• Proceedings of the Technology Innovation Conference
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• 기술경영경제학회 2005년도 제26회 동계학술발표회 논문집
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• pp.124-139
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• 2005

In the early stage, the radio communication industry was widely accepted as a monopoly industry, so it has been controled and managed by government. But the advanced technology in Information and Technology industry has led constant increase of demand and dramatic change of communication market. Furthermore it is expected that frequency resource is to be short by market change due to wire-wireless integration. That is why the effort to utilize and manage limited frequency resource efficiently is being executed around the world. Not only newly developing and allocating the spectrum but also reallocating the existing spectrum important are, since transforming inefficiently used existing spectrum to new service can increase producer's surplus and social welfare. The economic approach to valuate the spectrum and spectrum usage right is necessary different from the traditional cost based approach, and through this approach I expect active transaction of spectrum. In this paper the real option methodology is used for valuation of spectrum, considering spectrum user's option right based on future revenue. In detail, the matter of withdrawing and reallocating the existing analog radio broadcasting spectrum is evaluated in this paper, The digitalization of a broadcasting service is widely spreaded around the world in terms of technology and service utility, and analog TV broadcasting has already been decided to be transformed to digital TV broadcasting. It was planned to convert analog radio broadcasting to DAB service before adopting DMB service, but nowadays this issue is not on the table anymore. However if the increasing demand of digital voice and broadcasting service is considered, this kind of research to valuate a spectrum is needed urgently. The result of this research shows that when the redeployment of spectrum is done, social welfare will increases. The point of the reallocation time and value are suggested by the monte carlo simulation through ROVM. In this paper, I use real option to valuate the spectrum and provide the point of the reallocation time and reasonable guideline, and moreover, the suitable information of this paper is expected to reduce risk and loss in policy practice.

• Journal of KIISE:Computing Practices and Letters
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• 제13권7호
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• pp.520-533
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• 2007

The CRM(Customer Relationship Management) is the business strategy model for higher profits and competitive power of the enterprise in a new business environment. The large-scale customer response service technique uses internet, e-mail, SMS (Short Message Service), Telephony service, DM(Direct Mail) by customer channel point. Recently, business model diversify for new contract and retaining existing customer to the effort for a profitable model of business. This paper is based on Avaya PDS(Predictive Dialing System) model for CRM bond center. If the number of "available" agents are less than the number of inbound channels, then there may be real-time response problems in PDS system implemented. The Organization cannot afford to have many agents in available mode because of the high cost of manpower. This paper provides two contributions to the study. First, we present Call Object Management Mechanism of Customer Channel integration for reduce outbound consulting and reduce CallBack data in the PDS. Second, we design and implement the proposed system. Our simulation results show analysis of old model and proposed model. The proposed model can be efficiently used in Large-scale CRM.

• The Journal of the Korea Contents Association
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• 제9권8호
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• pp.41-48
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• 2009

As enactment and enforcement of capital markets integration law, investment banks are going to be appeared in our financial market and be able to provide payment services. To provide these kinds of services, investment banks need to be participated in the financial network. As the financial network enormously affect the economy, the operation of the network will require a variety of risk managements. In this paper we define operational risk management criteria for the financial network such as security, in-time response, economical efficiency and stability to be required for the healthy economy and propose the configuration of the financial network system based on virtual private networks for investment banks to provide payment services. Finally we analyze that the proposed VPN configuration for financial networks has high security and in-time response with the cost and operation effective.

• Journal of Korea Society of Industrial Information Systems
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• 제19권5호
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• pp.81-90
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• 2014

It is an element certainly required for the cost reduction of a company that forward and reverse logistics chain are unified and constitutes a resource closed-loop supply chain (CLSC). In this study, the inventory control which unifies inventory of distribution centers (DCs) of forward logistics and processing center of reverse logistics in the CLSC environment is proposed. The inventory system model for newly-constructed CLSC considers the JIT(Just-In-Time) delivery from the processing center to the manufacturer, including the making of decisions on whether to wait for the arrival of end-of-life products or to back-order necessary products for manufacturer when the supply of end-of-life products at the processing center via the returning center is insufficient for the demands of the manufacturers. The validity of the proposed model was verified using the genetic algorithm (GA). In order that a parameter might investigate the effect which it has on a solution, the simulation was carried out for priGA(priority-based GA) on three kinds of parameter conditions. Moreover, mhGA(modified hybrid GA) to which a parameter is adjusted for every Study on Reducing Logistics Costs and Inventory Control System according to facilities integration in the Closed-Loop Supply Chain Environment generation, the simulation was carried out to a four-kind numerical example.

