• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.97-106
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• 2023

Sentiment analysis using social network platforms such as Twitter has achieved tremendous results. Twitter is an online social networking site that contains a rich amount of data. The platform is known as an information channel corresponding to different sites and categories. Tweets are most often publicly accessible with very few limitations and security options available. Twitter also has powerful tools to enhance the utility of Twitter and a powerful search system to make publicly accessible the recently posted tweets by keyword. As popular social media, Twitter has the potential for interconnectivity of information, reviews, updates, and all of which is important to engage the targeted population. In this work, numerous methods that perform a classification of tweet sentiment in Twitter is discussed. There has been a lot of work in the field of sentiment analysis of Twitter data. This study provides a comprehensive analysis of the most standard and widely applicable techniques for opinion mining that are based on machine learning and lexicon-based along with their metrics. The proposed work is helpful to analyze the information in the tweets where opinions are highly unstructured, heterogeneous, and polarized positive, negative or neutral. In order to validate the performance of the proposed framework, an extensive series of experiments has been performed on the real world twitter dataset that alter to show the effectiveness of the proposed framework. This research effort also highlighted the recent challenges in the field of sentiment analysis along with the future scope of the proposed work.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1324-1327
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• 2009

Social infrastructure is the basis of public welfare and should be recognized and managed as important assets. Bridge is one of the most important infrastructures to be managed systematically because the impact of the failure is critical. It is essential to monitor the performance of bridges in order to manage them as an asset. But current analytical methods such as predictive modeling and structural analysis are very complicated and difficult to use in practice. To apply these methods, structural and material condition data collection should be performed in each element of bridge. But it is difficult to collect these detailed data in large numbers and various kinds of bridges. Therefore, it is necessary to collect data of major measurement items and predict the life of bridges roughly with advanced information technologies. When certain measurement items reach predefined limits in the monitoring bridges, precise performance measurement will be done by detailed site measurement. This paper describes the selection of major measurement items that can represent the tendency of bridge life and introduces automated bridge data collection test-bed using wireless sensor network technology. The following will be major parts of this paper: 1) Examining the features of conventional bridge management system and data collection method 2) Mileage concept as a bridge life indicator and measuring method of the indicator 3) Test-bed of automated and real-time based bridge life indicator monitoring system using wireless sensor network

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1795-1816
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• 2024

A Software-Defined Wireless Sensor Networks (SDWSNs) architecture is firstly proposed to address the issues of inflexible architecture strategies and low scalability of traditional WSNs in this article. The SDWSNs architecture involves the design of a software-defined sensor network model and a customized controller architecture, along with an analysis of the functionalities of each management module within the controller architecture. Secondly, to tackle limited energy problem of sensor nodes, a network coding opportunistic routing method (SDN-COR) is presented based on SDWSNs. This method incorporates considerations of coding opportunities, vertical distance, and remaining energy of nodes to design a metric for encoding opportunistic routing. By combining opportunistic forwarding mechanisms, candidate forwarding sets are selected and sorted based on priority to prioritize data transmission by higher-priority nodes. Simulation results indicate that, comparing with conventional methods, this approach achieves reduction in energy consumption by an average of 21.5%, improves network throughput by 24%, and extends network lifetime by 20%.

• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.21-29
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• 2020

The Topic Modeling research, the methodology for deduction keyword within literature, has become active with the explosion of data from digital society transition. The research objective is to investigate research trends in D.N.A.(Data, Network, Artificial Intelligence) field using DTM(Dynamic Topic Model). DTM model was applied to the 1,519 of research projects with SW·A.I technology classifications among ICT(Information and Communication Technology) field projects between 6 years(2015~2020). As a result, technology keyword for D.N.A. field; Big data, Cloud, Artificial Intelligence, extended keyword; Unstructured, Edge Computing, Learning, Recognition was appeared every year, and accordingly that the above technology is being researched inclusively from other projects can be inferred. Finally, it is expected that the result from this paper become useful for future policy·R&D planning and corporation's technology·marketing strategy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1081-1094
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• 2016

