• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.9-16
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• 2021

Recently, the traffic volume of mobile communications increases rapidly and the small-cell is one of the solutions using two offload schemes, i.e., local IP access (LIPA) and selected IP traffic offload (SIPTO), to reduce the end-to-end delay and amount of mobile data traffic in the core network (CN). However, 3GPP describes the concept of LIPA and SIPTO and there is no decision algorithm to decide the path from source nodes (SNs) to destination nodes (DNs). Therefore, this paper proposes a dynamic mobile data traffic offload scheme using small-cells to decide the path based on the SN and DN, i.e., macro user equipment, small-cell user equipment (SUE), and multimedia server, and type of the mobile data traffic for the real-time and non-real-time. Through analytical models, it is shown that the proposed offload scheme outperforms the conventional small-cell network in terms of the delay of end-to-end mobile data communications and probability of the mobile data traffic in the CN for the heterogeneous networks.

• 한국공간정보시스템학회:학술대회논문집
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• 2000.06a
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• pp.93-105
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• 2000

GIS is a powerful toolbox in managing spatial data associated with attribute data. However GIS is short of spatial analysis function and graphic user interface(GUI) function in dealing with dynamic planning problems. Decision Support Systems(DSS) make up for the shortage of GIS by providing GUI function, modeling function and database function. Spatial Decision Support Systems(SDSS), a new kind of DSS, incorporate display function, basic spatial analysis function and manipulation function of spatial data and attribute data of GIS and GUI function, modeling function and database function of DSS in dealing with spatial planning problems. Planning Support Systems(PSS) add more advanced spatial analysis function and intertemporal function to the functions of SDSS. This study focuses on the modeling of a PSS for capacity expansion of water-distribution network depending upon land use planning by using GIS, value engineering(VE) and life cycle costing(LCC). The PSS shows a guideline about the investment of water-distribution networks related to urban growth management through generating certain numbers of dynamic alternatives to supply the amount of water caused by land use planning.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.191-194
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• 2001

The ozone forecasting systems have many problems because the mechanism of the ozone concentration is highly complex, nonlinear, and nonstationary. Also, the results of prediction are not a good performance so far, especially in the high-level ozone concentration. This paper describes the modeling method of the ozone prediction system using neuro-fuzzy approaches and fuzzy clustering. The dynamic polynomial neural network (DPNN) based upon a typical algorithm of GMDH (group method of data handling) is a useful method for data analysis, identification of nonlinear complex system, and prediction of a dynamical system.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.125-127
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• 2007

현재 차량 내 네트워크에서 주로 쓰이는 CAN 프로토콜은 네트워크 내에 다수의 노드가 연결되어 동작하는 경우 우선순위가 낮은 메시지의 전송지연이 심각하게 발생할 수 있다. 이를 해결하기 위해 다양한 제어 방법들이 제안되어 시험되고 있는데, 본 논문에서는 동적 ID 차당 기법을 연로전지 하이브리드 자동차 네트워크 시스템에 적용하여 각 장치들간의 메시지 전송 지연문제를 해결 하며, 또한 이로 인해 발생하는 차량 내 네트워크 시스템의 수행 주기 변화의 문제점을 샘플링 주기 결정 기법을 이용하여 효율적으로 해결하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.303-308
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• 2004

Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision making in complex systems. The fuzzy-neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes learning approach of fuzzy-neural network by immune algorithm. The proposed learning model is presented in an immune based fuzzy-neural network (FNN) form which can handle linguistic knowledge by immune algorithm. The learning algorithm of an immune based FNN is composed of two phases. The first phase used to find the initial membership functions of the fuzzy neural network model. In the second phase, a new immune algorithm based optimization is proposed for tuning of membership functions and structure of the proposed model.

