• Journal of Advanced Marine Engineering and Technology
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• v.37 no.4
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• pp.409-417
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• 2013

Mu-communication board supported by multi-communication is designed with Atxmega 128A1 which is a low power energy consuming of 8-bit microcontroller. ATxmega128A1 microcontroller consists of 8 UART(Universal asynchronous receiver/transmitter) ports which can be setting appropriate user interface having command line interpreter(CLI) program with each port, 2 kbytes EEPROM, 128 kbytes flash memory, 8 kbytes SRAM. 8 URAT ports are used for the multi communication modem, GPS module, etc. and EEPROM is used for saving a configuration for program running, and flash memory of 128 kbytes is used for storing a Firm Ware, and 8 kbytes SRAM is used for stack, storing memory of global variables while program running. If we uses the hybrid communication of path optimization of VHF, TRS and CDMA to remote control AtoN(aid to navigation), it is able to remove the communication shadow area. Even though there is a shadow area for individual communication method, we can select an optimum communication method. The compatibility of data has been enhanced as using of same data frame per communication devices. For the test, 8640 of data has been collected from the each buoy during 30 days in every 5 minutes and the receiving rate of the data has shown more than 99.4 %.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1294-1300
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• 2010

In an environment where all nodes move, the sensor node receives anchor node's position information within communication radius and modifies the received anchor node's position information by one's traveled distance and direction in saving in one's memory, where if there at least 3, one's position is determined by performing localization through trilateration. The proposed localization mechanisms have been simulated in the Matlab. In an environment where certain distance is maintained and nodes move towards the same direction, the probability for the sensor node to meet at least 3 anchor nodes with absolute coordinates within 1 hub range is remote. Even if the sensor node has estimated its position with at least 3 beacon information, the angle ${\theta}$ error of accelerator and digital compass will continuously apply by the passage of time in enlarging the error tolerance and its estimated position not being relied. Dead reckoning technology is used as a supplementary position tracking navigation technology in places where GPS doesn't operate, where one's position can be estimated by knowing the distance and direction the node has traveled with acceleration sensor and digital compass. The localization algorithm to be explained is a localization technique that uses Dead reckoning where all nodes are loaded with omnidirectional antenna, and assumes that one's traveling distance and direction can be known with accelerator and digital compass. The simulation results show that our scheme performed better than other mechanisms (e.g. MCL, DV-distance).

• Journal of Information Management
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• v.41 no.4
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• pp.187-204
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• 2010

This study shows evaluation of how much OASIS meets "the korean web content accessibility guidelines" and analysis of some of the accessibility problems and their solutions in OASIS(Oriental Medicine Advanced Searching Integrated System) which is the only web site that offers papers and project information related to Traditional Medicine in Korea. The evaluation criteria to determine if OASIS is accessible is classified into four sub items; Perceivable - if information and user interface components is presentable to users in ways they can perceive, Operable - if user interface components and navigation are operable, Understandable - if information and the operation of user interface are understandable, Robust - if content is robust enough that it can be interpreted reliably by a wide variety of user agents, including assistive technologies. Based on the measured results, OASIS has just been redesigned and implemented in more accessible and effective way. OASIS that improves web accessibility for the disabled is expected to help them study oriental medicine more easily and conveniently by providing equal access and equal opportunity to use the web.

• Journal of Korea Port Economic Association
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• v.39 no.3
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• pp.33-46
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• 2023

The Autonomous ships are equipped with a function to judge and navigate the sea conditions on their own, so the job of the ship officer who operates it changes. The educational curriculum to nurture ship officer with the ability to operate and manage autonomous ships must also be changed. This study aimed to develop the curriculum for training autonomous ship officer by using the Delphi survey method suitable for predicting the uncertain future. Among the current 61 subjects for training ship officer identified in the Delphi survey, 32 subjects with high importance should be maintained in the training for autonomous ship officer, and subjects with low importance should be abolished or integrated into other subjects. These subjects were collectively referred to as 'general courses'. The expert panel of the Delphi survey suggested 42 items as new subjects, with 18 items of 'high', 14 items of 'middle', and 10 items of 'low'. Through in-depth analysis of these items by experts, 27 subjects were adjusted and three courses were proposed : 1)'Basic course(10 courses)' for developing basic capabilities such as basic theories for understanding advanced technology and information applied to autonomous ships, 2)'Job course(10 courses)' for practical competency directly related to autonomous ship operation, 3)'Intensive course(7 subjects)' for fostering land remote operators of autonomous ships. Since the introduction and spread of autonomous ships will progress rapidly, research to develop and supplement autonomous ship pilot training courses should be continued by reflecting the level of autonomous navigation of autonomous ships.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1135-1147
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• 2021

In order to geometrically correct high-resolution satellite imagery, the sensor modeling process that restores the geometric relationship between the satellite sensor and the ground surface at the image acquisition time is required. In general, high-resolution satellites provide RPC (Rational Polynomial Coefficient) information, but the vendor-provided RPC includes geometric distortion caused by the position and orientation of the satellite sensor. GCP (Ground Control Point) is generally used to correct the RPC errors. The representative method of acquiring GCP is field survey to obtain accurate ground coordinates. However, it is difficult to find the GCP in the satellite image due to the quality of the image, land cover change, relief displacement, etc. By using image maps acquired from various sensors as reference data, it is possible to automate the collection of GCP through the image matching algorithm. In this study, the RPC of KOMPSAT-3A satellite image was corrected through the extracted matching point using the UAV (Unmanned Aerial Vehichle) imagery. We propose a pre-porocessing method for the extraction of matching points between the UAV imagery and KOMPSAT-3A satellite image. To this end, the characteristics of matching points extracted by independently applying the SURF (Speeded-Up Robust Features) and the phase correlation, which are representative feature-based matching method and area-based matching method, respectively, were compared. The RPC adjustment parameters were calculated using the matching points extracted through each algorithm. In order to verify the performance and usability of the proposed method, it was compared with the GCP-based RPC correction result. The GCP-based method showed an improvement of correction accuracy by 2.14 pixels for the sample and 5.43 pixelsfor the line compared to the vendor-provided RPC. In the proposed method using SURF and phase correlation methods, the accuracy of sample was improved by 0.83 pixels and 1.49 pixels, and that of line wasimproved by 4.81 pixels and 5.19 pixels, respectively, compared to the vendor-provided RPC. Through the experimental results, the proposed method using the UAV imagery presented the possibility as an alternative to the GCP-based method for the RPC correction.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.939-951
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• 2022

The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.