• Knowledge Management Research
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• v.14 no.1
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• pp.1-19
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• 2013

Consumers have collected information and sought advices from other consumer through Internet. They could collect information in virtual space (online) not real world, that is Electronic Word of Mouth (eWOM). This study focused on research the factors on effect in Electronic Word-of-Mouth (eWOM) in the open market which is mediate between individuals and online stores. This is an exploratory study for research on finding factors of effect in eWOM. First of all, 5factors are selected from interview with 31 consumers. Then online surveys are conducted and 5 factors are significantly supported. This study is academically new approach on an exploratory study and it could suggest marketers to strategically manage eWOM.

• Journal of Korea Multimedia Society
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• v.20 no.4
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• pp.649-659
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• 2017

Typically, a smart car is equipped with access to the Internet and a wireless local area network. Moreover, a smart car is equipped with a global positioning system (GPS) based navigation system that presents a map to a user for recommending the shortest path to a desired destination. This paper presents the design and implementation of a real-time shortest path search system for directed and dynamic roads. Herein, we attempt to simulate real-world road environments, while considering changes in the ratio of directed roads and in road conditions, such as traffic accidents and congestions. Further, we analyze the effect of the ratio of directed roads and road conditions on the communication cost between the server and vehicles and the arrival times of vehicles. In this study, we compare and analyze distance-based shortest path algorithms and driving time-based shortest path algorithms while varying the number of vehicles to search for the shortest path, road conditions, and ratio of directed roads.

• Journal of Construction Engineering and Project Management
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• v.1 no.2
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• pp.11-17
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• 2011

Recent demands from construction industry have emphasized the capability for graduates to have improved skills both technical and non-technical such as problem solving, interpersonal communication. To satisfy these demands, problem-based learning that is an instructional method characterized by the use of real world problem has been adopted and has proven its effectiveness various disciplines. However, in spite of the importance of field senses and dealing with real problem, construction engineering education has generally focused on traditional lecture-oriented course. In order to improve limitations of current construction education and to satisfy recent demands from construction industry, this paper proposes a new educational approach that is Failure-Based Learning for using combination of the procedural characteristics of the problem-based learning theory in construction technology education utilizing failure information that has the educational value in the construction area by reinterpreting characteristics of construction industry and construction failure information. The major results of this study are summarized as follows. 1) Educational effect of problem-based learning methodology and limitation of application in construction area 2) The educational value of the information on construction failure and limitation in application of the information in construction sector 3) Anticipated effect from application of the failure-based learning 4) Development and application of the failure-based learning conceptual model.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.106-112
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• 1993

A new model for the construction of a sonar map in a specular environment has been developed ad implemented. In a real world where most of the object surfaces are specular ones, a sonar sensor suffers from a multipath effect which results in a wrong interpretation of an objects's location. To reduce this effect and hence to construct a reliable map of a robot's surroundings, a probabilistic approach based on Bayesian reasoning is adopted to both evaluation of object orientations and estimation of an occupancy probability of a cell by an object. The usefulness of this approach is illustrated with the results produced by our mobile robot equipped with ultrasonic sensors.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.20-27
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• 2020

Sound event detection in real-world environments suffers from the interference of non-stationary and time-varying noise. This paper presents an adaptive noise reduction method for sound event detection based on non-negative matrix factorization (NMF). In this paper, we proposed a deep learning model that integrates Convolution Neural Network (CNN) with Non-Negative Matrix Factorization (NMF). To improve the separation quality of the NMF, it includes noise update technique that learns and adapts the characteristics of the current noise in real time. The noise update technique analyzes the sparsity and activity of the noise bias at the present time and decides the update training based on the noise candidate group obtained every frame in the previous noise reduction stage. Noise bias ranks selected as candidates for update training are updated in real time with discrimination NMF training. This NMF was applied to CNN and Hidden Markov Model(HMM) to achieve improvement for performance of sound event detection. Since CNN has a more obvious performance improvement effect, it can be widely used in sound source based CNN algorithm.

