• 경영과학
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• 제25권3호
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• pp.101-122
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• 2008

A wide variety of convergent digital products are emerging through the combination of multiple independent digital technologies. Digital convergence provides new revenue sources for businesses and new ways of satisfying individual needs of consumers. Despite its business and consumer implications, little research has addressed how people perceive or evaluate convergent products. This study aims at understanding how consumers interpret and evaluate convergent digital products by conducting two consecutive studies. Firstly, a survey was conducted to understand how people interpret convergent products in three ways suggested by the conceptual combination theory based in cognitive science. Secondly, an experiment was conducted to investigate the impact of combination strategies and product similarities on user evaluation of convergent products. Study results indicate that similarity of constituent products has a substantial effect on the interpretation of concept combination strategies. Moreover, combination strategy and product similarity were found to have substantial effects on user comprehension, perceived newness, and preferences for convergent products. This paper ends with an examination of the implications and limitations of the study results.

• 품질경영학회지
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• 제46권4호
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• pp.1001-1014
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• 2018

Purpose: Autonomous driving cars, which are often represent the new convergence product, have been researched since the early years of 1900 but their safety assurance policies are yet to be implemented for real world practices. The primary purpose of this paper is to propose a modular concept based on which a safety assurance system can be designed and implemented for operating autonomous driving cars. Methods: We combine a set of key attributes of CE mark (European Assurance standard), E-Mark (Automobile safety assurance system), and A-SPICE (Automobile software assurance standard) into a modular approach. Results: Autonomous vehicles are emphasizing software safety, but there is no integrated safety certification standard for products and software. As such, there is complexity in the product and software safety certification process during the development phase. Using the concept of module, we were able to come up with an integrated safety certification system of product and software for practical uses in the future. Conclusion: Through the modular concept, both international and domestic standards policy stakeholders are expected to consider a new structure that can help the autonomous driving industries expedite their commercialization for the technology advanced market in the era of Industry 4.0.

• 말소리와 음성과학
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• 제7권4호
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• pp.17-25
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• 2015

For blind source separation of convolutive mixtures, FDICA(Frequency Domain Independent Component Analysis) algorithms are generally used. Since FDICA algorithm such as Sawada FDICA, IVA(Independent Vector Analysis) works on the frequency bin basis with a natural gradient descent method, it takes much time to converge. In this paper, we propose a new method to improve convergence speed in FDICA algorithm. The proposed method reduces the number of iteration drastically in the process of natural gradient descent method by applying a weighted inner product constraint of unmixing matrix. Experimental results have shown that the proposed method achieved large improvement of convergence speed without degrading the separation performance of the baseline algorithms.

• 식품보건융합연구
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• 제10권2호
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• pp.1-5
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• 2024

This study aims to investigate the impact of character collaboration product characteristics on brand awareness and purchase intention within the food and beverage (F&B) industry, with a special focus on Generation MZ's growing interest in such products. The methodology involves a comprehensive review of existing literature on character marketing, brand awareness, and consumer purchase intention, supplemented by case studies of successful character collaborations in the F&B sector. The findings reveal that character collaborations significantly impact brand awareness and purchase intentions, particularly among younger consumers like Generation MZ. These collaborations not only rekindle nostalgia but also introduce new and exciting consumer experiences, effectively attracting a wide demographic. The success of character-themed products, from Pokémon bread to Coca-Cola's League of Legends collaboration, underscores the strategy's effectiveness in boosting brand recognition and consumer engagement. The implications of this research are manifold for the F&B industry. Firstly, it highlights the importance of leveraging popular characters to forge emotional connections with consumers. Secondly, it suggests that product development should closely align with consumer preferences and market trends to maximize appeal. Lastly, it positions character collaboration as a strategic marketing tool that not only enhances product sales but also strengthens brand loyalty and facilitates sustained brand growth.

