• The KIPS Transactions:PartC
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• v.14C no.1 s.111
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• pp.81-86
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• 2007

New multimedia services over the cellular/WLAN overlay networks require different Quality of Service (QoS). Therefore, efficient network management system is necessary in order to provide QoS sensitive multimedia services while enhancing network performance. In this paper, we propose a new online network management scheme that implements bandwidth reservation, congestion and transmission control strategies. Our online approach to network management exhibits dynamic adaptability, flexibility, and responsiveness to the current traffic conditions in multimedia overlay networks. Simulation results indicate the superior performance of our proposed scheme to strike the appropriate performance balance between contradictory QoS requirements under widely varying diverse traffic loads.

• Journal of Distribution Science
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• v.18 no.8
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• pp.103-112
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• 2020

Purpose: Business has been completely revolutionized by the Internet. This study seeks to determine the impact of e-business on activity extension and business performance. It aims to examine the actual stage of e-business, help others to apply the knowledge gained, and help in expanding new researches in this field. Research design, data and methodology: The data utilized in this study was obtained from survey. In total of 60 questionnaires accepted as valid out of 80 distributed, data was analyzed using the SPSS, and methods used were correlation and reliability analyses. Results: The study result shows that e-business has a significant positive impact on activity extension and the performance of business in Kosovo. The findings also revealed that there is a correlation between the various online marketing strategies and consumer satisfaction. The development of e-business for Kosovo is an important factor in participation in the world market, where there is a growing need for innovation and modernization of business. Conclusions: The study recommends that there should be raised awareness among business owners and managers as well as the general public. Moreover, there should be a proper application of marketing strategies to e-business.

• Journal of the Korean Society for Library and Information Science
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• v.17
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• pp.49-83
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• 1989

A Full text retrieval system is a natural language document retrieval system in which the full text of all documents in a collection is stored on a computer so that every word in every sentence of every document can be located by the machine. This kind of IR System is recently becoming rapidly available online in the field of legal, newspaper, journal and reference book indexing. Increased research interest has been in this field. In this paper, research on full text databases and retrieval systems are reviewed, directions for research in this field are speculated, questions in the field that need answering are considered, and variables affecting online full text retrieval and various role that variables play in a research study are described. Two obvious research questions in full text retrieval have been how full text retrieval performs and how to improve the retrieval performance of full text databases. Research to improve the retrieval performance has been incorporated with ranking or weighting algorithms based on word occurrences, combined menu-driven and query-driven systems, and improvement of computer architectures and record structure for databases. Recent increase in the number of full text databases with various sizes, forms and subject matters, and recent development in computer architecture artificial intelligence, and videodisc technology promise new direction of its research and scholarly growth. Studies on the interrelationship between every elements of the full text retrieval situation and the relationship between each elements and retrieval performance may give a professional view in theory and practice of full text retrieval.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.908-925
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• 2014

Induction Motor (IM) has several desirable features for high performance adjustablespeed operation. This paper presents the design of a robust controller for vector control induction motor drive performances improvement. Proposed predictive speed controller, which is aimed to guarantee the stability of the closed loop, is based on the Poisson-Laguerre (PL) models for the association vector control drive and the induction motor; without necessity of any mechanical parameter, and requires only two control parameters to ensure implicitly the integrator effect on the steady state error, load torque disturbances rejection and anti-windup effect. In order to improve robustness, insensitivity against external disturbances and preserve desired performance, adaptive control is added with the aim to ensure an online identification of controller parameters through an online PL models identification. The proposed control is compared with the conventional approach using PI controller. Simulation with MATLAB/SIMULINK software and experimental results for a 1kW induction motor using a dSPACE system with DS1104 controller board are carried out to show the improvement performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.2115-2130
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• 2022

With the development of over-the-top (OTT) services, the demand for content is increasing, and you can easily and conveniently acquire various content in the online environment. As a result, copyrighted content can be easily copied and distributed, resulting in serious copyright infringement. Some special forms of online service providers (OSP) use filtering-based technologies to protect copyrights, but illegal uploaders use methods that bypass traditional filters. Uploading with a title that bypasses the filter cannot use a similar search method to detect illegal content. In this paper, we propose a technique for profiling the Heavy Uploader by normalizing the bypassed content title and efficiently detecting illegal content. First, the word is extracted from the normalized title and converted into a bit-array to detect illegal works. This Bloom Filter method has a characteristic that there are false positives but no false negatives. The false positive rate has a trade-off relationship with processing performance. As the false positive rate increases, the processing performance increases, and when the false positive rate decreases, the processing performance increases. We increased the detection rate by directly comparing the word to the result of increasing the false positive rate of the Bloom Filter. The processing time was also as fast as when the false positive rate was increased. Afterwards, we create a function that includes information about overall piracy and identify clustering-based heavy uploaders. Analyze the behavior of heavy uploaders to find the first uploader and detect the source site.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.45-73
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• 2008

