• Title/Summary/Keyword: digital population model

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Millennial Transformational Leadership on Organizational Performance in Indonesia Fishery Startup

  • WANASIDA, Albert Surya;BERNARTO, Innocentius;SUDIBJO, Niko;PRAMONO, Rudy
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.2
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    • pp.555-562
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    • 2021
  • This study aims to understand the effect of millennial transformational leadership (MTL) on organizational performance in Indonesian Fishery startups. The population of this study included select fishery startups in Indonesia based on the data released by the Ministry of Marine Affairs and Fisheries of the Republic of Indonesia and Digital Fishery Network. This study used the statistical method of PLS-SEM to analyze the data. The findings show that the MTL has no direct positive relationship with organizational performance; MTL has a direct positive relationship with organizational agility; MTL has a direct positive relationship with IT capability; IT capability has a direct positive relationship with organizational agility; organizational agility has a direct positive relationship with organizational performance in fishery startups in Indonesia during this pandemic era. It is suggested that future researches use covariance-based-structural equation modeling which is able to test the research model's feasibility. Roles of mediating variables in addition to the main variables-for example, organizational agility as a mediating variable on the relationship between MTL and organizational performance - are also suggested to be examined. In spite of the limitations, the model developed is still interesting to investigate and is expected to enhance the literature on transformational leadership.

New Landscape of Poverty Management in Land Information System (토지정보를 이용한 빈곤관리의 모델)

  • Liou, Jae-Ik;Oh, Min-Soo;Shin, Young-Chul
    • Journal of the Korean Association of Geographic Information Studies
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    • v.5 no.1
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    • pp.1-19
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    • 2002
  • Estimation and indication for spatial distribution of living quality and poor condition associated with land and house's access as a basic human need has been imperative questions and predicaments while it is required to boost digital economic development and consolidate social maturity. Although modern IT and sophisticated GIS/LIS technologies are used to examine spatial analysis of population location-patterns, land uses and development, and environmental degradation, etc, it still might remain immature step to figure out the causations and results of poverty in space and time. In this research, a new approach to poverty management is explicated by using 6 parameters as a major tool for assisting poverty monitoring concerning the poor who are very unpredictable in space and could be regarded as renegades in the Internet age. In addition, it expounds a new approach and conceptual idea for poverty management to notify spatial location of the digital divide when poverty reduction is closely concerned with sustainable goal of land information.

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A Preliminary Study on the Development of Data Model for Interoperability of Information in Building Disaster Prevention (건물 방재 분야 정보의 상호운용성을 위한 데이터모델 개발에 관한 기초연구)

  • Hwang, ByungJu;Kim, Jang-Wook;Kim, TaeHoon
    • The Journal of the Korea Contents Association
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    • v.19 no.4
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    • pp.30-40
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    • 2019
  • As the urban scale changes and the construction technology develops, the living space is being expanded in three dimensions. However, despite the development of construction technology represented by the appearance of skyscrapers, damage to high - rise buildings with dense population can be rather high. In order to solve such a situation, digital twin technology that can control and predict the real world in real time can be an alternative, and it is necessary to utilize pre-constructed spatial information actively. Therefore, this study aims to provide a standardized data model for using existing such information as well as various information produced in the future to the building disaster prevention field. To this end, we developed a data model that extends the CityGML standard, a representative city information model, to disaster prevention.

Development of Advanced TB Case Classification Model Using NHI Claims Data (국민건강보험 청구자료 기반의 결핵환자 분류 고도화 모형 개발)

  • Park, Il-Su;Kim, Yoo-Mi;Choi, Youn-Hee;Kim, Sung-Soo;Kim, Eun-Ju;Won, Si-Yeon;Kang, Sung-Hong
    • Journal of Digital Convergence
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    • v.11 no.9
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    • pp.289-299
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    • 2013
  • The aim of this study was to enhance the NHI claims data-based tuberculosis classification rule of KCDC(Korea centers for disease control & prevention) for an effective TB surveillance system. 8,118 cases, 10% samples of 81,199 TB cases from NHI claims data during 2009, were subject to the Medical Record Survey about whether they are real TB patients. The final study population was 7,132 cases whose medical records were surveyed. The decision tree model was evaluated as the most superior TB patients detection model. This model required the main independent variables of age, the number of anti-tuberculosis drugs, types of medical institution, tuberculosis tests, prescription days, types of TB. This model had sensitivity of 90.6%, PPV of 96.1%, and correct classification rate of 93.8%, which was better than KCDC's TB detection model with two or more NHI claims for TB and TB drugs(sensitivity of 82.6%, PPV of 95%, and correct classification rate of 80%).

