• Environmental and Resource Economics Review
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• v.30 no.2
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• pp.237-268
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• 2021

As variable renewable sources rapidly increase due to the Energy Transition plan, integration cost of renewable sources to the power system is rising sharply. The increase in variable renewable energy reduces the capacity factor of existing traditional power capacity, and this undermines the efficiency of the overall power supply, and demand resources are drawing attention as a solution. In this study, we analyzed how much electric vehicle demand resouces, which has great potential among other demand resources, can reduce power supply costs if it is used as a flexible resource for renewable generation. As a methodology, a stochastic form of power system optimization model that can effectively reflect the volatile characteristics of renewable generation is used to analyze the cost induced by renewable energy and the benefits offered by electric vehicle demand resources. The result shows that virtual power plant-based direct control method has higher benefits than the time-of-use tariff, and the higher the proportion of renewable energy is in the power system, the higher the benefits of electric vehicle demand resources are. The net benefit after considering commission fee for aggregators and battery wear-and-tear costs was estimated as 67% to 85% of monthly average fuel cost under virtual power plant with V2G capability, and this shows that a sufficient incentive for market participation can be offered when a rate system is applied in which these net benefits of demand resources are effectively distributed to consumers.

• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.233-239
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• 2021

Recently, the COVID-19 virus has caused people to stay indoors longer without going out. As a result of this, people's activity decreased sharply, and their weight gained. So people became more interested in health. Home training can be an alternative method to solve this problem. Accordingly, To find out the trends of home training, we collected articles from December 1, 2019, to November 30, 2020, using the news provided by BIG KINDS, a news analysis system. We analyzed frequency analysis, relational analysis according to weighting, and related word analysis with the program using the algorithm developed by BIG KINDS. In conclusion, first, it was found that home training is led by technology and the emergence of artificial intelligence. Second, it can be assumed that people mainly do home training using content and video services related to mobile carriers. Third, people had a high preference for Pilates in the sports category. It can be seen that the number of patent applications increased as the demand for exercise products related to Pilates increased. In the next study, we expect that this study will be used as primary data for various big data studies by supplementing the research methodology and conducting various analyses.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.241-262
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• 2021

This paper reviewed the necessity of a information and communication technology (ICT)-based smart livestock system as a development strategy for the animal life industry in the future. It also predicted the trends of livestock and animal food until 2050, 30 years later. Worldwide, livestock raising and consumption of animal food are rapidly changing in response to population growth, aging, reduction of agriculture population, urbanization, and income growth. Climate change can change the environment and livestock's productivity and reproductive efficiencies. Livestock production can lead to increased greenhouse gas emissions, land degradation, water pollution, animal welfare, and human health problems. To solve these issues, there is a need for a preemptive future response strategy to respond to climate change, improve productivity, animal welfare, and nutritional quality of animal foods, and prevent animal diseases using ICT-based smart livestock system fused with the 4th industrial revolution in various aspects of the animal life industry. The animal life industry of the future needs to integrate automation to improve sustainability and production efficiency. In the digital age, intelligent precision animal feeding with IoT (internet of things) and big data, ICT-based smart livestock system can collect, process, and analyze data from various sources in the animal life industry. It is composed of a digital system that can precisely remote control environmental parameters inside and outside the animal husbandry. The ICT-based smart livestock system can also be used for monitoring animal behavior and welfare, and feeding management of livestock using sensing technology for remote control through the Internet and mobile phones. It can be helpful in the collection, storage, retrieval, and dissemination of a wide range of information that farmers need. It can provide new information services to farmers.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.77-87
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• 2021

Smart Factory refers to a factory that can be controlled by itself with an intelligent factory that improves productivity, quality and customer satisfaction by combining the entire process of manufacturing and production with digital automation solutions. The manufacturing industry around the world is rapidly changing, with Germany, Europe, and the United States at the center. In order to cope with such changes, the Korean government is also implementing a policy to spread the supply of smart factories for small and medium-sized companies, and related ministries and agencies such as the Ministry of Commerce, Industry and Energy, the Ministry of SMEs and Venture Business, the Korea Institute of Technology and Information Promotion, and local technoparks, as well as large companies such as Samsung, SK and LG are actively investing in smart manufacturing projects to support smart factories[1]. Factory Automation (FA) construction has many issues regarding the connection of heterogeneous equipment. The most difficult aspect of configuring various communications from various equipment is the reason. Although it may not be known if there are standards or products made up of the same company, it is not easy to build equipment that is old, up-to-date, and different use environments through a series of communications. To solve this problem, we would like to propose a method of communication using Modbus, one of FieldBus, which is one of the many industrial devices of PLC, a representative facility control system, and is used as a communication standard.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.415-423
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• 2021

Recently, an R-based point time series data validation system has been established for the statistical post processing and improvement of the National Center for AgroMeteorology-Land Atmosphere Modeling Package (NCAM-LAMP) medium-range prediction data. The time series verification system was used to compare the NCAM-LAMP with the AWS observations and GDAPS medium-range prediction model data operated by Korea Meteorological Administration. For this comparison, the model latitude and longitude data closest to the observation station were extracted and a total of nine points were selected. For each point, the characteristics of the model prediction error were obtained by comparing the daily average of the previous prediction data of air temperature, wind speed, and hourly precipitation, and then we tried to improve the next prediction data using Support Vector Machine( SVM) method. For three months from August to October 2017, the SVM method was used to calibrate the predicted time series data for each run. It was found that The SVM-based correction was promising and encouraging for wind speed and precipitation variables than for temperature variable. The correction effect was small in August but considerably increased in September and October. These results indicate that the SVM method can contribute to mitigate the gradual degradation of medium-range predictability as the model boundary data flows into the model interior.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.133-146
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• 2021

