• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.7
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• pp.666-673
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• 2008

To construct the accurate radio satellite navigation system, the efficient communication each satellite with the ground station is very important. Throughout the communication, the orbit of each satellite can be corrected, and those information will be used to analyze the satellite satus by the operator. Since there are limited resources of ground station, the schedule of antenna's azimuth and elevation angle should be optimized. On the other hand, the satellite in the medium earth orbit does not pass the same point of the earth surface due to the rotation of the earth. Therefore, the antenna pass schedule must be updated at the proper moment. In this study, Q learning approach which is a form of model-free reinforcement learning and genetic algorithm are considered to find the optimal antenna schedule. To verify the optimality of the solution, numerical simulations are conducted.

• KDI Journal of Economic Policy
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• v.14 no.2
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• pp.189-203
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• 1992

Any money model should address the most important phenomenon of a monetary economy, which is the phenomenon of the rate of return dominance. Even if the holding returns on financial or nonfinancial assets are higher than the rate of return on fiat money holding, which is typically zero, people still hold and use money. In a period of accelerating inflation, number of dominating assets increases continuously, yet people continue to hold and use money. Wallace's (1980) overlapping generations model cannot address the rate of return dominance phenomenon. His model does not capture the mediun of exchange role of fiat money. In this paper, an overlapping types model of fiat money is constructed, in which different types of consumers have different preferences on different types of goods, are endowed with different types of goods, are located at seperated regions, and live for only two periods. In this model, people hold and use money despite the dominating assets, even if inflation accelates. Money in this case serves as a pure medium of exchange, whereas in Wallace's model, money serves as a pure store of value, and money disappears if a dominating asset exists. An interesting feature of the overlapping types model presented in this paper is that money does not provide a cheap approximation to an idealized and efficient real allocation. A monetary economy is always superior to a nonmonetary economy, because money helps overcome the incompleteness of the overlapping types friction. In a monetary economy, however, a pareto optimal allocation cannot always be achieved, because money cannot always overcome the overlapping types friction itself. Therefore, with the criterion of optimality of real allocations, the monetary economy is more optimal than a nonmonetary economy but less optimal than a complete Arrow-Debreu economy. This feature has important implications on macro modelling. Because of the difficulty in introducing money into a macro model in an essential and endogenous manner as in the overlapping types model of this paper, a macro model typically ignores money and studies real allocations without the money factor. The possible inefficiencies of a monetary economy, relative to a complete real Arrow-Debreu economy, may indicate differences in real allocations between the two models.

• Journal of KIISE:Databases
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• v.33 no.2
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• pp.201-213
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• 2006

A time-series database is a set of time-series data sequences, each of which is a list of changing values of the object in a given period of time. Subsequence matching is an operation that searches for such data subsequences whose changing patterns are similar to a query sequence from a time-series database. This paper addresses a performance issue of time-series subsequence matching. First, we quantitatively examine the performance degradation caused by the window size effect, and then show that the performance of subsequence matching with a single index is not satisfactory in real applications. We argue that index interpolation is fairly useful to resolve this problem. The index interpolation performs subsequence matching by selecting the most appropriate one from multiple indexes built on windows of their inherent sizes. For index interpolation, we first decide the sites of windows for multiple indexes to be built. In this paper, we solve the problem of selecting optimal window sizes in the perspective of physical database design. For this, given a set of query sequences to be peformed in a target time-series database and a set of window sizes for building multiple indexes, we devise a formula that estimates the cost of all the subsequence matchings. Based on this formula, we propose an algorithm that determines the optimal window sizes for maximizing the performance of entire subsequence matchings. We formally Prove the optimality as well as the effectiveness of the algorithm. Finally, we perform a series of extensive experiments with a real-life stock data set and a large volume of a synthetic data set. The results reveal that the proposed approach improves the previous one by 1.5 to 7.8 times.

