• Korean Journal of Remote Sensing
• /
• v.25 no.6
• /
• pp.547-557
• /
• 2009

LIDAR (LIght Detection And Ranging) is an active remote sensing technology which provides 3D coordinates of the Earth's surface by performing range measurements from the sensor. Early small footprint LIDAR systems recorded multiple discrete returns from the back-scattered energy. Recent advances in LIDAR hardware now make it possible to record full digital waveforms of the returned energy. LIDAR waveform decomposition involves separating the return waveform into a mixture of components which are then used to characterize the original data. The most common statistical mixture model used for this process is the Gaussian mixture. Waveform decomposition plays an important role in LIDAR waveform processing, since the resulting components are expected to represent reflection surfaces within waveform footprints. Hence the decomposition results ultimately affect the interpretation of LIDAR waveform data. Computational requirements in the waveform decomposition process result from two factors; (1) estimation of the number of components in a mixture and the resulting parameter estimates, which are inter-related and cannot be solved separately, and (2) parameter optimization does not have a closed form solution, and thus needs to be solved iteratively. The current state-of-the-art airborne LIDAR system acquires more than 50,000 waveforms per second, so decomposing the enormous number of waveforms is challenging using traditional single processor architecture. To tackle this issue, four parallel LIDAR waveform decomposition algorithms with different work load balancing schemes - (1) no weighting, (2) a decomposition results-based linear weighting, (3) a decomposition results-based squared weighting, and (4) a decomposition time-based linear weighting - were developed and tested with varying number of processors (8-256). The results were compared in terms of efficiency. Overall, the decomposition time-based linear weighting work load balancing approach yielded the best performance among four approaches.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.407-407
• /
• 2019

According to Asian Development Bank report Pakistan is among water scarce countries. Climate scenario on the basis IPCC fifth assessment report (AR5) revealed that annual mean temperature of Pakistan from year 2010-2019 was $17C^o$ which will rise up to $21C^o$ at the end of this century, similarly almost 10% decrease of annual rainfall is expected at the end of the century. It is a changing task in underdeveloped countries like Pakistan to meet the water demands of rapidly increasing population in a changing climate. While many studies have tackled scarcity and stream flow forecasting of the Upper Indus Basin (UIB) Pakistan, very few of them are related to socio-economic and climate change impact on sustainable water management of UIB. This study investigates the pattern of current and future surface water availability for various demand sites (e.g. domestic, agriculture and industrial) under different socio-economic and climate change scenarios in Upper Indus Basin (UIB) Pakistan for a period of 2010 to 2050. A state-of-the-art planning tool Water Evaluation and Planning (WEAP) is used to analyze the dynamics of current and future water demand. The stream flow data of five sub catchment (Astore, Gilgit, Hunza, Shigar and Shoyke) and entire UIB were calibrated and validated for the year of 2006 to 2011 using WEAP. The Nash Sutcliffe coefficient and coefficient of determination is achieved ranging from 0.63 to 0.92. The results indicate that unmet water demand is likely to increase severe threshold and the external driving forces e.g. socio-economic and climate change will create a gap between supply and demand of water.

• Journal of Korea Multimedia Society
• /
• v.22 no.10
• /
• pp.1168-1177
• /
• 2019

In order to diagnose and prevent Alzheimer's Disease (AD), it is becoming increasingly important to develop a CAD(Computer-aided Diagnosis) system for AD diagnosis, which provides effective treatment for patients by analyzing 3D MRI images. It is essential to apply powerful deep learning algorithms in order to automatically classify stages of Alzheimer's Disease and to develop a Alzheimer's Disease support diagnosis system that has the function of detecting hippocampus and CSF(Cerebrospinal fluid) which are important biomarkers in diagnosis of Alzheimer's Disease. In this paper, for AD diagnosis, we classify a given MRI data into three categories of AD, mild cognitive impairment, and normal control according by applying 3D brain MRI image to the Faster R-CNN model and detect hippocampus and CSF in MRI image. To do this, we use the 2D MRI slice images extracted from the 3D MRI data of the Faster R-CNN, and perform the widely used majority voting algorithm on the resulting bounding box labels for classification. To verify the proposed method, we used the public ADNI data set, which is the standard brain MRI database. Experimental results show that the proposed method achieves impressive classification performance compared with other state-of-the-art methods.

• Journal of Digital Convergence
• /
• v.19 no.10
• /
• pp.163-173
• /
• 2021

The purpose of this study was to explore a support model for domestic ICT companies to advance into overseas markets suitable for the post-corona era along with the rapidly changing global economic situation. As a result of the analysis, first, by analyzing the internationalization cases of domestic ICT companies through the realization theory, in the COVID-19 situation, domestic ICT companies organically respond to crisis situations through ad hoc responses, use of international networks, use of external organizations, and resource-based practices. Through qualitative analysis, we were able to confirm that we are growing overseas while achieving our goals. In addition, strategies for domestic ICT companies to grow through internationalization were derived. Ultimately, it was interpreted as a part that required advancement of government policy according to the government's overseas expansion support system.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.63 no.5
• /
• pp.49-62
• /
• 2021

