• Proceedings of the Korean Information Science Society Conference
• /
• 2007.06a
• /
• pp.194-195
• /
• 2007

• Proceedings of the Korean Information Science Society Conference
• /
• 2008.06c
• /
• pp.274-278
• /
• 2008

인터넷 사용의 증가로 인터넷이 사용자의 의견 표출의 장이 되었다. 이에 따라 사용자의 견해나 의견을 자동으로 인식 및 추출하는 방법들이 연구되어 오고 있다. 의견 분석 (opinion analysis)은 한국어에서는 아직 연구가 활발히 되지 않는 분야로 의견 분석에 필요한 자원 및 도구들이 미비하다. 본 논문은 다른 언어권에서 구축된 주관성 어휘를 사전을 이용해 번역하는 방법을 제시하고 문제점 및 개선방법과 향후 연구방향에 관하여 논의한다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2010.06c
• /
• pp.291-294
• /
• 2010

의견의 주체를 찾는 일은 의견 분석의 결과를 활용 하는데 있어 필수적인 분야이다. 본 논문은 발안자를 찾는 시스템의 성능을 높이기 위해 이전논문에 제안하였던 단어에 의견주체의 후보로서의 점수를 부여하는 방법을 개선하였고 미등록어 문제를 해결하기 위해 taxonomy에 의존하여 기존단어의 점수를 이용하는 방법을 제안하였다. 본 논문에서 제안한 방법은 Baseline과 비교하여 F1값이 18.9% 증가하였다.

• International Journal of Computer Science & Network Security
• /
• v.23 no.4
• /
• pp.95-102
• /
• 2023

The emergence of Internet of Things (IoT) into our daily lives has grown rapidly. It's been integrated to our homes, cars, and cities, increasing the intelligence of devices involved in communications. Enormous amount of data is exchanged over smart devices through the internet, which raises security concerns in regards of privacy evasion. This paper is focused on the forensics and intrusion detection on one of the most common protocols in IoT environments, especially smart home environments, which is the Message Queuing Telemetry Transport (MQTT) protocol. The paper covers general IoT infrastructure, MQTT protocol and attacks conducted on it, and multiple network forensics frameworks in smart homes. Furthermore, a machine learning model is developed and tested to detect several types of attacks in an IoT network. A forensics tool (MQTTracker) is proposed to contribute to the investigation of MQTT protocol in order to provide a safer technological future in the warmth of people's homes. The MQTT-IOT-IDS2020 dataset is used to train the machine learning model. In addition, different attack detection algorithms are compared to ensure the suitable algorithm is chosen to perform accurate classification of attacks within MQTT traffic.

• Journal of electromagnetic engineering and science
• /
• v.6 no.4
• /
• pp.235-243
• /
• 2006

In this paper, the fractal shape is applied to microstrip band pass filters and integrated on a high-resistivity Si substrate to solve conventional $2^{nd}$ harmonic problem. Conventional microstrip coupled line filters are popular in RF front ends, because they can be easily fabricated and integrated with other RF components. However, they typically have large second harmonics that can cause unwanted interference in interested frequency bands. Without any additional filters, the proposed Koch shape filters have suppressed the $2^{nd}$ harmonics by about -40 dB, so they can be used in systems such as direct conversion receiver with stringent harmonic suppression requirements.

• Journal of Information Processing Systems
• /
• v.16 no.5
• /
• pp.1145-1157
• /
• 2020

A convolution neural networks (CNNs) has demonstrated outstanding performance compared to other algorithms in the field of face recognition. Regarding the over-fitting problem of CNN, researchers have proposed a residual network to ease the training for recognition accuracy improvement. In this study, a novel face recognition model based on game theory for call-over in the classroom was proposed. In the proposed scheme, an image with multiple faces was used as input, and the residual network identified each face with a confidence score to form a list of student identities. Face tracking of the same identity or low confidence were determined to be the optimisation objective, with the game participants set formed from the student identity list. Game theory optimises the authentication strategy according to the confidence value and identity set to improve recognition accuracy. We observed that there exists an optimal mapping relation between face and identity to avoid multiple faces associated with one identity in the proposed scheme and that the proposed game-based scheme can reduce the error rate, as compared to the existing schemes with deeper neural network.

