• Informatization Policy
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• v.26 no.4
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• pp.85-106
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• 2019

Recently, there have been increasing cases of collective petitions filed in the electronic petitions system. However, there is no efficient management system, raising concerns on side effects such as increased administrative workload and mass production of social conflicts. Aimed at suggesting a methodology for estimating electronic collective petitions using anomaly detection and corpus linguistics-based content analysis, this study conducted the followings: i) a theoretical review of the concept of collective petitions, ii) estimation of electronic collective petitions using anomaly detection based on nonparametric unsupervised learning, iii) a content similarity analysis on petitions using n-gram cosine angle distance, and iv) a case study on the Voice of Citizens of Changwon City, through which the utility of the proposed methodology, policy implications and future tasks were reviewed.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.453-458
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• 2024

Due to global issues such as climate crisis and rising energy costs, there is an increasing focus on energy conservation and management. In the case of South Korea, approximately 53.5% of the total energy consumption comes from industrial complexes. In order to address this, we aimed to improve issues through the 'Shared Network Utility Plant' among companies using similar energy utilities to find energy-saving points. For effective energy conservation, various techniques are utilized, and stable data supply is crucial for the reliable operation of factories. Many anomaly detection and alert systems for checking the stability of data supply were dependent on Energy Management Systems (EMS), which had limitations. The construction of an EMS involves large-scale systems, making it difficult to implement in small factories with spatial and energy constraints. In this paper, we aim to overcome these challenges by constructing a data collection system and anomaly detection alert system on embedded devices that consume minimal space and power. We explore the possibilities of utilizing anomaly detection alert systems in typical institutions for data collection and study the construction process.

• Journal of Chest Surgery
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• v.15 no.2
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• pp.194-203
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• 1982

In this investigation we undertook to evaluate the utility of radionuclide cardiac angiography in the detection of cardiac shunts before and after surgical correction. Time-activity curves of ventricles and lungs were evaluated after bolus intravenous injection of 99mTc-human serum albumin in 512 preoperative patients and 551 post-operative patients. Omitting 31 cases of technical failure due to poor bolus, we detected shunts in 459 cases of 481 preoperative evaluations, so the detectability was 95.4%. The cases which couldn`t be detected by this method had small amount of shunt. Also the degree of shunt detected by radioisotope methods were well correlated with oxymetry method. [r=0.89, p<0.01 ] In postoperative evaluations, 18 out of 411 patients with left to right shunt and 10 out of 140 right to left shunt were found to have remnant shunts with radionuclide cardiac angiography. Of the 28 cases with failed operation, 2 were confirmed in reoperation, 2 by cardiac catheterization, 2 by two -dimensional echocardiography. All except one .f these patients had membranous ventricular septal defects and those with left to right shunts had moderate to severe pulmonary hypertension and shunt amount. Also those had larger septal defects than control group. We consider that radionuclide cardiac angiography is a simple and noninvasive method which can show the preoperative diagnosis and postoperative follow up of cardiac shunts.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.240-241
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• 2006

Islanding operations of DG usually occur when power supply from the main utility is interrupted due to several reasons but the DG keeps supplying power into the distribution networks. These kinds of islanding conditions cause negative impacts on protection, operation, and management of distribution systems. Therefore, it is necessary to effectively detect the islanding conditions and swiftly disconnect DG from distribution network. This paper proposes the islanding detection algorithm for DG using the change of the voltage unbalance and the output power of DG. The proposed method effectively combines the conventional parameters for detecting the islanding conditions. The proposed methods were verified using the radial distribution network of IEEE 34 bus.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.4
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• pp.426-435
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• 1999

A high impedance fault(HIF) is one of the serious problems facing the electric utility industry today. Because of the high impedance of a downed conductor under some conditions these faults are not easily detected by over-current based protection devices and can cause fires and personal hazard. In this paper a new method for detection of HIF which uses adaptive neuro-fuzzy inference system (ANFIS) is proposed. Since arcing fault current shows different changes during high and low voltage portion of conductor voltage waveform we firstly divided one cycle of fault current into equal spanned four data windows according to the mangnitude of conductor voltage. Fast fourier transform(FFT) is applied to each data window and the frequency spectrum of current waveform are chosen asinputs of ANFIS after input selection method is preprocessed. Using staged fault and normal data ANFIS is trained to discriminate between normal and HIF status by hybrid learning algorithm. This algorithm adapted gradient descent and least square method and shows rapid convergence speed and improved convergence error. The proposed method represent good performance when applied to staged fault data and HIFLL(high impedance like load)such as arc-welder.

