• Title/Summary/Keyword: Point-extraction

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An Analysis of a 100-Years-Old Map of the Heritage Trees in Jeju Island (제주도 노거수 자연유산의 100년 전과 현재 분석)

  • Song, Kuk-Man;Kim, Yang-Ji;Seo, Yeon-Ok;Choi, Hyung-Soon;Choi, Byoung-Ki
    • Journal of the Korean Institute of Traditional Landscape Architecture
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    • v.37 no.2
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    • pp.20-29
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    • 2019
  • The purpose of this study is to verify and reconstruct the record information for big old trees of Jeju on the basis of the precise map of Jeju island in 1918 which was produced 100 years ago. For the analysis of high altitude, coordinate system and georeferencing were performed by selecting representative points using ArcGIS. We extracted digitized information by using point extraction method and extracted attribute information based on legend type and relative size in map. Based on the map of the past 100 years ago, the present situation of the big old tree in Jeju was analyzed and their characteristics were analyzed. In addition, based on the information of the protected big old trees in present, we discussed the characteristics of past tree (1918), present tree (2019), and contribution of big old tree in Jeju landscape and vegetation. As a result, 1,013 individuals were distributed in Jeju Island 100 years ago. Even when it was intensive in the use of timber, the big old trees were protected, and contributed as a representative component of Jeju's unique landscape. The remaining distribution of Jeju's big old tree is 159 trees. As in the past, distribution has been confirmed around the lowlands, but declines in numbers are found throughout the island. The major factors for the decline of individuals are large-scale development projects such as reaching the limit of life, natural disturbance (typhoon, disease, pest, drought, etc.). However, it is presumed that a large number of individuals have played a leading role in shaping the current forests as contributing to important species sources in the restoration process of Jeju vegetation. However, it is presumed that a large number of individuals (405) have played a leading role in forming the present forest by contributing to the species pool in the restoration process of Jeju vegetation.

Analysis of Research Trends of 'Word of Mouth (WoM)' through Main Path and Word Co-occurrence Network (주경로 분석과 연관어 네트워크 분석을 통한 '구전(WoM)' 관련 연구동향 분석)

  • Shin, Hyunbo;Kim, Hea-Jin
    • Journal of Intelligence and Information Systems
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    • v.25 no.3
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    • pp.179-200
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    • 2019
  • Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

A Study on the Trend and Utilization of Stone Waste (석재폐기물 현황 및 활용 연구)

  • Chea, Kwang-Seok;Lee, Young Geun;Koo, Namin;Yang, Hee Moon
    • Korean Journal of Mineralogy and Petrology
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    • v.35 no.3
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    • pp.333-344
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    • 2022
  • The quarrying and utilization of natural building stones such as granite and marble are rapidly emerging in developing countries. A huge amount of wastes is being generated during the processing, cutting and sizing of these stones to make them useable. These wastes are disposed of in the open environment and the toxic nature of these wastes negatively affects the environment and human health. The growth trend in the world stone industry was confirmed in output for 2019, increasing more than one percent and reaching a new peak of some 155 million tons, excluding quarry discards. Per-capita stone use rose to 268 square meters per thousand persons (m2/1,000 inh), from 266 the previous year and 177 in 2001. However, we have to take into consideration that the world's gross quarrying production was about 316 million tons (100%) in 2019; about 53% of that amount, however, is regarded as quarrying waste. With regards to the stone processing stage, we have noticed that the world production has reached 91.15 million tons (29%), and consequently this means that 63.35 million tons of stone-processing scraps is produced. Therefore, we can say that, on a global level, if the quantity of material extracted in the quarry is 100%, the total percentage of waste is about 71%. This raises a substantial problem from the environmental, economical and social point of view. There are essentially three ways of dealing with inorganic waste, namely, reuse, recycling, or disposal in landfills. Reuse and recycling are the preferred waste management methods that consider environmental sustainability and the opportunity to generate important economic returns. Although there are many possible applications for stone waste, they can be summarized into three main general applications, namely, fillers for binders, ceramic formulations, and environmental applications. The use of residual sludge for substrate production seems to be highly promising: the substrate can be used for quarry rehabilitation and in the rehabilitation of industrial sites. This new product (artificial soil) could be included in the list of the materials to use in addition to topsoil for civil works, railway embankments roundabouts and stone sludge wastes could be used for the neutralization of acidic soil to increase the yield. Stone waste is also possible to find several examples of studies for the recovery of mineral residues, including the extraction of metallic elements, and mineral components, the production of construction raw materials, power generation, building materials, and gas and water treatment.