• Proceedings of the Korean Powder Metallurgy Institute Conference
• /
• 2006.09a
• /
• pp.563-564
• /
• 2006

The effect of different cooling rate on the structure and mechanical properties of Fe-3%Mn-(Cr)-(Mo)-0.3%C steels is described. Pre-alloyed Astaloy CrM and CrL, ferromanganese and graphite were used as the starting powders. Following pressing in a rigid die, compacts were sintered at $1120^{\circ}C$ and $1250^{\circ}C$ in $H_2/N_2$ atmospheres and cooled with cooling rates $1.4^{\circ}C/min$ and $6.5^{\circ}C/min$. Convective cooled specimens were subsequently tempered at $200^{\circ}C$ for 60 and 240 minutes.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.3
• /
• pp.486-489
• /
• 2021

Recently, the demand for the use of personal mobility vehicles, such as an electric kickboard, is increasing explosively because of its high portability and usability. However, the number of traffic accidents caused by personal mobility vehicles has also increased rapidly in recent years. To address the issues regarding the driver's safety, we propose a novel approach that can monitor context information around personal mobility vehicles using deep learning-based object detection and smartphone captured videos. In the proposed framework, a smartphone is attached to a personal mobility device and a front or rear view is recorded to detect an approaching object that may affect the driver's safety. Through the detection results using YOLOv5 model, we report the preliminary results and validated the feasibility of the proposed approach.

• Proceedings of the Korean Information Science Society Conference
• /
• 2008.06c
• /
• pp.268-273
• /
• 2008

의견(Opinion) 분석은 도전적인 분야로 언어 자원 구축, 문서의 Sentiment 분류, 문장 내의 의견 어구 추출 등의 다양한 문제를 다룬다. 이 중 의견 어구 추출문제는 단순히 문장이나 문서 단위로 분류하는 수준을 뛰어 넘는 문장 내 의견 어구를 추출하는 문제로 최근 많은 관심을 받고 있는 연구 주제이다. 그러나 의견 어구 추출에 대한 기존 연구는 문장 내 의견 어구부분이 태깅(tagging)된 학습 데이터와 의견 어휘 자원을 이용한 지도(Supervised)학습을 이용한 접근이 대부분으로 실제 적용 상의 한계를 갖는다. 본 논문은 문장 내 의견 어구 부분이 태깅된 학습 데이터와 의견 어휘 자원이 없는 환경에서도 문장단위의 극성 정보를 이용하여 의견 어구를 추출하는 부분 지도(Semi-Supervised)학습 장법을 제안한다. 본 논문의 방법은 Baseline에 비하여 정확률(Precision)은 33%, F-Measure는 14% 가량 높은 성능을 냈다.

• Annual Conference on Human and Language Technology
• /
• 2018.10a
• /
• pp.623-626
• /
• 2018

한국어 학습에 대한 관심이 전 세계적으로 높아짐에 따라 한국어 학습을 위한 다양한 프로그램들이 등장하고 있다. 한국어가 모국어가 아닌 외국인들의 한국어 학습을 위해서는 단어 학습이 기초가 되어야 하며, 단어 학습에서는 다양한 예문들이 필수적이다. 기존의 학습 시스템에서는 말뭉치에 있는 문장들을 예문으로 제시하는 기능을 제공하지만, 이 경우 한정적이고 반복된 문장만을 제공하는 문제를 가진다. 본 논문에서는 사용자가 학습하고자 하는 단어를 입력하면 해당 단어 단어를 포함하는 한국어 문장을 자동 생성하여 제공하는 시스템을 제안한다. 시스템에서는 언어 모델의 제어가 비교적 쉬운 마르코프체인을 활용한다.