• International journal of advanced smart convergence
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• v.4 no.1
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• pp.31-34
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• 2015

Recently, the various types of data are began to increase. In order to manage the data efficiently, a variety of cloud services are being made. However, while providing a cloud service, the problem is the cost and waste a lot of human power to manage the data that is generated and managed by the server. To solve this problem, it is build the cloud environment using a single board computer with Raspberry pi. In this paper, we used Raspberry pi as a cloud server to provide services for the users. And we construct a Total Server to manage the generated data. It can separate the processing of data and the provision of services. We ensure the efficient operation by building a cloud environment with Raspberry pi and by managing the data which generated in cloud environment with the total server.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.375-384
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• 2007

As teachings that use the ICT are more popular, many studies on the dynamic geometry environment(DGE) are under way. An important factor emphasized in the studies is to practical use learning activities of learners. In this study, we first define the learning history data in DGE. Second we develop a prototype of the DGE that is able to collect and analyze the learning history data automatically. The environment enables not only to grasp leaning history but also to create and manage new learning objects.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.85-90
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• 2016

In this paper, the biometric data is transmitted in real time from the IoT environment is runoff, forgery, alteration, prevention of the factors that can be generated from a denial-of-service in advance, and the security strategy for the biometric data to protect the biometric data secure from security threats offer. The convenience of living in our surroundings to life with the development of ubiquitous computing and smart devices are available in real-time. And is also increasing interest in the IOT. IOT environment is giving the convenience of life. However, security threats to privacy also are exposed for 24 hours. This paper examines the security threats to biological data to be transmitted in real time from IOT environment. The technology for such security requirements and security technology according to the analysis of the threat. And with respect to the biometric data transmitted in real time on the IoT environment proposes a security strategy to ensure the stability against security threats and described with respect to its efficiency.

• Journal of Korean Society on Water Environment
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• v.35 no.6
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• pp.481-496
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• 2019

The Ministry of Environment has measured streamflow at eight-day intervals for the estimation of standard flow of the Total Maximum Daily Loads (TMDL) system. This study identified the availability of the partially measured the eight-day interval data for estimating standard flow and found the optimal extension techniques of standard flow. The study area was selected for the Nakbon-A watershed in the Nakdong River, and four streamflow record extension techniques of standard flow were considered: extension, percentile, drainagearea, and regional regression methods. The flow duration curve (FDC) using the eight-day interval streamflow data indicated very high Nash and Sutcliffe Efficiency (NSE) values above 90 % from FDC-II to FDC-VII compared to FDC-VIII, the standard FDC. This result demonstrates that FDC using daily data of three-six cumulative years could represent standard FDC fairly well. For the streamflow record extension techniques of standard flow, the percentile method was selected as the optimal alternative, showing the minimal difference from FDC-VIII. These results validate the availability of the eight-day interval streamflow data in the standard flow estimation and the application of extension techniques. It seems that these results could reduce the uncertainty of partially measured streamflow data for water quantity and quality management.

• KIEAE Journal
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• v.12 no.6
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• pp.113-121
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• 2012

A hospital is the most important infra-facility of the places which take care of people's body in social environment. There exist several environmental factors in the ways to heal the human body in hospital ward, but this study tried to look into the improvable pleasant sickroom environment with focus on light environment among the factors. In other words, this study aims at the research on proper daylight inflow into sickroom space as basic data for understanding the link between healing environment and natural lighting. In the simulation analysis through this research, this study completed the initial simulation using Autodesk Revit 2011 with focus on two types of individual multi-bed room units of the two general hospitals located in Gwangju City. This study made a simulation analysis of The two multi-bed rooms looking to the west using the weather data on Gwangju district, which is the strong point of ECOTECT2011. Conclusively, looking into the analysis of the simulation model in time of attaching the length of in & outside light shelf, the angle controlling of light shelf, the daylight factor and DA were found to show the tendency to decrease in the numerical value due to the decrease in sunlight inflow as the simulation model moved more toward the room from the window in comparison with the existing analysis of multi-bed rooms. Particularly, this study was able to read that the daylight factor and DA were more decreasing to improve at the light shelf than the existing bedrooms; conclusively, this study judges that the natural lighting simulation analysis could be helpful in improving the healing environment as basic data.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.637-643
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• 2020

