• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1211-1216
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• 2000

Asynchronous transfer mode (ATM) can be efficiently used to transport packet data services. The switching system will support voice and packet data services simultaneously from end to end applications. To guarantee quality of service (QoS) of the offered services, source rateot send packet data is needed to control the network overload condition. Most existing control algorithms are shown to provide the threshold-based feedback control technique. However, real-time voice calls can be dynamically connected and released during data services in the network. If the feedback control information delays, quality of the serviced voice can be degraded due to a time delay between source and destination in the high speed link. An adaptive algorithm based on the optimal least mean square error technique is presented for the predictive feedback control technique. The algorithm attempts to predict a future buffer size from weight (slope) adaptation of unknown functions, which are used fro feedback control. Simulation results are presented, which show the effectiveness of the algorithm.

• Journal of Internet Computing and Services
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• v.3 no.3
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• pp.67-74
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• 2002

Asynchronous transfer mode (ATM) can be efficiently used to transport packet data services. The switching system will support voice and packet data services simultaneously from end to end applications. To guarantee quality of service (QoS) of the offered services, source rate to send packet data is needed to control the network overload condition. Most existing control algorithms are shown to provide the threshold-based feedback control technique. However, real-time voice calls can be dynamically connected and released during data services in the network. If the feedback control information delays, quality of the serviced voice can be degraded due to a time delay between source and destination in the high speed link, An adaptive algorithm based on the optimal least mean square error technique is presented for the predictive feedback control technique. The algorithm attempts to predict a future buffer size from weight (slope) adaptation of unknown functions, which are used for feedback control. Simulation results are presented, which show the effectiveness of the algorithm.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1561-1566
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• 2017

Due to the advances in machine learning and artificial intelligence technologies, many new services have become available. Among such services, recommendation systems have already been successfully applied to commercial services and made profits as in online shopping malls. Most recommendation algorithms in commercial services are based on content analysis or explicit feedback rates as in movie recommendations. However, many online shopping malls have difficulties in content analysis or are lacking explicit feedbacks on their items, which results in no recommendation system for their items. Even for such service systems, user log data is easily available, and if recommendations are possible with such log data, the quality of their service can be improved. In this paper, we extract implicit feedback like click information for items from log data and provide a recommendation system based on the implicit feedback. The proposed system is applied to a real in-service online shopping mall.

• Journal of Digital Contents Society
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• v.15 no.2
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• pp.219-225
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• 2014

Competition between corporations is getting more intense, so they need customer feedback in order to fulfill an effective management. Recently, SNS (Social Network Service) such as Twitter and Facebook has grown dramatically because of smart phones. Social media like Twitter and Facebook let customers to express their needs, and using big data such as data on SNS is a very effective method for getting customer's feedback. Collecting and analyzing social big data are operated by Buzz monitoring system. This research suggests how to utilize big data for getting customer's feedback on hotel CRM(Customer Relationship Management), which considers customer itself as asset of business. This paper demonstrates the research of buzz monitoring system that analyzes big data, and presents results of hotel customer reputation using buzz monitoring system. It would analyze the result from the hotel customer reputation, and research the implication in this paper.

• Journal of KIISE:Databases
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• v.37 no.2
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• pp.82-91
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• 2010

Data compression technique is traditional and effective to reduce network traffic. Generally, sensor data exhibit strong correlation in both space and time. Many algorithms have been proposed to utilize these characteristics. However, each sensor just utilizes neighboring information, because its communication range is restrained. Information that includes the distribution and characteristics of whole sensor data provide other opportunities to enhance the compression technique. In this paper, we propose an orthogonal approach for compression algorithm based on a novel feedback diffusion algorithm in sensor networks. The base station or a super node generates the Huffman code for compression of sensor data and broadcasts it into sensor networks. Every sensor that receives the information compresses their sensor data and transmits them to the base station. We define this approach as feedback-diffusion. In order to show the superiority of our approach, we compare it with the existing aggregation algorithms in terms of the lifetime of the sensor network. As a result, our experimental results show that the whole network lifetime was prolonged by about 30%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5C
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• pp.302-308
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• 2011

