• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1276-1295
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• 2023

Sensor networks are now an essential aspect of wireless communication, especially with the introduction of new gadgets and protocols. Their ability to be deployed anywhere, especially where human presence is undesirable, makes them perfect choices for remote observation and control. Despite their vast range of applications from home to hostile territory monitoring, limited battery power remains a limiting factor in their efficacy. To analyze and transmit data, it requires intelligent use of available battery power. Several studies have established effective routing algorithms based on clustering. However, choosing optimal cluster heads and similarity measures for clustering significantly increases computing time and cost. This work proposes and implements a simple two-phase technique of route creation and maintenance to ensure route reliability by employing nature-inspired ant colony optimization followed by the fuzzy decision engine (FDE). Benchmark methods such as PSO, ACO and GWO are compared with the proposed HRCM's performance. The objective has been focused towards establishing the superiority of proposed work amongst existing optimization methods in a standalone configuration. An average of 15% improvement in energy consumption followed by 12% improvement in latency reduction is observed in proposed hybrid model over standalone optimization methods.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.540-543
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• 2015

Solar energy is one of the most important alternative energy sources which have been shown to meet high levels of heating and cooling demands in buildings. However, the efficiencies to satisfy these demands using solar energy significantly vary based on the characteristics of individual building. Therefore, this paper is focused on developing the methodology which can help to design optimal solar system for heating and cooling to be in cooperated within the existing buildings according to their load profiles. This research has established the Solar Heating and Cooling (SHC) system which is composed of collectors, absorption chiller, boiler and heat storage tank. Each component of SHC system is analyzed and made by means of Modelica Language and Pistache tool is verified the results. Sequential approximate optimization (SAO) and meta-models determined to 15 design parameters to optimize SHC system. Finally, total coefficient of performance (COP) of the entire SHC system is improved approximately 7.3% points compared to total COP of the base model of the SHC system.

• Educational Technology International
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• v.10 no.2
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• pp.127-143
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• 2009

The purpose of this study was to identify the interaction patterns in distance only mode e-Learning. In order to investigate this study, messages shown in the electronic notice board were analyzed to see how interaction occurs between teacher and learner or learner and learner under the e-learning of cyber university. To analyze messages was applied according to the framework by Henri's contents analysis model. As a result of contents analysis on electronic board, the participative dimension was 399 messages. A learner put on 7~8 messages a day. The number of messages was low compared to the number of learners, but the number of inquiries was about 140. That means that each learner contacts and checks messages at least once a day. The meaning dimension was 600 units. The main interaction patterns were Interactive-social-cognitive-metacognitive. This means that e-Learning in distance only mode leads a positive attitude of learners as a self-directed learning, and needs teacher's well-structured instructional strategies for increasing interaction. In conclusion, social dimension and interactive dimension of messages support learners psychologically in the process of learning though they directly guide learning under the circumstances of e-learning lacking face-to-face element. It can be interpreted that the teacher's role is significantly important in order to attract learners' positive participation and cognitive and meta-cognitive dimension of messages and activities

• Asia pacific journal of information systems
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• v.32 no.2
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• pp.327-353
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• 2022

With the development of technology and media and the pursuit of non-face-to-face due to the corona pandemic, the influence of live commerce, a real-time streaming shopping channel, is growing. Starting from China, the popularity of live commerce is growing all over the world, and it has become an interesting topic among many practitioners and researchers. However, compared to its popularity, there are few studies on live commerce. Therefore, we build a theoretical model in terms of IT affordance such as visibility, guidance shopping, trading, and meta-voicing and investigate how live commerce affects engagement with customers. We empirically measure 428 individuals who have used live commerce using survey data. In addition, we conduct four types of scenario experiments on whether social cues on exposures of other consumers, influence customer engagement. Our results show that trading affordance has the most significant effect. This shows that the live commerce platform may want to devise a program that helps make payment easier for users who prefer a quick and simple process. Our study contributes to the literature by presenting the importance of IT affordance for live commerce.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.89-104
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• 2024

Cloud-based e-learning (CBEL) represents a promising technological frontier. Existing literature has presented a diverse array of findings regarding the determinants that influence the adoption of CBEL. The primary objective of this study is to conduct an exhaustive examination of the available literature, aiming to determine the key predictors of CBEL utilization by employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. A comprehensive review of 35 articles was undertaken, shedding light on the status of CBEL as an evolving field. Notably, there has been a discernible downturn in related research output during the COVID-19 pandemic, underscoring the temporal dynamics of this subject. It is noteworthy that a significant portion of this research has emanated from the Asian continent. Furthermore, the dominance of the technology acceptance model (TAM) in research frameworks is affirmed by our findings. Through a rigorous thematic analysis, our study identified five overarching themes, each encompassing a diverse range of sub-themes. These themes encompass 1) technological factors, 2) individual factors, 3) organizational factors, 4) environmental factors, and 5) security factors. This categorization provides a structured framework for understanding the multifaceted nature of CBEL adoption determinants. Our study serves as a compass, guiding future research endeavours in this domain. It underscores the imperative for further investigations utilizing diverse theoretical frameworks, contextual settings, research methodologies, and variables. This call for diversity and expansion in research efforts reflects the dynamic nature of CBEL and the evolving landscape of e-learning technologies.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.635-645
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• 2007

