• 한국정보과학회논문지:정보통신
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• 제31권4호
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• pp.393-404
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• 2004

최근 트랜스포트 계층에서 이동성을 지원하기 위한 방안으로 mSCTP가 제안되었다. mSCTP는 SCTP의 멀티호밍 특성을 기반으로 하며, 노드의 이동성을 지원하기 위해 SCTP 커넥션의 종단점에 매핑되는 IP 주소를 동적으로 추가ㆍ삭제하는 기능을 이용한다. 본 논문에서는 mSCTP의 성능 향상을 위해 2계층 정보를 이용하여 새로운 IP 주소를 추가하거나 이전 IP 주소를 삭제하는 시점을 결정하는 방안과 이동 노드에서 데이타 전송 경로 변경을 결정하는 방안을 제안하였다. 또한, 새로운 데이타 경로를 획득하는 시간이 길어지는 경우 핸드오버 지연을 줄이기 위한 방안을 제안하였다 시뮬레이션을 통하여 제안하는 방안이 네트워크 계층의 이동성 지원과 대등한 성능을 보임을 확인하였고, 이동 노드의 속도가 빠를 때는 네트워크 계층에서의 이동성 지원 방안보다 더 나은 성능을 제공함을 볼 수 있었다.

• Geomechanics and Engineering
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• 제30권1호
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• pp.75-91
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• 2022

This paper aims to show how to use several Machine Learning (ML) methods to estimate the TBM penetration rate systematically (TBM-PR). To this end, 1125 datasets including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), punch slope index (PSI), distance between the planes of weakness (DPW), orientation of discontinuities (alpha angle-α), rock fracture class (RFC), and actual/measured TBM-PRs were established. To evaluate the ML methods' ability to perform, the 5-fold cross-validation was taken into consideration. Eventually, comparing the ML outcomes and the TBM monitoring data indicated that the ML methods have a very good potential ability in the prediction of TBM-PR. However, the long short-term memory model with a correlation coefficient of 0.9932 and a route mean square error of 2.68E-6 outperformed the remaining six ML algorithms. The backward selection method showed that PSI and RFC were more and less significant parameters on the TBM-PR compared to the others.

• 한국멀티미디어학회논문지
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• 제25권2호
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• pp.382-389
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• 2022

In China, E-commerce live broadcast has emerged as the most popular and innovative online shopping form for today's consumers, and its "real-time interactive" feature can compensate for the communication delays of general online shopping. Based on the author's previous research it has been demonstrated that, in the E-commerce live broadcast environment, Internet Word of Mouth (IWOM) has become an important reference for consumers when making purchases. In this paper, we reconstructed the "IWOM-Purchase Intentions" model and use interaction (Auchor-Audience and Audience-Audience) as a mediating variable to empirically investigate the impact of IWOM on purchase intentions in E-commerce live broadcast. The data were collected through a questionnaire survey of individuals who had experience in E-commerce live broadcast and 250 valid data were obtained and analyzed by SPSS21.0. The results show that: the interaction (Auchor-Audience) acts as a mediator between IWOM (strength of relationship; word-of-mouth quality and word-of-mouth timeliness) and purchase intention; And the interaction (Audience-Audience) acts as a mediator between word-of-mouth timeliness on purchase intention, but has no significant mediation on the impact on the strength of relationship and word-of-mouth quality to purchase intention. On this basis, recommendations are made for the implementation of IWOM marketing strategies for E-commerce live broadcast platforms and anchors.

• 한국멀티미디어학회논문지
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• 제19권6호
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• pp.1074-1088
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• 2016

Successful Visual Story Telling(VST) of desire is a crucial key for the success of animation because desire is the leading power of story development of animation. An analysis of the desire of VST using the top 5 successful American feature film animations is carried out. Totally, 147 desire shots are extracted by using the proposed Objective Selection of Desire Shots(OSDS) method based on the theory of Makee's conflict and desire pursuing modeling, Maslow's 20 desire types, Greimas's actant model, and the 17 narrative process classification. In addition to them, the 5 Beat(5B) model of a scene is proposed. Five image specialists have evaluated VST of the selected 147 desire shots. For each shot, the desire type among the 20 desires and the strength are obtained. Among them, the top 3 desires(affiliation, achievement, and nurturance) appearing 51.8% are analyzed. The composition elements of shots affecting the desire type and the strength have found. These can be used for better VST of preproduction and production of animation.

• Journal of Information Processing Systems
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• 제13권2호
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• pp.400-416
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• 2017

Music emotion is an important component in the field of music information retrieval and computational musicology. This paper proposes an approach for automatic emotion classification, based on rough set (RS) theory. In the proposed approach, four different sets of music features are extracted, representing dynamics, rhythm, spectral, and harmony. From the features, five different statistical parameters are considered as attributes, including up to the $4^{th}$ order central moments of each feature, and covariance components of mutual ones. The large number of attributes is controlled by RS-based approach, in which superfluous features are removed, to obtain indispensable ones. In addition, RS-based approach makes it possible to visualize which attributes play a significant role in the generated rules, and also determine the strength of each rule for classification. The experiments have been performed to find out which audio features and which of the different statistical parameters derived from them are important for emotion classification. Also, the resulting indispensable attributes and the usefulness of covariance components have been discussed. The overall classification accuracy with all statistical parameters has recorded comparatively better than currently existing methods on a pair of datasets.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2005년도 공동추계학술대회
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• pp.516-525
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• 2005

