• Korean Journal of Remote Sensing
• /
• v.38 no.6_4
• /
• pp.1901-1910
• /
• 2022

Arriving in the new space age, securing technology for fusion application of KOMPSAT-3·3A and global satellite images is becoming more important. In general, multi-sensor satellite images have relative geometric errors due to various external factors at the time of acquisition, degrading the quality of the satellite image outputs. Therefore, we propose a fine-image registration methodology to minimize the relative geometric error between KOMPSAT-3·3A and global satellite images. After selecting the overlapping area between the KOMPSAT-3·3A and foreign satellite images, the spatial resolution between the two images is unified. Subsequently, tie-points are extracted using a hybrid matching method in which feature- and area-based matching methods are combined. Then, fine-image registration is performed through iterative registration based on pyramid images. To evaluate the performance and accuracy of the proposed method, we used KOMPSAT-3·3A, Sentinel-2A, and PlanetScope satellite images acquired over Daejeon city, South Korea. As a result, the average RMSE of the accuracy of the proposed method was derived as 1.2 and 3.59 pixels in Sentinel-2A and PlanetScope images, respectively. Consequently, it is considered that fine-image registration between multi-sensor satellite images can be effectively performed using the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.10
• /
• pp.1423-1431
• /
• 2022

Volatility is one of the variables that the Black-Scholes model requires for option pricing. It is an unknown variable at the present time, however, since the option price can be observed in the market, implied volatility can be derived from the price of an option at any given point in time and can represent the market's expectation of future volatility. Although volatility in the Black-Scholes model is constant, when calculating implied volatility, it is common to observe a volatility smile which shows that the implied volatility is different depending on the strike prices. We implement supervised learning to target implied volatility by adding V-KOSPI to ease volatility smile. We examine the estimation performance of KOSPI200 index options' implied volatility using various Machine Learning algorithms such as Linear Regression, Tree, Support Vector Machine, KNN and Deep Neural Network. The training accuracy was the highest(99.9%) in Decision Tree model and test accuracy was the highest(96.9%) in Random Forest model.

• Journal of the Korean Society for Library and Information Science
• /
• v.56 no.3
• /
• pp.241-264
• /
• 2022

Bibliographic metadata can help researchers effectively utilize essential publications that they need and grasp academic trends of their own fields. With the manual creation of the metadata costly and time-consuming. it is nontrivial to effectively automatize the metadata construction using rule-based methods due to the immoderate variety of the article forms and styles according to publishers and academic societies. Therefore, this study proposes a two-step extraction process based on rules and deep neural networks for generating bibliographic metadata of scientific articlles to overcome the difficulties above. The extraction target areas in articles were identified by using a deep neural network-based model, and then the details in the areas were analyzed and sub-divided into relevant metadata elements. IThe proposed model also includes a model for generating reference summary information, which is able to separate the end of the text and the starting point of a reference, and to extract individual references by essential rule set, and to identify all the bibliographic items in each reference by a deep neural network. In addition, in order to confirm the possibility of a model that generates the bibliographic information of academic papers without pre- and post-processing, we conducted an in-depth comparative experiment with various settings and configurations. As a result of the experiment, the method proposed in this paper showed higher performance.

• Applied Chemistry for Engineering
• /
• v.33 no.5
• /
• pp.459-465
• /
• 2022

A pitch coating method was proposed for the purpose of improving the electrochemical properties of natural graphite. The synthesis conditions of pitch coating were optimized via measuring electrochemical properties of pitch-coated graphite anodes. As the synthesis temperature increased, the thermal stability was improved in addition to an increase in the softening point and residual carbon weight. However, the synthesis temperature of 430 ℃ resulted in the synthesis of a large amount of NI (NMP Insoluble) due to excessive condensation reaction. As the surface uniformity and coating thickness increased due to high thermal stability, the initial coulombic efficiency and rate capability of the pitch-coated graphite were improved. However, the graphite coated with the pitch containing excessive NI showed lower electrochemical properties than the uncoated graphite. NI had low dispersibility and formed spheres after heat treatment, so it formed the heterogeneous and thicker SEI layer. The optimum conditions for forming a uniform surface and an appropriate coating layer were investigated.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.27 no.2
• /
• pp.266-274
• /
• 2021

Ship officers are subject to excessive job stress, which has negative physical and psychological impacts and may adversely affect the smooth supply and demand of human resources. In this study, a mobile web application was developed as a tool for systematic job stress measurement and management of officers and verified through quality evaluation. Requirement analysis was performed by ship officers and staff in charge of human resources of shipping companies, and the results were reflected in the application configuration step. The application was designed according to the waterfall model, which is a traditional software development method, and functions were implemented using JSP and Spring Framework. Performance evaluation on the user interface, confirmed that proper input and output results were implemented, and the respondent results and the database were configured in the administrator interface. The results of evaluation questionnaires for quality evaluation of the interface based on ISO/IEC 9126-2 metric were significant 4.60 for the user interface and 4.65 for the administrator interface in a 5-point scale. In the future, it is necessary to conduct follow-up research on the development of data analysis system through utilization of the collected big-data sets.

