• Design & Manufacturing
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• v.16 no.1
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• pp.55-61
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• 2022

As meters become digital and smart, energy data such as electricity, gas, heat, and water can be accurately and efficiently measured with a smart meter, providing consumers with data on energy used, so that real-time demand response and energy management services can be utilized. Although it is developing from a simple metering system to a smart metering industry to create a high value-added industry fused with ICT, illegal counterfeiting of electronic meters is causing problems in intelligent crimes such as manipulation and hacking of SW. The meter not only allows forgery of the meter data through arbitrary manipulation of the SW, but also leaves a fatal error in the metering performance, so that the OIML requires the validation of the SW from the authorized institution. In order to solve this problem, a quantitative confirmation device was developed in order to eradicate the act of cheating the fuel oil quantity through encoder pulse operation and program modulation, etc. In order to prevent the act of deceiving the lubricator, a device capable of checking pulse forgery was developed, manufactured, and verified. In addition, the performance of the device was verified by conducting an experiment on the meter being used in the actual field. It is judged that the developed quantitative confirmation device can be applied to other flow meters other than lubricators, and in this case, accurate measurement can be induced.

• Fashion & Textile Research Journal
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• v.20 no.1
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• pp.101-107
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• 2018

The purpose of this study is to develop the electroconductive textiles based on polyurethane(PU) nanoweb and to explore that it is applicable to smart clothing. The electroconductive textiles developed by coating 2.0 wt% aqueous dispersed non-oxidized graphene paste on the surface of PU nanoweb. The fabricated electroconductive nanoweb was applied as a transmission line to connect the LED lamp, and the brightness of the LED lamp was measured to confirm its performance. The nanoweb transmission line was fixed by two methods(seam sealing tape, embroidering) to connect the LED lamp and AA batteries. The results as follows, the brightness of the LED lamp fixed with seam sealing tape was about 82 lux, and which fixed with embroidering was about 57 lux. It represents that the nanoweb transmission line which fixed with the seam sealing tape has better electrical signal transmitting because the lux value higher than the one fixed by embroidering. In order to compare the performance of the nanoweb transmission line and the metal wire, we connected the LED lamp with copper wire. The brightness of copper wire connected LED lamp was about 193 lux. Although the electrical signal strength of the nanoweb transmission line was weaker than the copper wire, it was reachable to operate LED lamp. The results of this study will provide a basic data to develop the textile based electronic devices, and conducting wire for smart clothing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1833-1839
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• 2017

Korea Railway is enhancing the railway wireless communication system from VHF and TRS which have been used for 100 years to LTE-R starting with Ministry of Science and ICT's allocation of Integrated Public Network Frequency on December 2014. LTE-R has advantages on technology performance, also on ease of evolution based on standardization compared to existing technologies. However there are few problems that need to be solved to provide stable railway wireless services in the future. Due to national spectrum policy, LTE-R has frequency interference with Integrated Public Networks (PS-LTE, LTE-M ) and UHD-TV which was commercialized in 2017. This paper introduces performance changes caused by interferences which were founded from the test bed in Wonju~Gangneung LTE-R project and the result of RAN-Sharing. In addition, this paper suggests the standard for LTE-R cell planning in the case of sharing the Integrated Public Network Frequency by analyzing the changes of designed link-budget factor based on the test result.

• Journal of Broadcast Engineering
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• v.28 no.3
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• pp.302-313
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• 2023

This paper aims to develop a framework that can fully automate the quality management of training data used in large-scale Artificial Intelligence (AI) models built by the Ministry of Science and ICT (MSIT) in the 'AI Hub Data Dam' project, which has invested more than 1 trillion won since 2017. Autonomous driving technology using AI has achieved excellent performance through many studies, but it requires a large amount of high-quality data to train the model. Moreover, it is still difficult for humans to directly inspect the processed data and prove it is valid, and a model trained with erroneous data can cause fatal problems in real life. This paper presents a dataset reconstruction framework that removes abnormal data from the constructed dataset and introduces strategies to improve the performance of AI models by reconstructing them into a reliable dataset to increase the efficiency of model training. The framework's validity was verified through an experiment on the autonomous driving dataset published through the AI Hub of the National Information Society Agency (NIA). As a result, it was confirmed that it could be rebuilt as a reliable dataset from which abnormal data has been removed.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.221-228
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• 2022

With the application of artificial intelligence technology, robots can provide efficient services in real life. Unlike industrial manipulators that do simple repetitive work, this study presented design methods of 6 degree of freedom robot arm and intelligent object search and movement methods for use alone or in collaboration with no place restrictions in the service robot field and verified performance. Using a depth camera and deep learning in the ROS environment of the embedded board included in the robot arm, the robot arm detects objects and moves to the object area through inverse kinematics analysis. In addition, when contacting an object, it was possible to accurately hold and move the object through the analysis of the force sensor value. To verify the performance of the manufactured robot arm, experiments were conducted on accurate positioning of objects through deep learning and image processing, motor control, and object separation, and finally robot arm was tested to separate various cups commonly used in cafes to check whether they actually operate.

• International Commerce and Information Review
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• v.17 no.2
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• pp.307-327
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• 2015

Trade education methods that combine practical knowledge and on-site job training have significantly contributed in improving abilities of trade experts. For instance, GTEP and LINC have contributed to a substantial expansion of SME export performane. Moreover, students' cooperation experience have led to employment outcomes as SMEs can employ customized trade workers. I have conducted a survey to 100 students about university-industry collaboration. Results show that ICT skills and foreign language ability are the highest required conditions of employment while production and technology knowledge are the lowest. Furthermore, 50 companies operating in foreign markets responded that through industry-university cooperation, capabilities of university graduates have improved and trade education cooperation scheme is a success.

