• Journal of Korea Society of Industrial Information Systems
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• v.27 no.5
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• pp.1-11
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• 2022

With the development of deep learning technology, various research and development are underway to estimate preference rankings through learning, and it is used in various fields such as web search, gene classification, recommendation system, and image search. Approximation algorithms are used to estimate deep learning-based preference ranking, which builds more than k comparison sets on all comparison targets to ensure proper accuracy, and how to build comparison sets affects learning. In this paper, we propose a k-disjoint comparison set generation algorithm and a k-chain comparison set generation algorithm, a novel algorithm for generating paired comparison sets for crowd-sourcing-based deep learning affinity measurements. In particular, the experiment confirmed that the k-chaining algorithm, like the conventional circular generation algorithm, also has a random nature that can support stable preference evaluation while ensuring connectivity between data.

• ALGAE
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• v.36 no.4
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• pp.241-261
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• 2021

Amphidinium species are amongst the most abundant benthic dinoflagellates in marine intertidal sandy ecosystems. Some of them produce a variety of bioactive compounds that have both harmful effects and pharmaceutical potential. In this study, Amphidinium cells were isolated from intertidal sand collected from the East China Sea. The two strains established were subjected to detailed examination by light, and scanning and transmission electron microscopy. The vegetative cells had a minute, irregular, and triangular-shaped epicone deflected to the left, thus fitting the description of Amphidinium sensu stricto. These strains are distinguished from other Amphidinium species by combination characteristics: (1) longitudinal flagellum inserted in the lower third of the cell; (2) icicle-shaped scales, 276 ± 17 nm in length, on the cell body surface; (3) asymmetrical hypocone with the left side longer than the right; and (4) presence of immotile cells. Therefore, they are described here as Amphidinium stirisquamtum sp. nov. The molecular tree inferred from small subunit rRNA, large subunit rRNA, and internal transcribed spacer-5.8S sequences revealed that A. stirisquamtum is grouped together with the type species of Amphidinium, A. operculatum, in a fully supported clade, but is distantly related to other Amphidinium species bearing body scale. Live A.stirisquamtum cells greatly affected the survival of rotifers and brine shrimp, their primary grazers, making them more susceptible to predation by the higher tropic level consumers in the food web. This will increase the risk of introducing toxicity, and consequently, the bioaccumulation of toxins through marine food webs.

• Smart Media Journal
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• v.12 no.9
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• pp.152-158
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• 2023

This study analyzed the consciousness, unconsciousness, and individuation process of 'Cheongmyeong', the protagonist presented in the webtoon "Return of the Blossoming Blade", based on Jung's theory of individuation. The subject of the research was the webtoon "Return of the Blossoming Blade", which has formed a readership across various genders and age groups, based on a successful web novel. The individuation process of the protagonist of "Return of the Blossoming Blade", analyzed using Jung's theory, is as follows: Firstly, the protagonist's ego originated from the shadow derived from the unconscious. Secondly, the protagonist's persona is social and positive in reality, but the personal persona manifested as an unrevealed shadow. Thirdly, the protagonist's anima/animus connects the profound inner consciousness with reality, maintaining a complementary relationship with the persona. Fourthly, the protagonist's Self symbolizes the collective ideal human and the essence of the volcano. The protagonist was shown to achieve individuation through a continuous repetitive process of integrating consciousness and unconsciousness, and through the compensatory process.

• Asian Journal for Public Opinion Research
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• v.12 no.1
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• pp.53-74
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• 2024

The proliferation of health misinformation gained momentum amidst the outbreak of the novel coronavirus disease 2019 (COVID-19). People stuck in their homes, without work pressure, regardless of health concerns towards personal, family, or peer groups, consistently demanded information. People became engaged with misinformation while attempting to find health information content. This study used the content analysis method and analyzed 1,154 misinformation stories from four prominent signatories of the International Fact-Checking Network during the pandemic. The study finds the five main categories of misinformation related to the COVID-19 pandemic. These are 1) the severity of the virus, 2) cure, prevention, and treatment, 3) myths and rumors about vaccines, 4) health authorities' guidelines, and 5) personal and social impacts. Various sub-categories supported the content characteristics of these categories. The study also analyzed the emotional valence of health misinformation. It was found that misinformation containing negative sentiments got higher engagement during the pandemic. Positive and neutral sentiment misinformation has less reach. Surprise, fear, and anger/aggressive emotions highly affected people during the pandemic; in general, people and social media users warning people to safeguard themselves from COVID-19 and creating a confusing state were found as the primary motivation behind the propagation of misinformation. The present study offers valuable perspectives on the mechanisms underlying the spread of health-related misinformation amidst the COVID-19 outbreak. It highlights the significance of discerning the accuracy of information and the feelings it conveys in minimizing the adverse effects on the well-being of public health.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.55-75
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• 2010

