• Title/Summary/Keyword: Spatio-temporal parameters

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Estimation of Fish Habitat Suitability Index for Stream Water Quality - Case Species of Zacco platypus - (하천 수질에 대한 어류의 서식처적합도지수 산정 - 피라미를 대상으로 -)

  • Hong, Rokgi;Park, Jinseok;Jang, Seongju;Song, Inhong
    • Journal of The Korean Society of Agricultural Engineers
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    • v.63 no.6
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    • pp.89-100
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    • 2021
  • The conservation of stream habitats has been gaining more public attention and fish habitat suitability index (HSI) is an important measure for ecological stream habitat assessment. The fish habitat preference is affected not only by physical stream conditions but also by water quality of which HSI was not available due to the lack of field data. The purpose of this study is to estimate the HSI of Zacco platypus for water quality parameters of water temperature, dissolved oxygen (DO), and biochemical oxygen demand (BOD) using the water environment monitoring data provided by the Ministry of Environment (ME). Fish population data merged with water quality were constructed by spatio-temporal matching of nationwide water quality monitoring data with bio-monitoring data of the ME. Two types of the HSI were calculated by the Instream Flow and Aquatic Systems Group (IFASG) method and probability distribution (Weibull) fitting for the four major river basins. Both the HSIs by the IFASG and Weibull fitting appeared to represent the overall distribution and magnitude of fish population and this can be used in stream fish habitat evaluation considering water quality.

Gait Recovery Characteristic According to the Injury Aspect of Descending Motor Pathway in a Chronic Stroke Patient: a Case Study

  • Sang Seok Yeo
    • The Journal of Korean Physical Therapy
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    • v.34 no.6
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    • pp.326-331
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    • 2022
  • Purpose: The stroke patients have gait dysfunction due to impaired neural tracts; corticospinal tract (CST), corticoreticular pathway (CRP), and vestibulospinal tract (VST). In this study, we investigated characteristics of gait pattern according to the injury aspect of the neural track in a stroke patient. Methods: One patient and six control subjects of similar age participated. A 19-year-old male patient with spontaneous intracerebral hemorrhage on right basal ganglia, thalamus, corona radiata and cerebral cortex due to arteriovenous malformation rupture. Diffusion tensor imaging (DTI) data was acquired 21 months after the stroke. Kinematic and spatio-temporal parameters of gait were collected using a three-dimensional gait analysis system. Results: On 21 months DTI, the CST and CRP in affected hemisphere showed severe injury, in contrast, the VST in affected hemisphere showed intact integrity. Result of gait analysis, walking distance and speed were significantly decreased in a patient. The stance rate of unaffected lower limb, the swing rate of affected lower limb and the duration of double stance significantly increased compared with normal control. The knee and hip joint angle were significantly decreased in a patient. Conclusion: We found recovered independent gait ability may be associated with unimpaired VST in a patient with severe injury in CST and CRP.

Development and Application of Streamline Analysis Method (유선 분석법의 개발 및 적용)

  • Kim Tae Beom;Lee Chihyung;Cheong Jae-Yeol
    • Journal of Soil and Groundwater Environment
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    • v.28 no.6
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    • pp.9-15
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    • 2023
  • In order to properly evaluate the spatio-temporal variations of groundwater flow, the data obtained in field experiments should be corroborated into numerical simulations. Particle tracking method is a simple simulation tool often employed in groundwater simulation to predict groundwater flow paths or solute transport paths. Particle tracking simulations visually show overall the particle flow path along the entire aquifer, but no previous simulation studies has yet described the parameter values at grid nodes around the particle path. Therefore, in this study, a new technical approach was proposed that enables acquisition of parameters associated with particle transport in grid nodes distributed in the center of the particle path in groundwater. Since the particle tracking path is commonly referred to as streamline, the algorithm and codes developed in this works designated streamline analysis method. The streamline analysis method can be applied in two-dimensional and three-dimensional finite element or finite difference grid networks, and can be utilized not only in the groundwater field but also in all fields that perform numerical modeling.

