• Korea Science and Art Forum
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• v.20
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• pp.135-146
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• 2015

The purpose of this research is to highlight the importance of customer experience relating to servitization of manufacturing and to develop an index to analyze customer experience management. It occurred that customer experience management analysis should perform in diverse dimensions to get higher customer satisfaction. Following to this idea, new idex is designed : CEMC(Customer Experience Management Competency scale). CEMC includes three parties which are internal expert, external expert and customer, as evaluators of the appraisal. Each evaluator participates in the inspection about customer experience management through a questionnaire which composed four sections : Product and service, Business process, Culture and Asset. Researchers apply this index to one small manufacturing business and analyze the state of customer experience management. The result would be a reference for building strategy and align inside organization.

• Journal of Information Technology Applications and Management
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• v.30 no.4
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• pp.11-28
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• 2023

This paper proposes a method of integrating ChatGPT with traditional chatbot systems to enhance conversational artificial intelligence(AI) and create more efficient conversational systems. Traditional chatbot systems are primarily based on classification models and are limited to intent classification and simple response generation. In contrast, ChatGPT is a state-of-the-art AI technology for natural language generation, which can generate more natural and fluent conversations. In this paper, we analyze the business service areas that can be integrated with ChatGPT and traditional chatbots, and present methods for conducting conversational scenarios through case studies of service types. Additionally, we suggest ways to integrate ChatGPT with traditional chatbot systems for intent recognition, conversation flow control, and response generation. We provide a practical implementation example of how to integrate ChatGPT with traditional chatbots, making it easier to understand and build integration methods and actively utilize ChatGPT with existing chatbots.

• The Transactions of the Korea Information Processing Society
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• v.7 no.1
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• pp.146-155
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• 2000

This paper describes a 4-state bar code called HANGUL 4 ST that has been specifically designed for automatic processing of the letter mails, A HANGUL 4 ST bar code is a necessary data base that is applied data capture and data carrier with it all the information necessary for sorting, the amount capture for transportation of mail items, and valued-added services such as indicia, tracking and trace. The 4-state bar code information contents are composed of a postal code, delivery point, customer information including customer identification number and name, and parity bits for error detect and correct. The data density capability of HANGUL 4 St allows all useful sorting data and customer data to be encoded on one label. This supports better automatic processing in mail items, higher level of customer service and more efficient operation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.10
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• pp.2014-2027
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• 1994

A queueing model with two input streams of different service priorities is studied. Specifically, IBP+BP/D/1 with head-of-line priority is analyzed. IBP and BP stand for Interrupted Bernoulli Process and Bernoulli Process respectively. The BP-stream customers have the higher service priority over the IBP-stream customers. An exact analysis of this priority queue is presented to derive the distributions of the state of the system at steady state, the waiting time distributions for each class of customers, and the interdeparture time distributions. The numerical results of the analysis are presented to show how the various parameters of the low and high priority arrival processes affect the performance of the system.

• Journal of KIISE:Software and Applications
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• v.36 no.8
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• pp.673-682
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• 2009

Recently, photo sharing and publishing based Social Network Sites(SNSs) are increasingly attracting the attention of academic and industry researches. Unlike the face recognition environment addressed by existing works, face annotation problem under SNSs is differentiated in terms of daily updated images database, a limited number of training set and millions of users. Thus, conventional approach may not deal with these problems. In this paper, we proposed a face annotation method for sharing and publishing photographs that contain faces under a social network service using random projection, non-linear regression and representational state transfer. Our experiments on several databases show that the proposed method records an almost constant execution time with comparable accuracy of the PCA-SVM classifier.

• Structural Engineering and Mechanics
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• v.49 no.2
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• pp.203-223
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• 2014

The extensive use of prestressed reinforced concrete (PSC) highway bridges in marine environment drastically increases the sensitivity to both fatigue-and corrosion-induced damage of their critical structural components during their service lives. Within this scenario, an integrated method that is capable of evaluating the fatigue reliability, identifying a condition-based maintenance, and predicting the remaining service life of its critical components is therefore needed. To accomplish this goal, a procedure for fatigue reliability prediction of PSC highway bridges is proposed in the present study. Vehicle-bridge coupling vibration analysis is performed for obtaining the equivalent moment ranges of critical section of bridges under typical fatigue truck models. Three-dimensional nonlinear mathematical models of fatigue trucks are simplified as an eleven-degree-of-freedom system. Road surface roughness is simulated as zero-mean stationary Gaussian random processes using the trigonometric series method. The time-dependent stress-concentration factors of reinforcing bars and prestressing tendons are accounted for more accurate stress ranges determination. The limit state functions are constructed according to the Miner's linear damage rule, the time-dependent S-N curves of prestressing tendons and the site-specific stress cycle prediction. The effectiveness of the methodology framework is demonstrated to a T-type simple supported multi-girder bridge for fatigue reliability evaluation.

