in high-sulfur fuel were significantly higher than of those in low-sulfur fuel and can thus be used for distinguishing the sulfur content of ship fuel. In comparison to land-based and airborne-based measurements, we conclude that the UAS provides an active, close-range, low-cost, and accurate measurement approach for monitoring ship emissions in real time.
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Xu, Xiao-Yan, Janusz Mindykowski, Tomasz Tarasiuk, and Chen Cheng. "Study of Harmonic Detection Methods under Non-Ideal Conditions in Ship Power Network." Polish Maritime Research 22, no. 3 (September 1, 2015): 82–89. http://dx.doi.org/10.1515/pomr-2015-0060.
Повний текст джерелаАнотація:
Abstract An improved harmonic detection method based on average arithmetic is proposed. According to the research results, the designed solution uses an LPF (low-pass-filter) and a mean value module connected in series instead of the conventional mean value module, and simultaneously, a three-phase voltage phase-locked module instead of commonly used PLL (phase lock loop) module is applied in order to reduce the influence caused by three-phase distorted voltage and rapid variation of load. The experimental results show that the application of this solution leads to increase in the accuracy of harmonics detection for distorted three-phase voltage and rapid variation of load.
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Aoyama, Kazuhiro, Wu Chen Xi, Tomohiko Ishikawa, and Tsuyoshi Koga. "Development of disassembling module design system for ship-breaking planning." Marine Systems & Ocean Technology 6, no. 2 (December 2011): 97–105. http://dx.doi.org/10.1007/bf03449297.
Повний текст джерела
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Li, Peiyong, Qiming Huang, Kun Shu, Yongqing Zhou, and Chong Wang. "Design of the Remote Monitoring System for CNC Ship Cold Frame Bender." Journal of Ship Production and Design 36, no. 02 (May 1, 2020): 123–30. http://dx.doi.org/10.5957/jspd.2020.36.2.123.
Повний текст джерелаАнотація:
The aim of this study was to overcome the problems and difficulties in the process of using CNC ship cold frame bender, especially for the routine maintenance and troubleshooting of CNC ship cold frame bender. The remote monitoring system is established according to the work principle of CNC ship cold frame bender. The system is composed of Client/Server and Browser/Server mixed structure, which includes data acquisition module, data transmission module, data network sharing module, remote online fault detection module, etc. The test results show that the system can collect and analyze the operation condition of the equipment remotely, and then analyze the data to realize the remote online detection. Furthermore, experts can evaluate the performance data and the test results remotely and give feedback to the site by the data network distribution platform. The test results also demonstrate the promising application of the proposed remote monitoring system to effectively improve the efficiency of the CNC ship cold frame bender.
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Hashim, Hadi Fakhir, Marwah M. Kareem, Waleed Khalid Al-Azzawi, and Adnan H. Ali. "Improving the performance of photovoltaic module during partial shading using ANN." International Journal of Power Electronics and Drive Systems (IJPEDS) 12, no. 4 (December 1, 2021): 2435. http://dx.doi.org/10.11591/ijpeds.v12.i4.pp2435-2442.
Повний текст джерелаАнотація:
<span lang="EN-US">Photovoltaic (PV) panels have drawback of having their peak power reduced when clouds or shade are present. Furthermore, it is only available while the sun shine. Nearby structures, plants, bird droppings, and other obstacles shade operating photovoltaic (PV) devices, effectively reducing the incident solar radiation produced by the modules. When these PV panels are exposed to partial shading, their power efficiency is reduced. A neural network with a kind of artificial neural network is used in the suggested hybrid method (ANN). The key focus of this article is to use environmental effects dependent on partial shading to get the maximum performance from a solar system. The suggested hybrid solution is tested in the MATLAB/Simulink working platform using partial shading test cases, and the efficiency is compared to other approaches. Additionally, the best options for the suggested procedure, current, voltage, and power are examined.</span>
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Liu, Eric H., and Wenjing Du. "Arithmetic properties for Andrews’ (48,6)- and (48,18)-singular overpartitions." Open Mathematics 17, no. 1 (May 11, 2019): 356–64. http://dx.doi.org/10.1515/math-2019-0026.
Повний текст джерелаАнотація:
Abstract Singular overpartition functions were defined by Andrews. Let Ck,i(n) denote the number of (k, i)-singular overpartitions of n, which counts the number of overpartitions of n in which no part is divisible by k and only parts ±i (mod k) may be overlined. A number of congruences modulo 3, 9 and congruences modulo powers of 2 for Ck,i(n) were discovered by Ahmed and Baruah, Andrews, Chen, Hirschhorn and Sellers, Naika and Gireesh, Shen and Yao for some pairs (k, i). In this paper, we prove some congruences modulo powers of 2 for C48, 6(n) and C48, 18(n).
