• Journal of Intelligence and Information Systems
• /
• v.21 no.2
• /
• pp.93-112
• /
• 2015

Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.13 no.2
• /
• pp.45-56
• /
• 1980

Farming density of oyster cultured in Hansan-Geoje Bay was studied to obtain the optimal farming density based on the biosedimentation analysis and the annual yield data from 1970 to 1979. Farming density of oyster extrapolated by means of pollution grade of sediment is significantly correlated to COD and phaeophytin content of the bottom mud of the bay. Pollution grade is linearly related to the number of oyster clusters suspended in the unit area. Optimal farming density was $0.12\;string/m^2$ in case of raft culture, and it was $0.12\;string/m^2$ in case of long-line culture. Farming density was well expressed by the number of strings per raft and the area covered by a raft. As strings per raft increased from 350 to 558, total yield from a raft increased and when occupied sea area per raft ranged from $1.000\;m^2\;to\;6,000\;m^2$, the yield per raft linearly increased as the area increased. This analysis suggests that the optimal density be 0.11 string per unit area $(m^2)$. As increasing the number of strings per $m^2$ the yield per string decreases, and this is well dipicted by a linear function. At this time the yield per unit area increases when the number of string increases up to the density of $0.13\;strings/m^2$. From the point of these three comprehensive analyses the optimal density was $0.11\~0.13\;string/m^2$ in case of raft culture and $0.25\;strings/m^2$ in case of long-line culture in Hansan-Geoje Bay. The maximum expected yield of oyster in Hansan-Geoje Bay is approximately 5,600 tons when maintained the string density at $0.11\~0.13\;string/m^2$.

• Korean Journal of Soil Science and Fertilizer
• /
• v.37 no.4
• /
• pp.235-244
• /
• 2004

In this study, we compared the levels of methylotrophic bacterial community diversity in the leaf samples of 19 rice cultivars collected from three regions of Korea. Nineteen pink pigmented isolates showing characteristic growth on methanol were obtained. Physiological and biochemical characters of each isolate were examined according to methods described in Bergey's Manual of Systematic Bacteriology. When phylotypes were defined by performing numerical analysis of 37 characteristics, four distinct clusters were formed. The two reference strains, Methylobacterium extorquens AM1 and Methylobacterium fujisawaense KACC10744 were found to group under cluster IV and cluster III respectively. Cluster I diverged on the basis of nitrate reduction and four isolates showed tolerance upto 0.5 M NaCl concentrations. Two strains in cluster I and III were found to possess methane utilizing properties. Most of the isolates in all the four clusters utilized monosaccharides, disaccharide and polyols as carbon source. When the isolates were subjected for indole-3-acetic acid (IAA) analysis in the presence of L-tryptophan, only 8 isolates exhibited IAA production. In addition, the nitrogen source in the medium was found to influence the IAA production. Addition of $(NH_4)_2SO_4$ in the medium led to a 2 to 30 fold increase in the indole synthesis. However, $KNO_3$, $NH_4NO_3$ and $NH_4Cl$ substitution did not significantly stimulate the synthesis of IAA in the growth medium. Result of gnotobiotic root elongation assay significantly increased roots and shoots lengths, and number of lateral roots, which is mediated by IAA production in the culture medium. The rice seedlings primary roots from seeds treated with methylotrophic isolates were on average 27 to 56% longer than the roots from seeds treated with the uninoculated seeds. In addition, application of different high concentrations of authentic IAA ($400g\;mL^{-1}$) to roots of rice seedlings inhibited root growth. However, the IAA concentration from 10 to $200g\;mL^{-1}$, IAA promoted root growth of rice seedlings. These results suggest that bacterial IAA plays a major role in the development of the host plant root system.

