• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.2
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• pp.63-69
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• 2019

Recently, ultra-low latency flash storage devices such as Z-SSD and Optane SSD were introduced with the significant technological improvement in the storage devices which provide much faster response time than today's other NVMe SSDs. With such ultra-low latency, $10{\mu}s$, storage devices the cost of context switch could be an overhead during interrupt-driven I/O completion process. As an interrupt-driven I/O completion process could bring an interrupt handling overhead, polling or hybrid-polling for the I/O completion is known to perform better. In this paper, we analyze tail latency problem in a polling process caused by process scheduling in data center environment where multiple applications run simultaneously under one system and we introduce our adaptive polling selection technique which dynamically selects efficient processing method between two techniques according to the system's conditions.

• Earthquakes and Structures
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• v.24 no.2
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• pp.111-126
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• 2023

Highly reliable and versatile methods artificial intelligence (AI) have found multiple application in the different fields of science, engineering and health care system. In the present study, we aim to utilize AI method to investigated vibrations in the human leg bone. In this regard, the bone geometry is simplified as a thick cylindrical shell structure. The deep neural network (DNN) is selected for prediction of natural frequency and critical buckling load of the bone cylindrical model. Training of the network is conducted with results of the numerical solution of the governing equations of the bone structure. A suitable optimization algorithm is selected for minimizing the loss function of the DNN. Generalized differential quadrature method (GDQM), and Hamilton's principle are used for solving and obtaining the governing equations of the system. As well as this, in the results section, with the aid of AI some predictions for improving the behaviors of the various sport systems will be given in detail.

• Journal of Advanced Navigation Technology
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• v.25 no.3
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• pp.211-216
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• 2021

Multiple UAV System has been used for various purposes such as reconnaissance, networking and aerial photography. In such systems, it is essential to form and maintain the formation of multiple UAVs. This paper proposes the algorithm that produces an autonomous distributed control for each vehicle for a flexible formation. This command is a repulsive force in the form of the second-order system by the nearest UAV or mission area. The algorithm uses the relative position/speed through sensing and communication for calculating the command without external intervention. The command allows each UAV to follow the reference distance and fill the mission area as densely as possible without overlapping. We determine the reference distance via optimization technique solving the packing problem. The mission area comprises the desired formation outline and can be set flexibly depending on the mission. Numerical simulation is carried out to verify the performance of the proposed algorithm under a complex and flexible environment. The formation is formed in 26.94 seconds and has a packing density of 71.91%.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.620-626
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• 2004

For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.

• Korean Management Science Review
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• v.32 no.4
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• pp.109-133
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• 2015

This paper considers the allocation and engagement scheduling of air defense missiles by using MIP (mixed integer programming). Specifically, it focuses on developing a realistic MIP model for a real battle situation where multiple enemy missiles are headed toward valuable defended assets and there exist multiple air defense missiles to counteract the threats. In addition to the conventional objective such as the minimization of surviving target value, the maximization of total intercept altitude is introduced as a new objective. The intercept altitude of incoming missiles is important in order to minimize damages from debris of the intercepted missiles and moreover it can be critical if the enemy warhead contains an atomic or chemical bomb. The concept of so called the time window is used to model the engagement situation and a continuous time is assumed for flying times of the both missiles. Lastly, the model is extended to simulate the situation where the guidance radar, which guides a defense missile to its target, has the maximum guidance capacity. The initial mathematical model developed contains several non-linear constraints and a non-linear objective function. Hence, the linearization of those terms is performed before it is solved by a commercially available software. Then to thoroughly examine the MIP model, the model is empirically evaluated with several test problems. Specifically, the models with different objective functions are compared and several battle scenarios are generated to evaluate performance of the models including the extended one. The results indicate that the new model consistently presents better and more realistic results than the compared models.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1632-1638
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• 2020

