The neutral cluster beam deposition (NCBD) method has been applied to produce and characterize organic thin-film transistors (OTFTs) based upon tetracene and pentacene molecules as active layers. Organic thin films were prepared by the NCBD method on hexamethyldisilazane (HMDS)-untreated and -pretreated silicon dioxide (SiO2) substrates at room temperature. The surface morphology and structures for the tetracene and pentacene thin films were examined by atomic force microscopy (AFM) and X-ray diffraction (XRD). The measurements demonstrate that the weakly bound and highly directional neutral cluster beams are efficient in producing high-quality single-crystalline thin films with uniform, smooth surfaces and that SiO2 surface treatment with HMDS enhances the crystallinity of the pentacene thin-film phase. Tetracene- and pentacene-based OTFTs with the top-contact structure showed typical source-drain current modulation behavior with different gate voltages. Device parameters such as hole carrier mobility, current on/off ratio, threshold voltage, and subthreshold slope have been derived from the current-voltage characteristics together with the effects of surface treatment with HMDS. In particular, the high field-effect room-temperature mobilities for the HMDS-untreated OTFTs are found to be comparable to the most widely reported values for the respective untreated tetracene and pentacene thin-film transistors. The device performance strongly correlates with the surface morphology, and the structural properties of the organic thin films are discussed.
The purpose was to evaluate the effects of dienogest on Korean women with endometriosis. A cross-sectional questionnaire-based survey was conducted for 100 premenopausal women. They had taken or were taking 2 mg of dienogest daily. We assessed the pelvic pain score and quality-of-life (QOL) score before and after taking dienogest as well as the prevalence of short-term (≤12 weeks) and long-term adverse effects (>52 weeks). Patients were classified into three groups: dienogest treatment immediately following surgery (A), dienogest treatment for a recurrence of endometriosis after surgery (B), or dienogest treatment without any surgery (C). In groups A and C, the median pain score (from 5 to 0, p <.001; from 7 to 1.5, p <.001) and median QOL score (from 10 to 5, p = .002; from 7.5 to 6.5, p = .008) were significantly decreased. Irregular bleeding and decreased menstrual flow were more prevalent in patients with dienogest intake of fewer than 12 weeks, while amenorrhea, weight gain, hair loss, and dorsal pain were more prevalent in patients with dienogest treatment of over 52 weeks. Accordingly, proper counseling is necessary when prescribing dienogest.
Depending on the different types of raw materials used to produce hanji, a Korean traditional handmade paper, there can be significant differences in the durability and mechanical properties of the final product. In this study, near-infrared spectroscopy (NIR) combined with multivariate statistical methods were used to confirm the classification possibility of hanji based on the various type of raw materials. The hanji papers were prepared from paper mulberry trees, cooking agents, and mucilage. Altogether, a total of 60 hanji spectra were collected by NIR. Then, the 60 spectra were grouped into four categories: the control, paper mulberry, cooking agent, and mucilage type based on each of the types of raw materials contained in the hanji. Three different classification algorithms – partial least squares discriminant analysis (PLS-DA), support vector machines (SVM), and random forest (RF) – were used to classify the hanji types. The best hanji material classification performance was obtained when the hanji samples were classified according to paper mulberry type, wherein the prediction accuracies of PLS-DA, SVM, and RF were 100%, 100%, and 98%, respectively. These results suggested that NIR in combination with multivariate statistical methods can be used for hanji material classification.
The aim of this study is to analyze the research trends on Hanji (Korean traditional paper) in the academic literatures based on the purpose, content, and findings of various studies, and to present a direction for future research. Research papers published in 12 academic journals over the past 51 years were collected using 167 key-words for the search, and of them, 178 papers were selected for analysis. Statistical analysis of these papers based on year, research content, and discipline to understand and quantify the research trend. Revealed that the frequency of the published research paper was generally proportional by number of research projects in domestic government departments. They also indicated that while there were several studies on property valuation or functionality improvement of Hanji based on experiments, research was lacking in the areas of observation, analysis, case studies, and status survey of Hanji. The present study provides basic data for establishing the direction of research on Hanji.
In this paper, we propose an effective method for classifying machine-printed and handwritten addresses on Korean mail piece images. It is of vital importance to know if an input image is machine-printed or handwritten in such applications as address reading, form processing, FAX routing, and etc., since approaches for handwritten images are developed quite differently from those for machine-printed images. Our method consists of three blocks: valid connected component grouping, feature extraction and classification. A set of features related to width and position of groups of valid connected components is used for the classification based on a multi-layer perceptrons network. The experiment done with address images extracted from Korean live mail piece images has demonstrated the superiority of the proposed method. The correct classification rate for 3,147 testing images was about 98.9%.
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