• Korean Journal of Pharmacognosy
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• v.43 no.2
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• pp.137-146
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• 2012

Dipsaci Radix (Dipsacaceae) has been used as a tonic, an analgesic, anti-inflammatory and anti-complement agents in traditional herbal medicine for the therapy of low back pain, knee pain, rheumatic arthritis, traumatic hematoma, and bone fractures. A high-performance liquid chromatography-electrospray ionization-mass spectrometric method (HPLC-ESI-MS) was developed for the simultaneous quantitation method of the five compounds from the herbal drug: asperosaponin VI and asperosaponin XII (terpene glycosides), sweroside, loganin and dipsacus A(iridoid glycosides). HPLC separation of the analytes was achieved on a C18 column ($150{\times}2.0$ mm i.d., 5 ${\mu}m$) using the aqueous methanol containing 5 mM ammonium acetate with gradient flow of the mobile phase. Detection of the analytes was performed by positive ion electrospray ionization, and selected ion monitoring was used for data acquisition using m/z corresponding molecular adduct ion, $[M+NH_4]^+$ and $[M+H]^+$. Calibration graphs showed good linearity ($r^2$=0.9997) over the wide range of the analytes; intra- and inter-day precisions (RSD, %) were within 9.1% and the accuracy between 94.0-111.0%. Recoveries of the analytes through the assay procedure were in the range of 93.7-110.8%. Analytical results of the herbal drugs of Dipsaci Radix (17 samples) show wide distribution of the five marker compounds and clear difference of the species from Phlomidis Radix (4 samples). The developed method would provide a practical guide for the quality control of the herbal drug.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3587-3594
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• 2022

A distributed high-speed data acquisition and monitoring system for the RF negative ion source at Huazhong University of Science and Technology (HUST) is developed, which consists of data acquisition, data forwarding and data processing. Firstly, the data acquisition modules sample physical signals at high speed and upload the sampling data with corresponding absolute-time labels over UDP, which builds the time correlation among different signals. And a special data packet format is proposed for the data upload, which is convenient for packing or parsing a fixed-length packet, especially when the span of the time labels in a packet crosses an absolute second. The data forwarding modules then receive the UDP messages and distribute their data packets to the real-time display module and the data storage modules by PUB/SUB-pattern message queue of ZeroMQ. As for the data storage, a scheme combining the file server and MySQL database is adopted to increase the storage rate and facilitate the data query. The test results show that the loss rate of the data packets is within the range of 0-5% and the storage rate is higher than 20 Mbps, both acceptable for the HUST RF negative ion source.

• Journal of Sensor Science and Technology
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• v.21 no.1
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• pp.46-52
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• 2012

The rapid water pollution in stream, river, lake and sea in recent years raises an urgent need for continuous monitoring and policymaking to conserve the global clean environment. In particular, the increasing water pollution in coastal marine areas adds to the importance of the environmental monitoring systems. In this paper, the mobile server is designed to gathers information of the water quality at coastal areas. The obtained data by the server is transmitted from field servers to the base station via multi-hop communication in wireless sensor network. The information collected includes dissolved oxygen(DO), hydrogen ion exponent(pH), temperature, etc. By the information provided the real-time monitoring of water quality at the coastal marine area. In addition, wireless sensor network-based flooding routing protocol was designed and used to transfer the measured water quality information efficiently. Telosb sensor node is programmed using nesC language in TinyOS platform for small scale wireless sensor network monitoring from a remote server.

• Journal of Radiation Protection and Research
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• v.28 no.3
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• pp.255-261
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• 2003

An environmental radiation monitoring system based on high pressurized ionization chamber has been used for on-line gamma monitoring surrounding the KAERI (Korea Atomic Energy Research Institute), which transmits the dose data measured from ion chamber on the site via radio frequency to a central processing computer and stores the transmitted real-time data. Although communication using radio frequency has several advantages such as effective and economical transmission, storage, and data process, there is one main disadvantage that data loss during transmission often happens because of unexpected communication problems. It is possible to restore the loss data by off-line such as floppy disk but the simultaneous process and display of current data as well as the backup data are very difficult in the present on-line system. In this work, a new electronic circuit board and the operation software applicable to the conventional environmental radiation monitoring system are developed and the automatical synchronization of the ion chamber unit and the central processing computer is carried out every day. This system is automatically able to restore the backup data within 34 hours without additional equipments and also display together the current data as well as the transmitted backup data after checking time flag.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.3
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• pp.393-405
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• 2018

Volatile organic compounds (VOCs) are representative air pollutants due to their detrimental effects on human health and their role in formation of secondary organic aerosols. Assessments and monitoring programs of VOCs using periodic grab sampling like Tedlar bags, canisters, and sorbent traps provide limited information, often with delay times of days or weeks. Selected ion flow tube mass spectrometry (SIFT-MS) is an emerging analytical technique for the real-time quantification of VOCs in air. It relies on chemical ionization of the VOCs molecules in air introduced into helium carrier gas using $H_3O^+$, $NO^+$, and $O_2{^+}$ precursor ions. Real-time monitoring method of 60 VOCs in the ambient air was developed using TO-15 standard gas mixture. Calibration curves, method detection limit, and quantitation reproducibility of the target compounds were tested. Dynamic dilution system was used to dilute standard gas from 0.174 ppbv to 100 ppbv, where calibration curves showed good linearity with $r^2$> 0.95 in all target analytes. Limit of detection (LOD) all compounds were sub ppbv, and some halogenated compounds showed pptv levels. Seven consecutive analyses of target compounds showed good repeatability with relative standard deviation of less than 10%. One day monitoring of VOCs in ambient air was conducted in Geoje. Average concentration of target VOCs in Geoje were relatively lower than other regions, among which formaldehyde showed the highest concentration ($15.4{\pm}5.78ppbv$). SIFT-MS provided good temporal resolution data (1 data per 3.2 minute), which can be used for identifying ephemeral short-term event. It is expected that SIFT-MS will be a versatile monitoring platform for VOCs in ambient air.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.12
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• pp.21-27
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• 2020

