• Journal of Intelligence and Information Systems
• /
• v.23 no.1
• /
• pp.1-22
• /
• 2017

Analysis of future business or investment opportunities, such as business feasibility analysis and company or technology valuation, necessitate objective estimation on the relevant market and expected sales. While there are various ways to classify the estimation methods of these new sales or market size, they can be broadly divided into top-down and bottom-up approaches by benchmark references. Both methods, however, require a lot of resources and time. Therefore, we propose a data-based intelligent demand forecasting system to support evaluation of new business. This study focuses on analogical forecasting, one of the traditional quantitative forecasting methods, to develop sales forecasting intelligence systems for new businesses. Instead of simply estimating sales for a few years, we hereby propose a method of estimating the sales of new businesses by using the initial sales and the sales growth rate of similar companies. To demonstrate the appropriateness of this method, it is examined whether the sales performance of recently established companies in the same industry category in Korea can be utilized as a reference variable for the analogical forecasting. In this study, we examined whether the phenomenon of "mean reversion" was observed in the sales of start-up companies in order to identify errors in estimating sales of new businesses based on industry sales growth rate and whether the differences in business environment resulting from the different timing of business launch affects growth rate. We also conducted analyses of variance (ANOVA) and latent growth model (LGM) to identify differences in sales growth rates by industry category. Based on the results, we proposed industry-specific range and linear forecasting models. This study analyzed the sales of only 150,000 start-up companies in Korea in the last 10 years, and identified that the average growth rate of start-ups in Korea is higher than the industry average in the first few years, but it shortly shows the phenomenon of mean-reversion. In addition, although the start-up founding juncture affects the sales growth rate, it is not high significantly and the sales growth rate can be different according to the industry classification. Utilizing both this phenomenon and the performance of start-up companies in relevant industries, we have proposed two models of new business sales based on the sales growth rate. The method proposed in this study makes it possible to objectively and quickly estimate the sales of new business by industry, and it is expected to provide reference information to judge whether sales estimated by other methods (top-down/bottom-up approach) pass the bounds from ordinary cases in relevant industry. In particular, the results of this study can be practically used as useful reference information for business feasibility analysis or technical valuation for entering new business. When using the existing top-down method, it can be used to set the range of market size or market share. As well, when using the bottom-up method, the estimation period may be set in accordance of the mean reverting period information for the growth rate. The two models proposed in this study will enable rapid and objective sales estimation of new businesses, and are expected to improve the efficiency of business feasibility analysis and technology valuation process by developing intelligent information system. In academic perspectives, it is a very important discovery that the phenomenon of 'mean reversion' is found among start-up companies out of general small-and-medium enterprises (SMEs) as well as stable companies such as listed companies. In particular, there exists the significance of this study in that over the large-scale data the mean reverting phenomenon of the start-up firms' sales growth rate is different from that of the listed companies, and that there is a difference in each industry. If a linear model, which is useful for estimating the sales of a specific company, is highly likely to be utilized in practical aspects, it can be explained that the range model, which can be used for the estimation method of the sales of the unspecified firms, is highly likely to be used in political aspects. It implies that when analyzing the business activities and performance of a specific industry group or enterprise group there is political usability in that the range model enables to provide references and compare them by data based start-up sales forecasting system.

• Journal of Intelligence and Information Systems
• /
• v.21 no.4
• /
• pp.17-35
• /
• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.

• International Commerce and Information Review
• /
• v.10 no.4
• /
• pp.457-491
• /
• 2008

