Wind data forecasted from the numerical weather prediction (NWP) model is generally used as the first-guess of the target tracking process to obtain the atmospheric motion vectors(AMVs) because it increases tracking accuracy and reduce computational time. However, there is a contradiction that the NWP model used as the first-guess is used again as the reference in the AMVs verification process. To overcome this problem, model-independent first guesses are required. In this study, we propose the AMVs derivation from Lucas and Kanade optical flow method and then using it as the first guess. To retrieve AMVs, Himawari-8/AHI geostationary satellite level-1B data were used at 00, 06, 12, and 18 UTC from August 19 to September 5, 2015. To evaluate the impact of applying the optical flow method on the AMV derivation, cross-validation has been conducted in three ways as follows. (1) Without the first-guess, (2) NWP (KMA/UM) forecasted wind as the first-guess, and (3) Optical flow method based wind as the first-guess. As the results of verification using ECMWF ERA-Interim reanalysis data, the highest precision (RMSVD: 5.296-5.804 ms-1) was obtained using optical flow based winds as the first-guess. In addition, the computation speed for AMVs derivation was the slowest without the first-guess test, but the other two had similar performance. Thus, applying the optical flow method in the target tracking process of AMVs algorithm, this study showed that the optical flow method is very effective as a first guess for model-independent AMVs derivation.
Objective: To compare the pregnancy outcomes after in vitro fertilization with intracytoplasmic sperm injection (IVF-ICSI) between obstrucvtive and non-obstrucvtive azoospermia. Methods: From January 1994 to December 2002, 524 patients with obstructive azoospermia (886 cycles) and 163 patients with non-obstructive azoospermia (277 cycles) were included in this study. Microsurgical epididymal sperm aspiration (MESA) or testicular sperm extraction (TESE) in obstructive azoospermia and TESE in non-obstructive azoospermia were perfomed to retrieve sperm, which was used for ICSI and then fertilized embryos were transferred. The results of ICSI - fertlization rate (FR), clinical pregnancy rate (CPR), clinical abortion rate (CAR) and delivery rate (DR) - were statistically analysed in obstructive versus non-obstructive azoospermia. Results: There were no differences in the number of retrieved oocytes, injected oocytes for ICSI and oocyte maturation rate. FR was significantly higher in obstructive than non-obstructive azoospermia (71.7% vs. 61.1%, p<0.001). There was no difference in CPR per embryo transfer cycle. After pregnancy was established, however, CAR was significantly higher in non-obstructive than obstructive azoospermia (25.6% vs. 12.5%, p=0.004). DR per clinical pregnancy cycle was significantly higher in obstructive than non-obstructive azoospermia (78.0% vs. 64.4%, p=0.012). In the karyotype ananlysis of abortus, abnormal karyotypes were found in 75.0% (6/8) of obstructive and 55.6% (5/9) of non-obstructive azoospermia. Conclusion: Our data show significantly higher FR in obstructive than non-obstructive azoospermia. Though there was no differrence in CPR, CAR was significantly higher in non-obstructive than obstructive azoospermia. The abortion may be related to the abnormal karyotype of embryo, but further investigations are necessary to elucidate the cause of clinical abortion in azoospermia.