Estimation of Vegetation Carbon Budget in South Korea using Ecosystem Model and Spatio-temporal Environmental Information (생태계 모형과 시공간 환경정보를 이용한 우리나라 식생 탄소 수지 추정)

  • Yoo, Seong-Jin;Lee, Woo-Kyun;Son, Yo-Whan;Ito, Akihiko
    • Korean Journal of Remote Sensing
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    • v.28 no.1
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    • pp.145-157
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    • 2012
  • In this study, we simulated a carbon flux model, so called Vegetation Integrated Simulator for Trace gases (VISIT) using Spatio-temporal Environmental Information, to estimate carbon budgets of vegetation ecosystem in South Korea. As results of the simulation, the model estimated that the annual-average gross primary production (GPP), net primary production (NPP) for 10 years were $91.89Tg\;C\;year^{-1}$, and $40.16Tg\;C\;year^{-1}$, respectively. The model also estimated the vegetation ecosystems in South Korea as a net carbon sink, with a value of $3.51Tg\;C\;year^{-1}$ during the simulation period. Comparing with the anthropogenic emission of South Korea, vegetation ecosystems offsets 3.3% of human emissions as a net carbon sink in 2007. To estimate the carbon budget more accurately, it is important to prepare reliable input datasets. And also, model parameters should be calibrated through comparing with various independent method. The result of this study, however, would be helpful for devising ecosystem management strategies that may help to mitigate global climate change.

Spatio-temporal Distributions of Macrobenthic Community on Subtidal Area around Mokpo, Korea (목포 주변 해역 조하대 저서동물 군집의 시 ${\cdot}$ 공간적 분포)

  • Lee, Jae-Hac;Choi, Jin-Woo;Park, Heung-Sik
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.5 no.2
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    • pp.169-176
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    • 2000
  • This study was carried out to clarify the spatial and temporal patterns of macrobenthic assemblages on the subtidal area around Mokpo, southwest of Korea. A total of 238 species and 663 ind./$m^{2}$ were collected. Polychaetes were the most abundant faunal group that comprised 88 species and had a mean density of 389 ind./$m^{2}$. In the semi-enclosed Youngsan River estuarine bay and neighbouring Mokpo Port area were composed of fine sediments with high organic content, and revealed large seasonal variations in the salinity of surface water and bottom dissolved oxygen in contrast to little seasonal changes in those parameters in the outer area. The study area was classified into four station groups by the cluster analysis; the harbor area, the offshore area, and the inner and outer estuarine bay. Two estuarine bay areas showed different species composition; the dominant species of inner bay were Tharyx sp., Poecilochaetus johnsoni, Heteromastus filiformis and other opportunistic species whereas those in the outer bay were Ruditapes philippinarum, Corophium sinense. From the environmental data and species composition of benthic community, the inner bay was characterized to have unstable benthic faunal assemblages, especially under the seasonal disturbance and receiving large amount of organic matter input and intermittant discharge of fresh water. The coastal developments around Mokpo city also seem to have stressed the subtidal communities spatio-temporally.

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Characteristics of Industrial Heritage as Regional Cultural Contents (지역문화콘텐츠로서의 산업유산 특성 - 삿포로와 청주 사례를 중심으로 -)

  • Lee, Byung-min
    • Review of Culture and Economy
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    • v.20 no.2
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    • pp.89-117
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    • 2017
  • As the industrial paradigm shifts and the manufacturing industry declines, many changes also take place in the region as well. In this regard, interest in industrial heritage as a facet of cultural heritage is on the increase. In this paper, the meaning of regional 'cultural contents' as industrial heritage is investigated within the scope of specific region. It is meant to move beyond the viewpoint of considering industrial heritage as only relating to industrial machinery and relevant landmarks from the past. The concept of industrial heritage is established more clearly through the review policy and case study analysis of existing research; the analysis is conducted to investigate the characteristics associated with it, and then to explore how best to utilize it. In particular, this paper attempts to focus on how it operates within these parameters using a spatio-temporal context as much as possible, and concentrating on the recognition and experience of the subject of industrial heritage as being traceable through human story. This research is based on the case of 'Sapporo' which focuses on modern history based on historical importance, and the 'Cheongju' case study, which contrasts the former by focusing on urban regeneration using a spatial lens. This paper identifies the possibility of regional development through the examination of past identity and diversity in the present, and highlights the features that could be linked to future usability and development. In addition, it proposes the possibility that the cycle of regional development could change in the process of the different stages of territorialization, de-territorialization and re-territorialization.

