• Korean Journal of Food Science and Technology
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• v.46 no.5
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• pp.588-592
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• 2014

Under optimized condition mild pressure in combination with specific temperature for heat treatment transform the 6-gingerol into 6-shogaol. The purpose of this study was to optimize the conditions used for heat treatment under pressure for increasing 6-shogaol content in ginger (Zingiber officinale Roscoe). A central composite experimental design was used to evaluate the effects of application temperature ($70-130^{\circ}C$) and temperature-holding time (95-265 min) on the transformation of 6-shogaol. The experimental values were shown to be in significantly good agreement with the predicted values (adjusted determination coefficient, $R^2{_{Adj}}=0.9857$). 6-Shogaol content increased as the application temperature and temperature-holding time increased. By analyzing the response surface plots, the optimum conditions of heat treatment (temperature and time) for increasing 6-shogaol content were found to be $127^{\circ}C$ and 109 min, respectively. Under these optimal conditions, the predicted 6-shogaol content was 3.98 mg/g dried ginger. The adequacy of the model equation for predicting the optimum response values was effectively verified by the validation data.

• Electronic Materials Letters
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• v.14 no.6
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• pp.689-699
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• 2018

Nanostructured Ni doped $Bi_2S_3$ ($Bi_{2-x}Ni_xS_3$, $0{\leq}x{\leq}0.07$) is explored as a candidate for telluride free thermoelectric material, through a combination process of mechanical alloying with subsequent consolidation by cold pressing followed with a sintering process. The cold pressing method was found to impact the thermoelectric properties in two ways: (1) introduction of the dopant atom in the interstitial sites of the crystal lattice which results in an increase in carrier concentration, and (2) introduction of a porous structure which reduces the thermal conductivity. The electrical resistivity of $Bi_2S_3$ was decreased by adding Ni atoms, which shows a minimum value of $2.35{\times}10^{-3}{\Omega}m$ at $300^{\circ}C$ for $Bi_{1.99}Ni_{0.01}S_3$ sample. The presence of porous structures gives a significant effect on reduction of thermal conductivity, by a reduction of ~ 59.6% compared to a high density $Bi_2S_3$. The thermal conductivity of $Bi_{2-x}Ni_xS_3$ ranges from 0.31 to 0.52 W/m K in the temperature range of $27^{\circ}C$ (RT) to $300^{\circ}C$ with the lowest ${\kappa}$ values of $Bi_2S_3$ compared to the previous works. A maximum ZT value of 0.13 at $300^{\circ}C$ was achieved for $Bi_{1.99}Ni_{0.01}S_3$ sample, which is about 2.6 times higher than (0.05) of $Bi_2S_3$ sample. This work show an optimization pathway to improve thermoelectric performance of $Bi_2S_3$ through Ni doping and introduction of porosity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.320-330
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• 2020

Fire is difficult to achieve good performance in image detection using deep learning because of its high irregularity. In particular, there is little data on fire detection in underground utility facilities, which have poor light conditions and many objects similar to fire. These make fire detection challenging and cause low performance of deep learning models. Therefore, this study proposed a fire detection model using deep learning and estimated the performance of the model. The proposed model was designed using a combination of a basic convolutional neural network, Inception block of GoogleNet, and Skip connection of ResNet to optimize the deep learning model for fire detection under underground utility facilities. In addition, a training technique for the model was proposed. To examine the effectiveness of the method, the trained model was applied to fire images, which included fire and non-fire (which can be misunderstood as a fire) objects under the underground facilities or similar conditions, and results were analyzed. Metrics, such as precision and recall from deep learning models of other studies, were compared with those of the proposed model to estimate the model performance qualitatively. The results showed that the proposed model has high precision and recall for fire detection under low light intensity and both low erroneous and missing detection capabilities for things similar to fire.

• 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 Plant Biotechnology
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• v.49 no.3
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• pp.207-212
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• 2022

The optimal culture conditions for root organogenesis from the callus of peonies (Paeonia lactiflora Pall.) were investigated. Root explants with vascular bundles were cultured in Murashige and Skoog (MS) medium combined with 0.5-4.0 mg/L auxins (indole acetic acid [IAA], naphthalene acetic acid [NAA], indolebutyric acid [IBA], and 2,4-dichlorophenoxyacetic acid [2,4-D]) and 0.0-2.0 mg/L cytokinins (kinetin, zeatin, and benzylaminopurine [BAP]) to induce callus formation. The callus was then cultured in MS medium combined with three concentrations (0.1, 0.5, and 1.0 mg/L) of IAA, NAA, IBA, kinetin, zeatin, and BAP in the dark for 6 weeks. Based on the results, the effects of dark and light conditions on the callus cultured in MS medium with combinations of 0.1-1.0 mg/L IBA and zeatin for 6 weeks were studied. Callus formation was most effective (>+++) in the medium with a combination of 1.0 mg/L NAA and 1.0 mg/L zeatin. A high number of long adventitious roots were observed in the mediums with 0.1 mg/L IBA (6.66 and 4.82 cm) and 0.5 mg/L zeatin (2.32 and 0.72 cm) among auxins and cytokinins, respectively. The highest number (14.06) of adventitious roots were formed from the callus cultured in light in the MS medium combined with 0.1 mg/L IBA and 0.5 mg/L zeatin. This same medium induced the formation of the longest adventitious root (5.45 cm) in the dark. Thus, optimization of in vitro culture conditions may be possible for the mass propagation of adventitious roots in peonies.

• 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.