• Bulletin of the Korean Chemical Society
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• v.30 no.1
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• pp.102-106
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• 2009

A rapid and sensitive chemiluminescence (CL) method using flow-injection (FI) has been developed for the determination of mandelic acid which is based on the enhancement of mandelic acid to the CL intensity of ${Ru(bipy)_{3}}^{2+}$-Ce(IV) system. The enhancement effect was dependent on the concentration of mandelic acid, based on which, CL system was established for the determination of mandelic acid. The concentrations of ${Ru(bipy)_{3}}^{2+}$+, Ce(IV), and $H_2SO_4$ were optimized. Under the optimum experimental conditions, the linear range and detection limit are 1.46-342.0 ${\mu}g/ml$ and 0.072 ${\mu}g/ml$, respectively. The correlation coefficient (R) was 0.99732. The utility of this method was demonstrated by determining mandelic acid in capsules and human urine sample.

• Archives of Pharmacal Research
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• v.19 no.6
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• pp.469-474
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• 1996

A rapid and sensitive method has been developed to detect hepatitis B virus DNA (HBV) by nested polymerase chain reaction (PCR) technique with primers specific for the surface and core regions in capillary thermal cycler within 80 min. The lower limit for detection by present PCR method is $10^{-5}$ pg of recombinant HBV DNA which is equivalent to that determined by one round of PCR amplification and Southern blot hybridization analysis. When boiled HBV positive serum was serially diluted 10-fold, HBV DNA was successfully determined in $1{\mu}l-10^{-3}$ of serum. HBV DNA was detected by present method in 69 clinical samples including HBsAg positives and negatives by enzyme-linked immunosorbent assay (ELISA). When serum samples were amplified by nested PCR using surface and core region primers, HBV DNAs were detected in 37 of 69 samples (53.6%) and 18 of 69 samples (26.1%), respectively. These results can inform the infectious state of HBsAg positive pateints. A simple and rapid nested PCR protocol by using boiled serum as DNA template has been described for the clinical utility to determine HBV DNA in human serum.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.92-98
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• 2019

In this paper, we propose a deep learning system based on morphological neural network(MNN). The deep learning layers are morphological operation layer, pooling layer, ReLU layer, and the fully connected layer. The operations used in morphological layer are erosion, dilation, and edge detection, etc. Unlike CNN, the number of hidden layers and kernels applied to each layer is limited in MNN. Because of the reduction of processing time and utility of VLSI chip design, it is possible to apply MNN to various mobile embedded systems. MNN performs the edge and shape detection operations with a limited number of kernels. Through experiments using database images, it is confirmed that MNN can be used as a deep learning system and its performance.

• Textile Coloration and Finishing
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• v.32 no.4
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• pp.185-192
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• 2020

A novel binding site for metal ion made by designing molecule with tetrazolo quinoline with hydrazine carboxamide (TQC) and the designed molecule successfully synthesized. The probe works by selectively detecting Al3+ ion via both fluorimetric and colorimetric approach. The probe's effectiveness towards aluminium ion detection is highly sensitive and selective with no substantial interference with other competing ions. The added Al3+ ion to TQC fetched a rapid change of visual color to yellow from colorless, also the response of fluorescence turn-on. The fluorescence turn-on and color change visibly by the probe TQC with Al3+ ion credited to the ICT phenomenon (intramolecular charge-transfer transition). The likely interaction of the probe with aluminium ion has also been there predicted from ESI-MS spectral analysis results. The usefulness of the probe confirmed by practical utility by making a test kit to monitor Al3+ ion in water which showed a naked eye detection by notable color change.

• Korean Journal of Agricultural Science
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• v.48 no.4
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• pp.1051-1065
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• 2021

Recent times have seen sustained increases in genetically modified (GM) crops not only for cultivation but also for the utility of food and feed worldwide. Domestically, commercial planting and the accidental or unintentional release of living modified (LM) crops into the environment are not approved. Many detection methods had been devised in an effort to realize effective management of the safety of agricultural genetic resources. In order to develop event-specific polymerase chain reaction (PCR) markers for LM crops, we analyzed the genetic information of LM crops. Genetic components introduced into crops are of key importance to provide a basis for the development of detection methods for LM crops. To this end, a total of 18 varieties from four major LM crop species (maize, canola, cotton, and soybeans) were subjected to an analysis. The genetic components included introduced genes, promoters, terminators and selection markers. Thus, if proper monitoring techniques and single or multiplex PCR strategies that rely on selection markers can be established, such an accomplishment can be regarded as a feasible solution for the safe management of staple crop resources.