• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.5
• /
• pp.613-621
• /
• 2019

In the case of door locks most widely used in the market, the most used area as a one-dimensional problem is worn out, and a worn area which does not use a special attack method enables password guessing. To solve this problem, various methods such as a keypad for randomly displaying numbers are introduced, but this is also not completely safe. The common feature of all the solutions so far is that the keypad area is fixed. In this paper, we consider that point in reverse and create a new area smaller than the entire area in the entire area of the keypad, making the keypad of the new area move randomly, thereby preventing the password from being deduced. When using this technique, a new type of keypad is proposed for the first time because of the impossibility of a shoulder surfing attack even though the number of keypad is left as it is.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.18 no.4
• /
• pp.100-108
• /
• 2019

In this paper, a new stacked element pressure sensor has proposed for heartbeat and respiration measurement. This device can be directly attached to an individual's chest; heartbeat and respiration are detected by the pulsatile vibration and deformation of the chest. A key feature of the device is the simultaneous measurement of heart rate and respiration. The structure of the sensor consists of two stacked elements, in which one element includes one polyvinylidene fluoride (PVDF) thin film bonded on polydimethylsiloxane (PDMS) substrate. In addition, for the measurement and signal processing, the electric circuit and the filter are simply constructed with an OP-amp, resistance, and a capacitor. One element (element1, PDMS) maximizes the respiration signal; the other (element2, PVDF) is used to measure heartbeat. Element1 and element2 had sensitivity of 0.163V/N and 0.209V/N, respectively, and element2 showed improved characteristics compared with element1 in response to force. Thus, element1 and element2 were optimized for measuring respiration heart rate, respectively. Through mechanical and vivo human tests, this sensor shows the great potential to optimize the signals of heartbeat and respiration compared with commercial devices. Moreover, the proposed sensor is flexible, light weight, and low cost. All of these characteristics illustrate an effective piezoelectric pressure sensor for heartbeat and respiration measurements.

• Journal of the Korean Physical Society
• /
• v.73 no.12
• /
• pp.1821-1826
• /
• 2018

Uniformity is a key feature of state-of-the-art infrared focal planed array (IRFPA) and infrared imaging system. Unlike traditional infrared telescope facility, a ground-based infrared radiant characteristics measurement system with an IRFPA not only provides a series of high signal-to-noise ratio (SNR) infrared image but also ensures the validity of radiant measurement data. Normally, a long integration time tends to produce a high SNR infrared image for infrared radiant characteristics radiometry system. In view of the variability of and uncertainty in the measured target's energy, the operation of switching the integration time and attenuators usually guarantees the guality of the infrared radiation measurement data obtainted during the infrared radiant characteristics radiometry process. Non-uniformity correction (NUC) coefficients in a given integration time are often applied to a specified integration time. If the integration time is switched, the SNR for the infrared imaging will degenerate rapidly. Considering the effect of the SNR for the infrared image and the infrared radiant characteristics radiometry above, we propose a-wide-dynamic-range NUC algorithm. In addition, this essasy derives and establishes the mathematical modal of the algorithm in detail. Then, we conduct verification experiments by using a ground-based MWIR(Mid-wave Infared) radiant characteristics radiometry system with an Ø400 mm aperture. The experimental results obtained using the proposed algorithm and the traditional algorithm for different integration time are compared. The statistical data shows that the average non-uniformity for the proposed algorithm decreased from 0.77% to 0.21% at 2.5 ms and from 1.33% to 0.26% at 5.5 ms. The testing results demonstrate that the usage of suggested algorithm can improve infrared imaging quality and radiation measurement accuracy.

• Journal of English Language & Literature
• /
• v.58 no.2
• /
• pp.279-304
• /
• 2012

Since the publication of Foucault's Discipline and Punish, theatricality has become one of the key concepts in New Historicism. By defining theatricality as the most definitive feature of early modern society and culture, New Historicists have promoted the idea that theatrical practices in every day life were eventually replaced by textual practices as the western society started to undergo modernization with the advent of print culture and technologies. This paper questions this linear model of English literature, the shift of literary practices from theatricality to textuality in the event of modernization, by closely looking at the ways in which newsbooks and playlets during the English civil wars appealed to their target readers. The early print-based literary commodities during the English civil war (i.e. newsbooks and playlets) were able to win the attention of their audience not by breaking away from theatrical energy and creativity but instead by embracing and taking advantage of them through the use of dramatic conventions, dialogues, and many others. The newsbooks and the playlets during the time, however, did not simply replicate the dramatic forms and experiences of the previous generation. Instead, as the case study of Craftie Cromwell exemplifies, they went further to produce a different mode of theatricality by reshaping everyday lives into serialized drama, whose resolution is always already delayed and postponed into the ever-receding future. In conclusion, the study of the newsbook and playlets during the civil wars suggests that the textuality of modern times, materialized in print forms, have been co-evolved with the development of new theatricality, whose contents and forms are susceptible to the changes of everyday reality.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.21 no.4
• /
• pp.115-124
• /
• 2011

There has been significant research in security technology such as e-passport standards, as e-passports have been introduced internationally. E-passports combine the latest security technologies such as smart card, public key infrastructure, and biometric recognition, so that these technologies can prevent unauthorized copies and counterfeits. Biometric information stored in e-passports is the most sensitive personal information, and it is expected to bring the highest risk of damages in case of its forgery or duplication. The present e-passport standards cannot handle security features that verify whether its biometric information is copied or not. In this paper, we propose an e-passport security technology in which biometric watermarking is used to prevent the copy of biometric information in the e-passport. The proposed method, biometric watermarking, embeds the invisible date of acquisition into the original data during the e-passport issuing process so that the human visual system cannot perceive its invisibly watermarked information. Then the biometric sample, having its unauthorized copy, is retrieved at the moment of reading the e-passport from the issuing database. The previous e-passport security technology placed an emphasis on both access control readers and anti-cloning chip features, and it is expected that the proposed feature, copy protection of biometric information, will be demanded as the cases of biometric recognition to verify personal identity information has increased.

