• Journal of environmental and Sanitary engineering
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• v.18 no.3 s.49
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• pp.11-20
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• 2003

There are two ways of reducing air pollution. One is the approach of the pollutant source control and the other one is the traffic demand decreasing approach. This study is focusing on the approach of land use planning and optimal location of urban facilities because those are the basic cause to generate transportation demands. So, the purpose of this study would be to analyze the changes of NOx and CO distribution on environmental air by functional hierarchy of urban roads and to make evaluation model of 'Transportation-Land Use -Air Pollution'. It will contribute to improve the air pollution level at same actual traffic generation according to different location.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.131-135
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• 2008

In this paper, we deal with a hierarchical location-allocation problem in designing the broadband convergence networks (BcN). The objective is to minimize the total cost of switch and cable while satisfying the quality of service (QoS). We formulate the problem as an integer programming model and develop the Tabu Search (TS) heuristic algorithm to find a good feasible solution within a reasonable time limit. Initial solution is obtained by using the tree structure. Three neighborhood generation mechanisms are used by local search heuristic: insertion, switch up, and switch down. In order to demonstrate the effectiveness of the proposed algorithm, we generate lower bounds from nonlinear QoS relaxation problem. We present promising computational results of the proposed solution procedures.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1709-1712
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• 2002

In the microcell- or picocell-based system the frequent movements of the mobile bring about excessive traffics into the networks. A mobile location estimation mechanism can facilitate both efficient resource allocation and better QoS provisioning through handoff optimization. Existing location estimation schemes consider only LOS model and have poor performance in presence of multi- path and shadowing. In this paper we study a novel scheme which can increase estimation accuracy by considering NLOS environment

• Spatial Information Research
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• v.5 no.1
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• pp.11-26
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• 1997

The purpose of this study is to analyze the locational characteristics of bank branch offices in Kangnam-Gu, Seoul by using Geographic Information System. The number of bank branch offices have sharply increased due to financial liberalization, while the scale of them is getting smaller. The procedure of this research has four steps. First, the spatial distribution of bank branch offices in Seoul is analyzed by the places and time. Second, the spatial variations of bank offices in dong districts of Seoul is explained by factor analysis and multiple regression analysis. Third, the location-allocation model which is embedded within network module in Arc/Info is applied in order to find out optimal location of bank offices in Kangnam-Gu. Finally, the grid module is used in creating the potential surface map for locational sites of new bank branch offices The factors to affect the location of the bank offices contain mainly economic variables including local tax, collUl1ercial area, total establismnent and total employment. The actual locational pattern of bank offices is similar to the idealized locational pattern proposed by the function of min-distance in location-allocation models. In conclusion, this study shows that spatial analysis functions may potentially be improved using GIS technologies. However in order to analyze the location of bank offices more precisely, it should be found out the way to collect more appropriate data, construct computerized base maps, and investigate consumer behaviour and behavioural characteristics of bank themselves..

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.1
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• pp.108-116
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• 2022

Supply in military operations has a significant impact on overall combat capability and efficiency. Therefore, modernization of military logistics is underway to ensure rapid and accurate distribution. And, effective warehouse management is paramount. This paper proposes a new product allocation model that uses a genetic algorithm. The model considers order frequency and mass of products because the military equipment is usually heavier than available products. A computer simulation shows that products are assigned to optimal locations and reduce the consumed energy for forklifts by more than 25 % with similar travel time. Also, we show the superiority of genetic algorithm by comparing them with other algorithms.

• Journal of the Korean Geographical Society
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• v.46 no.3
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• pp.366-381
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• 2011

A competitive location problem in discrete space is computationally difficult to solve in general because of its combinatorial feature. In this paper, we address an alternative method for solving competitive location problems in discrete space, particularly employing deterministic allocation. The key point of the suggested method is to reducing the number of predefined potential facility sites associated with the size of problem by utilizing geometric concepts. The suggested method was applied to the existing broadband marketplace with increasing competition as an application. Specifically, we compared computational results and spatial configurations of two different sized problems: the problem with the original potential sites over the study area and the problem with the reduced potential sites extracted by a GIS-based geometric algorithm. The results show that the competitive location model with the reduced potential sites can be solved more efficiently, while both problems presented the same optimal locations maximizing customer capture.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.112-122
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• 2016