• 한국균학회소식:학술대회논문집
• /
• 2014.05a
• /
• pp.27-28
• /
• 2014

Beauveria bassiana (Cordycipitaceae, Hypocreales, Ascomycota) is an anamorphic fungus having a potential to be used as a biological control agent because it parasitizes a wide range of arthropod hosts including termites, aphids, beetles and many other insects. A number of bioactive secondary metabolites (SMs) have been isolated from B. bassiana and functionally verified. Among them, beauvericin and bassianolide are cyclic depsipeptides with antibiotic and insecticidal effects belonging to the enniatin family. Non-ribosomal peptide synthetases (NRPSs) play a crucial role in the synthesis of these secondary metabolites. NRPSs are modularly organized multienzyme complexes in which each module is responsible for the elongation of proteinogenic and non-protein amino acids, as well as carboxyl and hydroxyacids. A minimum of three domains are necessary for one NRPS elongation module: an adenylation (A) domain for substrate recognition and activation; a tholation (T) domain that tethers the growing peptide chain and the incoming aminoacyl unit; and a condensation (C) domain to catalyze peptide bond formation. Some of the optional domains include epimerization (E), heterocyclization (Cy) and oxidation (Ox) domains, which may modify the enzyme-bound precursors or intermediates. In the present study, we analyzed genomes of B. bassiana and its allied species in Hypocreales to verify the distribution of NRPS-encoding genes involving biosynthesis of beauvericin and bassianolide, and to unveil the evolutionary processes of the gene clusters. Initially, we retrieved completely or partially assembled genomic sequences of fungal species belonging to Hypocreales from public databases. SM biosynthesizing genes were predicted from the selected genomes using antiSMASH program. Adenylation (A) domains were extracted from the predicted NRPS, NRPS-like and NRPS-PKS hybrid genes, and used them to construct a phylogenetic tree. Based on the preliminary results of SM biosynthetic gene prediction in B. bassiana, we analyzed the conserved gene orders of beauvericin and bassianolide biosynthetic gene clusters among the hypocrealean fungi. Reciprocal best blast hit (RBH) approach was performed to identify the regions orthologous to the biosynthetic gene cluster in the selected fungal genomes. A clear recombination pattern was recognized in the inferred A-domain tree in which A-domains in the 1st and 2nd modules of beauvericin and bassianolide synthetases were grouped in CYCLO and EAS clades, respectively, suggesting that two modules of each synthetase have evolved independently. In addition, inferred topologies were congruent with the species phylogeny of Cordycipitaceae, indicating that the gene fusion event have occurred before the species divergence. Beauvericin and bassianolide synthetases turned out to possess identical domain organization as C-A-T-C-A-NM-T-T-C. We also predicted precursors of beauvericin and bassianolide synthetases based on the extracted signature residues in A-domain core motifs. The result showed that the A-domains in the 1st module of both synthetases select D-2-hydroxyisovalerate (D-Hiv), while A-domains in the 2nd modules specifically activate L-phenylalanine (Phe) in beauvericin synthetase and leucine (Leu) in bassianolide synthetase. antiSMASH ver. 2.0 predicted 15 genes in the beauvericin biosynthetic gene cluster of the B. bassiana genome dispersed across a total length of approximately 50kb. The beauvericin biosynthetic gene cluster contains beauvericin synthetase as well as kivr gene encoding NADPH-dependent ketoisovalerate reductase which is necessary to convert 2-ketoisovalarate to D-Hiv and a gene encoding a putative Gal4-like transcriptional regulator. Our syntenic comparison showed that species in Cordycipitaceae have almost conserved beauvericin biosynthetic gene cluster although the gene order and direction were sometimes variable. It is intriguing that there is no region orthologous to beauvericin synthetase gene in Cordyceps militaris genome. It is likely that beauvericin synthetase was present in common ancestor of Cordycipitaceae but selective gene loss has occurred in several species including C. militaris. Putative bassianolide biosynthetic gene cluster consisted of 16 genes including bassianolide synthetase, cytochrome P450 monooxygenase, and putative Gal4-like transcriptional regulator genes. Our synteny analysis found that only B. bassiana possessed a bassianolide synthetase gene among the studied fungi. This result is consistent with the groupings in A-domain tree in which bassianolide synthetase gene found in B. bassiana was not grouped with NRPS genes predicted in other species. We hypothesized that bassianolide biosynthesizing cluster genes in B. bassiana are possibly acquired by horizontal gene transfer (HGT) from distantly related fungi. The present study showed that B. bassiana is the only species capable of producing both beauvericin and bassianolide. This property led to B. bassiana infect multiple hosts and to be a potential biological control agent against agricultural pests.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.20 no.4
• /
• pp.1-14
• /
• 2017