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Yeo, Dong Jin, Moohyun Cha, and Duhwan Mun. "Simulating ship and buoy motions arising from ocean waves in a ship handling simulator." SIMULATION 88, no. 12 (July 16, 2012): 1407–18. http://dx.doi.org/10.1177/0037549712452128.
Повний текст джерелаАнотація:
A ship’s real-time three-dimensional (3D) visualization system, a component of a handling simulator, is one of its most important components, since realistic and intuitive image generation play an essential role in improving the effects of education using ship navigation simulators. Ship handling simulators should have capabilities of calculating ship motions (heave, pitch, and roll) at any given sea state and display the calculated motions through a real-time 3D visualization system. The motion solver of a ship handling simulator calculates those motions in addition to maneuverings for an own ship, the main simulation target, but only provides maneuvering information about traffic ships. Therefore, it is required to simulate traffic ship and buoy motions arising from ocean waves in a ship handling simulator for realistic visualization. In this paper, the authors propose a simple dynamics model by which ship and buoy motions are calculated with the input data of wave height and discuss a method for the implementation of a ship and buoy motion calculation module. The feasibility of the proposed dynamics model and the motion calculation module has been demonstrated through the development of a prototype real-time 3D visualization system based on an open-source 3D graphics engine.
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Hu, Yanzhe, Mengjie Xu, and Yang Li. "Simulation Model and State Analysis of Ship Transmission Line." Polish Maritime Research 25, s3 (December 1, 2018): 36–42. http://dx.doi.org/10.2478/pomr-2018-0110.
Повний текст джерелаАнотація:
Abstract In order to discuss the simulation model of the ship transmission line and the state of the transmission line, an early fault model is built according to the evolution principle of the short circuit fault of the transmission line and combining with the fault characteristics of the early fault. A small distributed ship transmission line system is built in MATLAB/ Simulink. Then, combined with the constructed fault module, the original short circuit module, and the load module, the various states (normal state, early fault state, severe early fault state, short circuit state) of the ship transmission line are stimulated, and the features of voltage signal in each state is analysed. It is concluded that, due to the normal operation of the ship transmission line system, the variation characteristics of the flow signal and voltage signal caused by the sudden load mutation, that is, the sudden load and the sudden increase load, are very similar to the changes caused by the early fault. Therefore, in order to find a more accurate early fault detection method, the state is divided into normal state, sudden load state, sudden increase and sudden decrease load state.
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Chapron, Kévin, Florentin Thullier, Patrick Lapointe, Julien Maître, Kévin Bouchard, and Sébastien Gaboury. "LIPSHOK: LIARA Portable Smart Home Kit." Sensors 22, no. 8 (April 7, 2022): 2829. http://dx.doi.org/10.3390/s22082829.
Повний текст джерелаАнотація:
Several smart home architecture implementations have been proposed in the last decade. These architectures are mostly deployed in laboratories or inside real habitations built for research purposes to enable the use of ambient intelligence using a wide variety of sensors, actuators and machine learning algorithms. However, the major issues for most related smart home architectures are their price, proprietary hardware requirements and the need for highly specialized personnel to deploy such systems. To tackle these challenges, lighter forms of smart home architectures known as smart homes in a box (SHiB) have been proposed. While SHiB remain an encouraging first step towards lightweight yet affordable solutions, they still suffer from few drawbacks. Indeed, some of these kits lack hardware support for some technologies, and others do not include enough sensors and actuators to cover most smart homes’ requirements. Thus, this paper introduces the LIARA Portable Smart Home Kit (LIPSHOK). It has been designed to provide an affordable SHiB solution that anyone is able to install in an existing home. Moreover, LIPSHOK is a generic kit that includes a total of four specialized sensor modules that were introduced independently, as our laboratory has been working on their development over the last few years. This paper first provides a summary of each of these modules and their respective benefits within a smart home context. Then, it mainly focus on the introduction of the LIPSHOK architecture that provides a framework to unify the use of the proposed sensors thanks to a common modular infrastructure capable of managing heterogeneous technologies. Finally, we compare our work to the existing SHiB kit solutions and outline that it offers a more affordable, extensible and scalable solution whose resources are distributed under an open-source license.
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Mat Radzi, Zulkifly Bin, Tang Jut Weng, Md Hafize Md Eusoff, Sarah Isnan, and Adenen Aziz. "Creation of Ship Navigation Data Using Simulation Technology in Training Module." Transactions on Maritime Science 10, no. 2 (October 21, 2021): 355–60. http://dx.doi.org/10.7225/toms.v10.n02.w03.
