• Journal of Internet Computing and Services
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• v.13 no.5
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• pp.33-43
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• 2012

Semantic web is utilized to construct advanced information service by using semantic relationships between entities. Text mining can be applied to generate semantic relationships from unstructured data resources. In this study, ontology schema guideline, ontology instance generation, disambiguation of same name by text mining and advanced historical people finding service by reasoning have been proposed. Various relationships between historical event, organization, people, which are created by domain experts, are linked to literatures of National Institute of Korean History (NIKH). It improves the effectiveness of user access and proposes advanced people finding service based on relationships. In order to distinguish between people with the same name, we compares the structure and edge, nodes of personal social network. To provide additional information, external resources including thesaurus and web are linked to all of internal related resources as well.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.64.4-65
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• 2018

We present a study of citizen science performed at Korean Minjok Leadership Academy (KMLA). The importance of citizen involvements in scientific studies has been increasing, with remarkable results and performances. For instance, the discovery of an impact scar near Jupiter's south polar region (A. Wesley, 2009) led to an international campaign of professional observations to understand the asteroidal collision responsible for the scar. Citizen science at KMLA has been and will be mainly conducted by members of the astronomical observation club 'Apple-Pie' through amateur telescopes. Members of 'Apple-Pie' are specialized in various fields related to astronomy, from planetary science to cosmology. The spectrum not only includes fields that are directly related to astronomy but also fields such as computer science and astrophotography. The scheduled construction of a new observatory will further enable students to participate in higher level projects such as planetary monitoring over long timescales and the observation and detection of solar system bodies and exoplanets. In addition, a new supervisor with expertise and research experience in galactic astronomy, planetary science, and meteorology has joined the school faculty. He will supplement students with fundamental theoretical backgrounds and essential research techniques to enhance astronomical research at KMLA. KMLA's ultimate goal is to deploy a remote-controlled observatory available to aspiring scientists around the world to create a network of citizen science system. The prime observational conditions of KMLA and the willingness of the students and faculty members will provide a competitive edge for KMLA over other similar institutes in Korea.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.2 s.40
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• pp.3-14
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• 2007

This study proposes an automatic method to generate 3D building models using a draft map, which is an intermediate product generated during the map generation process based on aerial photos. The proposed method is to generate a terrain model, roof models, and wall models sequentially from the limited 3D information extracted from an existing draft map. Based on the planar fitting error of the roof corner points, the roof model is generated as a single planar facet or a multiple planar structure. The first type is derived using a robust estimation method while the second type is constructed through segmentation and merging based on a triangular irregular network. Each edge of this roof model is then projected to the terrain model to create a wall facet. The experimental results from its application to real data indicates that the building models of various shapes in wide areas are successfully generated. The proposed method is evaluated to be an cost and time effective method since it utilizes the existing data.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.1-14
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• 2020

Leading the fourth industrial revolution era requires science and technology strategies that establish original research directions at the national level. To this end, it is necessary to look at the research and development activities for the fourth industrial revolution of technology-leading countries. In this study, the research programs of the U.S. Intelligence Advanced Research Projects Activity(IARPA), an organization focusing on cutting edge research on science and technology information such as artificial intelligence, are investigated by using network analysis. The findings show that, resolving around the information identification and forecasting, decision making and cybersecurity clusters, IARPA's research programs largely focus on finding hidden information and predicting specific events, supporting decision making by considering changes in and outside organizations or establishing cybersecurity. Also, this study finds that China and Japan, representative technology-leading Asian countries, refer to the research programs of IARPA to establish their science and technology policies. The results of this study suggest implications for Korea's science and technology policies in response to the fourth industrial revolution era.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.7B
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• pp.706-718
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• 2002

In bluetooth system, there are two kinds of interference. One is the frequency static interference, for example 802.11 direct sequence, the interferer uses fixed frequency band. Another is frequency dynamic interference, for example other piconets or 802.11 frequency hopping, the interferer uses dynamic frequency channel and cant be estimated. In this paper we introduce a novel solution of hybrid method of Listen-Before-Talk (LBT) and Adaptive Frequency Hopping (AFH) to address the coexistence of bluetooth and Direct Sequence of wireless local area network (WLAN). Before any bluetooth packet transmission, in the turn around time of the current slot, both the sender and receiver sense the channel whether there is any transmission going on or not. If the channel is busy, packet transmission is withdrawn until another chance. This is the LBT in Bluetooth. Because of asymmetry sense ability of WLAN and bluetooth, AFH is introduced to combat the left front-edge packet collisions. In monitor period of AFH, LBT is performed to label the channels with static interference. Then, all the labeled noisy channels are not used in the followed bluetooth frequency hopping. In this way, both the frequency dynamic and frequency static interference are effectively mitigated. We evaluate the solution through packet collision analysis and a detail realistic simulation with IP traffic. It turns out that the hybrid method can combat both the frequency dynamic and frequency static interference. The packet collision analysis shows it almost doubles the maximal system aggregate throughput. The realistic simulation shows it has the least packet loss.

