• Journal of Communications and Networks
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• v.14 no.1
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• pp.1-9
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• 2012

We consider a receiving node, located at the origin, and a Poisson point process (PPP) that models the locations of the desired transmitter as well as the interferers. Interference is known to be non-Gaussian in this scenario. The capacity bounds for additive non-Gaussian channels depend not only on the power of interference (i.e., up to second order statistics) but also on its entropy power which is influenced by higher order statistics as well. Therefore, a complete statistical characterization of interference is required to obtain the capacity bounds. While the statistics of sum of signal and interference is known in closed form, the statistics of interference highly depends on the location of the desired transmitter. In this paper, we show that there is a tradeoff between entropy power of interference on the one hand and signal and interference power on the other hand which have conflicting effects on the channel capacity. We obtain closed form results for the cumulants of the interference, when the desired transmitter node is an arbitrary neighbor of the receiver. We show that to find the cumulants, joint statistics of distances in the PPP will be required which we obtain in closed form. Using the cumulants, we approximate the interference entropy power and obtain bounds on the capacity of the channel between an arbitrary transmitter and the receiver. Our results provide insight and shed light on the capacity of links in a Poisson network. In particular, we show that, in a Poisson network, the closest hop is not necessarily the highest capacity link.

• Computers and Concrete
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• v.10 no.3
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• pp.277-294
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• 2012

The aim of the study is to determine the modal parameters of a prototype damaged arch dam by operational modal analysis (OMA) method for some damage scenarios. For this purpose, a prototype arch dam-reservoir-foundation model is constructed under laboratory conditions. Ambient vibration tests on the arch dam model are performed to identify the modal parameters such as natural frequency, mode shape and damping ratio. The tests are conducted for four test-case scenarios: an undamaged dam with empty reservoir, two different damaged dams with empty reservoirs, and a damaged dam with full reservoir. Loading simulating random impact effects is applied on the dam to crack. Cracks and fractures occurred at the middle of the upper part of the dams and distributed through the abutments. Sensitivity accelerometers are placed on the dams' crests to collect signals for measurements. Operational modal analysis software processes the signals collected from the ambient vibration tests, and enhanced frequency domain decomposition and stochastic subspace identification techniques are used to estimate modal parameters of the dams. The modal parameters are obtained to establish a basis for comparison of the results of two techniques for each damage case. Results show that approximately 35-40% difference exists between the natural frequencies obtained from Case 1 and Case 4. The natural frequencies of the dam considerably decrease with increasing cracks. However, observation shows that the filled reservoir slightly affected modal parameters of the dam after severe cracking. The mode shapes obtained are symmetrical and anti-symmetrical. Apparently, mode shapes in Case 1 represent the probable responses of arch dams more accurately. Also, damping ratio show an increase when cracking increases.

• Entomological Research
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• v.48 no.6
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• pp.505-513
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• 2018

The red imported fire ant is considered one of the most notorious invasive species because of its adverse impact on both humans and ecosystems. Public concern regarding red imported fire ants has been increasing, as they have been found seven times in South Korea. Even if red imported fire ants are not yet colonized in South Korea, a proper quarantine plan is necessary to prevent their widespread distribution. As a basis for quarantine planning, we modeled the potential distribution of the red imported fire ant under current climate conditions using six different species distribution models (SDMs) and then selected the random forest (RF) model for modeling the potential distribution under climate change. We acquired occurrence data from the Global Biodiversity Information Facility (GBIF) and bioclimatic data from WorldClim. We modeled at the global scale to project the potential distribution under the current climate and then applied models at the local scale to project the potential distribution of the red imported fire ant under climate change. Modeled results successfully represent the current distribution of red imported fire ants. The potential distribution area for red imported fire ants increased to include major harbors and airports in South Korea under the climate change scenario (RCP 8.5). Thus, we are able to provide a potential distribution of red imported fire ant that is necessary to establish a proper quarantine plan for their management to minimize adverse impacts of climate change.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.75-93
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• 2022

Machine learning (ML) data-driven meta-model is proposed as a surrogate model to reduce the excessive computational cost of the physics-based model and facilitate the real-time prediction of a nuclear power plant's transient response. To forecast the transient response three machine learning (ML) meta-models based on recurrent neural networks (RNNs); specifically, Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), and a sequence combination of Convolutional Neural Network (CNN) and LSTM are developed. The chosen accident scenario is a control element assembly withdrawal at power concurrent with the Loss Of Offsite Power (LOOP). The transient response was obtained using the best estimate thermal hydraulics code, MARS-KS, and cross-validated against the Design and control document (DCD). DAKOTA software is loosely coupled with MARS-KS code via a python interface to perform the Best Estimate Plus Uncertainty Quantification (BEPU) analysis and generate a time series database of the system response to train, test and validate the ML meta-models. Key uncertain parameters identified as required by the CASU methodology were propagated using the non-parametric Monte-Carlo (MC) random propagation and Latin Hypercube Sampling technique until a statistically significant database (181 samples) as required by Wilk's fifth order is achieved with 95% probability and 95% confidence level. The three ML RNN models were built and optimized with the help of the Talos tool and demonstrated excellent performance in forecasting the most probable NPP transient response. This research was guided by the Systems Engineering (SE) approach for the systematic and efficient planning and execution of the research.

