• 한국HCI학회:학술대회논문집
• /
• 2008.02b
• /
• pp.71-77
• /
• 2008

This study conducted to tried to find a way of on-line assessment of learner's interest and comprehension during interactive learning process. The result of experiment confirmed hat learners' behavior patterns acquired from log data could be good predictors of learner's level of interest and comprehension in actual performance on KORI program. To predict learning outcome depending on the behaviors of individual learners, self-efficacy and mastery goal orientation were measured as individual differences. Then, participants were asked to use TA program KORI program at home for ten days and their response patterns were recorded through network. After using KORI, the levels of interest and comprehension were measured. As the result of multiple regression analysis, each learner's interest and comprehension were predicted depending on the combination of log data captured on real-time. This prediction process was done differently depending on learners' characteristics. Since equations which predict learners' interest and comprehension are different depending on learners' characteristics, differential interfaces should be provided depending upon changes in their level of interest and comprehension.

• Spatial Information Research
• /
• v.22 no.4
• /
• pp.67-76
• /
• 2014

Recently, through the development of IT and mobile technology, spatial information plays a role of infrastructure of the people life and the national economy. Many kinds of applications including SNS and social commerce is to leverage the spatial information for their services. In the case of domestic, spatial open platform that can provide national spatial data infrastructure services in a stable manner has been released. And many people have been interested to the open platform services. However, the open platform currently has many difficulties to analyze its service status and load in real time, because it does not hold a real-time monitoring system. Therefore, we propose a method that can analyze the real-time service status of the open platform using the analysis of the web server log information. In particular, we propose the results of the analysis as follows: amount of data transferred, network bandwidth, number of visitors, hit count, contents usage, and connection path. We think the results presented in this study is insufficient to understand the perfect service status of the open platform. However, it is expected to be utilized as the basic data for understanding of the service status and for system expansion of the open platform, every year.

• The Journal of Engineering Geology
• /
• v.17 no.3
• /
• pp.483-494
• /
• 2007

The properties of fracture system on road-cut slopes along the Busan-Ulsan express way under construction are investigated and analyzed. Fracture spacing distributions show log-normal form with extension fractures and negative exponential form with shear fractures. Straight line segments in log-log plots of cumulative fracture length indicate a power-law scaling with exponents of -1.13 in site 1, -1.01 in site 2 and -1.52 in site 3. It is likely that the stability and strength of rock mass are the lowest in site 1 as judged from the analyses of spacing, density and inter-section of fractures in three sites. In contrast, the highest efficiency of the fracture network for conducting fluid flow is seen in site 3 where the largest cluster occupies 73% through the window map. Based on the field survey data, this study modified weighting values of the RMR system using a multiple regression analysis method. The analysis result suggests a modified weighting values of the RMR parameters as follows; 18 for the intact strength of rock; 61 for RQD; 2 for spacing of discontinuities; 2 for the condition of discontinuities; and 17 for ground water.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.3
• /
• pp.119-125
• /
• 2023

IT infrastructure operation has advanced, and the methods for managing systems have become widely adopted. Recently, research has focused on improving system management using Syslog. However, utilizing log data collected through these methods presents challenges, as logs are extracted in various formats that require expert analysis. This paper proposes a system that utilizes edge computing to distribute the collection of Syslog data and preprocesses duplicate data before storing it in a central database. Additionally, the system constructs a data dictionary to classify and count data in real-time, with restrictions on transmitting registered data to the central database. This approach ensures the maintenance of predefined patterns in the data dictionary, controls duplicate data and temporal duplicates, and enables the storage of refined data in the central database, thereby securing fundamental data for big data analysis. The proposed algorithms and procedures are demonstrated through simulations and examples. Real syslog data, including extracted examples, is used to accurately extract necessary information from log data and verify the successful execution of the classification and storage processes. This system can serve as an efficient solution for collecting and managing log data in edge environments, offering potential benefits in terms of technology diffusion.