In this paper, we investigate a multi-beam satellite communication system where multiple terminals transmit information signals to the gateway via a satellite. The satellite is equipped with phased array antennas to form multiple spot beams of which bandwidths are not identically allocated. We formulate an optimization problem to maximize fairness of beam bandwidth allocation. In order to solve the problem, we propose two heuristic algorithms; iterative beam bandwidth allocation (IBBA) and request ratio-based beam bandwidth allocation (RRBBA) algorithms. The IBBA algorithm iteratively equalizes the ratio of allocated bandwidth of each beam to their resource request while the RRBBA algorithm allocates beam bandwidth calculated from the ratio. Simulation results show that the IBBA algorithm has close fairness performance to the optimum while the RRBBA algorithm has less performance than the IBBA algorithm at the price of reduced computational complexity.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.89-96
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• 2016

In this paper, we study mobile data collector (MDC) based data-gathering schemes in wireless sensor networks. In Such networks, MDCs are used to collect data from the environment and transfer them to the sink. The majority of existing data-gathering schemes suffer from high data-gathering latency because they use only a single MDC. Although some schemes use multiple MDCs, they focus on maximizing network lifetime rather than minimizing packet delay. In order to address the limitations of existing schemes, this paper focuses on minimizing packet delay for given number of MDCs and minimizing the number of MDCs for a given delay bound of packets. To achieve the minimum packet delay and minimum number of MDCs, two optimization problems are formulated, and traveling distance and traveling time of MDCs are estimated. The interior-point algorithm is used to obtain the optimal solution for each optimization problem. Numerical results and analysis are presented to validate the proposed method.

• Journal of the Korean Geographical Society
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• v.43 no.2
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• pp.220-234
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• 2008

In many security monitoring contexts, the performance or efficiency of surveillance sensors/networks based on a single sensor type may be limited by environmental conditions, like illumination change. It is well known that different modes of sensors can be complementary, compensating for failures or limitations of individual sensor types. From a location analysis and modeling perspective, a challenge is how to locate different modes of sensors to support security monitoring. A coverage-based optimization model is proposed as a way to simultaneously site k different sensor types. This model considers common coverage among different sensor types as well as overlapping coverage for individual sensor types. The developed model is used to site sensors in an urban area. Computational results show that common and overlapping coverage can be modeled simultaneously, and a rich set of solutions exists reflecting the tradeoff between common and overlapping coverage.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.9
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• pp.932-940
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• 2011

This paper presents an integrated analysis of supply chain and financing decisions of multi-national corporation. We construct a model in which multiple currency storage units are installed to manage the currency flows associated with multi-national supply chain activities such as raw material procurement, process operation, inventory control, transportation and finished product sales. Core contribution of this study is to quantitatively investigate the influence of macroscopic economic factors such as exchange rates and taxes on operational decisions. The supply chain is modeled by the Process-Storage Network with recycle streams. The objective function of the optimization is minimizing the opportunity costs of annualized capital investments and currency/material inventories minus the benefit to stockholders interpreted by home currency. The major constraints of the optimization are that the material and currency storage units must not be depleted. A production and inventory analysis formulation, the periodic square wave (PSW) model, provides useful expressions for the upper/lower bounds and average levels of the currency and material inventory holdups. The expressions for the Kuhn-Tucker conditions of the optimization problem are reduced to a subproblem and analytical lot sizing equations. The procurement, production, transportation and financial transaction lot sizes can be determined by analytical expressions after the average flow rates are already known. We show that, when corporate income tax is taken into consideration, the optimal production lot and storage sizes are smaller than is the case when such factors are not considered typically by 20 %.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.8
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• pp.923-929
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• 2019

The stability of the propulsion system is crucial for the autonomous vessel. Multiple power generation and propulsion systems should be provided for the stability of the propulsion system. High power generation capacity is calculated for stability, resulting in economical decline due to low load operation. To solve this problem, we need to optimize the power system. In this paper, an OPMS for electric propulsion ship is constructed. The OPMS consists of a hybrid power generation system, an energy storage system, and a control load system. The power generation system consists of a dual fuel engine, the energy storage system is a battery, and the control load system consists of the propulsion load, continuous load, intermittent load, cargo part load and deck machine load. The power system was constructed by modeling the characteristics of each system. For the experiment, a scenario based on ship operation was prepared and the stability and economical efficiency were compared with existing electric propulsion ships.