• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3384-3398
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• 2020

In recent years, as the environment has become an important issue in dealing with food, energy, and urban development, diverse environment-related applications such as environmental monitoring and ecosystem management have emerged. In such applications, automatic classification of animals using video or sound is very useful in terms of cost and convenience. So far, many works have been done for animal sounds classification using artificial intelligence techniques such as a convolutional neural network. However, most of them have dealt only with the sound of a specific class of animals such as bird sounds or insect sounds. Due to this, they are not suitable for classifying various types of animal sounds. In this paper, we propose a sound classification scheme based on a multi-feature network for classifying sounds of multiple species of animals. To do that, we first collected multiple animal sound datasets and grouped them into classes. Then, we extracted their audio features by generating mixed records and used those features for training. To evaluate the effectiveness of our scheme, we constructed an animal sound classification model and performed various experiments. We report some of the results.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.6
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• pp.405-412
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• 2014

A number of algal bloom models (red-tide models) have been developed and applied to simulate the redtide growth and decline patterns as the interest on the phytoplankton blooms has been continuously increased. The quantitative error analysis of the model is of great importance because the accurate prediction of the red-tide occurrence and transport pattern can be used to setup the effective mitigations and counter-measures on the coastal ecosystem, aquaculture and fisheries damages. The word "red-tide model" is widely used without any clear definitions and references. It makes the comparative evaluation of the ecological models difficult and confusable. It is highly required to do the performance test of the red-tide models based on the suitable classification and appropriate error analysis because model structures are different even though the same/similar words (e.g., red-tide, algal bloom, phytoplankton growth, ecological or ecosystem models) are used. Thus, the references on the model classification are suggested and the advantage and disadvantage of the models are also suggested. The processes and methods on the performance test (quantitative error analysis) are recommend to the practical use of the red-tide model in the coastal seas. It is suggested in each stage of the modeling procedures, such as verification, calibration, validation, and application steps. These suggested references and methods can be attributed to the effective/efficient marine policy decision and the coastal ecosystem management plan setup considering the red-tide and/or ecological models uncertainty.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.1
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• pp.59-71
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• 2019

In the rapidly changing industrial environment, the continuous increase in demand for entrepreneurship emphasizes the effective support of the government for the survival and growth of entrepreneurs and the necessity of establishing systematic initiative promotion policies. To this end, Of the total number of enterprises. The purpose of this study is to establish a new classification system for entrepreneurial industry that reflects the trend of entrepreneurship based on convergence technology that emerged during the 4th Industrial Revolution era in order to establish a systematic initiative upbringing policy. In this paper, we propose a new classification system for entrepreneurial ecosystem by using Delphi technique. As a result of the study, the categories of entrepreneurial industry are classified into technology entrepreneurship and general entrepreneurship. Technology entrepreneurship is divided into ICT services, ICT manufacturing, general manufacturing, cultural contents and biotechnology. The results of this study suggest a meaningful implication in the establishment of effective policies to support entrepreneurship in the future by establishing new standards of industry classification system of entrepreneurs.

• Journal of Environmental Impact Assessment
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• v.5 no.2
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• pp.33-47
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• 1996

To select the criteria, literature review was made in the quantitative case of conservation biology, foreign country's EIA and domestic ecology. Among them, a few factors was extracted. To applicate the criteria to domestic forest ecosystem, expert opinion survey was executed to the ecologist. The results were summarized as follows; 1. Classification of sites was made of land use system which is related to forest ecosystem or forest conservation. Sites are divided into 3 categories which are nature preservation area, seminature preservation area and urbanized area. Evaluation criteria is consisted of rarity and naturalness. 2. Each area had different criteria composition according to the site characteristics. Criteria of nature preservation area is rarity in the broad sense (distribution pattern of vegetation), vegetation size, successional stage and depth of organic matters. Those of seminature preservation area are rarity in the broad sense (distribution area of vegetation), vegetation size, successional stage, diameter at breath height and depth of organic matters. And those of urbanized area are vegetation distribution in area, successional stage, age of forest and diameter of breath height. The basic data of criterion was gathered by field survey. 3. Evaluation index and total naturalness index was obtained by adding the each criterion. It is made up of two categories-rarity and naturalness. TNi is divided into 3 grades. Grade I is more than 70% for TNi, grade IT is 50~70%, and grade III is below 50%. According to the each grade, permitted action and facilities were suggested.. This research just focuses on the evaluation of vegetation quality and the assessment results do not directly judge conservation or development. To make better evaluation criteria, various fields of forest ecosystem-geological or physical nature environment and fauna ecosystem etc. -will be added wholly to this research.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.4
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• pp.37-52
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• 2022

