• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1481-1501
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• 2019

In opportunistic network, the behavior of a node is autonomous and has social attributes such as selfishness.If a node wants to forward information to another node, it is bound to be limited by the node's own resources such as cache, power, and energy.Therefore, in the process of communication, some nodes do not help to forward information of other nodes because of their selfish behavior. This will lead to the inability to complete cooperation, greatly reduce the success rate of message transmission, increase network delay, and affect the overall network performance. This article proposes a hybrid incentive mechanism (Mim) based on the Reputation mechanism and the Credit mechanism.The selfishness model, energy model (The energy in the article exists in the form of electricity) and transaction model constitute our Mim mechanism. The Mim classifies the selfishness of nodes and constantly pay attention to changes in node energy, and manage the wealth of both sides of the node by introducing the Central Money Management Center. By calculating the selfishness of the node, the currency trading model is used to differentiate pricing of the node's services. Simulation results show that by using the Mim, the information delivery rate in the network and the fairness of node transactions are improved. At the same time, it also greatly increases the average life of the network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.501-507
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• 2021

Neural networks with differentiable activation functions are differentiable with respect to input variables. We improve the approximation capability of neural networks by using the gradient and Hessian of neural networks to satisfy the differential equations of the problems of interest. We apply differential neural networks to the pricing of financial options, where stochastic differential equations and the Black-Scholes partial differential equation represent the differential relation of price of option and underlying assets, and the first and second derivatives of option price play an important role in financial engineering. The proposed neural network learns - (a) the sample paths of option prices generated by stochastic differential equations and (b) the Black-Scholes equation at each time and asset price. Experimental results show that the proposed method gives accurate option values and the first and second derivatives.

• Journal of the Korean Operations Research and Management Science Society
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• v.12 no.1
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• pp.157-157
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• 1987

Hydro-electric power generation from multi-purpose dams has been playing important roles in the electric power supply network in Korea. Although the total share of hydro power in national electricity supply now becomes very small, the peak-shaving and frequency control capability of hydro power helps the power company enormously in maintaining the quality of power. But since the company that builds and operates the multi-purpose dams in Korea has to sell all the electricity produced to the monopolistic utility, there have been various problems in justifying the investment, designing pricing mechanism, and controlling operations of the power plants. In addition, economic evaluation of the hydro power has been distorted by a variety of reasons and hence it has been very difficult to encourage effective development and utilization of national water resources. To make the problem worse, both parties are public companies with X-inefficiency problems. Thus, changing environment requires to reengineer the system that governs hydro power generation. We address the problems of Korean hydro-electric power generation system in four areas: the investment justification process, the operations decison right of the hydro power plants, the pricing of the purchased-power, and the negotiation of contract revision. Then we propose improvement directions of new hydro-electric power system in view of static and dynamic efficiency, X-inefficiency and equity.

• Korean Management Science Review
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• v.12 no.1
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• pp.157-173
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• 1995

Hydro-electric power generation from multi-purpose dams has been playing important roles in the electric power supply network in Korea. Although the total share of hydro power in national electricity supply now becomes very small, the peak-shaving and frequency control capability of hydro power helps the power company enormously in maintaining the quality of power. But since the company that builds and operates the multi-purpose dams in Korea has to sell all the electricity produced to the monopolistic utility, there have been various problems in justifying the investment, designing pricing mechanism, and controlling operations of the power plants. In addition, economic evaluation of the hydro power has been distorted by a variety of reasons and hence it has been very difficult to encourage effective development and utilization of national water resources. To make the problem worse, both parties are public companies with X-inefficiency problems. Thus, changing environment requires to reengineer the system that governs hydro power generation. We address the problems of Korean hydro-electric power generation system in four areas: the investment justification process, the operations decison right of the hydro power plants, the pricing of the purchased-power, and the negotiation of contract revision. Then we propose improvement directions of new hydro-electric power system in view of static and dynamic efficiency, X-inefficiency and equity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2231-2245
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• 2014

Cognitive Radio (CR) has very promising potential to improve spectrum utilization by allowing unlicensed Secondary Users (SUs) to access the spectrum dynamically without disturbing licensed Primary Users (PUs). Mitigating interference is a fundamental problem in CR scenarios. This is particularly problematic for deploying CR in cellular networks, when users are located at the cell edge, as the inter-cell interference mitigation and frequency reuse are critical requirements for both PUs and SUs. Further cellular networks require higher cell edge performance, then SUs will meet more challenges than PUs. To solve the performance decrease for SUs at the cell edge, a novel Dynamic Spectrum Allocation (DSA) scheme based on Game Theory is proposed in this paper. Full frequency reuse can be realized as well as inter-cell interference mitigated according to SUs' sensing, measurement and interaction in this scheme. A joint power/channel allocation algorithm is proposed to improve both cell-edge user experience and network performance through distributed pricing calculation and exchange based on game theory. Analytical proof is presented and simulation results show that the proposed scheme achieves high efficiency of spectrum usage and improvement of cell edge SUs' performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3966-3991
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• 2018

