• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.55-62
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• 2022

The perovskite solar cell is an active part of research in renewable energy fields such as solar energy, wind, hydroelectric power, marine energy, bioenergy, and hydrogen energy to replace fossil fuels such as oil, coal, and natural gas, which will gradually disappear as power demand increases due to the increase in use of the Internet of Things and Virtual environments due to the 4th industrial revolution. The perovskite solar cell is a solar cell device using an organic-inorganic hybrid material having a perovskite structure, and has advantages of replacing existing silicon solar cells with high efficiency, low cost solutions, and low temperature processes. In order to optimize the light absorption layer thin film predicted by the existing empirical method, reliability must be verified through device characteristics evaluation. However, since it costs a lot to evaluate the characteristics of the light-absorbing layer thin film device, the number of tests is limited. In order to solve this problem, the development and applicability of a clear and valid model using machine learning or artificial intelligence model as an auxiliary means for optimizing the light absorption layer thin film are considered infinite. In this study, to estimate the light absorption layer thin-film optimization of perovskite solar cells, the regression models of the support vector machine's linear kernel, R.B.F kernel, polynomial kernel, and sigmoid kernel were compared to verify the accuracy difference for each kernel function.

• 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.

• Journal of The Korean Association of Information Education
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• v.24 no.1
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• pp.39-48
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• 2020

This study analyzes PISA's ICT background survey on OECD countries published in December 2019 to analyze ICT accessibility and utilization of each subject. In Korea, ICT accessibility at home is 40.40%, ranking 17th, slightly higher than the OECD average (43.01%). Access to schools is 40.40%, ranking 21st below the OECD average(43.01%), which has improved from the lowest group to three in the middle three years ago. In nine subjects, the proportion of students using digital device in the classroom is 2.96%, well below the OECD average(8.22%), and ranked 31st in the OECD country. This shows that the state needs a change in education policy in order to cultivate the talent needed for the AI era.

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.63-74
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• 2020

AI products are used 'AI assistants' as embedded in smart phones, speakers, appliances as agents. Studies on anthropomorphism, such as personality, voice with a weak AI are being conducted. Role and function of AI agents will expand from development of AI technology. Various attributes related to the agent, such as user type, usage environment, appearance of the agent will need to be considered. This study intends to categorize interaction factors related to agents from the user's perspective through analysis of concept videos which agents with strong AI. Framework for analysis was built on the basis of theoretical considerations for agents. Concept videos were collected from YouTube. They are analyzed according to perspectives on environment, user, agent. It was categorized into 8 attributes: viewpoint, space, shape, agent behavior, interlocking device, agent interface, usage status, and user interface. It can be used as reference when developing, predicting agents to be commercialized in the future.

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.75-80
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• 2020

Since the Fourth Industrial Revolution, important technologies such as big data analysis, robotics, Internet of Things, and the artificial intelligence have been used in various fields. Generally speaking it is understood that the big-data technology consists of gathering stage for enormous data, analyzing and processing stage and distributing stage. Until now crime records which is one of useful big-sized data are utilized to obtain investigation information after occurring crimes. If crime records are utilized to predict crimes it is believed that crime occurring frequency can be lowered by processing big-sized crime records in big-data framework. In this research the design is proposed that the smart system can provide the users of smart devices crime occurrence probability by processing crime records in big-data analysis. Specifically it is meant that the proposed system will guide safer routes by displaying crime occurrence probabilities on the digital map in a smart device. In the experiment result for a smart application dealing with small local area it is showed that its usefulness is quite good in crime prevention.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.213-216
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• 2018

As the advantages of smart devices based on artificial intelligence and voice recognition become more prominent, Virtual Assistant is gaining popularity. Virtual Assistant provides a user experience through smart speakers and is valued as the most user friendly IoT device by consumers. The purpose of this study is to investigate whether there are differences in people's perception of the key virtual assistant brand voice recognition. We collected tweets that included six keyword form three companies that provide Virtual Assistant services. The authors conducted semantic network analysis for the collected datasets and analyzed the feelings of people through sentiment analysis. The result shows that many people have a different perception and mainly about the functions and services provided by the Virtual Assistant and the expectation and usability of the services. Also, people responded positively to most keywords.

