• Journal of Drive and Control
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• v.20 no.4
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• pp.100-106
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• 2023

We developed a crawler-based driving platform that can perform harvesting, transportation, pest control, and rotary operation by equipping it with various implements, and analyzed its performance. This single platform was developed to perform as pepper harvester, peanut harvester, and transporter with a 46-kW engine. A simulation model was developed to study the specifications of the platform, and the accuracy was also analyzed. The absolute percentage error ranged from 0.2 to 5.9%, which made it possible to predict the platform performance using simulation model. In T-test, both torque and speed on field and asphalt showed a significant difference (1%). Driving torque required differed depending on the nature of the field, and the speeds also changed based on soil load. The developed platform has the advantage of being equipped with a variety of working tools, expected to be used to harvest root crops in the future.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.173-178
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• 2020

As the fourth industrial revolution, in which people, objects, and information are connected as one, various fields such as smart energy, smart cities, artificial intelligence, the Internet of Things, unmanned cars, and robot industries are becoming the mainstream, drawing attention to big data. Among them, Smart Grid is a technology that maximizes energy efficiency by converging information and communication technologies into the power grid to establish a smart grid that can know electricity usage, supply volume, and power line conditions. Smart meters are equient that monitors and communicates power usage. We start with the goal of building a virtual smart grid and constructing a virtual environment in which real-time data is generated to accommodate large volumes of data that are small in capacity but regularly generated. A major role is given in creating a software/hardware architecture deployment environment suitable for the system for test operations. It is necessary to identify the advantages and disadvantages of the software according to the characteristics of the collected data and select sub-projects suitable for the purpose. The collected data was collected/loaded/processed/analyzed by the Hadoop ecosystem-based big data platform, and used to predict power demand through deep learning.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.903-921
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• 2024

Industry 5.0 puts forward higher requirements for smart cities, including low-carbon, sustainable, and people-oriented, which pose challenges to the design of smart cities. In response to the above challenges, this study introduces the cyber-physical-social system (CPSS) and parallel system theory into the design of smart cities, and constructs a smart city framework based on parallel system theory. On this basis, in order to enhance the security of smart cities, a sustainable patrol subsystem for smart cities has been established. The intelligent patrol system uses a drone platform, and the trajectory planning of the drone is a key problem that needs to be solved. Therefore, a mathematical model was established that considers various objectives, including minimizing carbon emissions, minimizing noise impact, and maximizing coverage area, while also taking into account the flight performance constraints of drones. In addition, an improved metaheuristic algorithm based on ant colony optimization (ACO) algorithm was designed for trajectory planning of patrol drones. Finally, a digital environmental map was established based on real urban scenes and simulation experiments were conducted. The results show that compared with the other three metaheuristic algorithms, the algorithm designed in this study has the best performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.664-671
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• 2020

A Smart Building, one that uses automated processes to control its operations, refers in this study to one that uses both Internet of Things (IoT) devices and cloud services software. Cloud service providers (e.g. Amazon, Google, and Microsoft) have recently providedIoT cloud platform application services on IoT devices. According to Postscapes, there are now 152 IoT cloud platforms. Choosing one for a smart building is challenging. We selected Microsoft Azure IoT Hub and Amazon's AWS (Amazon Web Services) IoT. The two platforms were evaluated and selected from a smart building perspective. Each prototype was evaluated on two different IoTplatforms, assuming a typical smart building scenario. The selection was based on information and experience gained from developing the prototype system using the IoT cloud platform. The assessment made in this evaluation may be used to select an IoTcloud platform for smart buildings in the future.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.237-243
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• 2014

In this paper, we propose a mobile image retrieval system which utilizes the mobile device's sensor information and enables running in a variety of the environments, and implement the system on Android platform. The proposed system deals with a new image descriptor using combination of the visual feature with EXIF attributes in the target of JPEG image, and image matching algorithm which is optimized to the mobile environments. Experiments are performed on the Android platform, and the experimental results revealed that the proposed algorithm exhibits a significant improved results with large image database.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.7-15
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• 2010

Recently, there are many home network applications using the convergence between mobile platforms and home network system. As smart phones which are called small PC in the hand becoming popular, the development of home network application beyond the one of cellular phones is required. Android mobile platform of Google includes OS, middleware and primary applications. Also, in addition to smart phones, it can be mounted on various devices such as set-top box and household appliances. In this paper, home network services on smart phones of Android platform are designed and implemented. The services provide real-time monitoring information (temperature, humidity, real-time video) of rooms and appliance control in a house.