Повний текст джерелаАнотація:
All ships need navigation data to ensure they stay on track during course-changing maneuvers. Navigation data are usually obtained by shipyards while conducting turning trials at sea. The aim of this research was to generate navigation data for warships, such as the Leander Class Frigate (LCF). The research was conducted using the Ship Bridge Simulator (SBS) simulation technology at the Maritime Centre of the National Defence University of Malaysia (NDUM). Turning trials were conducted at various speeds, rudder angels, and heading changes. Distance to new course, advance and transfer have been tabulated for LCF navigation data. Navigation experts validated the data by nautical chart plotting. The data were found to be highly reliable for the training module. The research was successfully conducted and generated LCF navigation data. The navigation data collected are highly accurate and effective for the naval cadet navigation training module at the NDUM. The SBS software is highly suitable for turning trials and navigation data generation.
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Montero, Francisco, Mario Di Capua, and Amador Guzmán. "Analytical and numerical analysis of a solar thermoelectric system cooled by an active system." MRS Advances 3, no. 24 (2018): 1347–54. http://dx.doi.org/10.1557/adv.2018.52.
Повний текст джерелаАнотація:
ABSTRACTA solar thermoelectric generator (STEG) system composed of an optical concentrator system (OPS), a Bismuth Telluride thermoelectric module (TEG), and a cold plate-based cooling system (CPCS) was numerically simulated, to measure the efficiency of electric generation of a commercial thermoelectric module under controlled temperatures. The OPS is composed by a Fresnel lens that allows a temperature of around 200 °C, the OPS works with a solar irradiance of 1000 W/m2 (AM 1.5 Reference) and an optical concentration of 60. The OPS is coupled to the hot side of the TEG that consists of a commercially available thermoelectric module. The CPCS maintains a temperature of around 50 °C on the cold side of the TEG. To evaluate the configuration, a computational fluid dynamic (CFD) analysis was carried out to evaluated the thermal performance of the CPCS and the temperature achieved on the upper surface of the cooling device. Based on the numerical results generated by the CFD analysis, an analytical TEG efficiency of around 5% was achieved when a temperature difference, between the hot and cold sides of the commercial TE module, of 150 °C was maintained. We perform an analysis using the Hogan and Shih model that uses the thermoelectric material properties exposed by Chen et al.
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Tirta, Made, and Dian Anggraeni. "The Development of Web-based Graphical User Interface for Learning and Fitting Generalized Estimating Equation with Spline Smoothers." Jurnal ILMU DASAR 19, no. 1 (February 23, 2018): 63. http://dx.doi.org/10.19184/jid.v19i1.6997.
Повний текст джерелаАнотація:
Statistical modeling (regression analyses) have been growing rapidly into various directions to accommodate various data conditions. For longitudinal or repeated measures data, one of the suitable models is GEE (Generalized Estimating Equation). In practice, to do complex modeling such as GEE, the use of statistical software is necessary and it is available on free open source software R. However, GEE modeling on R can only be access through command line interface (CLI), and most practical researchers very much rely on Graphical User Interface (GUI) based statistics software. To make access to GEE (both order 1 and 2) much easier, we developed, using Shiny toolkit, two types of web-based GUI, standard pull down menu type and e-module type (with narrative theories) that can be utilized for learning and fitting GEE. This paper discusses the features of the interfaces and illustrates the use of them.
Keywords: longitudinal data, Generalized Estimating Equation (GEE), exponential families, statistical modeling, correlated response, nonparametric, natural splines, shiny toolkit
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Wang, Xiaoxiao, Chaoqian Li, and Yaotang Li. "A Geršgorin-type eigenvalue localization set with n parameters for stochastic matrices." Open Mathematics 16, no. 1 (April 2, 2018): 298–310. http://dx.doi.org/10.1515/math-2018-0030.
Повний текст джерелаАнотація:
AbstractA set in the complex plane which involves n parameters in [0, 1] is given to localize all eigenvalues different from 1 for stochastic matrices. As an application of this set, an upper bound for the moduli of the subdominant eigenvalues of a stochastic matrix is obtained. Lastly, we fix n parameters in [0, 1] to give a new set including all eigenvalues different from 1, which is tighter than those provided by Shen et al. (Linear Algebra Appl. 447 (2014) 74-87) and Li et al. (Linear and Multilinear Algebra 63(11) (2015) 2159-2170) for estimating the moduli of subdominant eigenvalues.
