• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권12호
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• pp.5249-5267
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• 2016

Cognitive radio is an efficient technique to improve spectrum efficiency and relieve the pressure of spectrum resources. In this paper, we investigate the spectrum sensing period in cooperative relay cognitive radio networks; analyze the relationship between the available capacity and the signal-to-noise ratio of the received signal of second users, the target probability of detection and the active probability of primary users. Finally, we derive the closed form expression of the optimal spectrum sensing period in terms of maximum throughput. We simulate the probability of false alarm and available capacity of cognitive radio networks and compare optimal spectrum sensing period scheme with fixed sensing period one in these performance. Simulation results show that the optimal sensing period makes the cognitive networks achieve the higher throughput and better spectrum sensing performance than the fixed sensing period does. Cooperative relay cognitive radio networks with optimal spectrum sensing period can achieve the high capacity and steady probability of false alarm in different target probability of detection. It provides a valuable reference for choosing the optimal spectrum sensing period in cooperative relay cognitive radio networks.

• 통합자연과학논문집
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• 제3권2호
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• pp.117-121
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• 2010

Silicon quantum dots base on photoluminescent porous silicon were prepared from an electrochemical etching of n-type silicon wafer (boron-dopped<100> orientation, resistivity of 1~10 ${\Omega}-cm$) and used as a alcohol sensor. Silicon quantum dots displayed an emission band at the wavelength of 675 nm with an excitation wavelength of 480 nm. Photoluminescence of silicon quantum dots was quenched in the presence of alcohol vapors such as methanol, ethanol, and isopropanol. Quenching efficiencies of 21.5, 32.5, and 45.8% were obtained for isopropanol, ethanol, and methanol, respectively. A linear relationship was obtained between quenching efficiencies and vapor pressure of analytes used. Quenching photoluminescence was recovered upon introducing of fresh air after the detection of alcohol. This provides easy fabrication of alcohol sensor based on porous silicon.

• Bulletin of the Korean Chemical Society
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• 제28권4호
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• pp.553-556
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• 2007

We previously reported a 27.12 MHz inductively coupled plasma source at atmospheric pressure for atomic emission spectrometry based on polymer microchip plasma technology. For the PDMS polymer microchip plasma, molecular emission was observed, but no metallic detection was done. In this experiment, a lab-made electrothermal vaporizer (ETV) with tantalum coil was connected to the microchip plasma for aqueous sample introduction to detect metal ions. The electrode geometry of this microchip plasma was redesigned for better stability and easy monitoring of emission. The plasma was operated at an rf power of 30-70 W using argon gas at 300 mL/min. Gas kinetic temperatures between 800-3200 K were obtained by measuring OH emission band. Limits of detection of about 20 ng/mL, 96.1 ng/mL, and 1.01 μ g/mL were obtained for alkali metals, Zn, and Pb, respectively, when 10 μ L samples in 0.1% nitric acid were injected into the ETV.

• 전기학회논문지
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• 제57권12호
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• pp.2300-2307
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• 2008

This study receives the noise transmitted in a constant audio frequency range through a microphone array in which the noise(like grease in a pan) occurs on the power supply line due to the troublesome partial discharge(arc). Then by going through a series of signal processing of removing noise, this study measures the distance and direction up to the noise caused by the troublesome partial discharge(arc) and monitors the result by displaying in the analog and digital method. After these, it determines the state of each size and judges the distance and direction of problematic part. When the signal sound transmitted by the signal source of bad insulator is received on each microphone, the signal comes only in the frequency range of 20 kHz by passing through the circuit of amplification and 6th low pass filter. Then, this signal is entered in a digital value of digital signal processing(TMS320F2812) through the 16-bit A/D conversion. By doing so, the sound distance, direction and coordinate of bad insulator can be detected by realizing the correlation method of detecting the arriving time difference occurring on each microphone and the algorithm of detecting maximum time difference.

• Structural Engineering and Mechanics
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• 제21권6호
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• pp.635-658
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• 2005

The possibility of detecting a crack in L-shaped pipes filled with fluid based on measurement of transverse natural frequencies is examined. The problem is solved by representing the crack by a massless rotational spring, simulating the out-of-plane transverse vibration only without solving the coupled torsional vibration and using the transfer matrix method for solution of the governing equation. The theoretical solutions are verified by experiments. The cracks considered are external, circumferentially oriented and have straight front. Pipes made of aluminium and mild steel are tested with water as internal fluid. Crack size to pipe thickness ratio ranging from 0.20 to 0.57 and fluid (gauge) pressure in the range of 0 to 10 atmospheres are examined. The rotational spring stiffness is obtained by an inverse vibration analysis and deflection method. The details of the two methods are given. The results by the two methods are presented graphically and show good agreement. Crack locations are also determined by the inverse analysis. The maximum absolute error in the location is 13.80%. Experimentally determined variation of rotational spring stiffness with ratio of crack size to thickness is utilized to predict the crack sizes. The maximum absolute errors in prediction of crack size are 17.24% and 16.90% for aluminium and mild steel pipes respectively.

