• Journal of Agricultural Extension & Community Development
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• v.5 no.1
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• pp.93-102
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• 1998

The objectives of the study were 1) to make the reasonable standard, 2) to select the objective and scientific method and process for the location-allocation of a new provincial capital city. The Main standard of location-allocation were suggested as follows ; 1) Integration of province 2) Convenience of Administration service 3) Accomodations of new provincial capital city 4) Balanced development by region. The validity of location-allocation were reviewed the population potentials and nodal accessibilities. The population potential was examined to find the maximum point of administrative demand, and the locationallocation model was examined to find the minimum point of the aggregated travel-cost to a proposed provincial government office. The nodal accessibilities measured in travel-time distance and actual values. Two major concerns in locating public facilities are efficiency and equity.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.6
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• pp.71-82
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• 2002

The purpose of this study is to develop a 3 dimensional spatial planning model (3DSPLAM) for facilities allocation and visual evaluation in improvement planning of rural village. For the model development, this study developed both planning layers and a modelling process for spatial planning of rural villages. The 3DSPLAM generates road networks and village facilities location automatically from built area plan map and digital elevation model generated by geographic information system. The model also simulates 3-dimensional villagescape for visual presentation of the planned results. The 3DSPLAM could be conveniently used for automatic allocation of roads, easy partition of land lots and reasonable locating of facilities. The planned results could be also presented in the stereoscopic models with varied viewing positions and angles.

• Korean Management Science Review
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• v.30 no.1
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• pp.167-181
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• 2013

We investigate the dynamic asset allocation problem under inflation risk when the wealth of an investor is constrained with minimum requirements. To capture the investor's risk preference, the CRRA utility function is considered and he maximizes his expected utility at predetermined date of the refund by participation in the financial market. The financial market is supposed to consist of three kinds of financial instruments which are a risk free asset, a risky asset, and an index bond. The role of an index bond is managing inflation risk represented by price process. The optimal wealth and the optimal asset allocation are derived explicitly by using the method to get the European call option pricing formula. From the numerical results, it is confirmed that the investments on index bond is high when the investor's wealth level is low. However, as his wealth increases, the investments on index bond decreases and he invests on risky asset more. Furthermore, the minimum wealth constraint induces lower investment on risky asset but the effect of the constraints is reduced as the wealth level increases.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.184-184
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• 2017

A nation-wide water-energy-food (WEF) nexus simulation model has been developed by the authors and successfully applied to South Korea to predict the sustainability of those three resources in the next 30 years. The model was also capable of simulating future scenarios of resources allocation based on priority rules aiming to maximize resources sustainability. However, the process was still relying on several assumptions and trial-and-error approach, which sometimes resulted in non-optimal solutions of resources allocation. In this study, an optimization module was introduced to enhance the model in generating optimal resources management rules. The objective of the optimization was to maximize the reliability index of resources by determining the resources' allocation and/or priority rules for each demand type that accordingly reflect the resources management policies. Implementation of the optimization module would result in balanced allocation and management of limited resources and assist the stakeholders in deciding resources' management plans, either by fulfilling the domestic production or by global trading.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.128-130
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• 2021

Smart cities collect data from thousands of IoT-based sensor devices for intelligent application-based services. Centralized cloud servers support application tasks with higher computation resources but introduce network latency. Fog layer-based data centers bring data processing at the edge, but fewer available computation resources and poor task allocation strategy prevent real-time data analysis. In this paper, tasks generated from devices are distributed as high resource and low resource intensity tasks. The novelty of this research lies in deploying a virtual node assigned to each cluster of IoT sensor machines serving a joint application. The node allocates tasks based on the task intensity to either cloud-computing or fog computing resources. The proposed Task Allocation Strategy provides seamless allocation of jobs based on process requirements.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.687-688
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• 2015

The objective of identifying the cause of inconsistency in determining priority of educational facility maintenance, any related factors were thoroughly identified and tested, to see if it has any effect on decision-making process in resource allocation for educational facilities. On the assumption that 'the more there are to be repaired/maintained and deferred, the higher the relevant cost will be, this will lead to a significant social loss. Accordingly, this study established a framework of determining resource allocation priority based on deferred maintenance and its related expenses. For doing so, it was required to determine relative ranking in terms of resource allocation within a pre-assigned school district, in consideration of the criticality of each deferred maintenance attribute/variable.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.226-238
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• 2024

