• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.186-187
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• 2021

Education in Korean universities is rapidly expanding to online education due to COVID-19. In response to such changes, this study proposed a means of improving the learning management system of Korean universities and analyzed the effects of using the system. The important results of this study are as follows: the learning management system was composed of 'pre-class learning,' 'team activity,' and 'participation learning' to support team-based learning. The effects that the users (instructors, learners) can obtain by adopting team-based learning and using the system were analyzed. The study concludes that for instructors, teaching work may be alleviated. For learners, it was demonstrated that they could more easily access and use data required for their education.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.7
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• pp.219-230
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• 2014

In the cloud computing environment, cloud service users purchase and use the virtualized resources from cloud resource providers on a pay as you go manner. Typically, there are two billing plans for computing resource allocation adopted by large cloud resource providers such as Amazon, Gogrid, and Microsoft, on-demand and reserved plans. Reserved Virtual Machine(VM) instance is provided to users based on the lengthy allocation with the cheaper price than the one of on-demand VM instance which is based on shortly allocation. With the proper mixture allocation of reserved and on-demand VM corresponding to users' requests, cloud service providers are able to reduce the resource allocation cost. To do this, prior researches about VM allocation scheme have been focused on the optimization approach with the users' request prediction techniques. However, it is difficult to predict the expected demands exactly because there are various cloud service users and the their request patterns are heavily fluctuated in reality. Moreover, the previous optimization processing techniques might require unacceptable huge time so it is hard to apply them to the current cloud computing system. In this paper, we propose the cloud brokering system with the adaptive VM allocation schemes called A3R(Adaptive 3 Resource allocation schemes) that do not need any optimization processes and kinds of prediction techniques. By using A3R, the VM instances are allocated to users in response to their service demands adaptively. We demonstrate that our proposed schemes are able to reduce the resource use cost significantly while maintaining the acceptable Quality of Service(QoS) of cloud service users through the evaluation results.

• KNOM Review
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• v.22 no.1
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• pp.52-59
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• 2019

As the video streaming service are supported by various devices, the amount of usage increases and efforts to improve the service from the viewpoint of users have continued. When a user watches a video, a response time occurs from input to playback, and if this response time becomes longer, the user's service satisfaction decreases. In this paper, we are proposing a method prefetching each user's preference video data obtained by analyzing user's past history record to the device for reducing the response time. We will show the result that prefetching data can improve the response time to 41% at most. And we analyzed real-video streaming viewing record and got each user's preferred video list. We investigated the change of response time according to a hit-ratio and amount of overhead data that was prefetched to the device, but not viewed. It was shown that as the hit-ratio grows bigger, the improvement of response time becomes more effective.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2220-2226
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• 2018

Electric vehicles (EVs) are significant resources for demand response (DR). Thus, it is essential for EV aggregators to quantitatively evaluate their capability for DR. In this paper, a concept of dynamic equivalent battery (DEB) is proposed as a metric for evaluating the DR performance using EVs. The DEB is the available virtual battery for DR. The capacity of DEB is determined from stochastic calculation while satisfying the charging requirements of each EV, and it varies also with time. Further, a new indicator based on the DEB and time-varying electricity prices, named as value of DEB (VoDEB), is introduced to quantify the value of DEB coupled with the electricity prices. The effectiveness of the DEB and the VoDEB as metrics for the DR performance of EVs is verified with the simulations, where the difference of charging cost reduction between direct charging and optimized bidding methods is used to express the DR performance. The simulation results show that the proposed metrics accord well with the DR performance of an EV fleet. Thus, an EV aggregator may utilize the proposed concepts of DEB and VoDEB for designing an incentive scheme to EV users, who participate in a DR program.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.2
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• pp.62-64
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• 2006

The emerging peer-to-peer (P2P) model has recently gained a significant attention due to its high potential of sharing various resources among networked users. Super-peer based unstructured P2P systems have been found very effective by dividing the peers into two layers, super-peer and ordinary-peer Super-peers deal with all queries instead of ordinary-peers. The existing P2P systems assume all super-peers have equal responsibility and capabilities even if all super-peers have relative advantages and disadvantages. In this paper, we suggest the ISP2P (Intelligent Super-peer based P2P) which allows to select the best super peer to ordinary-peers. We classify super peers according as the capacity of an ordinary-peer a super-peer. We show that these considerations could improve the performance of the response time and Provide higher quality results to all peers in the network.

