• ETRI Journal
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• v.42 no.5
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• pp.686-699
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• 2020

In this paper, we propose a supervised-learning-based spatial performance prediction (SLPP) framework for next-generation heterogeneous communication networks (HCNs). Adaptive asset placement, dynamic resource allocation, and load balancing are critical network functions in an HCN to ensure seamless network management and enhance service quality. Although many existing systems use measurement data to react to network performance changes, it is highly beneficial to perform accurate performance prediction for different systems to support various network functions. Recent advancements in complex statistical algorithms and computational efficiency have made machine-learning ubiquitous for accurate data-based prediction. A robust network performance prediction framework for optimizing performance and resource utilization through a linear discriminant analysis-based prediction approach has been proposed in this paper. Comparison results with different machine-learning techniques on real-world data demonstrate that SLPP provides superior accuracy and computational efficiency for both stationary and mobile user conditions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.21-29
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• 2024

Fueled by international efforts towards AI standardization, including those by the European Commission, the United States, and international organizations, this study introduces a AI-driven framework for analyzing advancements in drone technology. Utilizing project data retrieved from the NTIS DB via the "drone" keyword, the framework employs a diverse toolkit of supervised learning methods (Keras MLP, XGboost, LightGBM, and CatBoost) enhanced by BERTopic (natural language analysis tool). This multifaceted approach ensures both comprehensive data quality evaluation and in-depth structural analysis of documents. Furthermore, a 6T-based classification method refines non-applicable data for year-on-year AI analysis, demonstrably improving accuracy as measured by accuracy metric. Utilizing AI's power, including GPT-4, this research unveils year-on-year trends in emerging keywords and employs them to generate detailed summaries, enabling efficient processing of large text datasets and offering an AI analysis system applicable to policy domains. Notably, this study not only advances methodologies aligned with AI Act standards but also lays the groundwork for responsible AI implementation through analysis of government research and development investments.

• Journal of Korean Society for Quality Management
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• v.40 no.1
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• pp.39-48
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• 2012

An early detection system for warranty issues periodically collects customers' claim data and automatically reports alarms about emerging issues based on statistical algorithms. It helps companies to reduce an issue definition time and save the handling cost of warranty claims. This paper provides an evaluation framework to validate the economic effect of an early detection system project. For this purpose, we present economical index of a project with explicit formulas such as ROI(return on investment), PP(payback period), NPV(net present value), PI(profitability index) and IRR(internal rate of return) and analyze the sensitivities of the index according to the variation of project input parameters. The proposed analysis framework is expected to be used for evaluating economic values of various system integration projects.

• Journal of Information Technology Applications and Management
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• v.24 no.4
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• pp.153-170
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• 2017

As the digital economy goes global, firms are trying to find suppliers that can address their managerial goals and strategies. The alternatives are not confined to domestic firms. Firms have been trying to connect to foreign partners worldwide. Although offshore outsourcing grants firms various benefits, they present big cultural challenges. However, there is little research on the impact of cultural or country factors on outsourcing. The goal of this paper is to synthesize the outsourcing success literature and develop propositions for outsourcing success in the context of offshore outsourcing. This paper proposes that cultural effects should be included in evaluating the success of offshore outsourcing. Knowledge sharing and the scope of outsourcing are adopted in the base outsourcing success model from previous literature. In the extended model partnership quality is included as a mediator and organizational capability and outsourcing relationship type are also included as moderator. Finally, the integrated framework of offshore outsourcing success includes cultural factors as moderators of the relationships between outsourcing success antecedents and the success of offshore outsourcing. Reasoning for propositions, managerial implications, and future research directions are discussed.

• Journal of KIISE:Software and Applications
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• v.37 no.11
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• pp.812-825
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• 2010

Service-Oriented Computing (SOC) is a reuse paradigm for developing business processes by dynamic service composition. Service consumers subscribe services deployed by service providers only through service interfaces. Therefore, services on server-side are perceived as black box to service consumers. Due to this nature of services, service consumers have limited knowledge on the quality of services. This limits utilizing of services in critical domains hard. Therefore, there is an increasing demand for effective methods for monitoring services. Current monitoring techniques generally depend on specific vendor's middleware without direct access to services due to the technical hardship of monitoring. However, these approaches have limitations including low data comprehensibility and data accuracy. And, this results in a demand for effective service monitoring framework. In this paper, we propose a framework for efficiently monitoring services. We first define requirements for designing monitoring framework. Based on the requirements, we propose architecture for monitoring framework and define generic patterns for efficiently acquiring monitored data from services. We present the detailed design of monitoring framework and its implementation. We finally implement a prototype of the monitor, and present the functionality of the framework as well as the results of experiments to verify efficiency of patterns for transmitting monitoring data.

• Journal of Korea Multimedia Society
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• v.25 no.7
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• pp.903-911
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• 2022

A shrimp quality detection model using YOLOv4 deep learning algorithm is designed, which is superior in terms of network architecture, data processing and feature extraction. The shrimp images were taken and data expanded on their own, the LableImage platform was used for data annotation, and the network model was trained under the Darknet framework. Through comparison, the final performance of the model was all higher than other common target detection models, and its detection accuracy reached 93.7% with an average detection time of 47 ms, indicating that the method can effectively detect the quality of shrimp in the production process.