Automatic Geo-referencing of Sequential Drone Images Using Linear Features and Distinct Points (선형과 특징점을 이용한 연속적인 드론영상의 자동기하보정)

  • Choi, Han Seung;Kim, Eui Myoung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.1
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    • pp.19-28
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    • 2019
  • Images captured by drone have the advantage of quickly constructing spatial information in small areas and are applied to fields that require quick decision making. If an image registration technique that can automatically register the drone image on the ortho-image with the ground coordinate system is applied, it can be used for various analyses. In this study, a methodology for geo-referencing of a single image and sequential images using drones was proposed even if they differ in spatio-temporal resolution using linear features and distinct points. Through the method using linear features, projective transformation parameters for the initial geo-referencing between images were determined, and then finally the geo-referencing of the image was performed through the template matching for distinct points that can be extracted from the images. Experimental results showed that the accuracy of the geo-referencing was high in an area where relief displacement of the terrain was not large. On the other hand, there were some errors in the quantitative aspect of the area where the change of the terrain was large. However, it was considered that the results of geo-referencing of the sequential images could be fully utilized for the qualitative analysis.

Characteristics of Algal Abundance and Statistical Analysis of Environmental Factors in Lake Paldang (팔당호 조류발생 특성 및 수질환경인자의 통계적 분석)

  • Park, Hae-Kyung;Lee, Hyun-Ju;Kim, Eun-Kyung;Jung, Dong-Il
    • Journal of Korean Society on Water Environment
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    • v.21 no.6
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    • pp.584-594
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    • 2005
  • The spatio-temporal abundance pattern of algae in Lake Paldang from 2002 to 2004 was investigated. The concentration of chlorophyll a representing algal biomass had fluctuated intensively throughout the year. Among three years, the highest algal biomass was shown in 2002, and typical growth peak of concentration of chlorophyll a was occurred in spring and autumn. There had been frequent rainfall in spring drought period in 2003 and it resulted in the decrease of the algal biomass. The distribution pattern of four algal groups on the surface water of Lake Paldang showed different abundance by season and by water area. In particular, different algal growth characteristics by water areas were observed. Influences of various environmental parameters on algal abundance in four water areas of Lake Paldang were analyzed statistically. From the results of Peason correlation analysis, it was understood that the kinds and affects of environmental parameters were different according to water areas and seasons. Based on the factors analysis of environmental parameters on the concentration of chlorophyll a, stepwise regression models whose independent variables were the factors produced by factor analysis and dependent variable was the concentration of chlorophyll a were derived by water areas and seasons. As a whole, factors related with organics and photosynthesis were revealed to have high affects to algal abundance, whereas limiting nutrients such as phosphorus and nitrogen showed little affect in Lake Paldang.

Relationship Between the Postural Alignments and Spatio-temporal Gait Parameters in Elderly Woman (여성 노인의 자세 정렬과 시공간 보행 변수 사이의 연관성)

  • Kim, Sung-Hyeon;Shin, Ho-Jin;Suh, Hye-Rim;Jung, Kyoung-Sim;Cho, Hwi-Young
    • Journal of the Korean Society of Physical Medicine
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    • v.15 no.3
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    • pp.117-125
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    • 2020
  • PURPOSE: Aging causes changes in the postural alignment and gait due to changes in the nervous and musculoskeletal systems. On the other hand, the relationship between the changes in posture alignment and gait is unclear. This study examined the relationship between the postural alignment and spatiotemporal gait parameters in Korean elderly women. METHODS: Thirty-two-healthy elderly women participated in this study. All subjects were assessed for their posture alignment and gait ability. Stepwise multiple linear regression was performed to determine to what extent the postural alignments could explain the spatiotemporal gait parameters. RESULTS: Coronal head angle was moderately correlated with the velocity (r = -.51), normalized velocity (r = -.46) and gait-stability ratio (r = .58) (p < .05). The trunk angle was moderately correlated with the normalized velocity (r = -.32) and gait-stability ratio (r = .32) and weakly correlated with the velocity (r = -.28) (p < .05). The coronal shoulder angle was moderately correlated with the swing phase (r = -.57), stance phase (r = .56), single limb stance (r = -.56) and double limb stance (r = .51) (p < .05). The coronal head angle and trunk angle accounted for 36% of the variance in velocity, 33% variance in normalized velocity and 46% variance in the gait-stability ratio (p < .05). The coronal shoulder angle accounted for 32% variance in the swing phase, 32% variance in the stance phase, 31% variance in the single limb stance and 26% variance in the double limb stance (p < .05). CONCLUSION: Changes in posture alignment in elderly women may serve as a biomarker to predict a decrease in walking ability due to physical aging.

Multivariate Congestion Prediction using Stacked LSTM Autoencoder based Bidirectional LSTM Model

  • Vijayalakshmi, B;Thanga, Ramya S;Ramar, K
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.1
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    • pp.216-238
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    • 2023
  • In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.