• Economic Analysis
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• v.27 no.1
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• pp.37-66
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• 2021

This paper examines the potential impacts of COVID-19 on poverty in ASEAN countries. The first estimate, adopted from Summer et al. (2020) and Nonvide (2020), configures three scenarios of contractions in per capita household income or consumption; the impact of each scenario on poverty is calculated using poverty lines at different thresholds. In the second estimate, poverty impacts in 2020 and 2021 were projected using regression models controlling for unobserved country effects, unbalanced data, and endogeneity. COVID-19 has been shown to have negative impacts on poverty reduction in the ASEAN Member States. To reduce poverty, concerted efforts are needed to implement policies for reducing income inequality and promoting economic growth. Such efforts will not only speed up the countries' return to pre-pandemic poverty levels but also contribute to further accelerating poverty reduction.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.338-343
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• 2013

Integrated Project Delivery (IPD) as a delivery method fully capitalizes on an integrated project team that takes advantage of the knowledge of all team members to maximize project outcomes. IPD is currently the highest form of collaboration available because all three core project stakeholders, owner, designer and contractor, are aligned to the same purpose. Compared with traditional project delivery approaches such as Design-Bid-Build (DBB), Design-Build (DB), and CM at-Risk, IPD is distinguished in that it eliminates the adversarial nature of the business by encouraging transparency, open communication, honesty and collaboration among all project stakeholders. The team appropriately shares the project risk and reward. Sharing reward is easy, while it is hard to fairly share a failure. So the compensation structure and the contingency in IPD are very different from those in traditional delivery methods and they are expected to encourage motivation, inspiration and creativity of all project stakeholders to achieve project success. This paper investigates the compensation structure in IPD and provides a method to determine the proper level of contingency allocation to reduce the risk of cost overrun. It also proposes a method in which contingency could be used as a functional monetary incentive when established to produce the desired level of collaboration in IPD. Based on the compensation structure scenario discovered, a probabilistic contingency calculation model was created by evaluating the random nature of changes and various risk drivers. The model can be used by the IPD team to forecast the probability of the cost overrun and equip the IPD team with confidence to really enjoy the benefits of collaborative team work.

• Journal of Advanced Navigation Technology
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• v.26 no.5
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• pp.304-311
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• 2022

Although the SEAD(suppression to enemy air defenses) mission is a strategically important task in modern warfare, the high risk of direct exposure to enemy air defense assets forces to use of unmanned aerial vehicles. this paper proposes a path planning algorithm for SEAD mission for an unmanned aerial vehicle and a method for calculating the mission effectiveness on the planned path. Based on the RRT-based path planning algorithm, a low-altitude ingress/egress flight path that can consider the enemy's short-range air defense threat was generated. The Dubins path-based Intercept path planning technique was used to generate a path that is the shortest path while avoiding the enemy's short-range anti-aircraft threat as much as possible. The ingress/intercept/egress paths were connected in order. In addition, mission effectiveness consisting of fuel consumption, the survival probability, the time required to perform the mission, and the target destruction probability was calculated based on the generated path. The proposed techniques were verified through a scenario.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.276-290
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• 2023

Several efforts in Korea are currently underway with the goal of commercializing autonomous vehicles. Hence, various studies are emerging on autonomous vehicles that drive safely and quickly according to operating guidelines. The current study examines the path search of an autonomous vehicle from a microscopic viewpoint and tries to prove the efficiency required by learning the lane change of an autonomous vehicle through Deep Q-Learning. A SUMO was used to achieve this purpose. The scenario was set to start with a random lane at the starting point and make a right turn through a lane change to the third lane at the destination. As a result of the study, the analysis was divided into simulation-based lane change and simulation-based lane change applied with Deep Q-Learning. The average traffic speed was improved by about 40% in the case of simulation with Deep Q-Learning applied, compared to the case without application, and the average waiting time was reduced by about 2 seconds and the average queue length by about 2.3 vehicles.