• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.73-77
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• 2005

To correctly invert and interpret Surface Nuclear Magnetic Resonance (SNMR) data collected in conductive terrains, an accurate estimate of subsurface conductivity structure is required. Given such an estimate, it would be useful to determine, before conducting an SNMR sounding, whether or not the conductivity structure would prevent groundwater being detected. Using SNMR forward modelling, we describe a method of determining the depth range from which most of the SNMR signal originates, given a model of subsurface conductivity structure. We use the method to estimate SNMR depth penetration in a range of halfspace models and show that for conductive halfspaces ($<10{\Omega}.m$) the depth of penetration Is less than 50 m. It is also shown that for these halfspaces, increasing coincident loop size does not significantly improve depth penetration. The results can be used with halfspace approximations of more complicated ID conductivity structures to give a reasonable estimate of the depth range over which signal is obtainable in conductive terrains.

• Food Engineering Progress
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• v.15 no.3
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• pp.214-220
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• 2011

$\beta$-Glucosidase enzyme reaction under high hydrostatic pressure was investigated in terms of physical chemistry. A model substrate (p-nitrophenyl-${\beta}$-D-glucopyranoside(pNPG)) was used, and the pressure effects on the enzymatic hydrolysis (pNPG${\rightarrow}$pNP) at 25 MPa, 50 MPa, 75 MPa, and 100 MPa were analyzed. Two parts of the reaction such as kinetic and equilibrium stages were considered for mathematical modelling, and their physicochemical parameters such as forward and inverse reaction constants, equilibrium constant, volume change by pressure, etc. were mathematically modeled. The product concentration increased with pressure, and the two stages of reaction were observed. Prediction models were derived to numerically compute the product concentrations according to reaction time over kinetic to equilibrium stages under high pressure condition. Conclusively, the $\beta$-Glucosidase enzyme reaction could be activated by pressurization within 100 MPa, and the developed models were very successful in their prediction.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.374-388
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• 2022

Cloud computing has been one of the most critical technology in the last few decades. It has been invented for several purposes as an example meeting the user requirements and is to satisfy the needs of the user in simple ways. Since cloud computing has been invented, it had followed the traditional approaches in elasticity, which is the key characteristic of cloud computing. Elasticity is that feature in cloud computing which is seeking to meet the needs of the user's with no interruption at run time. There are traditional approaches to do elasticity which have been conducted for several years and have been done with different modelling of mathematical. Even though mathematical modellings have done a forward step in meeting the user's needs, there is still a lack in the optimisation of elasticity. To optimise the elasticity in the cloud, it could be better to benefit of Machine Learning algorithms to predict upcoming workloads and assign them to the scheduling algorithm which would achieve an excellent provision of the cloud services and would improve the Quality of Service (QoS) and save power consumption. Therefore, this paper aims to investigate the use of machine learning techniques in order to predict the workload of Physical Hosts (PH) on the cloud and their energy consumption. The environment of the cloud will be the school of computing cloud testbed (SoC) which will host the experiments. The experiments will take on real applications with different behaviours, by changing workloads over time. The results of the experiments demonstrate that our machine learning techniques used in scheduling algorithm is able to predict the workload of physical hosts (CPU utilisation) and that would contribute to reducing power consumption by scheduling the upcoming virtual machines to the lowest CPU utilisation in the environment of physical hosts. Additionally, there are a number of tools, which are used and explored in this paper, such as the WEKA tool to train the real data to explore Machine learning algorithms and the Zabbix tool to monitor the power consumption before and after scheduling the virtual machines to physical hosts. Moreover, the methodology of the paper is the agile approach that helps us in achieving our solution and managing our paper effectively.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.884-894
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• 2023

Design and safety assessment of fuel pins for application in innovative Generation IV fast reactors calls for a dedicated nuclear fuel modelling and for the extension of the fuel performance code capabilities to the envisaged materials and irradiation conditions. In the INSPYRE Project, comprehensive and physics-based models for the thermal-mechanical properties of U-Pu mixed-oxide (MOX) fuels and for fission gas behaviour were developed and implemented in the European fuel performance codes GERMINAL, MACROS and TRANSURANUS. As a follow-up to the assessment of the reference code versions ("pre-INSPYRE", NET 53 (2021) 3367-3378), this work presents the integral validation and benchmark of the code versions extended in INSPYRE ("post-INSPYRE") against two pins from the SUPERFACT-1 fast reactor irradiation experiment. The post-INSPYRE simulation results are compared to the available integral and local data from post-irradiation examinations, and benchmarked on the evolution during irradiation of quantities of engineering interest (e.g., fuel central temperature, fission gas release). The comparison with the pre-INSPYRE results is reported to evaluate the impact of the novel models on the predicted pin performance. The outcome represents a step forward towards the description of fuel behaviour in fast reactor irradiation conditions, and allows the identification of the main remaining gaps.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3C
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• pp.157-170
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• 2006

Downhole method is considered as giving a little unreliable Vs profile when the signal to noise ratio(S/N) is low and the travel time information is erroneous although it is economical and ease of operation. Direct method has been applied for obtaining adequate result in this case. But it is difficult to determine optimum result by using direct method which is subjective and considering straight ray path. Therefore, in this paper, Mean Refracted Ray Path Method(MRM) was proposed, which is automated and considering refracted ray path. Artificial travel time data adding some travel time error was generated by forward modeling based on Snell's Law and travel time data was also obtained from numerical signal traces using FEM modelling. Using these travel time data, reliability of MRM was verified in the manner of comparing the results determined by MRM with the model. Finally, proposed method was applied to the real field data and it was considered as improved method for obtaining the optimum result in downhole seismic method.

