• Smart Media Journal
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• v.12 no.11
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• pp.48-56
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• 2023

The technology of Three-dimensional human posture estimation is used in sports, motion recognition, and special effects of video media. Among various methods for this, multi-view 3D human pose estimation is essential for precise estimation even in complex real-world environments. But Existing models for multi-view 3D human posture estimation have the disadvantage of high order of time complexity as they use 3D feature maps. This paper proposes a method to extend an existing monocular viewpoint multi-frame model based on Transformer with lower time complexity to 3D human posture estimation for multi-viewpoints. To expand to multi-viewpoints our proposed method first generates an 8-dimensional joint coordinate that connects 2-dimensional joint coordinates for 17 joints at 4-vieiwpoints acquired using the 2-dimensional human posture detector, CPN(Cascaded Pyramid Network). This paper then converts them into 17×32 data with patch embedding, and enters the data into a transformer model, finally. Consequently, the MLP(Multi-Layer Perceptron) block that outputs the 3D-human posture simultaneously updates the 3D human posture estimation for 4-viewpoints at every iteration. Compared to Zheng[5]'s method the number of model parameters of the proposed method was 48.9%, MPJPE(Mean Per Joint Position Error) was reduced by 20.6 mm (43.8%) and the average learning time per epoch was more than 20 times faster.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.565-574
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• 2024

ChatGPT is causing significant reverberations across all sectors of our society, and this holds true for the field of education as well. However, scholarly and societal discussions regarding ChatGPT in academic settings have primarily focused on issues such as plagiarism, with relatively limited research on the positive effects of utilizing generative AI. Additionally, amidst the educational crisis of the post-COVID era, there is a growing recognition of the need to enhance academic engagement. In light of these concerns, we investigated how academic engagement varies based on students' levels of ChatGPT literacy and examined whether students' academic confidence and perceived academic competence serve as mediators between ChatGPT literacy and academic engagement. An analysis using SPSS was conducted on the data collected from 406 college students. The results showed that ChatGPT literacy had a positive effect on academic engagement, and academic confidence mediated the relationship between ChatGPT literacy and academic engagement. Also, when the mediating effect of perceived academic competence was significant only when it was serially mediated. Based on these findings, we discussed the theoretical contributions of identifying the theoretical mechanism between ChatGPT literacy and academic engagement. In addition, practical implications regarding the importance of ChatGPT literacy education were described.

• Journal of the Korea Society for Simulation
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• v.33 no.1
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• pp.1-17
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• 2024

Forest management is known to beneficially influence stand structure and wood production, yet quantitative understanding as well as an illustrative depiction of the effects of different management approaches on tree growth and stand dynamics are still scarce. Long-term management of beech forests must balance public interests with ecological aspects. Efficient forest management requires the reliable prediction of tree growth change. We aimed to develop a novel hybrid simulation approach, which realistically simulates short- as well as long-term effects of different forest management regimes commonly applied, but not limited, to German low mountain ranges, including near-natural forest management based on single-tree selection harvesting. The model basically consists of three modules for (a) natural seedling regeneration, (b) mortality adjustment, and (c) tree growth simulation. In our approach, an existing validated growth model was used to calculate single year tree growth, and expanded on by including in a newly developed simulation process using calibrated modules based on practical experience in forest management and advice from the local forest. We included the following different beech forest-management scenarios that are representative for German low mountain ranges to our simulation tool: (1) plantation, (2) continuous cover forestry, and (3) reserved forest. The simulation results show a robust consistency with expert knowledge as well as a great comparability with mid-term monitoring data, indicating a strong model performance. We successfully developed a hybrid simulation that realistically reflects different management strategies and tree growth in low mountain range. This study represents a basis for a new model calibration method, which has translational potential for further studies to develop reliable tailor-made models adjusted to local situations in beech forest management.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.50 no.3
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• pp.227-237
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• 2024

In this study, we investigated anti-oxidative, anti-inflammatory and anti-bacterial constituents from the extract of Prunus mume (P. mume) branches. Five phytochemicals were isolated from the ethyl acetate (EtOAc) fraction of P. mume branches; noreugenin (1), naringenin (2), prunin (3), procyanidin A2 (4) and epiafzelechin-(2β→O→7, 4β→8)-epicatechin (5). The chemical structures of isolated compounds were elucidated based on the spectroscopic data including NMR spectra as well as comparison of the data to the literature values. Upon the anti-oxidative studies by DPPH and ABTS⁺ radicals, potent radical scavenging activities were observed in the extract, EtOAc, n-butanol (BuOH) fractions and isolated compounds 4, 5. In the anti-inflammatory tests using RAW 264.7 macrophages, the n-hexane (Hex), EtOAc fractions and compounds 1-5 inhibited production of nitric oxide (NO) without causing cell toxicity. Also, the extract, n-Hex, EtOAc and n-BuOH fractions showed anti-bacterial activities against Staphylococcus epidermidis and Cutibacterium acnes. Based on these results, it was suggested that the extract, solvent fractions and phytochemicals from P. mume branches could be applicable as natural source for cosmetic ingredients.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.5
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• pp.973-980
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• 2024

