• KIPS Transactions on Computer and Communication Systems
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• v.10 no.4
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• pp.117-122
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• 2021

In recent years, human damage and loss of money due to various disasters such as typhoons, earthquakes, forest fires, landslides, and wars are steadily occurring, and a lot of manpower and funds are required to prevent and recover them. In this paper, we designed and developed a disaster drone system based on artificial intelligence in order to monitor these various disaster situations in advance and to quickly recognize and respond to disaster occurrence. In this study, multiple disaster drones are used in areas where it is difficult for humans to monitor, and each drone performs an efficient search with an optimal path by applying a deep learning-based optimal path algorithm. In addition, in order to solve the problem of insufficient battery capacity, which is a fundamental problem of drones, the optimal route of each drone is determined using Ant Colony Optimization (ACO) technology. In order to implement the proposed system, it was applied to a forest fire situation among various disaster situations, and a forest fire map was created based on the transmitted data, and a forest fire map was visually shown to the fire fighters dispatched by a drone equipped with a beam projector. In the proposed system, multiple drones can detect a disaster situation in a short time by simultaneously performing optimal path search and object recognition. Based on this research, it can be used to build disaster drone infrastructure, search for victims (sea, mountain, jungle), self-extinguishing fire using drones, and security drones.

• Knowledge Management Research
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• v.22 no.4
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• pp.27-40
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• 2021

Click-Through Rate (CTR) prediction is a key function that determines the ranking of candidate items in the recommendation system and recommends high-ranking items to reduce customer information overload and achieve profit maximization through sales promotion. The fields of natural language processing and image classification are achieving remarkable growth through the use of deep neural networks. Recently, a transformer model based on an attention mechanism, differentiated from the mainstream models in the fields of natural language processing and image classification, has been proposed to achieve state-of-the-art in this field. In this study, we present a method for improving the performance of a transformer model for CTR prediction. In order to analyze the effect of discrete and categorical CTR data characteristics different from natural language and image data on performance, experiments on embedding regularization and transformer normalization are performed. According to the experimental results, it was confirmed that the prediction performance of the transformer was significantly improved when the L2 generalization was applied in the embedding process for CTR data input processing and when batch normalization was applied instead of layer normalization, which is the default regularization method, to the transformer model.

• The Journal of Sustainable Design and Educational Environment Research
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• v.20 no.4
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• pp.13-20
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• 2021

In the world, each country is preparing various policies to promote start-ups, and the Korean government is actively promoting policies to support start-ups and the national economy through technology-based start-ups for creating jobs. Recently, the number of start-up companies is on the rise. In particular, in accordance with the industrial structure transformation leading the 4th Industrial Revolution, technology-based start-ups are steadily growing based on knowledge-based services such as information and communication, science and technology service industry, and business support service industry. The purpose of this study is to find out whether the startup space provided by the university reflects the startup-friendly characteristics, and to investigate and analyze the satisfaction and requirements of the space required by the actual college campus startup space users to create a more efficient space configuration plan. Through this study, factors that should be considered first for universities in preparing startup spaces were derived for each space element. Therefore, it is necessary for university campuses to deeply recognize the importance of space provision among the future start-up support systems, and to improve them periodically through the consumers' satisfaction of the space in the construction and improvement of startup spaces.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.7
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• pp.233-240
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• 2022

Most of the recent AI researches has focused on developing AI models. However, recently, artificial intelligence research has gradually changed from model-centric to data-centric, and the importance of learning data is getting a lot of attention based on this trend. However, it takes a lot of time and effort because the preparation of learning data takes up a significant part of the entire process, and the generation of labeling data also differs depending on the purpose of development. Therefore, it is need to develop a tool with various labeling functions to solve the existing unmetneeds. In this paper, we describe a labeling system for creating precise and fast labeling data of medical images. To implement this, a semi-automatic method using Back Projection, Grabcut techniques and an automatic method predicted through a machine learning model were implemented. We not only showed the advantage of running time for the generation of labeling data of the proposed system, but also showed superiority through comparative evaluation of accuracy. In addition, by analyzing the image data set of about 1,000 patients, meaningful diagnostic indexes were presented for men and women in the diagnosis of sarcopenia.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.349-357
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• 2021

Recently, drones are rapidly becoming common and expanding. There is a great need for diversity in whether drone flight data can be used as entertainment technology analysis data. In particular, it is necessary to check whether it is possible to analyze and utilize the flight and operation process of entertainment drones, which are developing through autonomous and intelligent methods, through data analysis and machine learning. In this paper, it was confirmed whether it can be used as a machine learning technology by using FC data in the evaluation of drones for entertainment. As a result, FC data from DJI and Parrot such as Mavic2 and Anafi were unable to analyze machine learning for entertainment. It is because data is collected at intervals of 0.1 second or more, so that it is impossible to find correlation with other data with GCS. On the other hand, it was found that machine learning technologies can be applied in the case of Fixhawk, which used an ARM processor and operates with the Nuttx OS. In the future, it is necessary to develop technologies capable of analyzing the characteristics of entertainment by dividing fixed-wing and rotary-wing flight information. For this, a model shoud be developed, and systematic big data collection and research should be conducted.

