• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.469-478
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• 2001

In the virtual memory system, page replacement policy exerts a great influence on the performance of demand paging. There are LRU(Least Recently Used) and LFU (Least Frequently Used) as the typical replacement policies. The LRU policy performs effectively in many cases and adapts well to the changing workloads compared to other policies. It however cannot distinguish well between frequently and infrequently referenced pages. The LFU policy requires that the page with the smallest reference count be replaced. Though it considers all the references in the past, it cannot discriminate between references that occurred far back in the past and the more recent ones. Thus, it cannot adapt well to the changing workload. In this paper, we first analyze memory reference patterns of eight applications. The patterns show that the recently referenced pages or the frequently referenced pages are accessed continuously as the case may be. So it is rather hard to optimize page replacement scheme by using just one of the LRU or LFU policy. This paper makes an attempt to combine the advantages of the two policies and proposes a new page replacement policy. In the proposed policy, paging list is divided into two lists (LRU and LFU lists). By keeping the two lists in recency and reference frequency order respectively, we try to restrain the highly referenced pages in the past from being replaced by the LRU policy. Results from trace-driven simulations show that there exists points on the spectrum at which the proposed policy performs better than the previously known policies for the workloads we considered. Especially, we can see that our policy outperforms the existing ones in such applications that have reference patterns of re-accessing the frequently referenced pages in the past after some time.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.271-278
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• 2021

As the current cyber attacks become more intelligent, the existing Intrusion Detection System is difficult for detecting intelligent attacks that deviate from the existing stored patterns. In an attempt to solve this, a model of a deep learning-based intrusion detection system that analyzes the pattern of intelligent attacks through data learning has emerged. Intrusion detection systems are divided into host-based and network-based depending on the installation location. Unlike network-based intrusion detection systems, host-based intrusion detection systems have the disadvantage of having to observe the inside and outside of the system as a whole. However, it has the advantage of being able to detect intrusions that cannot be detected by a network-based intrusion detection system. Therefore, in this study, we conducted a study on a host-based intrusion detection system. In order to evaluate and improve the performance of the host-based intrusion detection system model, we used the host-based Leipzig Intrusion Detection-Data Set (LID-DS) published in 2018. In the performance evaluation of the model using that data set, in order to confirm the similarity of each data and reconstructed to identify whether it is normal data or abnormal data, 1D vector data is converted to 3D image data. Also, the deep learning model has the drawback of having to re-learn every time a new cyber attack method is seen. In other words, it is not efficient because it takes a long time to learn a large amount of data. To solve this problem, this paper proposes the Siamese Convolutional Neural Network (Siamese-CNN) to use the Few-Shot Learning method that shows excellent performance by learning the little amount of data. Siamese-CNN determines whether the attacks are of the same type by the similarity score of each sample of cyber attacks converted into images. The accuracy was calculated using Few-Shot Learning technique, and the performance of Vanilla Convolutional Neural Network (Vanilla-CNN) and Siamese-CNN was compared to confirm the performance of Siamese-CNN. As a result of measuring Accuracy, Precision, Recall and F1-Score index, it was confirmed that the recall of the Siamese-CNN model proposed in this study was increased by about 6% from the Vanilla-CNN model.

• Korean Journal of Environmental Biology
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• v.36 no.3
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• pp.359-369
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• 2018

