• Atmosphere
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• v.29 no.1
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• pp.75-86
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• 2019

In this paper, we introduce a novel Climate & Environment Database System (CEDS). The CEDS is developed by the National Institute of Meteorological Sciences (NIMS) to provide easy and efficient user interfaces and storage management of climate model data, so improves work efficiency. In uploading the data/files, the CEDS provides an option to automatically operate the international standard data conversion (CMORization) and the quality assurance (QA) processes for submission of CMIP6 variable data. This option increases the system performance, removes the user mistakes, and increases the level of reliability as it eliminates user operation for the CMORization and QA processes. The uploaded raw files are saved in a NAS storage and the Cassandra database stores the metadata that will be used for efficient data access and storage management. The Metadata is automatically generated when uploading a file, or by the user inputs. With the Metadata, the CEDS supports effective storage management by categorizing data/files. This effective storage management allows easy and fast data access with a higher level of data reliability when requesting with the simple search words by a novice. Moreover, the CEDS supports parallel and distributed computing for increasing overall system performance and balancing the load. This supports the high level of availability as multiple users can use it at the same time with fast system-response. Additionally, it deduplicates redundant data and reduces storage space.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.4
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• pp.341-349
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• 2016

To meet the requirements in the global age, the necessity and importance of global education in the field of education is rapidly increasing. However, according to the viewpoint on global education, a general consensus of its definition and model is not clear yet and the substantial outcome falls short of our expectation due to high cost, low effectiveness, and lack of persistency in the process of global education. Furthermore, there has been little research on global education for fostering global capabilities of pre-teachers. In this research, we compared and analyzed the ongoing global education programs for training global teachers in domestic universities. Also, through a study on IT fusion education system for tackling the difficulties in global education, we examined appropriate IT fusion education methods. In particular, beased on big data analysis techniques, we presented a recommendation system to complete a global curriculum, which can help a dual-degree or exchange student program.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.221-227
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• 2014

This paper presented a design which was a minimized remote control robot. This remote control robot was created for preventing life damage from conflagrations, nuclear events and HF gas accidents. This robot's system based smart phone that had camera and GPS systems. When fire came out, The robot figured out that how big fire was, where the fire was started and various aspects of situations. And The robot broadcasted the informations to smart phone using mobile application and wi-fi camera. By doing these, the fire mans could more accurate and be easier to plan a strategy for saving life. The body of robot are 2 parts. One is a car and the other one is a remote controller. By the power, 1step to 10steps, of grabbing remote controller could change the car's speed to move. Also, The prototype robot was already confirmed its utility itself.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.6
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• pp.203-209
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• 2017

Low birth rates and aging problems are raising a big issue in the worldwide. Recently, Korea also has no one to caring children who have low discernment and old ones who have Alzheimer's disease because of growing nuclear families and dual income furnitures. Therefore many serious crimes like kidnappings were occurred by people who have mental problems or bad intentions. Even though missing and ding alone are increasing together. The result of it, the needs of potable GPS system, to tracking for the olds and week ones, is highly growing nowadays. This paper introduce producing prototype tracker, looks like fashion accessories, which is using GPS, Zigbee and WiFi. It expects developing many accessory types of trackers effectively helps protect children and old ones from kidnappers at a low cost in this aging society.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1123-1130
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• 2020

This study aims to classify the severity in car crashes using five classification learning models. The dataset used in this study contains 21,013 vehicle crashes, obtained from Korea Expressway Corporation, between the year of 2015-2017 and the LightGBM(Light Gradient Boosting Model) performed well with the highest accuracy. LightGBM, the number of involved vehicles, type of accident, incident location, incident lane type, types of accidents, types of vehicles involved in accidents were shown as priority factors. Based on the results of this model, the establishment of a management strategy for response of highway traffic accident should be presented through a consistent prediction process of accident severity level. This study identifies applicability of Machine Learning Models for Predicting of the Severity of Car Traffic Accidents on a Highway and suggests that various machine learning techniques based on big data that can be used in the future.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.99-105
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• 2023

In the 4th industrial revolution, the field of criminal justice is paying attention to Legaltech using artificial intelligence to provide efficient legal services. This paper attempted to create a crime prediction model that can apply Recurrent Neural Network(RNN) to increase the potential for using legal technology in the domestic criminal justice field. To this end, the crime process was divided into pre, during, and post stages based on the criminal facts described in the judgment, utilizing crime script analysis techniques. In addition, at each time point, the method and evidence of crime were classified into objects, actions, and environments based on the sentence composition elements and the 8 principles of investigation. The case summary analysis framework derived from this study can contribute to establishing situational crime prevention strategies because it is easy to identify typical patterns of specific crime methods. Furthermore, the results of this study can be used as a useful reference for research on generating crime situation prediction data based on RNN models in future follow-up studies.