• Journal of Information Technology Applications and Management
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• v.20 no.2
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• pp.177-191
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• 2013

Social network has been expected to increase the value of social capital through online user interactions which remove geographical boundary. However, online users in social networks face challenges of assessing whether the anonymous user and his/her providing information are reliable or not because of limited experiences with a small number of users. Therefore. it is vital to provide a successful trust model which builds and maintains a web of trust. This study aims to propose a prediction method for the interpersonal trust which measures the level of trust about information provider in Facebook. To develop the prediction method. we first investigated behavioral research for trust in social science and extracted 5 antecedents of trust : lenience, ability, steadiness, intimacy, and similarity. Then we measured the antecedents from the history of interactive behavior and built prediction models using the two decision trees and a computational model. We also applied the proposed method to predict interpersonal trust between Facebook users and evaluated the prediction accuracy. The predicted trust metric has dynamic feature which can be adjusted over time according to the interaction between two users.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.260-263
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• 2023

Considering the growth of blockchain technology, the research aims to transform the efficiency of recommending optimal coffee suppliers within the complex supply chain network. This transformation relies on the extraction of vital transactional data and insights from stakeholders, facilitated by the dynamic interaction between the application interface (e.g., Rest API) and the blockchain network. These extracted data are then subjected to advanced data processing techniques and harnessed through machine learning methodologies to establish a robust recommendation system. This innovative approach seeks to empower users with informed decision-making abilities, thereby enhancing operational efficiency in identifying the most suitable coffee supplier for each customer. Furthermore, the research employs data visualization techniques to illustrate intricate clustering patterns generated by the K-Means algorithm, providing a visual dimension to the study's evaluation.

• Journal of Digital Convergence
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• v.10 no.9
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• pp.101-110
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• 2012

In recent days, lots of social commerce newly emerged business types of e-commerces are on the basis of social network. Therefore social commerce with social network might be powerful communication channel among customers and has suggested new paradigm in transaction model on the internet. In general, major roles of social commerce sites are to promote transaction with high discount rate and/or lots of event and to activate markets of local area. As characteristics of social commerce such as dynamic, rapid, and open, this research was assumed that design factors of sites that are different from existing e-commerce sites might be influential elements in decision making of purchase. This research is to empirically investigate which factors affect purchase decision making behaviors for 20s respondents who are major users of social commerce services. As a result major factor, easy-to-use, affecting decision making factors was identified and this result can give implication to researchers and persons in charge of fields who have interests in commerce site design and upgrade.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7A
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• pp.560-568
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• 2012

Spectrum sensing and spectrum decision are the main functions that cognitive radios (CRs) have to perform in order to get the best available spectrum band for the establishment of a wireless communication. These problems are worsened in the presence of users with different demands and spectrum channels with different properties in a heterogeneous network. The primary objective in this work is to design and simulate a new spectrum decision algorithm for heterogeneous cognitive radio system. To this end, first, we consider all cognitive users are separated into different traffic classes according to their Quality of Service (QoS). The cognitive users within one traffic class perform spectrum sensing in centralized group-based cooperative spectrum sensing system and the users of different traffic classes share the sensing results. Second, we propose a novel use of the Analytic Hierarchy Process (AHP) to optimally select available bands according to user requirements and detected spectrum channel characteristics (SCC). In this paper, utility function is used as spectrum decision algorithm. Simulation results demonstrate that the proposed method shows can effectively select the best available spectrum channels with a low complexity.

• International Journal of Highway Engineering
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• v.14 no.4
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• pp.163-173
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• 2012

PURPOSES : The purpose of this study is to check the possibilities of traffic pattern analysis using MatSIM for urban road network operation in incident case. METHODS : One of the stochastic dynamic models is MatSIM. MatSIM is a transportation simulation tool based on stochastic dynamic model and activity based model. It is an open source software developed by IVT, ETH zurich, Switzerland. In MatSIM, various scenario comparison analyses are possible and analyses results are expressed using the visualizer which shows individual vehicle movements and traffic patterns. In this study, trip distribution in 24-hour, traffic volume, and travel speed using MatSIM are similar to those of measured values. Therefore, results of MatSIM are reasonable comparing with measured values. Traffic patterns are changed according to incident from change of individual behavior. RESULTS : The simulation results and the actual measured values are similar. The simulation results show reasonable ranges which can be used for traffic pattern analysis. CONCLUSIONS : The change of traffic pattern including trip distribution, traffic volumes and speeds according to various incident scenarios can be used for traffic control policy decision to provide effective operation of urban road network.