• Journal of Sensor Science and Technology
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• v.29 no.6
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• pp.365-368
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• 2020

As a green and abundant source of energy, H2 has attracted the attention of researchers for use in different applications. Nevertheless, it is highly flammable, and because of its significantly small size, extreme attention is needed to detect its leakage. In this review, we discuss different effects of noble metals on the H2 gas response and performance of metal oxide-based gas sensors. In this regard, we discuss the effects of noble metals, in combination with metal oxides, on H2 gas detection. The catalytic activity towards H2 gas and the formation of heterojunctions with metal oxides are the main contributions of noble metals to the sensing improvement of H2 gas sensors. Furthermore, in the special case of Pd and somewhat Pt, the formation of PdHx and PtHx also affects the H2 sensing performance. This review paper provides useful information for researchers working in the field of H2 gas detection.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.414-417
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• 2008

This paper presents the design and analysis of 2.45GHz Low-IF Mixer using CMOS 0.18um. The Mixer is implemented by using the Gilbert-type configuration, current bleeding technique, and the resonating technique for the tail capacitance. And the design of this Double Balance Mixer is based on its lineaity since it is important in the interference cancellation system. The low flicker noise mixer is implemented by incorporating a double balanced Gilber-type configuration, the RF leakage-less current bleeding technique, and Cp resonating technique. The proposed mixer has a simulated conversion gain of 16dB a simulated IIP3 of -3.3dBm and P1dB is -19dBm. A simulated noise figure of 6.9dB at l0MHz and a flicker corner frequency of 510kHz while consuming only 10.65mW od DC power. The layout of Mixer for one-chip design in a 0.18-um TSMC process has 0.474mm$\times$0.39 mm size.

• The KIPS Transactions:PartA
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• v.14A no.3 s.107
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• pp.147-150
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• 2007

This paper describes a new low-swing inverter for low power consumption. To reduce a power consumption, an output voltage swing is in the range from 0 to VDD-2VTH. This can be done by the inverter structure that allow a full swing or a swing on its input terminal without leakage current. Using this low-swing voltage technology, we proposed a low-power 16$\times$16 bit parallel multiplier. The proposed circuits are designed with Samsung 0.35$\mu$m standard CMOS process at a 3.3V supply voltage. The validity and effectiveness are verified through the HSPICE simulation.. Compared to the previous works, this circuit can reduce the power consumption rate of 17.3% and the power-delay product of 16.5%.

• The KIPS Transactions:PartA
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• v.15A no.4
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• pp.211-216
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• 2008

In this paper we fabricated and measured the $0.26{\mu}m$ NMOSFET with wet gate oxide and nitride oxide gate to compare that the charateristics of hot carrier effect, charge to breakdown, transistor Id_Vg curve, charge trapping, and SILC(Stress Induced Leakage Current) using the HP4145 device tester. As a result we find that the characteristics of nitride oxide gate device better than wet gate oxide device, especially hot carrier lifetime(nitride oxide gate device satisfied 30 years, but the lifetime of wet gate oxide was only 0.1 year), variation of Vg, charge to breakdown, electric field simulation and charge trapping etc.

• Biomolecules & Therapeutics
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• v.20 no.4
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• pp.399-405
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• 2012

Silver nanoparticles (AgNPs) are widely used nanoparticles and they are mainly used in antibacterial and personal care products. In this study, we evaluated the effect of AgNPs on cell death induction in the murine dendritic cell line DC2.4. DC2.4 cells exposed to AgNPs showed a marked decrease in cell viability and an induction of lactate dehydrogenase (LDH) leakage in a time- and dose-dependent manner. In addition, AgNPs promoted reactive oxygen species (ROS)-dependent apoptosis and AgNP-induced ROS triggered a decrease in mitochondrial membrane potential. The activation of the intracellular signal transduction pathway was also observed in cells cultured with AgNPs. Taken together, our data demonstrate that AgNPs are able to induce a cytotoxic effect in DCs through ROS generation. This study provides important information about the safety of AgNPs that may help in guiding the development of nanotechnology applications.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.65-71
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• 2017

Since existing Internet of Things(IoT) is vulnerable, it may cause property damage due to the information leakage. Especially, the smart door lock system built on the IoT can cause more damage. To solve these problems, this paper classify the data generated by the sensor according to the condition and send an alarm message to the user's smartphone through Google Cloud Message (GCM). We made it possible to check the images in real time through the smartphone application and control the door lock using the TCP / IP protocol. Also, we applied OTP-Based Matrix SEED algorithm to door lock system to improve security.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2547-2555
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• 2021

The frequency of reactor coolant leakage is expected to increase over the lifetime of a nuclear power plant owing to degradation mechanisms, such as flow-acceleration corrosion and stress corrosion cracking. When loss of coolant accidents (LOCAs) occur, several parameters change rapidly depending on the size and location of the cracks. In this study, leak flow during LOCAs is predicted using a deep fuzzy neural network (DFNN) model. The DFNN model is based on fuzzy neural network (FNN) modules and has a structure where the FNN modules are sequentially connected. Because the DFNN model is based on the FNN modules, the performance factors are the number of FNN modules and the parameters of the FNN module. These parameters are determined by a least-squares method combined with a genetic algorithm; the number of FNN modules is determined automatically by cross checking a fitness function using the verification dataset output to prevent an overfitting problem. To acquire the data of LOCAs, an optimized power reactor-1000 was simulated using a modular accident analysis program code. The predicted results of the DFNN model are found to be superior to those predicted in previous works. The leak flow prediction results obtained in this study will be useful to check the core integrity in nuclear power plant during LOCAs. This information is also expected to reduce the workload of the operators.

• Journal of Soil and Groundwater Environment
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• v.24 no.1
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• pp.1-9
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• 2019

This study presents a technical perspective to the fate characteristics of phenol and m-cresol, which represent some of the most common organic chemicals found in chemical spill accidents, and likely to persist in soil and groundwater due to their highly stable physicochemical properties. Some cases of domestic and foreign chemical accidents linked to phenol and m-cresol contamination were compiled. Due to their low organic carbon-water partitioning coefficient (Koc), phenol and m-cresol tend to migrate into groundwater and remained as dissolved phase. On the other hands, phenol and m-cresol can be readily decomposed by microbes in soil and groundwater under appropriate conditions. Therefore, the fate characteristics of these chemicals are highly contingent on environmental conditions. Thus, if a great quantity of leakage is occurred by chemical accidents, the up-to-date and correct information about fate characteristics taking into account both the chemical and environmental conditions is greatly needed to minimized the potential hazards from these chemicals.

• Journal of Convergence for Information Technology
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• v.9 no.5
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• pp.21-26
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• 2019

Various pipes are buried in the city as needed, such as water pipes, gas pipes and hydrogen pipes. As the time passes, buried pipes becomes aged due to crack, etc. these pipes has the risk of accidents such as explosion and leakage. To prevent the risks, many pipes are repaired or replaced, but the location of the pipes can also be changed. Failure to identify the location of the altered pipe may cause an accident by touching the pipe. In this paper, we propose a method to detect buried pipes by gathering the GPR images by using GPR and Learning with Faster R-CNN. Then experiments was carried out by raw data sets and data sets augmentation applied to increase the amount of images.

• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.27-33
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• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.