• 전기학회논문지
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• 제64권10호
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• pp.1448-1453
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• 2015

In this paper, we propose an alternative method of communication to improve the reliability of in-vehicle networks by jointly using wireless communication networks. Wired Communication networks have been used in vehicles for the monitoring and the control of vehicle motion, however, the disconnection of wires or hardware fault of networks may cause a critical problem in vehicles. If the network manager detects a disconnection or faults in wired in-vehicle network like the Controller Area Network(CAN), it can redirect the communication path from the wired to the wireless communication like the Zigbee network. To show the validity and the effectiveness of the proposed in-vehicle network architecture, we implement the Electronic Stability Control(ESC) system as ECU-In-the-Loop Simulation(EILS) and verify that the control performance can be kept well even if some hardware faults like disconnection of wires occur.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1487-1497
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• 2016

Explosively growing service of digital multimedia data increases the need for highly scalable low-cost storage. This paper proposes the new storage architecture based on torus network which does not need network switch and erasure coding for efficient storage usage for high scalability and efficient disk utilization. The proposed model has to compensate for the disadvantage of long network latency and network processing overhead of torus network. The proposed storage model was compared to two most popular distributed file system, GlusterFS and Ceph distributed file systems through a prototype implementation. The performance of prototype system shows outstanding results than erasure coding policy of two file systems and mostly even better results than replication policy of them.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.993-996
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• 1993

This paper addresses the structure and its associated learning algorithms of a feedforward multi-layered connectionist network, which has distributed learning abilities, for realizing the basic elements and functions of a traditional fuzzy logic controller. The proposed neural-network-based fuzzy logic control system (NN-FLCS) can be contrasted with the traditional fuzzy logic control system in their network structure and learning ability. An on-line supervised structure/parameter learning algorithm dynamic learning algorithm can find proper fuzzy logic rules, membership functions, and the size of output fuzzy partitions simultaneously. Next, a Reinforcement Neural-Network-Based Fuzzy Logic Control System (RNN-FLCS) is proposed which consists of two closely integrated Neural-Network-Based Fuzzy Logic Controllers (NN-FLCS) for solving various reinforcement learning problems in fuzzy logic systems. One NN-FLC functions as a fuzzy predictor and the other as a fuzzy controller. As ociated with the proposed RNN-FLCS is the reinforcement structure/parameter learning algorithm which dynamically determines the proper network size, connections, and parameters of the RNN-FLCS through an external reinforcement signal. Furthermore, learning can proceed even in the period without any external reinforcement feedback.

• 한국컴퓨터정보학회논문지
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• 제18권10호
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• pp.121-128
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• 2013

기존의 센서 네트워크 연구들은 센서 자체가 가지는 에너지 측면만 강조하였다. 그러나 실제 센서 네트워크를 구성하였을 경우 특정 센서의 많은 활용으로 인해 센서 네트워크의 부분 단절을 초래한다. 이는 결국 센서네트워크가 오랜 시간 효율적으로 운영되지 못하는 단점이 되어 오히려 특정 센서 에너지 효율성이 센서 네트워크의 효율성을 저하시키는 결과를 초래하였다. 센서 네트워크들이 클러스터로 구성되었거나 하나의 큰 네트워크로 구성되어 있는 경우에도 센서의 에너지 효율성을 강조하기 때문에 결국 센서 네트워크의 단절을 회피할 수 없다. 따라서 센서 네트워크를 구성하는 모든 센서들을 고루 사용함으로써 센서 네트워크의 센서들이 단절을 회피하도록 하여 센서 네트워크의 수명을 연장할 수 있도록 한다. 본 논문은 유비쿼터스 환경에서 센서네트워크를 구성하는 프로토콜로 구성된 센서 네트워크의 에너지를 효율적으로 관리하여 센서 네트워크의 단절을 방지함으로써 구성된 센서 네트워크가 오랜 시간 유지되는 프로토콜을 제안한다.

• 정보처리학회논문지C
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• 제19C권2호
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• pp.149-152
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• 2012

이동통신 로밍(roaming)을 하는 경우 외부망(visited network)의 사용 요금이 홈망(home network)에 비해 높게 책정된다. 따라서, 단말이 외부망에 위치하다가 본인의 홈망으로 복귀했는데도 불구하고 여전히 외부망에 등록되어 있는 경우, 사용자의 의도와 무관하게 높은 통신요금이 책정되는 경우가 있다. 이와 같은 문제점은 같은 지역에 여러 사업자의 망이 중복되어 설치된 경우에 자주 발생하는데, 실례로 폴란드 이동통신망 사례를 들 수 있다. 이에 본 논문에서는 이동통신 로밍 사용자의 빠른 홈망 복귀를 위한 망탐색 알고리즘을 제안한다. 제안 기법은 3GPP 규격의 망탐색 동작을 따르면서 단말에 저장된 망정보 DB를 활용하여 홈망을 탐색하는 방식이다. 제안 기법의 성능평가를 위해 실제 단말기와 실험장비를 이용하여 폴란드 사업자 환경을 가상적으로 구축하였다. 실험 결과, 제안 방식이 기존 3GPP 규격 방식에 비해 홈망 복귀시간을 3~60분까지 단축시킬 수 있음을 확인하였다.