• Journal of Construction Engineering and Project Management
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• 제9권2호
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• pp.1-24
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• 2019

Poor project performance has been noted as the bane in the construction industry globally. This paper sought to investigate, by way of literature, the performance patterns of construction projects in Kenya since independence (1963-2018). This was informed by reports of undesirable project performance in the industry. This descriptive study used available studies previously done in this subject area. In sum, literature is replete with evidence on a myriad of challenges facing the execution of projects. The study established that generally, the project performance is poor and has assumed a chronic trajectory spanning over five decades. On average, the findings reveal that 35-60% of projects initiated in Kenya face cost overruns while time overrun is most severe with 35-73% projects overrunning their schedule. In addition, the findings problematize the issue of plurality of performance measurement regimes in the construction industry. Here, it was observed that no singular construct exists to objectively measure the various facets that constitute the 'health' of a project. This paper has contributed to the body of knowledge by examining the performance patterns in Kenya for over fifty years while at the same time identifying the bottlenecks inherent in projects execution. Importantly, the conceptual performance efficiency framework derived in the current study presents a paradigm shift in the monitoring and evaluation of projects. To this end, an in-depth analysis is recommended on the interaction of efficiency enablers in the buildup of performance efficiency index (PEI). Similarly, a further inquiry is recommended on the integration and impact of the proposed framework in the management of projects.

• Journal of Intelligence and Information Systems
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• 제18권1호
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• pp.125-141
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• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, total misclassification cost is more affected by FNE rather than FPE. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.

• Journal of the Korean Geotechnical Society
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• 제26권3호
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• pp.59-68
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• 2010

Systematic risk management is necessary in grand scaled urban construction because of the existence of complicated and various risk factors. Problems of obstructions, adjacent structures, safety, environment, traffic and geotechnical properties need to be solved because urban construction is progressed in limited space not as general earthwork. Therefore the establishment of special risk management system is necessary to manage not only geotechnical properties but also social and cultural uncertainties. This research presents the technique analysis by the current state of risk management technique. Risk factors were noticed and the importance of each factor was estimated through survey. The systemically categorized database was established. Risk extraction module, matrix and score module were developed based on the database. Expected construction budget and time distribution can be computed by Monte Carlo analysis of probabilities and influences. Construction budgets and time distributions of before and after response can be compared and analyzed 80 the risks are manageable for entire whole construction time. This system will be the foundation of standardization and integration. Procurement, efficiency improvement, effective time and resource management are available through integrated management technique development and application. Conclusively decrease in cost and time is expected by systemization of project management.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제22권7호
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• pp.1021-1029
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• 2018

The marine buoys are operated in various domains, which are navigation route and danger maker, weather and environment monitoring, military strategical element, etc. If the marine buoy is damaged, there consumes many cost and time for recovery or replacement, because of severe environmental condition, and causes a risk possibility of secondary accident. In this paper, we developed an active monitoring and approach alarm providing system using trail cameras and AIS for protection for the marine buoys. To do this, we analyzed existing researches and similar systems, extracted requirements for enhancement, and designed the system architecture that applied the enhanced elements. The main considerations of system enhancement are: integration of AIS and trail cameras, adopting of phased alarm technique by approaching ships, applying of selective communication module, conducting the image processing of ships for providing alarm, and applying thermal cameras. After that, we developed the system using designed architecture and verified effectiveness of the system based on laboratory or field-level tests.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• 제32권5호
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• pp.459-467
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• 2014

The importance of fusion and association using established spatial information has increased gradually with the production and supply of various spatial data by public institutions. The generation of necessary spatial information without field investigation and additional surveying can reduce time, labor, and financial costs. However, the study of the integration of the newly introduced road name address map with the digital map is very insufficient. Even though the use of the road name address map is encouraged for public works related to spatial information, the digital map is still widely used because it is the national basic map. Therefore, in this study, building matching and update were performed to associate the digital map with the road name address map. After geometric calibration using the block-based ICP (Iterative Closest Point) method, multi-scale corresponding pair searching with hierarchical clustering was applied to detect the multi-type match. The accuracy assessment showed that the proposed method is more than 95% accurate and the matched building layer of the two maps is useful for the integrated application and fusion. In addition, the use of the road name address map, which carries the latest and most frequently renewed data, enables cost-effective updating of new buildings.

• Korean Journal of Remote Sensing
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• 제36권6_1호
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• pp.1277-1290
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• 2020

Water resources which is formed of surface and groundwater, are considered as one of the pivotal natural resources worldwide. Since last century, the rapid population growth as well as accelerated industrialization and explosive urbanization lead to boost demand for groundwater for domestic, industrial and agricultural use. In fact, better management of groundwater can play crucial role in sustainable development; therefore, determining accurate location of groundwater based groundwater potential mapping is indispensable. In recent years, integration of machine learning techniques, Geographical Information System (GIS) and Remote Sensing (RS) are popular and effective methods employed for groundwater potential mapping. For determining the status of the integrated approach, a systematic review of 94 directly relevant papers were carried out over the six previous years (2015-2020). According to the literature review, the number of studies published annually increased rapidly over time. The total study area spanned 15 countries, and 85.1% of studies focused on Iran, India, China, South Korea, and Iraq. 20 variables were found to be frequently involved in groundwater potential investigations, of which 9 factors are almost always present namely slope, lithology (geology), land use/land cover (LU/LC), drainage/river density, altitude (elevation), topographic wetness index (TWI), distance from river, rainfall, and aspect. The data integration was carried random forest, support vector machine and boost regression tree among the machine learning techniques. Our study shows that for optimal results, groundwater mapping must be used as a tool to complement field work, rather than a low-cost substitute. Consequently, more study should be conducted to enhance the generalization and precision of groundwater potential map.