• Korean Journal of Heritage: History & Science
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• v.57 no.1
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• pp.6-19
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• 2024

The Korean Archaeological Dictionary, which represents Korean archaeological knowledge information, contains refined and high-quality information written by expert collective intelligence. This is a characteristic that clearly distinguishes it from overseas archaeological data archives, and can be called differentiated infrastructure data. However, it has not played a role as an information service or knowledge information platform reflecting the latest digital technology. As a way to maximize these strengths and compensate for weaknesses, it was proposed to develop and operate a GIS-based knowledge and information platform for Korean archaeology. To realize this, it is necessary to develop a title management system centered on repositories and metadata that can collect and store various information, link open linked data design and related systems, develop a search function that can analyze and visualize data in response to the big data era, and establish a WebGIS-based information service system. This will be a platform to continuously manage, supplement, and update Korean archaeological knowledge information, build a ubiquitous environment where anyone can use information anytime, anywhere, and create various types of business models.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.539-545
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• 2018

In recent years, research on shipping market forecasting with the employment of non-linear AI models has attracted significant interest. In previous studies, input variables were selected with reference to past papers or by relying on the intuitions of the researchers. This paper attempts to address this issue by applying the stepwise regression model and the random forest model to the Cape-size bulk carrier market. The Cape market was selected due to the simplicity of its supply and demand structure. The preliminary selection of the determinants resulted in 16 variables. In the next stage, 8 features from the stepwise regression model and 10 features from the random forest model were screened as important determinants. The chosen variables were used to test both models. Based on the analysis of the models, it was observed that the random forest model outperforms the stepwise regression model. This research is significant because it provides a scientific basis which can be used to find the determinants in shipping market forecasting, and utilize a machine-learning model in the process. The results of this research can be used to enhance the decisions of chartering desks by offering a guideline for market analysis.

• The Mathematical Education
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• v.61 no.2
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• pp.257-271
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• 2022

As information and communication technologies are being developed so rapidly, education research is actively conducted to provide optimal learning for each student using big data and artificial intelligence technology. In this study, using the mathematics learning data of elementary school 5th to 6th graders conducting blended mathematics classes, we tried to find out what factors predict mathematics academic achievement and developed an artificial intelligence model that predicts mathematics academic performance using the results. Math learning propensity, LMS data, and evaluation results of 205 elementary school students had analyzed with a random forest model. Confidence, anxiety, interest, self-management, and confidence in math learning strategy were included as mathematics learning disposition. The progress rate, number of learning times, and learning time of the e-learning site were collected as LMS data. For evaluation data, results of diagnostic test and unit test were used. As a result of the analysis it was found that the mathematics learning strategy was the most important factor in predicting low-achieving students among mathematics learning propensities. The LMS training data had a negligible effect on the prediction. This study suggests that an AI model can predict low-achieving students with learning data generated in a blended math class. In addition, it is expected that the results of the analysis will provide specific information for teachers to evaluate and give feedback to students.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.6
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• pp.999-1011
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• 2008

To most of the students studying fashion related major, the graduation fashion show is a big challenge. They have to put together all they learn and show what they can do to their future employers. They design, pattern work, and make up garments for the show all by themselves. Unfortunately. while they make up their garments, they usually don't Dow exactly body measurements of the models. So quite often they have to alter their art works up to the last minute of the fashion show opening. Sometimes such unadequate work process ruins their work. The purpose of this study is to suggest block patterns of Korean fashion models measurements for basic items, such as jacket and pants for male models and torso length block pattern, skirt and pants for female models. 20 male and 20 female professional models were measured. The block patterns were based on their measurements. After the first fitting test, patterns were corrected by their body characteristic. For both male and female models, it was found desirable to fix the shoulder width and make an adjustment to the patterns with a deviation of width and girth items. In case of the resultant patterns the satisfaction was made better. Model sizes proposed in this study are considered closer to the size of average models, since they were based on A-grade models who are currently working in Korea. The resultant patterns can be produced by simply making a slight adjustment to the width of the proposed pattern in this study.