• Journal of Platform Technology
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• v.6 no.3
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• pp.38-46
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• 2018

Smart Grid is an intelligent power grid for efficiently producing and consuming electricity through bi-directional communication between power producers and consumers. As renewable energy develops, the share of renewable energy in the smart grid is increasing. Renewable energy has a problem that it differs from existing power generation methods that can predict and control power generation because the power generation changes in real time. Applying a self-adaptative framework to the Smart Grid will enable efficient operation of the Smart Grid by adapting to the amount of renewable energy power generated in real time. In this paper, we assume that smart villages equipped with photovoltaic power generation facilities are installed, and apply the self-adaptative framework, AiTES, to show that smart grid can be efficiently operated through self adaptation framework.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2434-2454
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• 2021

This paper developed the software testing factory-cloud testing platform (STF-CTP) to address the software compatible issues in various smart devices. Software developers who only require uploading the application under test (AUT) and test script can test plenty of smart devices in STF-CTP. The challenge for the cloud test platform is how to optimize the resource and increase the performance in the limited resource. This paper proposed a new scheduling mechanism and a new process of the system operation which is based on the OpenStack platform. We decrease about 40% memory usage of OpenStack server, increase 3% to 10% Android device usage of STF-CTP, enhance about 80% test job throughput and reduces about 40% test job average waiting time.

• Smart Media Journal
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• v.13 no.6
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• pp.62-71
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• 2024

This study applies topic modeling to uncover user experience and app issues expressed in users' online reviews of a fan community platform, Weverse on Google Play Store. It allows us to identify the features which need to be improved to enhance user experience or need to be maintained and leveraged to attract more users. Therefore, we collect 88,068 first-level English online reviews of Weverse on Google Play Store with Google-Play-Scraper tool. After the initial preprocessing step, a dataset of 31,861 online reviews is analyzed using Latent Dirichlet Allocation (LDA) topic modeling with Gensim library in Python. There are 5 topics explored in this study which highlight significant issues such as network connection error, delayed notification, and incorrect translation. Besides, the result revealed the app's effectiveness in fostering not only interaction between fans and artists but also fans' mutual relationships. Consequently, the business can strengthen user engagement and loyalty by addressing the identified drawbacks and leveraging the platform for user communication.

• Journal of Information Technology Services
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• v.21 no.1
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• pp.127-144
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• 2022

Recently, Korea is promoting cooperation with various countries, centering on ASEAN countries, with the aim of exporting Korean smart cities for the globalization of smart cities. The purpose of this study is to select excellent smart city technologies through analysis of smart city technologies owned by domestic companies and company status, and to prepare a plan for revitalization of companies with smart city technologies. Through prior research, the implications were derived through research on the existing smart city. Next, established a smart city policy analysis and smart city technology classification criteria through Korea and Overseas smart city policy and Korea smart city technology status DB. And the big data of smart city technology possessed by Korea companies and a plan for selecting a smart city export technology was prepared through analysis by region and company. As a result, to activate the technology possessed by Korea companies and to export overseas, it seems to need financial support and tax incentives that secure a pathway to export specialized smart technologies of SMEs, along with citizen participation and institutional supplementation. The smart city technology fields with the highest utilization in Korea were traffic, green energy, e-government, crime prevention, and construction, and the service types were platform, IoT, AI, big data, and GIS/GPS. These technologies are expected to contribute to building a platform for overseas smart city technology exports.