• ETRI Journal
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• v.37 no.2
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• pp.359-368
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• 2015

In this paper, we investigate the capture effect through experiments conducted with Iris nodes equipped with AT86RF230 radio transceivers. It is shown that the first arriving packet in a collision can capture the radio channel for equal power transmissions and may be decoded depending on the amount of overlap. A new 3-packet-capture scenario is introduced and implemented. To be able to understand the impact of capture on the throughput performance of wireless sensor networks, we present an analysis of the capture coefficient using our practical results. For real-world implementations, the throughput of pure ALOHA considering a finite number of users is presented in analytical form. The capture coefficient is then applied to pure ALOHA as a case study. Using analytical and practical implementations of the capture effect on ALOHA, a very good match in channel throughput performance enhancement is demonstrated over the non-capture effect case. TinyOS-2.x is used to program the nodes and to observe data exchange on a computer through a base station.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.45-53
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• 2020

Past literatures have not studied the impact of real-world events or information on the return and volatility of virtual currencies, particularly on the COVID-19 event, day-of-the-week effect, daily high-low price spreads and information flow rate. The study uses the ARMA-GARCH model to capture Bitcoin's return and conditional volatility, and explores the impact of information flow rate on conditional volatility in the Bitcoin market based on the Mixture Distribution Hypothesis (Clark, 1973). There were 3,064 samples collected during the period from 1^st of January 2012 to 20^th April, 2020. Empirical results show that in the Bitcoin market, a daily high-low price spread has a significant inverse relationship for daily return, and information flow rate has a significant positive relationship for condition volatility. The study supports a significant negative relationship between information asymmetry and daily return, and there is a significant positive relationship between daily trading volume and condition volatility. When Bitcoin trades on Saturday & Sunday, there is a significant reverse relationship for conditional volatility and there exists a day-of-the-week volatility effect. Under the impact of COVID-19 event, Bitcoin's condition volatility has increased significantly, indicating the risk of price changes. Finally, the Bitcoin's return has no impact on COVID-19 events and holidays (Saturday & Sunday).

• Research in Mathematical Education
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• v.27 no.1
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• pp.111-127
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• 2024

There is an increasing concern in the United States regarding the workforce's ability to maintain a competitive position in the global economy. This has led to an increased interest in effective science, technology, engineering, and mathematics (STEM) education. The purpose of this study was to investigate the effect of STEM project-based learning (PBL) on students' self-regulation and motivation to learn. Secondary students (n = 60) participated in a STEM summer camp in which STEM PBL was utilized. Results showed that students increased their self-regulation skills (t = 2.83, df = 59, p = .004) and motivation (t = 2.25, df = 59, p =.004), with Cohen's d effect sizes of 0.395 and 0.404, respectively. Student-centered learning and peer collaboration while solving real-world problems were likely the greatest contributing factors to the outcomes. Educators should utilize the results to provide opportunities for students to experience STEM PBL.

• Environmental Engineering Research
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• v.13 no.4
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• pp.210-215
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• 2008

The present study investigates the effect of oxidation-reduction potential (ORP) and organic compounds on specific anaerobic ammonium oxidation activity (SAA) using batch experiments. The batch tests were based on the measurement of nitrogen gas production. The relationship between ORP and dissolved oxygen (DO) concentration was found to be ORP (mV) = 160.38 + 68 log [$O_2$], where [$O_2$] is the DO concentration in mg/L. The linear relationship obtained between ORP and SAA ($R^2$ = 0.99) clearly demonstrated that ORP can be employed as an operational parameter in the Anammox process. At ORP value of -110 mV, the SAA was $0.272{\pm}0.03\;g\;N_2-N\;(g\;VSS)^{-1}\;d^{-1}$. The investigation also revealed inhibitory effect of glucose on the SAA while acetate concentration up to 640 mg COD/L (corresponding to 10 mM) had stimulating effect on the SAA. However, acetate concentration beyond 640 mg COD/L had inhibitory effect on the Anammox activity. The results indicated that nitrogen rich wastewaters containing low level organic matter could be better treated by Anammox microorganisms in real-world conditions after some acidification process.

• Journal of Korea Multimedia Society
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• v.20 no.9
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• pp.1606-1618
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• 2017

The explosion effect of computer graphics Visual Effects(VFX) used in films and animations is an important element that determines the completeness of the film, and its usage is getting extended. The realistic explosion effect of VFX should be made according to observations and analysis of various factors of actual explosion in real world. This experimental research would suggest the efficient production guideline for the technical characteristics of underwater explosion of VFX. For this research process, first, the comparison of actual explosion and VFX explosion effect, classification of actual explosion, and characteristics of underwater explosion effect will be addressed. Second, based on the literature reviews, the four steps of experimental production analysis tool will be derived. Third, the experimental research will be processed in along with technical factors four steps of the underwater explosion effect, (1)realistic creation and emission of fluid, (2)fluid expansion control by water pressure, (3)bubble effect, and (4)motion of bubble & dissipation of fluid. The effective method of fluid simulation production will be verified through experimental studies based on the characteristics of the actual explosion process. This experimental study suggested the VFX production technique is expected to be used as the basic data for related research field.