농촌활성화를 위한 전라남도 구례군의 농촌공간특성 및 모델 연구

이민석,임효원,이세연,이지인,윤세은 한국농촌건축학회 2024 농촌건축 : 한국농촌건축학회논문집 Vol.26 No.1

This study aimed to suggest the direction of sustainable rural development through the analysis of existing rural revitalization policies and rural status. This study also aimed to explore ways to revitalize the agricultural-oriented rural economy and improve the settlement environment in consideration of the characteristics of rural spaces. Based on the results, we created a regional crop-specific agricultural space, planned concentration, farmland maintenance, and joint agricultural facilities to secure agricultural competitiveness. It also plans a walking-oriented settlement environment to create a safe and pleasant rural village. Finally, by overcoming the limitations of the existing land-use plan, a sub-concept rural spatial plan reflecting the characteristics of rural areas was proposed, and the rural revitalization plan was studied.

실시간 시스템에서의 진보된 프로세서 응용 ( Real -Time Systems and Advanced Processors )

이민석 대한전자공학회 1995 대한전자공학회 학술대회 Vol.1995 No.11

지식 기반 시뮬레이터를 위한 개발 환경 ( A Development Environment for a Knowledge-Based Simulator )

이민석,우영운,이종현,박충식,김재희,주재우,조동래 대한전자공학회 1995 대한전자공학회 학술대회 Vol.1995 No.7

TCP / IP 구현과 성능

이민석 대한전자공학회 1998 대한전자공학회 학술대회 Vol.1998 No.1

유기금속 화학증착에 의한 양자줄의 구조적 , 광학적 특성

이민석,김용,김무성,박용주,민석기,김영덕 대한전자공학회 1994 대한전자공학회 학술대회 Vol.1994 No.1

독일의 도시공간계획체계에 관한 연구

이민석 대한건축학회지회연합회 2017 대한건축학회연합논문집 Vol.19 No.1

우리나라의 도시재생에 관한 사업과 정책이 있지만, 획일적인 계획과 비체계적인 관리를 통해서 개별사업위주의 시행되고있어 많은 계획적, 사회적인 갈등을 야기하고 있다. 도시재생은 도시가 가지고 있는 구조, 형태에 따른 각각의 특성을 지닌 지역에 획일적인 해결방법(고층화, 고밀화, 경계내에서의 도시문제 해결)등은 또 다른 문제점을 야기시키고 있다. 본 연구의 목적은 미래지향적인 도시와 건축의 관리를 위한 해결방법의 일환으로 오랜 시행착오를 거쳐 도시와 건축을 이루어온 독일의 사례를 통해서 향후 우리의 도시재생 계획의 방향과 방법론을 모색해보고자 함이다. 도시와 건축계획은 개발과 보전 정비와 관리의 두갈림길에서, 현실적으로 어떻게 해석하게 되는 중요한 요소이다. 도시기본계획은 도면부재, 텍스트화 되어진 공간구조의 개념은 현실적으로 실행가능하지 못한 개념계획으로만 작동하고 있다. 이에 독일에서의 도시공간계획체계를 분석함으로써 미래도시 및 건축계획을 수립시 필요한 내용과 방향을 어떻게 설정하고 있는지, 도시공간을 어떻게 규제하고 정비, 보전 관리하고 있는 도시공간체계의 제도 및 방법을 살펴봄으로써 향후 미래도시공간을 한 종합적, 체계적으로 관리할 수 있는 방안 모색에 도움이 될 수 있을 것으로 판단된다. Although urban related projects and policies are available in Korea, projects are being implemented more onto the individual project basis through monolithic planning and non-systematic management which causes many social conflicts. Urban regeneration has provided single resolution (high-rise, high-density, and resolution of urban problems within boundaries) to all different areas regardless of each city’s structure or formation attribute and it causes another type of issue. As one of the resolution for future-oriented city and architectural management, this study is to investigate the direction and methodology of our urban regeneration plan through the case of Germany which has made urban and architectural works on the basis of long trial and error. Urban and architectural planning is an important factor to interpret realistically between development and maintenance/management. The basic plan of the city works only as a conceptual plan that is not practically feasible because of the absence of drawings and the presence of textualized spatial structure. In this paper, we analyze the urban spatial planning system in Germany to find out how to set up the details and directions needed to establish future urban and architectural plans and also examine the system and method of urban spatial system that regulates, maintains urban space. This would help us to find a way to manage future urban space in a comprehensive and systematic way.