Case-based reasoning (CBR) has been widely used in various areas due to its convenience and strength in complex problem solving. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However, designing a good matching and retrieval mechanism for CBR systems is still a controversial research issue. Most prior studies have tried to optimize the weights of the features or selection process of appropriate instances. But, these approaches have been performed independently until now. Simultaneous optimization of these components may lead to better performance than in naive models. In particular, there have been few attempts to simultaneously optimize the weight of the features and selection of the instances for CBR. Here we suggest a simultaneous optimization model of these components using a genetic algorithm (GA). We apply it to a customer classification model which utilizes demographic characteristics of customers as inputs to predict their buying behavior for a specific product. Experimental results show that simultaneously optimized CBR may improve the classification accuracy and outperform various optimized models of CBR as well as other classification models including logistic regression, multiple discriminant analysis, artificial neural networks and support vector machines.

• 전자공학회논문지
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• 제52권7호
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• pp.86-92
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• 2015

본 논문에서는 지역적인 에지의 방향 정보와 반응 크기, 주변 화소와의 밝기값 차이를 LDP 코드에 포함함으로써 얼굴 표정 인식률을 향상시킨다. 기존 LDP 코드를 사용하면 LBP에 비해서 영상의 밝기 변화에 덜 민감하고 잡음에 강한 장점을 가진다. 하지만, 밝기 변화가 없는 매끄러운 영역의 정보를 표현하기 어렵고, 배경에 얼굴과 유사한 에지 패턴이 존재하는 경우에는 인식률이 저하되는 문제점이 있다. 따라서 에지 방향 정보를 기반으로 에지 강도 및 밝기값을 추가할 수 있도록 LDP 코드를 개선하고, 인식률을 측정한다.

• 전기학회논문지P
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• 제67권1호
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• pp.9-14
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• 2018

In this paper, we introduce an AES-based security chip for the embedded system of Internet of Things(IoT). We used Verilog HDL to implement the AES algorithm in FPGA. The designed AES module creates 128-bit cipher by encrypting 128-bit plain text and vice versa. RTL simulations are performed to verify the AES function and the theory is compared to the results. An FPGA emulation was also performed with 40 types of test sequences using two Altera DE0-Nano-SoC boards. To evaluate the performance of security algorithms, we compared them with AES implemented by software. The processing cycle per data unit of hardware implementation is 3.9 to 7.7 times faster than software implementation. However, there is a possibility that the processing speed grow slower due to the feature of the hardware design. This can be solved by using a pipelined scheme that divides the propagation delay time or by using an ASIC design method. In addition to the AES algorithm designed in this paper, various algorithms such as IPSec can be implemented in hardware. If hardware IP design is set in advance, future IoT applications will be able to improve security strength without time difficulties.

• Journal of Information Processing Systems
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• 제16권3호
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• pp.541-556
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• 2020

Wireless networks have become integral to society as they provide mobility and scalability advantages. However, their disadvantage is that they cannot control the media, which makes them vulnerable to various types of attacks. One example of such attacks is the evil twin access point (AP) attack, in which an authorized AP is impersonated by mimicking its service set identifier (SSID) and media access control (MAC) address. Evil twin APs are a major source of deception in wireless networks, facilitating message forgery and eavesdropping. Hence, it is necessary to detect them rapidly. To this end, numerous methods using clock skew have been proposed for evil twin AP detection. However, clock skew is difficult to calculate precisely because wireless networks are vulnerable to noise. This paper proposes an evil twin AP detection method that uses a multiple-feature-based machine learning classification algorithm. The features used in the proposed method are clock skew, channel, received signal strength, and duration. The results of experiments conducted indicate that the proposed method has an evil twin AP detection accuracy of 100% using the random forest algorithm.

• 한국지리정보학회지
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• 제11권4호
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• pp.64-75
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• 2008

지반조사자료 관리를 위한 현재의 DB시스템은 점으로 표현되는 시추조사에 한정되었기 때문에 여타 GIS데이터와의 활용이 제한적이었다. 시추공 자료를 이용한 보간으로 지하의 공간적 분포특성을 찾고자 하는 연구들이 있었지만, GIS와의 상호운영이나 지반공학적 특성을 고려치 못하여 실무적으로 활용하기에는 어려웠다. 본 연구에서는 지반정보DB에서 필요한 지반공학 자료를 추출하여 지하공간정보 모델을 생성하였다. 지반정보 클러스터링 프로그램(GEOCL)을 개발하여 시추공구성(비), 지층분류, 지반강도에 대한 클러스터를 생성하였다. 생성된 클러스터의 공간적 분포를 고려하여 지구통계기법의 하나인 권역 크리깅(권역 크리깅)으로 보간을 수행하였다. 최종적으로 수치표고모형과 통합하여 지하공간정보 모델을 생성하고, 지하공간정보 가시화 프로그램(SSIVIEW)를 통해 3차원으로 가시화하였다. 개발된 지하공간정보 모델은 건설공사의 지반해석과 기초설계에 적극 활용되리라 기대된다.