• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.2
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• pp.23-32
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• 2020

The compression sensing technology, CAFB, was developed to obtain the raw signal of the target structure by compressing it into a signal of the intended frequency range. At this point, for compression sensing, the CAFB can be optimized for various reference signals depending on the desired frequency range of the target structure. In addition, optimized CAFB should be able to efficiently compress the effective structural answers of the target structure even in sudden/dangerous conditions such as earthquakes. In this paper, the targeted frequency range for efficient structural integrity monitoring of relatively flexible structures was set below 10Hz, and the optimization method of CAFB for this purpose and the seismic response performance of CAFB in seismic conditions were evaluated experimentally. To this end, in this paper, CAFB was first optimized using Kobe seismic waveform, and embedded it in its own wireless IDAQ system. In addition, seismic response tests were conducted on two span bridges using Kobe seismic waveform. Finally, using an IDAQ system with built-in CAFB, the seismic response of the two-span bridge was wirelessly obtained, and the compression signal obtained was cross-referenced with the raw signal. From the results of the experiment, the compression signal showed excellent response performance and data compression effects in relation to the raw signal, and CAFB was able to effectively compress and sensitize the effective structural response of the structure even in seismic situations. Finally, in this paper, the optimization method of CAFB was presented to suit the intended frequency range (less than 10Hz), and CAFB proved to be an economical and efficient data compression sensing technology for instrumentation-monitoring of seismic conditions.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.3
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• pp.189-204
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• 2013

Today, politics, economy and technique in the world are rapidly changed. To respond to these changes public institutions as well as government and corporate try to change themselves and to adapt these situation and environment. Total payroll costs system which is one of critical methods to adapt changing world began to introduce in 2004 for public services in Korea. After exhibition and enforcement, all education administration in Korea adopted this system in 2013. This study focus on how total payroll costs system can be successfully controled and utilized, and who this system increase organizational effectiveness and efficacy in public services. Organizational members' effort, perspective, attitude and behavior are most important factors for organizational change and new option. Organizational change and adaptation always involve members' change and adaptation, so this study emphasizes on members' perspective and attitude on total payroll costs system. As a result, distribution justice, procedure justice, and receptivity about total payroll costs system are related to organizational performance such as job satisfaction and organizational commitment. This means organizational members' perspective(distribution justice and procedure justice) and attitude(receptivity) are most crucial factors for effectiveness and efficacy of total payroll costs system. Furthermore with distribution justice, procedure justice and receptivity, total payroll costs system would increase members' job satisfaction and organizational commitment. To sum up, members' perspective and attitude are most important factors for change, thus for success of total payroll costs system, we should understand how people are critical, especially their distribution justice, procedure justice, and receptivity; and also how total payroll costs system are valuable system; and how we can control and handle this system.

• Progress in Medical Physics
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• v.13 no.3
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• pp.149-155
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• 2002

Recent advances in radiation transport algorithms, computer hardware performance, and parallel computing make the clinical use of Monte Carlo based dose calculations possible. To compare the speed and accuracies of dose calculations between different developed codes, a benchmark tests were proposed at the XIIth ICCR (International Conference on the use of Computers in Radiation Therapy, Heidelberg, Germany 2000). A Monte Carlo treatment planning comprised of 28 various Intel Pentium CPUs was implemented for routine clinical use. The purpose of this study was to evaluate the performance of our system using the above benchmark tests. The benchmark procedures are comprised of three parts. a) speed of photon beams dose calculation inside a given phantom of 30.5 cm$\times$39.5 cm $\times$ 30 cm deep and filled with 5 ㎣ voxels within 2% statistical uncertainty. b) speed of electron beams dose calculation inside the same phantom as that of the photon beams. c) accuracy of photon and electron beam calculation inside heterogeneous slab phantom compared with the reference results of EGS4/PRESTA calculation. As results of the speed benchmark tests, it took 5.5 minutes to achieve less than 2% statistical uncertainty for 18 MV photon beams. Though the net calculation for electron beams was an order of faster than the photon beam, the overall calculation time was similar to that of photon beam case due to the overhead time to maintain parallel processing. Since our Monte Carlo code is EGSnrc, which is an improved version of EGS4, the accuracy tests of our system showed, as expected, very good agreement with the reference data. In conclusion, our Monte Carlo treatment planning system shows clinically meaningful results. Though other more efficient codes are developed such like MCDOSE and VMC＋＋, BEAMnrc based on EGSnrc code system may be used for routine clinical Monte Carlo treatment planning in conjunction with clustering technique.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.39-57
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• 2012

