• Journal of the Korean Institute of Landscape Architecture
• /
• v.50 no.5
• /
• pp.69-79
• /
• 2022

This study aims to assess the current understanding of the landscape of wind power facilities as renewable energy sources that supply sightseeing, tourism, and other opportunities. Therefore, social media data related to the landscape of wind power facilities experienced by visitors from different regions was analyzed. The analysis results showed that the common characteristics of the landscape of wind power facilities are based on the scale of wind power facilities, the distance between overlook points of wind power facilities, the visual openness of the wind power facilities from the overlook points, and the terrain where the wind power facilities are located. In addition, the preference for wind power facilities is higher in places where the shape of wind power facilities and the surrounding landscape can be clearly seen- flat ground or the sea are considered better landscapes. Negative keywords about the landscape appear on Gade Mountain in Taibai, Meifeng Mountain in Taibai, Taiqi Mountain, and Gyeongju Wind Power Generation Facilities on Gyeongshang Road in Gangwon. The keyword 'negation' occurs when looking at wind power facilities at close range. Because of the high angle of the view, viewers can feel overwhelmed seeing the size of the facility and the ridge simultaneously, feeling psychological pressure. On the contrary, positive landscape adjectives are obtained from wind power facilities on flat ground or the sea. Visitors think that the visual volume of the landscape is fully ensured on flat ground or the sea, and it is a symbolic element that can represent the site. This study analyzes landscape awareness based on the opinions of visitors who have experienced wind power facilities. However, wind power facilities are built in different areas. Therefore, landscape characteristics are different, and there are many variables, such as viewpoints and observers, so the research results are difficult to popularize and have limitations. In recent years, landscape damage due to the construction of wind power facilities has become a hot issue, and the domestic methods of landscape evaluation of wind power facilities are unsatisfactory. Therefore, when evaluating the landscape of wind power facilities, the scale of wind power facilities, the inherent natural characteristics of the area where wind power facilities are set up, and the distance between wind power facilities and overlook points are important elements to consider. In addition, wind power facilities are set in the natural environment, which needs to be protected. Therefore, from the landscape perspective, it is necessary to study the landscape of wind power facilities and the surrounding environment.

• Journal of Wetlands Research
• /
• v.26 no.2
• /
• pp.147-159
• /
• 2024

Lack of streamflow observations makes model calibration difficult and limits model performance improvement. Satellite-based remote sensing products offer a new alternative as they can be actively utilized to obtain hydrological data. Recently, several studies have shown that artificial intelligence-based solutions are more appropriate than traditional conceptual and physical models. In this study, a data-driven approach combining various recurrent neural networks and decision tree-based algorithms is proposed, and the utilization of satellite remote sensing information for AI training is investigated. The satellite imagery used in this study is from MODIS and SMAP. The proposed approach is validated using publicly available data from 25 watersheds. Inspired by the traditional regionalization approach, a strategy is adopted to learn one data-driven model by integrating data from all basins, and the potential of the proposed approach is evaluated by using a leave-one-out cross-validation regionalization setting to predict streamflow from different basins with one model. The GRU + Light GBM model was found to be a suitable model combination for target basins and showed good streamflow prediction performance in ungauged basins (The average model efficiency coefficient for predicting daily streamflow in 25 ungauged basins is 0.7187) except for the period when streamflow is very small. The influence of satellite remote sensing information was found to be up to 10%, with the additional application of satellite information having a greater impact on streamflow prediction during low or dry seasons than during wet or normal seasons.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.24 no.1
• /
• pp.79-85
• /
• 2011

Bridge Weigh-in-Motion(BWIM) system calculates a travelling vehicle's weight without interruption of traffic flow by analyzing the signals that are acquired from various sensors installed in the bridge. BWIM system or data accumulated from the BWIM system can be utilized to development of updated live load model for highway bridge design, fatigue load model for estimation of remaining life of bridges, etc. Field test with moving trucks including various load cases should be performed to guarantee successful development of precise BWIM system. In this paper, a numerical simulation technique is adopted as an alternative or supplement to the vehicle traveling test that is indispensible but expensive in time and budget. The constructed numerical model is validated by comparison experimentally measured signal with numerically generated signal. Also vehicles with various dynamic characteristics and travelling conditions are considered in numerical simulation to investigate the variation of bridge responses. Considered parameters in the numerical study are vehicle velocity, natural frequency of the vehicle, height of entry bump, and lateral position of the vehicle. By analyzing the results, it is revealed that the lateral position and natural frequency of the vehicle should be considered to increase precision of developing BWIM system. Since generation of vehicle travelling signal by the numerical simulation technique costs much less than field test, a large number of test parameters can effectively be considered to validate the developed BWIM algorithm. Also, when artificial neural network technique is applied, voluminous data set required for training and testing of the neural network can be prepared by numerical generation. Consequently, proposed numerical simulation technique may contribute to improve precision and performance of BWIM systems.

