• Journal of People, Plants, and Environment
• /
• v.22 no.5
• /
• pp.455-466
• /
• 2019

This study was carried out to analyze trends in floral products and services through the big data analysis of various social networking services (SNSs) and then to provide objective marketing directions for the floricultural industry. To analyze the big data of SNSs, we used four analytical methods: Cotton Trend (Social Matrix), Naver Big Data Lab, Instagram Big Data Analysis, and YouTube Big Data Analysis. The results of the big data analysis showed that SNS users paid positive attention to flower one-day classes that can satisfy their needs for direct experiences. Consumers of floral products and services had their favorite designs in mind and purchased floral products very actively. The demand for flower items such as bouquets, wreaths, flower baskets, large bouquets, orchids, flower boxes, wedding bouquets, and potted plants was very high, and cut flowers such as roses, tulips, and freesia were most popular as of June 1, 2019. By gender of consumers, females (68%) purchased more flower products through SNSs than males (32%). Consumers preferred mobile devices (90%) for online access compared to personal computers (PCs; 10%) and frequently searched flower-related words from February to May for the past three years from 2016 to 2018. In the aspect of design, they preferred natural style to formal style. In conclusion, future marketing activities in the floricultural industry need to be focused on social networks based on the results of big data analysis of popular SNSs. Florists need to provide consumers with the floricultural products and services that meet the trends and to blend them with their own sensitivity. It is also needed to select SNS media suitable for each gender and age group and to apply effective marketing methods to each target.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.6
• /
• pp.883-888
• /
• 2023

Since data centers are places that provide IT services 24 hours a day, 365 days a year, data center power consumption is expected to increase to approximately 10% by 2030, and the introduction of high-density IT equipment will gradually increase. In order to ensure the stable operation of IT equipment, various types of research are required to conserve energy in cooling and improve energy management. This study proposes the following process for energy saving in data centers. We conducted CFD modeling of the data center, proposed an artificial intelligence-based thermal environment prediction model, compared actual measured data, the predicted model, and the CFD results, and finally evaluated the data center's thermal management performance. It can be seen that the predicted values of RCI, RTI, and PUE are also similar according to the normalization used in the normalization method. Therefore, it is judged that the algorithm proposed in this study can be applied and provided as a thermal environment prediction model applied to data centers.

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.6
• /
• pp.115-121
• /
• 2007

Recently, Location Based Service including tracking and way-finding services has been activated rapidly in the ubiquitous computing environment. According as the ubiquitous computing environment is developed, various types of sensor to acquire various data including location of the moving object are used widely, and acquired sensor data becomes abundant. However, the existing location management system based on a single location sensor is difficult to support LBS efficiently in the ubiquitous computing environment. In this paper, therefore, we propose the location management system in the ubiquitous computing environment that can manage the location data and the various sensor data efficiently. In addition, the location management system adopts the core technology for efficiently storing and transferring a large-volume of various data such as location data and for efficiently processing the various requests from a variety of servers and sensors. Especially, our architecture that is presented in this paper can support context-aware services and autonomous services efficiently in the ubiquitous computing environment.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.21 no.2
• /
• pp.58-66
• /
• 2016

We have evaluated the ammonium data in seawater as a potential short-term index for marine environment through the following steps. 1. reviewing of chemical characteristics of ammonium in seawater, 2. comparative relationships of ammonium data with other water quality indices such as DO, COD, and nutrients from Typical Marine Environment(TME) and Special Marine Environment(SME). Ammonium data generally represent negative correlation with DO, while positive correlation with COD. In particular, under frequent cases of seawater conditions showing similar concentration of COD or DO, we have limited choice of explanation for such situation. However ODIN(ODIN/RDIN) or RDIN(RDIN/TDIN) ratio could provide advanced information to understand these seawater conditions. Based on these results, we suggest ammonium data as a potential short-period index for transilient marine environment, such as benthic flux of bottom sediment, hypoxia, and algal bloom. Under overcoming several handicaps, ammonium data could be an useful tool for better understand short transformation of marine environment.