공대공 전투 모의를 위한 규칙기반 AI 교전 모델 개발

이민석,오지현,김천영,배정호,김용덕,지철규 한국군사과학기술학회 2022 한국군사과학기술학회지 Vol.25 No.6

Since the concept of Manned-UnManned Teaming(MUM-T) and Unmanned Aircraft System(UAS) can efficiently respond to rapidly changing battle space, many studies are being conducted as key components of the mosaic warfare environment. In this paper, we propose a rule-based AI engagement model based on Basic Fighter Maneuver(BFM) capable of Within-Visual-Range(WVR) air-to-air combat and a simulation environment in which human pilots can participate. In order to develop a rule-based AI engagement model that can pilot a fighter with a 6-DOF dynamics model, tactical manuals and human pilot experience were configured as knowledge specifications and modeled as a behavior tree structure. Based on this, we improved the shortcomings of existing air combat models. The proposed model not only showed a 100 % winning rate in engagement with human pilots, but also visualized decision-making processes such as tactical situations and maneuvering behaviors in real time. We expect that the results of this research will serve as a basis for development of various AI-based engagement models and simulators for human pilot training and embedded software test platform for fighter.

문장 분류를 위한 정보 이득 및 유사도에 따른 단어 제거와 선택적 단어 임베딩 방안

이민석,양석우,이홍주 한국지능정보시스템학회 2019 지능정보연구 Vol.25 No.4

Dimensionality reduction is one of the methods to handle big data in text mining. For dimensionality reduction, we should consider the density of data, which has a significant influence on the performance of sentence classification. It requires lots of computations for data of higher dimensions. Eventually, it can cause lots of computational cost and overfitting in the model. Thus, the dimension reduction process is necessary to improve the performance of the model. Diverse methods have been proposed from only lessening the noise of data like misspelling or informal text to including semantic and syntactic information. On top of it, the expression and selection of the text features have impacts on the performance of the classifier for sentence classification, which is one of the fields of Natural Language Processing. The common goal of dimension reduction is to find latent space that is representative of raw data from observation space. Existing methods utilize various algorithms for dimensionality reduction, such as feature extraction and feature selection. In addition to these algorithms, word embeddings, learning low-dimensional vector space representations of words, that can capture semantic and syntactic information from data are also utilized. For improving performance, recent studies have suggested methods that the word dictionary is modified according to the positive and negative score of pre-defined words. The basic idea of this study is that similar words have similar vector representations. Once the feature selection algorithm selects the words that are not important, we thought the words that are similar to the selected words also have no impacts on sentence classification. This study proposes two ways to achieve more accurate classification that conduct selective word elimination under specific regulations and construct word embedding based on Word2Vec embedding. To select words having low importance from the text, we use information gain algorithm to measure the importance and cosine similarity to search for similar words. First, we eliminate words that have comparatively low information gain values from the raw text and form word embedding. Second, we select words additionally that are similar to the words that have a low level of information gain values and make word embedding. In the end, these filtered text and word embedding apply to the deep learning