• Korean Journal of Environment and Ecology
• /
• v.30 no.6
• /
• pp.1057-1066
• /
• 2016

This study examined how 'forest name' or 'information of forest healing effectiveness' influence their perceived environmental restorativeness (PER) and perceived healing effectiveness (PHE). Study area was the 'Forest Healing Road (FHR)' in Mudeungsan National Park. Data were collected from 247 visitors selected by convenient sampling method using questionnaire survey during May-June, 2015. Respondents who read interpretive signs (forest name and information on forest healing effectiveness of FHR were written) installed along the FHR were regarded as placebo group and respondents who didn't read them as control group. The results showed that there were no overall differences on PER and PHE between control and placebo groups. Placebo group, however, rated more positive on 'being away' factor of PER than control group. All four factors (i.e., being away, coherence, fascination, comparability) of PER statistically influenced PHE (p<0.001), and these factors explained 51.1% of PHE. The 'coherence' was the most influential to PHE, followed by 'being away', 'comparability', and 'fascination' in order. Placebo effects on PER were shown in male, in lower age group(age${\leq}54$), or respondents with lower visiting experience to FHR(${\leq}20$ times/year). Placebo effects on PHE were found in male, in small group (${\leq}2$ persons), in respondents who visited 'alone' or 'with relatives/family', or in respondents with lower visiting experience to FHR(${\leq}20$ times/year). Some research and managerial implications were suggested.

• Journal of the Korean Institute of Gas
• /
• v.20 no.5
• /
• pp.104-111
• /
• 2016

Recently, the quantities of chemical material are increasing in chemical industries. At that time, release accident is increasing due to aging of equipment, mechanical failure, human error, etc. and industrial complexes found community properties in a specific area. For that matter, chemical release accident can lead to hight probability of large disaster. There is a need to analyze the boundaries optimal sensor placement calculated by selecting release scenarios through release condition and wether condition in a chemical process for release detection and response. This paper is to investigate chlorine release accident scenarios using COMSOL. Through accident scenarios, a numerical calculation is studied to determine optimized sensor placement with weight of detection probability, detection time and concentration. In addition, validity of sensor placement is improved by robustness analysis about unpredicted accident scenarios. Therefore, this verifies our studies can be effectively applicable on any process. As mention above, the result of this study can help to place mobile sensor, to track gas release based concentration data.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.11
• /
• pp.1653-1660
• /
• 2016

The synthetic aperture rardar (SAR) is an active sensor using microwaves. It transmits a microwave signal, called a chirp pulse, and receives the reflected signal in a moving platform such as satellite and unmanned aerial vehicle. Since this sensor uses microwaves that can penetrate the atmosphere, SAR generates the images regardless of light and weather conditions. However SAR operates on the moving platform, the Doppler shift and the side-looking observation method should be considered. In addtion, a residual image or ghost image can be occurred according to selection of the pulse repetition frequency (PRF). In this paper, a range design of the PRF for the L-band spaceborne SAR system is studied for prevention of SAR image distortion. And the system is studied for prevention of SAR image distortion. And the system parameter and the PRF are calibrated iteratively according to the proposed system design procedure and design constraints. The MATLAB based on SAR system simulator has been developed to verify the validity of calculated PRF. The developed simulator assumes that SAR sensor is operated by the PRF calculated from the design. The results of the simulator show that the targets in image has a valid peak to side-lobe ratio (PSLR) so that the PRF can be used for the spaceborne SAR sensor.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.18 no.2
• /
• pp.120-134
• /
• 2015

