• Proceedings of the Korea Concrete Institute Conference
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• 1996.10a
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• pp.122-126
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• 1996

In recent years, plenty of problems in the large-scaled bridges, piers…have been reported to the public due to the severe environment factors. The use of Epoxy-Coated reinforcement against salt and sulfate corrosion is considered as a reasonable solution and tested to study the bond performance between the thickness of coating and bond stresses. The results are that the strength of bond was decreased by 10 to 13 percent in the case of 100$\mu\textrm{m}$ of coating thickness and by 15 to 25 percent in the case of 200$\mu\textrm{m}$ to 300$\mu\textrm{m}$ and significantly fell down when the thickness was above 300$\mu\textrm{m}$. Accordingly, a 200$\mu\textrm{m}$ coating-thickness to the reinforcement is suggested to maintain the acceptable bond mechanism and goes well with the ASTM(item NO.A775) and those of Korean Concrete Institute.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.853-873
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• 2021

In recent years, deep reinforcement learning (DRL) models are enjoying great interest as their success in a variety of challenging tasks. Deep Q-Network (DQN) is a widely used deep reinforcement learning model, which trains an intelligent agent that executes optimal actions while interacting with an environment. This model is well known for its ability to surpass skilled human players across many Atari 2600 games. Although DQN has achieved excellent performance in practice, there lacks a clear understanding of why the model works. In this paper, we present a visual analytics system for understanding deep Q-network in a non-blind matter. Based on the stored data generated from the training and testing process, four coordinated views are designed to expose the internal execution mechanism of DQN from different perspectives. We report the system performance and demonstrate its effectiveness through two case studies. By using our system, users can learn the relationship between states and Q-values, the function of convolutional layers, the strategies learned by DQN and the rationality of decisions made by the agent.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5135-5142
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• 2011

A flexible mechanism is proposed in this paper to improve the dynamic response performance of a traffic flow control system in an urban area. The roads, vehicles, and traffic control systems are all modeled as intelligent systems, wherein a wireless communication network is used as the medium of communication between the vehicles and the roads. The necessary sensor networks are installed in the roads and on the roadside upon which reinforcement learning is adopted as the core algorithm for this mechanism. A traffic policy can be planned online according to the updated situations on the roads, based on all the information from the vehicles and the roads. This improves the flexibility of traffic flow and offers a much more efficient use of the roads over a traditional traffic control system. The optimum intersection signals can be learned automatically online. An intersection control system is studied as an example of the mechanism using Q-learning based algorithm, and simulation results showed that the proposed mechanism can improve the traffic efficiency and the waiting time at the signal light by more than 30% in various conditions compare to the traditional signaling system.

• ETRI Journal
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• v.43 no.5
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• pp.775-786
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• 2021

To translate in real time, a simultaneous translation system should determine when to stop reading source tokens and generate target tokens corresponding to a partial source sentence read up to that point. However, conventional attention-based neural machine translation (NMT) models cannot produce translations with adequate latency in online scenarios because they wait until a source sentence is completed to compute alignment between the source and target tokens. To address this issue, we propose a reinforced learning (RL)-based attention mechanism, the reinforced attention mechanism, which allows a neural translation model to jointly train the stopping criterion and a partial translation model. The proposed attention mechanism comprises two modules, one to ensure translation quality and the other to address latency. Different from previous RL-based simultaneous translation systems, which learn the stopping criterion from a fixed NMT model, the modules can be trained jointly with a novel reward function. In our experiments, the proposed model has better translation quality and comparable latency compared to previous models.

• Proceedings of the Korea Concrete Institute Conference
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• 1990.04a
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• pp.51-56
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• 1990

Investigations on the behavior of steel fiber reinforced high strength concrete beams subjected to predominant shear are accomplished to determine their diagonal shear strength including ultimate shear strength. The parameters varied were the volume fraction(Vf) of the fibers, shear span depth ratio(a/d). The test result show that diagonal shear strength and ultimate shear strength are increased siginificantly due to crack arrest mechanism. Predictive equations are suggested for evaluating the diagonal cracking strength and ultimate shear strength of the fiber reinforced high strength concrete beams.

• Journal of the Korean GEO-environmental Society
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• v.4 no.4
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• pp.85-96
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• 2003

The Geocell system is the advanced system of Geo-grids, and is one of geosynthetics used for earth reinforcement of weak soil. It is the way to increase earth strength and bearing capacity by using three dimension type of geo-composite. This paper analyzed the bearing capacity mechanism of Geocell system for earth reinforcement. Plate loading tests under the model laboratory condition were performed, and the increase of bearing capacity and the decrease of settlement with shallow foundation were evaluated.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.739-743
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• 2008

In this paper, we introduce a method for automatically generating accompaniment music, according to user's input melody. The initial accompaniment chord is generated by analyzing user's input melody. Then next chords are generated continuously based on markov chain probability table in which transition probabilities of each chord are defined. The probability table is learned according to reinforcement learning mechanism using sample data of existing music. Also during playing accompaniment, the probability table is learned and refined using reward values obtained in each status to improve the behavior of playing the chord in real-time. The similarity between user's input melody and each chord is calculated using pitch class histogram. Using our method, accompaniment chords harmonized with user's melody can be generated automatically in real-time.

• Tunnel and Underground Space
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• v.21 no.4
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• pp.251-263
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• 2011

The geomechanical characteristics of rock and the structural geological feature of the fault should be studied and examined for the successful construction of large-span tunnel. In this case study, that is a important case for the tunnel collapse and reinforcement during the construction for the waterway tunnel at large thrust fault zone in schist, we carried out geological and geotechnical survey for make the cause and mechanism of tunnel collapse. Also, we have designed the reinforcement and re-excavation for the safe construction for collapse zone and have carried out successfully the re-excavation and finished the final concrete lining.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05a
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• pp.126-129
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• 2006

A bending moment $M_u$ transferred at slab-column connection is resisted at the slab critical section by flexure and shear. The ACI 318-05 Building Code(1) gives an empirical equation for the fraction ${\gamma}_{\upsilon}$ of the moment $M_u$ to be transferred by shear at the slab critical section at d/2 from the column face and also the effective wide(c+3h). The equation is based on tests of interior slab-column connections without shear reinforcement. In order to investigate the data eight test specimens were examined. The test shows that increased slab load substantially reduces both the unbalanced moment capacity and the lateral drift capacity of the connection. Especially, the specimens with the bottom reinforcement existence and nonexistence, appears remarkable differences. Studies also show that the code equation for ${\gamma}_{\upsilon}$ does not apply to all cases. The purpose of this study is to compare the test results with present ACI 318-05 Building Code provisions for design of slab-column connections and with the analysis of the experimental data for a new limitation of strength equation without shear reinforcement and bottom reinforcement.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.11a
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• pp.233-236
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• 2008

This study evaluates the seismic performance of post-tensioned(PT) flat plate frames with or without slab bottom reinforcement. For this purpose, 3 and 9 story PT flat plate frames designed only considering gravity loads. This study conducts a nonlinear static pushover analysis. This study use an analytical model which is able to represent punching shear failure and fracture mechanism. The analytical results showed that seismic performance of PT flat plate frame is strongly influenced by the existence of slab bottom reinforcement through column. By placing slab bottom reinforcement in PT flat plate frame, lateral strength and deformation capacity are significantly increased.