• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.1035-1038
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• 2008

Network mobility (NEMO) has been studied extensively due to its potential applications in military and public transportation. NEMO Basic Support Protocol (NBSP) [1], the current NEMO standard based on mobile IPv6, can be readily deployed using the existing mobile IPv6 infrastructure. However, for Nested network mobility, multi-level tunnel and too many Binding Update packets results in substantial performance overhead, generally known as route sub-optimality, especially in the bottleneck root mobile router (root-MR) and Access Router. In this paper, we propose a route optimization mechanism for nested network mobility management to reduce the overhead of root-MR. In this system, Mobile Router (MR) has a cache that stores Mobile Network Nodes' (MNN) information, Correspondent Nodes' (CN) information for every MNN，and the attachments information with its subnet MRs. Home Agent performs Binding Update with CNs responsible for MRs. Through this mechanism, the number of tunnel is limited between CN and MR and the overhead of root-MR is reduced obviously.

• Journal of Biosystems Engineering
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• v.42 no.1
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• pp.23-43
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• 2017

Purpose: As application-specific wireless sensor networks are gaining popularity, this paper discusses the development and field performance of the GHAN, a greenhouse area network system to monitor, control, and access greenhouse microenvironments. GHAN, which is an upgraded system, has many new functions. It is an intelligent wireless sensor and actuator network (WSAN) system for next-generation greenhouses, which enhances the state of the art of greenhouse automation systems and helps growers by providing them valuable information not available otherwise. Apart from providing online spatial and temporal monitoring of the greenhouse microclimate, GHAN has a modified vapor pressure deficit (VPD) fuzzy controller with an adaptive-selective mechanism that provides better control of the greenhouse crop VPD with energy optimization. Using the latest soil-matrix potential sensors, the GHAN system also ascertains when, where, and how much to irrigate and spatially manages the irrigation schedule within the greenhouse grids. Further, given the need to understand the microclimate control dynamics of a greenhouse during the crop season or a specific time, a statistical assessment tool to estimate the degree of optimality and spatial variability is proposed and implemented. Methods: Apart from the development work, the system was field-tested in a commercial greenhouse situated in the region of Punjab, India, under different outside weather conditions for a long period of time. Conclusions: Day results of the greenhouse microclimate control dynamics were recorded and analyzed, and they proved the successful operation of the system in keeping the greenhouse climate optimal and uniform most of the time, with high control performance.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1069-1078
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• 2018

Demand response (DR) programs give opportunity to consumers to manage their electricity bills. Besides, distribution system operator (DSO) is interested in using DR programs to obtain technical and economic benefits for distribution network. Since small consumers have difficulties to individually take part in the electricity market, an entity named demand response provider (DRP) has been recently defined to aggregate the DR of small consumers. However, implementing DR programs face challenges to fairly allocate benefits and payments between DRP and DSO. This paper presents a procedure for modeling the interaction between DRP and DSO based on a bilevel programming model. Both DSO and DRP behave from their own viewpoint with different objective functions. On the one hand, DRP bids the potential of DR programs, which are load shifting and load curtailment, to maximize its expected profit and on the other hand, DSO purchases electric power from either the electricity market or DRP to supply its consumers by minimizing its overall cost. In the proposed bilevel programming approach, the upper level problem represents the DRP decisions, while the lower level problem represents the DSO behavior. The obtained bilevel programming problem (BPP) is converted into a single level optimizing problem using its Karush-Kuhn-Tucker (KKT) optimality conditions. Furthermore, point estimate method (PEM) is employed to model the uncertainties of the power demands and the electricity market prices. The efficiency of the presented model is verified through the case studies and analysis of the obtained results.

• Asia Marketing Journal
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• v.15 no.3
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• pp.141-157
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• 2013

Managing customers based on customer equity (CE) has emerged as the most effective way of doing business because of its ability to foster profitable customer relationship management (CRM) through appropriate marketing activities. Most research studies provide conceptual and empirical evidence of the positive link between CE and firm performance. However, regarding this possibility, it has been suggested by some researchers that this link may not hold true for other firms with different firmographic factors, such as firm growth rate, size, and resources. As previous research emphasizes that marketing managers should implement a strategy based on their unique business environment, our study addresses this issue by extending the framework to a different industry setting to investigate the impact of CE on firm performance. We develop a model for examining the relationship between the firm's estimated CE and firm performance by each time period using a distributed lagged model. Then, we investigate the effect of CE on the firm's profitability using a regression analysis. Finally, even though CRM is in increasing demand and firms are focusing on the customer as an asset, we conclude that there is a limited condition for this positive effect of CE. When the life cycle was divided by growth rate, CE was shown to have a distinctive effect on profit. In the case of a high-growth stage, the effect of CE on profit is positive because of its potential customer base, whereas the effect is not significant in a low-growth stage. That is, when the business environment is saturated and the firms are no longer competing in the market, CRM may not be effective. In other words, a long-term performance orientation may not be as effective as previously believed. This research contributes to the previous literature, providing a counterintuitive suggestion that firm managers should be cautious about implementing a CRM strategy and should allocate resources properly in terms of their resource capabilities and ability depending on their situation.

• 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.