Fuzzing is an automated testing technique that generates a lot of testcases and monitors for exceptions to test a program. Recently, fuzzing research using machine learning has been actively proposed to solve various problems in the fuzzing process, but a comprehensive evaluation of fuzzing research using machine learning is lacking. In this paper, we analyze recent research that applies machine learning to scheduling techniques for fuzzing, categorizing them into reinforcement learning-based and supervised learning-based fuzzers. We evaluated the coverage performance of the analyzed machine learning-based fuzzers against real-world programs with four different file formats and bug detection performance against the LAVA-M dataset. The results showed that AFL-HIER, which applied seed clustering and seed scheduling with reinforcement learning outperformed in coverage and bug detection. In the case of supervised learning, it showed high coverage on tcpdumps with high code complexity, and its superior bug detection performance when applied to hybrid fuzzing. This research shows that performance of machine learning-based fuzzer is better when both machine learning and additional fuzzing techniques are used to optimize the fuzzing process. Future research is needed on practical and robust machine learning-based fuzzing techniques that can be effectively applied to programs that handle various input formats.

• Progress in Medical Physics
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• v.11 no.2
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• pp.157-165
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• 2000

Purpose: For estimation of yields of l)NA damages induced by radiation and enhanced by oxygen, a mathematical model was used and tested. Materials and Methods: Reactions of the products of water radiolysis were modeled as an ordinary time dependant equations. These reactions include formation of radicals, DNA damage, damage repair, restitution, and damage fixation by oxygen and H-radical. Several rate constants were obtained from literature while others were calculated by fitting an experimental data. Sensitivity studies were performed changing the chemical rate constant at a constant oxygen number density and varying the oxygen concentration. The effects of oxygen concentration as well as the damage fixation mechanism by oxygen were investigated. Oxygen enhancement ratio(OER) was calculated to compare the simulated data with experimental data. Results: Sensitivity studies with oxygen showed that DNA survival was a function of both oxygen concentration and the magnitude of chemical rate constants. There were no change in survival fraction as a function of dose while the oxygen concentration change from 0 to 1.0 x 10$^{7}$ . When the oxygen concentration change from 1.0 $\times$ 107 to 1.0 $\times$ 101o, there was significant decrease in cell survival. The OER values obtained from the simulation study were 2.32 at 10% cell survival level and 1.9 at 45% cell survival level. Conclusion: Sensitivity studies with oxygen demonstrated that the experimental data were reproduced with the effects being enhanced for the cases where the oxygen rate constants are largest and the oxygen concentration is increased. OER values obtained from the simulation study showed good agreement for a low level of cell survival. This indicated that the use of the semi-empirical model could predict the effect of oxygen in cell killing.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.4
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• pp.263-271
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• 2009

This study evaluated the flocs forming characteristics in the mixing zone to increase the coagulation effect in the drinking water plant. As a measuring tool of formed flocs, on-line particle dispersion analyzer (iPDA) was used in Y drinking water plant. To evaluate the forming flocs, many parameters such as poly amine, coagulant dosing amount, raw water turbidity, and pH was applied in this study. During the periods of field test, poly aluminium chloride (PACl) as a coagulant was used. With the increase of the raw water turbidities, poly amine was also added as one of aids for increasing in coagulation efficiency. The turbidity and pH of raw water was ranged from 7 to 9 and from 25 to 140 NTU, respectively. The increasing of raw water turbidity brought the bigger floc sizes accordingly. From a regression analysis, $R^2$ value was 0.8040 as a function of T, raw water turbidity. Floc size index (FSI) was obtained from a correlation equation as follows; FSI = 0.9388logT - 0.3214 Also, polyamine gave the bigger flocs the moment it is added to the coagulated water in the rapid mixing zone. One of parameters influencing the floc sizes was the addition of powdered active carbon(PAC) in the mixing zone. In case of higher turbidity of raw water, $R^2$ value was 0.9050 in the parameters of [PACl] and [PAC]; FSI = $0.0407[T]^{0.324}[PACI]^{0.769}[PAC]^{0.178}$ On-line floc monitor was beneficial to evaluate the flocs sizes depending on the many parameters consisting raw water properties, bring the profitable basic data to control the mixing zone more effectively.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.39-60
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• 2011