• Journal of Life Science
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• v.33 no.3
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• pp.268-276
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• 2023

This study was conducted to optimize the formulation conditions of the immediate-release layer of carvedilol in the development of a two-layer tablet formulation for carvedilol and ivabradine. Using a 2⁴+3 full-factorial design of experiments, excipients (microcrystalline cellulose, citric acid, and crospovidone) of the carvedilol immediate-release layer (wet granulation part) and process parameters for the tablet compression process (main compression) were optimized, and seven types of each dependent variable (assay, content uniformity, hardness, friability, disintegration, and dissolution [pH 1.2 and 6.8]) were evaluated using design expert software. The analysis of variance results confirmed that the main compression has a significant effect on hardness, friability, and disintegration time and that microcrystalline cellulose has a major effect on friability and dissolution. In addition, it was confirmed that citric acid has a significant effect on friability. Crospovidone affects friability and dissolution. According to the design space from the design of the experiment results, the optimized range is microcrystalline cellulose (~18.0-32.0 mg), citric acid (~0.5-12 mg), and main compression (~615-837 kgf). Consequently, this study confirmed the availability of manufacturing the carvedilol immediate-release layer in which all risk factors evaluated in the initial risk assessment are removed.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2003.09a
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• pp.44-44
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• 2003

As a basic measurement tool in the areas of animal models of human disease, gene expression and therapy, and drug discovery and development, small animal PET imaging is being used increasingly. An ideal small animal PET should have high sensitivity and high and uniform resolution across the field of view to achieve high image quality. However, the combination of long narrow pixellated crystal array and small ring diameter of small animal PET leads to the degradation of spatial resolution for the source located at off center. This degradation of resolution can be improved by determining the depth of interaction (DOI) in the crystal and by taking into account the information in sorting the coincident events. Among a number of 001 identification schemes, dual layer phsowich detector has been widely investigated by many research groups due to its practicability and effectiveness on extracting DOI information. However, the effects of each crystal length composing dual layer phoswich detector on DOI measurements and image qualities were not fully characterized. In order to minimize the DOI effect, the length of each layer of phoswich detector should be optimized. The aim of this study was to perform simulations using a simulation tool, GATE to design the optimum lengths of crystals composing a dual layer phoswich detector. The simulated small PET system employed LSO front layer LuYAP back layer phoswich detector modules and the module consisted of 8${\times}$8 arrays of dual layer crystals with 2 mm ${\times}$ 2 mm sensitive area coupled to a Hamamatsu R7600 00 M64 PSPMT. Sensitivities and variation of radial resolutions were simulated by varying the length of LSO front layer from 0 to 10 mm while the total length (LSO + LuYAP) was fixed to 20 mm for 10 cm diameter ring scanner. The radial resolution uniformity was markedly improved by using DOI information. There existed the optimal lengths of crystal layers to minimize the variation of radial resolutions. In 10 cm ring scanner configuration, the radial resolution was kept below 3.4 mm over 8 cm FOV while the sensitivity was higher than 7.4% for LSO 5 mm : LuYAP 15 mm phoswich detector. In this study, the optimal length of dual layer phoswich detector was derived to achieve high and uniform radial resolution.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.409-416
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• 2006

Real-time traveler information disseminated through Variable Message Signs (VMS) is known to have effects on driver route choice decisions. In the past, many studies have attempted to optimize the system performance using VMS message content as the primary control variable of driver route choice. This research proposes a VMS information provision optimization model which searches the best combination of VMS message contents and display sequence to minimize the total travel time on a highway network considered. The driver route choice models under VMS information provision are developed using a stated preference (SP) survey data in order to realistically capture driver response behavior. The genetic algorithm (GA) is used to find the optimal VMS information provision strategies which consists of the VMS message contents and the sequence of message display. In the process of the GA module, the system performance is measured using micro traffic simulation. The experiment results highlight the capability of the proposed model to search the optimal solution in an efficient way. The results show that the traveler information conveyed via VMS can reduce the total travel time on a highway network. They also suggest that as the frequency of VMS message update gets shorter, a smaller number of VMS message contents performs better to reduce the total travel time, all other things being equal.

• Parasites, Hosts and Diseases
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• v.62 no.1
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• pp.42-52
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• 2024

Antimalarial drugs are an urgently need and crucial tool in the campaign against malaria, which can threaten public health. In this study, we examined the cytotoxicity of the 9 antimalarial compounds chemically synthesized using SKM13-2HCl. Except for SKM13-2HCl, the 5 newly synthesized compounds had a 50% cytotoxic concentration (CC₅₀) >100 μM, indicating that they would be less cytotoxic than SKM13-2HCl. Among the 5 compounds, only SAM13-2HCl outperformed SKM13-2HCl for antimalarial activity, showing a 3- and 1.3-fold greater selective index (SI) (CC₅₀/IC₅₀) than SKM13-2HCl in vitro against both chloroquine-sensitive (3D7) and chloroquine -resistant (K1) Plasmodium falciparum strains, respectively. Thus, the presence of morpholine amide may help to effectively suppress human-infectious P. falciparum parasites. However, the antimalarial activity of SAM13-2HCl was inferior to that of the SKM13-2HCl template compound in the P. berghei NK65-infected mouse model, possibly because SAM13-2HCl had a lower polarity and less efficient pharmacokinetics than SKM13-2HCl. SAM13-2HCl was more toxic in the rodent model. Consequently, SAM13-2HCl containing morpholine was selected from screening a combination of pharmacologically significant structures as being the most effective in vitro against human-infectious P. falciparum but was less efficient in vivo in a P. berghei-infected animal model when compared with SKM13-2HCl. Therefore, SAM13-2HCl containing morpholine could be considered a promising compound to treat chloroquine-resistant P. falciparum infections, although further optimization is crucial to maintain antimalarial activity while reducing toxicity in animals.