Quality has long been considered as an important factor in creating competitive advantage, and researches on quality have not been limited to off-line products but actively extended to e-services and information goods. However, given the nature of multi-dimensional aspect of quality, the systematic study on the quality of online service is still in its early stage. Especially, studies on the quality of ASP services have been rare in academic and professional journals despite the growth of ASP industry in its size and the rapid expansion in the range of application. In this paper we clarified the multi-dimensional quality aspects of the ASP service using a Garvin's framework (1984) which encompasses the service aspects of Products, and developed a measurement model for ASP service qualify. Then we empirically tested the effects of ASP service quality on user satisfaction and perceived firm performance using the data from 240 Korean small firms with less than 50 employees that had experienced the ASP service. Our results show that there are positive relationships among ASP service quality and personal performance, user satisfaction and perceived firm performance, and that product and service-related aspects of ASP service exert differential effects on performance measures so that the product-related aspects of the ASP service such as performance, features, reliability and conformance are considered to be more important in evaluating benefits from ASP services. Contrary to the approaches In literature where only the quality of online services is evaluated, our results emphasize the importance of differentiating Product and service-related aspects of ASP service and provide a basis for more comprehensive evaluation of ASP service quality.

• Journal of Information Technology Services
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• v.20 no.4
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• pp.129-140
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• 2021

Recently, interest in AI tutors is rising as a way to bridge the educational gap in school settings. However, research confirming the effectiveness of AI tutors is lacking. The purpose of this study is to explore how effective learner characteristics and recommended item learning activities are in predicting learner's academic performance in an adaptive online learning environment. This study proposed the hypothesis that learner characteristics (prior knowledge, midterm evaluation) and recommended item learning activities (learning time, correct answer check, incorrect answer correction, satisfaction, correct answer rate) predict academic achievement. In order to verify the hypothesis, the data of 362 learners were analyzed by collecting data from the learning management system (LMS) from the perspective of learning analytics. For data analysis, regression analysis was performed using the regsubset function provided by the leaps package of the R program. The results of analyses showed that prior knowledge, midterm evaluation, correct answer confirmation, incorrect answer correction, and satisfaction had a positive effect on academic performance, but learning time had a negative effect on academic performance. On the other hand, the percentage of correct answers did not have a significant effect on academic performance. The results of this study suggest that recommended item learning activities, which mean behavioral indicators of interaction with AI tutors, are important in the learning process stage to increase academic performance in an adaptive online learning environment.

• The Journal of the Korea Contents Association
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• v.17 no.7
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• pp.416-424
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• 2017

The purpose of this study is to analyze the effects of learning motivation on interaction in online collaborative learning. The study subjects are 79 university students who take courses in teaching. Learning motivations measured the intrinsic goal orientation, extrinsic goal orientation, tasks value, control of learning beliefs, test anxiety, self-efficacy, goal orientation by MSLQ. Next, the level of interaction was measured by online collaborative tasks. The group for online cooperation tasks consisted of four to five people and random assignment. The level of interaction was used frequency and score that quantitative Value assess. The collected data were analysed using multiple regression analysis(stepwise). As a result, self-efficacy and extrinsic goal orientation, tasks value, mastery goal orientation were positive effect on frequency and score. next, test anxiety and performance avoid goal orientation were negative effect on frequency and score.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.2866-2879
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• 2012

Among the various security threats in online games, the use of game bots is the most serious problem. Previous studies on game bot detection have proposed many methods to find out discriminable behaviors of bots from humans based on the fact that a bot's playing pattern is different from that of a human. In this paper, we look at the chatting data that reflects gamers' communication patterns and propose a communication pattern analysis framework for online game bot detection. In massive multi-user online role playing games (MMORPGs), game bots use chatting message in a different way from normal users. We derive four features; a network feature, a descriptive feature, a diversity feature and a text feature. To measure the diversity of communication patterns, we propose lightly summarized indices, which are computationally inexpensive and intuitive. For text features, we derive lexical, syntactic and semantic features from chatting contents using text mining techniques. To build the learning model for game bot detection, we test and compare three classification models: the random forest, logistic regression and lazy learning. We apply the proposed framework to AION operated by NCsoft, a leading online game company in Korea. As a result of our experiments, we found that the random forest outperforms the logistic regression and lazy learning. The model that employs the entire feature sets gives the highest performance with a precision value of 0.893 and a recall value of 0.965.

• Journal of Digital Convergence
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• v.16 no.2
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• pp.189-194
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• 2018

This study reflects the current trend of the blind hiring culture focused on job competency rather than education specification as government initiative. In order to overcome the limitation of the existing document-oriented online recruitment process, we proposed a system architecture design of video interview system. In addition, we have evaluated the effectiveness through the development of prototype and performance experiment based on it. The proposed online video interview system is designed to combine intelligent Web technology to enable customized job matching and distant job coaching. This system is designed to reduce recruitment cost and opportunity cost of job seekers. Based on results derived from this study, commercialization of the proposed video interview system can be expected to be an practical online recruitment solution for the job competency based employment.