• Journal of Korean Society of Transportation
• /
• v.26 no.4
• /
• pp.251-264
• /
• 2008

One of the crucial elements to fully facilitate the various benefits of intelligent transportation systems (ITS) is to obtain more reliable traffic monitoring in real time. To date, point and section-based traffic measurements have been available through existing surveillance technologies, such as loops and automatic vehicle identification (AVI) systems. However, seamless and more reliable traffic data are required for more effective traffic information provision and operations. Technology advancements including vehicle tracking and wireless communication enable the acceleration of the availability of individual vehicle travel information. This study presents a UBIquitous PRObe vehicle Surveillance System (UBIPROSS) using vehicle-to-vehicle (V2V) wireless communications. Seamless vehicle travel information, including origin-destination information, speed, travel times, and other data, can be obtained by the proposed UBIPROSS. A set of parameters associated with functional requirements of the UBIPROSS, which include the market penetration rate (MPR) of equipped vehicles, V2V communication range, and travel time update interval, are investigated by a Monte Carlo simulation- (MCS) based evaluation framework. In addition, this paper describes prototypical implementation. Field test results and identified technical issues are also discussed. It is expected that the proposed system would be an invaluable precursor to develop a next-generation traffic surveillance system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.37 no.1
• /
• pp.19-28
• /
• 2019

Images captured by drone have the advantage of quickly constructing spatial information in small areas and are applied to fields that require quick decision making. If an image registration technique that can automatically register the drone image on the ortho-image with the ground coordinate system is applied, it can be used for various analyses. In this study, a methodology for geo-referencing of a single image and sequential images using drones was proposed even if they differ in spatio-temporal resolution using linear features and distinct points. Through the method using linear features, projective transformation parameters for the initial geo-referencing between images were determined, and then finally the geo-referencing of the image was performed through the template matching for distinct points that can be extracted from the images. Experimental results showed that the accuracy of the geo-referencing was high in an area where relief displacement of the terrain was not large. On the other hand, there were some errors in the quantitative aspect of the area where the change of the terrain was large. However, it was considered that the results of geo-referencing of the sequential images could be fully utilized for the qualitative analysis.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.4
• /
• pp.1-9
• /
• 2021

In this paper, we propose a training algorithm of support vector machine (SVM) with a sensitive variable. Although machine learning models enable automatic decision making in the real world applications, regulations prohibit sensitive information from being used to protect privacy. In particular, the privacy protection of the legally protected attributes such as race, gender, and disability is compulsory. We present an efficient least square SVM (LSSVM) training algorithm using a fully homomorphic encryption (FHE) to protect a partial sensitive attribute. Our framework posits that data owner has both non-sensitive attributes and a sensitive attribute while machine learning service provider (MLSP) can get non-sensitive attributes and an encrypted sensitive attribute. As a result, data owner can obtain the encrypted model parameters without exposing their sensitive information to MLSP. In the inference phase, both non-sensitive attributes and a sensitive attribute are encrypted, and all computations should be conducted on encrypted domain. Through the experiments on real data, we identify that our proposed method enables to implement privacy-preserving sensitive LSSVM with FHE that has comparable performance with the original LSSVM algorithm. In addition, we demonstrate that the efficient sensitive LSSVM with FHE significantly improves the computational cost with a small degradation of performance.

• Journal of Broadcast Engineering
• /
• v.27 no.2
• /
• pp.228-239
• /
• 2022

In this paper, we propose an unmanned vehicle scratch detection deep learning model for car sharing services. Conventional scratch detection models consist of two steps: 1) a deep learning module for scratch detection of images before and after rental, 2) a manual matching process for finding newly generated scratches. In order to build a fully automatic scratch detection model, we propose a one-step unmanned scratch detection deep learning model. The proposed model is implemented by applying transfer learning and fine-tuning to the deep learning model that detects changes in satellite images. In the proposed car sharing service, specular reflection greatly affects the scratch detection performance since the brightness of the gloss-treated automobile surface is anisotropic and a non-expert user takes a picture with a general camera. In order to reduce detection errors caused by specular reflected light, we propose a preprocessing process for removing specular reflection components. For data taken by mobile phone cameras, the proposed system can provide high matching performance subjectively and objectively. The scores for change detection metrics such as precision, recall, F1, and kappa are 67.90%, 74.56%, 71.08%, and 70.18%, respectively.