Recently, multi-access edge computing (MEC) has emerged as a promising technology to alleviate the computing burden of vehicular terminals and efficiently facilitate vehicular applications. The vehicle can improve the quality of experience of applications by offloading their tasks to MEC servers. However, channel conditions are time-varying due to channel interference among vehicles, and path loss is time-varying due to the mobility of vehicles. The task arrival of vehicles is also stochastic. Therefore, it is difficult to determine an optimal offloading with resource allocation decision in the dynamic MEC system because offloading is affected by wireless data transmission. In this paper, we study computation offloading with resource allocation in the dynamic MEC system. The objective is to minimize power consumption and maximize throughput while meeting the delay constraints of tasks. Therefore, it allocates resources for local execution and transmission power for offloading. We define the problem as a Markov decision process, and propose an offloading method using deep reinforcement learning named deep deterministic policy gradient. Simulation shows that, compared with existing methods, the proposed method outperforms in terms of throughput and satisfaction of delay constraints.

• Korean Journal of Construction Engineering and Management
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• v.8 no.1 s.35
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• pp.87-95
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• 2007

If construction process operate composing work team by judgment manager's experience, possibility that progress of construction process becomes as inefficient is much. But, If produce optimal proposal of resources allocation, construction cost and duration through simulation at work plan step, work schedule because do quantification efficient operate do on. When plan construction process in this research, resources allocation by change of work team operation change, resources cost loss, total cost, optimal proposal of construction duration tentative plan of numerical formula model that can do simulation propose. Apply and revealed to apartment house framework which horizontal work area of process and vertical work area are composed as is each different construction process to verify proposed numerical formula model. Achieved efficiency than work team's operation results which apply numerical formula model that is presented in this research and enforce simulation is applied in actuality example construction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4661-4680
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• 2016

Cognitive radio (CR) technology is an effective solution to the spectrum scarcity issue. Collaborative spectrum sensing is known as a promising technique to improve the performance of spectrum sensing in cognitive radio networks (CRNs). However, collaborative spectrum sensing is vulnerable to spectrum data falsification (SSDF) attack, where malicious users (MUs) may send false sensing data to mislead other secondary users (SUs) to make an incorrect decision about primary user (PUs) activity, which is one of the key adversaries to the performance of CRNs. In this paper, we propose a coalition based malicious users detection (CMD) algorithm to detect the malicious user in CRNs. The proposed CMD algorithm can efficiently detect MUs base on the Geary'C theory and be modeled as a coalition formation game. Specifically, SSDF attack is one of the key issues to affect the resource allocation process. Focusing on the security issues, in this paper, we analyze the power allocation problem with MUs, and propose MUs detection based power allocation (MPA) algorithm. The MPA algorithm is divided into two steps: the MUs detection step and the optimal power allocation step. Firstly, in the MUs detection step, by the CMD algorithm we can obtain the MUs detection probability and the energy consumption of MUs detection. Secondly, in the optimal power allocation step, we use the Lagrange dual decomposition method to obtain the optimal transmission power of each SU and achieve the maximum utility of the whole CRN. Numerical simulation results show that the proposed CMD and MPA scheme can achieve a considerable performance improvement in MUs detection and power allocation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2233-2252
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• 2018

For the problem of cross-layer joint resource allocation (JRA) in the Long-Term Evolution (LTE)-Advanced standard using carrier aggregation (CA) technology, it is difficult to obtain the optimal resource allocation scheme. This paper proposes a joint resource allocation algorithm based on the weights of user's average quality of experience (JRA-WQOE). In contrast to prevalent algorithms, the proposed method can satisfy the carrier aggregation abilities of different users and consider user fairness. An optimization model is established by considering the user quality of experience (QoE) with the aim of maximizing the total user rate. In this model, user QoE is quantified by the mean opinion score (MOS) model, where the average MOS value of users is defined as the weight factor of the optimization model. The JRA-WQOE algorithm consists of the iteration of two algorithms, a component carrier (CC) and resource block (RB) allocation algorithm called DABC-CCRBA and a subgradient power allocation algorithm called SPA. The former is used to dynamically allocate CC and RB for users with different carrier aggregation capacities, and the latter, which is based on the Lagrangian dual method, is used to optimize the power allocation process. Simulation results showed that the proposed JRA-WQOE algorithm has low computational complexity and fast convergence. Compared with existing algorithms, it affords obvious advantages such as improving the average throughput and fairness to users. With varying numbers of users and signal-to-noise ratios (SNRs), the proposed algorithm achieved higher average QoE values than prevalent algorithms.