• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.73-83
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• 2011

In the manufacturing system, production-planning is very important in effective management for expensive production facilities and machineries. To enhance efficiency of Manufacturing Execution System(MES), a manufacturing system that reduces the difference between planning and execution, certain production-planning needs a dispatching rule that is properly designed for characteristic of work information and there should be a appropriate selection for the rule as well. Therefore, in this paper dispatching rule will be selected by several simulations based on characteristics of work information derived from process planning data. By constructing information that are from simulation into ontology, one of the knowledge-based-reasoning, production planning platform based on the selection of dispatching rule will be demonstrated. The platform has strength in its wider usage that is not limited to where it is applied. To demonstrate the platform, RacerPro and Prot$\acute{e}$g$\acute{e}$ are used in parts of ontology reasoning, and JAVA and FlexChart were applied for production-planning simulation.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.562-582
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• 2022

Although personal media have become a giant industry, there is a lack of understanding of personal media creators. Therefore, this study aims to clarify factors influencing personal media creators' choice of platform. According to the analysis, there is a significant difference between the factors considered by YouTube, AfreecaTV, and Twitch creators. Moreover, the moderating effect of creators' main genre and broadcasting type were also found to be partially significant. It was found that both creators who share the motive of vividness and communication as their main genre and creators who focus on recording and broadcasting with career development motivation prefer YouTube.

• Journal of Ocean Engineering and Technology
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• v.27 no.4
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• pp.22-32
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• 2013

This paper presents the conceptual design procedure for the taut-leg mooring lines of a floating-type combined renewable energy platform. The basic configuration of the platform is determined based on an understanding of floating offshore plants. The main dimensions and mass distribution are determined based on a hydrostatic calculation. To identify the motion history of the floating platform and the tension history of the mooring lines, a hydrodynamic analysis is executed using Ansys.Aqwa. This helps in the selection of the best configuration for the mooring system such as the number of mooring lines, wire types, anchored positions, etc. In addition, the fatigue life of the mooring lines can be predicted from the tension history using the rain-flow cycle counting method.

• 전자공학회논문지 IE
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• v.47 no.1
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• pp.48-55
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• 2010

The goal of this paper is to determine optimal hardware platform for specific applications. In order to develop an understanding of how select the optimal platform, we focus upon the real-time embedded vehicle system for processing forward image and sound. In this paper we propose to measure parameters such as instructions, execution cycle, required memory size for program and data by using ARMulator. We have measured three types of processor cores: ARM7, ARM9 and ARM10. The results of the study indicated that the proposed methods could measure the minimal requirements of hardware platform for specific applications. By defining lower limit of hardware specifications in embedded systems, we can minimize expenses with suitable system performance without implementing the system.

• ETRI Journal
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• v.41 no.6
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• pp.750-759
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• 2019

Presently, the extraction of hand-crafted features is still the dominant method in radar emitter recognition. To solve the complicated problems of selection and updation of empirical features, we present a novel automatic feature extraction structure based on deep learning. In particular, a convolutional neural network (CNN) is adopted to extract high-level abstract representations from the time-frequency images of emitter signals. Thus, the redundant process of designing discriminative features can be avoided. Furthermore, to address the performance degradation of a single platform, we propose the construction of an ensemble learning-based architecture for multi-platform fusion recognition. Experimental results indicate that the proposed algorithms are feasible and effective, and they outperform other typical feature extraction and fusion recognition methods in terms of accuracy. Moreover, the proposed structure could be extended to other prevalent ensemble learning alternatives.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.12
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• pp.7340-7349
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• 2014

BIM (Building Information Model) and GIS (Geographic Information System) are applied widely to all stages (Planning - Design - Building - Maintenance) of construction. Recently, research for designing an integrated BIM/GIS platform has been conducted to determine the synergy effects. This paper reports the derivation of BIM/GIS platform application scenarios and definition of specific functions in construction planning and design phases. First, BIM/GIS application scenarios and platform functions are derived for each phase based on an analysis of business affairs. Second, SW functions, which compose platform function, are defined. In the construction planning phase, location selection and route location business affairs were analyzed. Preliminary design and detailed design business affairs were analyzed in the construction design phase. The result of this research can be used for BIM/GIS integrated platform design in the future.