Sequential pattern mining aims to discover interesting sequential patterns in a sequence database, and it is one of the essential data mining tasks widely used in various application fields such as Web access pattern analysis, customer purchase pattern analysis, and DNA sequence analysis. In general sequential pattern mining, only the generation order of data element in a sequence is considered, so that it can easily find simple sequential patterns, but has a limit to find more interesting sequential patterns being widely used in real world applications. One of the essential research topics to compensate the limit is a topic of weighted sequential pattern mining. In weighted sequential pattern mining, not only the generation order of data element but also its weight is considered to get more interesting sequential patterns. In recent, data has been increasingly taking the form of continuous data streams rather than finite stored data sets in various application fields, the database research community has begun focusing its attention on processing over data streams. The data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. In data stream processing, each data element should be examined at most once to analyze the data stream, and the memory usage for data stream analysis should be restricted finitely although new data elements are continuously generated in a data stream. Moreover, newly generated data elements should be processed as fast as possible to produce the up-to-date analysis result of a data stream, so that it can be instantly utilized upon request. To satisfy these requirements, data stream processing sacrifices the correctness of its analysis result by allowing some error. Considering the changes in the form of data generated in real world application fields, many researches have been actively performed to find various kinds of knowledge embedded in data streams. They mainly focus on efficient mining of frequent itemsets and sequential patterns over data streams, which have been proven to be useful in conventional data mining for a finite data set. In addition, mining algorithms have also been proposed to efficiently reflect the changes of data streams over time into their mining results. However, they have been targeting on finding naively interesting patterns such as frequent patterns and simple sequential patterns, which are found intuitively, taking no interest in mining novel interesting patterns that express the characteristics of target data streams better. Therefore, it can be a valuable research topic in the field of mining data streams to define novel interesting patterns and develop a mining method finding the novel patterns, which will be effectively used to analyze recent data streams. This paper proposes a gap-based weighting approach for a sequential pattern and amining method of weighted sequential patterns over sequence data streams via the weighting approach. A gap-based weight of a sequential pattern can be computed from the gaps of data elements in the sequential pattern without any pre-defined weight information. That is, in the approach, the gaps of data elements in each sequential pattern as well as their generation orders are used to get the weight of the sequential pattern, therefore it can help to get more interesting and useful sequential patterns. Recently most of computer application fields generate data as a form of data streams rather than a finite data set. Considering the change of data, the proposed method is mainly focus on sequence data streams.

• Journal of the Korean Institute of Gas
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• v.16 no.6
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• pp.128-135
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• 2012

In this paper, we proposed a system and a scenario to raise efficiency of gas safety management by developing wireless ZigBee communication modules, smart-home gas safety appliances and the system suitable for gas safety. Our designed system consists of a micom gas meter, an automatic extinguisher, sensors, and a wall-pad. A micom-gas-meter monitors gas flow, gas pressure, and earthquake. An automatic fire extinguisher checks combustible gas leaks and temperature of $100^{\circ}C$(cut off) and $130^{\circ}C$(fire). Sensors measure smoke and CO gas. In our novel system, a micom-gas meter cut off inner valve with warnings, an automatic fire extinguisher cut off middle valve and spray extinguishing materials, and sensors generate signals when detecting smoke and CO and then take a next action. Gas safety appliances and sensors automatically takes measures, and transmit those information to a wall-pad. The wall-pad again transmits real time information to server. Users can check and manage gas safety situations by connecting BcN server through web or mobile application. We hereby devised scenarios for gas safety and risk management based on the smart, and demonstrated their efficiency through test applied to filed.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.5
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• pp.1803-1811
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• 2015