KREONET is a principal national R&E network running by KISTI in Korea. It uniquely provides production research network services for around 200 non-profit research and educational organizations, based on hybrid (IP and non-IP) network infrastructure. However, KREONET is limited to meet various needs of new network services for advanced Science & Technology (S&T) users because its infrastructure is inherently derived form classical hardware-based, fixed and closed environments. So, KREONET-S is designed to provide advanced S&T services to catch up with time-to-research and time-to-collaboration. In this paper, we present a system architecture of KREONET-S based on network infrastructure that consists of data and control planes separately. Furthermore, we propose and describe VDN service which is capable of building a virtual dedicate & bandwidth-guaranteed network for S&T group dynamically. we implement VDN application on KREONET-S and then perform performance analysis for proving that KREONET-S system and VDN application can be a good solutions to cope with new network paradigms for various advanced S&T applications and users.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2771-2778
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• 2014

In this paper, we propose an algorithm that select efficient relay nodes using information of network environment and nodes. The proposed algorithm can be used changeable weight factors as following network environment in node density. The routing protocols adopting store-carry-forward method are used for solving network problems occurred by unstable end-to-end connection in Delay Tolerant Networks(DTNs). Exiting DTN routing algorithms have problems that large latency and overhead because of deficiency of network informations. The proposed algorithm could be provide a solution this problems using changeable weight factor and prediction of network environment. Thus, selected relay nodes work efficiently in unstable and stressed network environment. Simulation results show that enhancement performance as overhead, delivery ratio, average latency compared to exiting DTN routing algorithm.

• Corrosion Science and Technology
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• v.12 no.2
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• pp.79-84
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• 2013

In general, pipelines at nuclear power plants are affected by various types of degradation mechanisms and may be ruptured after gradually thinning. FAC (Flow-Accelerated Corrosion) is typical aging mechanism affecting the secondary side piping system. In Korea nuclear power plants, CHECWORKS program have been used for management of wall thinning damages. However, sometimes, CHECWORKS program shows wrong results at the stage of NFA (Network Flow Analysis) in case of complex pipelines. This paper describes the calculation results of pressure drop in a complex pipeline and single line by using the CHECWORKS program and the analysis results are compared with those of engineering calculation results including errors between them.

• Journal of Advanced Marine Engineering and Technology
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• v.22 no.1
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• pp.77-84
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• 1998

Based on experimental analysis, the characteristics of pulsating pressure wave propagation is clarified by testing of 4-stroke gasoline engine. The pulsating pressure wave in exhaust system is generated by pulsating gas flow due to working of exhaust valve. The pulsating pressure wave is closely concerned to the loss of engine power according to back pressure and exhaust noise. It is difficult to exactly calculate pulsating pressure wave propagation in exhaust system because of nonlinear effect. Therefore, in the first step for solving these problems, this paper contains experimental model and analysis method which are applied two-port network analysis. Also, it shows coherence function, frequency response function, back pressure, and gradient of temperature in exhaust system.

• Journal of Information Technology Services
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• v.15 no.1
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• pp.97-111
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• 2016

In the creative economy paradigm, motivation of the opportunity based startup is a continuous concern to policy-makers. Recently, bigdata anlalytics challenge traditional methods by providing efficient ways to identify social trend and hidden issues in the public sector. In this study the authors introduce a case study using social bigdata analytics for conducting policy analysis. A semantic network analysis was employed using textual data from social media including online news, blog, and private bulletin board which create buzz on the startup business. Results indicates that each media has been forming different discourses regarding government's policy on the startup business. Furthermore, semantic network structures from private bulletin board reveal unexpected social burden that hiders opening a startup, which has not been found in the traditional survey nor experts interview. Based on these results, the authors found the feasibility of using social bigdata analysis for policy-making. Methodological and practical implications are discussed.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.11 no.6
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• pp.799-807
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• 1999

Exergy analysis is widely used in energy system analysis for more efficient energy use. Pinch technology has focused on chemical plants, such as pure heat exchanger networks. In this study, the objective is to seek more effective means with integrating above two methods. In order to demonstrate effective result and to prove possibility for pinch analysis, the steam turbine is adopted to make heat recovery in the heat exchanger network. Three cases are introduced using the integration of exergy and pinch analysis. The standard steam turbine utility is the base case, and adding the heat pump to this system is the second case. The third case is the system with the heat pump and minimum utilities. The results show that the output power of steam turbine in the case(2) and case(3) are increased up to 42% and 46%, respectively, compared with that of base case.