Since the introduction of web 2.0 technology, social network service has been recognized as the foundation of an important future information technology. The advent of web 2.0 has led to the change of content creators. In the existing web, content creators are service providers, whereas they have changed into service users in the recent web. Users share experiences with other users improving contents quality, thereby it has increased the importance of social network. As a result, diverse forms of social network service have been emerged from relations and experiences of users. Social network is a network to construct and express social relations among people who share interests and activities. Today's social network service has not merely confined itself to showing user interactions, but it has also developed into a level in which content generation and evaluation are interacting with each other. As the volume of contents generated from social network service and the number of connections between users have drastically increased, the social network extraction method becomes more complicated. Consequently the following problems for the social network extraction arise. First problem lies in insufficiency of representational power of object in the social network. Second problem is incapability of expressional power in the diverse connections among users. Third problem is the difficulty of creating dynamic change in the social network due to change in user interests. And lastly, lack of method capable of integrating and processing data efficiently in the heterogeneous distributed computing environment. The first and last problems can be solved by using FOAF, a tool for describing ontology-based user profiles for construction of social network. However, solving second and third problems require a novel technology to reflect dynamic change of user interests and relations. In this paper, we propose a novel method to overcome the above problems of existing social network extraction method by applying FOAF (a tool for describing user profiles) and RSS (a literary web work publishing mechanism) to OLAP system in order to dynamically innovate and manage FOAF. We employed data interoperability which is an important characteristic of FOAF in this paper. Next we used RSS to reflect such changes as time flow and user interests. RSS, a tool for literary web work, provides standard vocabulary for distribution at web sites and contents in the form of RDF/XML. In this paper, we collect personal information and relations of users by utilizing FOAF. We also collect user contents by utilizing RSS. Finally, collected data is inserted into the database by star schema. The system we proposed in this paper generates OLAP cube using data in the database. 'Dynamic FOAF Management Algorithm' processes generated OLAP cube. Dynamic FOAF Management Algorithm consists of two functions: one is find_id_interest() and the other is find_relation (). Find_id_interest() is used to extract user interests during the input period, and find-relation() extracts users matching user interests. Finally, the proposed system reconstructs FOAF by reflecting extracted relationships and interests of users. For the justification of the suggested idea, we showed the implemented result together with its analysis. We used C# language and MS-SQL database, and input FOAF and RSS as data collected from livejournal.com. The implemented result shows that foaf : interest of users has reached an average of 19 percent increase for four weeks. In proportion to the increased foaf : interest change, the number of foaf : knows of users has grown an average of 9 percent for four weeks. As we use FOAF and RSS as basic data which have a wide support in web 2.0 and social network service, we have a definite advantage in utilizing user data distributed in the diverse web sites and services regardless of language and types of computer. By using suggested method in this paper, we can provide better services coping with the rapid change of user interests with the automatic application of FOAF.

• Journal of Korea Spatial Information System Society
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• v.7 no.3 s.15
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• pp.67-81
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• 2005

Recently, the interest and research on the development of new application services such as the Location Based Service and Telemetics providing the emergency service, neighbor information search, and route search according to the development of the Geographic Information System have been increasing. User's search in the spatio-temporal database which is used in the field of Location Based Service or Telemetics usually fixes the current time on the time axis and queries the spatial and aspatial attributes. Thus, if the range of query on the time axis is extensive, it is difficult to efficiently deal with the search operation. For solving this problem, the snapshot, a method to summarize the location data of moving objects, was introduced. However, if the range to store data is wide, more space for storing data is required. And, the snapshot is created even for unnecessary space that is not frequently used for search. Thus, non storage space and memory are generally used in the snapshot method. Therefore, in this paper, we suggests the Hash-based Spatio-Temporal Clustering Algorithm(H-STCA) that extends the two-dimensional spatial hash algorithm used for the spatial clustering in the past to the three-dimensional spatial hash algorithm for overcoming the disadvantages of the snapshot method. And, this paper also suggests the knowledge extraction algorithm to extract the knowledge for the path search of moving objects from the past location data based on the suggested H-STCA algorithm. Moreover, as the results of the performance evaluation, the snapshot clustering method using H-STCA, in the search time, storage structure construction time, optimal path search time, related to the huge amount of moving object data demonstrated the higher performance than the spatio-temporal index methods and the original snapshot method. Especially, for the snapshot clustering method using H-STCA, the more the number of moving objects was increased, the more the performance was improved, as compared to the existing spatio-temporal index methods and the original snapshot method.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.321-322
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• 2012

