• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.270-278
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• 2023

We propose a container orchestration system for process workloads that combines the potential of big data and machine learning technologies to integrate enterprise process-centric workloads. This proposed system analyzes big data generated from industrial automation to identify hidden patterns and build a machine learning prediction model. For each machine learning case, training data is loaded into a data store and preprocessed for model training. In the next step, you can use the training data to select and apply an appropriate model. Then evaluate the model using the following test data: This step is called model construction and can be performed in a deployment framework. Additionally, a visual hierarchy is constructed to display prediction results and facilitate big data analysis. In order to implement parallel computing of PCA in the proposed system, several virtual systems were implemented to build the cluster required for the big data cluster. The implementation for evaluation and analysis built the necessary clusters by creating multiple virtual machines in a big data cluster to implement parallel computation of PCA. The proposed system is modeled as layers of individual components that can be connected together. The advantage of a system is that components can be added, replaced, or reused without affecting the rest of the system.

• Analytical Science and Technology
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• v.36 no.5
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• pp.205-215
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• 2023

In the present study, an analytical method was proposed for detecting trifluralin in aquatic products at trace concentrations. The method employed QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) and gas chromatography coupled with tandem mass spectrometry (GC-MS/MS) as the sample preparation and measurement, respectively. The effect of the aqueous phase volume used in the QuEChERS was demonstrated, and the ratio of 10:10 (mL) between water and acetonitrile phase was used for 5 g of sample. Besides, dSPE using C18 and primary-secondary amine (PSA) was applied to remove the potential interferences from the food matrices, indicating no remarkable analyte loss. The linear range was built up from 0.50 ㎍ L^-1 to 3.0 ㎍ L^-1 (R² = 0.9993). Other criteria, i.e., repeatability (RSD_r = 0.86-1.96 %), reproducibility (RSD_R = 1.09-2.01 %), and recovery (over 90 %), were in accordance with Appendix F of AOAC (2016) for method performance. Although no trifluralin was detected for the commercial samples (fish, shrimp, and breaded shrimp), the spiked samples performed favorable recoveries and precision.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.473-482
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• 2024

This study utilized virtual reality to construct a simulated public restroom environment to identify potential hazards. The objective was to discern actual risks in real-world public restrooms through this virtual setup. During the virtual restroom experience, data from the built-in 3-axis accelerometer and gyroscope sensors of testor's smart phones were collected. Analysis of this data helped in identifying spatio temporal factors impacting the users. The determination of these factors as risk elements was based on an evaluation algorithm grounded in data analysis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.681-687
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• 2017

We investigated the potential for wind-power generation using the wind produced by express trains. We built equipment to detect the wind velocity, including wind meters and a data analyzer. We considered various conditions that might change the wind. First, we measured the velocity and duration of the wind at three locations distinguished by the presence of a tunnel and a valley landscape. We analyzed the changes in the wind according to the geometric conditions. Also, we analyzed the changes in the wind according to three different heights relative to the train. We also compared the wind produced by a KTX train and an SRT train. Finally, we used the results to derive the wind power energy harvested from the wind and discuss the expected utility.

• Steel and Composite Structures
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• v.51 no.1
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• pp.25-41
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• 2024

The measurement of pile bearing capacity is crucial for the design of pile foundations, where in-situ tests could be costly and time needed. The primary objective of this research was to investigate the potential use of fuzzy-based techniques to anticipate the maximum weight that concrete driven piles might bear. Despite the existence of several suggested designs, there is a scarcity of specialized studies on the exploration of adaptive neuro-fuzzy inference systems (ANFIS) for the estimation of pile bearing capacity. This paper presents the introduction and validation of a novel technique that integrates the fire hawk optimizer (FHO) and equilibrium optimizer (EO) with the ANFIS, referred to as ANFIS_FHO and ANFIS_EO, respectively. A comprehensive compilation of 472 static load test results for driven piles was located within the database. The recommended framework was built, validated, and tested using the training set (70%), validation set (15%), and testing set (15%) of the dataset, accordingly. Moreover, the sensitivity analysis is performed in order to determine the impact of each input on the output. The results show that ANFIS_FHO and ANFIS_EO both have amazing potential for precisely calculating pile bearing capacity. The R² values obtained for ANFIS_FHO were 0.9817, 0.9753, and 0.9823 for the training, validating, and testing phases. The findings of the examination of uncertainty showed that the ANFIS_FHO system had less uncertainty than the ANFIS_EO model. The research found that the ANFIS_FHO model provides a more satisfactory estimation of the bearing capacity of concrete driven piles when considering various performance evaluations and comparing it with existing literature.