• Journal of the Korean Chemical Society
• /
• v.36 no.1
• /
• pp.87-94
• /
• 1992

The elution behavior of polystyrenes(PS), polymethylmethacrylates (PMMA), polybutadienes(PB), PS-PMMA(SM) block copolymers and PS-PB star shaped copolymers on the cross-linked polystyrene gels was studied. An interpretation was proposed for the plots of log hydrodynamic volume versus retention volume of solutes in the mobile phases such as tetrahydrofuran, toluene, chloroform, methylene chloride and tetrahydrofuran-cyclohexane mixture. In order to predict the retention of solutes from their physical properties, multiple stepwise regression analysis was applied to obtain the correlation. The distribution coefficients($K_p$) of solute-gel interactions in GPC for homopolymers and PS copolymers were also obtained in terms of network-limited separation mechanism. In the cases of PS and PB, $K_p$ values approach unity, while $K_p$ values for PMMA decrease as MW increase in the good solvent, but in poor solvent, $K_p$ values increase as MW increase. $K_p$ values of PS copolymers are dependent on their MW and composition, therefore, morohology of SM block copolymer is predicted to be random phase. A single universal plot of log[η]M vs. $(V_r-V_o)/K_p$

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.30 no.4
• /
• pp.647-656
• /
• 2020

Recently, there has been an increasing number of cases in which important data (personal information, technology, etc.) of national and public institutions are leaked to the outside world. Surveys show that the largest cause of such leakage accidents is "insiders." Insiders of organization with the most authority can cause more damage than technology leaks caused by external attacks due to the organization. This is due to the characteristics of insiders who have relatively easy access to the organization's major assets. This study aims to present an optimized property selection model for detecting such abnormalities through supervised learning algorithms among machine learning techniques using actual data such as CrossNet data transfer system transmission log, e-mail transmission log, and personnel information, which safely transmits data between separate areas (security area and non-security area) of the business network and the Internet network.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.6
• /
• pp.21-31
• /
• 2018

In Hyper-Connected Society, IoT-based Lifelog data is used throughout the Internet and is an important component of customized services that reflect user requirements. Also, Users are using social network services to easily express their interests and feelings, and various life log data are being accumulated. In this paper, Intelligent characters using IoT based lifelog data have been developed and qualitative/quantitative data are collected and analyzed in order to systematically grasp emotions of users. For this, qualitative data through the social network service used by the user and quantitative data through the wearable device are collected. The collected data is verified for reliability by comparison with the persona through esnography. In the future, more intelligent characters will be developed to collect more user life log data to ensure data reliability and reduce errors in the analysis process to provide personalized services.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.4
• /
• pp.1424-1440
• /
• 2015

It is a challenging problem to search the intended images from a large number of candidates. Content based image retrieval (CBIR) is the most promising way to tackle this problem, where the most important topic is to measure the similarity of images so as to cover the variance of shape, color, pose, illumination etc. While previous works made significant progresses, their adaption ability to dataset is not fully explored. In this paper, we propose a similarity learning method on the basis of probabilistic generative model, i.e., probabilistic latent semantic analysis (PLSA). It first derives Fisher kernel, a function over the parameters and variables, based on PLSA. Then, the parameters are determined through simultaneously maximizing the log likelihood function of PLSA and the retrieval performance over the training dataset. The main advantages of this work are twofold: (1) deriving similarity measure based on PLSA which fully exploits the data distribution and Bayes inference; (2) learning model parameters by maximizing the fitting of model to data and the retrieval performance simultaneously. The proposed method (PLSA-FK) is empirically evaluated over three datasets, and the results exhibit promising performance.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.5
• /
• pp.179-186
• /
• 2008

In proportion as the growth of the wireless sensor network applications, we need for more accuracy wireless channel information. In the case of indoor or outdoor wireless sensor networks, multipath propagation causes severe problems in terms of fading. Therefore, a path-loss model for multipath environment is required to optimize communication systems. This paper deals with log-normal path loss modeling of the indoor 2.4 GHz channel. We measured variation of the received signal strength between the sender and receiver of which separation was increased from 1 to 30m. The path-loss exponent and the standard deviation of wireless channel were determined by fitting of the measured data. By using the PRR(Packet Reception Rate) of this model. Wireless sensor channel is defined CR(Connect Region), DR(Disconnected Region). In order to verify the characteristics of wireless channel, we performed simulations and experiments. We demonstrated that connection ranges are 24m in indoor, and 14m in outdoor.

• Journal of the Korea Institute of Building Construction
• /
• v.22 no.3
• /
• pp.317-326
• /
• 2022

With the development of various technologies in the area of artificial intelligence, a number of studies to application of artificial intelligence technology in the construction field are underway. Diverse technologies have been applied to the task of predicting construction costs, and construction cost prediction technologies applying artificial intelligence technologies have recently been developed. However, it is difficult to secure the vast amount of construction cost data required for machine learning, which has not yet been practically used. In this study, to predict the construction cost, the latest artificial neural network(ANN) method is used to propose a method to improve the construction cost prediction performance. In particular, to improve predictive performance, a log conversion method of target variables and a feature scaling method to eliminate the difference in the relative influence of each column data are applied, and their performance in predicting construction cost is compared and analyzed.