A Study on UX-centered Smart Office Phone Design Development Process Using Service Design Process (서비스디자인 프로세스를 활용한 UX중심 오피스 전화기 디자인개발 프로세스 연구)

  • Seo, Hong-Seok
    • Science of Emotion and Sensibility
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    • v.25 no.1
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    • pp.41-54
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    • 2022
  • The purpose of this study was to propose a "user experience (UX)-centered product development process" so that the product design development process using the service design process can be systematized and used in practice. In a situation in which usability research on office phones is lacking compared to general home phones, this study expands to a product-based service design point of view rather than simple product development, intending to research ways to provide user experience value through office phone design in smart office. This study focused on extracting UX-centered user needs using the service design process and developing product design that realizes user experience value. In particular, the service design process was applied to systematically extract user needs and experience value elements in the product development process and to discover ideas that were converged with product-based services. For this purpose, the "Double Diamond Design Process Model," which is widely used in the service design field, was adopted. In addition, a product design development process was established so that usability improvement plans, user experience value elements, and product-service connected ideas could be extracted through a work-flow in which real users and people from various fields participate. Based on the double diamond design process, in the "Discover" information collection stage, design trends were identified mainly in the office phone markets. In the "Define" analysis and extraction stage, user needs were analyzed through user observation, interview, and usability survey, and design requirements and user experience issues were extracted. Persona was set through user type analysis, and user scenarios were presented. In the "Develop" development stage, ideation workshops and concept renderings were conducted to embody the design, and people from various fields within the company participated to set the design direction reflecting design preference and usability improvement plans. In the "Deliver" improvement/prototype development/evaluation stage, a working mock-up of a design prototype was produced and design and usability evaluation were conducted through consultation with external design experts. It is meaningful that it established a "UX-centered product development process" model that converged with the existing product design development process and service design process. Ultimately, service design-based product design development process was presented so that I Corp.'s products could realize user experience value through service convergence.