In Korea, the soil series derived from sedimentary rocks are classified into seven soil series of coarse loamy soil such as Dain, Danbug, Dongam, Imdong, Jeomgog, Maryeong, and Yonggog; seventeen soil series of fine loamy soil such as Angye, Anmi, Banho, Bigog, Deoggog, Dogye, Dojeon, Gamgog, Gugog, Jincheon, Maji, Mungyeong, Oggye, Samam, Yanggog, Yeongwol, and Yulgog; six soil series of fine silty soil such as Goryeong, Bonggog, Juggog, Gyeongsan, Yuga, and Yugog; and four soil series of clayey soil such as Mitan, Pyeongan, Pyeongjeon, and Uji. All thirty-four soil series have different drainage rates and topography. However, the soil texture depends on the parent rock. The buffer functions in GIS (Geographic Information System) techniques were used to calculate adjacent soil series from a soil series. The length of the adjacent soil series was adjusted because a side of the buffer area was one meter long. The cluster analysis was conducted using the CCC (Cubic Clustering Criterion) method, in which the number of clusters is calculated based on the individual soil series ratio. Soil survey has been carried out since 1964 as "The reconnaissance soil survey", and 1:5,000 detailed soil survey was completed in 1999 with a five-years plan in Korea. Today, all the soil survey information has been computerized. GIS techniques were used to establish a digital soil map; however, there have not been any studies to interpret pedogenesis using the GIS technique. In this study, the area of the adjacent soil series were obtained using the GIS technique. The area of the adjacent soil series can be calculated based on the information area. The similarities of soil originated from sedimentary rocks were estimated using the length. As a result, the distribution of grain size was different based on the types of sedimentary rocks and the location. The clusters were distinguished into limestone, sandstone, and shale. In addition, the soil derived from shale was divided into red shale and gray shale. This means that quantitative interpretation of the catena and this established method can be used to interpret the relationship between soil series.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.151-176
• /
• 2021

As the information technology industry develops, various kinds of data are being created, and it is now essential to process them and use them in the industry. Analyzing and utilizing various digital data collected online and offline is a necessary process to provide an appropriate experience for customers in the industry. In order to create new businesses, products, and services, it is essential to use customer data collected in various ways to deeply understand potential customers' needs and analyze behavior patterns to capture hidden signals of desire. However, it is true that research using data analysis and UX methodology, which should be conducted in parallel for effective service development, is being conducted separately and that there is a lack of examples of use in the industry. In thiswork, we construct a single process by applying data analysis methods and UX methodologies. This study is important in that it is highly likely to be used because it applies methodologies that are actively used in practice. We conducted a survey on the topic to identify and cluster the associations between factors to establish customer classification and target customers. The research methods are as follows. First, we first conduct a factor, regression analysis to determine the association between factors in the happiness data survey. Groups are grouped according to the survey results and identify the relationship between 34 questions of psychological stability, family life, relational satisfaction, health, economic satisfaction, work satisfaction, daily life satisfaction, and residential environment satisfaction. Second, we classify clusters based on factors affecting happiness and extract the optimal number of clusters. Based on the results, we cross-analyzed the characteristics of each cluster. Third, forservice definition, analysis was conducted by correlating with keywords related to happiness. We leverage keyword analysis of the thumb trend to derive ideas based on the interest and associations of the keyword. We also collected approximately 11,000 news articles based on the top three keywords that are highly related to happiness, then derived issues between keywords through text mining analysis in SAS, and utilized them in defining services after ideas were conceived. Fourth, based on the characteristics identified through data analysis, we selected segmentation and targetingappropriate for service discovery. To this end, the characteristics of the factors were grouped and selected into four groups, and the profile was drawn up and the main target customers were selected. Fifth, based on the characteristics of the main target customers, interviewers were selected and the In-depthinterviews were conducted to discover the causes of happiness, causes of unhappiness, and needs for services. Sixth, we derive customer behavior patterns based on segment results and detailed interviews, and specify the objectives associated with the characteristics. Seventh, a typical persona using qualitative surveys and a persona using data were produced to analyze each characteristic and pros and cons by comparing the two personas. Existing market segmentation classifies customers based on purchasing factors, and UX methodology measures users' behavior variables to establish criteria and redefine users' classification. Utilizing these segment classification methods, applying the process of producinguser classification and persona in UX methodology will be able to utilize them as more accurate customer classification schemes. The significance of this study is summarized in two ways: First, the idea of using data to create a variety of services was linked to the UX methodology used to plan IT services by applying it in the hot topic era. Second, we further enhance user classification by applying segment analysis methods that are not currently used well in UX methodologies. To provide a consistent experience in creating a single service, from large to small, it is necessary to define customers with common goals. To this end, it is necessary to derive persona and persuade various stakeholders. Under these circumstances, designing a consistent experience from beginning to end, through fast and concrete user descriptions, would be a very effective way to produce a successful service.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.8 no.2
• /
• pp.86-96
• /
• 2006