• Geophysics and Geophysical Exploration
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• v.14 no.1
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• pp.7-17
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• 2011

We have developed an inversion code for three-dimensional (3D) resistivity tomography including the anisotropy effect. The algorithm is based on the finite element approximations for the forward modelling and Active Constraint Balancing method is adopted to enhance the resolving power of the smoothness constraint least-squares inversion. Using numerical experiments, we have shown that anisotropic inversion is viable to get an accurate image of the subsurface when the subsurface shows strong electrical anisotropy. Moreover, anisotropy can be used as additional information in the interpretation of subsurface. This algorithm was also applied to the field dataset acquired in the abandoned old mine area, where a high-rise apartment block has been built up over a mining tunnel. The main purpose of the investigation was to evaluate the safety analysis of the building due to old mining activities. Strong electrical anisotropy has been observed and it was proven to be caused by geological setting of the site. To handle the anisotropy problem, field data were inverted by a 3D anisotropic tomography algorithm and we could obtain 3D subsurface images, which matches well with geology mapping observations. The inversion results have been used to provide the subsurface model for the safety analysis in rock engineering and we could assure the residents that the apartment has no problem in its safety after the completion of investigation works.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.203-211
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• 2020

This purpose of this study is to verity the impact of new logistics factors on the Intention of use and consumer happiness, the mediating effect of perceived benefits, and provide suggestions on how to improve the level of new distribution. Based on the previous theories of online experience, off-line experience, logistics experience, perceived benefits, Intention of use and consumer happiness, the study puts forward 6 key research hypotheses. Reliability and validity tests were carried out by using data collected on new logistics factors on the Intention of use and consumer happiness. The hypotheses are verified through structural equation modelling. The study on the impact of new logistics factors on the Intention of use and consumer happiness and the mediating effect of perceived benefits, indicates that online experience, off-line experience, logistics experience have positive effects on perceived benefits, the perceived benefits has positive effects on Intention of use and consumer happiness, and the Intention of use has positive effects on consumer happiness. Moreover, perceived benefits as the mediating variable have effects on the relationship between online experience, off-line experience, logistics experience and the Intention of use and consumer happiness. The study extended the existing previous studies to provide theoretical and practical implications by verifying the relationship between new logistics factors and the Intention of use and consumer happiness.

• Journal of the Korean Geotechnical Society
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• v.18 no.2
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• pp.51-64
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• 2002

Observational results of ground movement during the construction were very different from those predicted during the analysis of design step because of the uncertainty of the numerical analysis modelling, the soil parameter, and the condition of a construction field, etc., however accurately numerical analysis method was applied for prediction of ground movement per the excavation step. Therefore, the management system through the construction field measurement should be achieved for grasping the situation during the excavation. Until now, the measurement system restricted by 'Absolute Value Management system'analyzing only the stability of present step has been executed. So, it was difficult to expect the prediction of ground movement fur the next excavation step. In this situation, this study developed 'The Management system TOMAS-EXCAV'consisted of 'Absolute value management system'analyzing the stability of present step and 'Prediction management system'expecting the ground movement of next excavation step and analyzing the stability of next excavation step by 'Back Analysis'. TOMAS-EXCAV could be applied to all the uncertainty of earth retaining structures analysis by connecting 'Forward analysis program'and 'Back analysis program'and optimizing the main design variables using SQP-MMFD optimization method through measurement results. The applicability of TOMAS-EXCAV was confirmed by back analysis selecting two earth retains construction fields.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.105-113
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• 2009

The interpretation of observed waveform characteristics identified in refraction and wide-angle reflection data increases confidence in the crustal structure model obtained. When calculating traveltimes and raypaths, wavefront methods on a regular grid based on graph theory are robust even with complicated structures, but basically compute only first arrivals. In this paper, we develop new algorithms to compute traveltimes and raypaths not only for first arrivals, but also for fast and later reflection arrivals, later refraction arrivals, and converted waves between P and S, using the modified wavefront method based on slowness network nodes mapped on a multi-layer model. Using the new algorithm, we can interpret reflected arrivals, Pg-later arrivals, strong arrivals appearing behind Pn, triplicated Moho reflected arrivals (PmP) to obtain the shape of the Moho, and phases involving conversion between P and S. Using two models of an ocean-continent transition zone and an oceanic ridge or seamount, we show the usefulness of this algorithm, which is confirmed by synthetic seismograms using the 2D Finite Difference Method (2D-FDM). Characteristics of arrivals and raypaths of the two models differ from each other in that using only first-arrival traveltime data for crustal structure analysis involves risk of erroneous interpretation in the ocean-continent transition zone, or the region around a ridge or seamount.

• Korean Journal of Ecology and Environment
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• v.47 no.3
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• pp.186-193
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• 2014

This study aimed to analyze spatio-temporal trends of phenological characteristics in South Korea by using MODIS EVI. For the phenology analysis, we had applied double logistic function to MODIS time-series data. Our results showed that starting date of phenology seems to have a tendency along with latitudinal trends. Starting date of phenology of Jeju Island and Mt. Sobeak went back for 0.38, 0.174 days per year, respectively whereas, Mt. Jiri and Mt. Seolak went forward for 0.32 days, 0.239 days and 0.119 days, respectively. Our results exhibited the fluctuation of plant phonological season rather than the change of phonological timing and season. Starting date of plant phenology by spatial distribution revealed tendency that starting date of mountain area was late, and basin and south foot of mountain was fast. In urban ares such as Seoul metropolitan, Masan, Changwon, Milyang, Daegu and Jeju, the phonological starting date went forward quickly. Pheonoligcal attributes such as starting date and leaf fall in urban areas likely being affected from heat island effect and related warming. Our study expressed that local and regional monitoring on phonological events and changes in Korea would be possible through MODIS data.