의료용 방사선 장비는 초기의 아날로그 방식의 필름 및 카세트에서 진보되어 현재는 디지털 방식의 DR (Digital Radiography)이 널리 사용되며 그에 관한 연구개발이 활발히 진행되고 있다. DR은 크게 간접방식과 직접방식의 두 분류로 나눌 수 있는데, 간접방식은 X선을 흡수하면 가시광선으로 전환하는 형광체(Scintillator)를 사용하여 X선을 가시광선으로 전환하고, 이를 Photodiode와 같은 광소자로 전기적 신호로 변환하여 방사선을 검출하는 방식을 말하며, 직접 방식은 X선을 흡수하면 전기적 신호를 발생 시키는 광도전체(Photoconductor)를 사용하여 광도전체 양단 전극에 고전압을 인가한 형태를 취하고 있는 가운데, X선이 조사되면 일차적으로 광도전체 내부에서 전자-전공쌍(Electron-hole pair)이 생성된다. 이들은 광도전체 양단의 인가되어 있는 전기장에 의해 전자는 +극으로, 전공은 -극으로 이동하여 아래에 위치한 Active matrix array을 통해 방사선을 검출하는 방식이다. 본 연구에서는 직접방식 X-ray 검출기에서 활용되는 a-Se을 ITO (Indium Thin oxide) glass 상단에 Thermal evaporation증착을 이용하여 두께 $50{\mu}m$, 33 넓이로 증착 시킨 다음, a-Se상단에 Sputtering증착을 이용하여 ITO를 11 cm, 22 cm, $2.7{\times}2.7cm$ 넓이로 증착시켜 상하부의 ITO를 Electrode로 이용하여 직접방식의 X-ray검출기 샘플을 제작하였다. 제작 과정 중 a-Se의 Thermal evaporation증착 시, 저진공 $310^{-3}_{Torr}$, 고진공 $2.210^{-5}_{Torr}$에서 보트의 가열 온도를 두 번의 스텝으로 나누어 증착 시켰다. 첫 번째 스텝 $250^{\circ}C$, 두 번째 스텝은 $260^{\circ}C$의 조건으로 증착하여 보트 내의 a-Se을 남기지 않고 전량을 소모할 수 있었으며, 스텝간의 온도차를 $10^{\circ}C$로 제어하여 균일한 박막을 형성 할 수 있었다. Sputtering증착 시, 저진공 $2.510^{-3}$, 고진공 $310^{-5}$에서 Ar, $O_2$를 사용하여 100 Sec간 플라즈마를 생성시켜 ITO를 증착하였다. 제작된 방사선 각각의 검출기 샘플 양단의 ITO에 500V의 전압을 인가하고, 진단 방사선 범위의 70 kVp, 100 mA, 0.03 sec 조건으로 X-ray를 조사시켜 ITO넓이에 따른 민감도(Sensitivity)와 암전류(Dark current)를 측정하였다. 측정결과 민감도(Sensitivity)는 X-ray샘플의 두께에 따른 $1V/{\mu}m$ 기준 시, 증착된 ITO의 넓이가 11 cm부터 22 cm, $2.7{\times}2.7cm$까지 각각 $7.610nC/cm^2$, $8.169nC/cm^2$, $6.769nC/cm^2$로 22 cm 넓이의 샘플이 가장 높은 민감도를 나타내었으나, 암전류(Dark current)는 $1.68nA/cm^2$, $3.132nA/cm^2$, $5.117nA/cm^2$로 11 cm 넓이의 샘플이 가장 낮은 값을 나타내었다. 이러한 데이터를 SNR (Signal to Noise Ratio)로 합산 하였을 시 104.359 ($1{\times}1$), 60.376($2{\times}2$), 30.621 ($2.7{\times}2.7$)로 11 cm 샘플이 신호 대 별 가장 우수한 효율을 나타냄을 알 수 있었다. 따라서 ITO박막의 면적이 클수록 민감도는 우수하나 그에 따른 암전류의 증가로 효율이 떨어짐을 검증 할 수 있었으며, 이는 ITO면적이 넓어짐에 따른 저항의 증가로 암전류에 영향을 끼침을 할 수 있었다. 본 연구를 통해 a-Se의 ITO 박막 면적에 따른 전기적 특성을 검증할 수 있었다.