• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권11호
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• pp.3603-3618
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• 2022

The offloading method is important when there are multiple mobile nodes and multiple edge servers. In the environment, those mobile nodes connect with edge servers with different bandwidths, thus taking different time and energy for offloading tasks. Considering the system load of edge servers and the attributes (the number of instructions, the size of files, deadlines, and so on) of tasks, the energy-aware offloading problem becomes difficult under our mobile edge environment (MCE). Most of the past work mainly offloads tasks by judging where the job consumes less energy. But sometimes, one task needs more energy because the preferred edge servers have been overloaded. Those methods always do not pay attention to the influence of the scheduling on the future tasks. In this paper, first, we try to execute the job locally when the job costs a lower energy consumption executed on the MD. We suppose that every task is submitted to the mobile server which has the highest bandwidth efficiency. Bandwidth efficiency is defined by the sending ratio, the receiving ratio, and their related power consumption. We sort the task in the descending order of the ratio between the energy consumption executed on the mobile server node and on the MD. Then, we give a "suffrage" definition for the energy consumption executed on different mobile servers for offloading tasks. The task selects the mobile server with the largest suffrage. Simulations show that our method reduces the execution time and the related energy consumption, while keeping a lower value in the number of uncompleted tasks.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2001년도 제16회 학술발표회 논문초록집
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• pp.1-6
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• 2001

In this paper, edge delaminations in cracked composite plates are analytically investigated. A theoretical model based upon a sub-laminate approach is used to determine the strain energy release rate, $G^{ed}$, in [$\pm$$\theta_m$/$90_n$]$_s$ carbon/epoxy laminates loaded in tension. The analysis provides closed-form expressions for the reduced stiffness due to edge delamination and matrix cracking and the total energy release rate. The parameters controlling the laminate behaviour are identified. It is shown that the available energy for edge delamination is increased notably due to transverse ply cracking. Also thermal stresses increase substantially the strain energy release rate and this effect is magnified by the presence of matrix cracking. Prediction for the edge delamination onset strain is presented and compared with experimental data. The analysis could be applied to ceramic matrix composite laminates where similar mechanisms develop, but further experimental evidence is required.

• 반도체디스플레이기술학회지
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• 제22권4호
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• pp.7-12
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• 2023

The edge ring placed on the outside of the electrostatic chuck (ESC) is a key component for protecting the ESC and controlling the etching uniformity of the edge of the wafer. Therefore, it is very important to understand the etching phenomenon of edge rings for edge ring management and equipment homeostasis. In this study, a specimen with SiO₂ hard mask and underlying Si mold was installed on the edge ring surface and the etching results were measured by varying the edge ring 2MHz RF power. By developing PI-VM model with high prediction accuracy and analyzing the roles of key parameters in the model, we were able to evaluate the effect of plasma and sheath characteristics around the edge ring on edge ring erosion. This analysis method provided information necessary for edge ring maintenance and operation.

• 대한임베디드공학회논문지
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• 제18권4호
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• pp.159-164
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• 2023

Solar energy harvesting IoT devices prioritize maximizing the utilization of collected energy due to the periodic recharging nature of solar energy, rather than minimizing energy consumption. Meanwhile, research on edge AI, which performs machine learning near the data source instead of the cloud, is actively conducted for reasons such as data confidentiality and privacy, response time, and cost. One such research area involves performing various audio AI applications using audio data collected from multiple IoT devices in an IoT edge computing environment. However, in most studies, IoT devices only perform sensing data transmission to the edge server, and all processes, including data preprocessing, are performed on the edge server. In this case, it not only leads to overload issues on the edge server but also causes network congestion by transmitting unnecessary data for learning. On the other way, if data preprocessing is delegated to each IoT device to address this issue, it leads to another problem of increased blackout time due to energy shortages in the devices. In this paper, we aim to alleviate the problem of increased blackout time in devices while mitigating issues in server-centric edge AI environments by determining where the data preprocessed based on the energy state of each IoT device. In the proposed method, IoT devices only perform the preprocessing process, which includes sound discrimination and noise removal, and transmit to the server if there is more energy available than the energy threshold required for the basic operation of the device.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권6호
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• pp.2282-2303
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• 2021

To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.283-286
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• 2001

Based on a fuzzy system representation of gray scale images, we derive an edge detection algorithm whose convolution kernel is different from the known kernels such as those of Roberts', Prewitt's or Sobel's gradient. Our fuzzy system representation is an exact representation of the bicubic spline function which represents the gray scale image approximately. Hence the fuzzy system is a continuous function and it provides a natural way to define the gradient and the Laplacian operator. We show that the gradient at grid points can be evaluated by taking the convolution of the image with a 3 3 kernel. We also show that our gradient coupled with the approximate value of the continuous function generates an edge detection method which creates edge images clearer than those by other methods. A few examples of applying our methods are included.

