• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.13-19
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• 2021

This study examined the effects of stacking faults on the thermoelectric properties for n-type SiC semiconductors. Porous SiC semiconductors with 30~42 % porosity were fabricated by the heat treatment of pressed ��-SiC powder compacts at 1600~2100 ℃ for 20~120 min in an N2 atmosphere. XRD was performed to examine the stacking faults, lattice strain, and precise lattice parameters of the specimens. The porosity and surface area were analyzed, and SEM, TEM, and HRTEM were carried out to examine the microstructure. The electrical conductivity and the Seebeck coefficient were measured at 550~900 ℃ in an Ar atmosphere. The electrical conductivity increased with increasing heat treatment temperature and time, which might be due to an increase in carrier concentration and improvement in grain-to-grain connectivity. The Seebeck coefficients were negative due to nitrogen behaving as a donor, and their absolute values also increased with increasing heat treatment temperature and time. This might be due to a decrease in stacking fault density, i.e., a decrease in stacking fault density accompanied by grain growth and crystallite growth must have increased the phonon mean free path, enhancing the phonon-drag effect, leading to a larger Seebeck coefficient.

• International Journal of Quality Innovation
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• v.6 no.1
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• pp.109-118
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• 2005

The parameter design is the most emphasized measure by researchers for a new products development. It is critical for makers to achieve simultaneously in both the time-to-market production and the quality enhancement. However, there are difficulties in practical application, such as (1) complexity and nonlinear relationships co-existed among the system's inputs, outputs and control parameters, (2) interactions occurred among parameters, (3) where the adjustment factors of Taguchi's two-phase optimization procedure cannot be sure to exist in practice, and (4) for some reasons, the data became lost or were never available. For these incomplete data, the Taguchi methods cannot treat them well. Neural networks have a learning capability of fault tolerance and model free characteristics. These characteristics support the neural networks as a competitive tool in processing multivariable input-output implementation. The successful fields include diagnostics, robotics, scheduling, decision-making, prediction, etc. This research is a case study of spherical annealing model. In the beginning, an original model is used to pre-fix a model of parameter design. Then neural networks are introduced to achieve another model. Study results showed both of them could perform the highest spherical level of quality.

• Progress in Superconductivity
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• v.10 no.2
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• pp.149-154
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• 2009

We measured and analyzed the quench development in coated conductor(CC) tapes. The CC was grown on hastelloy substrates and has an Ag protection layer. The tapes were subjected to simulated AC fault currents for quench development measurement. They were immersed in liquid nitrogen during the experiment. The quench resistance increased rapidly first, and the increase slowed down afterwards. It increased linearly with applied voltage at lower voltages, and depended less strongly on applied voltage at higher voltages. The resistance was compared with that of Au/YBCO films grown on sapphire substrates, and found to increase more monotonously than the latter. Data were analyzed quantitatively with the concept of heat transfer within the tape and the surrounding liquid nitrogen. A heat balance equation was derived and solved, taking into consideration temperature dependence of thermal parameters of the tapes. Solutions, together with values of thermal parameters taken from the literature, explained the data well. Cooling by liquid nitrogen affected the quench development considerably at lower applied voltages. Dependence on applied voltages could be also understood quantitatively.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2001.09a
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• pp.19-27
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• 2001

Seismic parameters fur computation of ground motions in Southern Korea are obtained from recently recorded data, and site-independent regional and site-dependent local strong ground motions are predicted using efficient computational techniques. For the computation of ground motions, we devised an efficient procedure to compute site-independent $x_{q}$ and dependent $x_{s}$ values separately. The first step of this procedure is to use the coda normalization method far computation of site independent Q or corresponding $x_{q}$ value. The next step is the computation of $x_{s}$, values fur each site separately using the given $x_{q}$ value. For computation of ground motions the empirical Green's function (EGF) is modified to account fur the depth and distance variations of subevents on a finite fault plane using the theoritical Green's function. It is computed using wavenumber integration technique in layered media. The site dependent ground motions at seismic stations in southeastern local area were properly simulated using the modified empirical Green's function method in layered medium. The proposed method and procedures fur estimation of site dependent seismic parameters and ground motions could be efficiently used in the low and moderate seismicity regions.ons.s.ons.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.3
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• pp.294-301
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• 2015

Oil filters for vehicular parts are used under high and low temperatures as the engine is cooled, and defects can be generated with repeated changes in the operating environment and with changes in the shape, such as very high internal losses for the bolts. Visually checking for defects inside a bolt is impossible. Nondestructive evaluation methods such as eddy current testing (ECT) are recommended as a more effective way to examine inside a bolt and detect surface defects in a short amount of time. In this study, the fit bobbin coil eddy current probe was applied to checking the bolts. The bolt parameters were calculated by using a COMSOL analysis program to obtain parameters for professional interior design and fault diagnosis.

