The current Data Distribution Service for Real-Time Systems (DDS) is mainly designed for transmission in a single local network domain. However, when DDS applications communicate with other applications in different network domains over WAN, the DDS could face severe problems, because most ISPs in WAN do not allow multicast and UDP flows. In this paper, we propose a router design for DDS. While keeping the semantics of the DDS, the proposed DDS router provides an efficient data distribution over WAN using the local recovery and overlay multicast. Through the NS-3 simulations, we show that the system with the DDS routers outperforms the legacy unicast based communication method in terms of the scalability and robustness.
We study the Lorentz transformation of the minimal chiral Schwinger model in terms of the alternative action. We automatically obtain a chiral constraint, which is equivalent to the frame constraint introduced by McCabe, in order to solve the frame problem in phase space. As a result we obtain the Lorentz invariant spectrum in any moving frame by choosing a frame parameter.
Modeling and simulation technologies have been widely used in industry to assist in system development. Although simulation models can be used throughout most of the design phases, they should be finally transformed to source codes for the target platforms. This paper presents a method to smoothly transform simulation models for SAM fuzzy systems to C++ codes. Through multiple processing steps of the proposed method, simulation models of a fuzzy system are transformed to a C++ class. A prototype of our visual fuzzy system modeling tool to enable the proposed method is introduced.
Soil loss induced by erosion has come to be a serious problem in Korea's sloped land since more than 70% of upland fields are located on the sloped land area. The purpose of this study was to investigate the phase of water flow in differently soil textured plot soil types by rainfall amount. Lysimeters with slope of 15%, 5 m in length, 2 m in width, and 1 m in depth were prepared and filled up with three different soil textures, such as sandy loam, loam, and clay loam, then relationships between seasonal rainfall and runoff, percolation were analyzed. Runoff and percolation rate were shown to increase linearly with increasing rainfall intensity in all the soil textures, but the starting threshold and increment rate in runoff and percolation occurrence were dependent differently upon soil textures. Percolation increment rate according to the increasing rainfall amount was 0.52, 0.36, and 0.57 for sandy loam, loam and clay loam soil respectively. The threshold rainfall amounts in which percolation occurs were 5.73 mm, 6.80 mm, and 12.86 mm for sandy loam, loam and clay loam respectively. Runoff increment rates were 0.42, 0.48 and 0.46 for sandy loam, loam and clay loam soil. The threshold rainfall amount in which runoff occurs was 10.50 mm in sandy loam, 7.76 mm in loam and 17.40 mm in clay loam. These different phases of water flow by soil texture could be used to suggest guidelines for the best management practice of the farming slope land.
이 연구의 목적은 표토보존을 위해 국내 개발분야 중 주요한 사례에 해당하는 하천개발분야에서 표토관리의 실태를 조사 및 분석하는 데 있다. 전문가를 대상으로 한 설문조사를 통해 하천개발과정에서 표토관리의 실태와 문제를 파악하였다. 이를 분명히 하기 위해 국내 하천개선사업 중 환경부의 감독을 받는 생태하천복원사업으로서 최근 완료된 하천을 중심으로 개발 전과 개발 후의 토양특성을 분석하였다. 연구 결과는 다음과 같다. 첫째, 전문가들은 식물생장을 위해 최선의 토양관리 및 개선방법으로서 표토의 수거 및 재활용을 선호하였다. 둘째, 경제적 문제와 시공의 불편 때문에 실제 표토의 수거 및 재활용은 제대로 이루어지고 있지 않다. 셋째, 개발 후 식물생장에 필요한 유기물, 총질소 등 토양조건 요인들이 전반적으로 감소한다. This study aimed to research and analyze the real condition of topsoil management of river development field as a significant case among domestic development fields for topsoil preservation. Through survey with experts, we understood the real condition and problems of topsoil management during river development. In order to verify this, we analyzed the characteristics of soil before and after development focusing on the rivers recently completed as an ecological river restoration project, supervised by Ministry of Environment among domestic river improvement projects. The study results are like below. First, experts preferred collecting and reusing topsoil as the best method to maintain and improve soil for plant growth. Second, realistically collecting and reusing topsoil is not fully conducted due to economical issues and inconvenience in construction. In the soil condition, third, the contents of elements necessary for plant growth like organic matter and total nitrogen declined overall after development.
In this letter, we apply dynamic software updating to long-lived applications on the DDS middleware while minimizing service interruption and satisfying Quality of Service (QoS) requirements. We dynamically updated applications which run on a commercial DDS implementation to demonstrate the applicability of our approach to dynamic updating. The results show that our update system does not impose an undue performance overhead-all patches could be injected in less than 350ms and the maximum CPU usage is less than 17%. In addition, the overhead on application throughput due to dynamic updates ranged from 0 to at most 8% and the deadline QoS of the application was satisfied while updating.
As user requirements become increasingly complex, the demand for product personalization is growing, but traditional hardware-centric production relies on fixed procedures that lack the flexibility to support diverse requirements. Although bespoke manufacturing has been introduced, it provides users with only a few standardized options, limiting its ability to meet a wide range of needs. To address this issue, a new manufacturing concept called the software-defined factory has emerged. It is an autonomous manufacturing system that provides reconfigurable manufacturing services to produce tailored products. Reinforcement learning has been suggested for flexible scheduling to satisfy user requirements. However, fixed rule-based methods struggle to accommodate conflicting needs. This study proposes a novel federated digital twin scheduling that combines large language models and deep reinforcement learning algorithms to meet diverse user requirements in the software-defined factory. The large language model-based literacy module analyzes requirements in natural language and assigns weights to digital twin attributes to achieve highly relevant KPIs, which are used to guide scheduling decisions. The deep reinforcement learning-based scheduling module optimizes scheduling by selecting the job and machine with the maximum reward. Different types of user requirements, such as reducing manufacturing costs and improving productivity, are input and evaluated by comparing the flow-shop scheduling with job-shop scheduling based on reinforcement learning. Experimental results indicate that in requirement case 1 (the manufacturing cost), the proposed method outperforms flow-shop scheduling by up to 14.9% and job-shop scheduling by 5.6%. For requirement case 2 (productivity), it exceeds the flow-shop method by up to 13.4% and the job-shop baseline by 7.2%. The results confirm that the literacy DRL scheduling proposed in this paper can handle the individual characteristics of requirements.
Fault detection for dynamic loading conditions of rotational machineries was considered from the contactless, non-destructive infrared thermographic method, rather than the traditional diagnosis method. In this paper, by applying a rotating deep-grooved ball bearing, passive thermographic experiment was performed as an alternative way proceeding the traditional fault monitoring. In addition, the thermographic experiments were compared with the vibration spectrum analysis to evaluate the efficiency of the proposed method. Based on the results, it was concluded the temperature characteristics of the ball bearing under dynamic loading conditions were analyzed thoroughly.
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