It is becoming more essential than ever for office professionals to become competent in information collection/gathering and problem solving in today's global business society. In particular, office professionals do not only assist simple chores but are also forced to make decisions as quickly and efficiently as possible in problematic situations that can end in either profit or loss to their company. Since office professionals rely heavily on their tacit knowledge to solve problems that arise in everyday business situations, it is truly helpful and efficient to refer to similar business cases from the past and share or reuse such previous business knowledge for better performance results. Case-based reasoning(CBR) is a problem-solving method which utilizes previous similar cases to solve problems. Through CBR, the closest case to the current business situation can be searched and retrieved from the case or knowledge base and can be referred to for a new solution. This reduces the time and resources needed and increase success probability. The main purpose of this study is to design a system called COKRS(Case-based reasoning Office Knowledge Recommender System) and develop a prototype for it. COKRS manages cases and their meta data, accepts key words from the user and searches the casebase for the most similar past case to the input keyword, and communicates with users to collect information about the quality of the case provided and continuously apply the information to update values on the similarity table. Core concepts like system architecture, definition of a case, meta database, similarity table have been introduced, and also an algorithm to retrieve all similar cases from past work history has also been proposed. In this research, a case is best defined as a work experience in office administration. However, defining a case in office administration was not an easy task in reality. We surveyed 10 office professionals in order to get an idea of how to define a case in office administration and found out that in most cases any type of office work is to be recorded digitally and/or non-digitally. Therefore, we have defined a record or document case as for COKRS. Similarity table was composed of items of the result of job analysis for office professionals conducted in a previous research. Values between items of the similarity table were initially set to those from researchers' experiences and literature review. The results of this study could also be utilized in other areas of business for knowledge sharing wherever it is necessary and beneficial to share and learn from past experiences. We expect this research to be a reference for researchers and developers who are in this area or interested in office knowledge recommendation system based on CBR. Focus group interview(FGI) was conducted with ten administrative assistants carefully selected from various areas of business. They were given a chance to try out COKRS in an actual work setting and make some suggestions for future improvement. FGI has identified the user-interface for saving and searching cases for keywords as the most positive aspect of COKRS, and has identified the most urgently needed improvement as transforming tacit knowledge and knowhow into recorded documents more efficiently. Also, the focus group has mentioned that it is essential to secure enough support, encouragement, and reward from the company and promote positive attitude and atmosphere for knowledge sharing for everybody's benefit in the company.
Movie is a representative media that can transmit stories to audiences. Basically, a story is described by characters in the movie. Different from other simple videos, movies deploy narrative structures for explaining various conflicts or collaborations between characters. These narrative structures consist of 3 main acts, which are beginning, middle, and ending. The beginning act includes 1) introduction to main characters and backgrounds, and 2) conflicts implication and clues for incidents. The middle act describes the events developed by both inside and outside factors and the story dramatic tension heighten. Finally, in the end act, the events are developed are resolved, and the topic of story and message of writer are transmitted. When story information is extracted from movie, it is needed to consider that it has different weights by narrative structure. Namely, when some information is extracted, it has a different influence to story deployment depending on where it locates at the beginning, middle and end acts. The beginning act is the part that exposes to audiences for story set-up various information such as setting of characters and depiction of backgrounds. And thus, it is necessary to extract much kind information from the beginning act in order to abstract a movie or retrieve character information. Thereby, this paper proposes a novel method for extracting the beginning boundaries. It is the method that detects a boundary scene between the beginning act and middle using the accumulation graph of characters. The beginning act consists of the scenes that introduce important characters, imply the conflict relationship between them, and suggest clues to resolve troubles. First, a scene that the new important characters don't appear any more should be detected in order to extract a scene completed the introduction of them. The important characters mean the major and minor characters, which can be dealt as important characters since they lead story progression. Extra should be excluded in order to extract a scene completed the introduction of important characters in the accumulation graph of characters. Extra means the characters that appear only several scenes. Second, the inflection point is detected in the accumulation graph of characters. It is the point that the increasing line changes to horizontal line. Namely, when the slope of line keeps zero during long scenes, starting point of this line with zero slope becomes the inflection point. Inflection point will be detected in the accumulation graph of characters without extra. Third, several scenes are considered as additional story progression such as conflicts implication and clues suggestion. Actually, movie story can arrive at a scene located between beginning act and middle when additional several scenes are elapsed after the introduction of important characters. We will decide the ratio of additional scenes for total scenes by experiment in order to detect this scene. The ratio of additional scenes is gained as 7.67% by experiment. It is the story inflection point to change from beginning to middle act when this ratio is added to the inflection point of graph. Our proposed method consists of these three steps. We selected 10 movies for experiment and evaluation. These movies consisted of various genres. By measuring the accuracy of boundary detection experiment, we have shown that the proposed method is more efficient.
