• The Korean Journal of Food And Nutrition
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• v.28 no.3
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• pp.358-368
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• 2015

The study is focused on analyzing the SNS using characteristics of the people surveyed, as for the SNS acceptance channel of the food service corporations, accounted voluntarily for 71%. The SNS food service information regarding information of menu, location of store, price, coupon, taste evaluation, event, promotion, reservation and store atmosphere was researched. The most preferred information sharing for SNS food service were researched and found Facebook, blog and others in increasing order. The most preferred media to obtain SNS food service information were smart phone, desktop computer and others. The result of verifying differences in the perceived ease of use were also evaluated according to the food service corporation of SNS using characteristics of the people and was found: the longer period of SNS use, longer was access time: more number of visiting times, higher perceived ease of use. As for the difference in the perceived service value: longer the period of SNS use, more preferred was the blog: the more number of visiting times, the higher perceived service value. As for the difference in the online mouth-to-mouth intention: longer the period of SNS use, longer was access time: the more number of visiting times, the higher online mouth-to-mouth intention. Therefore, these research results provide useful implications in the working-level aspects such as providing basic data and the academic approach of the study, when the food service corporations establish marketing strategies through SNS.

• Journal of Venture Innovation
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• v.7 no.3
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• pp.101-121
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• 2024

The application of chatbots on e-commerce platforms is becoming increasingly widespread. With the rapid development of artificial intelligence technology, previous research has predominantly focused on service failures occurring with the chatbots themselves. There is limited research on scenarios where chatbots handle service failures that are controllable by the sellers. This paper conducted online surveys through two experiments involving a total of 546 participants. The results indicate that, in the event of a service failure, customers are more likely to spread negative word-of-mouth about the store and have lower repurchase intentions when served by chatbots compared to human customer service representatives. This is because customers experience higher levels of anger with the chatbots. However, when customers perceive the service failure as uncontrollable by the seller, the impact of the type of customer service provider on negative word-of-mouth via customer anger is weakened while when customers perceive it as controllable the impact is strengthened. This study provides theoretical contributions for online retail enterprises to apply intelligent customer service while preventing further deterioration of service failures.

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.71-76
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• 2017

It is necessary to develop a service that meets various environmental requirements so that the Internet of things can be applied to the fourth industry in overall. This paper presents a method for extracting IoT devices information to change the current provider centric service provision environment in order to construct a user centered service provision environment for Web services. Also, it provides users to utilize the appropriate web services through taking advantage of IoT devices information. The existing service provision environment is focused on the method of selecting the service using the provider service information, thus, it is considered necessary for a user-oriented service search method to be in need. In this study, the service list is provided to the user by combining provider information and information extracted from IoT Devices. IoT information collection generates information by separating context information such as information between IoT devices and users and event information between devices through identifiers. In this paper, we propose a development of a user centric service environment by presenting users with a necessary service list through the proposed IoT information.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.177-186
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• 2011

Mobile services which are applied PC performance and mobile characteristics are increased with spread of the smartphone. Recently, mobile cloud service is getting the spotlight as a solution of mobile service problems that mobile device is lack of memory, computing power and storage and mobile services are subordinate to a particular mobile device platform. However, mobile cloud service has more potential security threats by the threat inheritance of mobile service, wireless network and cloud computing service. Therefore, security threats of mobile cloud service has to be removed in order to deploy secure mobile cloud services and user and manager should be able to respond appropriately in the event of threat. In this paper, We define mobile cloud service threats by threat analysis of mobile device, wireless network and cloud computing and we propose mobile cloud service countermeasures in order to respond mobile cloud service threats and threat scenarios in order to respond and predict to potential mobile cloud service threats.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.10
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• pp.447-454
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• 2015

This paper proposes geographical name denoising by machine learning of event detection based on twitter. Recently, the increasing number of smart phone users are leading the growing user of SNS. Especially, the functions of short message (less than 140 words) and follow service make twitter has the power of conveying and diffusing the information more quickly. These characteristics and mobile optimised feature make twitter has fast information conveying speed, which can play a role of conveying disasters or events. Related research used the individuals of twitter user as the sensor of event detection to detect events that occur in reality. This research employed geographical name as the keyword by using the characteristic that an event occurs in a specific place. However, it ignored the denoising of relationship between geographical name and homograph, it became an important factor to lower the accuracy of event detection. In this paper, we used removing and forecasting, these two method to applied denoising technique. First after processing the filtering step by using noise related database building, we have determined the existence of geographical name by using the Naive Bayesian classification. Finally by using the experimental data, we earned the probability value of machine learning. On the basis of forecast technique which is proposed in this paper, the reliability of the need for denoising technique has turned out to be 89.6%.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.2
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• pp.79-83
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• 2009

