• ETRI Journal
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• v.41 no.4
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• pp.437-451
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• 2019

Outlier detection techniques play an important role in enhancing the reliability of data communication in wireless sensor networks (WSNs). Considering the importance of outlier detection in WSNs, many outlier detection techniques have been proposed. Unfortunately, most of these techniques still have some potential limitations, that is, (a) high rate of false positives, (b) high time complexity, and (c) failure to detect outliers online. Moreover, these approaches mainly focus on either temporal outliers or spatial outliers. Therefore, this paper aims to introduce novel algorithms that successfully detect both temporal outliers and spatial outliers. Our contributions are twofold: (i) modifying the Hampel Identifier (HI) algorithm to achieve high accuracy identification rate in temporal outlier detection, (ii) combining the Gaussian process (GP) model and graph-based outlier detection technique to improve the performance of the algorithm in spatial outlier detection. The results demonstrate that our techniques outperform the state-of-the-art methods in terms of accuracy and work well with various data types.

• Knowledge Management Research
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• v.20 no.2
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• pp.1-24
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• 2019

This tutorial introduces procedures and methods for performing structural equation modeling using R. To do this, we present advanced analysis methods based on structural equation model such as mediation effect analysis, moderation effect analysis, moderated mediation effect analysis, and multiple-group analysis with R program code using R lavaan package that supports structural equation modeling. R is flexible and scalable, unlike traditional commercial statistical packages. Therefore, new analytical techniques are likely to be implemented ahead of any other statistical package. From this point of view, R will be a very appropriate choice for applying new analytical techniques or advanced techniques that researchers need. Considering that various studies in the social sciences are applying structural equations modeling techniques and increasing interest in open source R, this tutorial is expected to be useful for researchers who are looking for alternatives to existing commercial statistical packages.

• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3491-3504
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• 2021

This paper reports on the state-of-the-art of the main non-destructive assay (NDA) techniques usually used for in-situ radiological characterization of nuclear facilities subject to a decommissioning programme. For the sake of clarity and coherence, they have been classified as environmental radiation monitoring, surface contamination measurements, gamma spectrometry, passive neutron counting and radiation cameras. Particular mention is also made here to the various challenges that each of these techniques must currently overcome, together with the formulation of some proposals for a potential evolution in the future.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.33-40
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• 2023

Machine-learning techniques are discovering effective performance on data analytics. Classification and regression are supported for prediction on different kinds of data. There are various breeds of classification techniques are using based on nature of data. Threshold determination is essential to making better model for unlabelled data. In this paper, threshold value applied as range, based on min-max normalization technique for creating labels and multiclass classification performed on rainfall data. Binary classification is applied on autism data and classification techniques applied on child abuse data. Performance of each technique analysed with the evaluation metrics.

• Journal of Oral Medicine and Pain
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• v.39 no.4
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• pp.119-126
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• 2014

This review provides an overview of the most commonly used dental age estimation techniques which focus on radiological methods in Korean adults. The literature from 1995 through July 31, 2014, was searched, using PubMed, for publications in English language. In PubMed, the keywords 'tooth' OR 'dental' AND 'pulp' AND 'age estimation' were searched. Inclusion criteria was comprised of the following: the subjects were living adults and dental radiography (excluded computed tomography [CT] and cone-beam CT) was used to measure the pulpal size. Twenty articles that met the criteria were selected. The method of age estimation using dental radiographs for measuring pulp and tooth size was represented in all studies. The methods were assorted into three categories generally; Kvaal's, Ikeda's and Cameriere's methods. Those methods had certain limitations such as large error range and low correlation coefficient depending on populations, type of employed teeth and particular method. Various techniques and many studies have been published for age estimation from human teeth using dental radiographs, but those techniques showed various predictability and reliability. Therefore, future studies on larger samples with well-distributed age group using not only existing techniques but new techniques are necessary for deriving convincing results.

• The Journal of Advanced Prosthodontics
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• v.6 no.6
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• pp.498-504
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• 2014

PURPOSE. Dental implant has gained clinical success over last decade with the major drawback related to osseointegration as properties of metal (Titanium) are different from human bone. Currently implant procedures include endosseous type of dental implants with nanoscale surface characteristics. The objective of this review article is to summarize the role of nanotopography on titanium dental implant surfaces in order to improve osseointegration and various techniques that can generate nanoscale topographic features to titanium implants. MATERIALS AND METHODS. A systematic electronic search of English language peer reviewed dental literature was performed for articles published between December 1987 to January 2012. Search was conducted in Medline, PubMed and Google scholar supplemented by hand searching of selected journals. 101 articles were assigned to full text analysis. Articles were selected according to inclusion and exclusion criterion. All articles were screened according to inclusion standard. 39 articles were included in the analysis. RESULTS. Out of 39 studies, seven studies demonstrated that bone implant contact increases with increase in surface roughness. Five studies showed comparative evaluation of techniques producing microtopography and nanotopography. Eight studies concluded that osteoblasts preferably adhere to nano structure as compared to smooth surface. Six studies illustrated that nanotopography modify implant surface and their properties. Thirteen studies described techniques to produce nano roughness. CONCLUSION. Modification of dental osseous implants at nanoscale level produced by various techniques can alter biological responses that may improve osseointegration and dental implant procedures.

