• Journal of electromagnetic engineering and science
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• v.17 no.2
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• pp.105-107
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• 2017

The self-biasing circuit through a feedback resistor is applied to a gallium nitride (GaN) distributed power amplifier (PA) monolithic microwave circuit (MMIC). The self-biasing circuit is a useful scheme for biasing depletion-mode compound semiconductor devices with a negative gate bias voltage, and is widely used for common source amplifiers. However, the self-biasing circuit is rarely used for PAs, because the large DC power dissipation of the feedback resistor results in the degradation of output power and power efficiency. In this study, the feasibility of applying a self-biasing circuit through a feedback resistor to a GaN PA MMIC is examined by using the high operation voltage of GaN high-electron mobility transistors. The measured results of the proposed GaN PA are the average output power of 41.1 dBm and the average power added efficiency of 12.2% over the 6-16 GHz band.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.133-138
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• 2009

When sensor networks are deployed in open environments, an adversary may compromise some sensor nodes and use them to inject false sensing reports. False report attack can lead to not only false alarms but also the depletion of limited energy resources in battery powered networks. The Interleaved hop-by-hop authentication (IHA) scheme detects such false reports through interleaved authentication. In IHA, when a report is forwarded to the base station, all nodes on the path must spend energies on receiving, authenticating, and transmitting it. An dversary can spend energies in nodes by using the methods as a relaying attack which uses macro. The Adversary aim to drain the finite amount of energies in sensor nodes without sending false reports to BS, the result paralyzing sensor network. In this paper, we propose a countermeasure using fuzzy logic from the Denial of Service(DoS) attack and show an efficiency of energy through the simulataion result.

• Journal of the Korea Society for Simulation
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• v.16 no.4
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• pp.57-65
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• 2007

In many sensor network applications, sensor nodes are deployed in open environments, and hence are vulnerable to physical attacks, potentially compromising the node's cryptographic keys. False sensing report can be injected through compromised nodes, which can lead to not only false alarms but also the depletion of limited energy resource in battery powered networks. Fan Ye et al. proposed that statistical en-route filtering scheme(SEF) can do verify the false report during the forwarding process. In this scheme, the choice of a partition value represents a trade off between resilience and energy where the partition value is the total number of partitions which global key pool is divided. If every partition are compromised by an adversary, SEF disables the filtering capability. Also, when an adversary has compromised a very small portion of keys in every partition, the remaining uncompromised keys which take a large portion of the total cannot be used to filter false reports. We propose a fuzzy-based adaptive partitioning method in which a global key pool is adaptively divided into multiple partitions by a fuzzy rule-based system. The fuzzy logic determines a partition value by considering the number of compromised partitions, the energy and density of all nodes. The fuzzy based partition value can conserve energy, while it provides sufficient resilience.

• Journal of the Korea Society for Simulation
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• v.16 no.2
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• pp.27-35
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• 2007

When sensor networks are deployed in open environments, all the sensor nodes are vulnerable to physical threat. An attacker can physically capture a sensor node and obtain the security information including the keys used for data authentication. An attacker can easily inject false reports into the sensor network through the compromised node. False report can lead to not only false alarms but also the depletion of limited energy resource in battery powered sensor networks. To overcome this threat, Fan Ye et al. proposed that statistical on-route filtering scheme(SEF) can do verify the false report during the forwarding process. In this scheme, the choice of a security threshold value is important since it trades off detection power and energy, where security threshold value is the number of message authentication code for verification of false report. In this paper, we propose a fuzzy rule-based system for security threshold determination that can conserve energy, while it provides sufficient detection power in the SEF based sensor networks. The fuzzy logic determines a security threshold by considering the probability of a node having non-compromised keys, the number of compromised partitions, and the remaining energy of nodes. The fuzzy based threshold value can conserve energy, while it provides sufficient detection power.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.339-346
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• 2022

Recently, the resource depletion and climate change problem caused by the massive usage of fossil fuels for electric power generation has become a critical issue worldwide. According to this issue, interest in renewable energy resources that can replace fossil fuels is increasing. Especially, photovoltaic power has gaining much attention because there is no risk of resource exhaustion compared to other energy resources and there are low restrictions on installation of photovoltaic system. In order to use the power generated by the photovoltaic system efficiently, a more accurate photovoltaic power forecasting model is required. So far, even though many machine learning and deep learning-based photovoltaic power forecasting models have been proposed, they showed limited success in terms of interpretability. Deep learning-based forecasting models have the disadvantage of being difficult to explain how the forecasting results are derived. To solve this problem, many studies are being conducted on explainable artificial intelligence technique. The reliability of the model can be secured if it is possible to interpret how the model derives the results. Also, the model can be improved to increase the forecasting accuracy based on the analysis results. Therefore, in this paper, we propose an explainable photovoltaic power forecasting scheme based on BiLSTM (Bidirectional Long Short-Term Memory) and SHAP (SHapley Additive exPlanations).

