• Journal of dental hygiene science
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• v.22 no.3
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• pp.191-198
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• 2022

Background: The purpose of this study was to evaluate the composition of the crystal phases of various calcium silicate-based materials (CSMs): ProRoot white MTA^Ⓡ (mineral trioxide aggregate) (WMTA), Ortho MTA^Ⓡ (OM), Endocem MTA^Ⓡ (EM), Retro MTA^Ⓡ (RM), Endocem Zr^Ⓡ (EN-Z), Biodentine^TM (BD), EZ-seal^TM (EZ), and OrthoMTA III (OM3). Methods: In a sample holder, 5 g of the powder sample was placed and the top surface of the material was packed flat using a sterilized glass slide. The prepared slides were mounted on an X-ray diffraction (XRD) instrument (D8 Advance; Bruker AXS GmbH, Germany). The X-ray beam 2θ angle range was set at 10~90° and scanned at 1.2° per minute. The Cu X-ray source set to operate at 40 kV and 40 mA in the continuous mode. The peaks in the diffraction pattern of each sample were analyzed using the software Diffrac (version 2.1). Then, the peaks were compared and matched with those of standard materials in the corresponding Powder Diffraction File (PDF-2, JCPDS International Center for Diffraction Data). A powder samples of the materials were analyzed using XRD and the peaks in diffraction pattern were compared to the Powder Diffraction File data. Results: Eight CSMs showed a similar diffraction pattern because their main component was calcium silicate. Eight CSMs showed similar diffraction peaks because calcium silicate was their main component. Two components were observed to have been added as radiopacifiers: bismuth oxide was detected in WMTA, OM, and EM while zirconium oxide was detected in RM, EN-Z, BD, EZ, and OM3. Unusual patterns were detected for the new material, OM3, which had strong peaks at low angles. Conclusion: It was caused by the presence of Brushite, which is believed to have resulted in crystal growth in a particular direction for a specific purpose.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2030-2052
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• 2023

Analysis of a bipartite (two-mode) network is a significant research area to understand the formation of social communities, economic systems, drug side effect topology, etc. in complex information systems. Most of the previous works talk about a projection-based model or latent feature model, which predicts the link based on singular similarity. The projection-based models suffer from the loss of structural information in the projected network and the latent feature is hardly present. This work proposes a novel method for link prediction in the bipartite network based on an ensemble of composite similarities, overcoming the issues of model-based and latent feature models. The proposed method analyzes the structure, neighborhood nodes as well as latent attributes between the nodes to predict the link in the network. To illustrate the proposed method, experiments are performed with five real-world data sets and compared with various state-of-art link prediction methods and it is inferred that this method outperforms with ~3% to ~9% higher using area under the precision-recall curve (AUC-PR) measure. This work holds great significance in the study of biological networks, e-commerce networks, complex web-based systems, networks of drug binding, enzyme protein, and other related networks in understanding the formation of such complex networks. Further, this study helps in link prediction and its usability for different purposes ranging from building intelligent systems to providing services in big data and web-based systems.

• Proceedings of the ESK Conference
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• 1997.04a
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• pp.56-60
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• 1997

The study of human erroneous actions has traditionally taken place along two different lines of approach. One has been concerned with finding and explaining the causes of erroneous actions, such as studies in the psychology of "error". The other has been concerned with the qualitative and quantitative prediction of possible erroneous actions, exemplified by the field of human reliability analysis (HRA). Another distinction is also that the former approach has been dominated by an academic point of view, hence emphasising theories, models, and experiments, while the latter has been of a more pragmatic nature, hence putting greater emphasis on data and methods. We have been developing a method to make predictions about error modes. The input to the method is a detailed task description of a set of scenarios for an experiment. This description is then analysed to characterise thd nature of the individual task steps, as well as the conditions under which they must be carried out. The task steps are expressed in terms of a predefined set of cognitive activity types. Following that each task step is examined in terms of a systematic classification of possible error modes and the likely error modes are identified. This effectively constitutes a qualitative analysis of the possibilities for erroneous action in a given task. In order to evaluate the accuracy of the predictions, the data from a large scale experiment were analysed. The experiment used the full-scale nuclear power plant simulator in the Halden Man-Machine Systems Laboratory (HAMMLAB) and used six crews of systematic performance observations by experts using a pre-defined task description, as well as audio and video recordings. The purpose of the analysis was to determine how well the predictions matiched the actually observed performance failures. The results indicated a very acceptable rate of accuracy. The emphasis in this experiment has been to develop a practical method for qualitative performance prediction, i.e., a method that did not require too many resources or specialised human factors knowledge. If such methods are to become practical tools, it is important that they are valid, reliable, and robust.