Under the hypothesis that the form of road network could affect crime occurrence, this study demonstrates to prove them using Space Syntax with real crime data. We calculated integration, control, connection index by means of Space Syntax and analyzed the relationship between the three indexes and the number of crime occurrence on the each road. Next, in order to generalize the analysis results we adopted Multi-Agent Model and simulated several scenarios on the computer virtual space. The results revealed that integration index has the strongest relationship with crime occurrence both in the case of real study area and virtual space simulations. Though this study has several limitations on the extent of virtual space and realistic computer programming of agents' behavior, the results are meaningful to verify the relationship between the form of read network and crime occurrence. Moreover the simulation platform that this study developed has promising possibilities to find realistic solutions on the effective police deployment or facility layout to improve smart safe city development.

• Journal of Korea Multimedia Society
• /
• v.10 no.10
• /
• pp.1295-1309
• /
• 2007

A wireless access point is used for all communications in the infrastructure mode wireless home networking, including communication between mobile nodes in the same service area. When a mobile station in the infrastructure mode wireless home networking moves into a dead zone, the communication between the mobile station and the access point is disconnected. To solve this problem, the existing wireless home network platforms focus on the ad hoc mode wireless home networking. However, the performance of an ad hoc network is poorly decreased when the number of mobile participating in the ad hoc network increases. In addition, although the ad hoc routing technique is necessary to support seamless communication of mobile nodes, the existing routing protocols, such as AODV and DSR, do not consider that a wireless channel state could affect performance significantly. Therefore, we propose a wireless home networking platform based on the ESCOD (End-to-end Seamless multi-hop COnnection based on Dual network mode) technique incorporating the VLR (Virtual Link Routing) scheme that supports end-to-end seamless connections. Extensive experiments show that the proposed wireless home networking platform incorporating the VLR scheme outperforms wireless home networking platforms based on the AODV and the DSR routing protocols respectively in terms of low packet transmission failure rate, fast packet transmission time, high TCP performance, and a wider coverage area of wireless home networks.

• Korean Journal of Remote Sensing
• /
• v.36 no.3
• /
• pp.487-501
• /
• 2020

As a viable option for retrieval of LST (Land Surface Temperature), this paper presents a DNN (Deep Neural Network) based approach using 148 Landsat 8 images for South Korea. Because the brightness temperature and emissivity for the band 10 (approx. 11-㎛ wavelength) of Landsat 8 are derived by combining physics-based equations and empirical coefficients, they include uncertainties according to regional conditions such as meteorology, climate, topography, and vegetation. To overcome this, we used several land surface variables such as NDVI (Normalized Difference Vegetation Index), land cover types, topographic factors (elevation, slope, aspect, and ruggedness) as well as the T₀ calculated from the brightness temperature and emissivity. We optimized four seasonal DNN models using the input variables and in-situ observations from ASOS (Automated Synoptic Observing System) to retrieve the LST, which is an advanced approach when compared with the existing method of the bias correction using a linear equation. The validation statistics from the 1,728 matchups during 2013-2019 showed a good performance of the CC=0.910~0.917 and RMSE=3.245~3.365℃, especially for spring and fall. Also, our DNN models produced a stable LST for all types of land cover. A future work using big data from Landsat 5/7/8 with additional land surface variables will be necessary for a more reliable retrieval of LST for high-resolution satellite images.

• Journal of Convergence for Information Technology
• /
• v.8 no.1
• /
• pp.253-263
• /
• 2018

Textile fashion industry is a core foundation industry, having the majority of companies with 10 or more workers, in Northern Gyeonggi Province. however the industry is mostly comprised of small unit-stream enterprises, orders are greatly reduced due to lately accelerated overseas expansion of medium/large-sized vendors and the growth-inhibiting vicious circle has being set in, as this situation causes the reduction of investment. For resolving the problems, this study proposes required political factors and concrete policy proposals by designing AHP research model(4 layers and 36 elements), based on grasp of the transitional aspect of industrial scale and business environment through analysis of various industrial statistics, preceding research such as related literature search and (industrial/academic/R&D/government) specialist opinion investigation, and then calculating relative importance and priority of each factor(element) within each layer. And for raising usefulness and availability of the research result by concretely suggesting the vision, strategies, core tasks and detailed projects in which the research model and deduced result are reflected.