• Journal of the Korean Solar Energy Society
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• v.31 no.2
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• pp.82-88
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• 2011

The artificial increase in the solar intensity incident on solar cells using lenses or mirrors can allow solar cells to generate equivalent power with a lower cost. There are two types of concentration optics for solar energy conversion. One is to use mirrors, and the other is to use Fresnel lenses. The gains that can be achieved with a Fresnel lens or a parabolic mirror are compared. The result showed the gains are comparable and the two configurations were developed competitively. In application areas of Fresnel lenses as solar concentrators, several variations of design were devised and tested. Some PV systems still use commercially available flat Fresnel lenses as concentrators. A convex linear Fresnel lens to improve the concentration ratio and the efficiency is devised and flat linear Fresnel lens in thermal energy collection is utilized. In this study, we designed and optimized flat Fresnel lens and the 'light pipe' to develop 500X concentrated solar PV system. In the process, we compare the transmission efficiencies according to groove types. We performed rigorous ray tracing simulation of the flat Fresnel lenses. The computer aided simulation showed the 'grooves in case' has the better efficiency than that of 'grooves out case'. Based on the ray-trace results we designed and manufactured sample Fresnel lenses. The optical performance were measured and compared with ray-trace results. Finally, the optical efficiency was measured to be above 75%. All the design and manufacturing were performed based on that InGaP/InGaAs/Ge triple junction solar cell is used to convert the photon energy to electrical power. Field test will be made and analyzed in the near future.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.791-801
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• 2021

In this paper, an educational case that can be applied as artificial intelligence literacy education for preservice teachers and incumbent teachers was studied. To this end, a case of educating the operating principle of an artificial neural network that recognizes images is proposed. This training case focuses on the basic principles of artificial neural network operation and implementation, and applies the method of finding parameter optimization solutions required for artificial neural network implementation in a spreadsheet. In this paper, we focused on the artificial neural network of supervised learning method. First, as an artificial neural network principle education case, an artificial neural network education case for recognizing two types of images was proposed. Second, as an artificial neural network extension education case, an artificial neural network education case for recognizing three types of images was proposed. Finally, the results of analyzing artificial neural network training cases and training satisfaction analysis results are presented. Through the proposed training case, it is possible to learn about the operation principle of artificial neural networks, the method of writing training data, the number of parameter calculations executed according to the amount of training data, and parameter optimization. The results of the education satisfaction survey for preservice teachers and incumbent teachers showed a positive response result of over 70% for each survey item, indicating high class application suitability.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.125-131
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• 2021

In recent years, Convolutional Neural Networks (CNNs) have achieved outstanding performance in the fields of computer vision such as image classification, object detection, visual quality enhancement, etc. However, as huge amount of computation and memory are required in CNN models, there is a limitation in the application of CNN to low-power environments such as mobile or IoT devices. Therefore, the need for neural network compression to reduce the model size while keeping the task performance as much as possible has been emerging. In this paper, we propose a method to compress CNN models by combining matrix decomposition methods of LR (Low-Rank) approximation and CP (Canonical Polyadic) decomposition. Unlike conventional methods that apply one matrix decomposition method to CNN models, we selectively apply two decomposition methods depending on the layer types of CNN to enhance the compression performance. To evaluate the performance of the proposed method, we use the models for image classification such as VGG-16, RestNet50 and MobileNetV2 models. The experimental results show that the proposed method gives improved classification performance at the same range of 1.5 to 12.1 times compression ratio than the existing method that applies only the LR approximation.

• Korean Journal of Construction Engineering and Management
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• v.20 no.2
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• pp.113-118
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• 2019

Recently, the maintenance concept of infrastructure has been changed from the stability management of the structure determined by the safety inspection of the existing facilities to the asset management related to evaluating and managing the performance of the facilities. For management of the property of the facilities, it is necessary to efficiently classify their information for the maintenance and service level of the facilities and to manage them. In the case of power plant facility, especially, it is a complex structure, which is constructed in a various component and detail. In this study, therefore, the components of power plant facility were classified into facilities, spaces, parts, and elements considering the type of integrated construction classification system in Korea. To reflect the deterioration rate of the facility in accordance with environmental conditions such as airborne salt and humidity etc., it was classified by adding direction, interior, and exterior condition of each component not to be considered in the existing classification system for its effective and systematic maintenance, since it is generally located in the coastal area due to the operation of the power generation structure. The classification system developed in this study can be used as fundamental data for development of the computer system for asset management of power plant facility.