models; Convolutional Neural Network and Attention-Based Bidirectional LSTM. This study uses customer reviews on Kindle in Amazon.com, IMDB, and Yelp as datasets, and classify each data using the deep learning models. The reviews got more than five helpful votes, and the ratio of helpful votes was over 70% classified as helpful reviews. Also, Yelp only shows the number of helpful votes. We extracted 100,000 reviews which got more than five helpful votes using a random sampling method among 750,000 reviews. The minimal preprocessing was executed to each dataset, such as removing numbers and special characters from text data. To evaluate the proposed methods, we compared the performances of Word2Vec and GloVe word embeddings, which used all the words. We showed that one of the proposed methods is better than the embeddings with all the words. By removing unimportant words, we can get better performance. However, if we removed too many words, it showed that the performance was lowered. For future research, it is required to consider diverse ways of preprocessing and the in-depth analysis for the co-occurrence of words to measure similarity values among words. Also, we only applied the proposed method with Word2Vec. Other embedding methods such as GloVe, fastText, ELMo can be applied with the proposed methods, and it is possible to identify the possible combinations between word embedding methods and elimination methods. 텍스트 데이터가 특정 범주에 속하는지 판별하는 문장 분류에서, 문장의 특징을 어떻게 표현하고 어떤 특징을 선택할 것인가는 분류기의 성능에 많은 영향을 미친다. 특징 선택의 목적은 차원을 축소하여도 데이터를 잘설명할 수 있는 방안을 찾아내는 것이다. 다양한 방법이 제시되어 왔으며 Fisher Score나 정보 이득(Information Gain) 알고리즘 등을 통해 특징을 선택 하거나 문맥의 의미와 통사론적 정보를 가지는 Word2Vec 모델로 학습된 단어들을 벡터로 표현하여 차원을 축소하는 방안이 활발하게 연구되었다. 사전에 정의된 단어의 긍정 및 부정 점수에 따라 단어의 임베딩을 수정하는 방법 또한 시도하였다. 본 연구는 문장 분류 문제에 대해 선택적 단어 제거를 수행하고 임베딩을 적용하여 문장 분류 정확도를 향상시키는 방안을 제안한다. 텍스트 데이터에서 정보 이득 값이 낮은 단어들을 제거하고 단어 임베딩을 적용하는방식과, 정보이득 값이 낮은 단어와 코사인 유사도가 높은 주변 단어를 추가로 선택하여 텍스트 데이터에서 제거하고 단어 임베딩을 재구성하는 방식이다. 본 연구에서 제안하는 방안을 수행함에 있어 데이터는 Amazon.com의 ‘Kindle’ 제품에 대한 고객리뷰, IMDB 의 영화리뷰, Yelp의 사용자 리뷰를 사용하였다. Amazon.com의 리뷰 데이터는 유용한 득표수가 5개 이상을 만족하고, 전체 득표 중 유용한 득표의 비율이 70% 이상인 리뷰에 대해 유용한 리뷰라고 판단하였다. Yelp의 경우는 유용한 득표수가 5개 이상인 리뷰 약 75만개 중 10만개를 무작위 추출하였다. 학습에 사용한 딥러닝 모델은 CNN, Attention-Based Bidirectional LSTM을 사용하였고, 단어 임베딩은 Word2Vec과 GloVe를 사용하였다. 단어 제거를 수행하지 않고 Word2Vec 및 GloVe 임베딩을 적용한 경우와 본 연구에서 제안하는 선택적으로 단어 제거를 수행하고 Word2Vec 임베딩을 적용한 경우를 비교하여 통계적 유의성을 검정하였다.

무선 충전 전기자동차의 운행 불확실성을 고려한 시스템 강건 최적화

이민석,정승민,장영재 한국경영과학회 2017 한국경영과학회 학술대회논문집 Vol.2017 No.4

ATM교환기의 프로세서간 통신을 위한 바이패싱 기능을 갖는 고속 셀 집속/분배 장치의 설계 및 성능평가

이민석,송광석,박동선 한국통신학회 1997 韓國通信學會論文誌 Vol.22 No.6

In this paper, we propose an efficient architecture for a high-speed cell concentrator/distributor(HCCD) in an ATM(Asynchronous Transfer Mode) switch and by analyzeing the simulation results evaluate the performance of the proposed architecuture. The proposed HCCD distributes cells from a switch link to local processors, or concentrates cells from local processor s to a switch link. This design is to guarntee a high throughput for the IPC (inter-processor communication) link in a distributed ATM switching system. The HCCD is designed in a moudlar architecture to provide the extensibility and the flexibility. The main characteristics of the HCCD are 1) Adaption of a local CPU in HCCD for improving flexibility of the system, 2) A cell-baced statistical multiplexing function for efficient multiplexing, 3) A cell distribution function based on VPI(Virtual Path Identifier), 4) A bypassing capability for IPC between processor attached to the same HCCD, 5) A multicasting capability for point-to-multipoint communication, 6) A VPI table updating function for the efficient management of links, 7) A self-testing function for detecting system fault.