• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.219-240
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• 2018

Sentiment analysis, which is one of the text mining techniques, is a method for extracting subjective content embedded in text documents. Recently, the sentiment analysis methods have been widely used in many fields. As good examples, data-driven surveys are based on analyzing the subjectivity of text data posted by users and market researches are conducted by analyzing users' review posts to quantify users' reputation on a target product. The basic method of sentiment analysis is to use sentiment dictionary (or lexicon), a list of sentiment vocabularies with positive, neutral, or negative semantics. In general, the meaning of many sentiment words is likely to be different across domains. For example, a sentiment word, 'sad' indicates negative meaning in many fields but a movie. In order to perform accurate sentiment analysis, we need to build the sentiment dictionary for a given domain. However, such a method of building the sentiment lexicon is time-consuming and various sentiment vocabularies are not included without the use of general-purpose sentiment lexicon. In order to address this problem, several studies have been carried out to construct the sentiment lexicon suitable for a specific domain based on 'OPEN HANGUL' and 'SentiWordNet', which are general-purpose sentiment lexicons. However, OPEN HANGUL is no longer being serviced and SentiWordNet does not work well because of language difference in the process of converting Korean word into English word. There are restrictions on the use of such general-purpose sentiment lexicons as seed data for building the sentiment lexicon for a specific domain. In this article, we construct 'KNU Korean Sentiment Lexicon (KNU-KSL)', a new general-purpose Korean sentiment dictionary that is more advanced than existing general-purpose lexicons. The proposed dictionary, which is a list of domain-independent sentiment words such as 'thank you', 'worthy', and 'impressed', is built to quickly construct the sentiment dictionary for a target domain. Especially, it constructs sentiment vocabularies by analyzing the glosses contained in Standard Korean Language Dictionary (SKLD) by the following procedures: First, we propose a sentiment classification model based on Bidirectional Long Short-Term Memory (Bi-LSTM). Second, the proposed deep learning model automatically classifies each of glosses to either positive or negative meaning. Third, positive words and phrases are extracted from the glosses classified as positive meaning, while negative words and phrases are extracted from the glosses classified as negative meaning. Our experimental results show that the average accuracy of the proposed sentiment classification model is up to 89.45%. In addition, the sentiment dictionary is more extended using various external sources including SentiWordNet, SenticNet, Emotional Verbs, and Sentiment Lexicon 0603. Furthermore, we add sentiment information about frequently used coined words and emoticons that are used mainly on the Web. The KNU-KSL contains a total of 14,843 sentiment vocabularies, each of which is one of 1-grams, 2-grams, phrases, and sentence patterns. Unlike existing sentiment dictionaries, it is composed of words that are not affected by particular domains. The recent trend on sentiment analysis is to use deep learning technique without sentiment dictionaries. The importance of developing sentiment dictionaries is declined gradually. However, one of recent studies shows that the words in the sentiment dictionary can be used as features of deep learning models, resulting in the sentiment analysis performed with higher accuracy (Teng, Z., 2016). This result indicates that the sentiment dictionary is used not only for sentiment analysis but also as features of deep learning models for improving accuracy. The proposed dictionary can be used as a basic data for constructing the sentiment lexicon of a particular domain and as features of deep learning models. It is also useful to automatically and quickly build large training sets for deep learning models.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.

• Journal of Life Science
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• v.18 no.8
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• pp.1090-1095
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• 2008

Marbling (intramuscular fat) is an important factor in determining meat quality in Korean beef market. A grain based finishing system for improving marbling leads to inefficient meat production due to an excessive fat production. Identification of intramuscular fat-specific gene might be achieved more targeted meat production through alternative genetic improvement program such as marker assisted selection (MAS). We carried out ddRT-PCR in 12 and 27 month old Hanwoo steers and detected 300 bp PCR product of the inducible cAMP early repressor (ICER) gene, showing highly gene expression in 27 months old. A 1.5 kb sequence was re-sequenced using primer designed base on the Hanwoo EST sequence. We then predicted the open reading frame (ORF) of ICER gene in ORF finder web program. Tissue distribution of ICER gene expression was analysed in eight Hanwoo tissue using realtime PCR analysis. The highest ICER gene expression showed in Small intestine followed by Longissimus dorsi. Interestingly, the ICER gene expressed 2.5 time higher in longissimus dorsi than in same muscle type, Rump. For gene expression analysis in high- and low marbled individuals, we selected 4 and 3 animal based on the muscle crude fat contents (high is 17-32%, low is 6-7% of crude fat contents). The ICER gene expression was analysed using ANOVA model. Marbling (muscle crude fat contents) was affected by ICER gene (P=0.012). Particularly, the ICER gene expression was 4 times higher in high group (n=4) than low group (n=3). Therefore, ICER gene might be a functional candidate gene related to marbling in Hanwoo.