• Iberoamérica
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• v.22 no.2
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• pp.25-57
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• 2020

Eduardo Galeano is a left-wing intellectual who led the criticism and accusations of dictatorship and social absurdity in Latin America. It digs into the truth of hidden history that has not been revealed in official history. He values the memory of history to stop repetition of the unfortunate history of the past. The main research topic of this study, 『The Book of Embraces』, is also an extension of such work. Most of the stories in this work depend on the writer's memory. There is no coherence or integration in the content of the story, and the length of the text is not constant, so it is extremely informal and fragmented. This is a strategy to formally reveal the illogical and irrational reality of Latin America. He analyzes the problems of the separation system prevalent in Latin American society from various perspectives. It separates me and the others as well as the past and the present. It makes the memory of history void and paralyzes the consciousness of history. These systems are fixed for convenient governance. In this situation, the pattern of violence becomes more explicit and broad. The anxiety and fear of the Latin American public become commonplace. It is a reality of enduring daily life without hope. Galeano finds this enduring force in historical memory. He believes that when the past and the present meet and embrace, a new history of the future can be encountered. Galeano does not just criticize reality or cynical attitude but also suggests hope for the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.201-217
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• 2022

The United States is one of the largest producers of major crops such as wheat, maize, and soybeans, and is a major exporter of these crops. Therefore, it is important to estimate the crop production of the country in advance based on reliable long- term weather forecast information for stable crops supply and demand in Korea. The purpose of this study is to improve the seasonal predictability of the agro-climatic indices over the United States by using regional-scale daily temperature. For long-term numerical weather prediction, a dynamical downscaling is performed using Weather Research and Forecasting (WRF) model, a regional climate model. As the initial and lateral boundary conditions of WRF, the global hourly prediction data obtained from the Pusan National University Coupled General Circulation Model (PNU CGCM) are used. The integration of WRF is performed for 22 years (2000-2021) for period from June to December of each year. The empirical quantile mapping, one of the bias correction methods, is applied to the timeseries of downscaled daily mean, minimum, and maximum temperature to correct the model biases. The uncorrected and corrected datasets are referred WRF_UC and WRF_C, respectively in this study. The daily minimum (maximum) temperature obtained from WRF_UC presents warm (cold) biases over most of the United States, which can be attributed to the underestimated the low (high) temperature range. The results show that WRF_C simulates closer to the observed temperature than WRF_UC, which lead to improve the long- term predictability of the temperature- based agro-climatic indices.

• KNOM Review
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• v.23 no.2
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• pp.18-28
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• 2020

With the development of the virtual community, the benefits that IT technology provides to people in fields such as healthcare, industry, communication, and culture are increasing, and the quality of life is also improving. Accordingly, there are various malicious attacks targeting the developed network environment. Firewalls and intrusion detection systems exist to detect these attacks in advance, but there is a limit to detecting malicious attacks that are evolving day by day. In order to solve this problem, intrusion detection research using machine learning is being actively conducted, but false positives and false negatives are occurring due to imbalance of the learning dataset. In this paper, a Random Oversampling method is used to solve the unbalance problem of the UNSW-NB15 dataset used for network intrusion detection. And through experiments, we compared and analyzed the accuracy, precision, recall, F1-score, training and prediction time, and hardware resource consumption of the models. Based on this study using the Random Oversampling method, we develop a more efficient network intrusion detection model study using other methods and high-performance models that can solve the unbalanced data problem.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.3
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• pp.343-350
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• 2022

High-resolution data are needed to understand water body mixing patterns at river junctions. In particular, in river analysis, hydrological and water quality characteristics are used as basic data for aquatic ecological health, so observation through continuous monitoring is necessary. In addition, since measurement is carried out through a one-dimensional and fixed measurement method in existing monitoring systems, a hydrological and water quality characteristics investigation of an entire river, except for in the immediate vicinity of the measurement point, is not undertaken. In order to obtain high-resolution measurement data, a measurer has to consider multiple factors, and the area or time that can be measured is limited. Although the resolution might be lowered, an appropriate interpolation method must be selected in order to acquire a wide range of data. Therefore, in this study, a high-elevation measurement method at a river junction was introduced, and the interpolation method according to the measurement results was compared. The overall hydraulic and water quality information of the river was indicated through the visualization of the prediction and interpolation method in the low-resolution measurement result. By comparing each interpolation method, Inverse Distance Weighting, Natural Neighbor, and Kriging techniques were applied in river mapping to improve the precision of river mapping through visualized data and quantitative evaluation. It is thought that this study will offer a new method for measuring rivers through spatial interpolation.

• Korean Journal of Clinical Laboratory Science
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• v.54 no.4
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• pp.285-292
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• 2022

The education and training system, the ISCO (International Standard Classification of Occupations), and the legal systems of Japan and the United States consider all ophthalmic optometry laboratory personnel as ophthalmologists. They encompass optometrists, orthoptists, optometric technicians, and ophthalmic medical technicians. Data retrieved from the KOSIS (Korean Statistical Information Service) revealed that the number of opticians associated with the department of ophthalmology in 2022 could be appraised by classifying their medical institutions; contrarily, the number of clinical laboratory technologists could not be assessed. However, the current research investigated a general tertiary hospital and determined that clinical laboratory technologists outnumber opticians. Classification in Korea is based on ophthalmic optometry laboratory personnel, ISCO, ISCED (International Standard Classification of Education), the medical service act, the act on medical service technologists, and the higher education act. These results cannot be compared to the optometrists evaluated in the United States. Ophthalmology is a suitable profession for optometric technologists and technicians who perform under the instructions of ophthalmologists and optometrists. The field of eye healthcare would be benefitted by assigning the management based on their qualification according to the requirement of the job title, such as 'Clinical Optometry Technologist' to be given to clinical laboratory technologists and opticians who work in the ophthalmic optometry laboratories after obtaining a private qualification endowed by the Korean Ophthalmological Society and the Korean Optometry Society.