Providing weather information on roads today means that the road weather conditions near weather observation points are presented to road managers and road users. These weather observation points are managed by the Korea Meteorological Administration. However, it is difficult to provide accurate weather information due to physical limitations such as the presence of precipitation collection points, distance to weather information provision roads, and the presence of mountains. Therefore, this study intends to perform a comparative analysis by time zone and administrative dong provided by the Meteorological Administration using the wiper information among the information contained in the PVD(Probe Vehicle Data) collected from the highway C-ITS project. As a result of the analysis it was possible to detect rainfall even in the event of local rainfall and rainfall over a long period of time and the higher the cumulative precipitation per hour, the higher the probability of coincidence. This study is meaningful because it used PVD to solve the limitations of the existing road weather information provision method and suggested utilization plan for PVD.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.45-51
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• 2022

Fear of contact exists due to the prevention of the spread of infectious diseases such as COVID-19. When using the common entrance door of an apartment, access is possible only if the resident enters a password or obtains the resident's permission. There is the inconvenience of having to manually enter the number and password for the common entrance door to enter. Also, contactless entry is required due to COVID-19. Due to the development of ICT, users can be easily identified through the development of face recognition and voice recognition technology. The proposed method detects a visitor's face through a CCTV or camera attached to the common entrance door, recognizes the face, and identifies it as a registered resident. Then, based on the registered information of the resident, it is possible to operate without contact by interworking with the elevator on the server. In particular, if face recognition fails with a hat or mask, the visitor is identified by voice or additional authentication of the visitor is performed based on the voice message. It is possible to block the spread of contagiousness without leaving any contactless function and fingerprint information when entering and exiting the front door of an apartment house, and without the inconvenience of access.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.367-376
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• 2022

In traditional criminal cases, there is a limit to information collection because information on the subject of investigation is provided only with personal information held by the national organization of legal. Surface web-based OSINT(Open Source Intelligence), including SNS and portal sites that can be searched by general search engines, can be used for meaningful profiling for criminal investigations. The Korean-style OSINT workflow can effectively profile based on OSINT, but in the case of individuals, OSINT that can be collected is limited because it begins with "name", and the reliability is limited, such as collecting information of the persons with the same name. In order to overcome these limitations, this paper defines information related to individuals, i.e., equivalent information, and enables efficient and accurate information collection based on this. Therefore, we present an improved workflow that can extract information related to a specific person, ie., equivalent information, from OSINT. For this purpose, different workflows are presented according to the person's profile. Through this, effective profiling of a person (individuals) is possible, thereby increasing reliability in collecting investigation information. According to this study, in the future, by developing a system that can automate the analysis process of information collected using artificial intelligence technology, it can lay the foundation for the use of OSINT in criminal investigations and contribute to diversification of investigation methods.

• Journal of the Korea Society for Simulation
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• v.31 no.1
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• pp.11-18
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• 2022

Recently, research to classify human activity using imagery has been actively conducted for the purpose of crime prevention and facility safety in public places and facilities. In order to improve the performance of human activity classification, most studies have applied deep learning based-transfer learning. However, despite the increase in the number of backbone network models that are the basis of deep learning as well as the diversification of architectures, research on finding a backbone network model suitable for the purpose of operation is insufficient due to the atmosphere of using a certain model. Thus, this study applies the transfer learning into recently developed deep learning backborn network models to build an intelligent system that classifies human activity using imagery. For this, 12 types of active and high-contact human activities based on sports, not basic human behaviors, were determined and 7,200 images were collected. After 20 epochs of transfer learning were equally applied to five backbone network models, we quantitatively analyzed them to find the best backbone network model for human activity classification in terms of learning process and resultant performance. As a result, XceptionNet model demonstrated 0.99 and 0.91 in training and validation accuracy, 0.96 and 0.91 in Top 2 accuracy and average precision, 1,566 sec in train process time and 260.4MB in model memory size. It was confirmed that the performance of XceptionNet was higher than that of other models.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.5
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• pp.133-138
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• 2022

Recently, as GPU performance has improved in HPC and artificial intelligence, its use is becoming more common, but GPU programming is still a big obstacle in terms of productivity. In particular, due to the difficulty of managing host memory and GPU memory separately, research is being actively conducted in terms of convenience and performance, and various CPU-GPU memory transfer programming methods are suggested. Meanwhile, recently many SoC (System on a Chip) products such as Apple M1 and NVIDIA Tegra that bundle CPU, GPU, and integrated memory into one large silicon package are emerging. In this study, data between CPU and GPU devices are used in such an integrated memory device and performance-related research is conducted during transmission. It shows different characteristics from the existing environment in which the host memory and GPU memory in the CPU are separated. Here, we want to compare performance by CPU-GPU data transmission method in NVIDIA SoC chips, which are integrated memory devices, and NVIDIA SMX-based V100 GPU devices. For the experimental workload for performance comparison, a two-dimensional matrix transposition example frequently used in HPC applications was used. We analyzed the following performance factors: the difference in GPU kernel performance according to the CPU-GPU memory transfer method for each GPU device, the transfer performance difference between page-locked memory and pageable memory, overall performance comparison, and performance comparison by workload size. Through this experiment, it was confirmed that the NVIDIA Xavier can maximize the benefits of integrated memory in the SoC chip by supporting I/O cache consistency.