• Atmosphere
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• v.33 no.1
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• pp.1-20
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• 2023

Holding the longest observation data from April 1904, Busan is one of the essential points to understand the climate variability of the Korean Peninsula without missing data since implementing the modern weather observation of the South Korea. Busan is featured by coastal areas and affected by various climate factors and fluctuations. This study aims to investigate climate variability and changes in climatic variables, extremes, and several weather indexes. The statistically significant change points in daily mean rainfall intensity and temperature were found in 1964 and 1965. Based on the change point detection, 117 years were divided into two periods for daily mean rainfall intensity and temperature, respectively. In the long-term temperature analysis of Busan, the increasing trend of the daily maximum temperature during the period of 1965~2021 was larger than the daily mean temperature and the daily minimum temperature. Applying Ensemble Empirical Mode Decomposition, daily maximum temperature is largely affected by the decadal variability compared to the daily mean and minimum temperature. In addition, the trend of daily precipitation intensity from 1964~2021 shows a value of about 0.50 mm day^-1, suggesting that the rainfall intensity has increased compared to the preceding period. The results in extremes analysis demonstrate that return values of both extreme temperatures and precipitation show higher values in the latter than in the former period, indicating that the intensity of the current extreme phenomenon increases. For Wet-Bulb Globe Temperature (effective humidity), increasing (decreasing) trend is significant in Busan with the second (third)-largest change among four stations.

• Geomechanics and Engineering
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• v.38 no.4
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• pp.381-395
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• 2024

With the wide application of urban subway tunnels, the foundation pits of new stations and existing subway tunnels are becoming increasingly close, and even zero-distance close-fitting construction has taken place. To optimize the construction support scheme, the existing tunnel's vertical displacement is theoretically analyzed using the two-stage analysis method to understand the action mechanism of the construction of zero-distance deep large foundation pits on both sides of the existing stations; a three-dimensional numerical calculation is also performed for further analysis. First, the additional stress field on the existing tunnel caused by the unloading of zero-distance foundation pits on both sides of the tunnel is derived based on the Mindlin stress solution of a semi-infinite elastic body under internal load. Then, considering the existing subway tunnel's joints, shear stiffness, and shear soil deformation effect, the tunnel is regarded as a Timoshenko beam placed on the Kerr foundation; a sixth-order differential control equation of the tunnel under the action of additional stress is subsequently established for solving the vertical displacement of the tunnel. These theoretical calculation results are then compared with the numerical simulation results and monitoring data. Finally, an optimized foundation pit support scheme is obtained considering the pit corner effect and external corner failure mode. The research shows a high consistency between the monitoring data,analytical and numerical solution, and the closer the tunnel is to the foundation pit, the more uplift deformation will occur. The internal corner of the foundation pit can restrain the deformation of the tunnel and the retaining structure, while the external corner can cause local stress concentration on the diaphragm wall. The proposed optimization scheme can effectively reduce construction costs while meeting the safety requirements of foundation pit support structures.

• Economic and Environmental Geology
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• v.19 no.spc
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• pp.193-206
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• 1986

A number of auriferous veins occur in the Precambrian metamorphic terrain from Chungju to Mugeug district. These gold (-silver) deposits consist mainly of the fissure-filling quartz veins intruding the Precambrian gneiss or schist and Jurassic or Cretaceous granite. These gold (-silver) deposits can be 'divided into two mineralization epochs, (a) gold-rich veins related to Daebo igneous activity, and (b) gold-silver veins related to Bulgugsa igneous activity. These two groups of ore deposits with different generation can be characterized by the mode of occurrence of ore vein and the ore mineral associations. The auriferous quartz veins of Taechang and Boryeon mines associated with late Jurassic igneous activity are massive in character, and show the simple mineral assemblages and low Ag/Au ratio in the ores, representing a single mineralization system. The ore minerals are predominantly quartz containing minor or trace amonts of pyrrhotite, sphalerite, galena, pyrite, chalcopyrite and electrum. Electrum is closely associated with pyrrhotite and has chemical compositions from 61.4 to 78.5 atomic % Au. Fluid inclusion data suggest that ore minerals were deposited at temperatures between 238 and $390^{\circ}C$ from $CO_2$-rich fluids. The gold and/or silver-bearing quartz veins of Geumwang mine related to middle Cretaceous igneous activity are characterized by the multistage history, diverse mineral assemblages with high Ag/Au ratio in the ores. The ores of Geumwang mine have two contrasting mineral assemblages (1) pyrite+galena+sphalerite+arsenopyrite+electrum+argentite, representing the higher gold mineralization, and (2) pyrite+chalcopyrite+ galena +sphalerite+ arsenopyrite+silver sulfosalts+ electrum+ native silver+argentite, representing the higher silver mineralization. Electrum is closely associated with pyrite and has chemical compositions from 11.2 to 49.9 atomic % Au. The depositional environment during the higher gold mineralization can be estimated as the range of both temperature and sulfur fugacity, T= $200{\sim}300^{\circ}C$, log f ($S_2$) = $10^{-10}{\sim}10^{-15}$. The higher silver mineralization may be interpreted to have formed a range of falling temperature ($150{\sim}200^{\circ}C$) and low sulfur fugacity($10^{-10}{\sim}10^{-15}$). These temperature data are consistent with homogenization temperatures of fluId inclusions in quartz. Thus, the gold veins related to the Daebo igneous activity may be formed by the environment of higher temperature and pressure than the gold-silver veins associated with the Bulgugsa igneous activity.

