• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.365-385
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• 2022

The easy payment service is a payment and remittance service that uses a simple authentication method. As online transactions have increased due to COVID-19, the use of an easy payment service is increasing. At the same time, electronic financial industries such as Naver Pay, Kakao Pay, and Toss are diversifying the competition structure of the easy payment market; meanwhile overseas fintech companies PayPal and Alibaba have a unique market share in their own countries, while competition is intensifying in the domestic easy payment market, as there is no unique market share. In this study, the participants in the easy payment market were classified as electronic financial companies, mobile phone manufacturers, and financial companies, and a SWOT analysis was conducted on the representative services in each industry. The analysis examined the user reviews of Google Play Store via a topic modeling analysis, and it employed positive topics as strengths and negative topics as weaknesses. In addition, topic modeling was conducted by dividing news articles into political, economic, social, and technology (PEST) articles to derive the opportunities and threats to easy payment services. Through this research, we intend to confirm the service capabilities of easy payment companies and propose a service activation strategy that allows gaining the upper hand in the market.

• The Korea Journal of Herbology
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• v.24 no.4
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• pp.115-120
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• 2009

Objectives : Due to the morphological similarity and frequent occurrence of intermediate forms as well as morphological variations of aerial part, the correct identification between Rhei Radix et Rhizoma and Rhei Undulatai Rhizoma is very difficult. To develop a reliable method for correct identification and improving the quality standards of Rhei Radix et Rhizoma and Rhei Undulatai Rhizoma, we analyzed RAPD and developed SCAR marker. Methods : To amplify target DNA at the genomic level, 32 Operon 10-mer random primers were applied with four Rheum species, R. officinale, R. palmatum, R. tanguticum and R. undulatum. The nucleotide sequences were determined and species-specific primers were prepared depending on the species-specific RAPD amplicons after subcloned into the pGEM-Teasy vector. To develop the SCAR markers, species-specific PCR amplification and multiplex-PCR were carried out using the single species-specific primer pairs and combinations of them, respectively. Results : We used RAPD analysis of four Rheum plant species to obtain several species-specific RAPD amplicons. From nucleotide sequences of these RAPD amplicons, we developed two SCAR markers that amplified 314 bp and 390 bp DNA fragments in only R. undulatum but not in R. officinale, R. palmatum, R. tanguticum and R. undulatum, for distinguishing Rhei Undulatai Rhizoma and Rhei Radix et Rhizoma. Furthermore, we established SCAR markers for the simultaneous discrimination of the three species within a single reaction by using multiplex-PCR. Conclusions : These genetic markers can be used for the efficient discrimination of plants species and commercial herbal medicines between Rhei Undulatai Rhizoma and Rhei Radix et Rhizoma, to ultimately prevent indiscriminate distribution and prescription of these herbal medicines.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.209-224
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• 2024

Speaker verification is becoming popular as a method of non-face-to-face identity authentication. It involves determining whether two voice data belong to the same speaker. In cases where the criminal's voice remains at the crime scene, it is vital to establish a speaker verification system that can accurately compare the two voice evidence. In this study, to achieve this, a new speaker verification system was built using a deep learning model for Korean language. High-dimensional voice data with a high variability like background noise made it necessary to use deep learning-based methods for speaker matching. To construct the matching algorithm, the ECAPA-TDNN model, known as the most famous deep learning system for speaker verification, was selected. A large dataset of the voice data, Voxceleb, collected from people of various nationalities without Korean. To study the appropriate form of datasets necessary for learning the Korean language, experiments were carried out to find out how Korean voice data affects the matching performance. The results showed that when comparing models learned only with Voxceleb and models learned with datasets combining Voxceleb and Korean datasets to maximize language and speaker diversity, the performance of learning data, including Korean, is improved for all test sets.

• Food Science of Animal Resources
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• v.28 no.3
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• pp.276-282
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• 2008

It is estimated that over 80% of deer antlers produced in the world are consumed in Korea. However, mislabeling or fraudulent replacement of costly antlers with cheaper ones is one of the most common problems in the domestic antler market. Therefore, there is a great need for the development of technology to identify species of antlers. This study was carried out to develop an accurate and reliable method for the identification and authentication of species or subspecies of antlers using DNA sequence analysis and comparison of mitochondrial cytochrome band D-loop region genes among antlers of five deer species, Cervus elaphus sibericus, Cervus elaphus canadensis, Cervus nippon, Cervus elaphus bactrianus and Rangifer tarandus. A variable region of cytochrome band D-loop genes was amplified using PCR with specifically designed primers and sequenced directly. The cytochrome band D-loop region genes showed different DNA sequences between the species of antlers and thus it is possible to differentiate between species on the basis of sequence variation. To distinguish between reindeer (Rangifer tarandus) antlers and other deer antlers, PCR amplicons of the cytochrome b gene were digested with the restriction enzymes NlaIV and TaqI, respectively, which generates a species-specific DNA profile of the reindeer. In addition, samples of 32 sliced antlers labeled Cervus elaphus sibericus from commercial markets were collected randomly and the mt DNA D-loop region of these antler samples was sequenced. Among the antler samples investigated, only 62.5% were from Cervus elaphus sibericus, and others were from Cervus elaphus bactrianus (25.0%), elk (Cervus elaphus canadensis) and reindeer (Rangifer tarandus). Our results suggest that DNA sequencing of mt DNA and PCR-RFLP methods using NlaIV and TaqI enzymes are useful for the identification and discrimination of deer antler species by routine analysis.