Harmful algal blooms (HABs) are a serious problem for public health and fisheries industries, thus there exists a need to investigate the possible ways for effective control of HABs. In the present study, we investigated the algicidal effects of a newly developed GreenTD against the HABs (Chattonella marina, Heterosigma akashiwo, Cochlodinium polykriokides, and Heterocapsa circularisquama) and non-HABs (Chaetoceros simplex, Skeletonema sp. and Tetraselmis sp.), which is focused on the different population density and concentration gradients of algicidal substances. The time series viability of target alga was assessed based on the activity of Chl. a photosynthetic efficiency in terms of $F_v/F_m$, and in vivo fluorescence (FSU). Effective control of Raphidophyta, C. marina and H. akashiwo was achieved at a GreenTD concentration of $0.5{\mu}gL^{-1}$ and $0.2{\mu}gL^{-1}$, respectively, and regrowth of both the species was not observed even after 14 days. The inhibitory ratio of the dinoflagellate, C. polykriokides was more than 80% at $0.2{\mu}gL^{-1}$ of GreenTD. H. circularisquama was constantly affected in the presence of $0.2{\mu}gL^{-1}$ of GreenTD in the high- and low-population density experimental groups. On the other hand, diatoms, C. simplex, and Skeletonema sp. were not significantly affected even in the presence of $0.2{\mu}gL^{-1}$ of GreenTD and exhibited re-growth activity with the passage of incubation time. In particular, green alga Tetraselmis sp. remained unaffected even in the presence of the highest concentration of GreenTD ($1.0{\mu}gL^{-1}$), implying that non-HABs were not greatly influenced by the algicidal substances. As a result, the algicidal activity of GreenTD on the harmful and nonharmful algae was as follows: raphidophyte>dinoflagellates>diatoms>green alga. Consequently, our results indicate that inoculation of GreenTD substances into natural blooms at a threshold concentration ($0.2{\mu}gL^{-1}$) can maximize the algicidal activity against HABs species. If we consider the dilution and diffusion rate in the field application, it is hypothesized that GreenTD will demonstrate economic efficiency, thus leading to effective control against the target HABs in the closed bay.

• Journal of Bio-Environment Control
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• v.28 no.4
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• pp.366-375
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• 2019

This experiment aims to determine the proper irrigation scheduling based on a whole-substrate capacitance using a newly developed device (SCMD) by comparing with the integrated solar radiation automated irrigation system (ISR) and sap flow sensor automated irrigation system (SF) for the cultivation of tomato (Solanum lycopersicum L. 'Hoyong' 'Super Doterang') during spring to winter season. For the SCMD system, irrigation was conducted every 10 minutes after the first irrigation was started until the first run-off was occurred, of which the substrate capacitance was considered to be 100%. When the capacitance threshold (CT) was reached to the target point, irrigation was re-conducted. After that, when the target drain volume (TDV) was occurred, the irrigation stopped. The irrigation volume per event for the SCMD was set to 50, 75, or 100 mL at CT 0.9 and TDV 100 mL during the spring to summer cultivation, and the CT was set to 0.65, 0.75, 0.80, or 0.90 in the winter cultivation. When the irrigation volume per event was set to 50, 75, or 100 mL, the irrigation frequency in a day was 39, 29, and 19, respectively, and the drain rate was 3.04, 9.25, and 20.18%, respectively. When the CT was set to 0.65, 0.75, or 0.90 in winter, the irrigation frequency was about 6, 7, 15 times, respectively and the drain rate was 9.9, 10.8, 35.3% respectively. The signal of stem sap flow at the beginning of irrigation starting time did not correspond to that of solar irradiance when the irrigation volume per event was set to 50 or 75 mL, compared to that of 100 mL. In winter cultivation, the stem sap flow rate and substrate volumetric water content at the CT 0.65 treatment were very low, while they were very high at CT 0.90 was high. All the integrated data suggest that the proper range of irrigation volume per event is from 75 to 100 mL under at CT 0.9 and TDV 100 mL during the spring to summer cultivation, and the proper CT seems to be higher than 0.75 and lower than 0.90 under at 75 mL of the irrigation volume per event and TDV 70 mL during the winter cultivation. It is going to be necessary to investigate the relationship between capacitance value and substrate volumetric water content by determining the correction coefficient.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.1
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• pp.1-18
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• 2021

