• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.4
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• pp.489-495
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• 2018

In this paper, we designed and fabricated WLAN / UWB communication antennas operating at 3.3 [GHz] and 5 [GHz] bands in order to effectively use the high-speed communication network system that improved antenna miniaturization, gain and radiation pattern. Microstrip patch antennas were chosen to improve the bandwidth. The slot width, length, and transmission line width were calculated using the theoretical formula for each step. Simulation results show that the return loss is -14.053 [dB] at 3.3 [GHz] and -13.118 [dB] at 5 [GHz]. The gain showed a value of 2.479 [dBi] at 3.3 [GHz] and a value of 3.317 [dBi] at 5 [GHz]. After optimizing it with the CST Microwave Studio 2014 program, which can be 3D-designed, Based on these results, we investigated the performance of antennas by measuring their characteristics. In recent years, WLAN, which is a variety of wireless technologies that are continuously developing, and UWB, which is a communication technology which is increasing in frequency band due to an increase in demand of the technology users, is used for a high speed wireless communication system. Communication seems to be possible.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.574-583
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• 2021

Predicting shipping markets is an important issue. Such predictions form the basis for decisions on investment methods, fleet formation methods, freight rates, etc., which greatly affect the profits and survival of a company. To this end, in this study, we propose a shipping freight rate prediction model for container ships using gated recurrent units (GRUs) and long short-term memory structure. The target of our freight rate prediction is the China Container Freight Index (CCFI), and CCFI data from March 2003 to May 2020 were used for training. The CCFI after June 2020 was first predicted according to each model and then compared and analyzed with the actual CCFI. For the experimental model, a total of six models were designed according to the hyperparameter settings. Additionally, the ARIMA model was included in the experiment for performance comparison with the traditional analysis method. The optimal model was selected based on two evaluation methods. The first evaluation method selects the model with the smallest average value of the root mean square error (RMSE) obtained by repeating each model 10 times. The second method selects the model with the lowest RMSE in all experiments. The experimental results revealed not only the improved accuracy of the deep learning model compared to the traditional time series prediction model, ARIMA, but also the contribution in enhancing the risk management ability of freight fluctuations through deep learning models. On the contrary, in the event of sudden changes in freight owing to the effects of external factors such as the Covid-19 pandemic, the accuracy of the forecasting model reduced. The GRU1 model recorded the lowest RMSE (69.55, 49.35) in both evaluation methods, and it was selected as the optimal model.

• The Journal of Society for e-Business Studies
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• v.24 no.1
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• pp.29-48
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• 2019

Recently, product design innovation to improve user experience has been perceived as a core element of enterprise competitiveness due to the fierce market competition and decrease of the technological gap between companies, but there is insufficient services to support the product experience evaluation of small and medium-sized companies (SMCs). The aim of this study is to develop a web-based product user experience evaluation and certification system supporting product design practices for SMCs. For system interface design, we conducted systematic functional requirement elicitation methods such as user survey, workflow analysis, user task definition, and function definition. Then main functions, information structure, navigation method, and detailed graphic user interfaces were developed with consideration of user interactions and requirements. In particular, it provides the databases for evaluation efficiency to support the evaluation process above a certain level of performance and efficiency, and knowledge databases to utilize in the evaluation and product design improvement. With help of the developed service platform, It is expected that the service platform would enhance SMCs' product development capability with regard to the user experience evaluation by connecting the consulting firms with SMCs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.352-361
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• 2021

An underwater positioning method that can be applied to structures for underwater construction is being developed at the Korea Institute of Ocean Science and Technology. The method uses an extended Kalman filter (EKF) based on an inertial navigation system for precise and continuous position estimation. The observation matrix was configured to be variable in order to apply asynchronous measured sensor data in the correction step of the EKF. A Doppler velocity logger (DVL) can acquire signals only when attached to the bottom of an underwater structure, and it is difficult to install and recover. Therefore, a complex sensor device for underwater structure attachment was developed without a DVL in consideration of an underwater construction environment, installation location, system operation convenience, etc.. Its performance was verified through a water tank test. The results are the measured underwater position using an ultra-short baseline, the estimated position using only a position vector, and the estimated position using position/velocity vectors. The results were compared and evaluated using the circular error probability (CEP). As a result, the CEP of the USBL alone was 0.02 m, the CEP of the position estimation with only the position vector corrected was 3.76 m, and the CEP of the position estimation with the position and velocity vectors corrected was 0.06 m. Through this research, it was confirmed that stable underwater positioning can be carried out using asynchronous sensors without a DVL.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.5
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• pp.780-790
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• 2022