Cognitive radio (CR) is considered an attractive technology to deal with the spectrum scarcity problem. Multi-radio access technology (multi-RAT) can improve network capacity because data are transmitted by multiple RANs (radio access networks) concurrently. Thus, multi-RAT embedded in a cognitive radio network (CRN) is a promising paradigm for developing spectrum efficiency and network capacity in future wireless networks. In this study, we consider a new CRN model in which the primary user networks consist of heterogeneous primary users (PUs). Specifically, we focus on the energy-efficient resource allocation (EERA) problem for CR users with a special location coverage overlapping region in which heterogeneous PUs operate simultaneously via multi-RAT. We propose a two-tier crossover genetic algorithm-based search scheme to obtain an optimal solution in terms of the power and bandwidth. In addition, we introduce a radio environment map to manage the resource allocation and network synchronization. The simulation results show the proposed algorithm is stable and has faster convergence. Our proposal can significantly increase the energy efficiency.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.946-952
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• 2014

Mobility prediction is one of hot topics using location history information. It is useful for not only user-level applications such as people finder and recommendation sharing service but also for system-level applications such as hand-off management, resource allocation, and quality of service of wireless services. Most of current prediction techniques often use a set of significant locations without taking into account possible location information changes for prediction. Markov-based, LZ-based and Prediction by Pattern Matching techniques consider interesting locations to enhance the prediction accuracy, but they do not consider interesting location changes. In our paper, we propose an algorithm which integrates the changing or emerging new location information. This approach is based on Active LeZi algorithm, but both of new location and all possible location contexts will be updated in the tree with the fixed depth. Furthermore, the tree will also be updated even when there is no new location detected but the expected route is changed. We find that our algorithm is adaptive to predict next location. We evaluate our proposed system on a part of Dartmouth dataset consisting of 1026 users. An accuracy rate of more than 84% is achieved.

• The Journal of Information Systems
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• v.27 no.1
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• pp.89-110
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• 2018

Purpose There is much information in customer reviews, but finding key information in many texts is not easy. Business decision makers need a model to solve this problem. In this study we propose a multi-topic sentiment analysis approach using Latent Dirichlet Allocation (LDA) for user-generated contents (UGC). Design/methodology/approach In this paper, we collected a total of 104,039 hotel reviews in seven of the world's top tourist destinations from TripAdvisor (www.tripadvisor.com) and extracted 30 topics related to the hotel from all customer reviews using the LDA model. Six major dimensions (value, cleanliness, rooms, service, location, and sleep quality) were selected from the 30 extracted topics. To analyze data, we employed R language. Findings This study contributes to propose a lexicon-based sentiment analysis approach for the keywords-embedded sentences related to the six dimensions within a review. The performance of the proposed model was evaluated by comparing the sentiment analysis results of each topic with the real attribute ratings provided by the platform. The results show its outperformance, with a high ratio of accuracy and recall. Through our proposed model, it is expected to analyze the customers' sentiments over different topics for those reviews with an absence of the detailed attribute ratings.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.11-22
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• 2007

This paper is to discuss analytical techniques to estimate demand sizes and volumes that determine optimal locations for multiple facilities for a given services. While demand size estimation is a core part of location modeling to enhance solution quality and practical applicability, the estimation method has been used in limited and restrict parts such as a single population centroid in a given larger census boundary area or small theoretical application experiments(e.s. census track and enumeration district). Therefore, this paper strives to develop an analytical estimation method of demand size that converts area based demand data to point based population weighted centroids. This method is free to spatial boundary units and more robust to estimate accurate demand volumes regardless of geographic boundaries. To improve the estimation accuracy, this paper uses house weighted value to the population centroid calculation process. Then the population weighted centroids are converted to individual demand points on a grid formated surface area. In turn, the population weighted centroids, demand points and network distance measures are operated into location-allocation models to examine their roles to enhance solution quality and applicability of GIS location models. Finally, this paper demonstrates the robustness of the weighted estimation method with the application of location-allocation models.