• Analytical Science and Technology
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• v.22 no.5
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• pp.395-406
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• 2009

The determination of iodine in the spent nuclear fuel and the volatile behavior during its acid dissolution have been studied by NAA(neutron activation analysis) and electron probe microanalysis (EPMA). Simulated spent fuels (SIMFUELs) were dissolved in $HNO_3$(1+1) at $90^{\circ}C$ for 8 hours. The iodine remained in a dissolver solution after dissolution, and that condensed in dissolution apparatus and trapped in the adsorbent by volatilization during the dissolution were determined, respectively. The condensed iodine was recovered by the redistillation with $HNO_3$(1+1) after transfer of the dissolver solution. The iodines in the dissolver and redistilled solution were separated by solvent extraction followed by ion exchange or precipitation method and determined by RNAA (radiochemical neutron activation analysis). The ion exchange column and filtration kit used for the isolation of iodine, which were prepared with a polyethylene tube, were used as an insert in the pneumatic tube for neutron irradiation. The iodine volatilized during the dissolution of SIMFUELs was collected in a trapping tube containing Ag-silica gel (Ag-impregnated silica gel) adsorbent, and the distribution of iodine trapped in the adsorbents were determined by EPMA. The adsorbing characteristics shown with the SIMFUELs were compared with those shown with a real spent fuel from the nuclear power plant.

• Analytical Science and Technology
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• v.21 no.6
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• pp.535-542
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• 2008

A liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI/MS/MS) method was developed for the determination and confirmation of clenbuterol in bovine muscle and milk. Clenbuterol and clenbuterol-D9 using as an internal standard in samples were extracted with ethyl acetate after hydrolysis and evaporated to dryness. The extracts were dissolved in 20% methanol and cleaned using HLB solid-phase extraction cartridge. The analytes were detected by LC-ESI/MS/MS on a $C_{18}$ column. Mass spectral acquisition was done in selected reaction monitoring (SRM) in positive ion mode to provide a high degree of sensitivity. Using MS/MS with SRM mode, the transitions (precursor to product) monitored were m/z 277${\rightarrow}$203 for clenbuterol, and m/z 286${\rightarrow}$204 for internal standard. The limits of quantitation (LOQ) and mean recoveries of clenbuterol in bovine muscle were $0.2{\mu}g/kg$ and 84.3~91.1%, respectively. The LOQ and mean recoveries in milk were $0.05{\mu}g/kg$ and 87.7~98.3%, respectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1A
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• pp.125-133
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• 2008

According to longer and longer span, dynamic instability of stay cable should be prevented. Dynamic instability occurs mainly symmetric 1st mode and antisymmetric 1st mode in stay cable. Especially symmetric 1st mode has a lot of influence on sag. Therefore fundamental frequency of stay cable is different from that of taut sting. Irvine, Triantafyllou, Ahn etc. analyzed dynamic behavior of taut cable with sag through analytical technical and their researches give important results for large bounds of Irvine parameter. But each research shows mutually different values out of characteristic (cross-over or mode-coupled) point and each solution of frequency equations of all researchers can be very difficultly found because of their very high non-linearity. Presented study focuses on fundamental frequency of stay cable. Generalized mechanical energy with symmetric 1st mode vibration shape satisfied boundary conditions is evolved by Rayleigh-Ritz method. It is possible to give linear analytic solution within characteristic point. Error by this approach shows only below 3% at characteristic point against existing researches. And taut cable don't exceed characteristic point. I.e. high accuracy, easy solving techniques, and a little bit limitations. Therefore presented study can be announced that it is good study ergonomically.

• Journal of Food Hygiene and Safety
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• v.38 no.3
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• pp.176-183
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• 2023

The extraction and filtration of red ginseng with a mixed solvent of water and alcohol-a common processing method-and the production of a concentrate through heat treatment, such as steaming, leads to its hydrolysis or polymerization. Approximately 200 ginsenosides have consequently been detected in small amounts, in addition to the identification of the functions of approximately 30 major ginsenosides. This complicates the identification of the functionality of red ginseng and its efficacy, and has negative effects as a functional food, as the astringent taste becomes stronger with an increase in the number of extractions. The red ginseng concentrate was, therefore, extracted at a low temperature (less than 40 ℃) and processed to eliminate these negative aspects, with a specific focus on the characteristics of the functional components of ginsenosides.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1A
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• pp.75-84
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• 2009

The present study assesses the chloride threshold level for corrosion of steel in concrete by examining the properties of four different binders used for blended concrete in terms of chloride binding, buffering of cement matrix to a pH fall and the corrosion behaviour. As binders, ordinary Portland cement (OPC), 30% pulverised fuel ash (PFA), 60% ground granulated blast furnace slag (GGBS) and 10% silica fume (SF) were used in a concrete mix. Testing for chloride binding was carried out using the water extraction method, the buffering of cement matrix was assessed by measuring the resistance to an artificial acidification of nitric acid, and the corrosion rate of steel in mortar with chlorides in cast was measured at 28 days using an anodic polarisation technique. Results show that the chloride binding capacity was much affected by $C_{3}A$ content and physical adsorption, and its order was 60% GGBS>30% PFA>OPC>10% SF. The buffering of cement matrix to a pH fall was varied with binder type and given values of the pH. From the result of corrosion test, it was found that the chloride threshold ranged 1.03, 0.65, 0.45 and 0.98% by weight of cement for OPC, 30% PFA, 60% GGBS and 10% SF respectively, assuming that corrosion starts at the corrosion rate of $0.1-0.2{\mu}A/cm^{2}$. The mole ratio of [$Cl^{-}$]:[$H^{+}$], as a new presentation of the chloride threshold, indicated the value of 0.008-0.009, irrespective of binder, which would be indicative of the inhibitive characteristic of binder.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.29-35
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• 2023