• Clinical and Experimental Pediatrics
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• v.63 no.6
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• pp.232-236
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• 2020

Background: Children today get access to smartphones at an early age. However, their ability to use mobile apps has not yet been studied in detail. Purpose: This study aimed to assess the ability of children aged 2-8 years to perform touchscreen gestures and follow prompting techniques, i.e., ways apps provide instructions on how to use them. Methods: We developed one mobile app to test the ability of children to perform various touchscreen gestures and another mobile app to test their ability to follow various prompting techniques. We used these apps in this study of 90 children in a kindergarten and a primary school in New Delhi in July 2019. We noted the touchscreen gestures that the children could perform and the most sophisticated prompting technique that they could follow. Results: Two- and 3-year-old children could not follow any prompting technique and only a minority (27%) could tap the touchscreen at an intended place. Four- to 6-year-old children could perform simple gestures like a tap and slide (57%) and follow instructions provided through animation (63%). Seven- and 8-year-old children could perform more sophisticated gestures like dragging and dropping (30%) and follow instructions provided in audio and video formats (34%). We observed a significant difference between the number of touchscreen gestures that the children could perform and the number of prompting techniques that they could follow (F=544.0407, P<0.05). No significant difference was observed in the performance of female versus male children (P>0.05). Conclusion: Children gradually learn to use mobile apps beginning at 2 years of age. They become comfortable performing single-finger gestures and following nontextual prompting techniques by 8 years of age. We recommend that these results be considered in the development of mobile apps for children.

• Journal of Plant Biotechnology
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• v.37 no.4
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• pp.343-356
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• 2010

Plant micropropagation techniques include bud cultures using apical or axillary buds, organogenesis through callus culture or adventitious bud induction, and somatic embryogenesis. In Korea Forest Research Institute (KFRI), the first tissue culture trial in woody plant was initiated from the bud culture of hybrid poplars (Populus alba x P. glandulosa) in 1978. Since then several mass propagation techniques have developed from conifer and hardwood species, resulting in allowing practical application to Poplars, Birches and some oak species. In addition, useful micropropagation and genetic resources conservation techniques were established in some rare and endangered tree species including Abeliophyllum distichum. Among various in vitro propagation techniques, somatic embryogenesis is known to be the most efficient plant regeneration system. Since the first somatic embryo induction was reported in Tilia amurensis by KFRI in 1986, various protocols for direct or indirect somatic embryogenesis systems have developed in conifer and hardwood species including Larix leptolepis, Pinus rigida x P. taeda F1, Kalopanax septemlobus and Liliodendron tulipifera, etc. However, most of these technologies have been developed using juvenile tissues, i.e. immature zygotic embryos or mature embryos. Therefore it has been difficult to directly application to tree breeding program due to their unproven genetic background. Recently remarkable progresses and new approaches have been achieved in mature tree somatic embryogenesis. In this article we reviewed several micropropagation techniques, which have been mainly developed by KFRI and recent international progresses.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.181-192
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• 2022

The emergence of new malware is incapacitating existing signature-based malware detection techniques., and applying various anti-analysis techniques makes it difficult to analyze. Recent studies related to signature-based malware detection have limitations in that malware creators can easily bypass them. Therefore, in this study, we try to build a machine learning model that can detect and classify the anti-analysis techniques of packers applied to malware, not using the characteristics of the malware itself. In this study, the n-gram opcodes are extracted from the malicious binary to which various anti-analysis techniques of the commercial packers are applied, and the features are extracted by using TF-IDF, and through this, each anti-analysis technique is detected and classified. In this study, real-world malware samples packed using The mida and VMProtect with multiple anti-analysis techniques were trained and tested with 6 machine learning models, and it constructed the optimal model showing 81.25% accuracy for The mida and 95.65% accuracy for VMProtect.

• Journal of Environmental Health Sciences
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• v.50 no.2
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• pp.113-124
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• 2024

Background: The increasing need to minimize animal testing has sparked interest in alternative methods with more humane, cost-effective, and time-saving attributes. In particular, in silico-based computational toxicology is gaining prominence. Adverse outcome pathway (AOP) is a biological map depicting toxicological mechanisms, composed of molecular initiating events (MIEs), key events (KEs), and adverse outcomes (AOs). To understand toxicological mechanisms, predictive models are essential for AOP components in computational toxicology, including molecular structures. Objectives: This study reviewed the literature and investigated previous research cases related to AOP and in silico methodologies. We describe the results obtained from the analysis, including predictive techniques and approaches that can be used for future in silico-based alternative methods to animal testing using AOP. Methods: We analyzed in silico methods and databases used in the literature to identify trends in research on in silico prediction models. Results: We reviewed 26 studies related to AOP and in silico methodologies. The ToxCast/Tox21 database was commonly used for toxicity studies, and MIE was the most frequently used predictive factor among the AOP components. Machine learning was most widely used among prediction techniques, and various in silico methods, such as deep learning, molecular docking, and molecular dynamics, were also utilized. Conclusions: We analyzed the current research trends regarding in silico-based alternative methods for animal testing using AOPs. Developing predictive techniques that reflect toxicological mechanisms will be essential to replace animal testing with in silico methods. In the future, since the applicability of various predictive techniques is increasing, it will be necessary to continue monitoring the trend of predictive techniques and in silico-based approaches.