• Journal of Digital Contents Society
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• v.17 no.3
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• pp.111-118
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• 2016

Proxy mobile IPv6 (PMIPv6), which is a centralized mobility management protocol, are dependent on a local mobility anchor (LMA) to process all control and data traffics. Therefore, it has serious problems such as the tremendous traffic concentration into the core network and the triangle routing. In this paper, therefore, in order to alleviate these drawbacks, we propose a PMIPv6-based enhanced distributed mobility management scheme considering a user's traffic locality. Performance evaluation results indicate that in most cases, except for when a user's mobility rate is relatively very higher than the traffic rate, the proposed scheme shows better performance result than that of PMIPv6. Besides, it is demonstrated that the proposed scheme can be an effective alternative that can distribute the significant loads on the LMA of the core networks to the MAGs of the edge networks.

• Journal of Digital Convergence
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• v.14 no.3
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• pp.243-250
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• 2016

The importance of platform businesses in the global market is growing, but in Korea, platform businesses with a global competitive edge are rare. This study compared the competitiveness of the local and international platform businesses by analyzing the six success factors of platform businesses. It surveyed 104 professionals in ICT regarding the competitiveness of SNS services (Kakao Talk, Facebook), mobile payment systems (Samsung Pay, Apply Pay), digital content (Naver, YouTube), online shopping (G Market, Amazon) and education (K-MOOC, MOOC). In sum, the local platform business sector, compared to its U.S. counterpart, is lagging behind in creativity, value creation, cost reduction, networking effects and the ability to build, change and develop new ecosystems.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.101-108
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• 2010

Many works on energy-efficient cluster event detection schemes have been done considering the energy restriction of sensor networks. The existing cluster event detection schemes transmit only the boundary information of detected cluster event nodes to the base station. However, If the range of the cluster event is widened and the distribution density of sensor nodes is high, the existing cluster event detection schemes need high transmission costs due to the increase of sensor nodes located in the event boundary. In this paper, we propose an energy-efficient cluster event detection scheme using the minimum boundary polygons (MBP) that can compress and summarize the information of event boundary nodes. The proposed scheme represents the boundary information of cluster events using the MBP creation technique in the large scale of sensor network environments. In order to show the superiority of the proposed scheme, we compare it with the existing scheme through the performance evaluation. Simulation results show that our scheme maintains about 92% accuracy and decreases about 80% in energy consumption to detect the cluster event over the existing schemes on average.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.253-259
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• 2017

Recent development in science and technology has modernized the weapon system of ROKN (Republic Of Korea Navy). Although the cost of purchasing, operating and maintaining the cutting-edge weapon systems has been increased significantly, the national defense expenditure is under a tight budget constraint. In order to maintain the availability of ships with low cost, we need accurate demand forecasts for spare parts. We attempted to find consumption pattern using data mining techniques. First we gathered a large amount of component consumption data through the DELIIS (Defense Logistics Intergrated Information System). Through data collection, we obtained 42 variables such as annual consumption quantity, ASL selection quantity, order-relase ratio. The objective variable is the quantity of spare parts purchased in f-year and MSE (Mean squared error) is used as the predictive power measure. To construct an optimal demand forecasting model, regression tree model, randomforest model, neural network model, and linear regression model were used as data mining techniques. The open software R was used for model construction. The results show that randomforest model is the best value of MSE. The important variables utilized in all models are consumption quantity, ASL selection quantity and order-release rate. The data related to the demand forecast of spare parts in the DELIIS was collected and the demand for the spare parts was estimated by using the data mining technique. Our approach shows improved performance in demand forecasting with higher accuracy then previous work. Also data mining can be used to identify variables that are related to demand forecasting.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1549-1557
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• 1999

In this paper, we propose a face recognition algorithm based on the differential image method-DCT This algorithm uses neural networks which is flexible for noise. Using the same condition (same luminous intensity and same distance from the fixed CCD camera to human face), we have captured two images. One doesn't contain human face. The other contains human face. Differential image method is used to separate the second image into face region and background region. After that, we have extracted square area from the face region, which is based on the edge distribution. This square region is used as the characteristics region of human face. It contains the eye bows, the eyes, the nose, and the mouth. After executing DCT for this square region, we have extracted the feature vectors. The feature vectors were normalized and used as the input vectors of the neural network. Simulation results show 100% recognition rate when face images were learned and 92.25% recognition rate when face images weren't learned for 30 persons.