• Proceedings of the KSRS Conference
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• v.2
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• pp.725-727
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• 2006

The development of GIS and Location-Based Services requires a high-level database that will be able to allow real-time access to moving objects for spatial and temporal operations. MODB.MM is able to meet these requirements quite adequately, providing operations with the abilities of acquiring, storing, and querying large-scale moving objects. It enables a dynamic and diverse query mechanism, including searches by region, trajectory, and temporal location of a large number of moving objects that may change their locations with time variation. Furthermore, MODB.MM is designed to allow for performance upon main memory and the system supports the migration on out-of-date data from main memory to disk. We define the particular query for truncation of moving objects data and design two migration methods so as to operate the main memory moving objects database system and file-based location storage system with.

• Archives of Pharmacal Research
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• v.24 no.3
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• pp.234-239
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• 2001

Three types of learning and memory tests (Morris water maze, active and passive avoidance) were performed in rats following intracerebroventricular infusion of ethylcholine aziridium (AF64A). In Morris water maze, AF64A-treated rats showed the delayed latencies to find the platform iron 6th day after the infusion. In pretrained rats, AF64A caused the significant delay of latency at 7th days but not 8th day. In the active avoidance for the pretrained rats, the escape latency was significantly delayed in AF64A-treatment. The percentages of avoidance in AF64A-treated rats were less increased than those in the control. Especially, the percentage of no response in the AF64A-treated rats was markedly increased in the first half trials. In the passive avoidance, AF64A-treated rats shortened the latency 1.5 h after the electronic shock, but not 24 h. AF64A also caused the pretrained rats to shorten the latency 7th day after the infusion, but not 8th day. These results indicate that AF64A might impair the learning and memory. However, these results indicate that the disturbed memory by AF64A might rapidly recover after the first retrain. Furthermore, these results suggest that AF64A may be a useful agent for the animal model of learning for Spatial cognition .

• Journal of Ginseng Research
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• v.41 no.2
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• pp.151-158
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• 2017

Background: Chong-Myung-Tang (CMT) extract is widely used in Korea as a traditional herbal tonic for increasing memory capacity in high-school students and also for numerous body ailments since centuries. The use of CMT to improve the learning capacity has been attributed to various plant constituents, especially black ginseng, in it. Therefore, in this study, we have first investigated whether black ginseng-enriched CMT extracts affected spatial learning using the Morris water maze (MWM) test. Their molecular mechanism of action underlying improvement of learning and memory was examined in vitro. Methods: We used two types of black ginseng-enriched CMT extracts, designated as CM-1 and CM-2, and evaluated their efficacy in the MWM test for spatial learning behavior and their anti-inflammatory effects in BV2 microglial cells. Results: Our results show that both black ginseng-enriched CMT extracts improved the learning behavior in scopolamine-induced impairment in the water maze test. Moreover, these extracts also inhibited nitric oxide production in BV2 cells, with significant suppression of expression of proinflammatory cytokines, especially inducible nitric oxide synthase, cyclooxygenase-2, and $interleukin-1{\beta}$. The protein expression of mitogen-activated protein kinase and nuclear $factor-{\kappa}B$ pathway factors was also diminished by black ginseng-enriched CMT extracts, indicating that it not only improves the memory impairment, but also acts a potent anti-inflammatory agent for neuroinflammatory diseases. Conclusion: Our research for the first time provides the scientific evidence that consumption of black ginseng-enriched CMT extract as a brain tonic improves memory impairment. Thus, our study results can be taken as a reference for future neurobehavioral studies.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1115-1121
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• 2009

For HRI (Human-Robot Interaction) in daily life, robots need to recognize non-rigid objects such as clothes and blankets. However, the recognition of non-rigid objects is challenging because of the variation of the shapes according to the places and laying manners. In this paper, the cognition of non-rigid object based on a cognitive system is presented. The characteristics of non-rigid objects are analysed in the view of HRI and referred to design a framework for the cognition of them. We adopt a linguistic cognitive system for describing all of the events happened to robots. When an event related to the non-rigid objects is occurred, the cognitive system describes the event into a sentential form and stores it at a sentential memory, and depicts the objects with a spatial model for being used as references. The cognitive system parses each sentence syntactically and semantically, in which the nouns meaning objects are connected to their models. For answering the questions of humans, sentences are retrieved by searching temporal information in the sentential memory and by spatial reasoning in a schematic imagery. Experiments show the feasibility of the cognitive system for cognizing non-rigid objects in HRI.

• Korean Institute of Interior Design Journal
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• v.21 no.2
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• pp.46-55
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• 2012

This study aims to analyze the design concepts of Libeskind's Jewish museums through their comparisons for figuring out his design intentions and characteristics in the realization process. Libeskind's realized four Jewish museums are chosen for this study. For more concrete study, their extracting and application process are also reviewed. The comparison of his museum designs can be good examples in that they show different design approaches on the same architectural type, Jewish museum, to tell their something in common from differences. He could realize his architectural thoughts and configuration methods made by experimental drawings for the first time as real buildings through a series of Jewish museum projects. The commonness of Libeskind's Jewish museums lie on their sharing design concept of Jewish 'history and memory', especially Holocaust, and realized as in contrast to surroundings and 'labyrinth' of spatial configuration to maximize spectator's experiences. As Libeskind regards museum architecture as a carrier of 'time and place', he tried to reflect surrounding context including places, cities, persons and events about museum programs. As a result, unprecedented museums which are not related to traditional museum systems about circulation and spatial configuration are suggested for users to experience Jewish life and history through architecture.