• Design Convergence Study
• /
• v.19 no.2
• /
• pp.107-122
• /
• 2020

"lux et sonitus" is an audiovisual art exhibition series with an artistic combination of music and video at its center. Since its first introduction in 2013, the series have been held five times under the theme of "exhibition of music", presenting works featuring both audio and visual media in an effort to explore the key issues in the field of audiovisual art. In addition to the previous achievement of the exhibition, recent works from the series feature new concepts that explore the possibility of expanding the realm of synesthesia. In this paper, details of the entire series are summarized. In addition, theoretical background behind creative results of the series is analyzed in the context of music, synesthesia and space found in Nam June Paik's audiovisual artwork as a source of inspiration. This will contribute to establishing a vision for the creation/analysis of audiovisual art in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.5
• /
• pp.1814-1828
• /
• 2021

Low-light image enhancement is a key technique to overcome the quality degradation of photos taken under scotopic vision illumination conditions. The degradation includes low brightness, low contrast, and outstanding noise, which would seriously affect the vision of the human eye recognition ability and subsequent image processing. In this paper, we propose an approach based on deep learning and Retinex theory to enhance the low-light image, which includes image decomposition, illumination prediction, image reconstruction, and image optimization. The first three parts can reconstruct the enhanced image that suffers from low-resolution. To reduce the noise of the enhanced image and improve the image quality, a super-resolution algorithm based on the Laplacian pyramid network is introduced to optimize the image. The Laplacian pyramid network can improve the resolution of the enhanced image through multiple feature extraction and deconvolution operations. Furthermore, a combination loss function is explored in the network training stage to improve the efficiency of the algorithm. Extensive experiments and comprehensive evaluations demonstrate the strength of the proposed method, the result is closer to the real-world scene in lightness, color, and details. Besides, experiments also demonstrate that the proposed method with the single low-light image can achieve the same effect as multi-exposure image fusion algorithm and no ghost is introduced.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.33 no.2
• /
• pp.75-95
• /
• 2022

This study was carried out with the aim of analyzing the development and functional changes of Webdewey, which has become a basic tool of classification learning, analyzing it in terms of usability for learners, and suggesting specific ways to improve WebDewey's usability. In order to achieve this research objective, the concepts and principles of UI and usability were first laid out, and Webdewey's structure and key functions were analyzed. Since then, Webdewey's media changes and periodical feature changes have been analyzed. In addition, an opinion survey was conducted on the usability of WebDewey among learners who used WebDewey in the learning process, and proposed ways to improve WebDewey's usability based on the implications and direction of improvement derived from it. In terms of UI, proposals have been made to introduce display methods, visualization devices, the advantages of printed versions, and the development of Korean versions. In terms of the 'Create built number' function, suggestions have been made to improve usability in terms of basic number selection, composite route guidance and error message provision, new reference and route construction, screen and button design, and built-number component guidance.

• The Korean Journal of Applied Statistics
• /
• v.35 no.5
• /
• pp.667-684
• /
• 2022

Gene expression data present the level of mRNA abundance of each gene, and analyses of gene expressions have provided key ideas for understanding the mechanism of diseases and developing new drugs and therapies. Nowadays high-throughput technologies such as DNA microarray and RNA-sequencing enabled the simultaneous measurement of thousands of gene expressions, giving rise to a characteristic of gene expression data known as high dimensionality. Due to the high-dimensionality, learning models to analyze gene expression data are prone to overfitting problems, and to solve this issue, dimension reduction or feature selection techniques are commonly used as a preprocessing step. In particular, we can remove irrelevant and redundant genes and identify important genes using gene selection methods in the preprocessing step. Various gene selection methods have been developed in the context of machine learning so far. In this paper, we intensively review recent works on gene selection methods using machine learning approaches. In addition, the underlying difficulties with current gene selection methods as well as future research directions are discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.1
• /
• pp.16-37
• /
• 2022

Accurate liver segment segmentation based on radiological images is indispensable for the preoperative analysis of liver tumor resection surgery. However, most of the existing segmentation methods are not feasible to be used directly for this task due to the challenge of exact edge prediction with some tiny and slender vessels as its clinical segmentation criterion. To address this problem, we propose a novel deep learning based segmentation model, called Boundary-Aware Dual Attention Liver Segment Segmentation Model (BADA). This model can improve the segmentation accuracy of liver segments with enhancing the edges including the vessels serving as segment boundaries. In our model, the dual gated attention is proposed, which composes of a spatial attention module and a semantic attention module. The spatial attention module enhances the weights of key edge regions by concerning about the salient intensity changes, while the semantic attention amplifies the contribution of filters that can extract more discriminative feature information by weighting the significant convolution channels. Simultaneously, we build a dataset of liver segments including 59 clinic cases with dynamically contrast enhanced MRI(Magnetic Resonance Imaging) of portal vein stage, which annotated by several professional radiologists. Comparing with several state-of-the-art methods and baseline segmentation methods, we achieve the best results on this clinic liver segment segmentation dataset, where Mean Dice, Mean Sensitivity and Mean Positive Predicted Value reach 89.01%, 87.71% and 90.67%, respectively.