• KIPS Transactions on Computer and Communication Systems
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• v.8 no.1
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• pp.17-28
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• 2019

In the financial investment management strategy, the distributed investment selecting and combining various financial assets is called portfolio management theory. In recent years, the blockchain based financial assets, such as cryptocurrencies, have been traded on several well-known exchanges, and an efficient portfolio management approach is required in order for investors to steadily raise their return on investment in cryptocurrencies. On the other hand, deep learning has shown remarkable results in various fields, and research on application of deep reinforcement learning algorithm to portfolio management has begun. In this paper, we propose an efficient financial portfolio investment management method based on Asynchronous Advantage Actor-Critic (A3C), which is a representative asynchronous reinforcement learning algorithm. In addition, since the conventional cross-entropy function can not be applied to portfolio management, we propose a proper method where the existing cross-entropy is modified to fit the portfolio investment method. Finally, we compare the proposed A3C model with the existing reinforcement learning based cryptography portfolio investment algorithm, and prove that the performance of the proposed A3C model is better than the existing one.

• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.140-145
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• 2019

With the development of IT technology, many changes are taking place in the health service environment over the past. However, even if medical technology is converged with IT technology, the problem of medical costs and management of health services are still one of the things that needs to be addressed. In this paper, we propose a model for hospitals that have established the IoT system to efficiently analyze and manage the personal information of users who receive medical services. The proposed model aims to efficiently check and manage users' medical information through an in-house IoT system. The proposed model can be used in a variety of heterogeneous cloud environments, and users' medical information can be managed efficiently and quickly without additional human and physical resources. In particular, because users' medical information collected in the proposed model is stored on servers through the IoT gateway, medical staff can analyze users' medical information accurately regardless of time and place. As a result of performance evaluation, the proposed model achieved 19.6% improvement in the efficiency of health care services for occupational health care staff over traditional medical system models that did not use the IoT system, and 22.1% improvement in post-health care for users who received medical services. In addition, the burden on medical staff was 17.6 percent lower on average than the existing medical system models.

• Journal of Climate Change Research
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• v.9 no.4
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• pp.319-324
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• 2018

Due to climate change, water shortages and water-related disasters will be serious. Since the damage and frequency of drought are increasing, the importance of water resource management technology is increasing. In this study, we analyzed the amount of greenhouse gas and the environmental impact caused by the production and operation system technologies of movable weir among various water resource management technologies. The research subjects were air inflatable rubber dams widely used in rivers and upright type rubber dams, which are an improvement on the existing rubber type. Each type of dam was studied at sizes of $1,500H{\times}10,000L\;mm$ and $3,000H{\times}20,000L\;mm$, and the two types and two sizes were compared and analyzed. Using life cycle assessment, we examined the environmental impacts using the amount of electricity required for operation and the discretionary amount required for production. In the '$1,500H{\times}10,000L$' dams, the global warming indexes were $9.35E+04kg\;CO_2-eq$. for upright type and $7.36E+04kg\;CO_2-eq$. for inflatable type. At size of '$3,000H{\times}20,000L$' the global warming indexes were $9.09E+05kg\;CO_2-eq$. for upright type and $1.07E+06kg\;CO_2-eq$. for inflatable type. Analysis of the life cycle environmental impact showed that the environmental impact of the air inflatable rubber dam was reduced by 39.8% at '$1,500H{\times}10,000L$' compared to the larger size. At the larger '$3,000H{\times}20,000L$' size, the upright dam showed a 10.1% smaller impact than the air inflatable rubber dam. Selection of water resource management system should consider climate change, not only management purpose and cost. Additional studies and improvements on rubber dam systems should be made.

• Journal of Climate Change Research
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• v.2 no.3
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• pp.203-219
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• 2011

Greenhouse gas(GHG) inventories were reported recently in various fields. It, however, has been rarely to mention about the accuracy and reliability of the GHG inventory results. Some reliable assessment methods were introduced to judge the accuracy of the GHG inventory results. It is, hence, critical to develop an evaluation methodology. This project was designed 1) to develop evaluation methodology for reliability of inventory results by GHG-CAPSS, 2) to check the feasibility of the developed evaluation methodology as a result of applying this methodology to two emission sources: liquid fossil fuel and landfill, and 3) to construct the technical roadmap for future role of GHG-CAPSS. Qualitative and quantitative assessment methodologies were developed to check the reliability and accuracy of the inventory results. Qualitative assessment methodology was designed to evaluate the accuracy and reliability of estimation methods of GHG emissions from emission and sink sources, activity data, emission factor, and quality management schemes of inventory results. On the other hand, quantitative assessment methodology was based on the uncertainty assessment of emission results. According to the results of applying the above evaluation methodologies to two emission sources, those seem to be working properly. However, it is necessary to develop source-specific rating systems because emission and sink sources exhibit source-specific characteristics of GHG emissions and sinks.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.7-13
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• 2019

This study aims to develop a FE Model to simulate dissimilar friction stir welding and to address its potential for fundamental analysis and practical applications. The FE model is based on Coupled Eulerian-Lagrangian approach. Multiphysics systems are calculated using explicit time integration algorithm, and heat generations by friction and inelastic heat conversion as well as heat transfer through the bottom surface are included. Using the developed model, friction stir welding between an Al6061T6 plate and an AZ61 plate were simulated. Three simulations are carried out varying the welding parameters. The model is capable of predicting the temperature and plastic strain fields and the distribution of void. The simulation results showed that temperature was generally greater in Mg plates and that, as a rotation speed increase, not the maximum temperature of Mg plate increased, but did the temperature of Al plate. In addition, the model could predict flash defects, however, the prediction of void near the welding tool was not satisfactory. Since the model includes the complex physics closely occurring during FSW, the model possibly analyze a lot of phenomena hard to discovered by experiments. However, practical applications may be limited due to huge simulation time.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.6
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• pp.1177-1192
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• 2018