Quantitative risk levels must be presented by analyzing the causes and consequences of accidents and predicting the occurrence patterns of the accidents. For the analysis of marine accidents related to vessel traffic, research on the traffic such as collision risk analysis and navigational path finding has been mainly conducted. The analysis of the occurrence pattern of marine accidents has been presented according to the traditional statistical analysis. This study intends to present a marine accident prediction model using the statistics on marine accidents related to vessel traffic. Statistical data from 1998 to 2021, which can be accumulated by month and hourly data among the Korean domestic marine accidents, were converted into structured time series data. The predictive model was built using a long short-term memory network, which is a representative artificial intelligence model. As a result of verifying the performance of the proposed model through the validation data, the RMSEs were noted to be 52.5471 and 126.5893 in the initial neural network model, and as a result of the updated model with observed datasets, the RMSEs were improved to 31.3680 and 36.3967, respectively. Based on the proposed model, the occurrence pattern of marine accidents could be predicted by learning the features of various marine accidents. In further research, a quantitative presentation of the risk of marine accidents and the development of region-based hazard maps are required.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.11
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• pp.933-940
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• 2017

The modern society is changing paradigm by the 4th industrial revolution. In these changes, the importance of geospatial information leading to the fusion and connection of persons and objects is increasing day by day. GNSS CORS(Continuously Operating Reference Station) plays a pivotal role in the geospatial information by providing basic data for surveying control points, mapping, navigation, geophysical research, and so on. On the other hand, the satellite surveying technologies are developing rapidly and it is necessary to investigate the status of the satellite surveying environment and search for future directions. In this study, the environment related to satellite survey by operation status of domestic and overseas CORS(Continuously Operating Reference Station) was tried to analyze. Through the research, The operation status of NGII and IGS CORS were presented. It was found that the availability ratio of multiple satellites to the CORS of NGII are lower than that of IGS CORS. Considering the improvement of positioning performance by using multiple GNSS, it is necessary to use multi-satellites in the future.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.307-315
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• 2023

Korea controls the departure of vessels based on the Maritime Safety Act such that only ships with seaworthiness can navigate in bad weather, but scientific evaluation results and quantitative basis for the designation of ships subject to control are insufficient. Opinions for improvement are being raised for a reasonable departure control operation. The purpose of this study is to evaluate the adequacy of the current departure control standards through actual measurement of tugboats, which are the type of vessels subject to control when a wind and wave advisory is effective, and to present quantitative grounds for improvement of controls. A sensor was installed on the tugboat to measure the ship's three-axis motion and hull acceleration, and the hull motion performance was measured by operating in the sea area with a significant wave height of 3 m. The measured values were compared and analyzed based on seaworthiness evaluation factors and limit value standards. The actual ship was excluded from the current control standard according to tonnage, but as a result of the analysis, the pitch value exceeded the operation standard, and a risk to navigation safety existed. The results of this study suggest the need for additional actual measurement studies that can represent various ship types and specifications and review ship departure control targets.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.980-991
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• 2023

To prevent accidents near the quay caused by a ship, ports are generally designed and constructed through navigation and berthing safety assessment. However, unpredictable accidents such as ship collisions with the quay or personal accidents caused by ropes still occur sometimes during the ship berthing or mooring process. Automatic mooring systems, which are equipped with an attachment mechanism composed of robotic manipulators and vacuum pads, are designed for rapid and safe mooring of ships. This paper deals with a displacement and velocity measurement system for the automatic mooring device, which is essential for the position and speed control of the vacuum pads. To design a suitable system for an automatic mooring device, we first analyze the sensor's performance and outdoor environmental characteristics. Based on the analysis results, we describe the configuration and design methods of a displacement and velocity measurement system for application in outdoor environments. Additionally, several algorithms for detecting the sensor's state and estimating a ship's velocity are developed. The proposed method is verified through some experiments for displacement and speed measurement targeted at a moving object with constant speed.