• Journal of Information Processing Systems
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• 제19권4호
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• pp.450-464
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• 2023

To address the problems of large system overhead and low timeliness when dealing with task scheduling in mobile edge cloud computing, a task scheduling and resource management strategy for edge cloud computing based on an improved genetic algorithm was proposed. First, a user task scheduling system model based on edge cloud computing was constructed using the Shannon theorem, including calculation, communication, and network models. In addition, a multi-objective optimization model, including delay and energy consumption, was constructed to minimize the sum of two weights. Finally, the selection, crossover, and mutation operations of the genetic algorithm were improved using the best reservation selection algorithm and normal distribution crossover operator. Furthermore, an improved legacy algorithm was selected to deal with the multi-objective problem and acquire the optimal solution, that is, the best computing task scheduling scheme. The experimental analysis of the proposed strategy based on the MATLAB simulation platform shows that its energy loss does not exceed 50 J, and the time delay is 23.2 ms, which are better than those of other comparison strategies.

• International Journal of Aeronautical and Space Sciences
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• 제16권3호
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• pp.407-417
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• 2015

Recently, piezo-aeroelastic energy harvesting has received greater attention. In the present study, a piezo-aeroelastic energy harvester using a nonlinear trailing-edge flap is proposed, and its nonlinear aeroelastic behaviors are investigated. The energy harvester is modeled using a piezo-aeroelastic model of a two-dimensional typical section airfoil with a trailing-edge flap (TEF). A piezo-aeroelastic analysis is carried out using RL and time-integration methods, and the results are verified with the experimental data. The linearizing method using a describing function is used for the frequency domain analysis of the nonlinear piezo-aeroelastic system. From the linear and nonlinear piezo-aeroelastic analysis, the limit cycle oscillation (LCO) characteristics of the proposed energy harvester with the nonlinear TEF are investigated in both the frequency and time domains. Finally, the authors discuss the air speed range for effective piezo-aeroelastic energy harvesting.

• 한국분말야금학회:학술대회논문집
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• 한국분말야금학회 2001년도 춘계학술강연 및 발표대회
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• pp.14-14
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• 2001

WC-Co 계의 입성장 억제는 현재 초경합금 분야에서 공학적으로 가장 중요한 이슈들 중의 하나이다 VC를 비롯한 입방정 탄화물이나 $Cr_3C_2$ 등의 여러 가지 탄화 물이 혼합되어 입성장 억제에 이용되는데 입성장 억제의 효과는 대략적으로 용해되는 탄화물의 양에 의존하고 있는 것으로 추정된다. 보다 효율적으로 입성장 억제를 실현하려면 입성장 기구를 명확히 할 필요가 있다. 최 등[1]은 VC가 WC 입자 표면 에서의 edge energy를 증가시켜서 2차원 핵생성의 에너지 장벽을 올리게 하고 이에 따라 입성장이 억제된다는 모델을 제안하였다. 이러한 모텔을 입증하기 위해서는 이론적으로만 예측이 가능한 edge energy보다 좀 더 명확한 물리적인 변수가 제시되어야 할 것이다. 여기서는 또 다른 계인 NbC- TiC-Co 계에서 NbC와 TiC의 버에 따른 입성장 거동과 입자의 형상간의 관계로부터 업성장과 edge energy 그리 고 edge energy와 입자 형상간의 관계를 알아보고 이로부터 좀 더 구체적인 의미 에서의 입성장 모텔과 입성장 억제기구를 제시하고자 한다.

• International Journal of Fluid Machinery and Systems
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• 제9권4호
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• pp.307-312
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• 2016

The present study reported of the use of special shaped blade to reduce the difference in pressure across the Wells turbine for wave energy conversion. The blade profile was composed of NACA0020 airfoils and trailing edge was notched like chevron. Experiments were performed investigating the influence of trailing edge shape on the turbine performance. Four notch depths were used to investigate the effect of depth of cut on the turbine performance. As results, by placing a notch-cut at the trailing edge of the blade, it was possible to reduce the pressure difference across the turbine without lowering the efficiency. In addition, the pressure difference substantially reduced at a constant rate with the increase of the cut ratio.