• Korean Journal of Construction Engineering and Management
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• v.4 no.4 s.16
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• pp.212-219
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• 2003

In construction project planning and control, a cost model performs a critical role such as cost determination on a contract stage and cost tracing. The model can maximize owner's profit and value within the project budget and optimize cost management works on overall construction implementation stages. A BoQ(Bill of Quantities) generally adopted in a unit price contract has been applied as an important tool for cost control and forecast. However a previous cost model based on the BoQ has shown limitations in that it requires too detailed information and heavy manpower on cost management and difficulty in keeping relationship with construction planning, scheduling and progress management. The each cost items and unit prices which constitute of construction works are individually very important management factors but the relative weight for each items and prices have a difference on the contents and conditions of each conditions of each construction works. In consideration of this structural mechanism of cost determination, this research is aimed at examining the critical factors affecting the construction cost determination and propose and verify a new cost forecasting model which is more simple and efficient and also keeps the accuracy of cost management.

• Journal of Internet Computing and Services
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• v.5 no.5
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• pp.17-26
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• 2004

Mobile multicast schemes are classified into remote subscription and bi-directional tunneling. While the former scheme has much overhead in the maintenances of multicast tree, the latter suffers from inefficient routing. In this paper, we propose dynamic mobile multicast routing (DMMR) scheme, which is operated on the basis of cost functions related with forwarding cost and tree reconstruction cost, Basically DMMR intends to find lower cost between forwarding cost and tree reconstruction cost. Forwarding cost is the cost of tunneling multicast packets from home agent, and tree reconstruction cost is the joining cost of foreign agent to multicast group. In the case that a mobile host moves to the other area, its foreign agent calculates cost functions related with forwarding cost and tree reconstruction cost. If forwarding cost is higher than tree reconstruction cost, foreign agent joins to multicast group and reconstructs the multicast tree. Accordingly, foreign agent can dynamically adapt remote subscription or bi-directional tunneling, Our scheme provides more stable multicast service to the mobile hosts regardless of the movements of mobile host and the number of mobile group members.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.12
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• pp.870-872
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• 2014

In this paper, we devise a cost function by considering the energy consumption rate and the remaining energy of a peer. Then, we propose a parent peer selection method that chooses the least cost peer in the system in a distributed manner. On the contrary to the conventional method that makes each peer select the least cost neighbor as a parent peer, the proposed method chooses a parent peer using the swarm intelligence formed among a set of peers. Therefore, the proposed method could extent distributedly the number of peers searched for parent peer selection. Thus, compared to the conventional method, the proposed method increases the probability of being a parent peer as the cost of a peer becomes smaller with less operational load.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3095-3111
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• 2018

Spectrum sensing (SS) is one of the fundamental tasks for cognitive radio. In SS, decisions can be made via comparing the test statistics with a threshold. Conventional adaptive algorithms for SS usually adjust their thresholds according to the radio environment. This paper concentrates on the issue of adaptive SS whose threshold is adjusted based on the Markovian behavior of primary user (PU). Moreover, Bayesian cost is adopted as the performance metric to achieve a trade-off between false alarm and missed detection probabilities. Two novel adaptive algorithms, including Markov Bayesian energy detection (MBED) algorithm and IMBED (improved MBED) algorithm, are proposed. Both algorithms model the behavior of PU as a two-state Markov process, with which their thresholds are adaptively adjusted according to the detection results at previous slots. Compared with the existing Bayesian energy detection (BED) algorithm, MBED algorithm can achieve lower Bayesian cost, especially in high signal-to-noise ratio (SNR) regime. Furthermore, it has the advantage of low computational complexity. IMBED algorithm is proposed to alleviate the side effects of detection errors at previous slots. It can reduce Bayesian cost more significantly and in a wider SNR region. Simulation results are provided to illustrate the effectiveness and efficiencies of both algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1732-1750
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• 2016

Recently, Peer-to-Peer (P2P) live streaming assisted by the cloud computing has attracted considerable attention to improve the reliability of the P2P such as the resilience to peer churn and the shortage of upload capacity. The cost of cloud-assistance is comprised of the number of requests issued to the cloud and the amount of data fetched from the cloud. In this paper, we propose three techniques to reduce the cost of such a cloud-assistance.More concretely, in the proposed method, 1) each peer which lost its parent in the overlay can find a new parent by referring to the information registered in the cloud, 2) several peers which proactively fetch chunks from the cloud are dynamically invested, and 3) the number of requests issued to the cloud is reduced by allowing peers to fetch a collection of chunks using a single request. The performance of the proposed method is evaluated by simulation. The simulation results indicate that it reduces the cost of conventional scheme by 46% while guaranteeing the quality of live streaming service.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2A
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• pp.139-148
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• 2011