• Science of Emotion and Sensibility
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• v.13 no.4
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• pp.613-620
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• 2010

The purpose of this study was to quantitatively evaluate the effects of the secondary task while simulated driving using the variable indicating control of vehicle and smoothness of motion. Fifteen healthy adults having 1~2years driving experience were participated. 9 markers were attached on the subjects' upper(shoulder, elbow, Wrist) and lower(knee, ankle, toe) limbs and all subjects were instructed to keep the 30m distance with the front vehicle running at 80km/hr speed. Sending text message(STM) and searching navigation(SN) were selected as the secondary task. Experiment consisted of driving alone for 1 min and driving with secondary task for 1 min, and was defined driving and cognition blocks respectively. To indicate the effects of secondary task, coefficient of variation of distance between vehicles and lane keeping(APCV and MLCV) and jerk-cost function(JC) were analyzed. APCV was increased by 222.1% in SN block. MLCV was increased by 318.2% in STM and 308.4% in SN. JC were increased at the drivers' elbow, knee, ankle and toe, especially the total mean JC of lower limbs were increased by 218.2% in STM and 294.7% in SN. Conclusively, Performing secondary tasks while driving decreased the smoothness of motion with increased JC and disturbed the control of vehicle with increased APCV and MLCV.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.123-136
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• 2014

Recently, online shopping has further developed as the use of the Internet and a variety of smart mobile devices becomes more prevalent. The increase in the scale of such shopping has led to the creation of many Internet shopping malls. Consequently, there is a tendency for increasingly fierce competition among online retailers, and as a result, many Internet shopping malls are making significant attempts to attract online users to their sites. One such attempt is keyword marketing, whereby a retail site pays a fee to expose its link to potential customers when they insert a specific keyword on an Internet portal site. The price related to each keyword is generally estimated by the keyword's frequency of appearance. However, it is widely accepted that the price of keywords cannot be based solely on their frequency because many keywords may appear frequently but have little relationship to shopping. This implies that it is unreasonable for an online shopping mall to spend a great deal on some keywords simply because people frequently use them. Therefore, from the perspective of shopping malls, a specialized process is required to extract meaningful keywords. Further, the demand for automating this extraction process is increasing because of the drive to improve online sales performance. In this study, we propose a methodology that can automatically extract only shopping-related keywords from the entire set of search keywords used on portal sites. We define a shopping-related keyword as a keyword that is used directly before shopping behaviors. In other words, only search keywords that direct the search results page to shopping-related pages are extracted from among the entire set of search keywords. A comparison is then made between the extracted keywords' rankings and the rankings of the entire set of search keywords. Two types of data are used in our study's experiment: web browsing history from July 1, 2012 to June 30, 2013, and site information. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The original sample dataset contains 150 million transaction logs. First, portal sites are selected, and search keywords in those sites are extracted. Search keywords can be easily extracted by simple parsing. The extracted keywords are ranked according to their frequency. The experiment uses approximately 3.9 million search results from Korea's largest search portal site. As a result, a total of 344,822 search keywords were extracted. Next, by using web browsing history and site information, the shopping-related keywords were taken from the entire set of search keywords. As a result, we obtained 4,709 shopping-related keywords. For performance evaluation, we compared the hit ratios of all the search keywords with the shopping-related keywords. To achieve this, we extracted 80,298 search keywords from several Internet shopping malls and then chose the top 1,000 keywords as a set of true shopping keywords. We measured precision, recall, and F-scores of the entire amount of keywords and the shopping-related keywords. The F-Score was formulated by calculating the harmonic mean of precision and recall. The precision, recall, and F-score of shopping-related keywords derived by the proposed methodology were revealed to be higher than those of the entire number of keywords. This study proposes a scheme that is able to obtain shopping-related keywords in a relatively simple manner. We could easily extract shopping-related keywords simply by examining transactions whose next visit is a shopping mall. The resultant shopping-related keyword set is expected to be a useful asset for many shopping malls that participate in keyword marketing. Moreover, the proposed methodology can be easily applied to the construction of special area-related keywords as well as shopping-related ones.