• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.182-182
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• 2017

Many small island nations rely on groundwater as their only other source of freshwater in addition to rainwater harvesting. The volume of groundwater resource of small island nations are further limited by their smaller surface area and specific hydrogeology. The rapid growth of population and tourism has led to increasing water demands and pollution of available groundwater resources. The predicted climate change effects pose significant threats to the already vulnerable freshwater lens of small islands in the form of rise in sea level, coastal inundation, saltwater intrusion, varied pattern of precipitation leading to droughts and storm surges. The effects of climate change are further aggravated by manmade stresses like increased pumping. Thus small island water resources are highly threatened under the effects of climate change. But due to the limited technical and financial capacity most of the small island developing states were unable to conduct detailed technical investigations on the effects of climate change on their water resources. In this study, we investigate how well small island countries are preparing for climate change. The current state of freshwater resources, impacts of predicted climate change along with adaptation and management strategies planned and implemented by small island countries are reviewed. Proper assessment and management practices can aid in sustaining the groundwater resources of small islands under climate change.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.5
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• pp.285-297
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• 2014

This paper presents the results of an investigation into bi-directional communication in spectrum sharing-based cognitive radio (Bi-CR) systems. A Bi-CR system can increase the spectral efficiency significantly by sharing the spectrum and through the bi-directional use of spatial resources for two-way communication. On the other hand, the primary user experiences more interference from the secondary users in a Bi-CR system. Satisfying the interference constraint by simply reducing the transmission power results in performance degradation for secondary users. In addition, secondary users also experience self-interference from echo channels due to full duplexing. These imperfections may weaken the potential benefits of the Bi-CR system. Therefore, a new way to overcome these defects in the Bi-CR system is needed. To address this need, this paper proposes some novel power allocation schemes for the Bi-CR system. This contribution is based on two major analytic environments, i.e., noise-limited and interference-limited environments, for providing useful analysis. This paper first proposes an optimal power allocation (OPA) scheme in a noise-limited environment and then analyzes the achievable sum rates. This OPA scheme has an effect in the noise-limited environment. In addition, a power allocation scheme for the Bi-CR system in an interference-limited environment was also investigated. The numerical results showed that the proposed schemes can achieve the full duplexing gain available from the bi-directional use of spatial resources.

• Microbiology and Biotechnology Letters
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• v.49 no.4
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• pp.478-484
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• 2021

Cellular resources including transcriptional and translational machineries in bacteria are limited, yet microorganisms depend upon them to maximize cellular fitness. Bacteria have evolved strategies for using resources economically. Regulatory networks for the gene expression system enable the cell to synthesize proteins only when necessary. At the same time, regulatory interactions enable the cell to limit losses when the system cannot make a cellular profit due to fake substrates. Also, the architecture of the gene expression flow can be advantageous for clustering functionally related products, thus resulting in effective interactions among molecules. In addition, cellular systems modulate the investment of proteomes, depending upon nutrient qualities, and fast-growing cells spend more resources on the synthesis of ribosomes, whereas nonribosomal proteins are synthesized in nutrient-limited conditions. A deeper understanding of cellular mechanisms underlying the optimal allocation of cellular resources can be used for biotechnological purposes, such as designing complex genetic circuits and constructing microbial cell factories.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.165-165
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• 2023

Streamflow prediction is a critical task in water resources management and essential for planning and decision-making purposes. However, the streamflow prediction is challenging due to the complexity and non-linear nature of hydrological processes. The transfer learning is a powerful technique that enables a model to transfer knowledge from a source domain to a target domain, improving model performance with limited data in the target domain. In this study, we apply the transfer learning using the Informer model, which is a state-of-the-art deep learning model for streamflow prediction. The model was trained on a large-scale hydrological dataset in the source basin and then fine-tuned using a smaller dataset available in the target basin to predict the streamflow in the target basin. The results demonstrate that transfer learning using the Informer model significantly outperforms the traditional machine learning models and even other deep learning models for streamflow prediction, especially when the target domain has limited data. Moreover, the results indicate the effectiveness of streamflow prediction when knowledge transfer is used to improve the generalizability of hydrologic models in data-sparse regions.

• Water for future
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• v.35 no.5
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• pp.43-50
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• 2002

The Yellow River Basin located in the Northern part of China is well-known not only as the seriously limited water sources but the greatest sediment-carrying stream in the world. The observed annual average sediment concentration in this area is $37.6kg/\textrm{mm}^3$, and 3.1% of the water volume is occupied by sediments. Due to the reason, water development has been extremely limited and it has been appeared as one of the most difficult problems in reservoir development and management. The major obstacle to surface water uses is reservoir sedimentation so that it has been strongly requested to seek the method managing sediment by optimal fashion. To solve this problem, KOWACO (Korea Water Resources Corporation) has developed various methods on the optimal reservoir management schemes including sediment management for the Upper Fenhe Basin Reservoir System at the cooperation project with Chinese. Information Variable Dynamic Programming. which is one of them, was developed for the reservoir sediment management and a set of non-dominated solutions are generated to choose the best alternative in water supply and reservoir sediment objective problem.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.465-466
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• 2005

• The Korean Nurse
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• v.20 no.3 s.111
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• pp.58-65
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• 1981

It is desirable to utilize the community health resources to manage community health services effectively with limited personnel, time and facilities. This study was conducted to determine the utilization of community health resources. During the period o

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1596-1599
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• 2010

Group method of data handling neural networks model (GMDH-NNM) is used to estimate daily pan evaporation (PE) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$), mean relative humidity ($RH_{mean}$) and sunshine duration (SD). And, for the performances of GMDH-NNM, it is composed of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of GMDH-NNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily PE data using GMDH-NNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as pan evaporation modeling can be generalized using GMDH-NNM.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.483-486
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• 2015

The objective of this study is to develop generalized regression neural networks (GRNN) model for estimating daily solar radiation using limited weather variables at Champaign and Springfield stations in Illinois. The best input combinations (one, two, and three inputs) can be identified using GRNN model. From the performance evaluation and scatter diagrams of GRNN model, GRNN 3 (three input) model produces the best results for both stations. Results obtained indicate that GRNN model can successfully be used for the estimation of daily global solar radiation at Champaign and Springfield stations in Illinois. These results testify the generation capability of GRNN model and its ability to produce accurate estimates in Illinois.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.3-32
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• 2008

The potential deep geothermal resources span a wide range of heat sources from the earth, including not only the more easily developed, currently economic hydrothermal resources; but also the earth's deeper, stored thermal energy, which is present anywhere. At shallow depths of 3,000~10,000m, the coincidence of substantial amounts heat in hot rock, fluids that heat up while flowing through the rock and permeability of connected fractures can result in natural hot water reservoirs. Although conventional hydrothermal resources which contain sufficient fluids at high temperatures and geo-pressures are used effectively for both electric and nonelectric applications in the world, they are somewhat limited in their location and ultimate potential for supplying electricity. A large portion of the world's geothermal resource base consists of hot dry rock(HDR) with limited permeability and porosity, an inadquate recharge of fluids and/or insufficient water for heat transport. An alternative known as engineered or enhanced geothermal systems(EGS), to dependence on naturally occurring hydrothermal reservoirs involves human intervention to engineer hydrothermal reservoirs in hot rocks for commercial use. Therefore EGS resources are with enormous potential for primary energy recovery using an engineered heat mining technology, which is designed to extract and utilize the earth's stored inexthermal energy. Because EGS resources have a large potential for the long term, United States focused his effort to provide 100GW of 24-hour-a-day base load electric-generating capacity by 2050.