• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.133-139
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• 2022

Recently, livestock farms in Korea are introducing data-based technologies to improve productivity, such as livestock environment and breeding management, safe livestock production, and animal welfare. In addition, the government has been conducting a smart livestock distribution project since 2017 through the modernization of ICT-based livestock facilities in order to improve the productivity of livestock products and improve the livestock environment as a policy. However, the current smart livestock house has limitations in connection, diversity, and integration between monitoring and control. Therefore, in order to intelligently systemize all processes of livestock with intelligent algorithms and remote control in order to link and integrate various monitoring and control, the Internet of Things, big data, artificial intelligence, cloud computing, and mobile It is necessary to develop a smart livestock system. In this study, domestic and foreign research trends related to smart livestock based on intelligent information technology were introduced and the limitations of domestic application of advanced technologies were analyzed. Finally, future intelligent information technology applicable to the livestock field was examined.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1259-1265
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• 2022

Recently, AI, big data, and IoT technologies are being used in various solutions such as fire detection and gas or dangerous substance detection for safety accident prevention. According to the status of occupational accidents published by the Ministry of Employment and Labor in 2021, the accident rate, the number of injured, and the number of deaths have increased compared to 2020. In this paper, referring to the dataset construction guidelines provided by the National Intelligence Service Agency(NIA), the dataset is directly collected from the field and learned with YOLOv4 to propose a collision risk object detection system through object detection. The accuracy of the dangerous situation rule violation was 88% indoors and 92% outdoors. Through this system, it is thought that it will be possible to analyze safety accidents that occur in industrial sites in advance and use them to intelligent platforms research.

• Journal of Broadcast Engineering
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• v.27 no.4
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• pp.581-592
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• 2022

Recently, as the requirements for using big data have increased, interest in dataset search technology needed for data analysis is also growing. Although it is necessary to proactively utilize metadata, unlike conventional text search, research on such dataset search systems has not been actively carried out. In this paper, we propose a new dataset-tailored search system that indexes metadata of datasets and performs dataset search based on metadata indices. The ranking given to the dataset search results from a newly devised algorithm that reflects the unique characteristics of the dataset. The system provides the capability to search for additional datasets which correlate with the dataset searched by the user-submitted query so that multiple datasets needed for analysis can be found at once.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.745-750
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• 2021

In Big data visualization analysis of unstructured text data, raw data is mostly large-capacity, and analysis techniques cannot be applied without cleansing it unstructured. Therefore, from the collected raw data, unnecessary data is removed through the first heuristic cleansing process and Stopwords are removed through the second machine cleansing process. Then, the frequency of the vocabulary is calculated, visualized using the word cloud technique, and key issues are extracted and informationalized, and the results are analyzed. In this study, we propose a new Stopword cleansing technique using an external Stopword set (DB) in Python word cloud, and derive the problems and effectiveness of this technique through practical case analysis. And, through this verification result, the utility of the practical application of word cloud analysis applying the proposed cleansing technique is presented.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.21-28
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• 2009

In the past, most of battle occurred in flatland and simple military force size gave a big influence in combat result. However, after the World War I, most of battles took place at the various terrain features such as forest, downtown, jungle and many others. Therefore, terrain factor exerts big influence on battle with weapon system in the ground warfare. However, effect of terrain has been explained only by quantitative manner in the battle. Furthermore, combat simulation and modeling applied a method that lower the combat capability of battle factors. In this paper, we present instrumentation that evaluate impact of terrain using fractal dimension. We determine the fractal dimension value by the "box counting dDimension" and density to calculate impact of terrain. Furthermore, we analyzed correlation with fractal dimension and density for battle result that obtained from the EINSTein model which is an agent-based simulation. We compare with 'Stalingrad battle' result out of battle example and analyzed. This study presented a method combat effectiveness that effect of terrain calculate quantitatively using fractal dimension.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.65-76
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• 2023