In this paper we propose a coordinated beamforming(CBF) scheme considering the effects of feedback quantization and delay in time-varying multiple-input multiple-output(MIMO) broadcast channels. By equal power allocation per data stream, the proposed CBF scheme transmits multiple data streams per user terminals without additional feedback overhead when quantized feedback information is used. The proposed CBF scheme also applies a linear channel predictor to each user terminals to prevent errors due to feedback delays that are not evitable in practical wireless systems. Each user terminal utilizes Wiener filter to predict future channel responses and generates feedback information based on the predicted channels. Consequently the proposed CBF scheme adapting Wiener filter improves system performances compared with the conventional scheme using delayed feedback.

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.1
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• pp.57-68
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• 2011

This paper examines how multiple performance feedbacks influence firm's technological search, using two types of indicators : accounting-based performance and market-based performance. Also we investigate how CEO's attention shift depends on firm specific factors such as firm size and outsider ownership. For empirical analysis, we utilized financial data on 675 manufacturing firms in Korea during the period between 1998 and 2009. The results show that technological search based on accounting-based performance feedback is moderated by focal firm's size. However, as outsider ownership increases, technological search increases in response to market-based performance feedback.

• Asia pacific journal of information systems
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• v.9 no.2
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• pp.1-17
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• 1999

A feedback echo is a structured restatement of the user's query and informs the user what the system intends to do for the query. This provides backtracking of the user's query so that the user knows how the system has interpreted the query. This study scrutinizes whether the feedback echo, as currently available in the INTELLECT commercial system, can improve the performance of a casual user using a restricted natural language database interface. This study concludes that the particular type of feedback echo available in this commercial system was not effective in terms of overall performance for casual users. It is worth mentioning, however, that the feedback echo was effective for the specific type of error: using wrong conditions for data retrieval.

• English Language & Literature Teaching
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• v.15 no.2
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• pp.151-168
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• 2009

The present study investigates the impact of trained peer feedback on the quantity and quality of revisions made by EFL students at a low-intermediate level. Peer review training was carried out in experimental group through four in-class training sessions and four peer dyad-instructor conferences after class. Students' $1^{st}$ drafts with written peer feedback and revised drafts prior to and post training were collected and analyzed. Results reveal that after training the students produced more revisions in response to their peer comments (96% of total revisions) and those revisions were counted as enhanced in quality (93% of peer-triggered revisions). In contrast, the results of paired t-test within control group indicate that there was no significant difference between two data collected from week 3 and week 16 (t = -.57, df =19, p = .577 at p < .05). The findings suggest that training as an ongoing process of teacher intervention contributes to effectiveness of the peer feedback activity. The study provides pedagogical implications for how to structure and implement peer review training for the sake of its direct strength in an EFL writing class.

• Korean System Dynamics Review
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• v.17 no.3
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• pp.145-173
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• 2016

This study aims to develop strategic diagnosis framework of performance by identifying and analysing the dynamics of the technology commercialization ecosystem in innovative region. To achieve the purpose of this study, the systems thinking approach is used. The systems thinking approach connects feedback structure and behavior more explicitly to diagnosis vicious feedback loop in the regional technology commercialization ecosystem. In terms of an ecological point of view, it will be possible to explore dominant feedback structure and find leverages to overcome the limitations of regional technology commercialization performance. The diagnosis of reenforcing and balancing feedback structure is based on the statistical analysis of the survey data which has been collected in a cluster random sampling method, targeting on the 200 firm located in the Pangyo and Daeduk region. The results from this research showed that the regional technology commercialization ecosystem was immature and faced limit to the growth. An important finding of this study was that regional technology commercialization ecosystem need to activation of startups and reinforcement of virtuous feedback structures of technology commercialization market systems.