• International Commerce and Information Review
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• v.16 no.4
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• pp.171-190
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• 2014

A short consumption cycle caused by the technological development and the diversification of customer lead to both the dynamic growth of the industry and the waste recycling issue at the same time. Including Korea, the situation is particularly worrisome in some countries, such as India and China, where acute environmental hazards have resulted from a combination of a lack of recycling centers' capacity and the domination of a large backyard recycling sector. A study about to maximize the current recycling center efficiency with minimal changes is required. In this study, we suggest the optimal location selection method for the recycling center based on the well-known reverse logistics cost minimization model. An actual recycling data about a specific electronic equipment and region in Korea are used for the verification of the method suggested.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.152-161
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• 2020

The purpose of this study was to conduct a task-based field experience program for medical care support departments in hospitals for 1st medical students, and then to analyze the their experiences and its meanings phenomenologically. We selected the following department in hospital; nursing, medical records, pharmacy, diagnosis laboratory, radiology, administration, customer consulting center, organ transplant center, palliative medical ward, and international medical center. The students visited the department and used various methods such as interviewing, observation, and experience to solve the given task. As a result, in the program satisfaction, students rated the highest as having many department in the hospital and understanding their role. The essential structure of the experience of medical care support department in the reflection journal written by the students was the recognition of reality, respect and collaboration, and self-reflection from experience recognition.

• Transactions of the Korean Society of Automotive Engineers
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• v.25 no.2
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• pp.133-139
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• 2017

The timing chain system, which is a typical power transmission technology applied to a vehicle, has been widely used by the automotive industry because it is normally designed to last a car's lifetime. However, the timing chain system may cause some problems due to the shape of the chains and the polygonal behavior on contact between the chain and the sprocket. In addition, noise and vibration caused by transmission error are the most typical problems encountered by major automotive manufacturers and they are considered as the main source of customer complaint. The initial tension of the chain-sprocket system is thought to be the main cause of transmission error, and it is regarded as the source of engine vibration and noise. The initial tension of the chain system should be controlled carefully since a low initial tension can cause twisting, which may lead to a system malfunction, while a high initial tension can reduce the service life due to a worn down contact surface. In this paper, the kinematic analysis model is generated with various initial tensions, which are controlled by changing the shape of the fixed guide with the largest contact surface with chain. The results showed that the transmission error was minimized on a particular range of initial tension, and the tendency showed that the error changed with a higher sensitivity at a lower initial tension.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1431-1439
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• 2017

In the security field, log analysis is important to detect malware or abnormal behavior. Recently, image visualization techniques for malware dectection becomes to a major part of security. These techniques can also be used in online games. Users can leave a game when they felt bad experience from game bot, automatic hunting programs, malicious code, etc. This churning can damage online game's profit and longevity of service if game operators cannot detect this kind of events in time. In this paper, we propose a new technique of PNG image conversion based churn prediction to improve the efficiency of data analysis for the first. By using this log compression technique, we can reduce the size of log files by 52,849 times smaller and increase the analysis speed without features analysis. Second, we apply data mining technique to predict user's churn with a real dataset from Blade & Soul developed by NCSoft. As a result, we can identify potential churners with a high accuracy of 97%.

• The Journal of Bigdata
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• v.6 no.1
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• pp.1-12
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• 2021

The rapid growth of mobile-based online shopping and the appearance of untact business initiated by COVID-19 has led to an explosive increase in demand for logistics services such as delivery services. In order to respond to the rapidly growing demand, most logistics and distribution companies are working to improve customer service levels through the establishment of a full-filament center in the city center. However, due to social factors such as high land prices and traffic congestion, it becomes more difficult to establish the logistics facilities in the city center. In this study, it has been proposed the way to choose the candidate locations for the shared distribution centers among the space nearby the tall-gate which can be idle after the smart tolling service is widely extended. In order to evaluate the candidate locations, it has been evaluated the centralities of all candidates using social network analysis (SNA). To understand the result considering the characteristics of centrality, the network structure was regenerated based on the distance and the traveling time, respectively. It is possible to refer the result of evaluation based on the cumulative relative importance to choose the best set of candidates.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.69-75
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• 2021

