• Journal of IKEEE
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• v.24 no.3
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• pp.783-790
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• 2020

In this paper, the human detecting radar system for indoor security applications is proposed, and its FPGA-based implementation results are presented. In order to minimize the complexity and memory requirements of the computation, the top half of the spectrogram was used to extract features, excluding the feature extraction techniques that require complex computation, feature extraction techniques were proposed considering classification performance and complexity. In addition, memory requirements were minimized by designing a pipeline structure without storing the entire spectrogram. Experiments on human, dog and robot cleaners were conducted for classification, and 96.2% accuracy performance was confirmed. The proposed system was implemented using Verilog-HDL, and we confirmed that a low-area design using 1140 logics and 6.5 Kb of memory was possible.

• Parasites, Hosts and Diseases
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• v.47 no.3
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• pp.227-233
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• 2009

Local malaria transmission in the United Arab Emirates (UAE) came to an end in 1997. Nevertheless, UAE has been subjected to substantial importation of malaria cases from abroad, concerning both UAE nationals and immigrants from malarious countries with a total number of 2,119 cases in 2007. To evaluate a new DNA extraction technique using nested PCR, blood samples were collected from 132 individuals who presented to Infectious Diseases Department in Rashid Hospital, Dubai, and Central Department of Malaria Control with fever and persistent headache. Giemsa-stained blood films and ELISA test for malaria antibodies were carried out for detection of Plasmodium infection. Plasmodium infections were identified with the genus-specific primer set and species differentiation using nested PCR. A rapid procedure for diagnosis of malaria infections directly from dried blood spots using for the first time DNA extract from FTA Elute cards was evaluated in contrast to extraction techniques using FTA classic cards and rapid boiling technique. Our new simple technique for DNA extraction using FTA Elute cards was very sensitive giving a sensitivity of 100% compared to 94% using FTA classic cards and 62% in the rapid boiling technique. No complex preparation of blood samples was required prior to the amplification. The production cost of DNA isolation in our PCR assay was much less incomparable to that of other DNA extraction protocols. The nested PCR detected plasmodial infection and could differentiate P. falciparum from P. vivax, and also detected the mixed infection.

• Journal of the Korean Chemical Society
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• v.42 no.1
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• pp.36-41
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• 1998

In this study, the extraction of Co(Ⅱ) and Cu(Ⅱ) into chloroform solution of dithizone, distribution ratios, extractabilities and extraction rate constants of the metal complexes were compared in each case with which thiocyanate ion was or not used as the auxiliary ligand. The use of the thiocyanate ion increased threefold the distribution ratio for Co(Ⅱ) complex in a basic solution and twofold for Cu(Ⅱ) complex in a wide pH range. And the extractability was also augmented from about 90 to 99 for Co(Ⅱ) and from 95 to 99 for Cu(Ⅱ) in a given period. The extraction rate constants were $k_1\;:\;1.2{\times}10^5$, $k_2\;:\;1.34{\times}10^{17}\; mol^{-1}dm^3s^{-1}$ in case of Co(Ⅱ) and$k_1\;:\;1.1{\times}10^8$, $k_2\;:\;2.83{\times}10^{10}\; mol^{-1}dm^3s^{-1}$ in case of Cu(Ⅱ) on the extraction of dithizonate complexes into chloroform solution.

• Journal of the Semiconductor & Display Technology
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• v.21 no.1
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• pp.95-102
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• 2022

Since the organic light-emitting diodes (OLEDs) have been widely investigated as next-generation displays, it has been successfully commercialized as a flexible and rollable display. However, there is still wide room and demand to improve the device characteristics such as power efficiency and lifetime. To solve this issue, there has been a wide research effort, and among them, the internal and the external light extraction techniques have been attracted in this research field by its fascinating characteristic of material independence. In this study, a micro-nano composite structured external light extraction layer was demonstrated. A reactive ion etching (RIE) process was performed on the surfaces of hexagonally packed hemisphere micro-lens array (MLA) and randomly distributed sphere diffusing films to form micro-nano composite structures. Random nanostructures of different sizes were fabricated by controlling the processing time of the O₂ / CHF₃ plasma. The fabricated device using a micro-nano composite external light extraction layer showed 1.38X improved external quantum efficiency compared to the reference device. The results prove that the external light extraction efficiency is improved by applying the micro-nano composite structure on conventional MLA fabricated through a simple process.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.1
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• pp.64-73
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• 2011

Oil price prediction is an important issue for the regulators of the government and the related industries. When employing the time series techniques for prediction, however, it becomes difficult and challenging since the behavior of the series of oil prices is dominated by quantitatively unexplained irregular external factors, e.g., supply- or demand-side shocks, political conflicts specific to events in the Middle East, and direct or indirect influences from other global economical indices, etc. Identifying and quantifying the relationship between oil price and those external factors may provide more relevant prediction than attempting to unclose the underlying structure of the series itself. Technically, this implies the prediction is to be based on the vectoral data on the degrees of the relationship rather than the series data. This paper proposes a novel method for time series prediction of using Semi-Supervised Learning that was originally designed only for the vector types of data. First, several time series of oil prices and other economical indices are transformed into the multiple dimensional vectors by the various types of technical indicators and the diverse combination of the indicator-specific hyper-parameters. Then, to avoid the curse of dimensionality and redundancy among the dimensions, the wellknown feature extraction techniques, PCA and NLPCA, are employed. With the extracted features, a timepointspecific similarity matrix of oil prices and other economical indices is built and finally, Semi-Supervised Learning generates one-timepoint-ahead prediction. The series of crude oil prices of West Texas Intermediate (WTI) was used to verify the proposed method, and the experiments showed promising results : 0.86 of the average AUC.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.660-663
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• 2009