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Jung, Gonghyun, T. D. Huang, Pingsha Dongg, Randall M. Dull, Christopher C. Conrardy, and Nancy C. Porter. "Numerical Prediction of Buckling in Ship Panel Structures." Journal of Ship Production 23, no. 03 (August 1, 2007): 171–79. http://dx.doi.org/10.5957/jsp.2007.23.3.171.
Повний текст джерелаАнотація:
A shell-element-based numerical module was used to effectively predict welding-induced distortions. The numerical results were validated by comparison with a series of physical test panels. Eigenvalue analyses were performed to evaluate the buckling propensity of each test panel with and without transient thermal tensioning.
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Tang, Gang, Yichao Zhuge, Christophe Claramunt, and Shaoyang Men. "N-YOLO: A SAR Ship Detection Using Noise-Classifying and Complete-Target Extraction." Remote Sensing 13, no. 5 (February 26, 2021): 871. http://dx.doi.org/10.3390/rs13050871.
Повний текст джерелаАнотація:
High-resolution images provided by synthetic aperture radar (SAR) play an increasingly important role in the field of ship detection. Numerous algorithms have been so far proposed and relative competitive results have been achieved in detecting different targets. However, ship detection using SAR images is still challenging because these images are still affected by different degrees of noise while inshore ships are affected by shore image contrasts. To solve these problems, this paper introduces a ship detection method called N-YOLO, which based on You Only Look Once (YOLO). The N-YOLO includes a noise level classifier (NLC), a SAR target potential area extraction module (STPAE) and a YOLOv5-based detection module. First, NLC derives and classifies the noise level of SAR images. Secondly, the STPAE module is composed by a CA-CFAR and expansion operation, which is used to extract the complete region of potential targets. Thirdly, the YOLOv5-based detection module combines the potential target area with the original image to get a new image. To evaluate the effectiveness of the N-YOLO, experiments are conducted using a reference GaoFen-3 dataset. The detection results show that competitive performance has been achieved by N-YOLO in comparison with several CNN-based algorithms.
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Wu, Jixiang, Zongxu Pan, Bin Lei, and Yuxin Hu. "LR-TSDet: Towards Tiny Ship Detection in Low-Resolution Remote Sensing Images." Remote Sensing 13, no. 19 (September 28, 2021): 3890. http://dx.doi.org/10.3390/rs13193890.
Повний текст джерелаАнотація:
Recently, deep learning-based methods have made great improvements in object detection in remote sensing images (RSIs). However, detecting tiny objects in low-resolution images is still challenging. The features of these objects are not distinguishable enough due to their tiny size and confusing backgrounds and can be easily lost as the network deepens or downsamples. To address these issues, we propose an effective Tiny Ship Detector for Low-Resolution RSIs, abbreviated as LR-TSDet, consisting of three key components: a filtered feature aggregation (FFA) module, a hierarchical-atrous spatial pyramid (HASP) module, and an IoU-Joint loss. The FFA module captures long-range dependencies by calculating the similarity matrix so as to strengthen the responses of instances. The HASP module obtains deep semantic information while maintaining the resolution of feature maps by aggregating four parallel hierarchical-atrous convolution blocks of different dilation rates. The IoU-Joint loss is proposed to alleviate the inconsistency between classification and regression tasks, and guides the network to focus on samples that have both high localization accuracy and high confidence. Furthermore, we introduce a new dataset called GF1-LRSD collected from the Gaofen–1 satellite for tiny ship detection in low-resolution RSIs. The resolution of images is 16m and the mean size of objects is about 10.9 pixels, which are much smaller than public RSI datasets. Extensive experiments on GF1-LRSD and DOTA-Ship show that our method outperforms several competitors, proving its effectiveness and generality.
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Shih, Naai-Jung, Pei-Huang Diao, and Yi Chen. "ARTS, an AR Tourism System, for the Integration of 3D Scanning and Smartphone AR in Cultural Heritage Tourism and Pedagogy." Sensors 19, no. 17 (August 28, 2019): 3725. http://dx.doi.org/10.3390/s19173725.
