• Atmosphere
• /
• v.29 no.4
• /
• pp.451-461
• /
• 2019

Medium-range forecast is highly dependent on ensemble forecast data. However, operational weather forecasters have not enough time to digest all of detailed features revealed in ensemble forecast data. To utilize the ensemble data effectively in medium-range forecasting, representative weather patterns in East Asia in this study are defined. The k-means clustering analysis is applied for the objectivity of weather patterns. Input data used daily Mean Sea Level Pressure (MSLP) anomaly of the ECMWF ReAnalysis-Interim (ERA-Interim) during 1981~2010 (30 years) provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). Using the Explained Variance (EV), the optimal study area is defined by 20~60°N, 100~150°E. The number of clusters defined by Explained Cluster Variance (ECV) is thirty (k = 30). 30 representative weather patterns with their frequencies are summarized. Weather pattern #1 occurred all seasons, but it was about 56% in summer (June~September). The relatively rare occurrence of weather pattern (#30) occurred mainly in winter. Additionally, we investigate the relationship between weather patterns and extreme weather events such as heat wave, cold wave, and heavy rainfall as well as snowfall. The weather patterns associated with heavy rainfall exceeding 110 mm day^-1 were #1, #4, and #9 with days (%) of more than 10%. Heavy snowfall events exceeding 24 cm day^-1 mainly occurred in weather pattern #28 (4%) and #29 (6%). High and low temperature events (> 34℃ and < -14℃) were associated with weather pattern #1~4 (14~18%) and #28~29 (27~29%), respectively. These results suggest that the classification of various weather patterns will be used as a reference for grouping all ensemble forecast data, which will be useful for the scenario-based medium-range ensemble forecast in the future.

• Journal of the Korean earth science society
• /
• v.42 no.5
• /
• pp.571-587
• /
• 2021

This study aims to investigate the problem recognition and clue capture processes of the observation stage in a geological field trip using abductive inquiry. To this end, eight outdoor geological programs were developed in the order of diagnostic evaluation, outdoor geological fieldwork, and review. Six middle-school students participated in these programs The geological field trip was conducted twice, followed by data provision, observation, rule generation, hypothesis generation, and final hypothesis presentation. Outdoor geological fieldwork recordings and student activity sheets were collected and analyzed qualitatively. From these data, three aspects of student observations emerged during the geological fieldwork: The characteristics of each pattern were subdivided into the geological importance of the clues, attention, type of clues, observation characteristics (attention factor), clue utilization, and clue deletion. Here, by combining these results, we propose educational applications that correspond to each aspect.

• Journal of KIISE:Software and Applications
• /
• v.29 no.3
• /
• pp.167-179
• /
• 2002

In this paper, we propose a new acoustic model for characterizing segmental features and an algorithm based upon a general framework of hidden Markov models (HMMs) in order to compensate the weakness of HMM assumptions. The segmental features are represented as a trajectory of observed vector sequences by a polynomial regression function because the single frame feature cannot represent the temporal dynamics of speech signals effectively. To apply the segmental features to pattern classification, we adopted segmental HMM(SHMM) which is known as the effective method to represent the trend of speech signals. SHMM separates observation probability of the given state into extra- and intra-segmental variations that show the long-term and short-term variabilities, respectively. To consider the segmental characteristics in acoustic model, we present segmental-feature HMM(SFHMM) by modifying the SHMM. The SFHMM therefore represents the external- and internal-variation as the observation probability of the trajectory in a given state and trajectory estimation error for the given segment, respectively. We conducted several experiments on the TIMIT database to establish the effectiveness of the proposed method and the characteristics of the segmental features. From the experimental results, we conclude that the proposed method is valuable, if its number of parameters is greater than that of conventional HMM, in the flexible and informative feature representation and the performance improvement.

• Journal of the Korean earth science society
• /
• v.24 no.6
• /
• pp.533-548
• /
• 2003

The prevailing wind phenomenon around Pohang in winter was investigated by using surface and vertical observatory datas and a numerical simulation was carried out to analyse this phenomenon using RAMS. Direction of the prevailing wind was westerly at upper atmosphere. However, near the surface, southwestern wind prevailed in winter. Using the RAMS to simulate a winter wind system numerically, it was found out that this phenomenon was strongly affected by the geographical features such as directions of coastline and low level valley, and distributions of land and sea. To investigate the accuracy of the model results, wind speed, temperature and wind direction of typical continuous southwestern wind occurring days were compared with observation data. Analyzing the characteristics of local circulation system was very hard because of horizontally sparse observation data. But from the result above, a numerical simulation using the RAMS, which satisfies the spatial high resolution, will provide more accurate results.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.5A
• /
• pp.375-387
• /
• 2012

This paper proposes a new real-time object tracking algorithm using particle filters with color and texture features in moving CCD camera images. If the user selects an initial object, this region is declared as a target particle and an initial state is modeled. Then, N particles are generated based on random distribution and CS-LBP (Centre Symmetric Local Binary Patterns) for texture model and weighted color distribution is modeled from each particle. For observation likelihoods estimation, Bhattacharyya distance between particles and their feature models are calculated and this observation likelihoods are used for weights of individual particles. After weights estimation, a new particle which has the maximum weight is selected and new particles are re-sampled using the maximum particle. For performance comparison, we tested a few combinations of features and particle filters. The proposed algorithm showed best object tracking performance when we used color and texture model simultaneously for likelihood estimation.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.817-819
• /
• 2003