Ecoclimap-1, a new complete surface parameter global database at a 1-km resolution, was previously presented. It is intended to be used to initialize the soil-vegetation- atmosphere transfer schemes in meteorological and climate models. Surface parameters in the Ecoclimap-1 database are provided in the form of a per-class value by an ecoclimatic base map from a simple merging of land cover and climate maps. The principal objective of this ecoclimatic map is to consider intra-class variability of life cycle that the usual land cover map cannot describe. Although the ecoclimatic map considering land cover and climate is used, the intra-class variability was still too high inside some classes. In this study, a new strategy is defined; the idea is to use the information contained in S10 NDVI SPOT/VEGETATION profiles to split a land cover into more homogeneous sub-classes. This utilizes an intra-class unsupervised sub-clustering methodology instead of simple merging. This study was performed to provide a new ecolimatic map over Northeast Asia in the framework of Ecoclimap-2 global database construction for surface parameters. We used the University of Maryland's 1km Global Land Cover Database (UMD) and a climate map to determine the initial number of clusters for intra-class sub-clustering. An unsupervised classification process using six years of NDVI profiles allows the discrimination of different behavior for each land cover class. We checked the spatial coherence of the classes and, if necessary, carried out an aggregation step of the clusters having a similar NDVI time series profile. From the mapping system, 29 ecosystems resulted for the study area. In terms of climate-related studies, this new ecosystem map may be useful as a base map to construct an Ecoclimap-2 database and to improve the surface climatology quality in the climate model.

• Journal of radiological science and technology
• /
• v.27 no.3
• /
• pp.31-41
• /
• 2004

Attention deficit hyperactivity disorder(ADHD)is one of the most common psychiatric disorders in childhood, especially school age children and persisting into adult. ADHD is affected 7.6% in our children, Korea. and persisting into $15{\sim}20%$ in adult. And it is characterized by hyperactivity, inattention and impulsivity. Brain imaging is one of way to diagnosis for ADHD. Brain imaging studies may be provide information two types - structural and functional imaging. Structural and functional images of the brain play an important role in management of neurologic and psyciatric disorders. Brain SPECT, with perfusion imaging radiopharmaceuticals is one of the appropriate test to diagnosis of neurologic and psychiatric diseases. Ther are a few studies about separated analysis between boys and girls ADHD SPECT brain images. Selection of Probability level(P-value) is very important to determind the abnormalities when analysis a data by SPM. SPM is a statistical method used for image analysis and determine statistical different between two groups-normal and ADHD. Commonly used P-value is P<0.05 in statistical analysis. The purpose of this study is to evaluation of blood flow clusters distribution, between boys and girls ADHD. The number of normal boys are 8(6-7y, average : $9.6{\pm}3.9y$) and 51(4-11y, average : $9.0{\pm}2.4$) ADHD patients, and normal girls are 4(6-12y, average : $9{\pm}2.4y$) and 13(2-13y, average $10{\pm}3.5y$) ADHD patiens. Blood flow tracer $^{99m}Tc-ethylcysteinate$ dimer(ECD) injected as rCBF agent and take blood flow images after 30 min. during sleeping by SPECT camera. The anatomical region of hyperperfusion of rCBF in boys ADHD group is posterior cingulate gyrus and hyperperfusion rate is 15.39-15.77% according to p-value. And girls ADHD group appears at posterior cerebellum, Lt. cerbral limbic lobe and Lt. Rt. cerebral temporal lobe. These areas hyperperfusion rate are 24.68-31.25%. Hypoperfusion areas in boys ADHD,s brain are Lt. cerebral insular gyrus, Lt. Rt. frontal lobe and mid-prefrontal lobe, these areas decresed blood flow as 15.21-15.64%. Girls ADHD decreased blood flow regions are Lt. cerebral insular gyrus, Lt. cerebral frontal and temporal lobe, Lt. Rt. lentiform nucleus and Lt. parietal lobe. And hypoperfusion rate is 30.57-30.85% in girls ADHD. The girls ADHD group's perfusion rate is more variable than boys. The studies about rCBF in ADHD, should be separate with boys and girls.