• Journal of Daesoon Thought and the Religions of East Asia
• /
• v.1 no.2
• /
• pp.41-59
• /
• 2022

Caodaism is a new religion from Vietnam which began in late 1925 and spread rapidly across the French colony of Indochina. With a broad syncretic aim, the new faith sought to revivify Vietnamese religious traditions whilst also incorporating religious, literary, and spiritist influences from France. Like Catholicism, Caodaism kept a strong focus on its monotheistic nature and today Caodaists are eager to label their religion a monotheism. It will be argued here, however, that the syncretic nature of this new faith complicates this claim to a significant degree. To make this argument, we will consider here the nature of God in Caodaism through two central texts from two important stages in the life of the religion. The first is the canonized Compilation of Divine Messages which collects a range of spirit messages from God and some other divine voices. These were received in the early years of the faith. The second is a collection of sermons from 1948/9 that takes Caodaist believers on a tour of heaven, and which is entitled The Divine Path to Eternal Life. It will be shown that in the first text, God speaks in the mode of a fully omnipotent and omniscient supreme being. In the second text, however, we are given a view of paradise that is much more akin to the court of a Jade Emperor within an East Asian milieu. In these realms, the personalities of other beings and redemptive mechanisms claim much of our attention, and seem to be a competing center of power to that of God. Furthermore, God's consort, the Divine Mother, takes on a range of sacred creative prerogatives that do something similar. Additionally, cadres of celestial administrators; buddhas, immortals, and saints help with the operation of a cosmos which spins on with guidance from its own laws. These laws form sacred mechanisms, such as cycles of reincarnation and judgement. These operate not in the purview of God, but as part of the very nature of the cosmos itself. In this context, the dualistic, polytheistic, and even automatic nature of Caodaism's cosmos will be considered in terms of the way in which they complicate this religion's monotheistic claims. To conclude, this article seeks to demonstrate the precise relevance of the term 'monotheism' for this religion.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.46 no.9
• /
• pp.58-67
• /
• 2009

This paper presents a fully digital gain control system with a new high bandwidth and wide dynamic range power detector for DVB-S2 application. Because the peak-to-average power ratio (PAPR) of DVB-S2 system is so high and the settling time requirement is so stringent, the conventional closed-loop analog gain control scheme cannot be used. The digital gain control is necessary for the robust gain control and the direct digital interface with the baseband modem. Also, it has several advantages over the analog gain control in terms of the settling time and insensitivity to the process, voltage and temperature variation. In order to have a wide gain range with fine step resolution, a new AGC system is proposed. The system is composed of high-bandwidth digital VGAs, wide dynamic range power detectors with RMS detector, low power SAR type ADC, and a digital gain controller. To reduce the power consumption and chip area, only one SAR type ADC is used, and its input is time-interleaved based on four power detectors. Simulation and measurement results show that the new AGC system converges with gain error less than 0.25 dB to the desired level within $10{\mu}s$. It is implemented in a $0.18{\mu}m$ CMOS process. The measurement results of the proposed IF AGC system exhibit 80-dB gain range with 0.25-dB resolution, 8 nV/$\sqrt{Hz}$ input referred noise, and 5-dBm $IIP_3$ at 60-mW power consumption. The power detector shows the 35dB dynamic range for 100 MHz input.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.14 no.2
• /
• pp.104-109
• /
• 2010