Hepatoma-derived growth factor (HDGF) is a novel jack-of-all-trades in cancer. Here we quantify the prognostic impact of this biomarker and assess how consistent is its expression in solid tumors. A comprehensive search strategy was used to search relevant literature updated on October 3, 2014 in PubMed, EMBASE and WEB of Science. Correlations between HDGF expression and clinicopathological features or cancer prognosis was analyzed. All pooled HRs or ORs were derived from random-effects models. Twenty-six studies, primarily in Eastern Asia, covering 2,803 patients were included in the analysis, all of them published during the past decade. We found that HDGF overexpression was significantly associated with overall survival (OS) ($HR_{OS}=2.35$, 95%CI=2.04-2.71, p<0.001) and disease free survival (DFS) ($HR_{DFS}=2.25$, 95%CI =1.81-2.79, p<0.001) in solid tumors, especially in non-small cell lung cancer, hepatocellular carcinoma and cholangiocarcinoma (CCA). Moreover, multivariate survival analysis showed that HDGF overexpression was an independent predictor of poor prognosis ($HR_{OS}=2.41$, 95%CI: 2.02-2.81, p<0.001; $HR_{DFS}=2.39$, 95%CI: 1.77-3.24, p<0.001). In addition, HDGF overexpression was significantly associated with tumor category (T3-4 versus T1-2, OR=2.12, 95%CI: 1.17-3.83, p=0.013) and lymph node status (N+ versus N-, OR=2.37, 95%CI: 1.31-4.29, p=0.03) in CCA. This study provides a comprehensive examination of the literature available on the association of HDGF overexpression with OS, DFS and some clinicopathological features in solid tumors. Meta-analysis results provide evidence that HDGF may be a new indicator of poor cancer prognosis. Considering the limitations of the eligible studies, other large-scale prospective trials must be conducted to clarify the prognostic value of HDGF in predicting cancer survival.

• Journal of KIISE:Databases
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• v.37 no.5
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• pp.258-266
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• 2010

In this paper, we introduce a novel method to predict next update of blogs. The number of RSS feeds registered on meta-blogs is on the order of several million. Checking for updates is very time consuming and imposes a heavy burden on network resources. Since blog search engine has limited resources, there is a fix number of blogs that it can visit on a day. Nevertheless we need to maximize chances of getting new data, and the proposed method which predicts update probability on blogs could bring better chances for it. Also this work is important to avoid distributed denial-of-service attack for the owners of blogs. Furthermore, for the internet as whole this work is important, too, because our approach could minimize traffic. In this study, we assumed that there is a specific pattern to when a blogger is actively posting, in terms of days of the week and, more specifically, hours of the day. We analyzed 15,119 blogs to determine a blogger's posting preference. This paper proposes a method to predict the update probability based on a blogger's posting history and preferred days of the week. We applied proposed method to 12,115 blogs to check the precision of our predictions. The evaluation shows that the model has a precision of 0.5 for over 93.06% of the blogs examined.

• Journal of Sericultural and Entomological Science
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• v.53 no.1
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• pp.44-49
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• 2015

We characterized tissue specific-expressed genes in the posterior silk gland of Bombyx mori using by the Annealing Control Primer based differential display-PCR manner. In this study, we isolated 34 differentially expressed PCR amplicons, which one of these was identified as a novel transcript named as ACP-16 (366 bp), its expression was observed only in the posterior silk glands by Northern blot analysis. To determine promoter region of the ACP-16, we isolated and analyzed a phage DNA having 1.7 kb-long genome DNA including the open reading flame and 5'- upstream untranslated region of the ACP-16 gene from a genomic DNA library. We have estimated a promoter region of the ACP-16 gene by a web promoter prediction engine, which locates -750 ~ -165 from translation initiation site (ATG, +1). ACP-16 gene is necessary to more studies about critical biological role in order to apply the silkworm's transgenic system.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.3
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• pp.13-20
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• 2011

In this paper, we proposed a system to raise gas safety management by using the wireless communication module and intelligent gas safety appliances. Our designed systems configure a micom-gas meter, an automatic extinguisher, sensors, and a wallpad. A micom-gas-meter monitors gas flow, gas pressure, and earthquake. An automatic fire extinguisher checks gas(combustible) leaks and temperature of $100^{\circ}C$ and $130^{\circ}C$. Sensors measure smoke and CO gas. In our novel system, a micom-gas meter cut off inner valve with warnings, an automatic fire extinguisher cut off middle valve and spray extinguishing materials, and sensors generate signals for smoke and CO when occurring gas risk. Gas safety appliances and sensors takes safety measures, and transmit those signal to a wallpad. The wallpad again transmit signal like events to a control server. Users can connect web pages for gas safety through B-ISDN and control and manage them. We hereby devised scenarios for gas safety and risk management, and demonstrated their effectiveness through experiments.