• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.9 no.1
• /
• pp.179-187
• /
• 2019

With the recent development of small computing devices, IoT sensor network can be widely deployed and is now readily available with sensing, calculation and communi-cation functions at low cost. Sensor data management is a major component of the Internet of Things environment. The huge volume of data produced and transmitted from sensing devices can provide a lot of useful information but is often considered the next big data for businesses. New column-wise compression technology is mounted to the large data server because of its superior space efficiency. Since sensor nodes have narrow bandwidth and fault-prone wireless channels, sensor-based storage systems are subject to incomplete data services. In this study, we will bring forth a short overview through providing an analysis on IoT sensor networks, and will propose a new storage management scheme for IoT data. Our management scheme is based on RAID storage model using column-wise segmentation and compression to improve space efficiency without sacrificing I/O performance. We conclude that proposed storage control scheme outperforms the previous RAID control by computer performance simulation.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.3
• /
• pp.469-477
• /
• 2017

Cloud computing is an IT resource providing technology to various users by using virtualization technology. Newly updated spatial information may not be used by other organizations since management authorities are dispersed for Korean public spatial information. Further, the national budget is wasted since each organization independently implements renewable GIS analysis function. These problems can be solved by applying cloud service. However, research related to the application of cloud service to Korea spatial information system has been proposed in the technology development direction, and no detailed development plan has been proposed. In this paper, we deal with the establishment of a technology development plan for national spatial information infrastructure cloud service. First, we deduct the implication to derive the technology development goals by analyzing the political and technical environment. Second, technology and critical technology elements are derived to achieve the goals of the specialist's analysis based on the evaluation elements. As a result, thirteen critical technology elements are derived. Finally, thirty-one research activities, which comprise the critical technology elements, are defined. Critical technology elements and research activities derived in this research will be used for the generation of a technology development road-map.

• Korean Journal of Remote Sensing
• /
• v.33 no.6_2
• /
• pp.1061-1073
• /
• 2017

In this study, images were classified using convolutional neural network (CNN) - a deep learning technique - to investigate the feasibility of information production through a combination of artificial intelligence and spatial data. CNN determines kernel attributes based on a classification criterion and extracts information from feature maps to classify each pixel. In this study, a CNN network was constructed to classify materials with similar spectral characteristics and attribute information; this is difficult to achieve by conventional image processing techniques. A Compact Airborne Spectrographic Imager(CASI) and an Airborne Imaging Spectrometer for Application (AISA) were used on the following three study sites to test this method: Site 1, Site 2, and Site 3. Site 1 and Site 2 were agricultural lands covered in various crops,such as potato, onion, and rice. Site 3 included different buildings,such as single and joint residential facilities. Results indicated that the classification of crop species at Site 1 and Site 2 using this method yielded accuracies of 96% and 99%, respectively. At Site 3, the designation of buildings according to their purpose yielded an accuracy of 96%. Using a combination of existing land cover maps and spatial data, we propose a thematic environmental map that provides seasonal crop types and facilitates the creation of a land cover map.

• Journal of the Korea Society for Simulation
• /
• v.19 no.1
• /
• pp.63-71
• /
• 2010

In modern war, Intercept Performance of SAM(Surface to Air Missile) is gaining importance as range and precision of Missile and Guided Weapon on information warfare have been improved. An aerial defence system using Surface-to-air Radar and Guided Missile is needed to be built for prediction and defense from threatening aerial attack. When developing SAM, M&S is used to free from a time limit and a space restriction. M&S is widely applied to education, training, and design of newest Weapon System. This study was conducted to develop simulator for evaluation of Intercept Performance of SAM. In this study, architecture of Intercept Performance of SAM analysis simulator for estimation of Intercept Performance of various SAM was suggested and developed. The developed Intercept Performance of SAM analysis simulator was developed by C++ and Direct3D, and through 3D visualization using the Direct3D, it shows procedures of the simulation on a user animation window. Information about design and operation of Fighting model is entered through input window of the simulator, and simulation engine consisted of Object Manager, Operation Manager, and Integrated Manager conducts modeling and simulation automatically using the information, so the simulator gives user feedback in a short time.

• Journal of Cadastre & Land InformatiX
• /
• v.47 no.1
• /
• pp.15-26
• /
• 2017

The decrease of green space according to the urbanization has caused many environmental problems as the destruction of habitat, air pollution, heat island effect. With interest growing in natural view recently, proper management of evergreen tree which is lived even the winter season has been on the rise importantly. This study analyzed the distribution area of evergreen tree using vegetation index based on unmanned aerial vehicle (UAV). Firstly, RGB and NIR+RG camera were loaded in fixed-wing UAV and image mosaic was achieved using GCPs based on Pix4d SW. And normalized differences vegetation index (NDVI) and soil adjusted vegetation index (SAVI) was calculated by band math function from acquired ortho mosaic image. validation points were applied to evaluate accuracy of the distribution of evergreen tree for each range value and analysis showed that kappa coefficient marked the highest as 0.822 and 0.816 respectively in "NDVI > 0.5" and "SAVI > 0.7". The area of evergreen tree in "NDVI > 0.5" and "SAVI > 0.7" was $11,824m^2$ and $15,648m^2$ respectively, that was ratio of 4.8% and 6.3% compared to total area. It was judged that UAV could supply the latest and high resolution information to vegetation works as urban environment, air pollution, climate change, and heat island effect.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.39 no.6
• /
• pp.469-476
• /
• 2021