Purpose: $[^{18}F]$Fallypride plays an effective radiotracer for the study of dopamine $D_2/D_3$ receptor occupancy, neuropsychiatric disorders and aging in humans. This tracer has the potential for clinical use, but automated labeling efficiency showed low radiochemical yields about 5~20% with relatively long labelling time of fluorine-18. In present study, we describe an improved automatic synthesis of [$^{18}F$]Fallypride using different base concentration for routine clinical use. Materials and Methods: Fully automated synthetic process of [$^{18}F$]Fallypride was perform using the TracerLab $FX_{FN}$ synthesizer under various labeling conditions and tosyl-fallypride was used as a precursor. [$^{18}F$]Fluoride was extracted with various concentration of $K_{2.2.2.}/K_2CO_3$ from $^{18}O$-enriched water trapped on the ion exchange cartridge. After azeotropic drying, the labeling reaction proceeded in $CH_3CN$ at $100^{\circ}C$ for 10 or 30 min. The reaction mixture was purified by reverse phase HPLC and collected organic solution was exchanged by tc-18 Sep-Pak for the clinically available solution. Results: The optimal labeling condition of [$^{18}F$]Fallypride in the automatic production was that 2 mg of tosyl-fallypride in acetonitrile (1 mL) was incubated at $100^{\circ}C$ for 10 min with $K_{2.2.2.}/K_2CO_3$ (11/0.8 mg). [$^{18}F$]Fallypride was obtained with high radiochemical yield about $66{\pm}1.4%$ (decay-corrected, n=28) within $51{\pm}1.2$ min including HPLC purification and solid-phase purification for the final formulation. Conclusion: [$^{18}F$]Fallypride was prepared with a significantly improved radiochemical yield with high specific activity and shorten synthetic time. In addition, this automated procedure provides the high reproducibility with no synthesis failures (n=28).

• Maxillofacial Plastic and Reconstructive Surgery
• /
• v.22 no.2
• /
• pp.164-173
• /
• 2000

The p16 protein is a cyclin dependent kinase inhibitor that inhibits cell cycle progression from $G_1$ phase to S phase in cell cycle. Many p16 gene mutations have been noted in many cancer-cell lines and in some primary cancers, and alterations of p16 gene function by DNA methylation have been noticed in various kinds of cancer tissues and cell-lines. There have been a large body of literature has accumulated indicating that abnormal patterns of DNA methylation (both hypomethylation and hypermethylation) occur in a wide variety of human neoplasma and that these aberrations of DNA methylation may play an important epigenetic role in the development and progression of neoplasia. DNA methylation is a part of the inheritable epigenetic system that influences expression or silencing of genes necessary for normal differentiation and proliferation. Gene activity may be silenced by methylation of up steream regulatory regions. Reactivation is associated with demethylation. Although evidence or a high incidence of p16 alterations in a variety of cell lines and primary tumors has been reported, that has been contested by other investigators. The precise mechanisms by which abnormal methylation might contribute to carcinogenesis are still not fully elucidated, but conceivably could involve the modulation of oncogene and other important regulatory gene expression, in addition to creating areas of genetic instability, thus predisposing to mutational events causing neoplasia. There have been many variable results of studies of head and neck squamous cell carcinoma(HNSCC). This investigation was studied on 13 primary HNSCC for p16 gene status by protein expression in immunohistochemistry, and DNA genetic/epigenetic analyzed to determine the incidence, the mechanisms, and the potential biological significance of its Inactivation. As methylation detection method of p16 gene, the methylation specific PCR(MSP) is sensitive and specific for methylation of any block of CpG sites in a CpG islands using bisulfite-modified DNA. The genomic DNA is modified by treatment with sodium bisulfate, which converts all unmethylated cytosines to uracil(thymidine). The primers designed for MSP were chosen for regions containing frequent cytosines (to distinguish unmodified from modified DNA), and CpG pairs near the 5' end of the primers (to provide maximal discrimination in the PCR between methylated and unmethylated DNA). The two strands of DNA are no longer complementary after bisulfite treatment, primers can be designed for either modified strand. In this study, 13 paraffin embedded block tissues were used, so the fragment of DNA to be amplified was intentionally small, to allow the assessment of methylation pattern in a limited region and to facilitate the application of this technique to samlples. In this 13 primary HNSCC tissues, there was no methylation of p16 promoter gene (detected by MSP and automatic sequencing). The p16 protein-specific immunohistochemical staining was performed on 13 paraffin embedded primary HNSCC tissue samples. Twelve cases among the 13 showed altered expression of p16 proteins (negative expression). In this study, The author suggested that low expression of p16 protein may play an important role in human HNSCC, and this study suggested that many kinds of genetic mechanisms including DNA methylation may play the role in carcinogenesis.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
• /
• 2000.06a
• /
• pp.16-23
• /
• 2000