• Proceedings of the KSPS conference
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• 1996.10a
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• pp.109-116
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• 1996

In this paper, I would like to explore the possibility that the nature of place assimilation can be captured in terms of the OCP within the Optimality Theory (Mccarthy & Prince 1999. 1995; Prince & Smolensky 1993). In derivational models, each assimilatory process would be expressed through a different autosegmental rule. However, what any such model misses is a clear generalization that all of those processes have the effect of avoiding a configuration in which two consonantal place nodes are adjacent across a syllable boundary, as illustrated in (1):(equation omitted) In a derivational model, it is a coincidence that across languages there are changes that have the result of modifying a structure of the form (1a) into the other structure that does not have adjacent consonantal place nodes (1b). OT allows us to express this effect through a constraint given in (2) that forbids adjacent place nodes: (2) OCP(PL): Adjacent place nodes are prohibited. At this point, then, a question arises as to how consonantal and vocalic place nodes are formally distinguished in the output for the purpose of applying the OCP(PL). Besides, the OCP(PL) would affect equally complex onsets and codas as well as coda-onset clusters in languages that have them such as English. To remedy this problem, following Mccarthy (1994), I assume that the canonical markedness constraint is a prohibition defined over no more than two segments, $\alpha$ and $\beta$: that is, $^{*}\{{\alpha, {\;}{\beta{\}$ with appropriate conditions imposed on $\alpha$ and $\beta$. I propose the OCP(PL) again in the following format (3) OCP(PL) (table omitted) $\alpha$ and $\beta$ are the target and the trigger of place assimilation, respectively. The '*' is a reminder that, in this format, constraints specify negative targets or prohibited configurations. Any structure matching the specifications is in violation of this constraint. Now, in correspondence terms, the meaning of the OCP(PL) is this: the constraint is violated if a consonantal place $\alpha$ is immediately followed by a consonantal place $\bebt$ in surface. One advantage of this format is that the OCP(PL) would also be invoked in dealing with place assimilation within complex coda (e.g., sink [si(equation omitted)k]): we can make the constraint scan the consonantal clusters only, excluding any intervening vowels. Finally, the onset clusters typically do not undergo place assimilation. I propose that the onsets be protected by certain constraint which ensures that the coda, not the onset loses the place feature.

• Journal of the Korea Society of Computer and Information
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• v.18 no.2
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• pp.117-126
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• 2013

Path planning is an essential problem to make virtual characters navigate in many applications including computer games. In many cases, multiple characters move in a group and qualitative aspects of planned paths are emphasized rather than optimality unlike Robotics. In this paper, we propose a two-level path planning algorithm in which the global path is planned for a single character specified as a leader and then the local path is planned to avoid dynamic obstacles while the group following this path. The space for group movement is achieved in the form of square grid array called a grid window. Member characters are located relatively to the leader within a space and moved. The static environment is reduced to the configuration space of this grid window to generate a roadmap on which a grid window can move. In local path planning, only the leader avoids dynamic obstacles by using an artificial potential field and the rest of members are located relatively to the leader in the grid window, which reduces computational load. Efficient algorithms to implement the proposed planning methods are introduced. The simulation results show that a group can handle with dynamic obstacles effectively while moving along the planned path for a static environment.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.250-251
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• 2023

The pallet, typically a form of tertiary packaging, is a flat structure used as a base for the unitization of goods in the supply chain. In addition, standard pallets such as T-11 and T-12 are used throughout the logistics industry to reduce the cost and enhance the efficiency of transportation. However, in the case of special cargo, it is impossible to handle such cargo using a standard pallet due to its size and weight, so many have developed and are now using their customized pallet. Therefore, this study suggests a pallet size optimization method to calculate the optimal pallet size, which minimizes the loss of space on a pallet. The main input features are the specifications and the storage quantity of each cargo, and the optimization method that has modified the Neighborhood Search Algorithm calculates the optimal pallet size. In order to verify the optimality of the developed algorithm, a comparative analysis has been conducted through simulation.