The framework plan for the development of an integrated underground space map was established of preventing ground subsidence. The mapping process is expected to be completed to the level of nationwide municipal government standards by end of this year. To facilitate the utilization of the integrated underground space map, paper-based drawings for specialized organizations in underground safety impact assessment have been provided since September 2018, and services for local government officials have been provided in the underground information utilization system since May 2019. However, the map is utilized based on the information at the time of the initial development of the map, without any updates, thereby resulting in a lack of accuracy and latest information. This has led to a decrease in the utilization and reliability of the information. Therefore, in this study, for the underground structures(subway, underground shopping mall, underground passage, underground roadway, underground parking lot, utility tunnel), which are the key components of the integrated underground space map, a standard format for the submission of completed drawings is designed in accordance with Article 42 (2) of the Special Act on Underground Safety Management, which aims at laying the foundation for establishing the updated system of the integrated underground space map. In addition, through the verification of the automatically updated underground structure data based on the standard format, the reliability of the data can be assured. This format is expected to contribute to the improved utilization of the integrated underground space map in the future.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.7
• /
• pp.1-8
• /
• 2017

As the IT environment becomes more sophisticated, various threats and their associated serious risks are increasing. Threats such as DDoS attacks, malware, worms, and APT attacks can be a very serious risk to enterprises and must be efficiently managed in a timely manner. Therefore, the government has designated the important system as the main information communication infrastructure in consideration of the impact on the national security and the economic society according to the 'Information and Communication Infrastructure Protection Act', which, in particular, protects the main information communication infrastructure from cyber infringement. In addition, it conducts management supervision such as analysis and evaluation of vulnerability, establishment of protection measures, implementation of protection measures, and distribution of technology guides. Even now, security consulting is proceeding on the basis of 'Guidance for Evaluation of Technical Vulnerability Analysis of Major IT Infrastructure Facilities'. There are neglected inspection items in the applied items, and the vulnerability of APT attack, malicious code, and risk are present issues that are neglected. In order to eliminate the actual security risk, the security manager has arranged the inspection and ordered the special company. In other words, it is difficult to check against current hacking or vulnerability through current system vulnerability checking method. In this paper, we propose an efficient method for extracting diagnostic data regarding the necessity of upgrading system vulnerability check, a check item that does not reflect recent trends, a technical check case for latest intrusion technique, a related study on security threats and requirements. Based on this, we investigate the security vulnerability management system and vulnerability list of domestic and foreign countries, propose effective security vulnerability management system, and propose further study to improve overseas vulnerability diagnosis items so that they can be related to domestic vulnerability items.

• Journal of Intelligence and Information Systems
• /
• v.29 no.2
• /
• pp.57-84
• /
• 2023

With the development of information and communications technology (ICT) and big data technology, anyone can easily obtain and utilize vast amounts of data through the Internet. Therefore, the capability of selecting high-quality data from a large amount of information is becoming more important than the capability of just collecting them. This trend continues in academia; literature reviews, such as systematic and non-systematic reviews, have been conducted in various research fields to construct a healthy knowledge structure by selecting high-quality research from accumulated research materials. Meanwhile, after the COVID-19 pandemic, remote healthcare services, which have not been agreed upon, are allowed to a limited extent, and new healthcare services such as health recommender systems (HRS) equipped with artificial intelligence (AI) and big data technologies are in the spotlight. Although, in practice, HRS are considered one of the most important technologies to lead the future healthcare industry, literature review on HRS is relatively rare compared to other fields. In addition, although HRS are fields of convergence with a strong interdisciplinary nature, prior literature review studies have mainly applied either systematic or non-systematic review methods; hence, there are limitations in analyzing interactions or dynamic relationships with other research fields. Therefore, in this study, the overall network structure of HRS and surrounding research fields were identified using citation network analysis (CNA). Additionally, in this process, in order to address the problem that the latest papers are underestimated in their citation relationships, the GraphSAGE algorithm was applied. As a result, this study identified 'recommender system', 'wireless & IoT', 'computer vision', and 'text mining' as increasingly important research fields related to HRS research, and confirmed that 'personalization' and 'privacy' are emerging issues in HRS research. The study findings would provide both academic and practical insights into identifying the structure of the HRS research community, examining related research trends, and designing future HRS research directions.

• Journal of Cadastre & Land InformatiX
• /
• v.48 no.1
• /
• pp.139-151
• /
• 2018

The National Base Map construction consists of the regular correction work of dividing the whole country into two regions and carrying out the modification Plotting by aerial photographs every two years as well as the real time updating work of correcting the major change feature within two weeks by the field survey and the As-Built Drawing. In the case of the Building Layout Drawing of Korea Real estate Administration intelligence System(KRAS) used for real time updating work of the National base map, the coordinate transformation error is included in the positional error when applied to the National Base Map based on the World Geodetic Reference System as the coordinate system based on the Regional Geodetic Reference System. In addition, National Base Map is registered based on the outline(eaves line) of the building in the Digital Topographic Map, and the Cadastral and Architecture are registered based on the building center line. Therefore, the Building Object management standard is inconsistent. In order to investigate the improvement method, the network RTK survey was conducted directly on a location of the Building Layout Drawing of Korea Real estate Administration intelligence System(KRAS) and the problems were analyzed by comparing with the plane plotting position reference in National Base Map. In the case of the general structure with the difference on the Building center line and the eaves line, beside the location information was different also the difference in the ratio of the building object was different between Building center line and the eave. In conclusion, it is necessary to provide the Base data of the double layer of the Building center line and the outline of the building(eaves line) in order to utilize the Building Layout Drawing of Korea Real estate Administration intelligence System(KRAS). In addition, it is necessary to study an organic map update process that can acquire the up-to-dateness and the accuracy at the same time.

• Journal of Intelligence and Information Systems
• /
• v.22 no.1
• /
• pp.187-204
• /
• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.