Sesquiterpenoids Bioconversion Analysis by Wood Rot Fungi

  • Lee, Su-Yeon;Ryu, Sun-Hwa;Choi, In-Gyu;Kim, Myungkil
    • 한국균학회소식:학술대회논문집
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    • 2016.05a
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    • pp.19-20
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    • 2016
  • Sesquiterpenoids are defined as $C_{15}$ compounds derived from farnesyl pyrophosphate (FPP), and their complex structures are found in the tissue of many diverse plants (Degenhardt et al. 2009). FPP's long chain length and additional double bond enables its conversion to a huge range of mono-, di-, and tri-cyclic structures. A number of cyclic sesquiterpenes with alcohol, aldehyde, and ketone derivatives have key biological and medicinal properties (Fraga 1999). Fungi, such as the wood-rotting Polyporus brumalis, are excellent sources of pharmaceutically interesting natural products such as sesquiterpenoids. In this study, we investigated the biosynthesis of P. brumalis sesquiterpenoids on modified medium. Fungal suspensions of 11 white rot species were inoculated in modified medium containing $C_6H_{12}O_6$, $C_4H_{12}N_2O_6$, $KH_2PO_4$, $MgSO_4$, and $CaCl_2$ for 20 days. Cultivation was stopped by solvent extraction via separation of the mycelium. The metabolites were identified as follows: propionic acid (1), mevalonic acid lactone (2), ${\beta}$-eudesmane (3), and ${\beta}$-eudesmol (4), respectively (Figure 1). The main peaks of ${\beta}$-eudesmane and ${\beta}$-eudesmol, which were indicative of sesquiterpene structures, were consistently detected for 5, 7, 12, and 15 days These results demonstrated the existence of terpene metabolism in the mycelium of P. brumalis. Polyporus spp. are known to generate flavor components such as methyl 2,4-dihydroxy-3,6-dimethyl benzoate; 2-hydroxy-4-methoxy-6-methyl benzoic acid; 3-hydroxy-5-methyl phenol; and 3-methoxy-2,5-dimethyl phenol in submerged cultures (Hoffmann and Esser 1978). Drimanes of sesquiterpenes were reported as metabolites from P. arcularius and shown to exhibit antimicrobial activity against Gram-positive bacteria such as Staphylococcus aureus (Fleck et al. 1996). The main metabolites of P. brumalis, ${\beta}$-Eudesmol and ${\beta}$-eudesmane, were categorized as eudesmane-type sesquiterpene structures. The eudesmane skeleton could be biosynthesized from FPP-derived IPP, and approximately 1,000 structures have been identified in plants as essential oils. The biosynthesis of eudesmol from P. brumalis may thus be an important tool for the production of useful natural compounds as presumed from its identified potent bioactivity in plants. Essential oils comprising eudesmane-type sesquiterpenoids have been previously and extensively researched (Wu et al. 2006). ${\beta}$-Eudesmol is a well-known and important eudesmane alcohol with an anticholinergic effect in the vascular endothelium (Tsuneki et al. 2005). Additionally, recent studies demonstrated that ${\beta}$-eudesmol acts as a channel blocker for nicotinic acetylcholine receptors at the neuromuscular junction, and it can inhibit angiogenesis in vitro and in vivo by blocking the mitogen-activated protein kinase (MAPK) signaling pathway (Seo et al. 2011). Variation of nutrients was conducted to determine an optimum condition for the biosynthesis of sesquiterpenes by P. brumalis. Genes encoding terpene synthases, which are crucial to the terpene synthesis pathway, generally respond to environmental factors such as pH, temperature, and available nutrients (Hoffmeister and Keller 2007, Yu and Keller 2005). Calvo et al. described the effect of major nutrients, carbon and nitrogen, on the synthesis of secondary metabolites (Calvo et al. 2002). P. brumalis did not prefer to synthesize sesquiterpenes under all growth conditions. Results of differences in metabolites observed in P. brumalis grown in PDB and modified medium highlighted the potential effect inorganic sources such as $C_4H_{12}N_2O_6$, $KH_2PO_4$, $MgSO_4$, and $CaCl_2$ on sesquiterpene synthesis. ${\beta}$-eudesmol was apparent during cultivation except for when P. brumalis was grown on $MgSO_4$-free medium. These results demonstrated that $MgSO_4$ can specifically control the biosynthesis of ${\beta}$-eudesmol. Magnesium has been reported as a cofactor that binds to sesquiterpene synthase (Agger et al. 2008). Specifically, the $Mg^{2+}$ ions bind to two conserved metal-binding motifs. These metal ions complex to the substrate pyrophosphate, thereby promoting the ionization of the leaving groups of FPP and resulting in the generation of a highly reactive allylic cation. Effect of magnesium source on the sesquiterpene biosynthesis was also identified via analysis of the concentration of total carbohydrates. Our current study offered further insight that fungal sesquiterpene biosynthesis can be controlled by nutrients. To profile the metabolites of P. brumalis, the cultures were extracted based on the growth curve. Despite metabolites produced during mycelia growth, there was difficulty in detecting significant changes in metabolite production, especially those at low concentrations. These compounds may be of interest in understanding their synthetic mechanisms in P. brumalis. The synthesis of terpene compounds began during the growth phase at day 9. Sesquiterpene synthesis occurred after growth was complete. At day 9, drimenol, farnesol, and mevalonic lactone (or mevalonic acid lactone) were identified. Mevalonic acid lactone is the precursor of the mevalonic pathway, and particularly, it is a precursor for a number of biologically important lipids, including cholesterol hormones (Buckley et al. 2002). Farnesol is the precursor of sesquiterpenoids. Drimenol compounds, bi-cyclic-sesquiterpene alcohols, can be synthesized from trans-trans farnesol via cyclization and rearrangement (Polovinka et al. 1994). They have also been identified in the basidiomycota Lentinus lepideus as secondary metabolites. After 12 days in the growth phase, ${\beta}$-elemene caryophyllene, ${\delta}$-cadiene, and eudesmane were detected with ${\beta}$-eudesmol. The data showed the synthesis of sesquiterpene hydrocarbons with bi-cyclic structures. These compounds can be synthesized from FPP by cyclization. Cyclic terpenoids are synthesized through the formation of a carbon skeleton from linear precursors by terpene cyclase, which is followed by chemical modification by oxidation, reduction, methylation, etc. Sesquiterpene cyclase is a key branch-point enzyme that catalyzes the complex intermolecular cyclization of the linear prenyl diphosphate into cyclic hydrocarbons (Toyomasu et al. 2007). After 20 days in stationary phase, the oxygenated structures eudesmol, elemol, and caryophyllene oxide were detected. Thus, after growth, sesquiterpenes were identified. Per these results, we showed that terpene metabolism in wood-rotting fungi occurs in the stationary phase. We also showed that such metabolism can be controlled by magnesium supplementation in the growth medium. In conclusion, we identified P. brumalis as a wood-rotting fungus that can produce sesquiterpenes. To mechanistically understand eudesmane-type sesquiterpene biosynthesis in P. brumalis, further research into the genes regulating the dynamics of such biosynthesis is warranted.