Recently, due to the introduction of high-tech equipment in interactive exhibits, many people's attention has been concentrated on Interactive exhibits that can double the exhibition effect through the interaction with the audience. In addition, it is also possible to measure a variety of audience reaction in the interactive exhibition. Among various audience reactions, this research uses the change of the facial features that can be collected in an interactive exhibition space. This research develops an artificial neural network-based prediction model to predict the response of the audience by measuring the change of the facial features when the audience is given stimulation from the non-excited state. To present the emotion state of the audience, this research uses a Valence-Arousal model. So, this research suggests an overall framework composed of the following six steps. The first step is a step of collecting data for modeling. The data was collected from people participated in the 2012 Seoul DMC Culture Open, and the collected data was used for the experiments. The second step extracts 64 facial features from the collected data and compensates the facial feature values. The third step generates independent and dependent variables of an artificial neural network model. The fourth step extracts the independent variable that affects the dependent variable using the statistical technique. The fifth step builds an artificial neural network model and performs a learning process using train set and test set. Finally the last sixth step is to validate the prediction performance of artificial neural network model using the validation data set. The proposed model is compared with statistical predictive model to see whether it had better performance or not. As a result, although the data set in this experiment had much noise, the proposed model showed better results when the model was compared with multiple regression analysis model. If the prediction model of audience reaction was used in the real exhibition, it will be able to provide countermeasures and services appropriate to the audience's reaction viewing the exhibits. Specifically, if the arousal of audience about Exhibits is low, Action to increase arousal of the audience will be taken. For instance, we recommend the audience another preferred contents or using a light or sound to focus on these exhibits. In other words, when planning future exhibitions, planning the exhibition to satisfy various audience preferences would be possible. And it is expected to foster a personalized environment to concentrate on the exhibits. But, the proposed model in this research still shows the low prediction accuracy. The cause is in some parts as follows : First, the data covers diverse visitors of real exhibitions, so it was difficult to control the optimized experimental environment. So, the collected data has much noise, and it would results a lower accuracy. In further research, the data collection will be conducted in a more optimized experimental environment. The further research to increase the accuracy of the predictions of the model will be conducted. Second, using changes of facial expression only is thought to be not enough to extract audience emotions. If facial expression is combined with other responses, such as the sound, audience behavior, it would result a better result.

• The KIPS Transactions:PartA
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• v.13A no.2 s.99
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• pp.123-136
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• 2006

The prefetching technique is an effective way to reduce the latency caused memory access. However, excessively aggressive prefetch not only leads to cache pollution so as to cancel out the benefits of prefetch but also increase bus traffic leading to overall performance degradation. In this thesis, a prefetch filtering scheme is proposed which dynamically decides whether to commence prefetching by referring a filtering table to reduce the cache pollution due to unnecessary prefetches In this thesis, First, prefetch hashing table 1bitSC filtering scheme(PHT1bSC) has been shown to analyze the lock problem of the conventional scheme, this scheme such as conventional scheme used to be N:1 mapping, but it has the two state to 1bit value of each entries. A complete block address table filtering scheme(CBAT) has been introduced to be used as a reference for the comparative study. A prefetch block address lookup table scheme(PBALT) has been proposed as the main idea of this paper which exhibits the most exact filtering performance. This scheme has a length of the table the same as the PHT1bSC scheme, the contents of each entry have the fields the same as CBAT scheme recently, never referenced data block address has been 1:1 mapping a entry of the filter table. On commonly used prefetch schemes and general benchmarks and multimedia programs simulates change cache parameters. The PBALT scheme compared with no filtering has shown enhanced the greatest 22%, the cache miss ratio has been decreased by 7.9% by virtue of enhanced filtering accuracy compared with conventional PHT2bSC. The MADT of the proposed PBALT scheme has been decreased by 6.1% compared with conventional schemes to reduce the total execution time.