This paper proposes a methodology applying sequence tagging methodology to improve the performance of NER(Named Entity Recognition) used in QA system. In order to retrieve the correct answers stored in the database, it is necessary to switch the user's query into a language of the database such as SQL(Structured Query Language). Then, the computer can recognize the language of the user. This is the process of identifying the class or data name contained in the database. The method of retrieving the words contained in the query in the existing database and recognizing the object does not identify the homophone and the word phrases because it does not consider the context of the user's query. If there are multiple search results, all of them are returned as a result, so there can be many interpretations on the query and the time complexity for the calculation becomes large. To overcome these, this study aims to solve this problem by reflecting the contextual meaning of the query using Bidirectional LSTM-CRF. Also we tried to solve the disadvantages of the neural network model which can't identify the untrained words by using ontology knowledge based feature. Experiments were conducted on the ontology knowledge base of music domain and the performance was evaluated. In order to accurately evaluate the performance of the L-Bidirectional LSTM-CRF proposed in this study, we experimented with converting the words included in the learned query into untrained words in order to test whether the words were included in the database but correctly identified the untrained words. As a result, it was possible to recognize objects considering the context and can recognize the untrained words without re-training the L-Bidirectional LSTM-CRF mode, and it is confirmed that the performance of the object recognition as a whole is improved.
SAR ground moving target indicator (GMTI) has long been an important issue for SAR advanced applications. As spatial resolution of space-borne SAR system has been significantly improved recently, the GMTI becomes a very useful tool. Various GMTI techniques have been developed particularly using multi-channel SAR systems. It is, however, still problematic to detect ground moving targets within single channel SAR images while it is not practical to access high resolution multi-channel space-borne SAR systems. Once a ground moving target is detected, it is possible to retrieve twodimensional velocities of the target from single channel space-borne SAR with an accuracy of about 5 % if moving faster than 3 m/s. This paper presents a quick-and-dirty method for detecting ground moving targets from single channel SAR single-look complex (SLC) images by differentiation. Since the signal powers of derivatives present Doppler centroid and rate, it is very efficient and effective for detection of non-stationary targets. The derivatives correlate well with velocities retrieved by a precise method with a correlation coefficient $R^2$ of 0.62, which is well enough to detect the ground moving targets. While the approach is theoretically straightforward, it is necessary to remove the effects of residual Doppler rate before finalizing the ground moving target candidates. The confidence level of results largely depends on the efficiency and effectiveness of the residual Doppler rate removal method. Application results using TerraSAR-X and truck-mounted corner reflectors validated the efficiency of the method. While the derivatives of moving targets remain easily detectable, the signal energy of stationary corner reflectors was suppressed by about 18.5 dB. It results in an easy detection of ground targets moving faster than 8.8 km/h. The proposed method is applicable to any high resolution single channel SAR systems including KOMPSAT-5.
Shin, Sung-Kyun;Noh, Youngmin;Lee, Kwonho;Shin, Dongho;Kim, KwanChul;Kim, Young J.
Korean Journal of Remote Sensing
/
v.30
no.2
/
pp.241-249
/
2014
The continuous observations for atmospheric aerosol were carried out during 3 years (2009-2011) by using a multi-wavelength Raman lidar at the Gwangju Institute of Science and Technology (GIST), Korea ($35.11^{\circ}N$, $126.54^{\circ}E$). The particle depolarization ratios were retrieved from the observations in order to distinguish the Asian dust layer. The vertical information of Asian dust layers were used as input parameter for the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model for analysis of its backward trajectories. The source regions and transport pathways of the Asian dust layer were identified. The most frequent source region of Asian dust in Korea was Gobi desert during observation period in this study. The statistical analysis on the particle depolarization ratio of Asian dust was conducted according to their transport route in order to retrieve the variation of optical properties of Asian dust during long-range transport. The transport routes were classified into the Asian dust which was transported to observation site directly from the source regions, and the Asian dust which was passed over pollution regions of China. The particle depolarization ratios of Asian dust which were transported via industrial regions of China was ranged 0.07-0.1, whereas, the particle depolarization ratio of Asian dust which was transported directly from the source regions to observation site were comparably higher and ranged 0.11-0.15. It is considered that the pure Asian dust particle from source regions were mixed with pollution particles, which is likely to spherical particle, during transportation so that the values of particle depolarization of Asian dust mixed with pollution was decreased.
