• KIISE Transactions on Computing Practices
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• v.21 no.10
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• pp.651-657
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• 2015

The amount of web traffic has increased as a result of the rapid growth of the use of web-based applications. In order to obtain valuable information from web logs, we need to develop systems that can support interactive, flexible, and efficient ways to analyze and handle large amounts of data. In this paper, we present CERES, a log-based, interactive web analytics system for backbone networks. Since CERES focuses on analyzing web log records generated from backbone networks, it is possible to perform a web analysis from the perspective of a network. CERES is designed for deployment in a server cluster using the Hadoop Distributed File System (HDFS) as the underlying storage. We transform and store web log records from backbone networks into relations and then allow users to use a SQL-like language to analyze web log records in a flexible and interactive manner. In particular, we use the data cube technique to enable the efficient statistical analysis of web log. The system provides users a web-based, multi-modal user interface.

• Journal of Korean Society of Transportation
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• v.24 no.5 s.91
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• pp.77-88
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• 2006

The purpose of this study is to Propose the time dependent K-least time path algorithm applicable to a real-time based operation strategy in multi-modal transportation network. For this purpose, we developed the extended method based on entire path deletion method which was used in the static K-least time path algorithm. This method was applied to time dependent K-least time path algorithm to find k least time paths in order based on both time dependant mode-link travel time and transfer cost In particular, this algorithm find the optimal solution, easily describing transfer behavior, such as walking and waiting for transfer by applying a link-based time dependent label. Finally, we examined the verification and application of the Proposed algorithm through case study.

• Journal of Korean Society of Transportation
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• v.31 no.1
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• pp.15-24
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• 2013

To accommodate urban concentration of population, multi-purpose super-tall buildings have been introduced, but they induce many travel demands causing regional traffic problems. While several travel demand management policies such as transit promotion or parking limits are presented to alleviate such problems, transportation infrastructure are still insufficient to meet high demands. In this study, super-tall buildings are categorized by scale and purpose, then mode-specific derived demand is estimated using modal share of each category. Optimal transportation infrastructure level is determined by condition-based average changing amount yielded by street network delay (in case of road) or the number of transit routes (in case of transit).

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.2
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• pp.1-12
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• 2016

This paper is to analyze characteristics of transfer trips and to identify impacts of land use on them. Using the smart transport card data of Seoul on a weekday in April 2013, we explored general characteristics of the transfer trips such as spatial and temporal distributions, transfer types, and geographical patterns of transfer trips. Then, the multiple regression model for the transfer trips was developed, considering land use as well as socio-economic variables as explanatory ones. For the characteristics of the transfer trips, their ratio to the total trips accounts for 26.7%. Nearly 87% of the trips are one-time transferred, and 64.7% are bus-subway transfer trips. In addition, the transfer trips are more likely to appear nearby subway stations and business facilities. The regression model indicates that land use variables such as the floor areas of business facilities and department stores and mixed land use index significantly positively affect the transfer trips. Our results can be used as basic data for choosing feasible locations of multi-modal transfer centers in urban areas.

• Korean Journal of Materials Research
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• v.31 no.9
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• pp.502-510
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• 2021

Hierarchically porous carbon materials with high nitrogen functionalities are extensively studied as high-performance supercapacitor electrode materials. In this study, nitrogen-doped porous carbon textile (N-PCT) with hierarchical pore structures is prepared as an electrode material for supercapacitors from a waste cotton T-shirt (WCT). Porous carbon textile (PCT) is first prepared from WCT by two-step heat treatment of stabilization and carbonization. The PCT is then nitrogen-doped with urea at various concentrations. The obtained N-PCT is found to have multi-modal pore structures with a high specific surface area of 1,299 m² g^-1 and large total pore volume of 1.01 cm³ g^-1. The N-PCT-based electrode shows excellent electrochemical performance in a 3-electrode system, such as a specific capacitance of 235 F g^-1 at 1 A g^-1, excellent cycling stability of 100 % at 5 A g^-1 after 1,000 cycles, and a power density of 2,500 W kg^-1 at an energy density of 3.593 Wh kg^-1. Thus, the prepared N-PCT can be used as an electrode material for supercapacitors.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.2
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• pp.347-363
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• 2019