• Korean Journal of Plant Taxonomy
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• v.42 no.4
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• pp.260-266
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• 2012

Because the embryological features of Jeffersonia dubia are poorly understood, we conducted the first embryological study comparing it to other related genera of Berberidaceae. Important embryological features of J. dubia are as follows: the anther is tetrasporangiate, anther wall formation confirms basic type, glandular tapetum cells are two nucleate, the epidermis persistent, and the endothecium develops fibrous thickenings, anther dehiscence by two valves, meiosis in a microspore mother cell is accompanied by simultaneous cytokinesis, microspore tetrads are usually tetrahedral, pollen grains two cells at the time of anthesis. The ovule is bitegmic, anatropous and crassinucellate, archesporium single celled, development of the embryo sac Polygonum type, a mature embryo sac is ellipsoidal in shape. Endosperm formation is of Nuclear type and embryogeny Onagrad type. Seeds are arillate and seed coat exotestal type. Embryological comparisons showed that Jeffersonia resemble to Epimedium and Vancouveria rather than Berberis and Mahonia in some features, like as number of tapetal cells, cytokinesis in meiosis, and thickness of exotesta. It also resembles to Gymnospermium in mode of anther wall formation, number of tapetal cells, formation of nucellar cap, and nature of antipodal cells. Nevertheless, Jeffersonia and Gymnospermium differ from several other embryological features and molecular data too. Therefore, embryological evidences support that Jeffersonia is closely related with Epimedium and Vancouveria.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.495-503
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• 2014

In recent days, a study of the intrusion detection system collecting and analyzing network data, packet or logs, has been actively performed to response the network threats in computer security fields. In particular, Bayesian network has advantage of the inference functionality which can infer with only some of provided data, so studies of the intrusion system based on Bayesian network have been conducted in the prior. However, there were some limitations to calculate high detection performance because it didn't consider the problems as like complexity of the relation among network packets or continuos input data processing. Therefore, in this paper we proposed two methodologies based on K-menas clustering to improve detection rate by reforming the problems of prior models. At first, it can be improved by sophisticatedly setting interval range of nodes based on K-means clustering. And for the second, it can be improved by calculating robust CPT through applying weighted-leaning based on K-means clustering, too. We conducted the experiments to prove performance of our proposed methodologies by comparing K_WTAN_EM applied to proposed two methodologies with prior models. As the results of experiment, the detection rate of proposed model is higher about 7.78% than existing NBN(Naive Bayesian Network) IDS model, and is higher about 5.24% than TAN(Tree Augmented Bayesian Network) IDS mode and then we could prove excellence our proposing ideas.

• Korean Journal of Plant Taxonomy
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• v.35 no.4
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• pp.295-311
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• 2005

Starch gel electrophoretic studies using 24 populations of five Korean Orostachys species were conducted to investigate allozyme variation and to test hypotheses of systematic relationships among species. The resulting phenogram showed that the populations of five Korean Orostachys species were divided into two major groups. And they were concordant with molecular and morphological data in suggesting that Orostachys was divided into two groups corresponding to the subsect. Appendiculatae and subsect. Orostachys. The low genetic identities among Korean Orostachys species indicated that the species of Orostachys have diverged gradually through the model of geographical species. Comparing the previous genetic data from the species with similar life history and mode of reproduction, most of Korean Orostachys species revealed a significant low genetic variation, while the widespread O. japonicus showed a relatively high genetic variation among the Korean species. This kind of genetic variation pattern might be the results of the isolated habitats, limited numbers of individuals within the populations, destruction of habitats, inbreeding and asexual reproduction in Korean Orostachys populations. The Jungdongjin population (POP 21) of O. malocophyllus was genetically unrelated with remaining populations of the same species, and this interpretation was consistent to the results from the previous palynological and morphological studies. Our allozyme data supported the taxonomic treatment of recently proposed taxa, O. iwarenge (Makino) Hara for. magnus and O. margaritifolius.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.137-148
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• 2014

Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used