Component technology has been widely accepted as an effective way for building software systems with reusable components, and Microsoft (MS) .NET is one of the recent representative component technologies. Model Driven Architecture (MDA) is a new development paradigm which generates software by transforming design models automatically and incrementally. Transformation of structural models in MDA has been successfully applied. However, transformation of dynamic models and pervasive services, such as transaction service, security service, synchronization service and object pooling are largely remains as an area for further research. The recent enterprise system has multi tier distributed architecture, and the functionality of early mentioned pervasive services is essential for this architecture. .NET platform can implement Component Object Model+ (COM+) component for supporting pervasive services by specify Attribute code. In this paper, we specify the functionalities of the COM+ component offering pervasive services, and then those functionalities are defined by UML profile. By using the profile, the Platform Specific Model (PSM) for .NET/C# is specified, and .NET components are automatically generated through our tool. The development productivity, extensibility, portability, and maintenance of software can be dramatically improved by using of the proposed methods.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.857-862
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• 2005

MND(Ministry of National Defense) has developed MND AF(Ministry of National Defense Architecture Framework) and CADM(Core Architecture Data Model to guarantee interoperability among defense information systems. But, it is very difficult to manage architecture product documented through MND AF and CADM. So, there Is necessity for development of modeling tool and repository system which can develop architecture products and manage architecture product informations in common repository In this paper, we developed architecture product management system which supports development and management of meta model and architecture product of MND AF and CADM. Through architecture product management system architect of each agency can construct architecture product in a more effective and efficient way with modeling method and a user can search and refer useful architecture product informations using query function. Also, architecture product management system provides the basis for system integration and interoperability with integration, analysis and comparison of architecture product.

• Journal of Korea Multimedia Society
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• v.2 no.3
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• pp.231-242
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• 1999

Generally, either caption-based search method or content-based search methods is used to retrieve video information. However, each search method has its limitations. Caption-based search is apt to lose consistency as for user's subjects, and content-based search is hard to extract general means. To enhance efficiency and correctness as for complementing each other, we propose the Integrated Video Data Model(IVDM) which integrates the two search methods, to device the model, we analyze video data and construct the structure of video information hierarchically. IVDM supports caption-based search as assigning meta-data by analyzing thematic-unit in the higher level, and also supports content-based search as extracting feature data by analyzing the content of video data in the lower level. We design Object-Oriented database schema of news video, based-on the IVDM. And we provide 4-type of queries and query processing algorithm to retrieve news video information.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.4697-4706
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• 2010

This paper suggested the optimal operating design method using simulation and ANP(Analytic Network Process) for mass-customization in the automotive component manufacturing industry. For this, first of all, we built the simulation model including various and complex factors in the field, and estimated the meta-model by RSM(Response Surface Method). Secondly using ANP, we calculated the weight of relative importance of evaluation factors gathered from decision makers. And then, we proposed the optimal operation designs by MOGA(Multi-Objective Genetic Algorithm), analyzed results of them. Moreover, by comparing the results with the consequences using AHP(Analytic Hierarchy Process), we showed its superiority of suggested method to the manner using AHP, because it reflects inner, outer dependency, and inter-relation among judgement factors. In conclusion, through this process, we can present the better way to serve mover effective, precise, and accurate information to decision makers when they build operation design for mass-customization system as automotive parts production system.

• The Journal of the Korea Contents Association
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• v.16 no.2
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• pp.374-386
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• 2016

Provenance means the meta data that represents the history or lineage of a data in collaboration storage environments. Therefore, as provenance has been accruing over time, it takes several ten times as large as the original data. The schemes for effciently compressing huge amounts of provenance are required. In this paper, we propose a provenance compression scheme considering the RDF graph patterns. The proposed scheme represents provenance based on a standard PROV model and encodes provenance in numeric data through the text encoding. We compress provenance and RDF data using the graph patterns. Unlike conventional provenance compression techniques, we compress provenance by considering RDF documents on the semantic web. In order to show the superiority of the proposed scheme, we compare it with the existing scheme in terms of compression ratio and the processing time.