The purpose of this study is to analyze the demand for cultural ecosystem services in urban forests based on user perception and experience value by using Naver blog posts and LDA topic modeling. Bukhansan National Park was used to analyze and review the feasibility of spatial assessments. Based on the results of topic modeling from blog posts, a review process was conducted considering the relevance of Bukhansan National Park's cultural services and its suitability as a spatial assessment case, and finally, an index for the spatial assessment of urban forest's cultural service was derived. Specifically, 21 topics derived through topic analysis were interpreted, and 13 topics related to cultural ecosystem services were derived based on the MA(Millennium Ecosystem Assessment)'s classification system for ecosystem services. 72.7% of all documents reviewed had data deemed useful for this study. The contents of the topic fell into one of the seven types of cultural services related to "mountainous recreation activities" (23.7%), "indirect use value linked to tourism and convenience facilities" (12.4%), "inspirational activities" (11.2%), "seasonal recreation activities" (6.2%), "natural appreciation and static recreation activities" (3.7%). Next, for the 13 cultural service topics derived from data gathered about Bukhansan National Park, the possibility of spatial assessment of the characteristics of cultural ecosystem services provided by urban forests was reviewed, and a total of 8 cultural service indicators were derived. The MA's cultural service classification system for ecosystem services, which was widely used in previous studies, has limitations in that it does not reflect the actual user demand of urban forests, but it is meaningful in that it categorizes cultural service indicators suitable for domestic circumstances. In addition, the study is significant as it presented a methodology to interpret and derive the demand for cultural services using a large amount of user awareness and experience data.

• The Journal of Information Systems
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• v.26 no.3
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• pp.273-293
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• 2017

Purpose The purpose of this study is to introduce a framework that helps Muslims to determine whether a food can be consumed. It can complement existing Halal food classification services having a difficulty of constructing Halal food database. Design/methodology/approach The proposed framework includes two components. First, OCR(Optical Character Recognition) technique is utilized to read the food additive information. Second, machine learning methods were used to trained and predicted to determine whether a food can be consumed using the provided information. Findings Among the compared machine learning methods, SVM(Support Vector Machine), DT(Decision Tree), and NB(Naive Bayes), SVM with linear kernel and DT had excellent performance in the Halal food classification. The framework which adopting the proposed framework will enhance the tourism experiences of Muslim tourists who consider keeping the Islamic law most importantly. Furthermore, it can eventually contribute to the enhancement of smart tourism ecosystem.

• Korean Journal of Environment and Ecology
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• v.36 no.3
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• pp.350-357
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• 2022

A national park is a place to conserve natural resources and visitors to experience nature, and thus, it is necessary to identify the noise distribution characteristic in the national park and preserve and restore the soundscape. However, most national parks in Korea are exposed to noise, leading to negative perceptions of the national park's soundscape and affecting the ecosystem. Many national parks in other countries have investigated the ecosystem impacts caused by noise and have performed various management to reduce the noise. However, in Korea, there is still a lack of awareness of the effect on the ecosystem, overlooking the need for soundscape management. Therefore, in this study, we developed a noise map of Mudeungsan National Park to investigate the quantitative impact of noise on visitors and the ecosystem. Also, we measured the trail's soundscape to describe a sound grade classification, and the soundscape of main spots in the park was recorded for a year and then analyzed. Finally, the sound resource distribution map was described, which can be used as preliminary data to determine the national park's sound distribution characteristics and manage the soundscape.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.1
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• pp.78-84
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• 2003