• Bulletin of the Korean Chemical Society
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• 제25권1호
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• pp.73-78
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• 2004

A highly sensitive detecting method has been developed for determining part per billion of sulfur in $H_2S$/Ar plasma. The method is based on the excitation of Ar/$H_2S\;or\;Ar/H_2S/O_2$ mixture in hollow cathode glow discharge sustained by radiofrequency (RF) or 60 Hz AC power and the spectroscopic measurement of the intensity of emission lines from electronically excited $S_2^*\;or\;SO_2^*$ species, respectively. The RF or AC power needed for the excitation did not exceed 30 W at a gas pressure maintained at several mbar. The emission intensity from the $SO_2^*$ species showed excellent linear response to the sulfur concentration ranging from 5 ppbv, which correspond to S/N = 5, to 500 ppbv. But the intensity from the $S_2^*$ species showed a linear response to the $H_2S$ only at low flow rate under 20 sccm (mL/min) of the sample gas. Separate experiments using $SO_2$ gas as the source of sulfur demonstrated that the presence of $O_2$ in the argon plasma is essential for obtaining prominent $SO_2^*$ emission lines.

• 전력전자학회논문지
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• 제24권1호
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• pp.62-65
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• 2019

Wireless power transfer systems require an algorithm to determine the presence of the target object for mitigating standby power and safety issues. Although many schemes that sense various external objects have been actively proposed for inductive power transfer systems, not many studies on capacitive power transfer systems have been conducted compared with those on inductive power transfer systems. This study proposes a target object detection algorithm by monitoring the capacitance in transmitter-side electrodes without additional pressure sensors or distance sensors. The proposed algorithm determines the presence of a target object by monitoring the change in capacitance in transmitter-side electrodes using the step pulse of the microcontroller unit. The algorithm is verified by two step processes. First, the performance in capacitance measurement is compared with that of an LCR meter. Then, the verification is conducted in a 5-W capacitive power transfer hardware. Experimental result shows that the interelectrode capacitance increases by 6 times when the target object is fully aligned. Thus, the proposed scheme can successfully detect the presence of the target object.

• Nuclear Engineering and Technology
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• 제50권8호
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• pp.1306-1313
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• 2018

The randomness and incipient nature of certain faults in reactor systems warrant a robust and dynamic detection mechanism. Existing models and methods for fault diagnosis using different mathematical/statistical inferences lack incipient and novel faults detection capability. To this end, we propose a fault diagnosis method that utilizes the flexibility of data-driven Support Vector Machine (SVM) for component-level fault diagnosis. The technique integrates separately-built, separately-trained, specialized SVM modules capable of component-level fault diagnosis into a coherent intelligent system, with each SVM module monitoring sub-units of the reactor coolant system. To evaluate the model, marginal faults selected from the failure mode and effect analysis (FMEA) are simulated in the steam generator and pressure boundary of the Chinese CNP300 PWR (Qinshan I NPP) reactor coolant system, using a best-estimate thermal-hydraulic code, RELAP5/SCDAP Mod4.0. Multiclass SVM model is trained with component level parameters that represent the steady state and selected faults in the components. For optimization purposes, we considered and compared the performances of different multiclass models in MATLAB, using different coding matrices, as well as different kernel functions on the representative data derived from the simulation of Qinshan I NPP. An optimum predictive model - the Error Correcting Output Code (ECOC) with TenaryComplete coding matrix - was obtained from experiments, and utilized to diagnose the incipient faults. Some of the important diagnostic results and heuristic model evaluation methods are presented in this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권4호
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• pp.1080-1099
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• 2023

Digital healthcare combined with telemedicine services in the form of convergence with digital technology and AI is developing rapidly. Digital healthcare research is being conducted on many conditions including shock. However, the causes of shock are diverse, and the treatment is very complicated, requiring a high level of medical knowledge. In this paper, we propose a shock detection method based on the correlation between shock and data extracted from hemodynamic monitoring equipment. From the various parameters expressed by this equipment, four parameters closely related to patient shock were used as the input data for a machine learning model in order to detect the shock. Using the four parameters as input data, that is, feature values, a random forest-based ensemble machine learning model was constructed. The value of the mean arterial pressure was used as the correct answer value, the so called label value, to detect the patient's shock state. The performance was then compared with the decision tree and logistic regression model using a confusion matrix. The average accuracy of the random forest model was 92.80%, which shows superior performance compared to other models. We look forward to our work playing a role in helping medical staff by making recommendations for the diagnosis and treatment of complex and difficult cases of shock.

• 분석과학
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• 제36권6호
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• pp.281-290
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• 2023

Zidovudine is an antiretroviral agent prescribed for the prevention and treatment of human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS). It is typically recommended to be used in combination with other antiretroviral drugs. Zidovudine has the potential to generate N-nitrosodimethylamine (NDMA) in the presence of dimethylamine and nitrite salt under acidic reaction conditions during the drug manufacturing process. NDMA is a potent human carcinogen that may be detected in drug substances or drug products. An analytical method was developed to determine NDMA in pharmaceuticals including zidovudine using high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The analysis involved reversed-phase chromatography on a Kinetex F5 column with a mobile phase comprising water-acetonitrile mixtures. The detection of positively charged ions was conducted using atmospheric pressure chemical ionization (APCI). The calibration curve demonstrated excellent linearity (r = 0.9997) across the range of 1-50 ng/mL with a highly sensitive limit of detection (LOD) at 0.3 ng/mL. The developed method underwent thorough validation for specificity, linearity, accuracy, precision, robustness, and system suitability. This sensitive and specific analytical method was applied for detecting NDMA in zidovudine drug substance and its formulation currently available in the market, indicating its suitability for drug quality management purposes.