Estimation of Livestock Pollutant Sources Reduction Effect on Water Quality in Hapcheon Dam Watershed Using HSPF Model (HSPF 모형을 이용한 축산계 비점오염 저감에 따른 합천댐 유역 수질 영향 분석)

  • Cho, Hyun Kyung;Kim, Sang Min
    • Journal of Korean Society on Water Environment
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    • v.36 no.2
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    • pp.98-108
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    • 2020
  • The purpose of this study was to evaluate water quality in Hapcheon dam via using the Hydrological Simulation Program-Fortran (HSPF) model and applied livestock reduction scenarios. Hapcheon dam watershed input data for the HSPF model were established using the stream, land use, digital elevation map and meteorological data and others. The HSPF model was calibrated and validated using the observed water quality data from 2000 to 2016. For water quality simulation, we calculated the generated and discharge loads of the population, livestock, industry and land use following the guideline provided by the Ministry of Environment. The pollutant data were obtained from National Institute of Environmental Research (NIER). The monthly discharge load were estimated by applying the delivery rate. The calibration and validation results showed that the annual mean BOD had a difference of 0.22 mg/L and an error of ±13 %, T-N had a difference of 0.66 mg/L and an error of ±16 % and T-P had a difference of 0.027 mg/L and an error of ±13 %. In order to evaluate the nonpoint pollutants management effects, we applied livestock reduction scenarios because livestock consists of the largest portion of pollutants. As a result of the 20 % of livestock reduction, BOD, T-N and T-P decreased by 3 %, 1 % and 3 %, respectively. When 40 % of livestock reduction was applied, BOD, T-N and T-P decreased by 5 %, 3 % and 4 %, respectively. Based on the results of this study, effective pollutant management methods can be applied to improve the water quality and achieve the target water quality of Hapcheon dam watershed.

Water consumption prediction based on machine learning methods and public data

  • Kesornsit, Witwisit;Sirisathitkul, Yaowarat
    • Advances in Computational Design
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    • v.7 no.2
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    • pp.113-128
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    • 2022
  • Water consumption is strongly affected by numerous factors, such as population, climatic, geographic, and socio-economic factors. Therefore, the implementation of a reliable predictive model of water consumption pattern is challenging task. This study investigates the performance of predictive models based on multi-layer perceptron (MLP), multiple linear regression (MLR), and support vector regression (SVR). To understand the significant factors affecting water consumption, the stepwise regression (SW) procedure is used in MLR to obtain suitable variables. Then, this study also implements three predictive models based on these significant variables (e.g., SWMLR, SWMLP, and SWSVR). Annual data of water consumption in Thailand during 2006 - 2015 were compiled and categorized by provinces and distributors. By comparing the predictive performance of models with all variables, the results demonstrate that the MLP models outperformed the MLR and SVR models. As compared to the models with selected variables, the predictive capability of SWMLP was superior to SWMLR and SWSVR. Therefore, the SWMLP still provided satisfactory results with the minimum number of explanatory variables which in turn reduced the computation time and other resources required while performing the predictive task. It can be concluded that the MLP exhibited the best result and can be utilized as a reliable water demand predictive model for both of all variables and selected variables cases. These findings support important implications and serve as a feasible water consumption predictive model and can be used for water resources management to produce sufficient tap water to meet the demand in each province of Thailand.

Are the conservation areas sufficient to conserve endangered plant species in Korea?

