• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1047-1056
• /
• 2022

Sea ice, frozen sea water, in the Artic is a primary indicator of global warming. Due to its importance to the climate system, shipping-route navigation, and fisheries, Arctic sea ice prediction has gained increased attention in various disciplines. Recent advances in artificial intelligence (AI), motivated by a desire to develop more autonomous and efficient future predictions, have led to the development of new sea ice prediction models as alternatives to conventional numerical and statistical prediction models. This study aims to evaluate the performance of the two-stream convolutional long-and short-term memory (TS-ConvLSTM) AI model, which is designed for learning both global and local characteristics of the Arctic sea ice changes, for the minimum September Arctic sea ice from 2001 to 2021, and to show the possibility for an operational prediction system. Although the TS-ConvLSTM model generally increased the prediction performance as training data increased, predictability for the marginal ice zone, 5-50% concentration, showed a negative trend due to increasing first-year sea ice and warming. Additionally, a comparison of sea ice extent predicted by the TS-ConvLSTM with the median Sea Ice Outlooks (SIOs) submitted to the Sea Ice Prediction Network has been carried out. Unlike the TS-ConvLSTM, the median SIOs did not show notable improvements as time passed (i.e., the amount of training data increased). Although the TS-ConvLSTM model has shown the potential for the operational sea ice prediction system, learning more spatio-temporal patterns in the difficult-to-predict natural environment for the robust prediction system should be considered in future work.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.773-777
• /
• 2009

In recent years, the field of synthesizing voice has been developed rapidly, and the technologies such as reading aloud an email or sound guidance of a car navigation system are used in various scenes of our life. The sound quality is monotonous like reading news. It is preferable for a text such as a novel to be read by the voice that expresses emotions wealthily. Therefore, we have been trying to develop a system reading aloud novels automatically that are expressed clear emotions comparatively such as juvenile literature. At first it is necessary to identify emotions expressed in a sentence in texts in order to make a computer read texts with an emotionally expressive voice. A method on the basis of the meaning interpretation that utilized artificial intelligence technology for a method to specify emotions of texts is thought, but it is very difficult with the current technology. Therefore, we propose a method to determine only emotion every sentence in a novel by a simpler way. This method determines the emotion of a sentence according to an emotion that words such as a verb in a Japanese verb sentence, and an adjective and an adverb in a adjective sentence, have. The emotional characteristics that these words have are prepared beforehand as a emotional words dictionary by us. The emotions used here are seven types: "joy," "sorrow," "anger," "surprise," "terror," "aversion" or "neutral."

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.10a
• /
• pp.178-179
• /
• 2018

Recently, methods of using machine learning in artificial intelligence such as autonomous navigation and speech recognition have been actively studied. Classical image processing methods such as classical boundary detection and pattern recognition have many limitations in order to recognize a specific object or area in a digital image. However, when a machine learning method such as deep-learning is used, Can be obtained. However, basically, a large amount of learning data must be secured for machine learning such as deep-learning. Therefore, it is difficult to apply the machine learning for area classification when the amount of data is very small, such as aerial photographs for environmental analysis. In this study, we apply a transfer-learning technique that can be used when the dataset size of the input image is small and the shape of the input image is not included in the category of the training dataset.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.18-20
• /
• 2021

In order to prevent collision accidents of ships, which has been increasing recently, research on artificial intelligence-based autonomously operated ships (Maritime Autonomous Surface Ship, MASS) is underway. However, most of the studies related to autonomous ships mainly target medium-to-large ships due to the size and cost of the autonomous navigation system, and the sensors used here have a problem in that it is difficult to mount them on small ships. Therefore, this paper provides a path tracking system equipped with GPS and IMU sensors for autonomous operation of small ships. GPS and IMU sensors are utilized to determine the exact position of the vessel, which allows the proposed system to manually control the small vessel model to create a path and then when the small vessel travels the same path. Use the Pure Pursuit algorithm to follow the path. As a result, In this research, it is expected that a lightweight and low-cost sensor can be used to develop an autonomous operation system for small ships at low cost.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.7
• /
• pp.597-606
• /
• 2020

Because the USV(Unmanned Surface Vehicle) is capable of remote control or autonomous navigation at sea, it can secure the superiority of combat power while minimizing human losses in a future combat environment. To plan the technology for the development of USV, the trend analysis of related technology and the selection of promising technology should be preceded, but there has been little research in this area. The purpose of this paper was to measure and evaluate the technology trends quantitatively. For this purpose, this study analyzed the technology trends and selected promising/declining technologies using topic modeling of papers and patent data. As a result of topic modeling, promising technologies include control and navigation, verification/validation, autonomous level, mission module, and application technology, and declining technologies include underwater communication and image processing technology. This study also identified new technology areas that were not included in the existing technology classification, e.g., technology related to research and development of USV, artificial intelligence, launch/recovery, and operation, such as cooperation with manned and unmanned systems. The technology trends and new technology areas identified through this study may be used to derive key technologies related to the development of the USV and establish appropriate R&D policies.

