• Journal of the Korean Society for Aviation and Aeronautics
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• v.30 no.2
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• pp.34-43
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• 2022

In Efforts to prevent CFIT accidents so far, have been emphasizing various education measures to minimize the occurrence of human errors, as well as enforcement measures. However, current engineering measures remain in a system (TAWS) that gives warnings before colliding with ground or obstacles, and even actual automatic avoidance maneuvers are not implemented, which has limitations that cannot prevent accidents caused by human error. Currently, various attempts are being made to apply machine learning-based artificial intelligence agent technologies to the aviation safety field. In this paper, we propose a deep reinforcement learning-based artificial intelligence agent that can recognize CFIT situations and control aircraft to avoid them in the simulation environment. It also describes the composition of the learning environment, process, and results, and finally the experimental results using the learned agent. In the future, if the results of this study are expanded to learn the horizontal and vertical terrain radar detection information and camera image information of radar in addition to the terrain database, it is expected that it will become an agent capable of performing more robust CFIT autonomous avoidance.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.550-555
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• 2011

Utilizing construction knowledge and experiences in design phase can reduce change orders and improve productivity in construction phase. To do so, information must be made available to the design team in time. Current approaches for effective utilization of constructability knowledge, however, only focus on the formalization of constructability knowledge such as a checklist, which lacks the consideration of the appropriate use at the proper point in time. The inadequate use of constructability knowledge can result in unnecessary reworks. To deal with this problem, the design team needs to know what constructability knowledge is required for specific design activities in the design process. This paper presents a constructability implementation model using the dependency structure matrix (DSM) that focuses on information flows between design activities and constructability knowledge. For this objective, design activities in the design process are modeled in a matrix form based on their dependency. Then, constructability knowledge, which needs to be considered in the design stage, is mapped into activities and incorporated into the matrix, creating Constructability-DSM (C-DSM). Next, the partitioning algorithm is applied to C-DSM for optimal information flow. The Partitioned C-DSM is then analyzed based on the relationship between activities. Finally, the optimal utilization of construction knowledge in the design process is determined by identifying what constructability knowledge is required for each design activity, and how and when it is reflected to design for constructability. Thus, this research can help provide robust control actions to reduce unnecessary iterative cycles in design process for efficient constructability implementation.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.8-14
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• 2020

Recently, there was an increasing demand for an integrated access control system which is capable of user recognition, door control, and facility operations control for smart buildings automation. The market available door lock access control solutions need to be improved from the current level security of door locks operations where security is compromised when a password or digital keys are exposed to the strangers. At present, the access control system solution providers focusing on developing an automatic access control system using (RF) based technologies like bluetooth, WiFi, etc. All the existing automatic door access control technologies required an additional hardware interface and always vulnerable security threads. This paper proposes the user identification and authentication solution for automatic door lock control operations using camera based visible light communication (VLC) technology. This proposed approach use the cameras installed in building facility, user smart devices and IoT open source controller based LED light sensors installed in buildings infrastructure. The building facility installed IoT LED light sensors transmit the authorized user and facility information color grid code and the smart device camera decode the user informations and verify with stored user information then indicate the authentication status to the user and send authentication acknowledgement to facility door lock integrated camera to control the door lock operations. The camera based VLC receiver uses the artificial intelligence (AI) methods to decode VLC data to improve the VLC performance. This paper implements the testbed model using IoT open-source based LED light sensor with CCTV camera and user smartphone devices. The experiment results are verified with custom made convolutional neural network (CNN) based AI techniques for VLC deciding method on smart devices and PC based CCTV monitoring solutions. The archived experiment results confirm that proposed door access control solution is effective and robust for automatic door access control.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.174-179
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• 2003

Through the simultaneous localization and map building (SLAM) technique, a robot can create maps about its unknown environment while it continuously localizes its position. Grid maps and feature maps have been widely used for SLAM together with application of probability methods and POMDP (partially observed Markov decision process). But this approach based on grid maps suffers from enormous computational burden. Topological maps, however, have drawn more attention these days because they are compact, provide natural interfaces, and are easily applicable to path planning in comparison with grid maps. Some topological SLAM techniques like GVG (generalized Voronoi diagram) were introduced, but it enables the robot to decide only whether the current position is part of GVG branch or not in the GVG algorithm. In this paper, therefore, to overcome these problems, we present a method for updating a global topological map from the local topological maps. These local topological maps are created through a labeled Voronoi diagram algorithm from the local grid map built based on the sensor information at the current robot position. And the nodes of a local topological map can be utilized as the features of the environment because it is robust in light of visibility problem. The geometric information of the feature is applied to the extended Kalman filter and the SLAM in the indoor environment is accomplished. A series of simulations have been conducted using a two-wheeled mobile robot equipped with a laser scanner. It is shown that the proposed scheme can be applied relatively well.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.40
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• pp.34.1-34.8
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• 2018