In a contact-free society, online services are becoming more important than classic offline services. At the same time, the role of a contact center, which executes customer relation management (CRM), is increasingly essential. For supporting the CRM tasks and their effectiveness, techniques of process automation need to be applied. Quality assurance (QA) is one of the time and resource consuming, and typical processes that are suitable for automation. In this paper, a method of automatic quality evaluation for voice based consultations is proposed. Firstly, the speech in consultations is transformed into a text by speech recognition. Then quantitative evaluation based on the QA metrics, including checking the elements in opening and closing mention, the existence of asking the mandatory information, the attitude of listening and speaking, is executed. 92.7% of the automated evaluations are the same to the result done by human experts. It was found that the non matching cases of the automated evaluations were mainly caused from the mistranslated Speech-to-Text (STT) result. With the confidence of STT result, this proposed method can be employed for enhancing the efficiency of QA process in contact centers.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.1
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• pp.91-102
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• 2019

Autonomous vehicles can be exposed to severe danger when failure occurs in any of its components. For this reason many countries are making efforts on the legislative issue how to objectively evaluate failure safety of an autonomous vehicle when such a vehicle is commercially available to a customer in the near future. In level-3 automation, a driver must take over the control of his vehicle when failure occurs, and the driver's controllability must be secured for escape from the imminent danger. In this paper, quantitative methods have been developed for evaluating failure safety of the level-3 autonomous vehicle, and they were validated by simulation. And also, we confirmed that the proposed evaluation method can quantitatively evaluate the failure safety.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.1
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• pp.55-65
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• 2021

In this paper, a methodology for reinforcing reverse logistics (RL) activities in a closed-loop supply chain (CLSC) model is proposed. For the methodology, the activities of the recovery center (RC) which can be considered as one of the facilities in the RL are reinforced. By the reinforced activities in the RC, the recovered parts and products after checking and recovering processes of the returned product from customer can be reused in the forward logistics (FL) of the CLSC model. A mathematical formulation is suggested for representing the CLSC model with reinforced RL activities, and implemented using a hybrid genetic algorithm (HGA) approach. In numerical experiment, two different scales of the CLSC model are presented and the performance of the HGA approach is compared with those of some conventional approaches. The experimental results show that the former outperforms the latter in most of performance measures. The robustness of the CLSC model is also proved by regulating various rates of the recovered parts and products in the RC.

• The Journal of the Acoustical Society of Korea
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• v.25 no.6
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• pp.269-276
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• 2006

In this paper, we propose an emotion recognition system that can discriminate human emotional state into neutral or anger from the speech captured by a cellular-phone in real time. In general. the speech through the mobile network contains environment noise and network noise, thus it can causes serious System performance degradation due to the distortion in emotional features of the query speech. In order to minimize the effect of these noise and so improve the system performance, we adopt a simple MA (Moving Average) filter which has relatively simple structure and low computational complexity, to alleviate the distortion in the emotional feature vector. Then a SFS (Sequential Forward Selection) feature optimization method is implemented to further improve and stabilize the system performance. Two pattern recognition method such as k-NN and SVM is compared for emotional state classification. The experimental results indicate that the proposed method provides very stable and successful emotional classification performance such as 86.5%. so that it will be very useful in application areas such as customer call-center.

• Industry Promotion Research
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• v.9 no.2
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• pp.1-12
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• 2024

This study examines the role of Environment, Social, and Governance (ESG) activity recognition on job satisfaction, prosocial activities, and job performance among customer representatives working in call center environments. After gathering data from 264 call center workers in major South Korean insurance companies, the analysis w as performed using SmartPLS 4.0. This study's findings reveal that employee recognition of ESG activities significantly enhanced job satisfaction. The impact of ESG activity recognition on prosocial behavior was positive but relatively weak. Job satisfaction influences both prosocial behavior and the job performance of employees. Finally, prosocial behavior positively influences job performance. The most significant finding is that employees' recognition of companies' ESG management practices serves as a job resource. This recognition enhances employees' attitudes, behavior, and performance, signaling the potential benefits of informing employees about corporations' ethical behaviors.