Streaming Technology can support the real-time playback without downloading and storing multimedia data in local HDD. So, client browser or plug-in can represent multimedia data before the end of file transmission using streaming technology. Recently, the demand for efficient real-time playback and transmission of large amounts of multimedia data is growing rapidly. But most users' connections over network are not fast and stable enough to download large chunks of multimedia data. In this paper, we propose an intelligent IP streaming system based on personalized media service. The proposed IP streaming system enables users to get an intelligent recommendation of multimedia contents based on the user preference information stored on the streaming server or the home media server. The supposed intelligent IP streaming system consists of Server Metadata Agent, Pumping Server, Contents Storage Server, Client Metadata Agent and Streaming Player. And in order to implement the personalized media service, the user information, user preference information and client device information are managed under database concept. Moreover, users are assured of seamless access of streamed content event if they switch to another client device by implementing streaming system based on user identification and device information. We evaluate our approach with manufacturing home server system and simulation results.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.4
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• pp.117-124
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• 2015

RAM (Reliability, Availability and Maintenance) has been applied to design and analysis tools which affects system's operational sustainability and its life cycle cost as RAM-c(2009 DoD). RAM-c plays also an important role to guarantee the system engineering for mission assurance. Reliability is highly related to the probability of system failure. Availability means mission capability or the condition of ready to mission. Maintenance includes both the repair to recover the system in the event of failure/unexpected breakdown and proactive maintenance to prolong the design service life of the system or machinery. It is the purpose that this paper is to analyze and conclude the objective service life of UAV. The more UAV is operated, the less the level of its reliability becomes. Repairing failures and supplying spare parts on time, system reliability could be improved up until the time over target. Applying statistical Weibull distributions, this paper suggests the analysis of the design service life and economic life of UAV based on RAM-c with operational data.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.619-622
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• 2004

For recent years, hacking is in the trends of making excessive traffic unnecessarily to obstruct the service by getting a system's performance down. And we can also see systems paralyzed in service ability due to the flash crowds of normal traffic to a popular website. This is an important problem certainly solved in the point of QoS guarantee for the clients. It is known that the former is DDoS(Distributed Denial of Service) attack and the latter is FE(Flash Event). These two are samely anomalous traffic because these make excessive congestion on the network or system and downgrade the system's service ability. In this paper, we propose a scheme for protecting the system against anomalous traffic and for guaranteeing the QoS. For this, a server records and maintains the information of clients accessed more than one time before when it is in normal condition. When it falls into the congestion, the records are used for filtering the spoofed IP. We send and receive the ICMP request/reply packet to know whether the IP is spoofed. And we also propose for applying the object spliting of CDN to guarantee the QoS in the initial FE situation.

• Journal of Digital Convergence
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• v.10 no.7
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• pp.179-184
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• 2012

The ultimate purpose of cities is 'the enhancement of quality of life in city'. In order to achieve this, it is required to optimize the Ontology-driven ubiquitous services included in the U-City and UIS of regions and communities and so on. Almost U-Service's contents are related to spatial or temporal extent. So it is important to design Spatio-temporal event schema for efficient access to U-City. There is a rapid change into an urban society in the shape of Ontology-driven ubiquitous services in which a content on a region or an incident is newly reconstructed through various ideas with the influence of the ubiquitous environment.

• Journal of the Korean Society of Safety
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• v.38 no.1
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• pp.87-92
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• 2023

The number of unmanned light rail train operators is continuously increasing in Korea. In a failure event during an operation due to the nature of the unmanned operation, recovery is performed based on the remote control. However, if remote recovery is not feasible, safety personnel arrive at the train to resume the train operation. There are regulations on safety personnel and the suspension time of the train operation. However, there is currently no rule for safety personnel deployment. Currently, railway operating organizations operate in three scenarios: safety personnel on board trains, stationed at stations, and deployed at major stations. Four major factors influence the downtime for each emergency response scenario. However, these four influencing factors vary too much to predict results with simple calculations. In this study, four influencing factors were considered as random variables with high uncertainty. In addition, the Monte Carlo method was applied to each scenario for the safety personnel deployment to predict train service downtime. This study found a 17% difference in train service suspension by safety personnel deployment scenario. The results of this study can be used in setting service goals, such as standards for future safety personnel placement and frequency of service interruptions.