• International Journal of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.19-24
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• 2018

Recently, people can create small content by themselves and it improved into a form that can be promoted. Also, as active small business owners increase, they produce the content for promotion by themselves without external professional help and they utilize it. This paper studies the method to make Mobile Apps, Mobile Web and homepage services available by automatically generating the mobile based mini content. The automated content creation system suggests the method that small business owners and groups can easily communicate with new people by bringing Single Page Application, hybrid mobile web app, N-Screen based content building, private cloud-based PaaS building technology, P2P network based file sharing and multimedia thread technologies together and creating the content.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1091-1110
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• 2016

Hybrid deployment under current cloud data centers is a combination of online and offline services, which improves the utilization of the cluster resources. However, the performance of the cluster is often affected by the online services in the hybrid deployment environment. To improve the response time of online service (e.g. search engine), an effective scheduling algorithm based on Storm is proposed. At the component level, the algorithm dispatches the component with more influence to the optimal performance node. Inside the component, a reasonable resource allocation strategy is used. By searching the compressed index first and then filtering the complete index, the execution speed of the component is improved with similar accuracy. Experiments show that our algorithm can guarantee search accuracy of 95.94%, while increasing the response speed by 68.03%.

• Journal of the Korean Ceramic Society
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• v.49 no.1
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• pp.48-55
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• 2012

Degradation of performance and life time of a functional material or device thereof is induced, to a great extent, by mass transfer in the material that is driven by various thermodynamic forces imposed intentionally or accidentally during its operation or service. The forces are any gradient of intensive thermodynamic variables, component chemical potentials, electrical potential, temperature, stresses, and the like. This paper reviews electric-field induced degradation phenomena in ionic solid compounds including insulation resistance degradation, crystal shift, microstructural alterations, compositional unmixing, and compound decomposition. Their inner workings are also discussed qualitatively.

• Proceedings of the Safety Management and Science Conference
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• 2010.04a
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• pp.393-400
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• 2010

현재까지 USN(Ubiquitous Sensor Network)이라 통칭되어지는 센서망은 불특정 공간에 배포된 무선방식의 센서노드를 통해 유선방식의 센서 인프라를 대체하려는 기술 지향적 및 공급자중심의 구성을 가지고 있다. 본 논문은 기존의 공급자 위주의 기술지향적인 제한적 구성에서 벗어나, u-City에서 제공하고자 하는 서비스들의 목적과 서비스 대상의 요구사항분석을 기반으로 성능, 품질, 비용 등을 고려하도록 다양한 기술들을 융 복합하여 서비스를 제공하는 하이브리드 센서망의 제안을 위한 선행 연구 결과이다. 우선, 센서망과 u-City 서비스와의 관계에 대해 서술한 후, 기존 센서망에 대한 조사, 분석 결과 및 문제점, 그리고 선진국에서의 하이브리드 센서망 적용 사례와 시사점에 대해 논의하도록 한다.

• Proceedings of the Safety Management and Science Conference
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• 2010.04a
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• pp.167-172
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• 2010

EPCIS(EPC Information Service)시스템은 EPC기반의 정보교환을 목표로 EPC global Network 상에서 RFID 태그에 기록된 화물의 EPC데이터, 인식시점, 인식장소 등의 정보를 제공하는 EPCglobal Architecture Framework의 구성요소 중 핵심부분이라고 할 수 있다. 본 논문에서는 EPCIS 시스템의 구성요소 중 동시에 수많은 RFID 단말기로부터 입력되는 대용량의 EPCIS Event 데이터를 지속적으로 저장하고 관리하는 EPCIS Repository를 효율적으로 관리하기 위하여 고성능이 필요한 데이터와 대용량이 필요한 데이터를 모두 처리할 수 있는 Hybrid DBMS를 적용하여 EPCIS Repository를 효율적으로 관리할 수 있는 방안을 제시하고자 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.381-385
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• 2004

In this paper, We consider various service models and mechanisms as a part of study for offering QoS with the requirement of user and discuss genetic algorithm and hybrid genetic algorithm for routing optimization in broa㏈and convergence network. If routing optimization based on OSPF is not sufficient, a number of MPLS paths can be set up to further improve QoS. We propose two mixed-integer programming models for the complementary MPLS problem, and consider the maximum link utilization within the network as the relevant network QoS measure

• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.31-40
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• 2022

Coronary heart disease (CHD) is a comorbidity of COVID-19; therefore, routine early diagnosis is crucial. A large number of examination attributes in the context of diagnosing CHD is a distinct obstacle during the pandemic when the number of health service users is significant. The development of a precise machine learning model for diagnosis with a minimum number of examination attributes can allow examinations and healthcare actions to be undertaken quickly. This study proposes a CHD diagnosis model based on feature selection, data balancing, and ensemble-based classification methods. In the feature selection stage, a hybrid SVM-GA combined with fast correlation-based filter (FCBF) is used. The proposed system achieved an accuracy of 94.60% and area under the curve (AUC) of 97.5% when tested on the z-Alizadeh Sani dataset and used only 8 of 54 inspection attributes. In terms of performance, the proposed model can be placed in the very good category.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• Journal of the Korean earth science society
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• v.29 no.4
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• pp.352-362
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• 2008

This study explored pre-service teachers' mental models about eclipse phenomena to investigate their understandings on the earth science concept needed f3r an integrated approach. We conducted in-depth interviews with two different contexts on 30 secondary and 36 primary pre-service teachers participants, and analyzed phenomenological primitives (p-prims) and facets of causal explanations about eclipses. Based on this study, we identified four different levels of mental models about eclipses. Four mental models were categorized as (1) Screening model, (2) Orbital plane model, (3) Hybrid model, and (4) Shadow cast model. Screening model is a flawed mental model, orbital plane model is an incomplete correct mental model, and shadow cast model is a scientifically correct mental model. Hybrid model, composite of two or more mental models, use multiple mental models simultaneously. Orbital plane model was the most widespread mental model in secondary pre-service teachers group, whereas screening model was used frequently in primary group. It was found that the level of mental model could be determined by the level of facet and p-prims. We confirmed context sensitivity of the mental models and perceived the necessity of integrated approaches to promote progression of mental models. Implications of our findings for enhancing pre-service science teachers' topic-specific pedagogical content knowledge (PCK) associated with eclipse phenomena are also discussed here.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.1
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• pp.49-58
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• 2011

Recently, GIS(Geographic Information System) has been developed to personalized service for providing the specialized services that is aimed to personal user based on mobile communication. The existing GIS system provides comprehensive and simple information but GIS System for personalized service must provide the adjustive information through the personal interest profile based on POI(PoInt of Interest). This paper describes the intelligent retrieval geographical information service module for providing personal oriented geographic information service. Our proposal model consists of user preference profile, acquisition of POI through hybrid network (Wireless LAN, CDMA), service platform and implementation of prototype system. Implementation model can apply to the life information service like restaurant, oil station, convenient store and etc.