• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.719-720
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• 2006

Ad hoc networks does not need any wired network infrastructure. Therefore, they have been developed in temporary networks or mainly in military networks. Infostations offer geographically intermittent coverage at high speeds. Up-to-date there have been frequent big forest fires in Korea mountain areas. It is very important to detect them early to prevent them from being big disasters. In this paper, we propose a disaster emergency management system using sensor attached wild boars' mobility combined with infostation system. We also make a numerical analysis of the performance of the system.

• Journal of KIBIM
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• v.13 no.1
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• pp.13-21
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• 2023

The purpose of this study is to establish a system that manages the safety of buildings efficiently by finding the correlation of elements related to the safety of buildings and intuitively visualizing them. Data were collected using the data of small-scale buildings managed by public institutions and the government, and an effective analysis visualization environment was established through pre-processing. We selected safety-vulnerable factors such as the structure of the building and completion date to find the relationship, and established a model to prioritize management to find vulnerable buildings.

• International journal of advanced smart convergence
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• v.12 no.1
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• pp.164-172
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• 2023

In this study, we identify the recognition of 'The First Slam Dunk', which is gaining popularity as a sports-based cartoon through big data analysis of social media channels, and provide basic data for the development and development of various contents in the sports industry. Social media channels collected detailed social big data from news provided on Naver and Google sites. Data were collected from January 1, 2023 to February 15, 2023, referring to the release date of 'The First Slam Dunk' in Korea. The collected data were 2,106 Naver news data, and 1,019 Google news data were collected. TF and TF-IDF were analyzed through text mining for these data. Through this, semantic network analysis was conducted for 60 keywords. Big data analysis programs such as Textom and UCINET were used for social big data analysis, and NetDraw was used for visualization. As a result of the study, the keyword with the high frequency in relation to the subject in consideration of TF and TF-IDF appeared 4,079 times as 'The First Slam Dunk' was the keyword with the high frequency among the frequent keywords. Next are 'Slam Dunk', 'Movie', 'Premiere', 'Animation', 'Audience', and 'Box-Office'. Based on these results, 60 high-frequency appearing keywords were extracted. After that, semantic metrics and centrality analysis were conducted. Finally, a total of 6 clusters(competing movie, cartoon, passion, premiere, attention, Box-Office) were formed through CONCOR analysis. Based on this analysis of the semantic network of 'The First Slam Dunk', basic data on the development plan of sports content were provided.

• Proceedings of the Korean Society of Computer Information Conference
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• 2010.07a
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• pp.173-179
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• 2010

Currently, the communication systems are progressing two ways as the wireless and multimedia and these need big transmission capacity then before. In these circumstance, communication services existed as two different service forms which have different rates and characteristics. For example Voice/Video Services accept some errors but transmit on realtime, but Date Services don't need to transmit on realtime but have to retransmit if these have only one bit error. In Voice/Date Integrated traffics, it has big throughput that realtime voice/video data which could have some errors if integrated traffic is increased rapidly have transmission priority, then Data traffics which delay is accepted is sent after that. In this paper, I introduce the calculation method for various traffic when voice/data mixed traffics is transmitted to asynchronous unslotted ALOHA CDMA system proposed and the result is presented. And We can easily theoretical analysis for the system traffic and changing traffic using proposed solution in this paper.

• Journal of Digital Contents Society
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• v.19 no.6
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• pp.1219-1224
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• 2018

Nowaday, smart mobile devices on Internet of Things are required to process and deliver greate amount of data in real-time. Therefore, heterogeneous mult-core architecture such the big.LITTLE core architecture, which shows high energy conservation while guaranteeing high performance, are widely employed on up to date smart mobile devices. The LITTLE cores should be highly utilized to gain higher energy conservation because LITTLE cores have much higher energy efficiency than big cores. In this paper, we propose a core selection algorithm, which tries to firstly assign a real-time task on a LITTLE core rather a big core while the task can be finished within its own deadline. We also perform simulation as performance evaluation to show that our proposed algorithm shows higher energy conservation while guaranteeing the required performance.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.57-62
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• 2014

In this paper, we proposed and implemented a crime pattern analysis algorithm using big data. The proposed algorithm uses crime-related big data collected and published in the supreme prosecutors' office. The algorithm analyzed crime patterns in Seoul city from 2011 to 2013 using the spatial statistics analysis like the standard deviational ellipse and spatial density analysis. Using crime frequency, We calculated the crime probability and danger factors of crime areas, time, date, and places. Through a result we analyzed spatial statistics. As the result of the proposed algorithm, we could grasp differences in crime patterns of Seoul city, and we calculated degree of risk through analysis of crime pattern and danger factor.

