• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2764-2782
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• 2021

Existing city-level boundary nodes identification methods need to locate all IP addresses on the path to differentiate which IP is the boundary node. However, these methods are susceptible to time-delay, the accuracy of location information and other factors, and the resource consumption of locating all IPes is tremendous. To improve the recognition rate and reduce the locating cost, this paper proposes an algorithm for city-level boundary node identification based on bidirectional approaching. Different from the existing methods based on time-delay information and location results, the proposed algorithm uses topological analysis to construct a set of candidate boundary nodes and then identifies the boundary nodes. The proposed algorithm can identify the boundary of the target city network without high-precision location information and dramatically reduces resource consumption compared with the traditional algorithm. Meanwhile, it can label some errors in the existing IP address database. Based on 45,182,326 measurement results from Zhengzhou, Chengdu and Hangzhou in China and New York, Los Angeles and Dallas in the United States, the experimental results show that: The algorithm can accurately identify the city boundary nodes using only 20.33% location resources, and more than 80.29% of the boundary nodes can be mined with a precision of more than 70.73%.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.206-212
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• 2022

The main purpose of the article is to study the peculiarities of the formation of information support mechanisms for economic growth and security under the influence of COVID-19. The cyclical nature of economic growth is a well-established and proven fact. In this context, one of the main tasks of the state is to develop measures to mitigate the impact of economic crises on the entire economic system of the state, individual economic entities, as well as to introduce anti-crisis mechanisms and tools to support the economy. When the cyclical nature of economic crises coincides with destabilizing processes in society, such as natural disasters, military actions or epidemics, the role of the state and adequate information support for economic growth is sharply actualized. As a result, an analysis was made of the main aspects of information support for economic growth and security in the context of COVID-19.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.2
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• pp.129-140
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• 2023

Autonomous driving systems are likely to be operated in various complex environments. However, the well-known integrated Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS), which is currently the major source for absolute position information, still has difficulties in accurate positioning in harsh signal environments such as urban canyons. To overcome these difficulties, integrated Visual/Inertial/GNSS (VIG) navigation systems have been extensively studied in various areas. Recently, a Compressed-State Constraint Kalman Filter (CSCKF)-based VIG navigation system (CSCKF-VIG) using a monocular camera, an Inertial Measurement Unit (IMU), and GNSS receivers has been studied with the aim of providing robust and accurate position information in urban areas. For this new filter-based navigation system, on the basis of time-propagation measurement fusion theory, unnecessary camera states are not required in the system state. This paper presents a performance evaluation of the CSCKF-VIG system compared to other conventional navigation systems. First, the CSCKF-VIG is introduced in detail compared to the well-known Multi-State Constraint Kalman Filter (MSCKF). The CSCKF-VIG system is then evaluated by a field experiment in different GNSS availability situations. The results show that accuracy is improved in the GNSS-degraded environment compared to that of the conventional systems.

• Proceedings of the KIEE Conference
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• 2004.10a
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• pp.179-181
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• 2004

This paper is proposed an adaptive fuzzy-neural network(A-FNN) controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed estimation of induction motor using A closed-loop state observer. The rotor position is calculated through the stator flux position and an estimated flux value of rotation reference frame. A closed-loop state observer is implemented to compute the speed feedback signal. The results of analysis prove that the proposed control system has strong robustness to rotor parameter variation, and has good steady-state accuracy and transitory response.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.12
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• pp.1933-1939
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• 1990

In this paper, we proposed an algorithm which used backtracking method to get time information, and it be modelled DMS (Dynamic Multisection) by feature vectors and time information whic are represented to similiar feature in word patterns spoken during continuous time domain, for Korean Speech recognition by independent speaker using DMS. Each state of model is represented time sequence, and have time information and feature vector. Typical feature vector is determined as the feature vector of each state to minimize the distance between word patterns. DDD Area names are selected as recognition wcabulary and 12th LPC cepstrum coefficients are used as the feature parameter. State of model is made 8 multisection and is used 0.2 as weight for time information. Through the experiment result, recognition rate by DMS model is 94.8%, and it is shown that this is better than recognition rate (89.3%) by MSVQ(Multisection Vector Quantization) method.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.126-128
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• 2012

