• Journal of the Korean Society of Environmental Restoration Technology
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• v.20 no.1
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• pp.131-142
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• 2017

The function of urban parks as wildlife habitats is becoming increasingly important. The urban park serves as a key area for preserving urban biodiversity. The purpose of this study is to estimate the bird species diversity in 30 parks in Cheonan city and quantitatively analyze the influence of vegetation, park structure and landscape connectivity index. As the results, a total of 27 birds species and 1,509 individuals were found at the sites and the largest number of birds were found in the Cheongsa park with 17 species. The optimal regression model was selected as the explanatory variables for the logged park area (LPA), the tree cover ratio (Co_T) and the patch betweenness centrality (PB). LPA and Co_T mean the internal characteristics of the park, and PB was the external environmental variable meaning landscape connectivity. LPA was the most important factor (73.3%) as bird habitat, and the PB could be interpreted as a factor that should be considered as important (26.7%). It will be possible to consider these environmental variables in the park and green area construction and management.

• Health Policy and Management
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• v.24 no.4
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• pp.380-388
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• 2014

Background: The volume of surgery has been examined as a major source of variation in outcome after surgery. This study investigated the direct effect of surgery volume to in hospitals mortality and the moderating effect of structural complexity-the level of diversity and sophistication of technology a hospital applied in patient care-to the volume outcome relationship. Methods: Discharge summary data of 11,827 cancer patients who underwent surgery and were discharged during a month period in 2010 and 2011 were analyzed. The analytic model included the independent variables such as surgery volume of a hospital, structural complexity measured by the number of diagnosis a hospital examined, and their interaction term. This study used a hierarchical logistic regression model to test for an association between hospital complexity and mortality rates and to test for the moderating effect in the volume outcome relationship. Results: As structural complexity increased the probability of in-hospital mortality after cancer surgery reduced. The interaction term between surgery volume and structural complexity was also statistically significant. The interaction effect was the strongest among the patients group who had surgery in low volume hospitals. Conclusion: The structural complexity and volume of surgery should be considered simultaneously in studying volume outcome relationship and in developing policies that aim to reduce mortality after cancer surgery.

• Journal of Korean Society for Quality Management
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• v.51 no.1
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• pp.1-18
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• 2023

Purpose: In Part 1, the purpose of this study is to examine how a used product provider optimizes a company's profits by comparing an extended warranty to a used product only when selling a product and what it provides later. In addition, in Part 2, an empirical study can confirm the structure in which extended guarantees can work effectively by grasping consumers' purchase intention according to the time of sale of extended guarantees, which is the basic premise of the analysis model of Part 1. Methods: This study aims to conduct not only analytical studies but also empirical studies applying various statistical analysis methods using questionnaires targeting customers and potential consumers who have subscribed to extended warranty services. Results: The study showed that the profits of companies providing extended warranty services were proportional to the coefficient of the extended guarantee service value, so it is necessary to create an environment in which the effect of extended guarantee services can be well realized. In the empirical model, the higher the emotional and economic benefits are perceived, the higher the purchase intention according to the future purchase of extended guarantees. Conclusion: Through this study, various problems that may be caused by the structural diversity of the supply chain providing extended warranties in the future can be viewed and contribute to the theoretical foundation for strategic understanding.

• Journal of Information Technology Services
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• v.17 no.2
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• pp.143-163
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• 2018

The business models has a great impact on the successful management of enterprises. Business environment has been shifting from industrial economy to knowledge-based economy. Enterprises go through numerous trials for successful management in the changing environment. Along with trial tests, research areas have been growing simultaneously. Although many researches have been conducted with regard to business models, it is very insufficient to systematically analyze the knowledge flow of research. Accordingly, successive researchers who want to study the business model may find it difficult to establish the orientation of future application research based on understanding the process of changing the knowledge structure that have accumulated so far. This study is intended to determine the current state of the business model research and to understand the process of knowledge structure changes in keywords that appear in 2,667 business model articles in the SCOPUS database. Identifying the knowledge structure has been completed through social network analysis, a methodology based on the 'relationship', and the changes in the knowledge structure were identified by classifying them into four different periods. The analysis showed that, first, the number of business model co-author increases over time with the need for academic diversity. Second, the 'innovation' keyword has the biggest center in the network, and over time, the lower-rank keyword which was in the former period has emerged as the top-rank keyword. Third, the cohesiveness group decreased from 12 before 2000 to 5 in 2015 and also the modularity decreased as well. Finally, examining characteristics of study area through a cognitive map showed that the relationships between domains increased gradually over time. The study has provided a systematic basis for understanding the current state of the business model research and the process of changing knowledge structure. In addition, considering that no research has ever systematically analyzed the knowledge structure accumulated by individual researches, it is considered as a significant study.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.21 no.6
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• pp.55-69
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• 2018