• 중소기업융합학회논문지
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• 제6권3호
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• pp.29-35
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• 2016

본 논문은 디바이스 불변 정보를 이용한 사용자 인증 시스템(DCIAS)을 설계 제안한다. 네트워크상의 시스템 접근 시 사용자 인증에 사용될 접근 디바이스 불변정보를 이용한 새로운 패스워드를 설계 정의하고, 다른 응용들에서 획득한 패스워드를 재사용하는 수동적 재전송 공격으로부터 요구되는 보안 위협에 대처할 수 있도록 신 개념 사용자 인증 시스템을 설계 제안한다. 또한 서버 내에 임의의 암호화된 장소에 설계 정의한 패스워드를 저장하여 네트워크를 통한 불법적인 시스템 접근을 무력화시키도록 설계한다. 따라서 제안한 본 시스템을 이용하면 어떠한 네트워크를 통하여 시스템에 접근하더라도 어느 곳에 패스워드가 저장되어 있는지를 알 수 없고, 설상 알았다고 하더라고 저장된 정보가 암호화되어 있어 해독이 쉽지 않아 네트워크상의 어떠한 재전송 공격이라도 무력화할 수 있다는 강력한 보안 특성을 갖는다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2006년도 춘계종합학술대회
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• pp.159-162
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• 2006

언제 어디서나 네트워크에 접속할 수 있는 유비쿼터스 환경에서 웨어러블 컴퓨터들은 자주네트워크의 접속점을 변경하게 된다. 이에 따라, 웨어러블 컴퓨터가 이동 중에 네트워크의 접속점이 변경되더라도 웨어러블 컴퓨터의 네트워크 구성에 대한 변경 없이 기존의 서비스를 계속할 수 있도록 해주는 이동성 지원 서비스의 요구가 증대되고 있다. 본 논문에서는 컴포넌트 기반 웨어러블 컴퓨터용 미들웨어 상에서 이동성 지원을 위한 컴포넌트를 설계하고 이동성 지원 서비스 방식을 제안한다. 제안된 방식은 웨어러블 컴퓨터가 다른 네트워크로 이동하더라도 Mobile IP를 이용하여 웨어러블 컴퓨터에게 기존의 데이터를 터널링 할 수 있도록 이동성 지원 컴포넌트를 웨어러블 컴퓨터 미들웨어 상에 동적으로 재구성한다.

• International journal of advanced smart convergence
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• 제8권3호
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• pp.69-77
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• 2019

Today, most of elevators have an emergency call facility for emergency situations. However, if the network installed in the elevator is also out of power, it cannot be used for the elevator remote monitoring and management. So, we develop an integrated and unified emergency call system, which can transmit not only telephone call but also data signals using PSTN(Public Switched Telephone Network) in order to remote monitoring and management of elevators, even though a power outage occurs. The proposed integrated emergency call system to process multiple data such as voice and operational information is a multi-channel board system which is composed of an emergency phone signal processing module and an operational information processing module in the control box of elevator. In addition, the RMS(remote management server) systems based on the Web consist of a dial-up server and a remote monitoring server where manages the elevator's operating information, status records, and operational faults received via the proposed integrated and unified emergency call system in real time. So even if there's a catastrophic emergency, the proposed RMS systems shall ensure and maintain the safety of passengers inside the elevator. Also, remote control of the elevator by this system should be more efficient and secure. In near future, all elevator emergency call system need to support multifunctional capabilities to transmit operational data as well as phone calls for the safety of passengers. In addition, for safer elevators, it is necessary to improve them more efficiently by combining them with high-tech technologies such as the Internet of Things and artificial intelligence.

• Nuclear Engineering and Technology
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• 제54권1호
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• pp.269-274
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• 2022

An artificial neural network (ANN) that identifies radionuclides from low-count gamma spectra of a NaI scintillator is proposed. The ANN was trained and tested using simulated spectra. 14 target nuclides were considered corresponding to the requisite radionuclide library of a radionuclide identification device mentioned in IEC 62327-2017. The network shows an average identification accuracy of 98.63% on the validation dataset, with the gross counts in each spectrum N_c = 100~10000 and the signal to noise ratio SNR = 0.05-1. Most of the false predictions come from nuclides with low branching ratio and/or similar decay energies. If the N_c>1000 and SNR>0.3, which is defined as the minimum identifiable condition, the averaged identification accuracy is 99.87%. Even when the source and the detector are covered with lead bricks and the response function of the detector thus varies, the ANN which was trained using non-shielding spectra still shows high accuracy as long as the minimum identifiable condition is satisfied. Among all the considered nuclides, only the identification accuracy of ²³⁵U is seriously affected by the shielding. Identification of other nuclides shows high accuracy even the shielding condition is changed, which indicates that the ANN has good generalization performance.

• Smart Structures and Systems
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• 제29권1호
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.