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A study on the classification of research topics based on COVID-19 academic research using Topic modeling (토픽모델링을 활용한 COVID-19 학술 연구 기반 연구 주제 분류에 관한 연구)

  • Yoo, So-yeon;Lim, Gyoo-gun
    • Journal of Intelligence and Information Systems
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    • v.28 no.1
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    • pp.155-174
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    • 2022
  • From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (

    ) were the topic modeling results for each research topic (
    ) was found to be derived from For example, as a result of topic modeling for papers related to 'vaccine', a new topic titled Topic 05 'neutralizing antibodies' was extracted. A neutralizing antibody is an antibody that protects cells from infection when a virus enters the body, and is said to play an important role in the production of therapeutic agents and vaccine development. In addition, as a result of extracting topics from papers related to 'treatment', a new topic called Topic 05 'cytokine' was discovered. A cytokine storm is when the immune cells of our body do not defend against attacks, but attack normal cells. Hidden topics that could not be found for the entire thesis were classified according to keywords, and topic modeling was performed to find detailed topics. In this study, we proposed a method of extracting topics from a large amount of literature using the LDA algorithm and extracting similar words using the Skip-gram method that predicts the similar words as the central word among the Word2vec models. The combination of the LDA model and the Word2vec model tried to show better performance by identifying the relationship between the document and the LDA subject and the relationship between the Word2vec document. In addition, as a clustering method through PCA dimension reduction, a method for intuitively classifying documents by using the t-SNE technique to classify documents with similar themes and forming groups into a structured organization of documents was presented. In a situation where the efforts of many researchers to overcome COVID-19 cannot keep up with the rapid publication of academic papers related to COVID-19, it will reduce the precious time and effort of healthcare professionals and policy makers, and rapidly gain new insights. We hope to help you get It is also expected to be used as basic data for researchers to explore new research directions.

  • A Proposal of a Keyword Extraction System for Detecting Social Issues (사회문제 해결형 기술수요 발굴을 위한 키워드 추출 시스템 제안)

    • Jeong, Dami;Kim, Jaeseok;Kim, Gi-Nam;Heo, Jong-Uk;On, Byung-Won;Kang, Mijung
      • Journal of Intelligence and Information Systems
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      • v.19 no.3
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      • pp.1-23
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      • 2013
    • To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.