Повний текст джерелаАнотація:
Interactions between cultural heritage, tourism, and pedagogy deserve investigation in an as-built environment under a macro- or micro-perspective of urban fabric. The heritage site of Shih Yih Hall, Lukang, was explored. An Augmented Reality Tourism System (ARTS) was developed on a smartphone-based platform for a novel application scenario using 3D scans converted from a point cloud to a portable interaction size. ARTS comprises a real-time environment viewing module, a space-switching module, and an Augmented Reality (AR) guide graphic module. The system facilitates scenario initiations, projection and superimposition, annotation, and interface customization, with software tools developed using ARKit® on the iPhone XS Max®. The three-way interaction between urban fabric, cultural heritage tourism, and pedagogy was made possible through background block-outs and an additive or selective display. The illustration of the full-scale experience of the smartphone app was made feasible for co-relating the cultural dependence of urban fabric on tourism. The great fidelity of 3D scans and AR scenes act as a pedagogical aid for students or tourists. A Post-Study System Usability Questionnaire (PSSUQ) evaluation verified the usefulness of ARTS.
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Saito, Kimio, Prasodjo Bubi S., Yasushi Higo, Hisashi Nobukawa, Katsuya Maeda, Akihiko Matsuda, and Mitsunori Uchida. "Study on Coastal Cargo Ship Consisting of Unit Modules." Journal of the Japan Society of Naval Architects and Ocean Engineers 3 (2006): 167–75. http://dx.doi.org/10.2534/jjasnaoe.3.167.
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García, Emilio, Eduardo Quiles, Ranko Zotovic-Stanisic, and Santiago C. Gutiérrez. "Predictive Fault Diagnosis for Ship Photovoltaic Modules Systems Applications." Sensors 22, no. 6 (March 10, 2022): 2175. http://dx.doi.org/10.3390/s22062175.
Повний текст джерелаАнотація:
In this paper, an application for the management and supervision by predictive fault diagnosis (PFD) of solar power generation systems is developed through a National Marine Electronics Association (NMEA) 2000 smart sensor network. Here, the NMEA 2000 network sensor devices for measuring and supervising the parameters inherent to solar power generation and renewable energy supply are applied. The importance of renewable power generation systems in ships is discussed, as well as the causes of photovoltaic modules (PVMs) aging due to superimposed causes of degradation, which is a natural and inexorable phenomenon that affects photovoltaic installations in a special way. In ships, PVMs are doubly exposed to inclement weather (solar radiation, cold, rain, dust, humidity, snow, wind, electrical storms, etc.), pollution, and a particularly aggressive environment in terms of corrosion. PFD techniques for the real-world installation and safe navigation of PVMs are discussed. A specific method based on the online analysis of the time-series data of random and seasonal I–V parameters is proposed for the comparative trend analyses of solar power generation. The objective is to apply PFD using as predictor symptom parameter (PS) the generated power decrease in affected PVMs. This PFD method allows early fault detection and isolation, whose appearance precedes by an adequate margin of maneuver, from the point of view of maintenance tasks applications. This early detection can stop the cumulative degradation phenomenon that causes the development of the most frequent and dangerous failure modes of solar modules, such as hot-spots. It is concluded that these failure modes can be conveniently diagnosed by performing comparative trend analyses of the measured power parameters by NMEA sensors.
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Wang, Jian Yu. "Application of AIS in Ship Collision Prevention." Advanced Materials Research 912-914 (April 2014): 577–80. http://dx.doi.org/10.4028/www.scientific.net/amr.912-914.577.
Повний текст джерелаАнотація:
This paper introduces the Working principle of AIS, emphatically introduces the main function and the application of AIS in ship collision prevention, illustrates the function of each module and the feasibility of making automatic decision, and the development status and application prospect of AIS is preliminary discussed. The AIS information contains almost all the necessary information for ship collision prevention, using the information for collision prevention decision-making, has a high credibility and broad application prospects.
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Qianghui, Zhong, Lin Mingchi, and Tang Yong. "Research on modular analysis and evaluation method of ship repair cost." E3S Web of Conferences 253 (2021): 03008. http://dx.doi.org/10.1051/e3sconf/202125303008.
Повний текст джерелаАнотація:
Based on the idea of modular design of ship, the ship modular method is used to study the target cost of ship repair, and a modular decomposition and analysis method of ship repair cost is proposed to decompose the ship repair project into relatively independent sub-modules, standardizes the repair scope of sub modules, determines the repair cost standard of sub-modules, and accumulates the repair cost of corresponding sub-modules. At the same time, from the perspective of cost control, cost risks are identified, and the fuzzy analytic hierarchy process is applied to analyze and evaluate risk factors to lay the foundation for cost adjustment and cost reduction risks.
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Yang, Hyun-Suk, Hyun-Jung Lim, Kun-Woo Kim, Yeong-Gwal Kwon, Dong-Mook Kim, and Sung-Geun Lee. "Development of Refer-container Remote Monitoring System for Ship using RF Module." Journal of the Korean Society of Marine Engineering 31, no. 4 (May 31, 2007): 425–32. http://dx.doi.org/10.5916/jkosme.2007.31.4.425.