This paper identifies the aspects of living environment elements (PM^2.5, PM¹⁰, Noise) throughout Seoul and the urban characteristics that affect them by utilizing the big data of the S-Dot sensors in Seoul, which has recently become a hot topic. In other words, it proposes a big data based urban computing research methodology and research direction to confirm the relationship between urban characteristics and living environments that directly affect citizens. The temporal range is from 2020 to 2021, which is the available range of time series data for S-Dot sensors, and the spatial range is throughout Seoul by 500mX500m GRID. First of all, as part of analyzing specific living environment patterns, simple trends through EDA are identified, and cluster analysis is conducted based on the trends. After that, in order to derive specific urban planning factors of each cluster, basic statistical analysis such as ANOVA, OLS and MNL analysis were conducted to confirm more specific characteristics. As a result of this study, cluster patterns of environment elements(PM^2.5, PM¹⁰, Noise) and urban factors that affect them are identified, and there are areas with relatively high or low long-term living environment values compared to other regions. The results of this study are believed to be a reference for urban planning management measures for vulnerable areas of living environment, and it is expected to be an exploratory study that can provide directions to urban computing field, especially related to environmental data in the future.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.655-661
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• 2023

Big data, an important element of the 4th industrial revolution, is actively opening public data in public institutions and local governments. In the public data portal, everyone can conveniently search for data and check related data, but only those in ICT-related fields are using public data. Although data held by public institutions is open to citizens, it is difficult for anyone to easily utilize public data to develop applications. In this paper, data provided in open API format from public data portals has XML and JSON formats. In this study, we are a method of modularizing public data in XML format into a part that can be easily developed by linking it to a GUI interface. Based on the necessary public data, we propose a way to easily develop mobile programs and promote the use of public data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1729-1740
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• 2022

Recently, a lot of data has been generated according to the diversity and utilization of information, and the importance of big data analysis to collect, store, process and predict data has increased, and the ability to collect only necessary information is required. More than half of the web space consists of text, and a lot of data is generated through the organic interaction of users. There is a crawling technique as a representative method for collecting text data, but many crawlers are being developed that do not consider web servers or administrators because they focus on methods that can obtain data. In this paper, we design and implement an improved dynamic web crawler that can efficiently fetch data by examining problems that may occur during the crawling process and precautions to be considered. The crawler, which improved the problems of the existing crawler, was designed as a multi-process, and the work time was reduced by 4 times on average.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.131-142
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• 2022

In order to examine the possibility of horizontal simulations of acoustic waves on the environments of big water depth variations, this study introduces a 3-dimensional model based on the pababolic equation. The model gives approximated solutions by separating the cross- and non cross-terms in the equation. Assuming artificial bathymetry (25 km × 4 km) with a source frequency 75 Hz, the simulations give clear horizontal refractions on the transmission loss distributions. The degree of refractions shows non-linear increase along the propagating range and proportional increase with water depth along the cross range. Another simulations with the real bathymetry (25 km × 8 km) also give clear horizontal refractions. The horizontal distributions present little difference with the depth resolution variations of the same data source because the model gives interpolations over the depth data before simulations. Meanwhile, the horizontal distributions show big difference with those of different data sources.

• The Journal of Bigdata
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• v.7 no.1
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• pp.139-171
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• 2022

Big Data and the fourth industrial revolution are the first revolution that has not spawned a new form of energy but has triggered a new technological phenomenon called digitization. Digital transformation has caused disruptive innovation, and each country and major corporations need to respond to it. Despite this importance, empirical studies at home and abroad are insufficient. Therefore, in this study, factors affecting the promotion of corporate digital transformation were discovered through literature review, and a research model was developed and empirically analyzed by modifying and supplementing it through a Delphi study. The research model was composed of the main standards such as technology, innovation, organization, and environment and 17 sub-standards by combining the IDT and TOE models. In order to empirically analyze this, the AHP decision-making technique was used for experts in domestic digital transformation promotion companies and business partners. Companies that promote digital transformation will be able to increase the chances of achieving successful digital transformation if they take into account the factors that influence the digital transformation promotion according to the characteristics of the type of industry and company size of the group to which the company belongs.