• Journal of Korea Multimedia Society
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• v.25 no.1
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• pp.10-28
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• 2022

In this paper, we present an entry-level COVID-19 stand-alone digitial signage player (CoSiP) which performs not only conventional digital signage functionalities but also fever detection, face mask wearing detection, and KI-pass QR code checking. The overall design of CoSiP is proposed, and implementation of a temperature checking algorithm using a low cost thermal sensor is elaborately presented. Through experiments over datasets and against a developed CoSiP device, it is shown that the fever detection, face mask wearing detection, KI-pass QR code checking as well as signage functionalities of the proposed CoSiP work properly and reliably.

• Journal of Korean Society on Water Environment
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• v.40 no.1
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• pp.19-35
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• 2024

The global pandemic, coronavirus disease caused by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to the implementation of wastewater surveillance as a means to monitor the spread of SARS-CoV-2 prevalence in the community. The challenging aspect of establishing wastewater surveillance requires a well-equipped laboratory for wastewater sample analysis. According to previous studies, RT-PCR-based molecular tests are the most widely used and popular detection method worldwide. However, this approach for the detection or quantification of SARS-CoV-2 from wastewater demands a specialized laboratory, skilled personnel, expensive instruments, and a workflow that typically takes 6 to 8 hours to provide results for a few samples. Rapid and reliable alternative detection methods are needed to enable less-well-qualified practitioners to set up and provide sensitive detection of SARS-CoV-2 within wastewater at regional laboratories. In some cases, the structural and molecular characteristics of SARS-CoV-2 are unknown, and various strategies for the correct diagnosis of COVID-19 have been proposed by research laboratories. The ongoing research and development of alternative and rapid technologies, namely RT-LAMP, ELISA, Biosensors, and GeneXpert, offer a wide range of potential options not only for SARS-CoV-2 detection but also for other viruses. This study aims to discuss the effective regional rapid detection and quantification methods in community wastewater.

• Journal of Information Processing Systems
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• v.13 no.3
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• pp.590-598
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• 2017

Recently, there has been an increase in the number of hazardous events, such as fire accidents. Monitoring systems that rely on human resources depend on people; hence, the performance of the system can be degraded when human operators are fatigued or tensed. It is easy to use fire alarm boxes; however, these are frequently activated by external factors such as temperature and humidity. We propose an approach to fire detection using an image processing technique. In this paper, we propose a fire detection method using multichannel information and gray level co-occurrence matrix (GLCM) image features. Multi-channels consist of RGB, YCbCr, and HSV color spaces. The flame color and smoke texture information are used to detect the flames and smoke, respectively. The experimental results show that the proposed method performs better than the previous method in terms of accuracy of fire detection.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.4
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• pp.149-156
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• 2022

In the current COVID-19 pandemic, fake news and misinformation related to COVID-19 have been causing serious confusion in our society. To accurately detect such fake news, social context-based methods have been widely studied in the literature. They detect fake news based on the social context that indicates how a news article is propagated over social media (e.g., Twitter). Most existing COVID-19 related datasets gathered for fake news detection, however, contain only the news content information, but not its social context information. In this case, the social context-based detection methods cannot be applied, which could be a big obstacle in the fake news detection research. To address this issue, in this work, we collect from Twitter the social context information based on CoAID, which is a COVID-19 news content dataset built for fake news detection, thereby building CoAID⁺ that includes both the news content information and its social context information. The CoAID⁺ dataset can be utilized in a variety of methods for social context-based fake news detection, thus would help revitalize the fake news detection research area. Finally, through a comprehensive analysis of the CoAID⁺ dataset in various perspectives, we present some interesting features capable of differentiating real and fake news.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.79-82
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• 2007

Recently the diffusion of the advancement of mobile communication technique and mobile terminal increased, The users were demanded seamless services when carrying and moving. It proposed the FMIPv6 (Fast Handoff for Mobile IPv6) from the IETF like this meeting this requirement. The handover procedure of the FMIPv6 causes to defecate with movement detection, new CoA configuration and binding update. But, the delay occurs from each process, when the DAD(Duplicate Address Detection) of the CoA executing, the big delay occurs. This paper proposes a scheme of delay reduction, it omits DAD process and stores in the AR(Access Router) relates in the CoA of the mobile terminal information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2027-2031
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• 2007

Recently the diffusion of the advancement of mobile communication technique and mobile terminal increased, The users were demanded seamless services when carrying and moving. It proposed the FMIPv6(Fast Handoff for Mobile IPv6) from the IETF like this meeting this requirement. The handover procedure of the FMIPv6 causes to defecate with movement detection, new CoA configuration and binding update. But, the delay occurs from each process, when the DAD(Duplicate Address Detection) of the CoA executing, the big delay occurs. This paper proposes a scheme of delay reduction, it omits DAD process and stores in the AR(Access Router) relates in the CoA of the mobile terminal information.

• Journal of Microbiology and Biotechnology
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• v.22 no.11
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• pp.1575-1579
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• 2012

Paenibacillus polymyxa is known to be a plant-growth-promoting rhizobacterium. The present study describes a quantitative polymerase chain reaction (qPCR) assay for the specific detection and quantitation of P. polymyxa using a primer pair based on the sequence of a membrane-fusion protein for the amplification of a 268 bp DNA fragment. This study reports that the qPCR-based method is applicable for the rapid and sensitive detection of P. polymyxa and can be used as an alternative method for agricultural soil monitoring.

• Bulletin of the Korean Chemical Society
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• v.15 no.1
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• pp.23-25
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• 1994

A simple analytical method that allows direct monitoring of small amount of CO$_2$ in a CO$_2$ discharge tube which utilizes the optoacoustic detection technique is described. The dependence of the optoacoustic signal on the mole fraction of CO$_2$ was shown that the system responded linearly to the amount of CO$_2$ present in the miniature discharge cavity equipped with Cu electrodes. It was also found that fraction of dissociated CO$_2$ varied from 14 to 37% of the initial concentration which depended on the current and the pressure in the tube. This simple and easy detection method has proven to possess the practical advantages over the conventional systems for the study of CO$_2$ laser electrodes.

• Journal of KIISE
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• v.44 no.8
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• pp.774-781
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• 2017

Mention detection systems use nouns or noun phrases as a head and construct a chunk of text that defines any meaning, including a modifier. The term "mention detection" relates to the extraction of mentions in a document. In the mentions, a coreference resolution pertains to finding out if various mentions have the same meaning to each other. A pointer network is a model based on a recurrent neural network (RNN) encoder-decoder, and outputs a list of elements that correspond to input sequence. In this paper, we propose the use of mention detection using pointer networks. Our proposed model can solve the problem of overlapped mention detection, an issue that could not be solved by sequence labeling when applying the pointer network to the mention detection. As a result of this experiment, performance of the proposed mention detection model showed an F1 of 80.07%, a 7.65%p higher than rule-based mention detection; a co-reference resolution performance using this mention detection model showed a CoNLL F1 of 52.67% (mention boundary), and a CoNLL F1 of 60.11% (head boundary) that is high, 7.68%p, or 1.5%p more than coreference resolution using rule-based mention detection.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.10
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• pp.883-892
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• 2021

This paper provides a process for developing deep learning-based aerial object detection models that can run in realtime on onboard. To improve object detection performance, we pre-process and augment the training data in the training stage. In addition, we perform transfer learning and apply a weighted cross-entropy method to reduce the variations of detection performance for each class. To improve the inference speed, we have generated inference acceleration engines with quantization. Then, we analyze the real-time performance and detection performance on custom aerial image dataset to verify generalization.