• Clean Technology
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• v.27 no.4
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• pp.332-340
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• 2021

With the recent reinforcement of emission standards, it is necessary to make efforts to reduce NOx from air pollutant-emitting workplaces. The NOx reduction method mainly used in industrial facilities is selective catalytic reduction (SCR), and the most commercial SCR catalyst is the ceramic honeycomb catalyst. This study was carried out to reduce the NOx emitted from steel plants by applying De-NOx catalyst coated on metallic monolith. The De-NOx catalyst was synthesized through the optimized coating technique, and the coated catalyst was uniformly and strongly adhered onto the surface of the metallic monolith according to the air jet erosion and bending test. Due to the good thermal conductivity of metallic monolith, the De-NOx catalyst coated on metallic monolith showed good De-NOx efficiency at low temperatures (200 ~ 250 ℃). In addition, the optimal amount of catalyst coating on the metallic monolith surface was confirmed for the design of an economical catalyst. Based on these results, the De-NOx catalyst of commercial grade size was tested in a semi-pilot De-NOx performance facility under a simulated gas similar to the exhaust gas emitted from a steel plant. Even at a low temperature (200 ℃), it showed excellent performance satisfying the emission standard (less than 60 ppm). Therefore, the De-NOx catalyst coated metallic monolith has good physical and chemical properties and showed a good De-NOx efficiency even with the minimum amount of catalyst. Additionally, it was possible to compact and downsize the SCR reactor through the application of a high-density cell. Therefore, we suggest that the proposed De-NOx catalyst coated metallic monolith may be a good alternative De-NOx catalyst for industrial uses such as steel plants, thermal power plants, incineration plants ships, and construction machinery.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.562-569
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• 2019

Raman spectroscopy has been receiving increased attention as a standoff explosive detection technique. In addition, there is a growing need for a fast search method that can identify raman spectrum for measured chemical substances compared to known raman spectra in large database. By far the most simple and widely used method is to calculate and compare the Euclidean distance between the given spectrum and the spectra in a database. But it is non-trivial problem because of the inherent high dimensionality of the data. One of the most serious problems is the high computational complexity of searching for the closet spectra. To overcome this problem, we presented the MPS Sort with Sorted Variance+PDS method for the fast algorithm to search for the closet spectra in the last paper. the proposed algorithm uses two significant features of a vector, mean values and variance, to reject many unlikely spectra and save a great deal of computation time. In this paper, we present two new methods for the fast algorithm to search for the closet spectra. the PCA+PDS algorithm reduces the amount of computation by reducing the dimension of the data through PCA transformation with the same result as the distance calculation using the whole data. the Hierarchical Cluster Tree algorithm makes a binary hierarchical tree using PCA transformed spectra data. then it start searching from the clusters closest to the input spectrum and do not calculate many spectra that can not be candidates, which save a great deal of computation time. As the Experiment results, PCA+PDS shows about 60.06% performance improvement for the MPS Sort with Sorted Variance+PDS. also, Hierarchical Tree shows about 17.74% performance improvement for the PCA+PDS. The results obtained confirm the effectiveness of the proposed algorithm.

• (The) Research of the performance art and culture
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• no.35
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• pp.509-541
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• 2017