• The Journal of Bigdata
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• v.5 no.1
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• pp.11-27
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• 2020

In this paper, we developed a big data platform to store, process, and analyze effectively on such education longitudinal study data. And it was applied to the Seoul Education Longitudinal Study(SELS) to confirm its usefulness. The developed platform consists of data preprocessing unit and data analysis unit. The data preprocessing unit 1) masking, 2) converts each item into a factor 3) normalizes / creates dummy variables 4) data derivation, and 5) data warehousing. The data analysis unit consists of OLAP and data mining(DM). In the multidimensional analysis, OLAP is performed after selecting a measure and designing a schema. The DM process involves variable selection, research model selection, data modification, parameter tuning, model training, model evaluation, and interpretation of the results. The data warehouse created through the preprocessing process on this platform can be shared by various researchers, and the continuous accumulation of data sets makes further analysis easier for subsequent researchers. In addition, policy-makers can access the SELS data warehouse directly and analyze it online through multi-dimensional analysis, enabling scientific decision making. To prove the usefulness of the developed platform, SELS data was built on the platform and OLAP and DM were performed by selecting the mathematics academic achievement as a measure, and various factors affecting the measurements were analyzed using DM techniques. This enabled us to quickly and effectively derive implications for data-based education policies.

• The Korean Journal of Food & Health Convergence
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• v.10 no.4
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• pp.9-19
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• 2024

This qualitative study explores the impact of online food delivery platform attributes on customer satisfaction and repurchase intentions. Employing a phenomenological approach, we conducted in-depth interviews and focus group discussions with 15 participants to gain rich insights into user experiences. Thematic analysis revealed key factors influencing satisfaction and loyalty: service quality dimensions (efficiency, reliability, fulfillment, privacy), expectation disconfirmation, perceived usefulness and ease of use, multi-level customer value, relationship quality, electronic word-of-mouth, value co-creation, and phased loyalty formation. Our findings extend customer behavior theory in digital platforms, offering a comprehensive framework for understanding the complex mechanisms underlying user satisfaction and repurchase decisions. The study provides valuable implications for platform operators, highlighting the importance of exceeding customer expectations, enhancing user experience, building trust, leveraging user-generated content, and fostering co-creation processes. Methodologically, we demonstrate the efficacy of qualitative approaches in uncovering nuanced insights in digital service contexts. While acknowledging limitations in generalizability, this research establishes a solid foundation for future investigations into the rapidly evolving domain of online food delivery services. The integrated theoretical approach offers a robust model for analyzing customer behavior in emerging digital service environments, contributing significantly to both academic understanding and practical application in the field of digital service provision and platform management.

• Asia pacific journal of information systems
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• v.29 no.2
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• pp.248-267
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• 2019

As merging online and offline channels into one single platform, individuals could easily and frequently switch between online and offline channels. In order for understanding such unique behaviors, this study attempts to explore why and how consumers choose their channels to search and purchase a product. We have drawn on multiple theories that have been used to explain individuals' judgment and decision making (i.e., construal level theory and regula-tory focus theory) in order to develop and tested two-way ANOVA based models of how both regulatory focus (e.g., promotion vs. prevention) and product types (e.g., experience goods vs. searching goods) including the psychological distance cue separately and jointly affect individuals' channel selection behavior (e.g., intention to use single channel vs. intention to use cross-channels). Our results have indicated that consumers with promotion-focus are more likely to use a single channel in experience goods rather than in searching goods when there exists the psychological cue. Based on our findings, the implication for both research and practice are discussed.

• Journal of the Korea Knowledge Information Technology Society
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• v.13 no.1
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• pp.11-23
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• 2018

This paper empirically investigates the factors that influence the consumer choice of an app market based on the rational choice theory. The app market is the only channel where a consumer can buy smartphone apps, which give various functional convenience and are considered to be a major contributor to the proliferation of smartphones. Analyses of 281 questionnaires show that usability and structural guarantees as benefit factors significantly influence the app market choice. From the cost perspectives, both monetary and non-monetary conversion costs are found to significantly influence the app market choice. On the other hand, customer trust, information quality, and market image were found to have no significant effect on app market selection. In particular, Korean app market platform providers (KT, LG U +) seem to be superior in terms of structural guarantees, such as customer center operation and damage compensation regulations, compared to overseas app market platform operators (Google). However, in the case of the Google App Market, it is pre-installed on all Android phones, so it is not inconvenient to install additional apps to use other app market. This is disadvantageous to domestic app market platform operators, and it is necessary to establish a policy solution point. In terms of operator costs, both monetary and non-monetary conversion costs have a significant impact on app market choice. In particular, non-monetary conversion costs have a negative impact on Korean app market platform operators. It can be explained that the service expectation level of the domestic app market is low and it is recognized that the time cost factor such as membership is large for new users to use. It seems to be necessary to improve the domestic app market business. Meanwhile, extant research on smartphone apps focuses on the purchase of apps themselves, but not on the selection of the app market itself. In order to fill in this gap, this study focuses on the determinants of app market selection, including the characteristics of an app market and the switching costs.