CCTV is used for various purposes such as crime prevention, public safety reinforcement, and traffic management. However, as the range and resolution of the camera improve, there is a risk of exposing personal information in the video. Therefore, there is a need for new technologies that can identify individuals while protecting personal information in images. In this paper, we propose histogram-based singular value decomposition for object identification and tracking. The proposed method distinguishes different objects present in the image using color information of the object. For object recognition, YOLO and DeepSORT are used to detect and extract people present in the image. Color values are extracted with a black-and-white histogram using location information of the detected person. Singular value decomposition is used to extract and use only meaningful information among the extracted color values. When using singular value decomposition, the accuracy of object color extraction is increased by using the average of the upper singular value in the result. Color information extracted using singular value decomposition is compared with colors present in other images, and the same person present in different images is detected. Euclidean distance is used for color information comparison, and Top-N is used for accuracy evaluation. As a result of the evaluation, when detecting the same person using a black-and-white histogram and singular value decomposition, it recorded a maximum of 100% to a minimum of 74%.

• Journal of Cadastre & Land InformatiX
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• v.53 no.2
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• pp.5-18
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• 2023

As the development of drones and sensors accelerates, new services and values are created by fusing data acquired from various sensors mounted on drone. However, the construction of spatial information through data fusion is mainly constructed depending on the image, and the quality of data is determined according to the specification and performance of the hardware. In addition, it is difficult to utilize it in the actual field because expensive equipment is required to construct spatial information of high-quality. In this study, super-resolution was performed by applying deep learning to low-resolution images acquired through RGB and THM cameras mounted on a drone, and quantitative evaluation and feature point extraction were performed on the generated high-resolution images. As a result of the experiment, the high-resolution image generated by super-resolution was maintained the characteristics of the original image, and as the resolution was improved, more features could be extracted compared to the original image. Therefore, when generating a high-resolution image by applying a low-resolution image to an super-resolution deep learning model, it is judged to be a new method to construct spatial information of high-quality without being restricted by hardware.

• Sim-seong Yeon-gu
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• v.33 no.1
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• pp.61-80
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• 2018

We investigated whether the 81 items of the Gray-Wheelwright test correctly measure the concept of Jung's typology and aimed to refine the test. Participants (n=431) completed the Gray-Wheelwright test, and the results were analyzed using factor analysis with the varimax rotation and the maximum likelihood extraction method. A pair of opposing attitudes, introversion/extroversion, or one of the two pairs of opposing functional types, thinking/feeling or intuition/sensation, was labeled to the extracted factor according to the majority type of the items in the factor. The minority items or items not included in any factors were excluded from making a short form of the Gray-Wheelwright test with 45 items. We used intraclass correlation (ICC) coefficient and Cronbach's alpha for the test-retest reliability and internal consistency of the test, respectively. The newly developed short form of the Gray-Wheelwright test measured the Jung's personality types well, which was comparable to the original one while reducing time and effort required for the testing.

• Journal of Korean Society of Archives and Records Management
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• v.24 no.2
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• pp.89-112
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• 2024

Metadata is a crucial component of record management, playing a vital role in properly managing and understanding the record. In cases where automatic metadata assignment is not feasible, manual input by records professionals becomes necessary. This study aims to alleviate the challenges associated with manual entry by proposing a method that harnesses ChatGPT technology for extracting records management metadata elements. To employ ChatGPT technology, a Python program utilizing the LangChain library was developed. This program was designed to analyze PDF documents and extract metadata from records through questions, both with a locally installed instance of ChatGPT and the ChatGPT online service. Multiple PDF documents were subjected to this process to test the effectiveness of metadata extraction. The results revealed that while using LangChain with ChatGPT-3.5 turbo provided a secure environment, it exhibited some limitations in accurately retrieving metadata elements. Conversely, the ChatGPT-4 online service yielded relatively accurate results despite being unable to handle sensitive documents for security reasons. This exploration underscores the potential of utilizing ChatGPT technology to extract metadata in records management. With advancements in ChatGPT-related technologies, safer and more accurate results are expected to be achieved. Leveraging these advantages can significantly enhance the efficiency and productivity of tasks associated with managing records and metadata in archives.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.57-67
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• 2024

This paper explores the potential of electromyography (EMG) as a means of gesture recognition for user input in gesture-based interaction. EMG utilizes small electrodes within muscles to detect and interpret user movements, presenting a viable input method. To classify user gestures based on EMG data, machine learning techniques are employed, necessitating the preprocessing of raw EMG data to extract relevant features. EMG characteristics can be expressed through formulas such as Integrated EMG (IEMG), Mean Absolute Value (MAV), Simple Square Integral (SSI), Variance (VAR), and Root Mean Square (RMS). Additionally, determining the suitable time for gesture classification is crucial, considering the perceptual, cognitive, and response times required for user input. To address this, segment sizes ranging from a minimum of 100ms to a maximum of 1,000ms are varied, and feature extraction is performed to identify the optimal segment size for gesture classification. Notably, data learning employs overlapped segmentation to reduce the interval between data points, thereby increasing the quantity of training data. Using this approach, the paper employs four machine learning models (KNN, SVC, RF, XGBoost) to train and evaluate the system, achieving accuracy rates exceeding 96% for all models in real-time gesture input scenarios with a maximum segment size of 200ms.