• Journal of Practical Agriculture & Fisheries Research
• /
• v.23 no.1
• /
• pp.89-104
• /
• 2021

Based on the TF-IDF weighted value that evaluates the importance of words that play a key role, the semantic network analysis(SNA) was conducted on the self-introduction letter of freshman at Korea National College of Agriculture and Fisheries(KNCAF) in 2020. The top three words calculated by TF-IDF weights were agriculture, mathematics, study (Q. 1), clubs, plants, friends (Q. 2), friends, clubs, opinions, (Q. 3), mushrooms, insects, and fathers (Q. 4). In the relationship between words, the words with high betweenness centrality are reason, high school, attending (Q. 1), garbage, high school, school (Q. 2), importance, misunderstanding, completion (Q.3), processing, feed, and farmhouse (Q. 4). The words with high degree centrality are high school, inquiry, grades (Q. 1), garbage, cleanup, class time (Q. 2), opinion, meetings, volunteer activities (Q.3), processing, space, and practice (Q. 4). The combination of words with high frequency of simultaneous appearances, that is, high correlation, appeared as 'certification - acquisition', 'problem - solution', 'science - life', and 'misunderstanding - concession'. In cluster analysis, the number of clusters obtained by the height of cluster dendrogram was 2(Q.1), 4(Q.2, 4) and 5(Q. 3). At this time, the cohesion in Cluster was high and the heterogeneity between Clusters was clearly shown.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.16 no.3
• /
• pp.105-119
• /
• 2021

The innovation cluster is formed by cooperation and networking among a number of actors, including companies, universities, research institutes, government and other supporting organizations, but the main subject of innovation in the venture ecosystem, which can be said to be the core of the innovation cluster, is the enterprise. Therefore, enterprises in innovation cluster can be seen as a major user of the innovation cluster policy. In order for the policy to be executed smoothly, policy acceptance is important. However, existing research on policy prioritization tends to be centered on policy providers, so it is necessary to check them from the perspective of policy users. Accordingly, this study conducted discussions from a two-way perspective to establish the correct policy direction through a balanced perspective between a policy provider-centered top-down perspective and a policy user's bottom-up perspective. First, the factors for activating the innovation cluster (three factors in the first level and 14 factors in the second level) were derived through prior research and expert interviews. After that, the importance of the factors for activating the innovation cluster was analyzed using AHP (Analytic Hierarchy Process) for the policy provider group and the user group in the Daedeok Innopolis, a representative case of innovation cluster policy. As a result of analyzing the importance of the innovation cluster activation factors from the perspectives of policy providers and users, some similarities were also seen, but overall differences in mutual perception were found. It was found that the policy provider group focused on innovation creation factors, while the policy user group viewed innovation creation, clusters, and industrial location factors from a more balanced perspective. This study is meaningful in that it deals with both perspectives in a balanced way by expanding the targets from the existing policy provider-centered research to policy users. In addition, practical contributions exist in the aspect of providing basic data so that policies can be carried out based on corporate needs in fostering innovation clusters.