• The KIPS Transactions:PartC
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• v.11C no.5
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• pp.613-620
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• 2004

Traditionally, simulation method was used to test and evaluate the performance of communication protocol or functional elements for mobile communication service. In this Paper, PCSsim(Personal Communication System Simulator) was realized that can evaluate and review the call process of mobile communication service or to predict its performance by using the object-oriented simulation platform. PCSsim can simulate the base station and mobile host by considering the user's mobility, call generation rate and call duration time. In this paper, based on the simulation, presented the simulation results of hand-off generation ratio according to call generation, user's moving speed and call duration time both in residence area and commercial area, and it was confirmed that the hand-off rates in simulation and actual service environment have similar features. PCSsim can be used in adjusting the characteristics of base station fellowing the dynamic hand-off buffering or the characteristics of user's call in the design stage, and also can be used in building new mobile communication network by reflecting the characteristics of region where the base station is located and the mobility of the user.

• Convergence Security Journal
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• v.12 no.6
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• pp.69-75
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• 2012

MANET(Mobile Ad-hoc Network) is target of many attacks because of dynamic topology and hop-by-hop data transmission method. In MANET, location setting of intrusion detection system is difficult and attack detection using information collected locally is more difficult. The amount of traffic grow, intrusion detection performance will be decreased. In this paper, MANET is composed of zone form and we used random projection technique which reduces dimension without loss of information in order to perform stable intrusion detection in even massive traffic. Global detection node is used to detect attacks which are difficult to detect using only local information. In the global detection node, attack detection is performed using received information from IDS agent and pattern of nodes. k-NN and ZBIDS were experimented to evaluate performance of the proposed technique in this paper. The superiority of performance was confirmed through the experience.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9B
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• pp.563-568
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• 2007

This paper proposes a routing establishment method for improving path stability in mobile ad-hoc networks. In mobile ad-hoc networks, the network topology is highly dynamic due to the node mobility unlike wired networks. Since the existing methods are based on the shortest path algorithm with the minimum hop count regardless of the path stability, it could lead to packet loss and path disconnection in mobile ad-hoc networks. In particular, if control packets and critical data are transmitted on the unstable path, it causes serious problems. Therefore, this paper proposes one approach in order to minimize packet loss and path disconnection by considering the node mobility. After the destination node receives multiple RREQ messages, it selects the stable path through the proposed MinMax algorithm according to the node speed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3168-3186
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• 2020

Automatic topic essay generation (TEG) is a controllable text generation task that aims to generate informative, diverse, and topic-consistent essays based on multiple topics. To make the generated essays of high quality, a reasonable method should consider both diversity and topic-consistency. Another essential issue is the intrinsic link of the topics, which contributes to making the essays closely surround the semantics of provided topics. However, it remains challenging for TEG to fill the semantic gap between source topic words and target output, and a more powerful model is needed to capture the semantics of given topics. To this end, we propose a pretraining-based contextual self-attention (PC-SAN) model that is built upon the seq2seq framework. For the encoder of our model, we employ a dynamic weight sum of layers from BERT to fully utilize the semantics of topics, which is of great help to fill the gap and improve the quality of the generated essays. In the decoding phase, we also transform the target-side contextual history information into the query layers to alleviate the lack of context in typical self-attention networks (SANs). Experimental results on large-scale paragraph-level Chinese corpora verify that our model is capable of generating diverse, topic-consistent text and essentially makes improvements as compare to strong baselines. Furthermore, extensive analysis validates the effectiveness of contextual embeddings from BERT and contextual history information in SANs.

• Smart Structures and Systems
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• v.25 no.5
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• pp.605-617
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• 2020

The existence of damages in structures causes changes in the physical properties by reducing the modal parameters. In this paper, we develop a two-stages approach based on normalized Modal Strain Energy Damage Indicator (nMSEDI) for quick applications to predict the location of damage. A two-dimensional IsoGeometric Analysis (2D-IGA), Machine Learning Algorithm (MLA) and optimization techniques are combined to create a new tool. In the first stage, we introduce a modified damage identification technique based on frequencies using nMSEDI to locate the potential of damaged elements. In the second stage, after eliminating the healthy elements, the damage index values from nMSEDI are considered as input in the damage quantification algorithm. The hybrid of Teaching-Learning-Based Optimization (TLBO) with Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) are used along with nMSEDI. The objective of TLBO is to estimate the parameters of PSO-ANN to find a good training based on actual damage and estimated damage. The IGA model is updated using experimental results based on stiffness and mass matrix using the difference between calculated and measured frequencies as objective function. The feasibility and efficiency of nMSEDI-PSO-ANN after finding the best parameters by TLBO are demonstrated through the comparison with nMSEDI-IGA for different scenarios. The result of the analyses indicates that the proposed approach can be used to determine correctly the severity of damage in beam structures.

