• Geophysics and Geophysical Exploration
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• v.23 no.1
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• pp.38-49
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• 2020

Full-waveform inversion (FWI) is an optimization process of fitting observed and modeled data to reconstruct high-resolution subsurface physical models. In acoustic FWI (AFWI), pressure data acquired using a marine streamer has mainly been used to reconstruct the subsurface P-wave velocity models. With recent advances in marine seismic-acquisition techniques, acquiring multi-component data in marine environments have become increasingly common. Thus, AFWI strategies must be developed to effectively use marine multi-component data. Herein, we proposed an AFWI strategy using horizontal and vertical particle-acceleration data. By analyzing the modeled acoustic data and conducting sensitivity kernel analysis, we first investigated the characteristics of each data component using AFWI. Common-shot gathers show that direct, diving, and reflection waves appearing in the pressure data are separated in each component of the particle-acceleration data. Sensitivity kernel analyses show that the horizontal particle-acceleration wavefields typically contribute to the recovery of the long-wavelength structures in the shallow part of the model, and the vertical particle-acceleration wavefields are generally required to reconstruct long- and short-wavelength structures in the deep parts and over the whole area of a given model. Finally, we present a sequential-inversion strategy for using the particle-acceleration wavefields. We believe that this approach can be used to reconstruct a reasonable P-wave velocity model, even when the pressure data is not available.

• Composites Research
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• v.34 no.5
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• pp.290-295
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• 2021

The application of lightweight structural composites to automobiles as a solution in line with global fuel economy regulations to curb global warming is recognized as a megatrend. This study was conducted to provide a technical approach that can respond to the issue of replacing parts that require conductive properties to maximize the application of thermoplastic carbon fiber reinforced plastics (CFRPs), which are advantageous in terms of repair, disposal and recycling. By utilizing the properties of the low-viscosity polymerizable oligomer matrix, it was possible to prepare a thermoplastic CFRP exhibiting excellent impregnation properties while uniformly mixing the conductive filler. Various carbon-based conductive fillers such as carbon black, carbon nanotubes, graphene nanoplatelets, graphite, and pitch-based carbon fibers were filled up to the maximum content, and electrical and thermal conductive properties of the fabricated composites were compared and studied. It was confirmed that the maximum incorporation of filler was the most important factor to control the conductive properties of the composites rather than the type or shape of the conductive carbon filler. Experimental results were observed in which it might be advantageous to apply a one-dimensional conductive carbon filler to improve electrical conductivity, whereas it might be advantageous to apply a two-dimensional conductive carbon filler to improve thermal conductivity. The results of this study can provide potential insight into the optimization of structural design for controlling the conductive properties of thermoplastic CFRPs.

• Journal of the HCI Society of Korea
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• v.14 no.2
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• pp.49-60
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• 2019

With the appearance of self-driving cars and electric cars, the automobile industry is rapidly changing. In the midst of these changes, HMI studies are becoming more important as to how the driver obtains safety and convenience with controlling the vehicle. This study sought to understand how automobile manufacturers understand the driving situation, and how they define and limit driver interaction. For this, prior studies about HMI were reviewed and 15 participants performed an on-road study to drive vehicles from five manufacturers with using their interfaces. The results of the study confirmed that buttons and switches that are easily controlled by the user while driving were different from manufacturer to manufacturer. And there are some buttons that are more intensively controlled and others that are difficult to control while driving. It was able to derive 'selection and concentration' from Audi's vehicle, 'optimization of the driving ' from BMW's, 'simple and minimize' from Benz's vehicle, 'remove the manual distraction' from the vehicle of Lexus, and 'visual stability' from KIA's vehicle as the distinctive keywords for the HMI. This shows that each manufacturer has a different definition and interpretation of the driver's driving control area. This study has a distinct value in that it has identified the characteristics of vehicle-specific HMI in actual driving conditions, which is not apparent in appearance. It is expected that this research approach can be useful to see differences in interaction through actual driving despite changes in driving environment such as vehicle platooning and self-driving technology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.517-524
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• 2019

The overdrive hub clutch is attached to a 6-speed automatic transmission to reduce fuel consumption by using the additional power of the engine. This paper proposes a means to minimize the load and roll-over ratio on the punch during the piercing process for the overdrive hub clutch product. Die clearance, shear angle, and friction coefficient, which can affect the load and roll-over ratio of the punch during processing, were set as the design variables. Sensitivity analysis was also conducted to determine the influence of each design variable on the punch load and roll-over ratio. As a result, shear angle, friction coefficient and die clearance were found to be sensitive to load and roll-over ratio. The punch load and roll-over ratio were set as the objective function and the equation of each design variable and objective function was derives using the Response Surface Method. Finally, the optimal value of the design variables was derived using the Response Surface Method. Application of this model to finite element analysis resulted in 22.14% improvement in the roll-over ratio of the punch load and material.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.217-217
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• 2015