As disaster risk and climate change volatility increase, there are more efforts to adapt to disasters such as forest fires, floods, and landslides. Most of the research, however, is about influence of human activities on disaster and there is few research on disaster adaptation for species. Previous studies focusing on biodiversity in selecting conservation areas have not addressed threats of disaster in the habitats for species. The natural disasters sometimes play role of drivers of ecological successions in the long run, but they might cause serious problems for the conservation of vulnerable species which are endangered. The purpose of this study is to determine whether soil loss (SL) is effective in selecting habitat management areas for amphibians and reptiles. RUSLE model was used to calculate soil loss (SL) and the distribution of each species (SD) was computed with MaxEnt model to find out the biodiversity index. In order to select the habitat management area, we estimated the different results depending if value of soil loss was applied or not by using MARXAN, a conservation priority selection tool. With using MARXAN, conservation goals can be achieved according to the scenario objectives, and the study has been made to meet the minimum habitat area. Finally, the results are expressed in two; 1) the result of soil loss and biodiversity with MATRIX method and 2) the result of regional difference calculated with MARXAN conservation prioritization considering soil loss. The first result indicates that the area with high soil loss and low species diversity have lower conservation values and thus can be managed as natural disturbances. In the area where soil loss is high and species diversity is also high, it becomes where a disaster mitigation action should be taken for the species. According to the conservation priorities of the second result, higher effectiveness of conservation was obtained with fewer area when it considered SL in addition to SD, compared to when considered only biodiversity. When the SL was not taken into consideration, forest area with high distribution of species were important, but when SL considered, the agricultural area or downstream of the river were represented to be a major part of habitats. If more species data or disaster parameters other than soil loss are added as variables later, it could contribute as a reference material for decision-making to achieve various purposes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1481-1501
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• 2019

In opportunistic network, the behavior of a node is autonomous and has social attributes such as selfishness.If a node wants to forward information to another node, it is bound to be limited by the node's own resources such as cache, power, and energy.Therefore, in the process of communication, some nodes do not help to forward information of other nodes because of their selfish behavior. This will lead to the inability to complete cooperation, greatly reduce the success rate of message transmission, increase network delay, and affect the overall network performance. This article proposes a hybrid incentive mechanism (Mim) based on the Reputation mechanism and the Credit mechanism.The selfishness model, energy model (The energy in the article exists in the form of electricity) and transaction model constitute our Mim mechanism. The Mim classifies the selfishness of nodes and constantly pay attention to changes in node energy, and manage the wealth of both sides of the node by introducing the Central Money Management Center. By calculating the selfishness of the node, the currency trading model is used to differentiate pricing of the node's services. Simulation results show that by using the Mim, the information delivery rate in the network and the fairness of node transactions are improved. At the same time, it also greatly increases the average life of the network.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.191-202
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• 2023

This study aims to propose a framework for evaluating the impact of artificial intelligence (AI) services, based on the concept of AI service impact. It also suggests a model for evaluating this impact and identifies relevant factors and measurement approaches for each item of the model. The study classifies the impact of AI services into five categories: ethics, safety and reliability, compliance, user rights, and environmental friendliness. It discusses these five categories from a broad perspective and provides 21 detailed factors for evaluating each category. In terms of ethics, the study introduces three additional factors-accessibility, openness, and fairness-to the ten items initially developed by KISDI. In the safety and reliability category, the study excludes factors such as dependability, policy, compliance, and awareness improvement as they can be better addressed from a technical perspective. The compliance category includes factors such as human rights protection, privacy protection, non-infringement, publicness, accountability, safety, transparency, policy compliance, and explainability.For the user rights category, the study excludes factors such as publicness, data management, policy compliance, awareness improvement, recoverability, openness, and accuracy. The environmental friendliness category encompasses diversity, publicness, dependability, transparency, awareness improvement, recoverability, and openness.This study lays the foundation for further related research and contributes to the establishment of relevant policies by establishing a model for evaluating the impact of AI services. Future research is required to assess the validity of the developed indicators and provide specific evaluation items for practical use, based on expert evaluations.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.249-263
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• 2023