• 한국태양에너지학회:학술대회논문집
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• 2012.03a
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• pp.419-424
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• 2012

This paper discusses the state-of-the-art techniques in real-time state estimation for the Smart Microgrids. The most popular method used in traditional power system state estimation is a Weighted Least Square(WLS) algorithm which is based on Maximum Likelihood(ML) estimation under the assumption of static system state being a set of deterministic variables. In this paper, we present a survey of dynamic state estimation techniques for Smart Microgrids based on Belief Propagation (BP) when the system state is a set of stochastic variables. The measurements are often too sparse to fulfill the system observability in the distribution network of microgrids. The BP algorithm calculates posterior distributions of the state variables for real-time sparse measurements. Smart Microgrids are modeled as a factor graph suitable for characterizing the linear correlations among the state variables. The state estimator performs the BP algorithm on the factor graph based the stochastic model. The factor graph model can integrate new models for solar and wind correlation. It provides the Smart Microgrids with a way of integrating the distributed renewable energy generation. Our study on Smart Microgrid state estimation can be extended to the estimation of unbalanced three phase distribution systems as well as the optimal placement of smart meters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.924-942
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• 2020

The facial expression is diverse and various among persons due to the impact of the psychology factor. Whilst the facial action is comparatively steady because of the fixedness of the anatomic structure. Therefore, to improve performance of the action unit recognition will facilitate the facial expression recognition and provide profound basis for the mental state analysis, etc. However, it still a challenge job and recognition accuracy rate is limited, because the muscle movements around the face are tiny and the facial actions are not obvious accordingly. Taking account of the moving of muscles impact each other when person express their emotion, we propose to make full use of co-occurrence relationship among action units (AUs) in this paper. Considering the dynamic characteristic of AUs as well, we adopt the 3D Convolutional Neural Network(3DCNN) as base framework and proposed to recognize multiple action units around brows, nose and mouth specially contributing in the emotion expression with putting their co-occurrence relationships as constrain. The experiments have been conducted on a typical public dataset CASME and its variant CASME2 dataset. The experiment results show that our proposed AU co-occurrence constraint 3DCNN based AU recognition approach outperforms current approaches and demonstrate the effectiveness of taking use of AUs relationship in AU recognition.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.818-819
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• 2015

PAL-XFEL 장치에 사용 할 고전압 펄스 모듈레이터 출력파워는 수 ${\mu}s$ 범위의 짧은 고전압(400 kV), 대전류(500 A) 펄스를 요구한다. 이러한 펄스파워를 얻기 위해서 PFN(Pulse Forming Network)에 에너지를 축적하고, 플라즈마 스위치인 싸이라트론을 통하여 에너지를 신속하게 클라이스트론 쪽으로 전달한다. 클라이스트론은 모듈레이터에서 공급하는 펄스 전원을 이용하여 RF를 증폭하는 대출력 고주파 증폭장치이다. 고전압 펄스 모듈레이터 제어기는 고속펄스 신호처리 모듈(Fast Pulse Signal Conditioning Module), PLC(Programmable Logic Controller)로 구성되어 있다. 고전압 펄스 모듈레이터에 사용하는 대용량 싸이라트론은 고전력을 스위칭 할 때 발생하는 스위칭 노이즈는 매우 크다. 이러한 노이즈는 모듈레이터의 출력 시그널인 빔 전압, 빔 전류, EOLC(End of Line Clipper) 전류, DC high voltage에 섞여 있으면서 신호 왜곡 및 제어장치의 고장을 유발시킨다. 이처럼 노이즈가 많이 포함되어 있는 아닐로그 신호를 깨끗한 신호(a clean signal)로 바꾸어주는 노이즈 필터링 장치인 고속펄스 신호처리 모듈을 제작하여 실험한 결과를 알아보고 모듈레이터 인터록 시스템인 PLC에서 Dynamic Interlock의 응답시간을 빠르게 하기위한 회로 수정에 대한 결과에 관하여 기술하고자 한다.

• Smart Structures and Systems
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• v.26 no.5
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• pp.559-573
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• 2020

One of the powerful data management tools is Building Information Modeling (BIM) which operates through obtaining, recalling, sharing, sorting and sorting data and supplying a digital environment of them. Employing SHM, a BIM in monitoring systems, would be an efficient method to address their data management problems and consequently optimize the economic aspects of buildings. The recording of SHM data is an effective way for engineers, facility managers and owners which make the BIM dynamic through the provision of updated information regarding the occurring state and health of different sections of the building. On the other hand, digital transformation is a continuous challenge in construction. In a cloud-based BIM platform, environmental and localization data are integrated which shape the Internet-of-Things (IoT) method. In order to improve work productivity, living comfort, and entertainment, the IoT has been growingly utilized in several products (such as wearables, smart homes). However, investigations confronting the integration of these two technologies (BIM and IoT) remain inadequate and solely focus upon the automatic transmission of sensor information to BIM models. Therefore, in this composition, the use of BIM based on SHM and IOT is reviewed and the economic application is considered.

• The Journal of the Korea Contents Association
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• v.11 no.2
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• pp.142-151
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• 2011

All medical information over sensor networks need to transmit and process securely in the u-Health services. The reliability of transmission between u-Health medical sensor devices and gateway is very important issue. When the user moves to other place with u-Health devices, its signal strength is going down and is far from the coverage of gateway. In this case, Malicious user can be carried out an intrusion under the situation. And also rogue gateway can be tried to steal medical information. Therefore, it needs mutual authentication between sensor devices and gateway. In this paper, we design a mutual authentication protocol which divided sessions from an authenticated session are updated periodically. And in order to reduce the traffic overhead for session authentication, we also introduce dynamic session management according to sampling rate of medical sensor type. In order to verify this, we implemented the programs for the test-bed, and got an overall success from three types of experiment.