• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.37 no.1
• /
• pp.153-166
• /
• 2017

Recently, the construction industry has been pursuing economical construction by introducing improved construction equipment and methods. However, in many cases, the equipment operation according to the intuition of the field manager and in the manner of traditional methods impedes the increase in effectiveness in terms of productivity and economy. The performance of new construction equipment has rapidly improved; however, the maximum effect of mechanized construction cannot be obtained unless the effective management and operation methods are implemented. According to the expert survey, it has been discovered that the problems of conventional construction equipment operation methods can be classified into several categories: allocation of construction equipment that is not suitable for the construction work, the combination of equipment that does not take into consideration real-time field situations, the decline in the skill of the construction equipment drivers, and lack of real-time access to necessary information. This paper proposes a construction equipment management system to solve these problems. The construction equipment management system can provide a method to maximize the work rate of the construction equipment fleet by developing an equipment allocation plan based on field conditions, whenever necessary, and transferring this information to the construction equipment drivers in real time. Ultimately, it is believed that the application of the construction equipment operation system in the field will make it possible to reduce carbon emissions by improving productivity and reducing fuel consumption.

• Journal of the Korean Society for Railway
• /
• v.19 no.2
• /
• pp.262-269
• /
• 2016

Subway station scales are determined by peak predictions. In this study, the purpose behind the installation of a subway is public transportation convenience and public interest, but economic validity is also important. By proving that the scale of the station is excessive with regard to the target station size for Seoul subway Line 5-8, a reasonable plan. can be sought. According to station installation standards, the area of the station under investigation here is out of the service levels by six stages (A~F), and it must be four or more levels (D). The Actual level for the B level is a two-step design. The Actual ratio for over- Peak predictions is only 17.8% on average. The results of measurements of the excess area and determination of the excessive costs were analyzed by subdividing the area and by calculating it based on the B level, finding that it is possible to provide benefits for customers only in the current design, with an area ratio of 16.3%. Given the weight, it was estimated that current conditions can meet the needs of only 18.6% of the current area. Simplifying the scale calculation method of the station, it is convenient, safe, and advantageous to move citizens only if the scale can be streamlined. Then, with a reduced initial investment, maintenance costs during the operation can be reduced.

• Membrane Journal
• /
• v.19 no.4
• /
• pp.291-301
• /
• 2009

Double-layered polymer electrolyte membranes were prepared from two different sulfonated poly(aryl ether sulfone) copolymers by the two-step solution casting method for direct methanol fuel cells (DMFC). Sulfonation degrees were adjusted 10% (SPAES-10) and 50% (SPAES-50) by controlling monomer ratios, and the weight ratios of SPAES-10 copolymer were varied in the range of 5~20% to investigate the effect of thickness of coating layers on the membranes. Proton conducting layers were fabricated from SPAES-50 solutions of N-methyl-2-pyrrolidone (NMP) by a solution casting technique, and coating layers formed on the semiliquid surface of the conducting layer by pouring of SPAES-10-NMP solutions onto. It was found that double-layered polymer electrolyte membrane could significantly reduce the methanol crossover through the membrane and maintain high proton conductivities being comparable to single-layered SPAES-50 membrane. The maximum power density of membrane-electrolyte assembly (MEA) at the condition of $60^{\circ}C$ and 2 M methanol-air was $134.01\;mW/cm^2$ for the membrane prepared in the 5 wt-% of SPAES-10 copolymer, and it was corresponding to the 105.5% of the performance of the commercial Nafion 115 membrane.

• KIPS Transactions on Software and Data Engineering
• /
• v.1 no.2
• /
• pp.127-136
• /
• 2012

Many research of hand gesture recognition based on vision system have been conducted which enable user operate various electronic devices more easily. 3D position calculation and meaningful gesture classification from similar gestures should be executed to recognize hand gesture accurately. A simple and cost effective method of 3D position calculation and gesture spotting (a task to recognize meaningful gesture from other similar meaningless gestures) is described in this paper. 3D position is achieved by calculation of two cameras relative position through pan/tilt module and a marker regardless with the placed position. Fuzzy garbage model is proposed to provide a variable reference value to decide whether the user gesture is the command gesture or not. The reference is achieved from fuzzy command gesture model and fuzzy garbage model which returns the score that shows the degree of belonging to command gesture and garbage gesture respectively. Two-stage user adaptation is proposed that off-line (batch) adaptation for inter-personal difference and on-line (incremental) adaptation for intra-difference to enhance the performance. Experiment is conducted for 5 different users. The recognition rate of command (discriminate command gesture) is more than 95% when only one command like meaningless gesture exists and more than 85% when the command is mixed with many other similar gestures.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.11
• /
• pp.115-126
• /
• 2014

In order to improvement of the perceptive of health state and the motivation, this study suggests the ways and design forms which provide PHR information customizing individual attributes as well as guidelines through a decision support system and services which integrate medical information visualization. Expression methods using the color, form, position in order to visualization based on images improved performance of information awareness by changing radar chart from existing information which provide only numerical figure. The methods providing a graphic figure which seems like beads of blood which shows the result of blood tests would also arise patient's attention. They gives the patient's information which is able to compare their health status and normal status and visualizes the records as a human figure in order to perceiving their status as well. The visualization showing the position of human body figures marks in inspection elements located in position of relevant organs. The method also uses icons represent examination results so they improve attention of the results and shorten recognize times.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.25 no.4
• /
• pp.65-74
• /
• 2021