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Xie, Chun Ling, and Shu Ying Li. "Design of Multi-Module Experiment-Rig of Ship Electrical Propulsion Prime Mover." Key Engineering Materials 419-420 (October 2009): 233–36. http://dx.doi.org/10.4028/www.scientific.net/kem.419-420.233.
Повний текст джерелаАнотація:
Diesel engine power plant, gas turbine power plant and steam turbine power plant are in common use in ship main propulsion power. These power plants have each advantage and disadvantage at mass, size, most high-power, economic ability, and maneuverability. But any single power is difficult to meet the requirement of improving the ships’ tactical performance, speed and maneuverability. In developing history of ship propulsion system, in order to solve the contradiction between full speed high-power and cruise economic ability, combined power plant form can change the performance of simple plant, which collected the advantage of all kinds of power plants[1]. Here combined power plant form is two or more same or not the same type engine combine used or trade off. The combined power plant can not only supply total power for ships when cruising, but also be more economical. So this plant is used widely. This paper, designs a multi-module experiment-rig and introduces its composition, working principle and disposition scheme, and carried out the dynamic characteristic experiment of the CODAG power plant.
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Han, Soon-Hung, and Dongkon Lee. "Integration of ship design software modules utilizing the superapplication concept." Journal of Marine Science and Technology 1, no. 5 (October 1996): 268–73. http://dx.doi.org/10.1007/bf02390725.
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Choi, Minjoo, Carl Fredrik Rehn, and Stein Ove Erikstad. "A hybrid method for a module configuration problem in modular adaptable ship design." Ships and Offshore Structures 13, no. 4 (October 11, 2017): 343–51. http://dx.doi.org/10.1080/17445302.2017.1382664.
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Xu, Xiaowo, Xiaoling Zhang, and Tianwen Zhang. "Lite-YOLOv5: A Lightweight Deep Learning Detector for On-Board Ship Detection in Large-Scene Sentinel-1 SAR Images." Remote Sensing 14, no. 4 (February 20, 2022): 1018. http://dx.doi.org/10.3390/rs14041018.
Повний текст джерелаАнотація:
Synthetic aperture radar (SAR) satellites can provide microwave remote sensing images without weather and light constraints, so they are widely applied in the maritime monitoring field. Current SAR ship detection methods based on deep learning (DL) are difficult to deploy on satellites, because these methods usually have complex models and huge calculations. To solve this problem, based on the You Only Look Once version 5 (YOLOv5) algorithm, we propose a lightweight on-board SAR ship detector called Lite-YOLOv5, which (1) reduces the model volume; (2) decreases the floating-point operations (FLOPs); and (3) realizes the on-board ship detection without sacrificing accuracy. First, in order to obtain a lightweight network, we design a lightweight cross stage partial (L-CSP) module to reduce the amount of calculation and we apply network pruning for a more compact detector. Then, in order to ensure the excellent detection performance, we integrate a histogram-based pure backgrounds classification (HPBC) module, a shape distance clustering (SDC) module, a channel and spatial attention (CSA) module, and a hybrid spatial pyramid pooling (H-SPP) module to improve detection performance. To evaluate the on-board SAR ship detection ability of Lite-YOLOv5, we also transplant it to the embedded platform NVIDIA Jetson TX2. Experimental results on the Large-Scale SAR Ship Detection Dataset-v1.0 (LS-SSDD-v1.0) show that Lite-YOLOv5 can realize lightweight architecture with a 2.38 M model volume (14.18% of model size of YOLOv5), on-board ship detection with a low computation cost (26.59% of FLOPs of YOLOv5), and superior detection accuracy (1.51% F1 improvement compared with YOLOv5).
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Li, Linhao, Zhiqiang Zhou, Bo Wang, Lingjuan Miao, Zhe An, and Xiaowu Xiao. "Domain Adaptive Ship Detection in Optical Remote Sensing Images." Remote Sensing 13, no. 16 (August 10, 2021): 3168. http://dx.doi.org/10.3390/rs13163168.
