• Journal of the Korean Society for Precision Engineering
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• v.25 no.7
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• pp.79-86
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• 2008

This paper describes the development of wearing intelligent shoe system to measure applied forces and moments (ground reaction forces and moments) on the soles of feet during human walking. In order to walk safely, robot must get the intelligent feet with 6-axis force/moment sensors (Fx sensor (x-direction force sensor), Fy sensor, Fz sensor, Mx sensor (Mx : x-direction moment sensor), My sensor, and Mz sensor) and detect the forces and moments data from the sensors. And the feet must be controlled with the data and controllers. While a human is walking, the forces and moments should be measured and analyzed for robot's intelligent feet. Therefore, the wearing intelligent shoe system should be developed. In this paper, four 6-axis farce/moment sensors and two high speed measuring devices were designed and fabricated, and the wearing intelligent shoe system was made using these. The characteristic tests of the wearing intelligent shoe system were performed, and the forces and moments were detected using it.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.1
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• pp.79-89
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• 1993

This paper deals with a computer aided control of an adjustment process for the complete electronic devices by means of an application of artificial neural network and an implementation of neuro-controller for intelligent control. Multi-layer neural network model is employed as artificial neural network with the learning method of the error back propagation. Information initially available from real plant under control are the initial values of plant output, and the augmented plant input and its corresponding plant output at that time. For the intelligent control of adjustment process utilizing artificial neural network, the neural network emulator (NNE) and the neural network controller(NNC) are developed. The initial weights of each neural network are determined through off line learning for the given product and it is also employed to cope with environments of the another product by on line learning. Computer simulation, as well as the application to the real situation of proposed intelligent control system is investigated.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1563-1567
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• 2005

The Home network system means that information appliances, Home PCs, etc., using wired or wireless network method enable to control and share with peripheral devices such as internet, shared data, a scanner and a printer, and it is networking solution, which intelligent communication will be possible as the system which can do a remote control such as TV Set, refrigerators, air conditioners, DVD players, digital camcorders based on external network using an internet, a potable information terminal and a mobile phone whenever, wherever and freely. In this study, the home network interface solution is used one of the wired network standards, PLC (Power-Line Communication) technology, so we can construct of intelligent home network's home controller without re-build a network at home. On keeping with current waves of thought, we will focus on a home controller development with great interest which is enabled to do an effective managed control, applying intelligent home network technology which can be new paradigm like a cyber apartment.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.25-27
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• 2009

In this paper, a sensor network system for providing intelligent home network services is suggested. It steadily collects biological data of resident people and automatically detects emergency situations LEID(Lighting Embedded Information Device) system are the most essential component of the sensor network. They embed sensor network technology into lightening devices which are indispensable most living spaces. To verify practicality of the proposed intelligent home network service system, a prototypical system is realized in the Smart Home Industrialization Support Center at Kookmin University, and is tested within many practical circumstances.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.790-796
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• 1998

A novel mode of parallel operation of a modular 3-phase AC-DC flyback converter for power factor correction along with tight regulation was recently analyzed and presented. The advantage of the proposed converter does not require expensive high voltage and high current devices that are normally needed in popular boost type 3-phase converter. In this paper the detailed small signal analysis of the modular 3-phase AC-DC flyback converter is provided for control purposes and also experimental results are included to confirm the validity of the analysis.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.23-29
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• 2022

To improve spectrum and energy efficiency in the fifth generation (5G) wireless channels, intelligent reflecting surface (IRS) transmissions have been envisioned, possibly towards the sixth generation (6G) networks. In this paper, we analyze the bit-error rate (BER) performance of intelligent reflecting surface (IRS) assisted non-orthogonal multiple access (NOMA) systems. First, we derive a closed-form expression of the BER in terms of Q functions. Then we analyze the BER improvement of the IRS NOMA system over the conventional NOMA system with respect to the power allocation. Furthermore, we also demonstrate numerically the BER improvement of the IRS NOMA network over the conventional NOMA network in respect of the number of reflecting devices.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.84-89
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• 2023

Recently, the sixth generation (6G) networks have become tremendous research topics. Intelligent reflecting surface (IRS) technologies have been envisioned, to increase spectrum and energy efficiency for the fifth generation (5G) mobile networks, towards the sixth generation (6G) communications. In this paper, especially for the strongest channel gain user, we investigate the bit-error rate (BER) of non-orthogonal multiple access (NOMA) systems with intelligent reflecting surface (IRS). First, we derive a BER expression in a closed-form of Q functions. Second, we investigate the BER performance improvement of IRS NOMA systems over NOMA systems versus the power allocation. Moreover, we analyze the BER performance improvement of IRS NOMA systems over NOMA systems versus the number of IRS devices. In results, NOMA equipped with IRS technologies could play an important role in the paradigm shift from 5G mobile networks to 6G mobile networks.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.47-56
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• 2010

In navigation, officers receive data about inside and outside of ship from several devices(ex, GPS / AIS / ECDIS / ARPA Radar / etc) in bridge, and use it to recognize and predict safety situations. However, observation work of a officer is still hard for a torrent of data from several devices, and the problem of inconsistent data among the devices. In previous research, we presented the conceptual model of Intelligent Navigation Safety Information System based on information fusion, and showed the example of the conceptual model using CF (Certainty Factor) expert system to solve this problem. The information fusion technology needs various reasoning skills, and CF expert system is not enough to express ambiguous or indefinite factors. In this paper, we propose the concept of an intelligent navigation information fusion using fuzzy expert system to describe the ambiguous factors, and show the validity of applying fuzzy expert system to the Navigation Safety Information System through the design and implementation of the proposed concept.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.565-570
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• 2015

In this paper, we implemented the smart door lock system that control remotely devices using the concept of internet of things. Internet of things is intelligent system that can help devices to communicate with people and devices. And recently internet of things is getting attention because of advance of hardware technology and big data. The smart doorlock system based on internet of things used raspberry pi, sensor and doorlock. Using the smart phone, doorlock can be controlled from the raspberry pi server. And the user can identify some people that is in front of doorlock. also user can check around of doorlock in realtime using the raspberry pi camera.