• Korean small business review
• /
• v.42 no.4
• /
• pp.251-283
• /
• 2020

The purpose of this study is to provide assistance to the establishment of related policies to improve the level of acceptance and use of smart factories for SMEs in Korea. To this end, the Unified Technology Acceptance Model (UTAUT) was extended to select additional factors that could affect the intention to accept technology, and to demonstrate this. To achieve the research objective, a questionnaire composed of 7-point Likert scales was prepared, and a survey was conducted for manufacturing-related companies. A total of 136 questionnaires were used for statistical processing. As a result of the hypothesis test, performance expectation and social influence had a positive (+) positive effect on voluntary use, but effort expectation and promotion conditions did not have a significant effect. As an extension factor, the network effect and organizational characteristics had a positive (+) effect, and the innovation resistance had a negative effect (-), but the perceived risk had no significant effect. When the size of the company is large, the perceived risk and innovation resistance are low, and the level of influencing factors for veterinary intentions, veterinary intentions, and veterinary behaviors are excluded. Through this study, factors that could have a positive and negative effect on the adoption (reduction) of smart factory-related technologies were identified and factors to be improved and factors to be reduced were suggested. As a result, this study suggests that smart factory-related technologies should be accepted.

• Journal of Korea Entertainment Industry Association
• /
• v.14 no.1
• /
• pp.117-124
• /
• 2020

Chinese youth films fall into the dilemma of continuous development after experiencing rapid development from 2013 to 2017. How to update the creative ideas and methods of the films, arouse the audience's interest in watching and stimulate a new aesthetic experience has become a focal point for the creators who concern about the Chinese film market. "Us and Them" is a successful youth film in 2018. Its creative practice proves that defamiliarization can provide theoretical and methodological basis for the creation of Chinese youth films. Therefore, taking the current situation of Chinese youth film as the research background, treating "Us and Them" as the research object, the defamiliarization of narrative discourse and narrative content used in the film are analyzed. First, the defamiliarization of narrative discourse composed of scenes, characters and plots makes the film "stand out" from the real world. Second, the defamiliarization of narrative content composed of metropolis adoration, self-identity and hometown affection makes the film "stand out" from the existing context. These methods of creation not only meet the needs of the contemporary, but also provide an effective reference for the creation of other youth films. Research will be needed to utilize the elements of defamiliarization through the analysis of the successful case in spite of the time change.

• Journal of Korean Neurosurgical Society
• /
• v.65 no.5
• /
• pp.751-757
• /
• 2022

Objective : Tumours of the brain are a rare occurrence accounting for approximately 2% of all neoplasms in adults. Few studies have been done in Nigeria on the profile of brain tumours. The aim of this study is to determine the profile of brain tumours in general and determine the change in Kanofsky Performance Score (KPS) after treatment. Methods : This is a prospective hospital-based study in Kaduna. All consecutive patients over 18 years of age with diagnosis of brain tumours from January 2016 to December 2019 were included in the study. Demographic and clinical data was collected using a proforma during the study. Patients who received treatment were followed up for 12 months. The primary outcome data was the difference in the quality of life as measured by KPS at the point of first contact and at 1-month after treatment and at 12-month follow up. Data obtained was analysed with SPSS version 25.0 for Windows. Descriptive statistics was done to determine the profile. Paired t-test at 95% confidence interval was done to check for significant correlation between the mean KPS. Results : A total of 39 consecutive patients were included in the study. There was a slight male preponderance with a M : F of 1.17 : 1. Meningioma and metastasis were more common in females while gliomas and pituitary tumours were more common in males. The mean age of patients was 49.8 years and standard deviation of 11.8 years. Pituitary tumours were the most common tumours. The most common location of the tumour was frontal lobe followed by the pituitary gland. The mean duration of symptoms before neurosurgical consultation was 38 weeks. The most common presenting symptoms of patient with brain tumour was headache. The quality of life improve compare to the baseline in 81% of patient at discharge and at 1 year follow up. The overall mortality rate was 25.6%. Conclusion : The most common brain tumour in our study is pituitary tumour. Most patients present late. The most common presenting symptoms is headache. There is significant improvement in the KPS of patients following treatment. The overall mortality rate at 1-year post treatment is 25.6%.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.22 no.4
• /
• pp.87-94
• /
• 2022

This paper researched a study to find a combination of acquisition scores for 9 dart throws, which is the minimum number of dart tactile throws in 501 point dart games. The maximum score that can be obtained by throwing once in a dart game is 60 points, which can end the perfect dart game with 60 points eight times according to 60×8+21×1=501, and if you earn 21 points once, you can finish the game with 9 throws. This is called 9-dart finish. As such, only 18 and 14 studies on the combination of scores that can obtain 501 points with 9 throws are known, and no studies have been conducted applying the exhaustive search algorithm. This paper proposed a division branch-and-bound algorithm as a method of simplifying the O(2ⁿ) exponential time performance complexity of the typical branch-and-bound method of a exhaustive search method, to polynomial time complexity. The proposed method limited the level to 8, jumped to a quotient level of 501/60, and backtracked to explore only possible score combinations in the previous level. The possible score combinations of the nine perfect games found with the proposed algorithm were 90(101 cases).

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.15 no.2
• /
• pp.152-163
• /
• 2022

In this paper, we present a method to enable an unmanned aerial vehicle to drop the sonobuoy, an essential element of anti-submarine warfare, in an optimal deployment. To this end, an environment simulating the distribution of sound detection performance was configured through the Unity game engine, and the environment directly configured using Unity ML-Agents and the reinforcement learning algorithm written in Python from the outside communicated with each other and learned. In particular, reinforcement learning is introduced to prevent the accumulation of wrong actions and affect learning, and to secure the maximum detection area for the sonobuoy while the vehicle flies to the target point in the shortest time. The optimal placement of the sonobuoy was achieved by applying the Deep Deterministic Policy Gradient (DDPG) algorithm. As a result of the learning, the agent flew through the sea area and passed only the points to achieve the optimal placement among the 70 target candidates. This means that an autonomous aerial vehicle that deploys a sonobuoy in the shortest time and maximum detection area, which is the requirement for optimal placement, has been implemented.