Collaborative Filtering, a representative recommendation system methodology, consists of two approaches: neighbor methods and latent factor models. Among these, the latent factor model using matrix factorization decomposes the user-item interaction matrix into two lower-dimensional rectangular matrices, predicting the item's rating through the product of these matrices. Due to the factor vectors inferred from rating patterns capturing user and item characteristics, this method is superior in scalability, accuracy, and flexibility compared to neighbor-based methods. However, it has a fundamental drawback: the need to reflect the diversity of preferences of different individuals for items with no ratings. This limitation leads to repetitive and inaccurate recommendations. The Adaptive Deep Latent Factor Model (ADLFM) was developed to address this issue. This model adaptively learns the preferences for each item by using the item description, which provides a detailed summary and explanation of the item. ADLFM takes in item description as input, calculates latent vectors of the user and item, and presents a method that can reflect personal diversity using an attention score. However, due to the requirement of a dataset that includes item descriptions, the domain that can apply ADLFM is limited, resulting in generalization limitations. This study proposes a Generalized Adaptive Deep Latent Factor Recommendation Model, G-ADLFRM, to improve the limitations of ADLFM. Firstly, we use item ID, commonly used in recommendation systems, as input instead of the item description. Additionally, we apply improved deep learning model structures such as Self-Attention, Multi-head Attention, and Multi-Conv1D. We conducted experiments on various datasets with input and model structure changes. The results showed that when only the input was changed, MAE increased slightly compared to ADLFM due to accompanying information loss, resulting in decreased recommendation performance. However, the average learning speed per epoch significantly improved as the amount of information to be processed decreased. When both the input and the model structure were changed, the best-performing Multi-Conv1d structure showed similar performance to ADLFM, sufficiently counteracting the information loss caused by the input change. We conclude that G-ADLFRM is a new, lightweight, and generalizable model that maintains the performance of the existing ADLFM while enabling fast learning and inference.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.32-32
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• 2019

The aim of this study was to provide basic guidelines for conservation and management of endangered plants in the national parks of Korea. Iris dichotoma Pall. (Iridaceae), which is a popular garden plant, is considered a second-class endangered species by Korean government and it is listed as a EN (Endangered) species in Red Data Book of Korea. We analyzed ecological conditions of I. dichotoma habitats based on vegetation properties and soil characteristics. This species which is known to inhabit in grassland adjacent to the ocean of lowlands slope and its population was located at an elevation of 8 m to 11 m. In the study sites, the mean of soil organic matter, total nitrogen and soil pH were 6.16%, 0.234% and 5.39 respectively. Additionally, the genetic variation and structure of three populations were assessed using ISSR (Inter Simple Sequence Repeat) markers. The genetic diversity of I. dichotoma (P = 59.46%, H = 0.206, S = 0.310) at the species level was relatively high. Analysis of molecular variance (AMOVA) showed 82.1% of the total genetic diversity was occurred in within populations and 17.9% variation among populations. Lastly, we developed predicted distribution model based on climate and topographic factors by applying SDMs (Species Distribution Models). Consequently, current status of I. dichotoma habitats is limited with natural factors such as the increase of the coverage rate of the herbs due to ecological succession. Therefore, it is essential to establish in situ and ex situ conservation strategies for protecting natural habitats and to require exploring potential and alternative habitats for reintroduction.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.2
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• pp.11-16
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• 2015

A lot of factor effects on the enterprise's innovation and business performance, for instance CEO and members intention etc.. Niehoff et al. says, The success factors of innovation enterprise's management lead to members of vision, innovation, innovation activities and support for an aggressive attitude of the enterprise members. However, today's products consumers wanted diverse and complex needs. CEO and members of the enterprise has been the diversity effort. The increase cost savings as well as in the profit improve factors that enterprise's participated a education and training, Subgroup activities, process quality, eliminate waste, improve yields, lead time reduction, process capability increasing, ets. This paper is a report of an empirical survey performed to 277 small and medium-sized enterprise in the korea. Cronbach's alpha coefficient is employed to analyze the reliability of the data. The effect analysis of each group is performed by the SEM(structural equation model). We use the SPSS' Amos program to analyze the equation modeling and test the hypotheses of the model.