The objective of this study is to develop the existing drainage system for catching the partial leakage of tunnel structures operating in cold region. The drainage system consists of drainage board, Hotty-gel as a waterproofing material, cover for preventing protrusion of Hotty-gel, air nailer, fixed nail, pipe for collecting ground leak, pipe for conveying ground leak, wire-mesh, and sprayed cement mortar. The drainage systems were installed in conventional concrete lining tunnels to evaluate the site applicability and constructability. The performances of waterproof and the drainage in the drainage system were evaluated by injecting 1,000 ml of red water in the back of the drainage system at 7 days, 14 days, 21 days, 28 days, 2 months, 3 months, 4 months, 5 months, 6 months, 7 months and 8 months. During 8 months of field test, the average daily temperature of the tunnel site was measured from $-16.0^{\circ}C$ to $25.6^{\circ}C$. The daily minimum temperature was $-21.3^{\circ}C$ and the daily maximum temperature was $30.8^{\circ}C$. There was no problem in waterproof and drainage performance of the drainage board in the drainage system. However, the pipe for conveying ground leak had the leakage problem from 14 days. It is considered that the leakage of the pipe for conveying ground leak was caused by the deformation of the pipe of the flexible plastic material having a thickness of 0.2 cm by using the high pressure air nailer and the fixing pin and the insufficient thickness and width of the hotty-gel for preventing the leakage.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.855-865
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• 2018

Sound event detection is one of the research areas to model human auditory cognitive characteristics by recognizing events in an environment with multiple acoustic events and determining the onset and offset time for each event. DCASE, a research group on acoustic scene classification and sound event detection, is proceeding challenges to encourage participation of researchers and to activate sound event detection research. However, the size of the dataset provided by the DCASE Challenge is relatively small compared to ImageNet, which is a representative dataset for visual object recognition, and there are not many open sources for the acoustic dataset. In this study, the sound events that can occur in indoor and outdoor are collected on a larger scale and annotated for dataset construction. Furthermore, to improve the performance of the sound event detection task, we developed a dual CNN structured sound event detection system by adding a supplementary neural network to a convolutional neural network to determine the presence of sound events. Finally, we conducted a comparative experiment with both baseline systems of the DCASE 2016 and 2017.

• The Journal of the Acoustical Society of Korea
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• v.37 no.6
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• pp.483-488
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• 2018

Far field input utterance is one of the major causes of performance degradation of speaker verification systems. In this study, we used teacher student learning framework to compensate for the performance degradation caused by far field utterances. Teacher student learning refers to training the student deep neural network in possible performance degradation condition using the teacher deep neural network trained without such condition. In this study, we use the teacher network trained with near distance utterances to train the student network with far distance utterances. However, through experiments, it was found that performance of near distance utterances were deteriorated. To avoid such phenomenon, we proposed techniques that use trained teacher network as initialization of student network and training the student network using both near and far field utterances. Experiments were conducted using deep neural networks that input raw waveforms of 4-channel utterances recorded in both near and far distance. Results show the equal error rate of near and far-field utterances respectively, 2.55 % / 2.8 % without teacher student learning, 9.75 % / 1.8 % for conventional teacher student learning, and 2.5 % / 2.7 % with proposed techniques.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.7
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• pp.953-959
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• 2018

This paper deals with controlling surge oscillations of a mooring vessel system under large external disturbances such as wind, waves and currents. A control synthesis based on Sliding Mode Control (SMC) with a Super-Twisting Algorithm (STA) has been applied to suppress nonlinear surge oscillations of a two-point mooring system. Despite the advantages of robustness against parameter uncertainties and disturbances for SMC, chattering is the main drawback for implementing sliding mode controllers. First-order SMC shows convergence within the desired level of accuracy, in which chattering is the main obstacle related to the destructive phenomenon. Alternatively, STA completely eliminates chattering phenomenon with high accuracy even for large disturbances. SMC based on STA is an effective tool for the motion control of a nonlinear mooring system because it avoids the chattering problems of a first-order sliding mode controller. In addition, the error trajectories of controlled mooring systems implemented by means of STA form in the bounded region. Finally, the control gain effect of STA can be observed in sliding surface and position trajectory errors.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.8
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• pp.317-322
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• 2019

Programming judge systems for programming training support are typically built on the Web, where the examiners uploads a programming problem, which the student reads and submits an answer to the problem. The judge system executes the submitted answer of source code to provide feedback such as pass, failure, and error messages. Students who receive the feedback except for the pass continues debugging the source code until they are judged to pass. We developed an online judge system to support programming training and analyzed answers submitted by the students and found that many of the students who were not judged to pass that test did not know exactly where they were wrong but continued to solve the problem. The current judge system generally feeds runtime error messages back to students. However, with only runtime error message, it is difficult for student who train to find the wrong part of the answer. Therefore, in this paper, we propose a system that provides the feedback of programming failure by analyzing the control flow of the test cases used in the source code submitted by the student. The proposed system helps students find the wrong parts more quickly by feeding back the paths where faults in the control flow may exist. In addition, we show that this system is applicable to the answer source code that the actual student submitted.