As stage equipment export markets along with special lighting service lack the attraction for already globally established businesses, such markets can be viewed as an advantageous opportunity for SMEs as in general. In reality, global businesses tend to focus on large construction projects and this indicates relatively less substantial markets such as stage equipment and special lighting service export are more suitable for SME businesses. However, possible problems may be recognized as following; doubtful capabilities by such businesses to join in the vast and competitive global market and pursue manufacturing and service based export. This point is also supported by the fact that such in general SME businesses have substantially less experience in exporting products and services abroad. Realizing the distinctive features of the Korean economy, it is unarguable that every sector and area of global market must be regarded and monitored closely. Hence, it can be argued that there is an imminent need for establishment of supportive institution to assist export process of combination of stage equipments and special lighting service. This study emphasizes the need to improve export process of stage equipments, special lighting services as well as other related products and services which have been focused in domestic market only until now. Further, it also analyzed the potential prospect of such direction reconciling current crisis our manufacturing industry is facing. Even though it maybe regarded as one of the niche market for export of Korea in the short term view, stage equipment and special lighting service industry may rapidly grow as the global cultural industries have grown along with the increase of national income earnings overall. Due to such advantageous features, it can be expected that such industries will show strong growth in the near future. After analyzing the fact that Korea's plants (eg. powerplants) export sector is at its boom, there is a need to transform stage equipment and special lighting service export market into a primary market from a secondary(niche) market for SMEs. This study is viewed from the Korean economic and export sector aspect in the aim of seeking a solution to conquest our realistic limit in our export sector by developing a suitable export model. There have been cases of very few attempts to expand abroad by SMEs who have failed miserably due to their failure to adapt to foreign culture, practice and languages as well as substantial lack in experience in export marketing. Despite this, neglecting our manufacturing industry as it is which is showing its limit and problems is out of option therefore, it is imminent that we come up with an effective measure to address this problem and service export can be suggested as one of them. This study reveals manufacturing-service export model of stage equipment and special lighting service and its related areas is recognized as a field with a very strong future and furthermore, it is expected to bring synergy effects in manufacturing and services sector as well. Further, the operation strategy contains combination, composition and fusion(convergence) of manufacturing and service sectors which could derive various of export products which displays greater success probability or this export model. The outcome of this research is expected to become a useful source for enterprises related to such industry which are seeking a possible global expansion. Furthermore, it is also expected to become a catalyst which fastens the process of global expansion and not only that, we are firmly assured that this study will become an opportunity to improve our current policies and institutions related to this area's export market.

• Journal of Intelligence and Information Systems
• /
• v.26 no.3
• /
• pp.149-169
• /
• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.14 no.4
• /
• pp.1-10
• /
• 2011

This study was conducted to compare the growth of Zoysia japonica depending on different soil treatments in Saemangeum sea dike, which is filled with dredged soil. Zoysia japonica was planted using sod-pitching method on the control plot. On plots which were treated with forest soil and soil improvement, Zoysia japonica seeds were sprayed mechanically. Sixteen months after planting, coverage rate, leaf length, leaf width, and root length were measured and analyzed. Also, three Zoysia japonica samples per plot were collected to analyze nutrient contents. Coverage rate was 100% in B treatment plot(dredged soil+$40kg/m^3$ soil improvement+forest soil), in C treatment plots (dredged soil+$60kg/m^3$ soil improvement+forest soil), and D treatment plots (dredged soil+$60kg/m^3$ soil improvement), while only 43% of the soil surface was covered with Zoysia japonica on control plots. The width of the leaf on C treatment plots (3.79mm) was the highest followed by D treatment (3.49mm), B treatment (2.40mm) and control plots (1.97mm). Leaf and root length of D treatment was 30.18cm and 13.18cm, which were highest among different treatments. The leaf length of D treatment was highest followed by C, B, and A treatments. The root length of D treatment was highest followed by C, A, and B treatments. The nitrogen and phosphate contents of the above ground part of Zoysia japonica were highest in C treatment, followed by D, B, and A treatments. The nitrogen and phosphate contents of the underground part of Zoysia japonica were highest in D treatment, followed by C, A, and B treatments. C and D treatments showed the best results in every aspect of grass growth. The results of this study could be used to identify the cost effective way to improve soil quality for soil surface fixation on reclaimed areas using grass species.

• The Korean Journal of Petroleum Geology
• /
• v.14 no.1
• /
• pp.1-11
• /
• 2008