The purpose of this study is to evaluate the ecosystem soundness in landscape scale using landscape indices, and to extract regional information that can be used for sustainable landuse planning. About BongWha-gun, the landcover classification using Landsat TM images and patch analysis ware carried out, and some landscape indices were calculated using geographic information system(GIS) and patch analyst program. As the results of this study, Seokpo, Jaesan and Sochun got higher scores in landscape indices related to the ecosystem soundness. But, Bonghwa-eup got lowest scores in the 10 regions. When compared with normalized difference vegetation index(NDVI), this result showed consistency to some degree. Although, there needs more supplementary studies, it is anticipated that landscape scale ecosystem evaluation using landscape indices can gives us some informations related to sustainable landuse planning.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.17 no.1
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• pp.111-122
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• 2014

The provided habitat of many services from natural capital is important. But because most ecosystem services tools qualitatively evaluated biodiversity or habitat quality, this study quantitatively analyzed those aspects using the species distribution model (MaxEnt). This study used location point data of the goat(Naemorhedus caudatus), marten(Martes flavigula), leopard cat(Prionailurus bengalensis), flying squirrel(Pteromys volans aluco) and otter(Lutra lutra) from the 3rd National Ecosystem Survey. Input data utilized DEM, landcover classification maps, Forest-types map and digital topographic maps. This study generated the MaxEnt model, randomly setting 70% of the presences as training data, with the remaining 30% used as test data, and ran five cross-validated replicates for each model. The threshold indicating maximum training sensitivity plus specificity was considered as a more robust approach, so this study used it to conduct the distribution into presence(1)-absence(0) predictions and totalled up a value of 5 times for uncertainty reduction. The test data's ROC curve of endangered mammals was as follows: growing down goat(0.896), otter(0.857), flying squirrel(0.738), marten(0.725), and leopard cat(0.629). This study was divided into two groups based on habitat: the first group consisted of the goat, marten, leopard cat and flying squirrel in the forest; and the second group consisted of the otter in the river. More than 60 percent of endangered mammals' distribution probability were 56.9% in the forest and 12.7% in the river. A future study is needed to conduct other species' distribution modeling exclusive of mammals and to develop a collection method of field survey data.

• Asia pacific journal of information systems
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• v.34 no.1
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• pp.150-190
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• 2024

This article proposes a framework to elucidate the structural dynamics of the generative AI ecosystem. It also outlines the practical application of this proposed framework through illustrative policies, with a specific emphasis on the development of the Korean generative AI ecosystem and its implications of platform strategies at AI platform-squared. We propose a comprehensive classification scheme within generative AI ecosystems, including app builders, technology partners, app stores, foundational AI models operating as operating systems, cloud services, and chip manufacturers. The market competitiveness for both app builders and technology partners will be highly contingent on their ability to effectively navigate the customer decision journey (CDJ) while offering localized services that fill the gaps left by foundational models. The strategically important platform of platforms in the generative AI ecosystem (i.e., AI platform-squared) is constituted by app stores, foundational AIs as operating systems, and cloud services. A few companies, primarily in the U.S. and China, are projected to dominate this AI platform squared, and consequently, they are likely to become the primary targets of non-market strategies by diverse governments and communities. Korea still has chances in AI platform-squared, but the window of opportunities is narrowing. A cautious approach is necessary when considering potential regulations for domestic large AI models and platforms. Hastily importing foreign regulatory frameworks and non-market strategies, such as those from Europe, could overlook the essential hierarchical structure that our framework underscores. Our study suggests a clear strategic pathway for Korea to emerge as a generative AI powerhouse. As one of the few countries boasting significant companies within the foundational AI models (which need to collaborate with each other) and chip manufacturing sectors, it is vital for Korea to leverage its unique position and strategically penetrate the platform-squared segment-app stores, operating systems, and cloud services. Given the potential network effects and winner-takes-all dynamics in AI platform-squared, this endeavor is of immediate urgency. To facilitate this transition, it is recommended that the government implement promotional policies that strategically nurture these AI platform-squared, rather than restrict them through regulations and stakeholder pressures.