• Journal of the Korean Society for information Management
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• v.29 no.4
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• pp.165-189
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• 2012

This study investigated the current state of online subject guides in Korean academic libraries and suggests improvement. Through the examination of 100 academic libraries' Web sites, only 14 online subject guides were identified, showing that the development of online subjects guides in Korea is still in infancy. The examined online subject guides were evaluated as high quality in terms of accessibility, integration of information resources, and format consistency, but low quality in the provision of specialized subjects, user instruction, and information retrieval systems. An online subject guide should be a one-stop service that provides fast access to information resources along with subject-specialized user instruction and effective communication with librarians.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3865-3883
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• 2016

Infrastructure as a Service (IaaS) encapsulates computer hardware into a large amount of virtual and manageable instances mainly in the form of virtual machine (VM), and provides rental service for users. Currently, VM anomaly incidents occasionally occur, which leads to performance issues and even downtime. This paper aims at detecting anomalous VMs based on performance metrics data of VMs. Due to the dynamic nature and increasing scale of IaaS, detecting anomalous VMs from voluminous correlated and non-Gaussian monitored performance data is a challenging task. This paper designs an anomaly detection framework to solve this challenge. First, it collects 53 performance metrics to reflect the running state of each VM. The collected performance metrics are testified not to follow the Gaussian distribution. Then, it employs independent components analysis (ICA) instead of principal component analysis (PCA) to extract independent components from collected non-Gaussian performance metric data. For anomaly detection, it employs multi-class Bayesian classification to determine the current state of each VM. To evaluate the performance of the designed detection framework, four types of anomalies are separately or jointly injected into randomly selected VMs in a campus-wide testbed. The experimental results show that ICA-based detection mechanism outperforms PCA-based and LDA-based detection mechanisms in terms of sensitivity and specificity.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.377-384
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• 2005

The purpose of this research is to develop and evaluate a traffic engineering architecture that uses local state information. This architecture is applied to an Internet protocol radio access network (RAN) that uses multi-protocol label switching (MPLS) and differentiated services to support mobile hosts. We assume mobility support is provided by a protocol such as the hierarchical mobile Internet protocol. The traffic engineering architecture is router based-meaning that routers on the edges of the network make the decisions onto which paths to place admitted traffic. We propose an algorithm that supports the architecture and uses local network state in order to function. The goal of the architecture is to provide an inexpensive and fast method to reduce network congestion while increasing the quality of service (QoS) level when compared to traditional routing and traffic engineering techniques. We use a number of different mobility scenarios and a mix of different types of traffic to evaluate our architecture and algorithm. We use the network simulator ns-2 as the core of our simulation environment. Around this core we built a system of pre-simulation, during simulation, and post-processing software that enabled us to simulate our traffic engineering architecture with only very minimal changes to the core ns-2 software. Our simulation environment supports a number of different mobility scenarios and a mix of different types of traffic to evaluate our architecture and algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5A
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• pp.355-362
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• 2009

In real-time communication services, delay constraints are among the most important QoS (Quality of Service) factors. In particular, it is difficult to guarantee the delay requirement over wireless channels, since they exhibit dynamic time-varying behavior and even severe burst-errors during periods of deep fading. Channel throughput may be increased, but at the cost of the additional delays when ARQ (Automatic Repeat Request) schemes are used. For real-time communication services, it is very essential to predict data deliverability. This paper derives the delay distribution and the successful delivery probability within a given delay budget using a priori channel model and a posteriori information from the perspective of queueing theory. The Gilbert-Elliot burst-noise channel is employed as an a Priori channel model, where a two-state Markov-modulated Bernoulli process $(MMBP_2)$ is used. for a posteriori information, the channel parameters, the queue-length and the initial channel state are assumed to be given. The numerical derivation is verified and analyzed via Monte Carlo simulations. This numerical derivation is then applied to a rate control scheme for real-time video transmission, where an optimal encoding rate is determined based on the future channel capacity and the distortion of the reconstructed pictures.