This paper presents the minimum-cost network selection scheme which determines the transmission instance in the multi-band maritime communication system, so that the shipment-related real-time information can be transmitted within the maximum allowed period. The transmission instances and the corresponding network selection process are modeled by a Markov Decision Process (MDP), for the channel model in the 2-state Markov chain, which can be solved by stochastic dynamic programming. It derives the minimum-cost network selection rule, which can reduce the network cost significantly as compared with the straight-forward scheme with a periodic transmission.

• Journal of KIISE:Information Networking
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• v.29 no.4
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• pp.397-404
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• 2002

We propose a heuristic distributed unicast routing algorithm for minimizing the total cost of the path in a point to point network with do]ay constraint. The algorithm maintains a delay vector and a cost vector about the network states and finds the path using this information. In this paper, we show that our algorithm always finds a delay-constrained path if such a path exists and has O(│E│) message complexity(│E│is the number of links in the network). Also, simulation results show that the proposed algorithm has better cost performance than other delay-constrained routing algorithms.

• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.17-24
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• 2009

Increasing use of information system has led to larger amount of developing expenses and demands on software. Until recent days, the model using regression analysis based on statistical algorithm has been used. However, Machine learning is more investigated now. This paper estimates the software cost using SVR(Support Vector Regression). a sort of machine learning technique. Also, it finds the best set of parameters applying immune algorithm. In this paper, software cost estimation is performed by SVR based on immune algorithm while changing populations, memory cells, and number of allele. Finally, this paper analyzes and compares the result with existing other machine learning methods.

• Asia pacific journal of information systems
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• v.33 no.2
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• pp.298-317
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• 2023

This study is about the attitudes and intentions of consumers considering the usage of O2O application (app) under the COVID-19 situation. By integrating TAM and TPB as a theoretical background, we selected VPC (various product choice) and PII (product information intensity) as new functional external variables that have a positive effect on new system called O2O commerce. We also applied the transaction cost theory to investigate the obstacle of O2O business. We conducted a survey of consumers in large cities in the Korean market. As a result of this study, it was found that the more O2O app users recognized the influence of SN (subject norms), the more useful O2O app was, the more it led to a change in attitude and usage intention was positively significant. In addition, as the O2O app was easy to use and useful, and the SN was recognized, the user's attitude was positive. On the other hand, it was also found that the transaction cost that consumers have to pay had a negative effect on usage intention. Additionally, VPC and PII have been shown to positively influence on usefulness of O2O apps.

• The Journal of Information Systems
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• v.19 no.3
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• pp.35-58
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• 2010

Portal sites have been providing diverse services to attract new users and retain existing customers. Recently, they also added new services and increased quality of the services they provide to secure more customers. It is, however, not clear how people actually react to such activities. We wanted to understand the mechanism associated with users' continued usage intention of current Portal site. We assumed search, e-mail, information, community, e-commerce services as key services provided by most Portal sites and considered valuable by many customers. The quality of these services may directly affect users' continued usage intention. However, we can also assume that attractive alternatives and switching cost may have some influence on users' continued usage intention. Therefore, in this study, key variables pertaining to the quality of key services provided by Portal sites, attractive alternatives, and switching cost were examined to explain the dynamics of users' continued usage intention. An empirical study based on 891 survey responses showed the importance of the quality of key services for users' continued usage intention. Switching cost also demonstrated strong association with users' continued usage intention. However, attractive alternatives did not show a significant association with users' continued usage intention. We also found that the variable attractive alternatives moderated the relationship between the quality of search service and users' continued usage intention and the relationship between the quality of information service and users' continued usage intention. On the other hand, the variable switching cost showed a moderating effect on the relationship between the quality of e-mail service and users' continued usage intention and the relationship between the quality of community service and users' continued usage intention. This study implies that Portal sites need to make efforts not only to improve the quality of key services but also to consider attractiveness of other Portal sites' services and switching cost to secure more customers.