The objective of this study was mainly to evaluate the water resources potential of Lake Tana Basin (LTB) by using Soil and Water Assessment Tool (SWAT). From SWAT simulation of LTB, about 5236 km2 area of LTB is gauged watershed and the remaining 9878 km2 area is ungauged watershed. For calibration of model parameters, four gauged stations were considered namely: Gilgel Abay, Gummera, Rib, and Megech. The SWAT-CUP built-in techniques, particle swarm optimization (PSO) and generalized likelihood uncertainty estimation (GLUE) method was used for calibration of model parameters and PSO method were selected for the study based on its performance results in four gauging stations. However the level of sensitivity of flow parameters differ from catchment to catchment, the curve number (CN2) has been found the most sensitive parameters in all gauged catchments. To facilitate the transfer of data from gauged catchments to ungauged catchments, clustering of hydrologic response units (HRUs) were done based on physical similarity measured between gauged and ungauged catchment attributes. From SWAT land use/ soil use/slope reclassification of LTB, a total of 142 HRUs were identified and these HRUs are clustered in to 39 similar hydrologic groups. In order to transfer the optimized model parameters from gauged to ungauged catchments based on these clustered hydrologic groups, this study evaluates three parameter transfer schemes: parameters transfer based on homogeneous regions (PT-I), parameter transfer based on global averaging (PT-II), and parameter transfer by considering Gilgel Abay catchment as a representative catchment (PT-III) since its model performance values are better than the other three gauged catchments. The performance of these parameter transfer approach was evaluated based on values of Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R2). The computed NSE values was found to be 0.71, 0.58, and 0.31 for PT-I, PT-II and PT-III respectively and the computed R2 values was found to be 0.93, 0.82, and 0.95 for PT-I, PT-II, and PT-III respectively. Based on the performance evaluation criteria, PT-I were selected for modelling ungauged catchments by transferring optimized model parameters from gauged catchment. From the model result, yearly average stream flow for all homogeneous regions was found 29.54 m3/s, 112.92 m3/s, and 130.10 m3/s for time period (1989 - 2005) for region-I, region-II, and region-III respectively.

• Korean Journal of Food Science and Technology
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• v.53 no.2
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• pp.174-180
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• 2021

The optimal recipe for manufacturing composite honey-based herbal pills mainly comprising Rubus coreanus powder (RCP), black mulberry powder (BMP), and vitamin C was investigated. Honey-based herbal pills were prepared by mixing these powders, binding them with honey, and then forming a round shape. The experiment was designed based on the D-optimal mixture design, which included 12 experimental points with one replicate for three independent variables as follows: RCP (10~35%), BMP (10~35%), and vitamin C (5~10%). In addition, the dependent variables (total phenolic and flavonoid content and antioxidant activity) were measured and used to optimize the manufacturing conditions. The results showed that high amounts of RCP were correlated with high total flavonoid content, whereas the addition of high amounts of vitamin C resulted in higher antioxidant activity. In conclusion, an optimized formulation for the honey-based herbal pill was found to contain 35% RCP, 10% BMP, and 10% vitamin C.

• Journal of Korea Water Resources Association
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• v.55 no.7
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• pp.545-556
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• 2022

It is recommended to use long-term hydrometeorological data for more than the service life of the hydraulic structures and water resource planning. For the purpose of expanding rainfall data, stochastic simulation models, such as Modified Bartlett-Lewis Rectangular Pulse (BLRP) and Neyman-Scott Rectangular Pulse (NSRP) models, have been widely used. The optimal parameters of the model can be estimated by repeatedly comparing the statistical moments defined through a combination of parameters of the probability distribution in the optimization context. However, parameter estimation using relatively small observed rainfall statistics corresponds to an ill-posed problem, leading to an increase in uncertainty in the parameter estimation process. In addition, as shown in previous studies, extreme values are underestimated because objective functions are typically defined by the first and second statistical moments (i.e., mean and variance). In this regard, this study estimated the parameters of the NSRP model using the objective function with the third moment and compared it with the existing approach based on the first and second moments in terms of estimation of extreme rainfall. It was found that the first and second moments did not show a significant difference depending on whether or not the skewness was considered in the objective function. However, the proposed model showed significantly improved performance in terms of estimation of design rainfalls.

• Journal of Microbiology and Biotechnology
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• v.32 no.5
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• pp.630-637
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• 2022