Malware has its own unique behavior characteristics, like DNA for living things. To respond APT (Advanced Persistent Threat) attacks in advance, it needs to extract behavioral characteristics from malware. To this end, it needs to do classification for each malware based on its behavioral similarity. In this paper, various similarity of Windows malware is estimated; and based on these similarity values, malware's family is predicted. The similarity measures used in this paper are as follows: 'TF-IDF cosine similarity', 'Nilsimsa similarity', 'malware function cosine similarity' and 'Jaccard similarity'. As a result, we find the prediction rate for each similarity measure is widely different. Although, there is no similarity measure which can be applied to malware classification with high accuracy, this result can be helpful to select a similarity measure to classify specific malware family.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.510-512
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• 2019

Recently, there have been growing requirements in the public safety sector to ensure safety through detection of hazardous situations or preemptive predictions. It is noteworthy that various sensor data can be analyzed and utilized as a result of mobile device's dissemination, and many advantages can be used in terms of safety and security. An effective modeling technique is needed to combine sensor data generated by smart-phones and wearable devices to analyze users' moving patterns and behavioral patterns, and to ensure public safety by fusing location-based crime risk data provided.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.261-270
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• 2020

In this study, we identify promising technologies for Piggyback transportation system by analyzing the relevant patent information. In order for this, we first develop the patent database by extracting relevant technology keywords from the pioneering research papers for the Piggyback flactcar system. We then employed textmining to identify the frequently referred words from the patent database, and using these words, we applied the LDA (Latent Dirichlet Allocation) algorithm in order to identify "topics" that are corresponding to "key" technologies for the Piggyback system. Finally, we employ the ARIMA model to forecast the trends of these "key" technologies for technology forecasting, and identify the promising technologies for the Piggyback system. with keyword search method the patent analysis. The results show that data-driven integrated management system, operation planning system and special cargo (especially fluid and gas) handling/storage technologies are identified to be the "key" promising technolgies for the future of the Piggyback system, and data reception/analysis techniques must be developed in order to improve the system performance. The proposed procedure and analysis method provides useful insights to develop the R&D strategy and the technology roadmap for the Piggyback system.

• Journal of Korean Association for Spatial Structures
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• v.22 no.3
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• pp.33-40
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• 2022

Recently, cultural heritages in South Korea gain many interests of restoration and preservation from the government since many of that have been severely damaged during earthquakes. Many previous studies in both terms of experimental and analytical approaches have been done to examine structural behavior and decide appropriate methods of preservation. Being motivated by such researches, this research aims to investigate a religious stone pagoda dated back to the Goryeo Dynasty in Korea. The structure consists of a granite stone foundation and baked bricks, which resembles the shape of traditional pagodas. In order to examine the structural behavior of the pagoda, an analytical model is implemented using ANSYS, a comprehensive engineering simulation platform. For the time history analysis of the pagoda, several earthquake excitations are chosen and input to simulation modeling. Seismic response of the tower such as time domain, natural frequency, modal shapes and peak acceleration measured at each layer are presented and discussed. In addition, the amplification ratio of the tower is calculated from the accelerations of each layer to determine tower stability in accordance with Korean seismic design guide. The determination and evaluation of status and response of the brick tower by simulation analysis play an important role in the preservation of history as well as valuable architectural heritages in South Korea.

• Korean Journal of Materials Research
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• v.32 no.9
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• pp.369-378
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• 2022

The recycling of solid waste materials to fabricate carbon-based electrode materials is of great interest for low-cost green supercapacitors. In this study, porous carbon foam (PCF) was prepared from waste floral foam (WFF) as an electrode material for supercapacitors. WFF was directly carbonized at various temperatures of 600, 800, and 1,000 ℃ under an inert atmosphere. The WFF-derived PCF (C-WFF) was found to have a specific surface area of 458.99 m²/g with multi-modal pore structures. The supercapacitive behavior of the prepared C-WFF was evaluated using a three-electrode system in a 6 M KOH aqueous electrolyte. As a result, the prepared C-WFF as an active material showed a high specific capacitance of 206 F/g at 1 A/g, a rate capability of 36.4 % at 20 A/g, a specific power density of 2,500 W/kg at an energy density of 2.68 Wh/kg, and a cycle stability of 99.96 % at 20 A/g after 10,000 cycles. These results indicate that the C-WFF prepared from WFF could be a promising candidate as an electrode material for high-performance green supercapacitors.