• KDI Journal of Economic Policy
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• v.26 no.2
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• pp.63-104
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• 2004

Economists have long been involved in various studies, theoretical and empirical, on the economic gains from innovative activities and as their outcome, intellectual properties. In Korea, however, research in this field has experienced rather slow progress, partly due to the lack of data availability and the awareness of its importance. This study attempts to measure the economic impact of patents on market value of firms from a microeconomic point of view. Analyses are performed to examine the ex-ante market valuation of patent acquisition activities by investigating the effect of patent acquisitions on daily stock prices as well as on annual market values. The study on the effect of a disclosure of granted patents on daily stock prices reveals that the economic value of a firm's patent acquisition is fairly high. The study on listed firms also reveals that a firm's patent registration stock has a positive and statistically significant effect on its year-end market value. Therefore, it can be concluded that the analysis performed in this study supports the validity of Korea's current patent system. The result, however, does not guarantee the optimality of current system. Studies on various aspects of intellectual property should follow to shape the system into a socially optimal one.

• Journal of KIISE:Information Networking
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• v.35 no.6
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• pp.521-528
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• 2008

Such conventional maritime communication technologies as radio have short some comings in their transmission quality. It can be overcome by wireless channels provided by satellites such as INMARSAT, which nevertheless suffer from the high costs. In this paper, we propose a novel technology resolving the above problems, featuring in the establishment of maritime communication networks with multi-hop structures. The inter vessel and ship-to- shore networks previously modeled after MANET are remodeled by SANET (Ship Ad Hoc Networks) in the present work. Fan-shaped Search Zone Routing (FSR) protocol also is presented, which utilizes not only static geographical information including the locations of ports and the navigations of courses but also the unique characteristics of ships in terms of mobile nodes. The FSR finds the fan-shaped search zone on which the shortest path is located. The performance of LAR protocol is compared with that of FSR in several ways. First, FSR does not make use of a type of control packets as beaconing data, resulting in a full utilization of the bandwidth of the wireless channels. Second, the delivery rate by the FSR is 100% for the fan-shaped search zone includes at least one route between source and destination nodes on its border line, where as that of LAR has been turned out to be 64%. Third, the optimality of routes searched by the FSR is on a 97% level. Of all, the FSR shows a better performance than LAR by about 50%.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.103-114
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• 2005

The transit fare resulted from the renovation of public transit system in Seoul is basically determined based on the distance-based fare policy (DFP). In DFP, the total fare a passenger has to pay for is calculated by the basic-transfer-premium fare decision rule. The fixed amount of the basic fare is first imposed when a passenger get on a mode and it lasts within the basic travel distance. The transfer fare is additionally imposed when a passenger switches from one mode to another and the fare of the latter mode is higher than the former. The premium fare is also another and the fare of the latter begins to exceed the basic travel distance and increases at the proportion of the premium fare distance. The purpose of this study is to propose an algorithm for finding K number of paths, paths that are sequentially sorted based on total amount of transit fare, under DFP of the idstance-based fare policy. For this purpose, the link mode expansion technique is proposed in order to save notations associated with the travel modes. Thus the existing K shortest path algorithms adaptable for uni-modal network analysis are applicable to the analysis for inter-modal transportation networks. An optimality condition for finding the K shortest fare routes is derived and a corresponding algorithms is developed. The case studies demonstrate that the proposed algorithm may play an important role to provide diverse public transit information considering fare, travel distance, travel time, and number of transfer.

• Communications of Mathematical Education
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• v.37 no.1
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• pp.65-84
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• 2023

The method of Lagrange multipliers, one of the most fundamental algorithms for solving equality constrained optimization problems, has been widely used in basic mathematics for artificial intelligence (AI), linear algebra, optimization theory, and control theory. This method is an important tool that connects calculus and linear algebra. It is actively used in artificial intelligence algorithms including principal component analysis (PCA). Therefore, it is desired that instructors motivate students who first encounter this method in college calculus. In this paper, we provide an integrated perspective for instructors to teach the method of Lagrange multipliers effectively. First, we provide visualization materials and Python-based code, helping to understand the principle of this method. Second, we give a full explanation on the relation between Lagrange multiplier and eigenvalues of a matrix. Third, we give the proof of the first-order optimality condition, which is a fundamental of the method of Lagrange multipliers, and briefly introduce the generalized version of it in optimization. Finally, we give an example of PCA analysis on a real data. These materials can be utilized in class for teaching of the method of Lagrange multipliers.