In this study, the information from environmental impact statements was converted into spatial data because environmental data from development sites are collected during the environmental impact assessment (EIA) process. Spatiotemporal big data were built from environmental spatial data for each environmental medium for 2,235 development sites during 2007-2018, available from public data portals. Comparing air-quality monitoring stations, 33,863 measurement points were constructed, which is approximately 75 times more measurement points than that 452 in Air Korea's real-time measurement network. Here, spatiotemporal big data from 2,677,260 EIAs were constructed. In the future, such data might be used not only for EIAs but also for various spatial plans.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.354-361
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• 2023

Big data analysis systems apply NoSQL databases like MongoDB to store, process, and analyze diverse forms of large-scale data. MongoDB offers scalability and fast data processing speeds through distributed processing and data replication, depending on its configuration. This paper investigates the suitable MongoDB environment configurations for implementing big data analysis systems. For performance evaluation, we configured both single-node and multi-node environments. In the multi-node setup, we expanded the number of data nodes from two to three and measured the performance in each environment. According to the analysis, the processing speeds for complex data structures with three or more dimensions are approximately 5.75% faster in the single-node environment compared to an environment with two data nodes. However, a setting with three data nodes processes data about 25.15% faster than the single-node environment. On the other hand, for simple one-dimensional data structures, the multi-node environment processes data approximately 28.63% faster than the single-node environment. Further research is needed to practically validate these findings with diverse data structures and large volumes of data.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.91.3-91
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• 2001

A sensor fusion scheme for mobile robot environment recognition that incorporates range data and contour data is proposed. Ultrasonic sensor provides coarse spatial description but guarantees open space with no obstacle within sonic cone with relatively high belief. Laser structured light system provides detailed contour description of environment but prone to light noise and is easily affected by surface reflectivity. Overall fusion process is composed of two stages: Noise elimination and belief updates. Dempster Shafer´s evidential reasoning is applied at each stage. Open space estimation from sonar range measurements brings elimination of noisy lines from laser sensor. Comparing actual sonar data to the simulated sonar data enables ...

• The Journal of the Korea Contents Association
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• v.9 no.1
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• pp.147-158
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• 2009

Recently, the data model in stream data environment has massive, continuous, and infinity properties. However the stream data processing like query process or data analysis is conducted using a limited capacity of disk or memory. In these environment, the traditional frequent pattern discovery on transaction database can be performed because it is difficult to manage the information continuously whether a continuous stream data is the frequent item or not. In this paper, we propose the method which we are able to predict the frequent items using the regression model on continuous stream data environment. We can use as a prediction model on indefinite items by constructing the regression model on stream data. We will show that the proposed method is able to be efficiently used on stream data environment through a variety of experiments.

• Journal of Korea Multimedia Society
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• v.20 no.9
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• pp.1559-1566
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• 2017

Recently in the IoT(Internet of Things) environment, a data collection in real-time through device's sensor has increased with an emergence of various devices. Collected data from IoT environment shows a large scale, non-uniform generation cycle and atypical. For this reason, the distributed processing technique is required to analyze the IoT sensor data. However if you do not consider the optimal scheduling for data and the processor of IoT in a distributed processing environment complexity increase the amount in assigning a task, the user is difficult to guarantee the QoS(Quality of Service) for the sensor data. In this paper, we propose APQTA(Adaptive Priority Queue-driven Task Allocation method for sensor data processing) to efficiently process the sensor data generated by the IoT environment. APQTA is to separate the data into job and by applying the priority allocation scheduling based on the deadline to ensure that guarantee the QoS at the same time increasing the efficiency of the data processing.