• Journal of KIISE:Computing Practices and Letters
• /
• v.8 no.5
• /
• pp.510-519
• /
• 2002

The OpenGIS Consortium has proposed a new web-mapping technology to support interoperability in web GIS environment by developing the specifications of MapServer and GML. In this environment, the MapServer transforms legacy spatial data into GML data, and clients display them on standard web browsers. This web-mapping testbed proposes methods for discovering, accessing, integrating and displaying GIS information except processing of spatial operations which are essential services in GIS environment. This paper proposes the method for executing spatial operations on GML data which are overlays of different map layers in legacy data servers. To support spatial operations on GML data in web GIS environment, this paper designs and implements GDOM based on the W3C's DOM Specifications and OGC's Simple Features Specifications. This paper shows the specifications and implementation of GDOM and the process of spatial operations in web-mapping testbed environment.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.10
• /
• pp.117-124
• /
• 2021

In this paper, we propose CANVAS (Creative ANalytics enVironment And System), an analytics system of the National Research Data Platform (DataON). CANVAS is a personalized analytics cloud service for researchers who need computing resources and tools for research data analysis. CANVAS is designed in consideration of scalability based on micro-services architecture and was built on top of open-source software such as eGovernment Standard framework (Spring framework), Kubernetes, and JupyterLab. The built system provides personalized analytics environments to multiple users, enabling high-speed and large-capacity analysis by utilizing high-performance cloud infrastructure (CPU/GPU). More specifically, modeling and processing data is possible in JupyterLab or GUI workflow environment. Since CANVAS shares data with DataON, the research data registered by users or downloaded data can be directly processed in the CANVAS. As a result, CANVAS enhances the convenience of data analysis for users in DataON and contributes to the sharing and utilization of research data.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.676-678
• /
• 2003

Recently, in according as rapid improvement of telecommunication markets and wireless internet technology, Location- Based Services (LBS) have been discussed as new 'Killer' application. The purpose of LBS is to determine location of user through mobile handset and to offer location information service to end-user. This paper has suggested an efficient transmission scheme of maps data as one of the important content services relating to data transmission of LBS in mobile environment. The basic system consists of three parts : (1) GIS (Geographic Information System) Server for storing, processing and handling map data, (2) Middleware Server for transmitting of map data by request of client, and (3) Client for requesting map data to Server and displaying them on handset. Also, in order to transmit map data, we are to expand WKB (Well Known Binary) in conformance to Simple Feature Specification of OGC (Open GIS Consortium), and increase efficiency of data transmission by developing trans mission data format to be able to transmit lightweight data and considering data compression technology.

• Journal of the Korean Society of Visualization
• /
• v.1 no.2
• /
• pp.58-70
• /
• 2003

Meteorological data contains observation and numerical weather prediction model output data. The computerized analysis and visualization of meteorological data often requires very high computing capability due to the large size and complex structure of the data. Because the meteorological data is frequently formed in multi-variables, 3-dimensional and time-series form, it is very important to visualize and analyze the data in 3D spatial domain in order to get more understanding about the meteorological phenomena. In this research, we developed interactive 3-dimensional visualization techniques for visualizing meteorological data on a PC environment such as volume rendering, iso-surface rendering or stream line. The visualization techniques developed in this research are expected to be effectively used as basic technologies not only for deeper understanding and more exact prediction about meteorological environments but also for scientific and spatial data visualization research in any field from which three dimensional data comes out such as oceanography, earth science, and aeronautical engineering.

• International journal of advanced smart convergence
• /
• v.12 no.2
• /
• pp.173-181
• /
• 2023

Data collection is an essential element in the construction and operation of a smart factory. The quality of data collection is greatly influenced by network conditions, and existing wireless network systems for IoT inevitably lose data due to wireless signal strength. This data loss has contributed to increased system instability due to misinformation based on incorrect data. In this study, I designed a distributed MQTT IoT smart sensor and gateway structure that supports wireless multicasting for smooth sensor data collection. Through this, it was possible to derive significant results in the service latency and data loss rate of packets even in a wireless environment, unlike the MQTT QoS-based system. Therefore, through this study, it will be possible to implement a data collection management system optimized for the domestic smart factory manufacturing environment that can prevent data loss and delay due to abnormal data generation and minimize the input of management personnel.

• Proceedings of the IEEK Conference
• /
• 1998.10a
• /
• pp.491-494
• /
• 1998

This paper describes the design and implementation of file system which allows the collaborative computing in mobile environment. The design goal is to make a logically one file system in the distributed computer systems. The characteristics of frequent, foreseeable and variable disconnections in a mobile environment wrer taken into consideration. We introduce an auto-hoarding system that provides the availability of large number of nodes which are weakly and intermittently connected. The data consistency problems in distributed or replicated mobile data are also discussed.