Lithium-ion batteries are the heart of energy-storing devices and electric vehicles. Owing to their superior qualities, such as high capacity and energy efficiency, they have become quite popular, resulting in an increased demand for failure/damage prevention and useable life maximization. To prevent failure in Lithium-ion batteries, improve their reliability, and ensure productivity, prognosticative measures such as condition monitoring through sensors, condition assessment for failure detection, and remaining useful life prediction through data-driven prognostics and health management approaches have become important topics for research. In this study, the residual useful life of Lithium-ion batteries was predicted using two efficient artificial recurrent neural networks-ong short-term memory (LSTM) and gated recurrent unit (GRU). The proposed approaches were compared for prognostics accuracy and cost-efficiency. It was determined that LSTM showed slightly higher accuracy, whereas GRUs have a computational advantage.

• Journal of Powder Materials
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• v.30 no.4
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• pp.310-317
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• 2023

Small-film-type ion sensors are garnering considerable interest in the fields of wearable healthcare and home-based monitoring systems. The performance of these sensors primarily relies on electrode capacitance, often employing nanocomposite materials composed of nano- and sub-micrometer particles. Traditional techniques for enhancing capacitance involve the creation of nanoparticles on film electrodes, which require cost-intensive and complex chemical synthesis processes, followed by additional coating optimization. In this study, we introduce a simple one-step electrochemical method for fabricating gold nanoparticles on a carbon nanotube (Au NP-CNT) electrode surface through cyclic voltammetry deposition. Furthermore, we assess the improvement in capacitance by distinguishing between the electrical double-layer capacitance and diffusion-controlled capacitance, thereby clarifying the principles underpinning the material design. The Au NP-CNT electrode maintains its stability and sensitivity for up to 50 d, signifying its potential for advanced ion sensing. Additionally, integration with a mobile wireless data system highlights the versatility of the sensor for health applications.

• Transactions of the Korean hydrogen and new energy society
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• v.31 no.5
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• pp.489-497
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• 2020

The Li-ion battery is considered to be one of the potential power sources for electric vehicles. In fact, the efficiency, reliability, and cycle life of Li-ion batteries are highly influenced by their thermal conditions. Therefore, a novel thermal management system is highly required to simultaneously achieve high performance and long life of the battery pack. Basically, thermal modeling is a key issue for the novel thermal management of Li-ion battery systems. In this paper, as a basic study for battery thermal modeling, temperature distributions inside the simple Li-ion battery pack (comprises of nine 18650 Li-ion batteries) under a 1C discharging condition were investigated using measurement and computational fluid dynamics (CFD) simulation approaches. The heat flux boundary conditions of battery cells for the CFD thermal analysis of battery pack were provided by the measurement of single battery cell temperature. The temperature distribution inside the battery pack were compared at six monitoring locations. Results show that the accurate estimation of heat flux at the surface of single cylindrical battery is paramount to the prediction of temperature distributions inside the Li-ion battery under various discharging conditions (C-rates). It is considered that the research approach for the estimation of temperature distribution used in this study can be used as a basic tool to understand the thermal behavior of Li-ion battery pack for the construction of effective battery thermal management systems.

• YAKHAK HOEJI
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• v.40 no.2
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• pp.141-148
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• 1996

GC/MS analysis of 27 controlled pesticides in herbal drugs was studied. Selected ion monitoring(sim) technique was applied to increase the GC/MS sensitivity. Typical peaks in th e mass spectrum of each pesticides were selected as quantitation, comfirmation or alternate ion. Twenty seven pesticides were divided into five groups according to their retention time and the peaks for SIM were programmed accordingly. The combination of two ionization methods, electron impact(EI)-SIM-MS and negative ion chemical ionization(NCI)-SIM-MS, were well-fitted for the detection, confirmation and quantitation of multiclass residual pesticides in herbal drugs.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1855-1856
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• 2008

본 연구에서는 공정 중에 민감하게 반응하는 플라즈마로부터 수집되는 이온에너지 분포(IED : Ion Energy Distribution)와 시계열 신경망 모델링을 결합한 플라즈마 감시 기술을 개발하였다. NIEA(Non-invasive ion analyzer)를 이용하여 IED를 측정하였으며, 모델링에 사용된 신경망은 자기 상관 시계열 신경망(A-NTS : Auto-Correlated Neural Time-Series)이다. 모델 개발을 위한 학습과 테스트 데이터로는 Duty ratio 100%에서 수집한 IED를 이용하였으며, 개발된 모델의 감시 성능은 60%에서 수집된 IED로 평가하였다. 학습인자 k와 m의 범위는 각각 1-3 으로 총 9종류의 (k, m) 조합에 대해서 모델 성능을 평가하였다. 신경망 은닉층 뉴런수는 2-9의 범위에서 최적화하였다. 최적화된 모델은 (2, 3)과 뉴런수 2에서 구해졌으며, 0.335의 예측 에러를 보였다. 60% IED 데이터로 평가한 결과 플라즈마 고장에의 민감도는 62% 이상이었다. 이는 IED의 A-NTS 모델이 플라즈마 고장의 감시에 효과적으로 적용될 수 있음을 의미한다.