Due to the lack of visualization services and organic combinations between public and private buildings data, the usability of the basic map has remained low. To address this issue, this paper reports on a solution that organically combines public and private data while providing visualization services to general users. For this purpose, factors that can affect building prices first were examined in order to define the related data attributes. To extract the relevant data attributes, this paper presents a method of acquiring public information data and real estate-related information, as provided by private real estate portal sites. The paper also proposes a pretreatment process required for intelligent machine learning. This report goes on to suggest an intelligent machine learning algorithm that predicts buildings' value pricing and future value by using big data regarding buildings' spatial information, as acquired from a database containing building value attributes. The algorithm's availability was tested by establishing a prototype targeting pilot areas, including Suwon, Anyang, and Gunpo in South Korea. Finally, a prototype visualization solution was developed in order to allow general users to effectively use buildings' value ranking and value pricing, as predicted by intelligent machine learning.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.610-618
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• 2016

A green cognitive radio network (CRN), characterized by base stations (BSs) that conserve energy during sleep periods, is a promising candidate for realizing more efficient spectrum allocation. To improve the spectrum efficiency and achieve greener communication in wireless applications, we consider CRNs with an long term evolution advanced (LTE-A) structure and propose a novel energy-saving strategy. By establishing a type of preemptive priority queueing model with a single vacation, we capture the stochastic behavior of the proposed strategy. Using the method of matrix geometric solutions, we derive the performance measures in terms of the average latency of secondary user (SU) packets and the energy-saving degree of BSs. Furthermore, we provide numerical results to demonstrate the influence of the sleeping parameter on the system performance. Finally, we compare the Nash equilibrium behavior and social optimization behavior of the proposed strategy to present a pricing policy for SU packets.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.717-729
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• 2021

This paper examines the efficacy of the default risk factor in an emerging market context using the Fama-French five-factor model. Our aim is to test whether the Fama-French five-factor model augmented with a default risk factor improves the predictability of returns of portfolios sorted on the firm's characteristics as well as on industry. The default risk factor is constructed by estimating the probability of default using a hybrid version of dynamic panel probit and artificial neural network (ANN) to proxy default risk. This study also provides evidence on the temporal stability of risk premiums obtained using the Fama-MacBeth approach. Using a sample of 3,806 firm-year observations on non-financial listed companies of Pakistan over 2006-2015 we found that the augmented model performed better when tested across size-investment-default sorted portfolios. The investment factor contains some default-related information, but default risk is independently priced and bears a significantly positive risk premium. The risk premiums are also found temporally stable over the full sample and more recent sample period 2010-2015 as evidence by the Fama-MacBeth regressions. The finding suggests that the default risk factor is not a useless factor and due to mispricing, default risk anomaly prevails in the Pakistani equity market.

• Korean Management Science Review
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• v.15 no.1
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• pp.1-12
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• 1998

This paper discusses a new algorithm, the PAPANET (Pivot And Probe Algorithm for NETwork optimization), for solving linear, capacitated linear network flow problem (NPs), PAPANET is a variation and specialization of the Pivot And Probe Algorithm (PAPA) developed by Sethi and Thompson, published in 1983-1984. PAPANET first solves an initial relaxed NP (RNP) with all the nodes from the original problem and a limited set of arcs (possibly all the artificial and slack arcs). From the arcs not considered in the current relaxation, we PROBE to identify candidate arcs that violate the current solution's dual constraints maximally. Candidate arcs are added to the RNP, and this new RNP is solved to optimality. This candidate pricing procedure and pivoting continue until all the candidate arcs price unfavorably and all of the dual constraints corresponding to the other, so-called noncandidate arcs, are satisfied. The implementation of PAPANET requires significantly fewer arcs and less solution CPU time than is required by the standard network simplex method implementation upon which it is based. Computational tests on randomly generated NPs indicate that our PAPANET implementation requires up to 40-50% fewer pivots and 30-40% less solution CPU time than is required by the comparable standard network simplex implementation from which it is derived.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12B
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• pp.1099-1111
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• 2006

As W-CDMA R5(HSDPA) service became recently commercialized in Korea, there is increasing demand for new pricing methodology for the 3G mobile interconnection at the earliest possible time. However, it is hard to find any case of systematic study on it. In this paper, a synthetic investigation into the three aspects of new mobile telecommunication service - technology, market, and regulation - is conducted to verify the validity of new interconnection pricing methodology. As the findings of this research indicate, given the several technological limits of 3G, speed of mobile telecommunication industry evolution, the problem of verifying ex-ante regulations' validity, and the cases of some foreign countries, it is suggested that immediate revision of interconnection policy is not sensible and that the revision is more desirable to be postponed until the maturity of the 3G market or the adoption of All-IP network.