Land degradation is a crucial issue in mountainous areas and is manifested in a variety of processes. For its assessment, application of existing models is not straightforward. In addition, data availability might be a problem. In this paper, a procedure for land degradation assessment is described, which follows a four-step approach: (1) detection, inventory and mapping of land degradation features, (2) assessing the magnitude of soil loss, (3) study of causal factors, and (4) hazard assessment by applying decision trees. This approach is applied to a case study in the Middle Mountain region of Nepal. The study shows that individual mass movement features such as debris slides and slumps can be easily mapped by photo interpretation techniques. Application of soil loss estimation models helps get insight on the magnitude of soil losses. In the study area soil losses are higher in rainfed crops on sloping terraces (highest soil loss is 32 tons/ha/yr) and minimal under dense forest and in irrigated rice fields (less than 1 ton/ha/yr). However there is high frequency of slope failures in the form of slumps in the rice fields. Debris slides are more common on south-facing slopes under rainfed agriculture or in degraded forest. Field evidences and analysis of causal factors for land degradation helps in building decision trees, the use of which for modelling land degradation has the advantage that attributes can be ranked and tested according to their importance. In addition, decision trees are simple to construct, easy to implement and very flexible in adaptations.

• Journal of Science Education
• /
• v.37 no.1
• /
• pp.142-156
• /
• 2013

The purpose of this study was to analyze observation characteristics through eye movement according to cognitive style. For this, developed observation task that can be shown the difference between wholistic cognitive style group and analytic cognitive style group, measured eye movement of university students who has different cognitive style, as given observation task. It is confirmed the difference between two cognitive style groups by analysing gathered statistics and visualization data. The findings of this study were as follows; First, Compared observation sequence and pattern by cognitive style, analytic cognitive style group is concerned with spider first and moving on surrounding environment, whereas wholistic cognitive style group had not fixed pattern as observing spider itself and surrounding area of spider alternately or looking closely on particular part at first. When observing entire feature and partial feature, wholistic cognitive style group was moving on Fixation from outstanding factor without fixed pattern, analytic cognitive style had certain directivity and repetitive investigation. Second, compared the ratio of observation, analytic cognitive style group gave a large part to spider the very thing, wholistic cognitive style group gave weight to surrounding area of spider, and analytic group shown higher concentration on observing partial feature, wholistic cognitive style group shown higher concentration on observing wholistic feature. Wholistic cognitive style group gave importance to partial features in surrounding area, and wholistic feature of spider than analytic cognitive style group, analytic cognitive style group was focus on partial features of spider than wholistic cognitive style group. Through the result of this study, there are differences of observing time, frequency, object, area, sequence, pattern and ratio from cognitive styles. It is shown the reason why each student has varied outcome, from the difference of information following their cognitive style, and the result of this study help to figure out and give direction to what observation fulfillment is suitable for each student.

• Journal of the Korean Wood Science and Technology
• /
• v.38 no.4
• /
• pp.292-297
• /
• 2010

Sound absorption capability and anatomical features of kagikazura (Uncaria rhynchophylla) and larch (lalix kaemferi) wood were estimated. Sound absorption coefficients had been measured by the two microphone transfer function method and anatomical features of kagikazura wood examined by SEM observation. The sound absorption coefficients of Uncaria rhynchophylla was higher than lalix kaemferi. Especially, in the frequency range of 1 to 4KHz, sound absorption coefficients of kagikazura was about 2~3 times higher than those of lalix kaemferi. Abundant and big vessel observed on the cross sectional surface of kagikazura wood and simple perforation plate observed on the longitudinal surface. It was surmised that the abundant big vessel element and simple perforation plate behaved as a sound absorbing pore.

• The Korea Journal of Herbology
• /
• v.26 no.1
• /
• pp.1-6
• /
• 2011

Objectives : Due to morphological similarity, many substitutes and counterfeits have been used as Moktong for thousands of years. This study was designed to determine discriminative criteria for identifying medicinal herbs used as Moktong. Methods : Akebia quinata, A. trifoliata, Clematis armandii, and Aristolochia manshuriensis were collected in various regions. Samples were authenticated and examined by observation and microscopy with paraffin embedding and triple staining using the modified Ju staining method. Results : Three different types of features to establish discriminative criteria for four kinds of Moktong were identified. Botanical features include differences in phyllotaxy, leaf shape, and caulescent. External morphological features were arrangement and size of fine holes(xylem), and overall shape of the section. Internal morphological features include the number of medullary rays, shape of the pitch, type of tissues rounding pitch, appearance of annual rings, shape and amount of crystals(calcium-oxalate), and the appearance of cork cambium. Further details(e.g. identification keys) are in the article. Conclusions : These criteria could provide an effective method for identifying numerous kinds of Moktong distributed in markets throughout northeast Asian nations.

• Journal of KIISE
• /
• v.43 no.8
• /
• pp.848-856
• /
• 2016

Seeking and recognizing maritime targets are very important tasks for maritime safety. While searching for maritime targets using radar is possible, recognition is conducted without automatic identification system, radio communicator or visibility. If this recognition is not feasible, radar operator must tediously recognize maritime targets using movement features on radar base on know-how and experience. In this paper, to support the radar operator's mission of continuous observation, we propose an algorithm for automatic recognition of an unknown ship using movement features on radar and a method of detecting potential ship related accidents. We extract features from contact range, course and speed of four types of vessels and evaluate the recognition accuracy using SVM and suggest a method of detecting potential ship related accidents through the algorithm. Experimentally, the resulting recognition accuracy is found to be more than 90% and presents the possibility of detecting potential ship related accidents through the algorithm using information of MV Sewol. This method is an effective way to support operator's know-how and experience in various circumstances and assist in detecting potential ship related accidents.