• Journal of Environmental Policy
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• v.4 no.1
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• pp.93-111
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• 2005

Defining soil quality in scopes and applications is one of the prerequisite for the sustainable management of soil environment to orient researches, strategies and policies. However, definition of soil quality is controversial depending upon a viewpoint of soil science or soil environment. Soil quality can be, irrespective of the disciplines, defined as the capacity of a soil to function within ecosystem boundaries to sustain biological productivity, maintain environmental quality and promote plant and animal health. Common to all of the soil quality concepts can be summarized as the capacity of soil to function effectively at present and in the future. The OECD includes soil quality as one of the agri-environment indicators. This article intends to i) summarize the current soil quality research, and ii) provide information on protocol of soil quality assessment. A framework for soil quality was divided into three steps: indicator selection as minimum data set (MDS), scoring of the selected indicators, and integration of scores into soil quality index. Korean government suggested possible physical and chemical indicators such as bulk density and organic matter for paddy and upland soils to OECD. The framework of soil quality assessment is not yet implemented in Korea. Countries such as USA, Canada and New Zealand have constructed the framework on soil quality assessment and developed a user-friendly version of soil quality assessment tools to evaluate the integrated effects of various soil management practices. The protocol provided in this review might help policymakers, scientists, and administrators improve awareness about soil quality and understand the way of soil environment management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4268-4290
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• 2015

Future mobile communications face enormous challenges as traditional voice services are replaced with increasing mobile multimedia and data services. To address the vast data traffic volume and the requirement of user Quality of Experience (QoE) in the next generation mobile networks, it is imperative to develop efficient content distribution technique, aiming at significantly reducing redundant data transmissions and improving content delivery performance. On the other hand, in recent years cloud computing as a promising new content-centric paradigm is exploited to fulfil the multimedia requirements by provisioning data and computing resources on demand. In this paper, we propose a cooperative caching framework which implements State based Content Distribution (SCD) algorithm for future mobile networks. In our proposed framework, cloud service providers deploy a plurality of cloudlets in the network forming a Distributed Cloud Service Network (DCSN), and pre-allocate content services in local cloudlets to avoid redundant content transmissions. We use content popularity and content state which is determined by content requests, editorial updates and new arrivals to formulate a content distribution optimization model. Data contents are deployed in local cloudlets according to the optimal solution to achieve the lowest average content delivery latency. We use simulation experiments to validate the effectiveness of our proposed framework. Numerical results show that the proposed framework can significantly improve content cache hit rate, reduce content delivery latency and outbound traffic volume in comparison with known existing caching strategies.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.937-944
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• 2006

Although people's anxiety about the environmental problem has been getting higher, they are not provided good quality of knowledge about the environment. Based on this situation, Ecoblog can be a new type of online community to educate the public in ecological knowledge. Especially, Ecoblog can be utilized as a method of "preventive education", and it will contribute to reduce great amounts of environmental budget to restore contaminated environment to previous condition. Ecoblog also utilizes the concept of blog which user can create and append their site with chosen themes. A weblog or a blog is a non-commercial webpage regularly updated through the use of a blogging software which allows the user to "publish" kinds of amalgamations of text and graphics to the page as posts. The technology offered in Ecoblog is utilizing the concept of 4D place and game metaphor in order to provide users the sense of participation, interaction and immersion among them and the growing community. Thus, it requires applying the CAAD technology by implementing semantically well-defined building data model as a core database to create a 4D virtual community. This research focuses on defining a 4d spatial framework suitable for developing an online ecological community. Through our study, the state-of-the-art of online community has been studied at the first step. Second, the scenario of using EcoBlog described with content, visualization and navigation are defined based on the critical features derived at the first step. Finally, a 4d spatial framework composed of semantic building data model, content and rule database is constructed to propose factors that are necessary to establish an ecological virtual community. In conclusion, our framework could enhance the comprehension and interaction between users and virtual buildings in the ecological community by integrating the concept of game design, 4D CAD and semantic data model. Such framework can be applied to any online community for an educational purpose.

• Korean Journal of Artificial Intelligence
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• v.7 no.1
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• pp.1-4
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• 2019

This study to investigate Mobile service quality factors influencing on customer satisfaction and repurchase intention for the research purpose. This study collected data by a survey method for an empirical. A total of 340 replies were used for data analysis. While 340 replies were collected from Chinese users of Mobile e-commerce. Our results support previous researches to results of SPSS analysis all of the 7 hypotheses, 4 hypotheses are adopted and 3 are deleted. After an empirical analysis of this study, the academic implications are as follows. As there have not been many academic studies related to mobile commerce quality, this study can be a meaningful framework when quality factors associated with mobile commerce are being analyzed. This paper as the mobile commerce industry is very sensitive to environmental changes, academic research that can be used to cope with these changes is continuously required. Further studies should be carried out to overcome limitations that have not been analyzed by this study.