• Journal of Navigation and Port Research
• /
• v.39 no.4
• /
• pp.299-305
• /
• 2015

Modbus is a serial communications protocol, it has since become a practically standard communication protocol, and it is now a commonly available means of connecting industrial electronic devices. Therefore, it can be connected with all devices using Modbus protocol to the measurement and remote control on the ships, buildings, trains, airplanes and etc.. In this paper, we add the Modbus communication protocol to the existing lighting controller sensitivity to enable verification and remote control by external environmental factors, and also introduces a fuzzy inference system was configured by external environmental factors to control LED lighting. External environmental factors of temperature, humidity, illuminance value represented by the LED through a fuzzy control algorithm, the values accepted by the controller through the sensor. Modbus is using the RS485 Serial communication with other devices connected to the temperature, humidity, illumination and LED output status check is possible. In addition, the remote user is changed to enable it is possible to change the RGB values in the desired color change. Produced was confirmed that the LED controller output is based on the temperature, humidity and illumination.

• Journal of Navigation and Port Research
• /
• v.42 no.6
• /
• pp.421-426
• /
• 2018

With regard to LED lighting devices which have currently been commercialized, LED operating sequences are being sold in a fixed state. In such a state, the external environmental factors are not taken into consideration as only the illumination environment application is considered. Currently, it is difficult to create an optimal lighting environment which can adapt to changes in external environmental factors in the ship. Therefore, it was concluded that there is a need to input the external environment value so that the optimal illumination value can be reflected in real time in order to adapt more organically and actively to the change of external environmental factors. In this paper, we used a microprocessor as an integrated management system for environmental data that changes in real time according to existing external environmental factors. In addition, a controller capable of lighting control of RGB LED module by combining fuzzy inference system. For this, a fuzzy control algorithm is designed and a fuzzy control system is constructed. The distance and the illuminance value from the external environment element are input to the sensor, and these values are converted to the optimum illumination value through the fuzzy control algorithm, and are expressed through the dimming control of the RGB LED module and the practical effectiveness of the fuzzy control system is confirmed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2023.05a
• /
• pp.100-103
• /
• 2023

Recently, development of maritime autonomoust surface ships and eco-friendly ships, production and evaluation research considering various marine environments is needed in the field of optimal routes as the demand for accurate and detailed real-time marine environment prediction information expands. An algorithm that can calculate the optimal route while reducing the risk of the marine environment and uncertainty in energy consumption in smart ships was developed in 2 stages. In the first stage, a profile was created by combining marine environmental information with ship location and status information within the Automatic Ship Identification System(AIS). In the second stage, a model was developed that could define the marine environment energy map using the configured profile results, A regression equation was generated by applying Random Forest among machine learning techniques to reflect about 600,000 data. The Random Forest coefficient of determination (R²) was 0.89, showing very high reliability. The Dijikstra shortest path algorithm was applied to the marine environment prediction at June 1 to 3, 2021, and to calculate the optimal safety route and express it on the map. The route calculated by the random forest regression model was streamlined, and the route was derived considering the state of the marine environment prediction information. The concept of route calculation based on real-time marine environment prediction information in this study is expected to be able to calculate a realistic and safe route that reflects the movement tendency of ships, and to be expanded to a range of economic, safety, and eco-friendliness evaluation models in the future.

• Journal of Advanced Navigation Technology
• /
• v.27 no.4
• /
• pp.447-452
• /
• 2023

In this paper, gain enhancement of a double dipole quasi-Yagi antenna using a meanderline array structure was studied. A 4×1 meanderline array structure consisting of a meanderline conductor- shaped unit cell is located above the second dipole of the double dipole quasi-Yagi antenna. It was designed to have gain over 7 dBi in the frequency range between 1.70 and 2.70 GHz in order to compare the performance with the case using a conventional strip director. As a result of comparison, the average gain of the double dipole quasi-yagi antenna with the proposed meander line array structure was larger compared to the case with the conventional strip director. A double dipole quasi-Yagi antenna using the proposed meanderline array structure was fabricated on an FR4 substrate and its characteristics were compared with the simulation results. Experiment results show that the frequency band for a VSWR less than 2 was 1.55-2.82 GHz, and the frequency band for gain over 7 dBi was measured to be 1.54-2.83 GHz. The frequency bandwidth with gain over 7 dBi increased, and average gain also slightly increased, compared to the conventional case using a strip director.

• Journal of Internet Computing and Services
• /
• v.22 no.2
• /
• pp.59-68
• /
• 2021

As artificial intelligence(AI) technologies, which have made rapid growth recently, began to be applied to the marine environment such as ships, there have been active researches on the application of CNN-based models specialized for digital videos. In E-Navigation service, which is combined with various technologies to detect floating objects of clash risk to reduce human errors and prevent fires inside ships, real-time processing is of huge importance. More functions added, however, mean a need for high-performance processes, which raises prices and poses a cost burden on shipowners. This study thus set out to propose a method capable of processing information at a high rate while maintaining the accuracy by applying Quantization techniques of a deep learning model. First, videos were pre-processed fit for the detection of floating matters in the sea to ensure the efficient transmission of video data to the deep learning entry. Secondly, the quantization technique, one of lightweight techniques for a deep learning model, was applied to reduce the usage rate of memory and increase the processing speed. Finally, the proposed deep learning model to which video pre-processing and quantization were applied was applied to various embedded boards to measure its accuracy and processing speed and test its performance. The proposed method was able to reduce the usage of memory capacity four times and improve the processing speed about four to five times while maintaining the old accuracy of recognition.