• Journal of Life Science
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• v.26 no.11
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• pp.1259-1268
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• 2016

In this study, we investigated antimicrobial peptide from the acidified muscle extract of Mytilus coruscus, which mostly inhabits China, Japan, and Korea, to develop a natural product-derived antibiotics substitution in terms of its abuse and restriction. Antimicrobial peptide was purified by $C_{18}$ reversed-phase high-performance liquid chromatography and was detected as having a molecular mass of 6,701 Da by MALDI-TOF/MS. The N-terminal amino acid sequence of the purified peak was obtained from edman degradation, and 20 identified residues shown 100% identity with the N-terminus region of sperm-specific protein and protamine-like PL-II/PL-IV precursor of Mytilus californianus. We also identified 60 open-reading frame (ORF) encoding amino acids with 183 bp of purified peptide based on the obtained amino acid residues. The amino acid sequence of ORF showed 100% and the nucleotide sequence revealed 97.2% identity with the protamine-like PL-II/PL-IV precursor of Mytilus californianus. Synthesized antimicrobial peptide showed antimicrobial activity against gram-positive bacteria, including Bacillus cereus (minimal effective concentration [MEC], $20.8{\mu}g/ml$), Bacillus subtilis (MEC, $0.2{\mu}g/ml$), Streptococcus mutans (MEC, $0.2{\mu}g/ml$), gram-negative bacteria including Pseudomonas aeruginosa (MEC, $5.7{\mu}g/ml$), Escherichia coli (MEC, $2.6{\mu}g/ml$) and fungi, Candida albicans (MEC, $56.3{\mu}g/ml$). In addition, synthesized peptide showed stable activities under heat and salt conditions against gram-positive and gram-negative bacteria, but was inhibited by salt against only C. albicans. With these results, isolated peptide from M. coruscus could be an alternative agent to antibiotics for defending against pathogenic microorganisms, and helpful information to understand the innate immune system of marine invertebrates.

• Journal of the Korean Society of Radiology
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• v.9 no.7
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• pp.529-533
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• 2015

VCUG(Voiding Cystourethrography) study is being performed to check urinary reflex symptom from bladder to ureter or kidney in the method of filling the bladder with radiation opaque contrast agent. However, VCUG study have been performed impersonally, patients have to be naked and open their legs and then void. This method is so impersonal that it is immediately needed to improve the way of testing and crete new aid. Therefore, this study through producing underwear for VCUG, analysis and compares the test time of VCUG, patient radiation dose and patient satisfaction. The target of this study was 79 Male and Female patients who visited genitourinary clinic of PNUYH for their VCUG tests AXIUM Iconos R200(Siemens Medical System : Germany) and self-produced plastic underwears made by vinyl and plasic molding machine were used. The 79 patient were divided into two groups : experiment of patient and comparison group of we patient (using aid) in order to compare, testing time, DAP (dose area product) and patient satisfaction. There was time reduction, from 35.3min of comparison group to 27.8min experimentation group by 7.5min decrease. And comparison group of $4566.6{\mu}Gym^2$(DAP) decreased experimental group (using aid) of $3411.9{\mu}Gym^2$ by $1154.7{\mu}Gym^2$. In the case of patients satisfaction study, anxiety had a drop by 3.45 of comparison group to 2.51 experimentation group by 0.94 decrease. in experimental group. And shame had a drop by 4.02 of comparison group to 3.08 experimentation group by 0.94 increase. in experimental group. Difference of the smooth voiding had a drop by 1.90 of comparison group to 2.84 experimentation group by 0.94 increase. in experimental group. In addition satisfaction had a rise by 1.19 in experimental group. There were also other opinions of uncomfortableness on it and troublesome to wear. VCUG is one of the sensitive care required test. Therefore staff and the aid can give patients such comfortable and the aid can consentive on voiding. As a result test time and DAP can be reduced. It is needed to make testing at more comfortable for patients.