• ETRI Journal
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• v.45 no.5
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• pp.768-780
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• 2023

The application of unmanned aerial vehicles (UAVs) has recently attracted considerable interest in various areas. A three-dimensional multiple-input multiple-output concentric two-hemisphere model is proposed to characterize the scattering environment around a vehicle in an urban UAV-to-vehicle communication scenario. Multipath components of the model consisted of lineof-sight and single-bounced components. This study focused on the key parameters that determine the scatterer distribution. A time-variant process was used to analyze the nonstationarity of the proposed model. Vital statistical properties, such as the space-time-frequency correlation function, Doppler power spectral density, level-crossing rate, average fade duration, and channel capacity, were derived and analyzed. The results indicated that with an increase in the maximum scatter radius, the time correlation and level-crossing rate decreased, the frequency correlation function had a faster downward trend, and average fade duration increased. In addition, with the increase of concentration parameter, the time correlation, space correlation, and level-crossing rate increased, average fade duration decreased, and Doppler power spectral density became flatter. The proposed model was compared with current geometry-based stochastic models (GBSMs) and showed good consistency. In addition, we verified the nonstationarity in the temporal and spatial domains of the proposed model. These conclusions can be used as references in the design of more reasonable communication systems.

• Atmosphere
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• v.16 no.3
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• pp.225-234
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• 2006

Convective systems propagate eastward with a persistent pattern in the longitude-time space. The characteristic structure and fluctuation of convective system is helpful in determining its predictability. In this study, convective index (CI) was defined as a difference between GOES-9 window and water vapor channel brightness temperatures following Mosher (2001). Then the temporal-spatial scales and variational characteristics of the summer convective systems in the East Asia were analyzed. It is found that the average moving speed of the convective system is about 14 m/s which is much faster than the low pressure system in the summer. Their average duration is about 12 hours and the average length of the cloud streak is about 750km. These characteristics are consistent with results from other studies. Although the convective systems are forced by the synoptic system and are mostly developed in the eastern edge of the Tibetan Plateau, they have a persistent pattern, i.e., appearance of the maximum intensity of convective systems, as they approach the Korean Peninsula. The consistency of the convective systems, i.e., the eastward propagation, suggests that there exists an intrinsic predictability.

• Atmosphere
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• v.17 no.4
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• pp.327-337
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• 2007

In this study, we examined the new ensemble training approach to reduce the systematic error and improve prediction skill of wind by using the Short-range Ensemble prediction system (SENSE), which is the mesoscale multi-model ensemble prediction system. The SENSE has 16 ensemble members based on the MM5, WRF ARW, and WRF NMM. We evaluated the skill of surface wind prediction compared with AWS (Automatic Weather Station) observation during the summer season (June - August, 2006). At first stage, the correction of initial state for each member was performed with respect to the observed values, and the corrected members get the training stage to find out an adaptive weight function, which is formulated by Root Mean Square Vector Error (RMSVE). It was found that the optimal training period was 1-day through the experiments of sensitivity to the training interval. We obtained the weighted ensemble average which reveals smaller errors of the spatial and temporal pattern of wind speed than those of the simple ensemble average.

• Ocean Science Journal
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• v.42 no.2
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• pp.103-116
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• 2007

Seasonal changes of tide signal(s), temperature, salinity and current were studied during the years 2004-2005 in the northernmost Gulf of Aqaba, which is under developmental activities, to obtain scientific bases for best management and sustainability. Spectrum analysis revealed permanent signals of tide measurements during all seasons, which represented semidiurnal and diurnal barotropic tides. The other signal periods of 8.13, 6.10-6.32, 4.16 and 1.02-1.05 h were not detected in all seasons, which were related to shallow water compound and overtides of principle solar and lunar constituent and to seiches generated in the Red Sea and the Gulf of Aqaba. Spatial and temporal distribution of temperature, salinity and density showed significant differences between months in the coastal and offshore region and no significant differences among the coastal sites, between the surface and bottom waters and between coastal and offshore waters. Therefore, the temporal and spatial variation of water properties in the northernmost Gulf of Aqaba behave similarly compared to other parts. The coastal current below 12 m depth was weak $(3-6\;cms^{-1})$ and fluctuated from east-northeastward to west-southwestward (parallel to the shoreline), which may be related to the effect of bottom topography and/or current density due to differential cooling between eastern and western parts in the study area, and wind-induced upwelling and downwelling in the eastern and western side, respectively. The prevailing northerly winds and stratification conditions during summer were the main causes of the southward current at 6 and 12 m depths with average speed of 28 and $12cms^{-1}$ respectively.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.877-885
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• 2022

Vision-based activity recognition has been widely attempted at construction sites to estimate productivity and enhance workers' health and safety. Previous studies have focused on extracting an individual worker's postural information from sequential image frames for activity recognition. However, various trades of workers perform different tasks with similar postural patterns, which degrades the performance of activity recognition based on postural information. To this end, this research exploited a concept of human-object interaction, the interaction between a worker and their surrounding objects, considering the fact that trade workers interact with a specific object (e.g., working tools or construction materials) relevant to their trades. This research developed an approach to understand the context from sequential image frames based on four features: posture, object, spatial features, and temporal feature. Both posture and object features were used to analyze the interaction between the worker and the target object, and the other two features were used to detect movements from the entire region of image frames in both temporal and spatial domains. The developed approach used convolutional neural networks (CNN) for feature extractors and activity classifiers and long short-term memory (LSTM) was also used as an activity classifier. The developed approach provided an average accuracy of 85.96% for classifying 12 target construction tasks performed by two trades of workers, which was higher than two benchmark models. This experimental result indicated that integrating a concept of the human-object interaction offers great benefits in activity recognition when various trade workers coexist in a scene.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.340-354
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• 2021