In order to efficiently inspect rapidly increasing old tunnels in many well-developed countries, many inspection methodologies have been proposed using imaging equipment and image processing. However, most of the existing methodologies evaluated their performance on a clean concrete surface with a limited area where other objects do not exist. Therefore, this paper proposes a 6-step framework for tunnel crack detection deep learning model development. The proposed method is mainly based on negative sample (non-crack object) training and Cascade Mask R-CNN. The proposed framework consists of six steps: searching for cracks in images captured from real tunnels, labeling cracks in pixel level, training a deep learning model, collecting non-crack objects, retraining the deep learning model with the collected non-crack objects, and constructing final training dataset. To implement the proposed framework, Cascade Mask R-CNN, an instance segmentation model, was trained with 1561 general crack images and 206 non-crack images. In order to examine the applicability of the trained model to the real-world tunnel crack detection, field testing is conducted on tunnel spans with a length of about 200m where electric wires and lights are prevalent. In the experimental result, the trained model showed 99% precision and 92% recall, which shows the excellent field applicability of the proposed framework.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.2
• /
• pp.750-762
• /
• 2019

The importance of the call center as a contact point for the enterprise is growing. However, call centers have difficulty with their operating agents due to the agents' lack of knowledge and owing to frequent agent turnover due to downturns in the business, which causes deterioration in the quality of customer service. Therefore, through an N-bank call center case study, we developed a system to reduce the burden of keeping up business knowledge and to improve customer service quality. It is a "real-time agent advisor" system that provides agents with answers to customer questions in real time by combining AI technology for speech recognition, natural language processing, and questions & answers for existing call center information systems, such as a private branch exchange (PBX) and computer telephony integration (CTI). As a result of the case study, we confirmed that the speech recognition system for real-time call analysis and the corpus construction method improves the natural speech processing performance of the query response system. Especially with name entity recognition (NER), the accuracy of the corpus learning improved by 31%. Also, after applying the agent advisor system, the positive feedback rate of agents about the answers from the agent advisor was 93.1%, which proved the system is helpful to the agents.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.24 no.5
• /
• pp.69-76
• /
• 2020

Global warming is a very important problem as it causes rapid climate change and natural disasters. Therefore, researches related to renewable energy are being actively conducted while promoting policies such as reducing carbon dioxide emission and increasing the proportion of renewable energy. Solar power generation is being applied in urban areas like BIPV as well as existing idle areas outside the city. Therefore, in this study, precast concrete blocks developed for paving roadways capable of solar power generation were designed and constructed. For the evaluation of field applicability for 6 months, skid resistance and block settlement were measured. As a result of the experiment, it was found that skid resistance satisfies the standard of general roadway in Korea, but not the standard of highway. The skid resistance tended to decrease as time passed. In addition, the settlement of the block gradually increased slightly, but it is much smaller than the allowable settlement of the roadway. Therefore, it is necessary to establish a maintenance period and method based on the periodic measurement results in the future.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.3
• /
• pp.141-148
• /
• 2022

Recently, reinforcement learning combined with deep neural network technology has achieved remarkable success in various fields such as board games such as Go and chess, computer games such as Atari and StartCraft, and robot object manipulation tasks. However, such deep reinforcement learning describes states, actions, and policies in vector representation. Therefore, the existing deep reinforcement learning has some limitations in generality and interpretability of the learned policy, and it is difficult to effectively incorporate domain knowledge into policy learning. On the other hand, dNL-RRL, a new relational reinforcement learning framework proposed to solve these problems, uses a kind of vector representation for sensor input data and lower-level motion control as in the existing deep reinforcement learning. However, for states, actions, and learned policies, It uses a relational representation with logic predicates and rules. In this paper, we present dNL-RRL-based policy learning for transportation mobile robots in a manufacturing environment. In particular, this study proposes a effective method to utilize the prior domain knowledge of human experts to improve the efficiency of relational reinforcement learning. Through various experiments, we demonstrate the performance improvement of the relational reinforcement learning by using domain knowledge as proposed in this paper.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.15 no.1
• /
• pp.36-44
• /
• 2022

Reversible data hiding techniques have been developed to hide confidential data in the image by shifting the histogram of the image. These techniques have a weakness in which the security of hidden confidential data is weak. In this paper, to solve this drawback, we propose a technique of triple encrypting confidential data using pixel value information and hiding it in the cover image. When confidential data is triple encrypted using the proposed technique and hidden in the cover image to generate a stego-image, since encryption based on pixel information is performed three times, the security of confidential data hidden by triple encryption is greatly improved. In the experiment to measure the performance of the proposed technique, even if the triple-encrypted confidential data was extracted from the stego-image, the original confidential data could not be extracted without the encryption keys. And since the image quality of the stego-image is 48.39dB or higher, it was not possible to recognize whether confidential data was hidden in the stego-image, and more than 30,487 bits of confidential data were hidden in the stego-image. The proposed technique can extract the original confidential data from the triple-encrypted confidential data hidden in the stego-image without loss, and can restore the original cover image from the stego-image without distortion. Therefore, the proposed technique can be effectively used in applications such as military, medical, digital library, where security is important and it is necessary to completely restore the original cover image.