• Korean Journal of Construction Engineering and Management
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• v.20 no.4
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• pp.104-113
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• 2019

Construction dispute about Extension of Time are complexly intertwined with various issues. The duration delay analysis defines the impact the issue has on the duration variation. And The international court and the arbitrator use the results of the analysis as a basis for reasonable duration judging. However, most of the domestic Construction sites have not established a business process for Extension of Time litigation. Therefore, Analysis data are collected after the occurrence of the dispute, there is not enough basic data of analysis almost. This study sought to improve the management efficiency by organizing information requirement for delay analysis and suggesting a reasonable business process. As a result of applying the proposed process to actual construction duration extension disputes, about 33% of practitioners, 46% of contractors, and 48% of legal advisors were satisfied with the process application site And Matrix validation was 91% identical. This study suggests that it is possible to increase the efficiency of the construction duration analysis work used as a basis in the construction dispute. Finally, the Computer based system design for this process should continue in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.186-188
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• 2014

In recent years, domestic as well as LTE wireless network of Wi-Fi and most used. In addition, mobile-intensive services that used mainly in our society makes it easier, SNS, application (APP), and file downloads. As such, the amount of data requested, while living at the time of mobile users will want to be safe from the earliest. And the wireless network communications mortality (3G, 4G (LTE), LTE-A) and Wi-Fi (802.11 n-2.4 G H z z H a c-5, 802.11 G), and users are mainly used in the death 4G (LTE), communication Wi-Fi, 802.11 n-2.4 GHz are used most frequently. As above, use the wireless network in order to safely and quickly developed the technology of the Li-Fi. Li-Fi light (visible light) technology to communicate with, and Wi-Fi (802.11 n-2.4 G z H) 100 times faster, LTE-A 66 times faster. However, the current Li-Fi to commercialise the big issue exists. In this paper, there are a lot of existing problems in the commercialization of Li-Fi being used in Wi-Fi, and a comparative analysis.

• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.43-52
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• 2018

Livestock production is the second largest economic activity of Pakistan's rural population, more specifically; sixty-seven percent of Pakistan's total population that live in rural areas sources their income from livestock activities. As this subsector of agriculture within rural Pakistan is so critical to Pakistan's economy it is especially important to further develop the sector through the introduction of cost effective, efficient, and practical technologies. In an effort to improve such an important sector within the agriculture sector in Pakistan research has been carried out to better understand the capabilities and feasibility of leveraging Internet of Things based technologies, such as, microprocessors and microcontrollers within Pakistan's livestock production and management. The internet of Things can potentially allow for the scaling of small-scale rural livestock production to larger operations through cost effective and efficient livestock management through the application of IoT technologies. This paper discusses the architecture models of IoT based smart animal farms and delves into the pitfalls and advantages of applying IoT technologies in this sector. In this work we will explore the cheap sensors to monitor the internal activities of cattle farm with the aim of using these sensors as part of system to detect the important operations that need on the time response. This system should provide the feed and water as required, and control the temperature in sheds to protect the cattle being ill and on heat, and humidity level .internet connection used to connect these devices with smartphones or computers. In this paper we proposed the architecture model of IoT based smart animal farm.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.132-144
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• 2018

3D Geo-spatial information models have been widely used in the field of Civil Engineering, Medical, Computer Graphics, Urban Management and many other. Especially, in surveying and geo-spatial field, the demand for high quality 3D geospatial information and indoor spatial information is so highly increasing. However, it is so difficult to provide a low-cost and high efficiency service to the field which demand the highest quality of 3D model, because pre-constructed spatial data are composed of different formats and storage structures according to the application purpose of each institutes. In fact, the techniques to construct a high applicable 3D geo-spatial model is very expensive to collect and analyze geo-spatial data, but most demanders of 3D geo-spatial model never want to pay the high-cost to that. This study, therefore, suggest the effective way to construct 3D geo-spatial model with low-cost of construction. In general, the effective way to reduce the cost of constructing 3D geo-spatial model as presented in previous studies is to combine the raw data obtained from point cloud observatory and UAV imagery, however this method has some limitation of usage from difficulties to approve the use of raw data because of those have been managed separately by various institutes. To solve this problem, we developed the linking & management system for unifying a high-Resolution raw geo-spatial data based on the point cloud DB and apply this system to extract the basic database from 3D geo-spatial mode for the road database registration. As a result of this study, it can be provided six contents of main entries for road registration by applying the developed system based on the point cloud DB.

• Korean Journal of Poultry Science
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• v.45 no.4
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• pp.237-244
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• 2018

In this study, to increase the survival rate of frozen/thaw rooster semen, standard protocols of semen thawing procedures were tested by computer-assisted sperm assay (CASA). We tested 4 different thawing protocols for frozen semen, $5^{\circ}C$ for 2 min, $35^{\circ}C$ for 30 s, $54^{\circ}C$ for 13 s, and $70^{\circ}C$ for 7 s. The pooled semen from 5 to 8 Ogye rooster line was diluted in the HS-1 diluent and frozen in 8% methylacetamide (MA) in liquid nitrogen vapors. To determine standard thawing method, straws were plunged into different temperatures and times. The resulting motilities were recorded by the CASA system. The results of this study showed that the best viability of the spermatozoa was shown by exposure at $5^{\circ}C$ for 2 min. Moreover, the longevity test of thawed sperm at $5^{\circ}C$ for 2 min also supported the higher viability under low temperature preservation of $17^{\circ}C$ for 1 hr. Further research is needed to increase the motility of thawed rooster semen for field application. In addition, the in vivo tests for different rooster lines are also needed for the establishment of avian genetic resource bank.