• Clinical and Experimental Pediatrics
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• v.48 no.11
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• pp.1153-1161
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• 2005

As known by other name(natural immunity), the innate immune system comprises all those mechanisms for dealing with infection that are constitutive or built in, changing little with age or with experience of infection. Though in some ways less sophisticated than adaptive immunity, innate immunity should not belittled, since it has evidently protected thousands of species of invertebrates sufficiently to survive for up to 2 billion years. In the innate immune system, molecules of both cellular and humoral types are involved, corresponding to the need to recognize and dispose of different types of pathogen, to promote inflammatory responses and to interact to the adaptive immune system. A major features of innate immunity are the presence of the normal gut flora, complements, macrophages, dendritic cells, natural killer cells and many cytokines that can block the establishment of infection. Both phagocytic cells and complement system have tremendous potential for damaging host cells, but fortunately they are normally only triggered by foreign materials, and usually most of their destructive effects are focussed on the surface of these or in the safe environment of the phagolysosome. This article addreses the comprehensive mechanisms of the major components of the innate immune system to prevent the infection.

• KIEAE Journal
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• v.12 no.2
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• pp.111-116
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• 2012

Faced with the international issue of environmental problems from global warming and energy consumption, the Korean Government has made many efforts on reducing energy and $CO_2$ emission under the motto of "Low-Carbon Green Growth". In order to reduce energy in the building sector, severe design standards and regulations on saving energy in new buildings have been established. Now, it is necessary to focus on deteriorated buildings where applications of energy saving designs and techniques have been insufficient, for maximizing energy saving in the building sector. Specially, it is very important to reduce energy through the remodeling process at deteriorated school buildings which were built over 20 years ago and sharply changed into the excessive energy consumption structure from new educational curricula. Thus, this paper examined the effects of potential factors to reduce energy at deteriorated elementary school buildings using the energy simulation on the Visual DOE 4.0 program. Among applied factors of insulations, southern louver, window's SHGC, indoor setup temperature, and system efficiency, all factors except window's SHGC turned out contribute to reduce energy at the deteriorated elementary school buildings, compared with the baseline energy performance.

• Bulletin of the Korean Chemical Society
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• v.31 no.1
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• pp.92-99
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• 2010

Photoexcitation of a precursor ion inside a cell floated at high voltage installed in a tandem time-of-flight (TOF) mass spectrometer provides triple tandem mass spectrometric information and allows kinetic and mechanistic studies. In this work, the factors affecting, or downgrading, the performance of the technique were identified. Ion-optical and computational analyses showed that an optimum instrument could be designed by utilizing a reflectron with linear-plus-quadratic potential inside. Theoretical predictions were confirmed by tests with instruments built with different ion-optical layout. With optimized instruments, masses of intermediate ions in the consecutive dissociation of a precursor ion could be determined with the maximum error of $\pm5$ Da. We also observed excellent agreement in dynamical parameters (critical energy and entropy) for the dissociation of a model peptide ion determined by instruments with different ion-optical layout operated under optimum conditions. This suggests that these parameters can be determined reliably by the kinetic method developed previously when properly designed and operated tandem TOF instruments are used.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.53 no.4
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• pp.218-224
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• 2004

We present a miniature Direct Methanol Fuel Cell (micro-DMFC) using platinum sputtered microcolumn electrodes with a limited amount of fuel. We use the microcolumn electrode in order to improve the power density of the micro-DMFC that consists of two electrodes and polymer electrolyte. We also design the built-in fuel chamber in the anode for the portable electronics applications. We design and fabricate both microcolumn and planar electrodes, having an identical projective area of 5mm${\times}$5mm. The diffusion current density of the microcolumn electrode is 1.73 times higher than that of the planar electrode at electrode potential of 1.1V in the half-cell test. The micro-DMFC based on the microcolumn electrodes shows the maximum power of 10.8$\pm$7.54㎼(43.23$\pm$0.16㎼/$\textrm{cm}^2$) at the projective area of 5mm${\times}$5mm, while the planar electrode micro-DMFC shows the maximum power of 0.81$\pm$0.42㎼(3.24$\pm$1.68㎼/$\textrm{cm}^2$) at the same projective area. The micro-DMFC based on the microcolumn electrodes shows 13 times higher power density that the micro-DMFC based on the planar electrodes does.

• Wind and Structures
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• v.29 no.5
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• pp.313-321
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• 2019

The wind blowing at high velocity in an open storage yard leads to wind erosion and loss of material. Fence structures can be constructed around the periphery of the storage yard to reduce the erosion. The fence will cause turbulence and recirculation behind it which can be utilized to reduce the wind erosion and loss of material. A properly designed fence system will produce lesser turbulence and longer shelter effect. This paper aims to show the applicability of Support Vector Machine (SVM) to predict the recirculation length. A SVM model was built, trained and tested using the experimental data gathered from the literature. The newly developed model is compared with numerical turbulence model, in particular, modified $k-{\varepsilon}$ model along with the experimental results. From the results, it was observed that the SVM model has a better capability in predicting the recirculation length. The SVM model was able to predict the recirculation length at a lesser time as compared to modified $k-{\varepsilon}$ model. All the results are analyzed in terms of statistical measures, such as root mean square error, correlation coefficient, and scatter index. These examinations demonstrate that SVM has a strong potential as a feasible tool for predicting recirculation length.