소프트웨어 시스템의 안전성을 보장하기 위해 여러 안전성 분석 기법들이 사용되고 있으며, 안전성 분석의 결과인 안전성 요구사항을 시스템이 만족하고 있는지 확인하는지 확인하는 안전성 평가과정이 수행되고 있다. 안전성 평가는 많은 시간과 비용이 드는 문제점을 가지고 있다. 본 논문은 안전성 평가에 드는 시간과 비용을 줄이기 위해 테스트 케이스를 이용하여 안전성 요구사항을 소프트웨어 개발의 가장 기본적인 검증기법인 테스팅을 이용하여 시스템이 만족하는지 확인하는 방법을 제안하고 핸드폰의 카메라 컨트롤러 예제를 이용한 사례 연구를 진행하였으며 이를 지원 위한 도구인 TC2SMV를 개발하였다. TC2SMV는 UML의 state chart diagram에서 생성된 test case들을 SMV 입력 프로그램으로 자동으로 변환하여 사용자가 SMV 모델체킹을 수행할 수 있는 환경을 제공한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5360-5376
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• 2017

In this paper, we study the cross-layer design for the AMC/HARQ-based wireless networks, and propose a new dynamic transmission-mode selection scheme to improve system spectrum efficiency. In the proposed scheme, dynamic thresholds for transmission-mode selection in each packet transmission and retransmission are jointly designed under the constraint of the overall packet error rate. Comparing with the existing schemes, the proposed scheme is inclined to apply higher modulation order at the first several (re)transmissions, which corresponds to higher-rate transmission modes thus higher average system spectrum efficiency. We also extend the cross-layer design to MIMO (Multi-input Multi-output) communication scenarios. Numerical results show that the proposed new dynamic transmission-mode selection scheme generally achieves higher average spectrum efficiency than the conventional and existing cross-layer design.

• The Journal of Information Systems
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• v.29 no.1
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• pp.181-199
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• 2020

Purpose The purpose of this study is to analyze the current state of grounded theory methodology in Korea information systems studies and to suggest its application strategies. Design/methodology/approach After reviewing previous studies, this study reviewed 16 papers which adopted grounded theory methodology and analyzed these papers by two ways, research contents and methods adopted from grounded theory methodology: Main characteristics in grounded theory methodology are selected as main criteria in analysis such as data collection method, constant comparison, software use, coding ways, suggested model, proposition suggestion etc., while subject, theory/practice orientation, and role of prior knowledge are included in research contents. Findings Based on the review and analysis, this paper suggested four guidelines for adopting grounded theory methodology to information systems research in Korea: First, division of research methodology into stages. Second, explicit documentation of research process. Third, pursuit of diversity in research topics. Fourth, strengthening scale up and theoretical integration.

• Journal of Information Processing Systems
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• v.7 no.1
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• pp.159-172
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• 2011

A designated verifier signature is a special type of digital signature, which convinces a designated verifier that she has signed a message in such a way that the designated verifier cannot transfer the signature to a third party. A strong designated verifier signature scheme enhances the privacy of the signer such that no one but the designated verifier can verify the signer's signatures. In this paper we present two generic frame works for constructing strong designated verifier signature schemes from any secure ring signature scheme and any deniable one-pass authenticated key exchange protocol, respectively. Compared with similar protocols, the instantiations of our construction achieve improved efficiency.

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.96-102
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• 2022

We aim to build predictive models for Airbnb's prices using a GPU-accelerated RAPIDS in a big data cluster. The Airbnb Listings datasets are used for the predictive analysis. Several machine-learning algorithms have been adopted to build models that predict the price of Airbnb listings. We compare the results of traditional and big data approaches to machine learning for price prediction and discuss the performance of the models. We built big data models using Databricks Spark Cluster, a distributed parallel computing system. Furthermore, we implemented models using multiple GPUs using RAPIDS in the spark cluster. The model was developed using the XGBoost algorithm, whereas other models were developed using traditional central processing unit (CPU)-based algorithms. This study compared all models in terms of accuracy metrics and computing time. We observed that the XGBoost model with RAPIDS using GPUs had the highest accuracy and computing time.