This study was intended to present measures for the improvement of the apartment house landscaping supervision system by examining the adequacy of landscaping supervision, which is aimed at improving the quality of landscape plants and facilities in apartment house landscaping sites. Additionally, this study aims to identify the problems occurring in the process of the performance of landscaping supervision and to provide the evidence for legislative activities and revision of the laws currently being pushed forward for the mandatory deployment of apartment house landscaping supervision personnel. The results of the analysis showed that no landscaping supervision personnel was deployed to apartment complexes with less than 1,500 households and that the landscaping comprised 19% to 46% of the entire construction process. The civil engineering firm performed the landscaping supervision, which made it impracticable to fully focus on the construction quality in the field of landscaping. The quality control in terms of landscape plants revealed differences in quality control, depending on the competence and experience of the civil engineer supervising the personnel, where the landscaping supervision personnel was not deployed. The apartment houses landscaping supervision activity index was analyzed, and the results showed that the supervision activity index for apartment house A was 72.0, B was 70.4, and apartment houses C to G ranged from 38.7 to 46.9, which suggested that the difference in quality control, process control, and technical support affected the construction quality and occurrence of defects.The improvement of landscaping process quality control and process management will be carried out more smoothly and the rate of defects will be drastically reduced if the landscaping supervision personnel placement threshold is lowered from 1,500 households to 300 households in complexes. The results of this study are expected to be useful in promoting and re-establishing the landscaping industry based on the improvement of construction quality in the field of landscaping in connection with the construction of apartment houses.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.2
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• pp.239-247
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• 2023

The FIDIC Red Book is an international standard contract condition in which the Employer designs and the Contractor performs the construction. The Engineer of FIDIC Red Book shall agree or determine any matter or Claim in accordance with Sub-Clause 3.7 neutrally, not as an agent of the Employer. This study aimed to derive Key Risk Sub-Clauses out of 49 Sub-Clauses that the Engineer of FIDIC Red Book recently revised in 18 years shall agree or determine according to Sub-Clause 3.7 using the Delphi method. A panel of 35 experts with more than 10 years of experience and expertise in international construction contracts was formed, and through total three Delphi surveys, errors and biases were prevented in the judgment process to improve reliability. As for the research method, 49 Sub-Clauses that engineers shall agree on or determine according to Sub-Clause 3.7 of the FIDIC Red Book were investigated through the analysis of contract conditions. In order to evaluate the probability and impact of contractual risk for each 49 Sub-Clause, the Delphi survey conducted repeatedly a closed-type survey three times on a Likert 10-point scale. The results of the first Delphi survey were delivered during the second survey, and the results of the second survey were delivered to the third survey, which was re-evaluated in the direction of increasing the consensus of experts' opinions. The reliability of the Delphi 3rd survey results was verified with the COV value of the coefficient of variation. The PI Risk Matrix was applied to the average value of risk probability and impact of each of the 49 Sub-Clauses and finally, 9 Key Risk Sub-Clauses that fell within the extreme risk range were derived.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.3
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• pp.21-29
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• 2023

In this study, the stress characteristics of temporary fixed steel rods were analyzed in the "temporary fixing system using internal prestressing tension", which is mainly applied to the construction of superstructures by FCM. It was difficult to confirm the changes in initial tensile force in this system because the steel rod was internally connected to the pier and the PSC BOX. Therefore, measurement was performed before and after the completion of each segment using an FBG sensor to measure the change in the micro length of the steel rod. The results of the analysis showed that 75% to 90% of the maximum vertical contraction of the steel rod that occurred until the completion of the cantilever segment occurred in the fixing ~ 1segment, and the maximum loss of initial prestressing force was 39%. Such excessive loss of tension force to 1 segment means that tension is needed to improve the precision of construction during the fixation, and re-tension is needed to secure stability for conduction of cantilever segments after the completion of 1segment. In the 2 ~ last segment, the stress of the steel rod decreased gradually, and in the summer, the decrease in stress tended to partially recover due to the increase in the length of the steel rod corresponding to the increase in the vertical volume of PSC BOX. The dominant factor in the stress change in 2~ last segment in this phenomenon is judged to be the change in the length of the steel rod according to the temperature. Unlike the change in length, the relaxation was 1.2-2.7%, which was mostly offset by the opposite stress corresponding to the temperature stress. Therefore, a plan was proposed to improve the internal stress, such as adjusting the fixation time.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.33-54
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• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.