As conventional oil and gas reservoirs become depleted, interests for oil sands has rapidly increased in the last decade. Oil sands are mixture of bitumen, water, and host sediments of sand and clay. Most oil sand is unconsolidated sand that is held together by bitumen. Bitumen has hydrocarbon in situ viscosity of >10,000 centipoises (cP) at reservoir condition and has API gravity between $8-14^{\circ}$. The largest oil sand deposits are in Alberta and Saskatchewan, Canada. The reverves are approximated at 1.7 trillion barrels of initial oil-in-place and 173 billion barrels of remaining established reserves. Alberta has a number of oil sands deposits which are grouped into three oil sand development areas - the Athabasca, Cold Lake, and Peace River, with the largest current bitumen production from Athabasca. Principal oil sands deposits consist of the McMurray Fm and Wabiskaw Mbr in Athabasca area, the Gething and Bluesky formations in Peace River area, and relatively thin multi-reservoir deposits of McMurray, Clearwater, and Grand Rapid formations in Cold Lake area. The reservoir sediments were deposited in the foreland basin (Western Canada Sedimentary Basin) formed by collision between the Pacific and North America plates and the subsequent thrusting movements in the Mesozoic. The deposits are underlain by basement rocks of Paleozoic carbonates with highly variable topography. The oil sands deposits were formed during the Early Cretaceous transgression which occurred along the Cretaceous Interior Seaway in North America. The oil-sands-hosting McMurray and Wabiskaw deposits in the Athabasca area consist of the lower fluvial and the upper estuarine-offshore sediments, reflecting the broad and overall transgression. The deposits are characterized by facies heterogeneity of channelized reservoir sands and non-reservoir muds. Main reservoir bodies of the McMurray Formation are fluvial and estuarine channel-point bar complexes which are interbedded with fine-grained deposits formed in floodplain, tidal flat, and estuarine bay. The Wabiskaw deposits (basal member of the Clearwater Formation) commonly comprise sheet-shaped offshore muds and sands, but occasionally show deep-incision into the McMurray deposits, forming channelized reservoir sand bodies of oil sands. In Canada, bitumen of oil sands deposits is produced by surface mining or in-situ thermal recovery processes. Bitumen sands recovered by surface mining are changed into synthetic crude oil through extraction and upgrading processes. On the other hand, bitumen produced by in-situ thermal recovery is transported to refinery only through bitumen blending process. The in-situ thermal recovery technology is represented by Steam-Assisted Gravity Drainage and Cyclic Steam Stimulation. These technologies are based on steam injection into bitumen sand reservoirs for increase in reservoir in-situ temperature and in bitumen mobility. In oil sands reservoirs, efficiency for steam propagation is controlled mainly by reservoir geology. Accordingly, understanding of geological factors and characteristics of oil sands reservoir deposits is prerequisite for well-designed development planning and effective bitumen production. As significant geological factors and characteristics in oil sands reservoir deposits, this study suggests (1) pay of bitumen sands and connectivity, (2) bitumen content and saturation, (3) geologic structure, (4) distribution of mud baffles and plugs, (5) thickness and lateral continuity of mud interbeds, (6) distribution of water-saturated sands, (7) distribution of gas-saturated sands, (8) direction of lateral accretion of point bar, (9) distribution of diagenetic layers and nodules, and (10) texture and fabric change within reservoir sand body.

• Journal of Intelligence and Information Systems
• /
• v.28 no.1
• /
• pp.107-129
• /
• 2022

It is important to preempt new technology because the technology competition is getting much tougher. Stakeholders conduct exploration activities continuously for new technology preoccupancy at the right time. Gartner's Hype Cycle has significant implications for stakeholders. The Hype Cycle is a expectation graph for new technologies which is combining the technology life cycle (S-curve) with the Hype Level. Stakeholders such as R&D investor, CTO(Chef of Technology Officer) and technical personnel are very interested in Gartner's Hype Cycle for new technologies. Because high expectation for new technologies can bring opportunities to maintain investment by securing the legitimacy of R&D investment. However, contrary to the high interest of the industry, the preceding researches faced with limitations aspect of empirical method and source data(news, academic papers, search traffic, patent etc.). In this study, we focused on two research questions. The first research question was 'Is there a difference in the characteristics of the network structure at each stage of the hype cycle?'. To confirm the first research question, the structural characteristics of each stage were confirmed through the component cohesion size. The second research question is 'Is there a pattern of diffusion at each stage of the hype cycle?'. This research question was to be solved through centralization index and network density. The centralization index is a concept of variance, and a higher centralization index means that a small number of nodes are centered in the network. Concentration of a small number of nodes means a star network structure. In the network structure, the star network structure is a centralized structure and shows better diffusion performance than a decentralized network (circle structure). Because the nodes which are the center of information transfer can judge useful information and deliver it to other nodes the fastest. So we confirmed the out-degree centralization index and in-degree centralization index for each stage. For this purpose, we confirmed the structural features of the community and the expectation diffusion patterns using Social Network Serice(SNS) data in 'Gartner Hype Cycle for Artificial Intelligence, 2021'. Twitter data for 30 technologies (excluding four technologies) listed in 'Gartner Hype Cycle for Artificial Intelligence, 2021' were analyzed. Analysis was performed using R program (4.1.1 ver) and Cyram Netminer. From October 31, 2021 to November 9, 2021, 6,766 tweets were searched through the Twitter API, and converting the relationship user's tweet(Source) and user's retweets (Target). As a result, 4,124 edgelists were analyzed. As a reult of the study, we confirmed the structural features and diffusion patterns through analyze the component cohesion size and degree centralization and density. Through this study, we confirmed that the groups of each stage increased number of components as time passed and the density decreased. Also 'Innovation Trigger' which is a group interested in new technologies as a early adopter in the innovation diffusion theory had high out-degree centralization index and the others had higher in-degree centralization index than out-degree. It can be inferred that 'Innovation Trigger' group has the biggest influence, and the diffusion will gradually slow down from the subsequent groups. In this study, network analysis was conducted using social network service data unlike methods of the precedent researches. This is significant in that it provided an idea to expand the method of analysis when analyzing Gartner's hype cycle in the future. In addition, the fact that the innovation diffusion theory was applied to the Gartner's hype cycle's stage in artificial intelligence can be evaluated positively because the Gartner hype cycle has been repeatedly discussed as a theoretical weakness. Also it is expected that this study will provide a new perspective on decision-making on technology investment to stakeholdes.