Kim, Min-Jung;Oh, Hyun-Ju;Kim, Geon-A;Jo, Young-Kwang;Choi, Jin;Lee, Byeong-Chun
Journal of Veterinary Clinics
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v.31
no.4
/
pp.267-271
/
2014
Accurate determination of in vivo oocyte maturation is particularly critical for dog cloning compared to other assisted reproductive technologies because oocytes in metaphase II stage have to be recovered in order to undergo somatic cell nuclear transfer right after its recovery. The aim of present study was to evaluate the reliability and to set a reference range of a chemiluminescence enzyme immunoassay (CLEIA) compared to radioimmunoassay (RIA) method to retrieve in vivo matured oocytes. Serum progesterone concentration during proestrus and estrus was analyzed by RIA and CLEIA to determine ovulation day (Day 0). On Day 3, in vivo oocytes were recovered surgically and evaluated microscopically maturation status after staining nucleus with bisbenzimidazole dye. Mean progesterone concentration by CLEIA ($7.64{\pm}0.06ng/ml$) was significantly higher than by RIA ($6.46{\pm}0.04ng/ml$, P < 0.0001). It was not different between CLEIA ($10.01{\pm}0.34ng/ml$) and RIA values ($7.91{\pm}0.14ng/ml$, P < 0.05) on Day 0, but significantly higher CLEIA level on Day -1 and Day 1 ($6.41{\pm}0.15$ and $14.25{\pm}0.44ng/ml$) was assessed compared to RIA ($4.95{\pm}0.10$ and $11.29{\pm}0.34ng/ml$). However, with both methods, progesterone level was significantly increased from Day -1 to Day 2. To determine oocyte maturation with CLEIA method, a wider and higher reference range has to be considered.
In this present study, we identified the $SO_2$ effect on $O_3$ retrieval from the Ozone Monitoring Instrument (OMI) measurement over Chinese Industrial region from 2005 through 2007. The Planetary boundary layer (PBL) $SO_2$ data measured by OMI sensor is used in this present study. OMI-Total Ozone Mapping Spectrometer (TOMS) total $O_3$ is compared with OMI-Differential Optical Absorption Spectrometer (DOAS) total $O_3$ in various $SO_2$ condition in PBL. The difference between OMI-TOMS and OMI-DOAS total $O_3$ (T-D) shows dependency on $SO_2$ (R (Correlation coefficient) = 0.36). Since aerosol has been reported to cause uncertainty of both OMI-TOMS and OMI-DOAS total $O_3$ retrieval, the aerosol effect on relationship between PBL $SO_2$ and T-D is investigated with changing Aerosol Optical Depth (AOD). There is negligible aerosol effect on the relationship showing similar slope ($1.83{\leq}slope{\leq}2.36$) between PBL $SO_2$ and T-D in various AOD conditions. We also found that the rate of change in T-D per 1.0 DU change in PBL, middle troposphere (TRM), and upper troposphere and stratosphere (STL) are 1.6 DU, 3.9 DU and 4.9 DU, respectively. It shows that the altitude where $SO_2$ exist can affect the value of T-D, which could be due to reduced absolute radiance sensitivity in the boundary layer at 317.5 nm which is used to retrieve OMI-TOMS ozone in boundary layer.
Considerable research efforts are being directed towards analyzing unstructured data such as text files and log files using commercial and noncommercial analytical tools. In particular, researchers are trying to extract meaningful knowledge through text mining in not only business but also many other areas such as politics, economics, and cultural studies. For instance, several studies have examined national pending issues by analyzing large volumes of text on various social issues. However, it is difficult to provide successful information services that can identify R&D documents on specific national pending issues. While users may specify certain keywords relating to national pending issues, they usually fail to retrieve appropriate R&D information primarily due to discrepancies between these terms and the corresponding terms actually used in the R&D documents. Thus, we need an intermediate logic to overcome these discrepancies, also to identify and package appropriate R&D information on specific national pending issues. To address this requirement, three methodologies are proposed in this study-a hybrid methodology for extracting and integrating keywords pertaining to national pending issues, a methodology for packaging R&D information that corresponds to national pending issues, and a methodology for constructing an associative issue network based on relevant R&D information. Data analysis techniques such as text mining, social network analysis, and association rules mining are utilized for establishing these methodologies. As the experiment result, the keyword enhancement rate by the proposed integration methodology reveals to be about 42.8%. For the second objective, three key analyses were conducted and a number of association rules between national pending issue keywords and R&D keywords were derived. The experiment regarding to the third objective, which is issue clustering based on R&D keywords is still in progress and expected to give tangible results in the future.
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