• Journal of the Semiconductor & Display Technology
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• v.18 no.3
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• pp.122-126
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• 2019

These-days technology related to IoT (Internet of Thing) is widely used and there are many types of smart system based IoT like smart health, smart building and so on. In smart health system, it is possible to check someone's health by analyzing data from wearable IoT device like smart watch. Smart building system aims to collect data from sensor such as humidity, temperature, human counter like that and control the building for energy efficiency, security, safety and so forth. Furthermore, smart city system can comprise several smart systems like smart building, smart health, smart mobility, smart energy and etc. In this paper, we propose multimedia IoT based intelligent emergency alarm system for smart city. In existing IoT based smart system, it communicates lightweight data like text data. In the past, due to network's limitations lightweight IoT protocol was proposed for communicating data between things but now network technology develops, problem which is to communicate heavy data is solving. The proposed system obtains video from IP cameras/CCTVs, analyses the video by exploiting AI algorithm for detecting emergencies and prevents them which cause damage or death. If emergency is detected, the proposed system sends warning message that emergency may occur to people or agencies. We built prototype of the intelligent emergency alarm system based on MQTT and assured that the system detected dangerous situation and sent alarm messages. From the test results, it is expected that the system can prevent damages of people, nature and save human life from emergency.

• Journal of The Korean Association of Information Education
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• v.22 no.6
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• pp.711-721
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• 2018

The development of artificial intelligence technology and the shift to a software-driven society are raising the need for digital literacy education on how to access, understand, use, create and share new open content in a variety of sustainable open content. At this point in time, this paper defines the digital literacy as the subliteracy concept for data, tools, and device elements. It is defined as a concept that includes cognitive and non-cognitive abilities and is stratified by computer literacy, ICT literacy, and information literacy. Open content is also defined as teaching-learning materials that can be used and shared freely by anyone, such as the Open Education Resource (OER) and the Open Access movement. Based on the two definitions, a three-step strategy for digital literacy education was developed to select open content in the digital environment, followed by a digital literacy education plan, and finally, an education frame to foster digital literacy capabilities.

• Convergence Security Journal
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• v.18 no.4
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• pp.73-79
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• 2018

Since 1910s, the drones were mainly used for military purposes for reconnaissance and attack targets, but they are now being used in various fields such as disaster prevention, exploration, broadcasting, and surveillance of risk areas. As drones are widely used from military to civilian field, hacking into the drones such as radio disturbance, GPS spoofing, hijacking, etc. targeting drones has begun to occur. Recently, the use of drones in hacking into wireless network has been reported. If the artificial intelligence technology is applied to the drones in the military, hacking into unmanned combat system using drones will occur. In addition, a drone with a hacking program may be able to relay a hacking program to the hacking drone located far away, just as a drone serves as a wireless communication station. And the drones will be equipped with a portable GPS jamming device, which will enable signal disturbance to unmanned combat systems. In this paper, we propose security threats and the anticipated hacking scenarios using the drones on the battlespace to know the seriousness of the security threats by hacking drones and prepare for future cyberspace.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.111-116
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• 2019

New technologies such as the IoT, Big Data, and Artificial Intelligence, starting from the Web, mobile, and smart device, enable new business models that did not exist before, and various types of Internet companies based on these business models has been emerged. In this research, we examine the factors that influence the success and failure of Internet companies. To do this, we review the recent studies on business model and examine the variables affecting the success of Internet companies in terms of network effect, user interface, cooperation with actors, creating value for users. Using the five derived variables, we will select 14 Internet companies that succeeded and failed in seven commercial business model categories. We derive decision tree by applying inductive learning based on ID3 algorithm to the analysis result and derive rules that affect success and failure based on derived decision tree. With these rules, we want to present the strategic implications for actors to succeed in Internet companies.