• Journal of the Korea Computer Industry Society
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• v.3 no.2
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• pp.227-234
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• 2002

An cluster web server system, one has the problem that does the low availability occured by the high chance of the server failures and it is not easy to provide high performance and availability occuring software aging. In this paper, running cluster web sewers consists of n primary servers and k backup servers, propose software rejuvenation model on performance and switchover time. Based on the various system operational parameters, we calculate to evaluate the rejuvenation policy such steady-state probabilities, availability, and downtime cost. And we validate the solutions of mathematical model by experiments based on various operation parameters and fud that the software rejuvenation method can be adopted as prventive fault tolerant technique for stability of system.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.833-852
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• 2019

In real time applications, due to their effective cost and small size, wireless networks play an important role in receiving particular data and transmitting it to a base station for analysis, a process that can be easily deployed. Due to various internal and external factors, networks can change dynamically, which impacts the localisation of nodes, delays, routing mechanisms, geographical coverage, cross-layer design, the quality of links, fault detection, and quality of service, among others. Conventional methods were programmed, for static networks which made it difficult for networks to respond dynamically. Here, machine learning strategies can be applied for dynamic networks effecting self-learning and developing tools to react quickly and efficiently, with less human intervention and reprogramming. In this paper, we present a wireless networks survey based on different machine learning algorithms and network lifetime parameters, and include the advantages and drawbacks of such a system. Furthermore, we present learning algorithms and techniques for congestion, synchronisation, energy harvesting, and for scheduling mobile sinks. Finally, we present a statistical evaluation of the survey, the motive for choosing specific techniques to deal with wireless network problems, and a brief discussion on the challenges inherent in this area of research.

• Geomechanics and Engineering
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• v.36 no.5
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• pp.475-487
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• 2024

Many uncertainties affect the stability assessment of rock structures. Some of these factors significantly influence technology decisions. Some of these factors belong to the geological domain, and spatial uncertainty measurements are useful for structural stability analysis. This paper presents an integrated approach to study the stability of rock structures, including spatial factors. This study models two main components: discrete structures (fault zones) and well known geotechnical parameters (rock quality indicators). The geostatistical modeling criterion are used to quantify geographic uncertainty by producing simulated maps and RQD values for multiple equally likely error regions. Slope stability theorem would be demonstrated by modeling local failure zones and RQDs. The approach proided is validated and finally, the slope stability analysis method and fuzzy Laypunov criterion are applied to mining projects with limited measurement data. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and fuzzy theory.

• Journal of Power Electronics
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• v.13 no.2
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• pp.264-274
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• 2013

A new sensorless position estimation method for switched reluctance motor (SRM) drives is presented in this paper. This method uses the change of the slope of the phase inductance to detect the aligned position. Since the aligned positions for successive electrical cycle of each phase are apart by a fixed mechanical angle $45^{\circ}$ in the case of 12/8 SRM, the speed of the machine can be calculated to estimate the rotor position. Since no prior knowledge of motor parameters is required, the method is easy for implementation without adding any additional hardware or memory. In order to verify the validity of this technique, effects such as changes in the advanced angle and phase lacking faults are examined. In addition, an inductance threshold based sensorless starting scheme is also proposed. Experimental results demonstrate the validity of the proposed method.

• Proceedings of the KIPE Conference
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• 2016.07a
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• pp.357-358
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• 2016

This paper presents a dynamic, electric-thermal model for a photovoltaic (PV) cell that combines electrical and thermal parameters. In this model, the irradiance and ambient temperature are used to calculate the PV cell temperature based on a five-layer thermal model. The cell temperature is then used in the electrical model to accurately adjust the PV cell output electrical characteristics and power. A custom experimental setup was built to test and verify the electrical and thermal characteristics of the PV cell and its surrounding layers. The electric-thermal model is validated using experimental data in realistic scenarios. This PV model can be scaled up and used to simulate PV systems in wide variety of applications, extreme environmental conditions, and fault conditions in real-time.