• Journal of the Korea Organic Resources Recycling Association
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• v.24 no.4
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• pp.11-20
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• 2016

Depletion of natural resources and reduction of greenhouse gas emissions are an important issue which we have to solve. The recycling of waste has emerged as a global concern. In Korea, the development of cost-effective treatment and recycling technologies also need to be improved. In this study, we compared and analyzed the cost per unit of treatment and recycling of organic waste, and presented an effective recycling scheme. We investigated the current status of treatment and costs for six types of organic wastes from 80 workplaces, including organic wastewater treatment sludge, processed organic sludge, and plant residues. In addition, environmental costs for greenhouse gas reduction were calculated. It's an economic way that organic waste is composted and used as cement additives. In particular, the economic analysis was done by realistic results of the survey target companies. In conclusion, in order for reliable processing and recycling of organic wastes, wastewater treatment sludge and sewage sludge need to be classified based on hazard characteristics. Finally, technical difficulties need to be further resolved such as odors, leachate, and debris on recycling organic wastes.

• Biomolecules & Therapeutics
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• v.21 no.1
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• pp.29-34
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• 2013

The tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) is a member of the tumor necrosis factor family of cytokines. TRAIL selectively induces apoptotic cell death in various tumors and cancer cells, but it has little or no toxicity in normal cells. Agonism of TRAIL receptors has been considered to be a valuable cancer-therapeutic strategy. However, more than 85% of primary tumors are resistant to TRAIL, emphasizing the importance of investigating how to overcome TRAIL resistance. In this report, we have found that nemadipine-A, a cell-permeable L-type calcium channel inhibitor, sensitizes TRAIL-resistant cancer cells to this ligand. Combination treatments using TRAIL with nemadipine-A synergistically induced both the caspase cascade and apoptotic cell death, which were blocked by a pan caspase inhibitor (zVAD) but not by autophagy or a necrosis inhibitor. We further found that nemadipine-A, either alone or in combination with TRAIL, notably reduced the expression of survivin, an inhibitor of the apoptosis protein (IAP) family of proteins. Depletion of survivin by small RNA interference (siRNA) resulted in increased cell death and caspase activation by TRAIL treatment. These results suggest that nemadipine-A potentiates TRAIL-induced apoptosis by down-regulation of survivin expression in TRAIL resistant cells. Thus, combination of TRAIL with nemadipine-A may serve a new therapeutic scheme for the treatment of TRAIL resistant cancer cells, suggesting that a detailed study of this combination would be useful.

• Journal of Soil and Groundwater Environment
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• v.10 no.2
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• pp.44-51
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• 2005

Fractional composition and mobility of some heavy metals in sediments from Okdong stream are investigated. The fractional scheme for heavy metals in the sediment was established for five chemically defined heavy metal forms as adsorbed fraction, carbonate fraction, reducible fraction, organic fraction, and residual fraction. The most abundant fraction heavy metals in the sediments is reducible and secondly abundant is organic fraction. Adsorbed fraction is minor part of the total heavy metals. Mobilization of heavy metals in the sediments from Okdong stream occur $19.8{\sim}56.7%$ of total cadmium concentrate. The most abundant fraction of the sediment metal is organic fraction in Cu, Pb metals investigated. Labile fraction of sediment metals are $0.5{\sim}48.5%$ of total Zn, $2.6{\sim}48.1%$ of total Pb, and $0.2{\sim}36.9%$ of total Cu, respectively. Most of labile fraction consists of reducible fraction for Cd, Zn, adsorbed fraction for Pb, reducible fraction for Cu, adsorbed fraction for Ni. The Mobilization of Zn and Cu is most likely to occur when oxygen depletes and that of Pb and Ni occurs when physical impact, oxygen depletion and pH reduction.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.53-61
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• 2010

In wireless sensor networks(WSNs) individual sensor nodes are subject to security compromises. An adversary can physically capture sensor nodes and obtain the security information. And the adversary injects false reports into the network using compromised nodes. If undetected, these false reports are forwarded to the base station. False reports injection attacks can not only result in false alarms but also depletion of the limited amount of energy in battery powered sensor nodes. To combat these false reports injection attacks, several filtering schemes have been proposed. The statistical en-routing filtering(SEF) scheme can detect and drop false reports during the forwarding process. In SEF, The number of the message authentication codes(threshold) is important for detecting false reports and saving energy. In this paper, we propose a dynamic threshold determination method for energy efficient SEF using fuzzy-logic in wireless sensor networks. The proposed method consider false reports rate and the number of compromised partitions. If low rate of false reports in the networks, the threshold should low. If high rate of false reports in networks, the threshold should high. We evaluated the proposed method’s performance via simulation.