• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.4
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• pp.254-259
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• 2014

In this paper, we describe construction of a wind stabilization demo-site and effects of output power control of wind turbines for suppression of ramp rate using ESS (Energy Storage System). It is difficult to control the output power of distributed generator such as wind turbine which of variation is very large. If the large capacity wind farm be interconnected into power system may cause blackout due to Power Quality. For these reasons, the international standards such as Grid-Code is limited to less than 10 [%/min] of renewable energy ramp rate. The case of Korea, government actively conducts propagating large-scale renewable energy for green growth policy, to interconnecting more renewable energy into power system is necessary for stabilization technology. For these reasons, the POSCO consortium has constructed a wind stabilization demo-site that is configured as 500 [kWh] battery energy storage systems can output up to 3 [C-Rate] and two wind turbines rated 750 [kW]. In POSCO consortium, which implements various methods stabilizing output power of wind turbine such as smoothing, section firming and ramp control, we derive the results of long-term demonstration that can be controlled to satisfy to the international standard about ramp rate [%/kW] of wind turbine output power.

• Journal of Korea Multimedia Society
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• v.22 no.5
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• pp.613-625
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• 2019

The rise of the Internet of Things (IoT) devices have greatly influenced many industries and one of them is healthcare where wearable devices started to track all your daily activities for better health monitoring accuracy and even down to tracking daily food intake in some cases. With the amounts of data that are being tracked and shared between from these devices, questions were raised on how to uphold user's data privacy when data is shared between these IoT devices and third party. With the blockchain platforms started to mature since its inception, the technology can be implemented according to a variety of use case scenarios. In this paper, we present a system architecture based on the healthcare system and IoT network by leveraging on multiple blockchain networks as the medium in between that should enable users to have direct authority on data accessibility of their shared data. We provide proof of concept implementation and highlight the results from our testing to show how the efficiency and scalability of the healthcare system improved without having a significant impact on the performance of the Electronic Medical Record (EMR) that mostly affected by the previous solution since these solutions directly connected to a public blockchain network and which resulted in significant delays and high cost of operation when a large amount of data or complicated functions are involved.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.3
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• pp.27-35
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• 2016

Ministry of Science, ICT and Future Planning have boosted up launching more 'GRI(Government Research Institute) Spin-off High-tech startup' to accelerate the technology commercialization of GRI technologies via the alternative of high-tech startup since 2101. This paper is proposing to found the global platform of accommodating more successful high-tech startup with diagnosing the current policy platform of launching GRI high-tech startup. This paper deliver the outcomes of case study including FGI research over developing the ideas of the experts for the policy line-up of starting from GRI technologies-Hardware Manufacture-BtoB-Global. The research result suggests that the focus of policy should falls not on the quantitative goals, but on more disruptive successful case through utilizing uprising private equity investment in the early stage of business. One of the best policy brought by this research is 'Inbound Globalization Strategy of bringing global early stage investors in Korea for incubation and investment rather than sending out our startup to global without validation by global investor.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.6
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• pp.689-702
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• 2019

This paper deals with the verification of the functions about mining robot, which is the system for developing deep seabed resources by applying V&V(verification and validation). In order to overcome water pressure of 500 bar and to travel on soft ground, and to operate in deep sea environment with bad conditions, it is necessary to develop a robot that can satisfy various deepsea conditions. A mining robot has been developed based on simulation based design and Multidisciplinary design optimization. In order to verify the developed robot, lab test and real sea test should be performed for various marine environment conditions. There are too many requirements to consider, such as space, time, cost, personnel, and environment to do performance test. So it is costly and time consuming for developing robot. In order to solve this problems, V&V technique was applied to mining robot. The stages of mining robot design, fabrication and commission were verified.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.943-948
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• 2022

Drones have been widely used in various fields due to the rapid development of done-related technologies, which causes various problems. The schemes which can track target drones by using signal transmitted by target drones have been investigated as a key technology for anti-drone systems to solve these problems. In this paper, we investigate an illegal drone tracking system based on swarming flight that consists of multiple small drones in order to resolve the limitations of a conventional system that consists of a single drone. In addition, we also propose a scheme with which we can adaptively adjust the separation distance between small drones in a swarm according to channel situations. We analyzed the performance of the proposed scheme in terms of success ratio and the number of movements. The proposed scheme can improve the success ratio and the number of movements by 170% and 63% respectively, compared to the conventional scheme.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.2
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• pp.67-72
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• 2022