The objective of this study was to evaluate the flood control capacity of the agricultural reservoir based on state-of-the-art climate change scenario - SSP (Shared Socioeconomic Pathways). 18 agricultural reservoirs were selected as the study sites, and future rainfall data based on SSP scenario provided by CMIP6 (Coupled Model Intercomparison Project 6) was applied to analyze the impact of climate change. The frequency analysis module, the rainfall-runoff module, the reservoir operation module, and their linkage system were built and applied to simulate probable rainfall, maximum inflow, maximum outflow, and maximum water level of the reservoirs. And the maximum values were compared with the design values, such as design flood of reservoirs, design flood of direct downstream, and top of dam elevation, respectively. According to whether or not the maximum values exceed each design value, cases were divided into eight categories; I-O-H, I-O, I-H, I, O-H, O, H, X. Probable rainfall (200-yr frequency, 12-h duration) for observed data (1973~2020) was a maximum of 445.2 mm and increased to 619.1~1,359.7 mm in the future (2011~2100). For the present, 61.1% of the reservoirs corresponded to I-O, which means the reservoirs have sufficient capacity to discharge large inflow; however, there is a risk of overflowing downstream due to excessive outflow. For the future, six reservoirs (Idong, Baekgok, Yedang, Tapjung, Naju, Jangsung) were changed from I-O to I-O-H, which means inflow increases beyond the discharge capacity due to climate change, and there is a risk of collapse due to dam overflow.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.9 no.1
• /
• pp.815-824
• /
• 2019

It is not easy to present a generalized operating model because the operating environment of a sport event is composed of a complex matrix structure. In this study, we propose 'standardization' which provides guidance of concept and process of sport event management to solve this sports event management problem. To purpose complete of this study, the frame was developed by the international standard ISO 9001: 2015 is applied. The standards framework for sports event process management system structure proposed in this study consists of scope of application, citing standard, Terms and definitions, organizational situation, leadership, planning, support, operation, performance evaluation, and improvement. This sport event process management system standard can be applied to any organization that wants to host, prepare, and operate sport events regardless of the form or scale of the sport event. In addition, this standard was focused on process management of life-cycle stages of sporting events, therefor it was possible to manage interrelationships and dependencies between processes and processes.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.9 no.3
• /
• pp.51-59
• /
• 2019

In the foreign language learning theory, self-regulated learning, subject interest, learning flow, and self-efficacy have been studied as major constructs. With the help of researches regarding these constructs, a research model was set up and the contents were analyzed through SEM analysis in order to grasp the influence of these constructs on each other. Through data collected from middle school students in Gyeongnam, the analysis result shows as follows. First, the subject interest has a positive influence on learning flow. Second, the subject interest has a positive influence on self-efficacy as well as self regulated learning. Third, learning flow has a positive effect on self-efficacy. Fourth, self regulated learning has a positive influence on self-efficacy. Fifth, self-regulated learning has a positive influence on learning flow. As is shown in the analysis, in case of English education, subject specific interest brings forth learning flow and enhances self-efficacy as well as self-regulated learning thus, leading to academic achievements.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.9 no.7
• /
• pp.891-900
• /
• 2019

In this paper, we investigate the relationship between IPR creation and export activity. And we try to examine the effects of IPR use as innovation on export performance. The dataset used in the empirical analysis are the annual "Survey of Business Activity(2006~2014)" panel data which include total of 6,144 samples of firms. Data set includes the sample characteristic such as employee, industry, export performance, possession/use/development of IPR. According to analysis results, this paper confirms that R&D and export activities of firms make positive effects on IPR creation. In addition, this paper finds that IPR use of firms make positive effects on firm's export performance. Exporting firms achieve higher export performance by developing new products and processes to enter and compete in overseas markets. In addition, exporting firms can achieve higher performance by using intellectual property rights to appropriate innovation outcomes in foreign markets and to exclude the possibility of patent disputes in advance.

• The Journal of Korean Institute of Next Generation Computing
• /
• v.15 no.6
• /
• pp.7-14
• /
• 2019

The automatic monitoring and detection of crowd behavior in the surveillance videos has obtained significant attention in the field of computer vision due to its vast applications such as security, safety and protection of assets etc. Also, the field of crowd analysis is growing upwards in the research community. For this purpose, it is very necessary to detect and analyze the crowd behavior. In this paper, we proposed a deep learning-based method which detects abnormal activities in surveillance cameras installed in a smart city. A fine-tuned VGG-16 model is trained on publicly available benchmark crowd dataset and is tested on real-time streaming. The CCTV camera captures the video stream, when abnormal activity is detected, an alert is generated and is sent to the nearest police station to take immediate action before further loss. We experimentally have proven that the proposed method outperforms over the existing state-of-the-art techniques.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.9 no.8
• /
• pp.199-208
• /
• 2019

The escape theory is the theory of problem behavior such as suicide. The purpose of this study is to investigate the causes of gaming disorder, which has been attracting attention as a typical youth problem, through escape theory. Suicide theory is a process in which the problem triggered by the negative external environment flows into internal attribution and self-criticism, and this leads to a process leading to problematic behavior with disgust self-awareness. This process was applied to the environment, psychology, and behavior of adolescents. As a result, the lack of affection and consistency of the parents resulted in negative external environment, which affected the self-esteem of children by creating a negative external environment. And low self-esteem caused negative emotions, lowered self control, and confirmed to induce game addiction. The results of this analysis show that game addiction has a structure similar to obsessive behaviors such as binge eating and shopping addiction explained through the escape theory model and it is necessary to concentrate more on the environmental psychological factors for game addiction research.