Повний текст джерелаАнотація:
With the successful application of the convolutional neural network (CNN), significant progress has been made by CNN-based ship detection methods. However, they often face considerable difficulties when applied to a new domain where the imaging condition changes significantly. Although training with the two domains together can solve this problem to some extent, the large domain shift will lead to sub-optimal feature representations, and thus weaken the generalization ability on both domains. In this paper, a domain adaptive ship detection method is proposed to better detect ships between different domains. Specifically, the proposed method minimizes the domain discrepancies via both image-level adaption and instance-level adaption. In image-level adaption, we use multiple receptive field integration and channel domain attention to enhance the feature’s resistance to scale and environmental changes, respectively. Moreover, a novel boundary regression module is proposed in instance-level adaption to correct the localization deviation of the ship proposals caused by the domain shift. Compared with conventional regression approaches, the proposed boundary regression module is able to make more accurate predictions via the effective extreme point features. The two adaption components are implemented by learning the corresponding domain classifiers respectively in an adversarial training way, thereby obtaining a robust model suitable for both of the two domains. Experiments on both supervised and unsupervised domain adaption scenarios are conducted to verify the effectiveness of the proposed method.
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Dymarski, Czesław, and Paweł Dymarsk. "Computational Simulation of Motion of a Rescue Module During its Launching from Ship at Rough Sea." Polish Maritime Research 21, no. 3 (October 28, 2014): 54–60. http://dx.doi.org/10.2478/pomr-2014-0030.
Повний текст джерелаАнотація:
Abstract This paper is a continuation of the work titled: “A computational model for simulation of motion of rescue module during its launching from stern ramp of a ship at rough sea”. It presents results of computer simulations of motion of a rescue module with embarked persons during its launching on rollers along stern ramp of a ship at rough sea. Te simulations were conducted for a selected ship fitted with a launching ramp, for a few selected scenarios of sea conditions. It was assumed that during this operation the ship drifts across direction of wave propagation.
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Borkowski, Piotr. "Ship course stabilization by feedback linearization with adaptive object model." Polish Maritime Research 21, no. 1 (January 1, 2013): 14–19. http://dx.doi.org/10.2478/pomr-2014-0003.
Повний текст джерелаАнотація:
ABSTRACT The algorithm of ship course stabilization herein presented is based on a feedback linearization controller with adaptive object model. The described method, consisting in current approximation of unknown object model functions by neuro-fuzzy approximators, represents a new generation of adaptive control methods. The implementation of this algorithm, which may constitute an executive module of a navigational decision support system, will contribute to a higher degree of automation and navigational safety improvement.
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Cheng, Peng, Ning Liang, Ruiye Li, Hai Lan, and Qian Cheng. "Analysis of Influence of Ship Roll on Ship Power System with Renewable Energy." Energies 13, no. 1 (December 18, 2019): 1. http://dx.doi.org/10.3390/en13010001.
Повний текст джерелаАнотація:
Renewable energy ship was regarded as one of the ship energy technologies with a good prospect. In order to study the application of solar and wind energy on ships in the marine environment and the impact of ship rolling on the system, the feasibility of applying solar energy and wind energy to ships was analyzed, and the structural composition of ship power system incorporating renewable energy source was studied. The model of the ship power system integrated with renewable energy was built in PSCAD/EMTDC simulation software. The layout of wind power generation system and photovoltaic power generation system was given for the actual ship, and the ship parameters and specific parameters of each simulation module were determined. It can be seen that the rolling of ship will cause fluctuations in the grid-connected power of the photovoltaic power generation system and the wind power generation system from the comparison of the simulation curves. Finally, a simulation experiment is provided to prove the access of the battery can well suppress the grid-connected power fluctuation caused by the rolling of the ship, which has an important impact on the stability of the ship power system with renewable energy.
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Chen, Dehai, Shiru Sun, Zhijun Lei, Heng Shao, and Yuzhao Wang. "Ship Target Detection Algorithm Based on Improved YOLOv3 for Maritime Image." Journal of Advanced Transportation 2021 (September 4, 2021): 1–11. http://dx.doi.org/10.1155/2021/9440212.
Повний текст джерелаАнотація:
Accurate identification of ships is the key technology of intelligent transportation in water. At the same time, it also provides a judgment basis for water traffic safety control. This paper proposed a detection method of ships in water based on improved You Only Look Once version 3 (YOLOv3), which is called Feature Attention, Feature Enhancement YOLOv3 (AE-YOLOv3). The feature attention module was constructed by introducing the attention mechanism, which was embedded in Darknet-53 for feature recalibration, which improved the feature extraction ability of the model in the complex navigable background. For the problem of insufficient semantic information of low-level features in the feature fusion process, a feature enhancement module was constructed and applied to the feature fusion part to enhance the receptive field size of the corresponding feature layer and the correlation degree of feature extraction network. Experiments were carried out on the public SeaShips dataset. Experiments show that the detection accuracy is as high as 98.72%, which is better than that of other mainstream ship identification models, fully verifying the superiority of this method in the detection of waterborne traffic ships.