The objective of this study was to optimize industrial-grade media for improving the biomass production of Weissella cibaria JW15 (JW15) using a statistical approach. Eleven variables comprising three carbon sources (glucose, fructose, and sucrose), three nitrogen sources (protease peptone, yeast extract, and soy peptone), and five mineral sources (K₂HPO₄, potassium citrate, ⳑ-cysteine phosphate, MgSO₄, and MnSO₄) were screened by using the Plackett-Burman design. Consequently, glucose, sucrose, and soy peptone were used as significant variables in response surface methodology (RSM). The composition of the optimal medium (OM) was 22.35 g/l glucose, 15.57 g/l sucrose, and 10.05 g/l soy peptone, 2.0 g/l K₂HPO₄, 5.0 g/l sodium acetate, 0.1 g/l MgSO₄·7H₂O, 0.05 g/l MnSO₄·H₂O, and 1.0 g/l Tween 80. The OM significantly improved the biomass production of JW15 over an established commercial medium (MRS). After fermenting OM, the dry cell weight of JW15 was 4.89 g/l, which was comparable to the predicted value (4.77 g/l), and 1.67 times higher than that of the MRS medium (3.02 g/l). Correspondingly, JW15 showed a rapid and increased production of lactic and acetic acid in the OM. To perform a scale-up validation, batch fermentation was executed in a 5-l bioreactor at 37℃ with or without a pH control at 6.0 ± 0.1. The biomass production of JW15 significantly improved (1.98 times higher) under the pH control, and the cost of OM was reduced by two-thirds compared to that in the MRS medium. In conclusion, OM may be utilized for mass producing JW15 for industrial use.

• Animal Bioscience
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• v.34 no.10
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• pp.1579-1589
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• 2021

Objective: This study was conducted to generate single stranded DNA oligonucleotides with selective affinity to bovine spermatozoa, assess its binding potential and explore its potential utility in trapping spermatozoa from suspensions. Methods: A combinatorial library of 94 mer long oligonucleotide was used for systematic evolution of ligands by exponential enrichment (SELEX) with bovine spermatozoa. The amplicons from sixth and seventh rounds of SELEX were sequenced, and the reads were clustered employing cluster database at high identity with tolerance (CD-HIT) and FASTAptamer. The enriched nucleotides were predicted for secondary structures by Mfold, motifs by Multiple Em for Motif Elicitation and 5' labelled with biotin/6-FAM to determine the binding potential and binding pattern. Results: We generated 14.1 and 17.7 million reads from sixth and seventh rounds of SELEX respectively to bovine spermatozoa. The CD-HIT clustered 78,098 and 21,196 reads in the top ten clusters and FASTAptamer identified 2,195 and 4,405 unique sequences in the top three clusters from the sixth and seventh rounds, respectively. The identified oligonucleotides formed secondary structures with delta G values between -1.17 to -26.18 kcal/mol indicating varied stability. Confocal imaging with the oligonucleotides from the seventh round revealed different patterns of binding to bovine spermatozoa (fluorescence of the whole head, spot of fluorescence in head and mid- piece and tail). Use of a 5'-biotin tagged oligonucleotide from the sixth round at 100 pmol with 4×10⁶ spermatozoa could trap almost 80% from the suspension. Conclusion: The binding patterns and ability of the identified oligonucleotides confirms successful optimization of the SELEX process and generation of aptamers to bovine spermatozoa. These oligonucleotides provide a quick approach for selective capture of spermatozoa from complex samples. Future SELEX rounds with X- or Y- enriched sperm suspension will be used to generate oligonucleotides that bind to spermatozoa of a specific sex type.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.345-353
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• 2021

Cloud computing represent a new era of computing that's forms through the combination of service-oriented architecture (SOA), Internet and grid computing with virtualization technology. Virtualization is a concept through which every cloud is enable to provide on-demand services to the users. Most IT service provider adopt cloud based services for their users to meet the high demand of computation, as it is most flexible, reliable and scalable technology. Energy based performance tradeoff become the main challenge in cloud computing, as its acceptance and popularity increases day by day. Cloud data centers required a huge amount of power supply to the virtualization of servers for maintain on- demand high computing. High power demand increase the energy cost of service providers as well as it also harm the environment through the emission of CO₂. An optimization of cloud computing based on energy-performance tradeoff is required to obtain the balance between energy saving and QoS (quality of services) policies of cloud. A study about power usage of resources in cloud data centers based on workload assign to them, says that an idle server consume near about 50% of its peak utilization power [1]. Therefore, more number of underutilized servers in any cloud data center is responsible to reduce the energy performance tradeoff. To handle this issue, a lots of research proposed as energy efficient algorithms for minimize the consumption of energy and also maintain the SLA (service level agreement) at a satisfactory level. VM (virtual machine) consolidation is one such technique that ensured about the balance of energy based SLA. In the scope of this paper, we explore reinforcement with fuzzy logic (RFL) for VM consolidation to achieve energy based SLA. In this proposed RFL based active VM consolidation, the primary objective is to manage physical server (PS) nodes in order to avoid over-utilized and under-utilized, and to optimize the placement of VMs. A dynamic threshold (based on RFL) is proposed for over-utilized PS detection. For over-utilized PS, a VM selection policy based on fuzzy logic is proposed, which selects VM for migration to maintain the balance of SLA. Additionally, it incorporate VM placement policy through categorization of non-overutilized servers as- balanced, under-utilized and critical. CloudSim toolkit is used to simulate the proposed work on real-world work load traces of CoMon Project define by PlanetLab. Simulation results shows that the proposed policies is most energy efficient compared to others in terms of reduction in both electricity usage and SLA violation.