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MEC를 활용한 커넥티드 홈의 DRL 기반 태스크 오프로딩 기법
임덕선,손규식 한국인터넷방송통신학회 2023 한국인터넷방송통신학회 논문지 Vol.23 No.6
The rise of 5G and the proliferation of smart devices have underscored the significance of multi-access edge computing (MEC). Amidst this trend, interest in effectively processing computation-intensive and latency-sensitive applications has increased. This study investigated a novel task offloading strategy considering the probabilistic MEC environment to address these challenges. Initially, we considered the frequency of dynamic task requests and the unstable conditions of wireless channels to propose a method for minimizing vehicle power consumption and latency. Subsequently, our research delved into a deep reinforcement learning (DRL) based offloading technique, offering a way to achieve equilibrium between local computation and offloading transmission power. We analyzed the power consumption and queuing latency of vehicles using the deep deterministic policy gradient (DDPG) and deep Q-network (DQN) techniques. Finally, we derived and validated the optimal performance enhancement strategy in a vehicle based MEC environment.
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임덕선,민연아,임동균 한국인터넷방송통신학회 2023 한국인터넷방송통신학회 논문지 Vol.23 No.4
Existing simple statistics-based recommendation systems rely solely on students' course enrollment history data, making it difficult to identify classes that match students' preferences. To address this issue, this study proposes a personalized major subject recommendation system based on deep reinforcement learning (DRL). This system gauges the similarity between students based on structured data, such as the student's department, grade level, and course history. Based on this information, it recommends the most suitable major subjects by comprehensively considering information about each available major subject and evaluations of the student's courses. We confirmed that this DRL-based recommendation system provides useful insights for university students while selecting their major subjects, and our simulation results indicate that it outperforms conventional statistics-based recommendation systems by approximately 20%. In light of these results, we propose a new system that offers personalized subject recommendations by incorporating students' course evaluations. This system is expected to assist students significantly in finding major subjects that align with their preferences and academic goals
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林悳善(Lim, Duk-sun) 대동한문학회 2009 大東漢文學 Vol.30 No.-
본고는 문화의 集積이라 할 수 있는 문집간행의 한 과정을 告成詩를 통하여 고찰한 것이다. 1934년 7월 15일에 晉州에서 『月村集』과 『梨谷集』이 동시에 간행되어 頒帙되자 문집을 발행한 刊所에서 「時到記」·「文集告成韻」·「文集頒帙記」·「捐助錄」의 4문건으로 구성된 「文集刊所記」를 작성하였다. 「時到記」에는 두 문집을 頒帙할 때 刊所에 참가한 鄕村社會의 構成員이 기록되어 있고, 「文集告成韻」에는 16人의 文士가 지은 17首의 時가 수록되어 있다. 「文集頒帙記」에는 두 文集의 配付處가 기재되어 一次的讀者層과 문집의 발행규모를 알 수 있게 하며, 「捐助錄」에는 문집을 頒帙받고 出捐한 금액을 적어 당시 經濟活動의 한 斷面을 볼 수 있다. 특히 「文集告成韻」에는 당시 文名이 높았던 人士들의 詩作이 수록되어 있다. 이 詩人들은 두 문집이 同時에 반질된 이채로운 주제를 두고, 문집간행의 제반 과정을 짧은 時句로 含蓄性있게 표현하였다. 告成詩의 내용은 크게 遺文의 收拾, 校讎 와 編次, 印出과 裝幀, 문집의 頒帙로 나누어져, 문집간행에 따른 제반 과정에 대한 인식이 공통적으로 表出되었다. 東學亂과 淸日戰爭으로 불안한 정세가 이어지자 梨谷 河仁壽 父親인 月村 河達弘의 遺稿가 兵火에 燒失될까 염려하여 鼎蓋山의 斗芳菴 뒤 石室에 보관하여 무난히 수습하였다. 告成時의 詩人들은 이 점을 놓치지 않고 時로 나타내었으며, 아울러 校讎와 編次, 印出과 裝幀, 頒帙에 대해서도 거의 같은 比率로 吐露하였다. This thesis is to review the process of publishing a collection of poems, so called the accumulation of culture, through the poems to contribute for publishing the collection of poems. When the publisher printed and distributed both <Collection of poems composed by Wolchon> and <Collection of poems composed by Igok> on July 15. 1934 in Jinju, he issued <The poems to contribute for publishing the collection of poems> that was consisted of 4 parts, <The list of participants>, <The poems to contribute for publishing the collection of poems>, <The record of distribution>, <The list of donor> There was a list of scholars living in the country district to take part in publishing and distributing and were 17 poems composed by 16 poets to contribute for publishing the collection of poems. The record of places distributed for these two collections of poems had informed us who were primary readers and the size of publication for the collection of poems, and the amount donated for it showed us a facet of economic activity at that time. Specially, some poems composed by the highly respected poets at that time were included in the poems to contribute for publishing the collection of poems. These poets expressed suggestively the process of publishing in the short verses by the way of repeating their questions on the many themes included in the two collections of poems. The contents of poems to contribute for publishing the collection of poems were largely consisted of 4 parts, the collection of posthumous works, revision and edition, print and decoration, distribution, and explained the various processes in common for publishing a collection of poems. Though the unrest political situations caused by Donghak Peasant Revolution and the first Sino- Japanese War had been continuing, Insu Ha, Igok, could preserve successfully his father's posthumous works, Dalhong Ha with pen-name Wolchon, by keeping it in the stone cell located at the backside of Dubangam in Jeonggae mountain for fear of burning in the midst of wars. The poets to compose poems to contribute for publishing the collection of poems did not fail to indicate this point and expressed the efforts to preserve it through poems, and explained the processes of revision and edition, print and decoration, distribution at the nearly same proportion as well.
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FMI기반 co-simulation에서 step size control을 위한 Markov chain을 사용한 예측 방법
홍석준(Seokjoon Hong),임덕선(Ducsun Lim),김원태(Wontae Kim),조인휘(Inwhee Joe) 한국전기전자학회 2019 전기전자학회논문지 Vol.23 No.4
FMI를 기반으로 하는 co-simulation의 마스터 알고리즘(MA)에서 시뮬레이션 결과의 정확도를 높이는 방법으로 zero crossing 포인트를 찾기 위한 Bisectional algorithm을 사용할 수 있다. 그러나 이 알고리즘은 많은 Rollback을 야기한다. 따라서 본 논문에서는 제안하는 MA는 Bisection algorithm을 통해 zero crossing 포인트를 검출하면서도 반복되는 구간 그래프를 분석하여 그 값을 Markov chain을 적용하여 다음 구간을 예측하여 이를 step size에 적용한다. 시뮬레이션에서 실제 Rollback이 발생했을 때 그래프 형태별로 변화되는 step size를 배열로 저장하고, 이룰 다음 예측 구간에 적용함으로서 Rollback을 최소화하는 알고리즘을 제안한다. 시뮬레이션 결과를 통해 제안하는 알고리즘이 기존 알고리즘에 비해 최대 20%이상의 시뮬레이션 시간이 감소되는 것을 확인하였다. In Functional Mockup Interface(FMI)-based co-simulation, a bisectional algorithm can be used to find the zerocrossing point as a way to improve the accuracy of the simulation results. In this paper, the proposed master algorithm(MA) analyzes the repeated interval graph and predicts the next interval by applying the Markov Chain to the step size. In the simulation, we propose an algorithm to minimize the rollback by storing the step size that changes according to the graph type as an array and applying it to the next prediction interval when the rollback occurs in the simulation. Simulation results show that the proposed algorithm reduces the simulation time by more than 20% compared to the existing algorithm.
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