Background: Radiation therapy is widely employed in the treatment of head and neck cancer. Adverse effects of therapeutic irradiation include delayed bone healing after dental extraction or impaired bone regeneration at the irradiated bony defect. Development of a reliable experimental model may be beneficial to study tissue regeneration in the irradiated field. The current study aimed to develop a relevant animal model of post-radiation cranial bone defect. Methods: A lead shielding block was designed for selective external irradiation of the mouse calvaria. Critical-size calvarial defect was created 2 weeks after the irradiation. The defect was filled with a collagen scaffold, with or without incorporation of bone morphogenetic protein 2 (BMP-2) (1 ㎍/ml). The non-irradiated mice treated with or without BMP-2-included scaffold served as control. Four weeks after the surgery, the specimens were harvested and the degree of bone formation was evaluated by histological and radiographical examinations. Results: BMP-2-treated scaffold yielded significant bone regeneration in the mice calvarial defects. However, a single fraction of external irradiation was observed to eliminate the bone regeneration capacity of the BMP-2-incorporated scaffold without influencing the survival of the animals. Conclusion: The current study established an efficient model for post-radiation cranial bone regeneration and can be applied for evaluating the robust bone formation system using various chemokines or agents in unfavorable, demanding radiation-related bone defect models.

• Nuclear Engineering and Technology
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• v.43 no.2
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• pp.187-194
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• 2011

Korea Nuclear Fuel is developing the X-GEN fuel which shows high performance and robust reliability for the worldwide supply. However, the simplified code systems such as CESEC-III which were developed in 1970s are still used in the current Non-LOCA safety analysis of OPR1000 and APR1400 plants. Therefore, it is essential to secure an advanced safety analysis methodology to make the best use of the merits of X-GEN fuel. To accomplish this purpose, the $\b{i}$ntegrated $\b{s}$afety $\b{a}$nalysis $\b{m}$ethodology (iSAM), is developed by selecting the best-estimate thermal-hydraulic code RETRAN. iSAM possesses remarkable advantages, such as generality, integrity, and designer-friendly features. That is, iSAM can be applied to both OPR1000 and APR1400 plants and uses only one computer code, RETRAN, in the whole scope of the non-LOCA safety analyses. Also the iSAM adopts the unique and automatic initialization and run tool, $\b{a}$utomatic $\b{s}$teady-$\b{s}$tate $\b{i}$nitialization and $\b{s}$afety analysis too l (ASSIST), to enable unhandy designers to use the new design code RETRAN without difficulty. In this paper, a brief overview of the iSAM is given, and the results of applying the iSAM to typical non-LOCA transients being checked during the reload design are reported. The typical non-LOCA transients selected are the single control element assembly withdrawal (SCEAW) accident, the asymmetric steam generator transients (ASGT), the locked rotor (LR) accident, and bank CEA withdrawal (BCEAW) event. Comparison to current licensing results shows a close resemblance; thus, it reveals that the iSAM can be applied to the non-LOCA safety analysis of OPR1000 and APR1400 plants.

• Journal of Korea Multimedia Society
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• v.5 no.6
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• pp.697-703
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• 2002

In this paper, we propose the adaptive multi stream transmission technique based on SPIHT video signal for the highest quality service over the current Internet that does not guarantee QoS. In addition to the reliable transmission of the video stream over the asynchronous packet network, the proposed approach provides the transmission using the adaptive frame pattern control and multi steam over the TCP for continuous replay. The adaptive frame pattern control makes the transmission date scalable in accordance with the client's buffer status. Apart from this, the multi stream transmission improves the efficiency of video stream, and is robust to the network jitter problem, and maximally utilizes the bandwidth of the client's. As a result of the experiment, the DR(delay ratio) in the proposed adaptive multi-stream transmission is more close to zero than in the existing signal stream transmission, which enables the best-efforts service to be implemented.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.89-92
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• 2005