The basic intent of this thesis lies in proposing a meaningful direction of developing cultural content by combining Asian traditional dance forms which hold cultural closeness in common historically. For this study, this paper selected Oyangseon(五羊仙; 'Five Taoist Hermits on Five Sheep'), a Korean court dance of Chinese origin as an example as the Oyangseon story is commonly found in ancient Vietnam and China as well as Korea. Its original narrative is a mythic story that five hermits had come down to ancient Vietnam region riding on five sheep of five colors to bestow 6 ears of milets to people. Later, the story was spread to other regions to be reformed into Woljeongjeon(越井傳; Vietnam), Choi Wee(崔?; China) and Oyangseon(Korea) that have different plot and background. While Woljeongjeon and Choi Wee were adapted into novels that describe the hero Choi Wee's mysterious adventure to be repaid his father's previous devotion to ancient King's shrine. Meanwhile, the epic narrative of Korean Oyangseon proves the modification of the original myth by adding a Seowangmo(西王母; a Chinese mythic heavenly queen) motif while it was enacted as a court dance to praise king's long life and pray country's prosperity following Confucian concept. Based on this historical lineage of Oyangseon story, I searched for the possiblity of constructing a cultural content program by combining the Oyangseon dance of three countries. While there was Oyangseonmu(五羊仙舞) in China which was recently composed by referring to Korean Oyangseon, any traditional dance item based on Oyangseon story was not available in Vietnam. Thus, I tried to propose the Vietnam Dance College to choreograph a new dance item with Woljeongjeon story while using the traditional dance technique, music, costume, etc. of Vietnam as most as possible. As a result, I could display a direction of developing a cultural content by staging three countries' dance items based on Oyangseon story at Korean National Haneul Theater in Oct 2016.

• (The) Research of the performance art and culture
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• no.35
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• pp.471-508
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• 2017

The basic intent of this thesis lies in proposing a meaningful direction of developing cultural content by combining Asian traditional dance forms which hold cultural closeness in common historically. For this study, this paper selected Oyangseon(五羊仙; 'Five Taoist Hermits on Five Sheep'), a Korean court dance of Chinese origin as an example as the Oyangseon story is commonly found in ancient Vietnam and China as well as Korea. Its original narrative is a mythic story that five hermits had come down to ancient Vietnam region riding on five sheep of five colors to bestow 6 ears of milets to people. Later, the story was spread to other regions to be reformed into Woljeongjeon(越井傳; Vietnam), Choi Wee(崔?; China) and Oyangseon(Korea) that have different plot and background. While Woljeongjeon and Choi Wee were adapted into novels that describe the hero Choi Wee's mysterious adventure to be repaid his father's previous devotion to ancient King's shrine. Meanwhile, the epic narrative of Korean Oyangseon proves the modification of the original myth by adding a Seowangmo(西王母; a Chinese mythic heavenly queen) motif while it was enacted as a court dance to praise king's long life and pray country's prosperity following Confucian concept. Based on this historical lineage of Oyangseon story, I searched for the possiblity of constructing a cultural content program by combining the Oyangseon dance of three countries. While there was Oyangseonmu(五羊仙舞) in China which was recently composed by referring to Korean Oyangseon, any traditional dance item based on Oyangseon story was not available in Vietnam. Thus, I tried to propose the Vietnam Dance College to choreograph a new dance item with Woljeongjeon story while using the traditional dance technique, music, costume, etc. of Vietnam as most as possible. As a result, I could display a direction of developing a cultural content by staging three countries' dance items based on Oyangseon story at Korean National Haneul Theater in Oct 2016.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.1-17
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• 2023

With the recent rapid development of ICT(Information and Communication Technology) and the popularization of digital devices, the size of the online market continues to grow. As a result, we live in a flood of information. Thus, customers are facing information overload problems that require a lot of time and money to select products. Therefore, a personalized recommender system has become an essential methodology to address such issues. Collaborative Filtering(CF) is the most widely used recommender system. Traditional recommender systems mainly utilize quantitative data such as rating values, resulting in poor recommendation accuracy. Quantitative data cannot fully reflect the user's preference. To solve such a problem, studies that reflect qualitative data, such as review contents, are being actively conducted these days. To quantify user review contents, text mining was used in this study. The general CF consists of the following three steps: user-item matrix generation, Top-N neighborhood group search, and Top-K recommendation list generation. In this study, we propose a recommendation algorithm that applies an extended similarity measure, which utilize quantified review contents in addition to user rating values. After calculating review similarity by applying TF-IDF, Word2Vec, and Doc2Vec techniques to review content, extended similarity is created by combining user rating similarity and quantified review contents. To verify this, we used user ratings and review data from the e-commerce site Amazon's "Health and Personal Care". The proposed recommendation model using extended similarity measure showed superior performance to the traditional recommendation model using only user rating value-based similarity measure. In addition, among the various text mining techniques, the similarity obtained using the TF-IDF technique showed the best performance when used in the neighbor group search and recommendation list generation step.