The aim of this study was to investigate the spatial and temporal distribution of phytoplankton biomass and community composition in Jinhae Bay on the southern coast of Korea. Phytoplankton pigment analysis was conducted using ultra performance liquid chromatography (UPLC) were conducted from April to December 2019 at seven stations. Temperature, salinity, and dissolved oxygen (DO) and inorganic nutrients (dissolved nitrogen, dissolved phosphorus, and orthosilicic acid) were measured to investigate the environmental factors associated with the structure of phytoplankton community. Phytoplankton biomass (Chl-a) was the highest in July (mean 15.4±4.3 ㎍/L) and the lowest in December (mean 3.5±0.6 ㎍/L). Fucoxanthin was the most abundant carotenoid and showed a similar variation pattern to Chl-a, peridinin, and Chl-b. Phytoplankton community composition analysis showed that diatoms were a predominant group with an average abundance of 70 % whereas chlorophytes, cryptophytes, and dinoflagellates often appeared with lower averages. Further, the dominance of diatoms was closely correlated with water temperature and N:P ratio, which might be influenced by high temperatures in the summer and nutrient loading from the land. Additionally, freshwater and nutrient input by rainfall was estimated to be the most important environmental factor. Hence, the spatial and temporal variations in the composition of phytoplankton pigments and phytoplankton community were correlated with physicochemical and environmental parameters.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.43-52
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• 2023

Rubber produced by rubber companies is subjected to quality suitability inspection through rheometer test, followed by secondary processing for automobile parts. However, rheometer test is being conducted by humans and has the disadvantage of being very dependent on experts. In order to solve this problem, this paper proposes a deep learning-based rheometer quality inspection system. The proposed system combines LSTM(Long Short-Term Memory) and CNN(Convolutional Neural Network) to take advantage of temporal and spatial characteristics from the rheometer. Next, combination materials of each rubber was used as an auxiliary input to enable quality conformity inspection of various rubber products in one model. The proposed method examined its performance with 30,000 validation datasets. As a result, an F1-score of 0.9940 was achieved on average, and its excellence was proved.

• Journal of Korean Tunnelling and Underground Space Association
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• v.8 no.3
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• pp.249-257
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• 2006

The spatial distribution of design parameters greatly affects tunnel behavior during and after construction, as well as in the long-term temporal responses. However, the tunnel design parameters commonly used in numerical modeling tend to be representative or average values of global-scale properties. Furthermore, the uncertainty and spatial variation of the design parameters increase as the tunnel scale increases. Consequently, the probability of failure also increases. In order to achieve structural stability in large-section tunnels, the design framework must take into consideration the quantitative effect of design parameter variations on tunnel behavior. Therefore, this paper suggests a statistical approach to numerical modeling to explore the effect of spatially distributed design parameters in a circular tunnel. Also, the effect of spatial variation in the lining strength is studied in this paper. The numerical results suggest that the deformation around the tunnel increases with an increase in the variation of the design parameters.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.1035-1039
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• 2010

For 65 national forest areas in 1993 to 2008, the ambient sulfur dioxide ($SO_2$) concentrations were measured monthly using passive samplers and compared to the those of urban areas in order to investigate the characteristics of temporal and spatial distribution. In the forest areas, annual average concentration of sulfur dioxide gradually decreased from the beginning year of monitoring to 1997 and then had no significant change, such as the annual trend in urban areas monitored by Ministry of Environment. For the monitoring term, average concentration of sulfur dioxide in the forest areas was 5.6ppb, which was lower than the 10.1ppb in the urban areas and the EC ecological standard level (7.6 ppb). Seasonally, both in forest areas and urban areas the monthly average concentrations were much higher in winter and spring due to much more heating fuel consumption, and lowest in summer. Regional comparison to other regions of Gyeongbuk and Gyeonggi province showed that the concentration of sulfur dioxide was the highest during year. A significant positive correlation between sulfur oxides' emissions and sulfur dioxide concentration by province was observed, reflecting that the size and proximity of sources of atmospheric sulfur oxides could be important factors in determination.

• Journal of ILASS-Korea
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• v.18 no.1
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• pp.27-34
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• 2013

A preburner is one of the key components for a staged combustion cycle engine fueled by kerosene and Lox. Since it has oxygen rich combustion inside, temperature control is very crucial. The temperature of the exhaust gas should be low enough not to burn turbine blade and yet high to keep the efficiency high. In addition temporal and spatial deviations also managed strictly. Conventionally, the required average and maximum temperature are determined by engine system and the preburner should be developed to meet the criteria. Currently being developed preburner has 50K spatial temperature deviation requirement. It was estimated by numerical simulations and proven by tests. The numerical analysis were done with both supercritical condition and normal conditions. The tests results showed that the temperature deviations were less than expected, and the results from the test and simulations were well agreed when the supercritical conditions were considered. Above all, since the gas temperature created by the preburner is very stable with minimum deviation, the preburner developed can be used to drive a turbine and for gas-liquid combustion chambers.