• Journal of Information Technology Applications and Management
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• 제20권3_spc호
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• pp.295-314
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• 2013

These days a great mix of traditional and digital contents such as movie, broadcasting, advertisement, e-books, music, game, animation, cartoon, character, knowledge information, and art performance are widely available. Many more are yet to come, with improved quality and added features. It is expected that all these contents will be evolved into a new breed of convergence content through the process of consolidation, expansion, integration, and recreation. Across the digital ecosystem, a new formula is being added to the industrial structure : 'Information/Content-Platform/Device-Goods/Service.' In the near future, as a result of technological innovation and convergence, the business sector will lose its boundaries as well, as businesses will be forced to look beyond the product itself and focus more on multi-functionality. Especially, in the era of creative economy, more policies need to be crafted in order to procure a new growth engine for the future with the agenda for convergence between humanities and technology. Therefore, the purpose of this paper is to analyze the concept, factors, elements, types, and cases of convergence, which are the essence of content convergence. This analysis, with its focus on the convergence process, will help identify the effects and limits of content convergence as well as the prospects for convergence contents in the smart ecosystem under the creative economic system.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제2권6호
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• pp.377-382
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• 2013

제품라인공학 기반의 융합소프트웨어 개발 방법론에서는 어플리케이션 개발을 위해 아키텍처 모델을 제안하고 있다. 그리고 명세를 이용하여 제어컴포넌트를 개발하도록 제안하는데 워크플로우는 트랜잭션을 주로 처리하는 어플리케이션 개발을 위해 제안되었다. 제품라인 공학 기반의 소프트웨어 개발이 효과를 발휘하기 위해서는 도구의 지원이 반드시 필요하다. 하지만 기존의 워크플로우 모델링 도구들은 제품라인 공학개념을 지원하지 않기 때문에 워크플로우 기반의 제품라인 소프트웨어 개발을 지원할 수 있는 도구의 개발이 필요했다. 본 논문에서는 워크플로우 기반의 제품라인 소프트웨어 개발을 지원하기 위해서 개발된 도구를 소개하고 개발된 도구의 활용 가능성을 확인하기 위해서 간단한 활용예제를 소개한다.

• 한국정보통신학회논문지
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• 제18권5호
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• pp.1201-1206
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• 2014

소규모 상점은 상품 관리를 대부분 수기에 의존하고 있다. 이러한 수기 관리는 다양한 제품의 입출고 현황을 관리하는데 제한적이며 실시간 상품현황 관리는 별도의 통계 시스템을 이용해야 한다. 이러한 문제점을 해결하기 위해 개발된 기존의 POS 시스템은 고가의 비용 및 공간의 제약으로 중대형 및 특수매장 위주로 운용되고 있다. 이 때문에 소규모 상점의 수기에 의한 상품관리 대신 비용부담이 적지만 자동화된 새로운 상품관리 시스템이 필요하다. 본 논문에서는 NFC 기능을 탑재한 스마트폰을 활용하여 소규모 상점에서 판매되는 상품을 실시간으로 관리할 수 있는 시스템을 개발하였다.

• 대한수학회논문집
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• 제34권4호
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• pp.1157-1162
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• 2019

In this paper, we extend the study of general convergence theorems for the Picard iteration of Proinov contraction from the class of continuous mappings to the class of discontinuous mappings. As a by product we provide a new affirmative answer to the open problem posed in [20].

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.134-134
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• 2021

Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.143-143
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• 2022

Precipitation plays an essential role in water resources management and disaster prevention. Therefore, the understanding related to spatiotemporal characteristics of rainfall is necessary. Nowadays, highly accurate precipitation is mainly obtained from gauge observation systems. However, the density of gauge stations is a sparse and uneven distribution in mountainous areas. With the proliferation of technology, satellite-based precipitation sources are becoming increasingly common and can provide rainfall information in regions with complex topography. Nevertheless, satellite-based data is that it still remains uncertain. To overcome the above limitation, this study aims to take the strengthens of machine learning to generate a new reanalysis of precipitation data by fusion of multiple satellite precipitation products (SPPs) with gauge observation data. Several machine learning algorithms (i.e., Random Forest, Support Vector Regression, and Artificial Neural Network) have been adopted. To investigate the robustness of the new reanalysis product, observed data were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the machine learning model showed higher accuracy than original satellite rainfall products, and its spatiotemporal variability was better reflected than others. Thus, reanalysis of satellite precipitation product based on machine learning can be useful source input data for hydrological simulations in ungauged river basins.