Consumers express how they evaluate what they purchased by writing reviews especially when they purchased products online. By analyzing the reviews about a product, it will be possible to find out what the consumers liked and disliked about the product. It will be also possible to identify the general consensus on what matters in purchaing certain product type such as a laptop if many reviews about many instances of a particular product type is analyzed. However, it takes a lot of time to manually analyzing the reviews. Thus, we propose to use two natural language processing oriented computational techniques to analyze a large number of reviews. The techniques are text classification and information extraction. We developed an review analysis system and conducted experiments against the reviews about the laptop computers posted on the Naver information portal.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.1 s.2
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• pp.75-84
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• 2003

Current techniques for road-traffic monitoring rely on sensors which have limited capabilities, are costly and disruptive to install. The use of video cameras coupled with computer vision techniques offers an attractive alternative to current sensors. Video based traffic monitoring systems are now being considered key points of advanced traffic management systems. In this paper, we propose the new method which extract the traffic information using video camera. The proposed method uses an adaptive updating scheme for background in order to reduce the false alarm rate due to various noises in images. also, the proposed extraction method of traffic information calculates the traffic volume ratio of vehicles passing through predefined detection area, which is defined by the length of profile occupied by cars over that of overall detection area. Then the ratio is used to define 8 different states of traffic and to interpret the state of vehicle flows. The proposed method is verified by an experiment using CCTV traffic data from urban area.

• Membrane and Water Treatment
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• v.7 no.3
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• pp.223-240
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• 2016

In this study, poly(vinyl-alcohol) and water insoluble ${\beta}$-cyclodextrin polymer (${\beta}$-CDP) cross-linked with citric acid, have been used as macrocyclic carrier in the preparation of polymer inclusion membranes (PIMs) for aniline (as molecule model) extraction from aqueous media. The obtained membranes were firstly characterized by X-ray diffraction, Fourier transform infrared and water swelling test. The transport of aniline was studied in a two-compartment transport cell under various experimental conditions, such as carrier content in the membranes, stirring rate and initial aniline concentration. The kinetic study was performed and the kinetic parameters were calculated as rate constant (k), permeability coefficient (P) and flux (J). These first results demonstrated the utility of such polymeric membranes for environmental decontamination of toxic organic molecules like aniline. Predictive modeling of transport flux through these materials was then studied using design of experiments; the design chosen was a two level full factorial design $2^k$. An empirical correlation between aniline transport flux and independent variables (Poly ${\beta}$-CD membrane content, agitation speed and initial aniline concentration) was successfully obtained. Statistical analysis showed that initial aniline concentration of the solution was the most important parameter in the study domain. The model revealed the existence of a strong interaction between the Poly ${\beta}$-CD membrane content and the stirring speed of the source solution. The good agreement between the model and the experimental transport data confirms the model's validity.

• Journal of the Korean Geotechnical Society
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• v.40 no.4
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• pp.69-79
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• 2024

Field geotechnical data are obtained from various field and laboratory tests and are documented in geotechnical investigation reports. For efficient design and construction, digitizing these geotechnical parameters is essential. However, current practices involve manual data entry, which is time-consuming, labor-intensive, and prone to errors. Thus, this study proposes an automatic data extraction method from geotechnical investigation reports using image-based deep learning models and text-mining techniques. A deep-learning-based page classification model and a text-searching algorithm were employed to classify geotechnical investigation report pages with 100% accuracy. Computer vision algorithms were utilized to identify valid data regions within report pages, and text analysis was used to match and extract the corresponding geotechnical data. The proposed model was validated using a dataset of 205 geotechnical investigation reports, achieving an average data extraction accuracy of 93.0%. Finally, a user-interface-based program was developed to enhance the practical application of the extraction model. It allowed users to upload PDF files of geotechnical investigation reports, automatically analyze these reports, and extract and edit data. This approach is expected to improve the efficiency and accuracy of digitizing geotechnical investigation reports and building geotechnical databases.

• Imaging Science in Dentistry
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• v.48 no.2
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• pp.79-86
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• 2018

Purpose: This study aimed to carry out a systematic review of studies in the literature comparing conventional imaging techniques with cone-beam computed tomography in terms of the role of these techniques for assessing any of the following periodontal conditions and parameters: infrabony defects, furcation involvement, height of the alveolar bone crest, and the periodontal ligament space. Materials and Methods: Interventional and observational studies comparing conventional imaging techniques with cone-beam computed tomography were considered eligible for inclusion. The MEDLINE and Embase databases were searched for articles published through 2017. The PRISMA statement was followed during data assessment and extraction. Results: The search strategy yielded 351 publications. An initial screening of the publications was performed using abstracts and key words, and after the application of exclusion criteria, 13 studies were finally identified as eligible for review. Conclusion: These studies revealed cone-beam computed tomography to be the best imaging technique to assess infrabony defects, furcation lesions, the height of the alveolar bone crest, and the periodontal ligament space.