Recently, various intelligent application services using artificial intelligence are being actively developed. In particular, research on artificial intelligence-based real-time prediction services is being actively conducted in the manufacturing industry, and the demand for artificial intelligence services that can detect and predict fire and odors is very high. However, most of the existing detection and prediction systems do not predict the occurrence of fires and odors, but rather provide detection services after occurrence. This is because AI-based prediction service technology is not applied in existing systems. In addition, fire prediction, odor detection and odor level prediction services are services with ultra-low delay characteristics. Therefore, in order to provide ultra-low-latency prediction service, edge computing technology is combined with artificial intelligence models, so that faster inference results can be applied to the field faster than the cloud is being developed. Therefore, in this paper, we propose an LSTM algorithm-based learning model that can be used for fire prediction and odor detection/prediction, which are most required in the manufacturing industry. In addition, the proposed learning model is designed to be implemented in edge devices, and it is proposed to receive real-time sensor data from the IoT terminal and apply this data to the inference model to predict fire and odor conditions in real time. The proposed model evaluated the prediction accuracy of the learning model through three performance indicators, and the evaluation result showed an average performance of over 90%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.6
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• pp.733-739
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• 2019

Water level measurement is highly demanding in IoT monitoring areas such as smart factory, smart farm, and smart fish farm. However, existing water level indicators are limited to be used in industrial fields as commercial products due to the high cost of sensors and the complexity of algorithms used. In order to solve these problems, our paper proposed methods using an infrared distance sensor as well as a hall sensor for the water level measurement, both of which are contactless smart sensors. Data errors caused by the inaccuracy of existing sensors were decreased by applying new simple structures so that versatility is enhanced. The performance of our method was validated using experiments based on simulations. We expect that our new water depth indicator can be extended to a general-purpose water level monitoring system based on IoT technology.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.865-872
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• 2017

Recently, in response to the Internet age, the demand for hardware devices has been increasing, centering on the rapidly growing smart home field, due to the growth and management of sensor and control technology, mobile application, network traffic, big data management and cloud computing. In order to maintain the sustainable development of the hardware system, it is necessary to update the system, and the hardware device is absolutely necessary in real time processing of complex data (voice, image, etc.) as well as data collection. In this paper, we propose a method to simplify the control and communication method by integrating the hardware devices in two operating systems in a unified structure to solve the simultaneous control and communication method of hardware under different operating systems. The performance evaluation results of the proposed integrated hardware and the cloud control system connected to the cloud server are described and the main directions to be studied in the field of internet smart home are described.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.47-53
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• 2015

In this paper the factors are analyzed, which influenced on the acceptance of Electronic Medical System (EMR) of healthcare organization in Korea. The measured variables and factors were defined on the base of former research works. The questionnaires with Likert's 5 scale were administrated in the 102 general hospitals in Korea. This data was analyzed with SPSS v. 20. According to the result of factor analysis, the 4 influencing factors were grouped. They are, "ICT-infrastructure of healthcare organization", "Management strategy of healthcare organization", "EMR acceptance" and "EMR-performance". 5 hypotheses about the correlations between factors were formulated and analyzed with structural equation model(SEM). The result of this paper could be the good reference to the healthcare organizations on how they should implement and operate the EMR system.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.41-49
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• 2024

Speech recognition technology is continuously advancing and widely used in various fields. In this study, we aimed to investigate the impact of speech data quality on speech recognition models by dividing the dataset into the entire dataset and the top 70% based on Signal-to-Noise Ratio (SNR). Utilizing Seamless M4T and Google Cloud Speech-to-Text, we examined the text transformation results for each model and evaluated them using the Levenshtein Distance. Experimental results revealed that Seamless M4T scored 13.6 in models using data with high SNR, which is lower than the score of 16.6 for the entire dataset. However, Google Cloud Speech-to-Text scored 8.3 on the entire dataset, indicating lower performance than data with high SNR. This suggests that using data with high SNR during the training of a new speech recognition model can have an impact, and Levenshtein Distance can serve as a metric for evaluating speech recognition models.