The increasing functional needs of top-quality printing papers and packaging paperboards, and especially the rapid developments in electronic printing processes and various computer printers during past few years, set new targets and requirements for modern paper quality. Most of these paper grades of today have relatively high filler content, are moderately or heavily calendered , and have many coating layers for the best appearance and performance. In practice, this means that many of the traditional quality assurance methods, mostly designed to measure papers made of pure. native pulp only, can not reliably (or at all) be used to analyze or rank the quality of modern papers. Hence, introduction of new measurement techniques is necessary to assure and further develop the paper quality today and in the future. Paper formation , i.e. small scale (millimeter scale) variation of basis weight, is the most important quality parameter of paper-making due to its influence on practically all the other quality properties of paper. The ideal paper would be completely uniform so that the basis weight of each small point (area) measured would be the same. In practice, of course, this is not possible because there always exists relatively large local variations in paper. However, these small scale basis weight variations are the major reason for many other quality problems, including calender blacking uneven coating result, uneven printing result, etc. The traditionally used visual inspection or optical measurement of the paper does not give us a reliable understanding of the material variations in the paper because in modern paper making process the optical behavior of paper is strongly affected by using e.g. fillers, dye or coating colors. Futhermore, the opacity (optical density) of the paper is changed at different process stages like wet pressing and calendering. The greatest advantage of using beta transmission method to measure paper formation is that it can be very reliably calibrated to measure true basis weight variation of all kinds of paper and board, independently on sample basis weight or paper grade. This gives us the possibility to measure, compare and judge papers made of different raw materials, different color, or even to measure heavily calendered, coated or printed papers. Scientific research of paper physics has shown that the orientation of the top layer (paper surface) fibers of the sheet paly the key role in paper curling and cockling , causing the typical practical problems (paper jam) with modern fax and copy machines, electronic printing , etc. On the other hand, the fiber orientation at the surface and middle layer of the sheet controls the bending stiffness of paperboard . Therefore, a reliable measurement of paper surface fiber orientation gives us a magnificent tool to investigate and predict paper curling and coclking tendency, and provides the necessary information to finetune, the manufacturing process for optimum quality. many papers, especially heavily calendered and coated grades, do resist liquid and gas penetration very much, bing beyond the measurement range of the traditional instruments or resulting invonveniently long measuring time per sample . The increased surface hardness and use of filler minerals and mechanical pulp make a reliable, nonleaking sample contact to the measurement head a challenge of its own. Paper surface coating causes, as expected, a layer which has completely different permeability characteristics compared to the other layer of the sheet. The latest developments in sensor technologies have made it possible to reliably measure gas flow in well controlled conditions, allowing us to investigate the gas penetration of open structures, such as cigarette paper, tissue or sack paper, and in the low permeability range analyze even fully greaseproof papers, silicon papers, heavily coated papers and boards or even detect defects in barrier coatings ! Even nitrogen or helium may be used as the gas, giving us completely new possibilities to rank the products or to find correlation to critical process or converting parameters. All the modern paper machines include many on-line measuring instruments which are used to give the necessary information for automatic process control systems. hence, the reliability of this information obtained from different sensors is vital for good optimizing and process stability. If any of these on-line sensors do not operate perfectly ass planned (having even small measurement error or malfunction ), the process control will set the machine to operate away from the optimum , resulting loss of profit or eventual problems in quality or runnability. To assure optimum operation of the paper machines, a novel quality assurance policy for the on-line measurements has been developed, including control procedures utilizing traceable, accredited standards for the best reliability and performance.

• Journal of Intelligence and Information Systems
• /
• v.24 no.3
• /
• pp.1-19
• /
• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.