• Korean Journal of Child Studies
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• v.37 no.6
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• pp.107-117
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• 2016

Objective: This study examined the construct validity of K-WPPSI-IV. Factor structures of the structures of the K-WPPSI-IV full scale as well as primary index scales for two age ranges (2 years, 6 months to 3 years, 11 months; 4 years to 7 years, 7 months) were examined. Methods: Data were collected from 1,700 children aged 2 years, 6 months to 7 years, 7 months during the K-WPPSI-IV standardization. Confirmatory factor analyses were conducted using the K-WPPSI-IV subtest performances with maximum likelihood estimation using Amos 18. Results: First, the three-factor model (verbal comprehension, visual spatial, and working memory) fitted best for the younger age range. However, the five-factor model (verbal comprehension, visual spatial, fluid reasoning, working memory, and processing speed) fitted best for the older age range. Residuals suggest the presence of two nested subfactors within the verbal comprehension factor (broad/expressive and focused/simple). Second, the confirmatory factor analysis on primary index subtests identified factors that account for the intercorrelations among the reduced sets of primary index subtests. Conclusion: The findings showed that the theoretical structures of WPPSI-IV subtests were confirmed within K-WPPSI-IV.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.719-731
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• 2021

This study proposes a two-stage hybrid classification model for crop classification using multi-temporal remote sensing images; the model combines feature embedding by using an autoencoder (AE) with a convolutional neural network (CNN) classifier to fully utilize features including informative temporal and spatial signatures. Long short-term memory (LSTM)-based AE (LAE) is fine-tuned using class label information to extract latent features that contain less noise and useful temporal signatures. The CNN classifier is then applied to effectively account for the spatial characteristics of the extracted latent features. A crop classification experiment with multi-temporal unmanned aerial vehicle images is conducted to illustrate the potential application of the proposed hybrid model. The classification performance of the proposed model is compared with various combinations of conventional deep learning models (CNN, LSTM, and convolutional LSTM) and different inputs (original multi-temporal images and features from stacked AE). From the crop classification experiment, the best classification accuracy was achieved by the proposed model that utilized the latent features by fine-tuned LAE as input for the CNN classifier. The latent features that contain useful temporal signatures and are less noisy could increase the class separability between crops with similar spectral signatures, thereby leading to superior classification accuracy. The experimental results demonstrate the importance of effective feature extraction and the potential of the proposed classification model for crop classification using multi-temporal remote sensing images.

• Smart Structures and Systems
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• v.32 no.5
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• pp.297-308
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• 2023

Dynamic deflection is important for evaluating the performance of a long-span cable-stayed bridge, and its continuous measurement is still cumbersome. This study proposes a dynamic deflection monitoring method for cable-stayed bridge based on Bi-directional Long Short-term Memory (BiLSTM) neural network taking advantages of the characteristics of spatial variation of cable acceleration response (CAR) and main girder deflection response (MGDR). Firstly, the relationship between the spatial and temporal variation of the CAR and the MGDR is described based on the geometric deformation of the bridge. Then a data-driven relational model based on BiLSTM neural network is established using CAR and MGDR data, and it is further used to monitor the MGDR via measuring the CAR. Finally, numerical simulations and field test are conducted to verify the proposed method. The root mean squared error (RMSE) of the numerical simulations are less than 4 while the RMSE of the field test is 1.5782, which indicate that it provides a cost-effective and convenient method for real-time deflection monitoring of cable-stayed bridges.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.88.3-89
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• 2017

We present our experiences with open-source NoSQL database systems in analyzing spatial and temporal astronomical data. We conduct experiments of using Redis in-memory NoSQL database system by modifying and exploiting its support of geohash for astronmical spatial data. Our experiment focuses on performance, cost, difficulty, and scalability of the database system. We also test OpenTSDB as a possible NoSQL database system to process astronomical time-series data. Our experiments include ingesting, indexing, and querying millions or billions of astronomical time-series measurements. We choose our KMTNet data and the public VVV (VISTA Variables in the Via Lactea) catalogs as test data. We discuss issues in using these NoSQL database systems in astronomy.

• Journal of Korean Association for Spatial Structures
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• v.19 no.2
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• pp.17-25
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• 2019

In this study, we propose a new scheme of nonlinear analysis for Incheon International Airport Terminal-2 which was opened on January of 2018 for the Olympic Winter Games of PyeongChang in South Korea. The terminal was built by a single layered irregular space frame. It has hard problems for nonlinear analysis geometrically, because of a limitation of personal computer's ability by the number of rigid joints in the roof. Therefore we attempt easier approach to be chosen a center part of the roof instead of the whole structure, and to substitute the other boundary parts as springs. The scheme shows some merits for saving memory and calculation time and so on.