• Journal of Applied Biological Chemistry
• /
• v.57 no.3
• /
• pp.267-277
• /
• 2014

Objective of this paper is to assess the available data on the pesticide uses and regulations in the golf courses, and provide the nationwide systematic management options. Numbers of golf courses in Korea are rapidly increasing from 2000s and reached at 421 sites by the end of 2011. Accordingly pesticide usage has been increased with years in direct proportion to the increasing number of golf courses. Amounts of pesticide applied in 2011 were 118,669 kg as of an active ingredient and were in the orders of fungicides (54.9%) > insecticides (24.4%) > herbicides (13.3%) > growth regulators (0.1%). Average pesticide usages in 2011 were 280.9 kg per golf course and $5.4kg\;ha^{-1}$. Frequencies of the residual pesticide detections in green and turf were higher than those in fairway and soil, respectively. Residue of highly toxic pesticides was not detected in golf courses. Ministry of Environment in 2010 has developed the 'golf course pesticide monitoring and management system' which is the advanced online registry for kind and amount of pesticides applied in each golf course. This system is intended for monitoring of the pesticide uses and residual levels and protecting the environmental pollution from pesticides in the golf course. In 2009, management of pesticides in the golf courses became the task of Ministry of Environment, being merged from many federal agency and ministries. The protocol for the site-specific best management practices, on which to base results from the risk assessment, should be set for pesticides in the golf to minimize the environmental impacts.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.59 no.1
• /
• pp.1-15
• /
• 2014

The cultivation situation of Korean wheat of 175 farmers in nationwide for two years, 2010/2011 and 2011/2012, was analyzed to obtain basic data for extension cultivated area and enhancing the self-sufficiency ratio of Korean wheat. Compared to the mean temperature and precipitation in the normal year, the mean temperature was lower before the heading stage and higher amount of precipitation after the heading stage in 2010/2011 and higher the mean temperature and lower amount of precipitation after the heading stage in 2011/2012. Average cultivation career and area were 7.7years and 2.4~3.3ha, Keumkang cv. was mainly cultivated for two years and Jokyung and Baekjoong cvs. were increased cultivation areas in southern part of Korea, Gyeongsangnam-do, Jeolllanambuk-do and Kwangju metropolitan city, including in 2011/2012. Most farmers (144) sown wheat seeds from late October to the beginning November with broadcasting method and the other famers were sown using the drill method. Average amount for basal fertilizer was 29.7 kg/10a with complex fertilizer mixed for wheat and barley cultivation, which was higher amount compared to recommended rate of fertilizer amount by rural development administration. Top dressing using nitrogen fertilizer was applied from in the late February to the beginning March. Heading date was the beginning May in 2011 and the late April in 2012, which the mean temperature from regeneration stage to tillering stage in 2011 was higher than that of 2012. Most farmers harvested wheat in mid-June and Pre-harvest sprouting and Fusarium head blight were occurred in 2011 due to the high amount precipitation during grain filling period.

• Korean Journal of Childcare and Education
• /
• v.2 no.1
• /
• pp.65-88
• /
• 2006

This study intended to activate public education, researched and analyzed real conditions of preschool education to know desirable directions of public education and help parents recognize public education. The final purpose is to offer basic materials to reestablish preschool education in the public education system. First, parents' recognition concerning preschool education in the public education system was much different from that of teachers. As for definitions of preschool education as a public education, parents understood that it means 'the nation and self-governing bodies manage aid both the public and private kindergartens', and teachers recognized that it means that 'the nation and self-governing bodies not only found operate public kindergartens but also aid manage educational funds of private kindergartens. Second, the examination of educational environments of kindergartens told that teachers and parents thought that opportunity to enter the kindergarten is not equal for all children in our country, and quality of kindergarten teachers is satisfactory. Also, they thought that curriculums of preschool educational organs have been set well according to children's developmental stages, education quality is different according to preschool education organs' foundation-types. They recognized that facilities and apparatus of preschools are satisfactory, security and neatness of preschools are satisfactory, too. Third, the examination of developmental directions of preschool education as a public education proved following facts; as for foundation-types of kindergartens in the future when promoting preschool education as a public education, parents answered financial support and supervision by the government, teachers answered aid and management of operational fees as well as support for teacher personnel expenses.