• Journal of the Korea Convergence Society
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• v.10 no.8
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• pp.165-170
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• 2019

According to the statistics of the Ministry of Land Transport and Transportation in 2018, the average annual average number of air traffic users for has increased by 5.07% for domestic flights and 8.84% for international flights. Korea is facing a steady rise in demand from foreign tourists due to the Korean Wave. At the same time, a new lifestyle that values the quality of life of individuals is taking root, along with the emergence of LCC, and Korean tourists' overseas tours are also increasing, so improvement and expansion of domestic airport passenger terminals is urgently needed. it is important to develop a structured airport infrastructure by making efficient and accurate forecasts of aviation demand. in this study, based on the Big Data, long-term domestic and international demand forecasts for urban airports were conducted.. Domestic flights will see a decrease in the number of airport passengers after 2028, and international flights will continue to increase. It is imperative to improve and expand passenger terminals at domestic airports.

• Korean Educational Research Journal
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• v.43 no.1
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• pp.1-27
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• 2022

As the COVID-19 virus became prevalent worldwide, non-face-to-face contact was implemented in various ways, and the education system also began to draw much attention due to rapid non-face-to-face contact. The purpose of this study is to analyze the direction of non-face-to-face education in line with the continuously changing educational environment to date. In this study, data were visualized using Textom and Ucinet6 analysis tool programs to collect social network big data with various opinions. As a result of the study, keywords related to "COVID-19" were dominant, and keywords with high frequency such as "article" and "news" existed. As a result of the analysis, various issues related to non-face-to-face education, such as network failures and security issues, were identified. After the analysis, the direction of the non-face-to-face education system was studied according to the growth of the education market and changes in the educational environment. In addition, there is a need to strengthen security and feedback on teaching methods in non-face-to-face education analyzed using big data.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.5
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• pp.748-753
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• 2007

Serum biochemical values were measured in blood samples collected from 8 fasted stags from both jugular and femoral veins at 18-day intervals during antler growth. Samples were analyzed for blood substrate, enzyme activity values, minerals and electrolyte. There were no significant differences in total protein, albumin, urea, creatinine, triglyceride, glucose or cholesterol concentration between veins or sampling dates. However, total-bilirubin concentration in the jugular vein on the casting date was three times higher than on the other sampling dates (p<0.05). There were no significant differences in alkaline phosphatase, aspartate aminotransferase, and alanine aminotransferase with progressing antler growth. The highest level of alkaline phosphatase concentration was on day 55 after casting. There were no significant differences in inorganic phosphorus, sodium and chloride concentration between jugular and femoral samples. Calcium concentration was significantly higher in the femoral vein on the cutting date (55 day) than in the jugular vein (p<0.05). There were few changes in serum biochemical values. However, some electrolytes and minerals had differences during antler growth. It is suggested that despite such a big event as antler growth, blood biochemical values are not variable if feeding conditions are consistently maintained as was the case in this study.

• Journal of Satellite, Information and Communications
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• v.10 no.2
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• pp.40-45
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• 2015

In this paper, we proposed and implemented a crime prediction algorithm based upon crime influential factors. To collect the crime-related big data, we used a data which had been collected and was published in the supreme prosecutors' office. The algorithm analyzed various crime patterns in Seoul from 2011 to 2013 using the spatial statistics analysis. Also, for the crime prediction algorithm, we adopted a Bayesian network. The Bayesian network consist of various spatial, populational and social characteristics. In addition, for the more precise prediction, we also considered date, time, and weather factors. As the result of the proposed algorithm, we could figure out the different crime patterns in Seoul, and confirmed the prediction accuracy of the proposed algorithm.