  • Kang, Hye-Soon;Shin, Sook-Yung;Whang, Hye-Jin
    • Journal of Ecology and Environment
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    • v.33 no.4
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    • pp.377-389
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    • 2010
  • Understanding the factors relevant to endangerment and the patterns of habitat locations in relation to protected areas is critically important for the conservation of rare species. Although 64 plant species have recently been listed as endangered species in Korea, this information has, until now, not been available, making appropriate management and conservation strategies impossible to devise. Thus, we collected information on potentially threatening factors, as well as information on the locations in which these species were observed. The potentially threatening factors were classified into seven categories. National parks, provincial parks, ecosystem conservation areas, and wetland conservation areas were defined as protected conservation areas. Korean digital elevation model data, along with the maps of all protected areas were combined with the maps of endangered plant species, and analyzed via Geographic Information Systems (GIS). Excluding the category of "small population", endangered plant species in Korea were associated more frequently with extrinsic factors than intrinsic factors. Considering land surface only, all conservation areas in Korea totaled 4.9% of the land, far lower than International Union for Conservation of Nature and Natural Resources (IUCN)'s 10% coverage target. At the species level, 69% of the endangered plant species were detected in conservation areas, mostly in national parks. However, this result demonstrates that 31% of endangered species inhabit areas outside the conservation zones. Furthermore, at the habitat level, a large proportion of endangered species were found to reside in unprotected areas, revealing "gaps" in protected land. In the face of rapid environmental changes such as population increases, urbanization, and climate changes, converting these gap areas to endangered species' habitats, or at least including them in habitat networks, will help to perpetuate the existence of endangered species.

A Multivariate Analysis of Changing Information Gaps in Korea (사회인구학적 배경에 따른 정보격차의 다원모형분석)

  • 심상완;김정석
    • Korea journal of population studies
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    • v.24 no.2
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    • pp.235-253
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    • 2001
  • As we are entering the information society, there are increasing concerns about information gaps which are believed to create serious obstacles to social integration and development. Previous studies on the information gaps in Korea, despite their contributions to our understanding of the issue, appear to be descriptive. This study attempts to analyze the relative importance of residential area, gender, age education, and household income for information gaps and their changes in recent years. Based on the data from two surveys conducted by the Information Culture Center, the study run multivariate logit model analysis of the sue of computer and internet. The result shows that all the variables except residential area have influences on the use of computer and internet. In terms of time change, gender-based difference in the use of digital media has decreased between 1998 and 2000 while the differences by all the other variables have remained constant or increased.

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Convolutional neural network of age-related trends digital radiographs of medial clavicle in a Thai population: a preliminary study

  • Phisamon Kengkard;Jirachaya Choovuthayakorn;Chollada Mahakkanukrauh;Nadee Chitapanarux;Pittayarat Intasuwan;Yanumart Malatong;Apichat Sinthubua;Patison Palee;Sakarat Na Lampang;Pasuk Mahakkanukrauh
    • Anatomy and Cell Biology
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    • v.56 no.1
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    • pp.86-93
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    • 2023
  • Age at death estimation has always been a crucial yet challenging part of identification process in forensic field. The use of human skeletons have long been explored using the principle of macro and micro-architecture change in correlation with increasing age. The clavicle is recommended as the best candidate for accurate age estimation because of its accessibility, time to maturation and minimal effect from weight. Our study applies pre-trained convolutional neural network in order to achieve the most accurate and cost effective age estimation model using clavicular bone. The total of 988 clavicles of Thai population with known age and sex were radiographed using Kodak 9000 Extra-oral Imaging System. The radiographs then went through preprocessing protocol which include region of interest selection and quality assessment. Additional samples were generated using generative adversarial network. The total clavicular images used in this study were 3,999 which were then separated into training and test set, and the test set were subsequently categorized into 7 age groups. GoogLeNet was modified at two layers and fine tuned the parameters. The highest validation accuracy was 89.02% but the test set achieved only 30% accuracy. Our results show that the use of medial clavicular radiographs has a potential in the field of age at death estimation, thus, further study is recommended.

Analysis of Success Cases of InsurTech and Digital Insurance Platform Based on Artificial Intelligence Technologies: Focused on Ping An Insurance Group Ltd. in China (인공지능 기술 기반 인슈어테크와 디지털보험플랫폼 성공사례 분석: 중국 평안보험그룹을 중심으로)

  • Lee, JaeWon;Oh, SangJin
    • Journal of Intelligence and Information Systems
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    • v.26 no.3
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    • pp.71-90
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    • 2020
  • Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.