Using natural speech commands for controlling a human-robot is an interesting topic in the field of robotics. In this paper, our main focus is on the verification of a speaker who gives a command to decide whether he/she is an authorized person for commanding. Among possible dynamic features of natural speech, pitch period is one of the most important ones for characterizing speech signals and it differs usually from person to person. However, current techniques of pitch detection are still not to a desired level of accuracy and robustness. When the signal is noisy or there are multiple pitch streams, the performance of most techniques degrades. In this paper, we propose a two-level approach for pitch detection which in compare with standard pitch detection algorithms, not only increases accuracy, but also makes the performance more robust to noise. In the first level of the proposed approach we discriminate voiced from unvoiced signals based on a neural classifier that utilizes cepstrum sequences of speech as an input feature set. Voiced signals are then further processed in the second level using a modified standard AMDF-based pitch detection algorithm to determine their pitch periods precisely. The experimental results show that the accuracy of the proposed system is better than those of conventional pitch detection algorithms for speech signals in clean and noisy environments.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.177-183
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• 2002

Current state-of-the-art of VMS control is based upon simple knowledge-based inference engine with message set and each message's priority. And R&Ds of the VMS control are focused on the accurate detection and estimation of traffic condition of the subject roadways. However VMS display itself cannot achieve a desirable traffic allocation among alternative routes in the network In this context, VMS display strategy is the most crucial part in the VMS control. VMS itself has several limitations in its nature. It is generally known that VMS causes overreaction and concentration problems, which may be more serious in urban network than highway network because diversion should be more easily made in urban network. A feedback control algorithm is proposed in this paper to address the above-mentioned issues. It is generally true that feedback control approach requires low computational effort and is less sensitive to models inaccuracy and disturbance uncertainties. Major features of the proposed algorithm are as follows: Firstly, a regulator is designed to attain system optimal traffic allocation among alternative routes for each VMS in the network. Secondly, strategic messages should be prepared to realize the desirable traffic allocation, that is, output of the above regulator. VMS display strategy module is designed in this context. To evaluate Probable control benefit and to detect logical errors of the Proposed feedback algorithm, a offline simulation test is performed using real network in Daejon, Korea.

• KDI Journal of Economic Policy
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• v.31 no.2
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• pp.127-153
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• 2009

There is a growing concern about potential harmful effect of second-hand or environmental tobacco smoking. As a result, smoking bans in workplace become more prevalent worldwide. In Korea, workplace smoking ban policy become more restrictive in 2003 when National health enhancing law was amended. The new law requires all office buildings larger than 3,000 square meters (multi-purpose buildings larger than 2,000 square meters) should be smoke free. Therefore, a lot of indoor office became non smoking area. Previous studies in other counties often found contradicting answers for the effects of workplace smoking ban on smoking behavior. In addition, there was no study in Korea yet that examines the causal impacts of smoking ban on smoking behavior. The situation in Korea might be different from other countries. Using 2001 and 2005 Korea National Health and Nutrition surveys which are representative for population in Korea we try to examine the impacts of law change on current smoker and cigarettes smoked per day. The amended law impacted the whole country at the same time and there was a declining trend in smoking rate even before the legislation update. So, the challenge here is to tease out the true impact only. We compare indoor working occupations which are constrained by the law change with outdoor working occupations which are less impacted. Since the data has been collected before (2001) and after (2005) the law change for treated (indoor working occupations) and control (outdoor working occupations) groups we will use difference in difference method. We restrict our sample to working age (between 20 and 65) since these are the relevant population by the workplace smoking ban policy. We also restrict the sample to indoor occupations (executive or administrative and administrative support) and outdoor occupations (sales and low skilled worker) after dropping unemployed and someone working for military since it is not clear whether these occupations are treated group or control group. This classification was supported when we examined the answers for workplace smoking ban policy existing only in 2005 survey. Sixty eight percent of indoor occupations reported having an office smoking ban policy compared to forty percent of outdoor occupation answering workplace smoking ban policy. The estimated impacts on current smoker are 4.1 percentage point decline and cigarettes per day show statistically significant decline of 2.5 cigarettes per day. Taking into account consumption of average sixteen cigarettes per day among smokers it is sixteen percent decline in smoking rate which is substantial. We tested robustness using the same sample across two surveys and also using tobit model. Our results are robust against both concerns. It is possible that our measure of treated and control group have measurement error which will lead to attenuation bias. However, we are finding statistically significant impacts which might be a lower bound of the true estimates. The magnitude of our finding is not much different from previous finding of significant impacts. For cigarettes per day previous estimates varied from 1.37 to 3.9 and for current smoker it showed between 1%p and 7.8%p.