• Journal of Korea Trade
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• v.26 no.7
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• pp.145-166
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• 2022

Purpose - The field of online videos has seen rapid changes in information and communications technology (ICT) development. Despite active academic research on the use of online platforms, few studies have analyzed the relative importance among the factors determined. In this study, the relative importance of factors found in previous studies was identified for users of online video platforms in China and Korea. Through this, factors that should be considered first in research on online video use were derived. In addition, the quality level of online video platforms currently used in China and Korea was measured and used for analysis. The analysis results can provide information for companies to enter Chinese and Korean markets and also be useful to platform providers aiming to increase usage. Design/methodology - Among the factors of Online Video Usage identified in previous studies, 13 factors to be studied were selected through focus group interviews and hierarchized into 2 layers. For the analytic hierarchy process (AHP), each factor was designed as a pairwise comparison questionnaire. The survey included questions on the quality of online video platform currently in use. Data collection was conducted on 16 platforms in China and 11 platforms in Korea, and the relative importance of factors and user perspectives was compared and analyzed using importance performance analysis (IPA). In the analytical process, platforms were divided into over-the-top (OTT) group and Creator group according to the weight of user-generated content, and data analysis focused on these groups. Findings - As a result of AHP, China and Korea showed both "Fun" and "Interests" factors at the top, while the importance of the Entertainment factor "Vicarious satisfaction" was very different for China and Korea. "Relationship with content creators" was the most important factor in China, but it ranked the lowest in Korea. The IPA showed that the factors with high importance and performance were fun, interests, and easy accessibility for both China and Korea. In contrast, the factors that showed low performance compared to high importance in China were relationship with content creators, relationship with acquaintances/friends, and trustworthiness. As for Korea, vicarious satisfaction was observed; thus, this study has raised the need for academic and industrial interest in vicarious satisfaction. The results show that fun, interests, vicarious satisfaction, and easy accessibility of the platform are factors that must be included in further studies on online videos. Originality/value - Existing studies related to the use of online platforms have derived factors or focused on the influence relationship between factors and performance. However, few studies have analyzed the relative importance among the determined factors. This paper explores factors to be considered in future studies by deriving the relative importance between these factors from the perspective of users in China and Korea.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.159-166
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• 2022

Artificial Intelligence has stimulated every aspect of today's life. Human thinking quality is trying to be involved through digital tools in all research areas of the modern era. The education industry is also leveraging artificial intelligence magical power. Uses of digital technologies in pedagogical paradigms are being observed from the last century. The widespread involvement of artificial intelligence starts reshaping the educational landscape. Adaptive learning is an emerging pedagogical technique that uses computer-based algorithms, tools, and technologies for the learning process. These intelligent practices help at each learning curve stage, from content development to student's exam evaluation. The quality of information technology students and professionals training has also improved drastically with the involvement of artificial intelligence systems. In this paper, we will investigate adopted digital methods in the education sector so far. We will focus on intelligent techniques adopted for information technology students and professionals. Our literature review works on our proposed framework that entails four categories. These categories are communication between teacher and student, improved content design for computing course, evaluation of student's performance and intelligent agent. Our research will present the role of artificial intelligence in reshaping the educational process.

• Journal of Korean Society of Water and Wastewater
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• v.33 no.5
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• pp.329-339
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• 2019

Recently, the advancement of information and communication technology(ICT) is expanding the connectivity through Internet of Things(IoT), and the media of connection is also expanding from wire/cable transmission to broadband wireless communication, which has significantly improved mobility. This hyperconnectivity has become a key element of the fourth industrial revolution, whereas the supervisory control network of purification plants in korea is operated as a communication network separated from the outside, thereby lagging in terms of connectivity. This is considered the best way to ensure security, and thus there is hardly any consideration of establishing alternatives to operate an efficient and stable communication network. Moreover, security for management of a commercialized communication network and network management solution may be accompanied by immense costs, making it more difficult to make new attempts. Therefore, to improve the conditions for the current supervisory control network of purification plants, this study developed a industrial security L2 switch that supports modbus TCP(Transmission Control Protocol) communication and encryption function of the transmission section. As a result, the communication security performance improved significantly, and the cost for implementing the network management system using Historical Trend and information of HMI(Human Machine Interface) could be reduced by approximately KRW 200 million. The results of this study may be applied to systems for gas, electricity and social safety nets that are infrastructure communication networks that are similar to purification plants.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.50-56
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• 2020

With the rapid development of deep neural network theory and application research, the effect of face detection has been improved. However, due to the complexity of deep neural network calculation and the high complexity of the detection environment, how to detect face quickly and accurately becomes the main problem. This paper is based on the relatively simple model of the MTCNN model, using FDDB (Face Detection Dataset and Benchmark Homepage), LFW (Field Label Face) and FaceScrub public datasets as training samples. At the same time of sorting out and introducing MTCNN(Multi-Task Cascaded Convolutional Neural Network) model, it explores how to improve training speed and Increase performance at the same time. In this paper, the dynamic image pyramid technology is used to replace the traditional image pyramid technology to segment samples, and OHEM (the online hard example mine) function in MTCNN model is deleted in training, so as to improve the training speed.