• Electronics and Telecommunications Trends
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• v.35 no.7
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• pp.67-76
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• 2020

Because of the development and spread of artificial intelligence (AI) technology, new security threats and adverse AI functions have emerged as a real problem in the process of diversifying areas of use and introducing AI-based products and services to users. In response, it is necessary to develop new AI-based technologies in the field of information protection and security. This paper reviews topics such as domestic and international trends on false information detection technology, cyber security technology, and trust distribution platform technology, and it establishes the direction of the promotion of technology development. In addition, the development of international trends in ethical AI guidelines to ensure the human-centered ethical validity of AI development processes and final systems in parallel with technology development are analyzed and discussed. ETRI has developed AI policing technology, information protection, and security technologies as well as derived tasks and implementation strategies to prepare ethical AI development guidelines to ensure the reliability of AI based on its capabilities.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.10
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• pp.909-919
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• 2013

Pneumatic exciters can be good replacements of electrodynamic, piezoelectric and hydraulic exciters owing to simple structure and large exciting force. One problem to be solved is a slow response caused by compressibility of air. Desirable frequency response characteristics of exciter are constant magnitude and zero degree phase, because users want no time delay between input signal and output force. For this reason, frequency range of pneumatic exciters is limited about 0~1 Hz. Therefore, expansion of frequency range is an important issue when designing the pneumatic exciter. In this paper, the pneumatic exciter which has same structure with active pneumatic isolator is dealt with. The dynamic characteristics are presented, and its limitation of expanding frequency range is shown based on analytical studies. Then the pneumatic exciter with dual-chamber is suggested to overcome this problem. Based on simulation study, a design method is presented.

• Proceedings of the KSPS conference
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• 2006.11a
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• pp.109-112
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• 2006

This paper presents a dialogue interface using the dialogue management system as a method for controlling home appliances in Home Network Services. In order to realize this type of dialogue interface, we first investigated the user requirements for Home Network Services by analyzing the dialogues entered by users. Based on the analysis, we were able to extract 15 user intentions and 22 semantic components. In our study, example dialogues were collected from WOZ (Wizard-of-OZ) environment to implement a reasoning model for generating meaningful responses for example-based dialogue modeling technique. An overview of the Home Network Control System using proposed dialogue interface will be presented. Lastly, we will show that the Dialogue Management System trained with our collected dialogues behaves properly to achieve its task of controlling Home Network appliances by going through the steps of natural language understanding, response reasoning, response generation.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.628-645
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• 2014

In past few years, distributed hash table (DHT)-based P2P systems have been proven to be a promising way to manage decentralized index information and provide efficient lookup services. However, the skewness of users' preferences regarding keywords contained in a multi-keyword query causes a query load imbalance that combines both routing and response load. This imbalance means long file retrieval latency that negatively influences the overall system performance. Although index replication has a great potential for alleviating this problem, existing schemes did not explicitly address it or incurred high cost. To overcome this issue, we propose, in this paper, an integrated solution that consists of three replication schemes to alleviate query load imbalance while minimizing the cost. The first scheme is an active index replication that is used in order to decrease routing load in the system and to distribute response load of an index among peers that store replicas of the index. The second scheme is a proactive pointer replication that places location information of each index to a predetermined number of peers for reducing maintenance cost between the index and its replicas. The third scheme is a passive index replication that guarantees the maximum query load of peers. The result of simulations indicates that the proposed schemes can help alleviate the query load imbalance of peers. Moreover, it was found by comparison that our schemes are more cost-effective on placing replicas than PCache and EAD.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.3103-3103
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• 2001

NIR has been extensively used to predict directly measurable properties of materials that are important to the appropriate industries. Commonly, NIR is used to perform fast, routine tests to improve control response as against the response time for the (normally chemical) base test. This paper discusses the use of NIR to measure indirect properties of materials. In these cases, the pure chemical or physical tests are either unable measure the appropriate parameters (eg GMO modification) or there are mitigating effects that are not properly addressed by the base tests. In particular, we looked at the digestible portion of amino acids within meat and bone meal. This is the desired response measurement by end-users of the product (intensive livestock producers) but is currently unable to be offered as a measurement by producers. The base test method is by controlled feeding trials. These are somewhat cumbersome, taking 2-3 months, involving several sets of animals, and considerable expense. A shortened test (feed trial based) would be of little use, as the precision blows out over short period feeding trials. For example, a rat ileal digestibility test requires around 2 months, and costs some $USD1000. This is clearly impractical test for a producer involved in continuous production, with a 1-2 day turn around. While the amino acid abundance is accessible chemically, the uptake of amino acids into usable material by mammalian species is not simply related to the measured abundance within the material. There are many co-related material properties that might help or hinder uptake, some chemical based (eg protein damage), some indirect (eg palatability), some physiological (intestinal tract response vs speed of throughput). We discuss the approaches taken to provide a suitable reference data set, and present the derived prediction and validation relationships.