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Tian, Ling, Yu Cao, Bokun He, Yifan Zhang, Chu He, and Deshi Li. "Image Enhancement Driven by Object Characteristics and Dense Feature Reuse Network for Ship Target Detection in Remote Sensing Imagery." Remote Sensing 13, no. 7 (March 31, 2021): 1327. http://dx.doi.org/10.3390/rs13071327.
Повний текст джерелаАнотація:
As the application scenarios of remote sensing imagery (RSI) become richer, the task of ship detection from an overhead perspective is of great significance. Compared with traditional methods, the use of deep learning ideas has more prospects. However, the Convolutional Neural Network (CNN) has poor resistance to sample differences in detection tasks, and the huge differences in the image environment, background, and quality of RSIs affect the performance for target detection tasks; on the other hand, upsampling or pooling operations result in the loss of detailed information in the features, and the CNN with outstanding results are often accompanied by a high computation and a large amount of memory storage. Considering the characteristics of ship targets in RSIs, this study proposes a detection framework combining an image enhancement module with a dense feature reuse module: (1) drawing on the ideas of the generative adversarial network (GAN), we designed an image enhancement module driven by object characteristics, which improves the quality of the ship target in the images while augmenting the training set; (2) the intensive feature extraction module was designed to integrate low-level location information and high-level semantic information of different resolutions while minimizing the computation, which can improve the efficiency of feature reuse in the network; (3) we introduced the receptive field expansion module to obtain a wider range of deep semantic information and enhance the ability to extract features of targets were at different sizes. Experiments were carried out on two types of ship datasets, optical RSI and Synthetic Aperture Radar (SAR) images. The proposed framework was implemented on classic detection networks such as You Only Look Once (YOLO) and Mask-RCNN. The experimental results verify the effectiveness of the proposed method.
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Guan, Wei, Haowen Peng, Xianku Zhang, and Hui Sun. "Ship Steering Adaptive CGS Control Based on EKF Identification Method." Journal of Marine Science and Engineering 10, no. 2 (February 20, 2022): 294. http://dx.doi.org/10.3390/jmse10020294.
Повний текст джерелаАнотація:
In recent years, marine autonomous surface vessels (MASS) have grown into a ship research issue to increase the level of autonomy of ship behavior decision-making and control while sailing at sea. This paper focuses on the MASS motion control module design that aims to improve the accuracy and reliability of ship steering control systems. Nevertheless, the stochastic sea and wind environment have led to the extensive use of filters and state observers for estimating the ship-motion-related parameters, which are important for ship steering control systems. In particular, the ship maneuverability Nomoto index, which primarily determines the designed ship steering controller’s performance, cannot be observed directly due to the model errors and the external environment disturbance in the process of sailing. Hence, an adaptive robust ship steering controller based on a closed-loop gain shaping (CGS) scheme and an extended Kalman filter (EKF) on-line identification method is explored in this paper. To verify the effectiveness of the proposed steering controller design scheme, the motor vessel YUKUN was taken as the control plant and a series of simulation experiments were carried out. The results show the advantages of the dynamic response performance of the proposed steering controller compared with the classical PD and traditional CGS controllers. Therefore, the proposed adaptive CGS steering controller would be a good solution for MASS motion control module design.
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Prasodjo, Budi S., Kimio Saito, Yasushi Higo, Hisashi Nobukawa, and Katsuya Maeda. "Wave responses of a coastal cargo ship consisting of unit modules." Journal of Marine Science and Technology 11, no. 4 (December 20, 2006): 260–69. http://dx.doi.org/10.1007/s00773-006-0228-3.
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Borkowski, Piotr. "Inference Engine in an Intelligent Ship Course-Keeping System." Computational Intelligence and Neuroscience 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/2561383.
Повний текст джерелаАнотація:
The article presents an original design of an expert system, whose function is to automatically stabilize ship’s course. The focus is put on the inference engine, a mechanism that consists of two functional components. One is responsible for the construction of state space regions, implemented on the basis of properly processed signals recorded by sensors from the input and output of an object. The other component is responsible for generating a control decision based on the knowledge obtained in the first module. The computing experiments described herein prove the effective and correct operation of the proposed system.
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Choi, Hyeung-Sik, Kyoung-Youb Kwon, Koo-Rack Chung, Joo-No Seo, and Hyung-Suk Kang. "Development of Cleaning Module and Operating System of Underwater Robot for Ship Hull Cleaning." Journal of the Korean Society of Marine Engineering 33, no. 4 (May 31, 2009): 553–61. http://dx.doi.org/10.5916/jkosme.2009.33.4.553.
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