• Journal of the Korea Institute of Military Science and Technology
• /
• v.4 no.1
• /
• pp.170-176
• /
• 2001

An optimization problem to obtain the optimal replacement interval considering the salvage values is studied. The system is minimally repaired at failure and is replaced by new one at age T(periodic replacement policy with minimal repair of Barlow and Hunter〔2〕). Our model assumes that the time horizon associated with the number of replacements is random The total expected cost considering the salvage values with random time horizon is obtained and the optimal replacement interval minimizing the cost is found by numerical methods. Comparisons between non-considered salvage values and this case are made by a numerical example.

• Journal of KIISE:Information Networking
• /
• v.35 no.3
• /
• pp.243-250
• /
• 2008

Recently, researched RFID authentication protocols still have vulnerability of attack, such as location tracking attack, replay attack. spoofing attack etc. This paper designed method of making one time random number in DB server side unlike previously researched protocols, and it protects RFID communication from location tracking, replay attack and spoofing attack.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.59 no.1
• /
• pp.47-52
• /
• 2010

The low power of ultra-wideband (UWB) signal makes the acquisition of UWB signal be a more challenging task. In this paper, we propose the method of high order template signal technique that reduces the synchronization time. Experimental results are presented to show the improvements of performance in the mean acquisition time (MAT) and the probability of detection. The performance compared with the serial search, the truly random search and the random permutation search. It is shown that over typical UWB multipath channels, a random permutation search scheme may yield lower MAT than serial search.

• International Journal of Reliability and Applications
• /
• v.1 no.1
• /
• pp.49-64
• /
• 2000

We consider a system whose inherent life follows an Erlang distribution, which is subject to two heterogeneous random shocks. Minor shocks arrive according to a renewal process and each causes the system to fail independently with a certain probability. A major shock whose interarrival times follow an Erlang distribution causes the system to fail with probability one. The Laplace transform of the distribution of the time to system failure is derived in a functional form of the Laplace transform of the interarrival time distribution of minor shocks. An algorithm is given for the computation of the moments of the time to system failure.

• International Journal of Control, Automation, and Systems
• /
• v.6 no.3
• /
• pp.444-452
• /
• 2008

We propose an intelligent predictive control approach for a nonlinear networked control system (NCS) with time-varying delay and random observation. The control is given by the sum of a nominal control and a corrective control. The nominal control is determined analytically using a linearized system model with fixed time delay. The corrective control is generated online by a neural network optimizer. A Markov chain (MC) dynamic Bayesian network (DBN) predicts the dynamics of the stochastic system online to allow predictive control design. We apply our proposed method to a satellite attitude control system and evaluate its control performance through computer simulation.

• The Journal of the Acoustical Society of Korea
• /
• v.22 no.1E
• /
• pp.26-32
• /
• 2003

We propose new time-frequency (TF) tools for analyzing linear time-varying (LTV) systems and nonstationary random processes showing hyperbolic TF structure. Obtained through hyperbolic warping the narrowband Weyl symbol (WS) and spreading function (SF) in frequency, the new TF tools are useful for analyzing LTV systems and random processes characterized by hyperbolic time shifts. This new TF symbol, called the hyperbolic WS, satisfies the hyperbolic time-shift covariance and scale covariance properties, and is useful in wideband signal analysis. Using the new, hyperbolic time-shift covariant WS and 2-D TF kernels, we provide a formulation for the hyperbolic time-shift covariant TF symbols, which are 2-D smoothed versions of the hyperbolic WS. We also propose a new interpretation of linear signal transformations as weighted superposition of hyperbolic time shifted and scale changed versions of the signal. Application examples in signal analysis and detection demonstrate the advantages of our new results.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.39 no.4
• /
• pp.38-49
• /
• 2002

In this paper, we propose a solution for random time-delay in teleoperation via internet using QoS, and show the experimental results of our proposed method. By ensuring a constant bandwidth required for the specific telecontrolled system, we change irregular random time-delay to a predictable time-delay, and so we can control the system with the time-delay shorter than the specified time-delay. Through the experimental results, we show the effectiveness of our proposed method.

• Journal of Electrical Engineering and Technology
• /
• v.11 no.4
• /
• pp.951-960
• /
• 2016

Tower insulators in electric power transmission network play a crucial role in preserving the reliability of the system. Electrical utilities frequently face the problem of flashover of insulators due to pollution deposition on their surface. Several research works based on leakage current (LC) measurement has been already carried out in developing diagnostic techniques for these insulators. Since the LC signal is highly intermittent in nature, estimation of pollution severity based on LC signal measurement over a short period of time will not produce accurate results. Reports on the measurement and analysis of LC signals over a long period of time is scanty. This paper attempts to use Random Forest (RF) classifier, which produces accurate results on large data bases, to analyze the pollution severity of high voltage tower insulators. Leakage current characteristics over a long period of time were measured in the laboratory on porcelain insulator. Pollution experiments were conducted at 11 kV AC voltage. Time domain analysis and wavelet transform technique were used to extract both basic features and histogram features of the LC signal. RF model was trained and tested with a variety of LC signals measured over a lengthy period of time and it is noticed that the proposed RF model based pollution severity classifier is efficient and will be helpful to electrical utilities for real time implementation.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.6
• /
• pp.1635-1656
• /
• 2023

In Bayesian multi-target tracking, the Poisson multi-Bernoulli mixture (PMBM) filter is a state-of-the-art filter based on the methodology of random finite set which is a conjugate prior composed of Poisson point process (PPP) and multi-Bernoulli mixture (MBM). In order to improve the random finite set-based filter utilized in multi-target tracking of sensor scanning, this paper introduces the Poisson multi-Bernoulli mixture filter into time-matching Bayesian filtering framework and derive a tractable and principled method, namely: the time-matching Poisson multi-Bernoulli mixture (TM-PMBM) filter. We also provide the Gaussian mixture implementation of the TM-PMBM filter for linear-Gaussian dynamic and measurement models. Subsequently, we compare the performance of the TM-PMBM filter with other RFS filters based on time-matching method with different birth models under directional continuous scanning and out-of-order discontinuous scanning. The results of simulation demonstrate that the proposed filter not only can effectively reduce the influence of sampling time diversity, but also improve the estimated accuracy of target state along with cardinality.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.3
• /
• pp.305-312
• /
• 2010

The aim of this study is to find an analytic solution to the problem of determining the optimal capacity of a batch-storage network to meet demand for finished products in a system undergoing joint random variations of operating time and batch material loss. The superstructure of the plant considered here consists of a network of serially and/or parallel interlinked batch processes and storage units. The production processes transform a set of feedstock materials into another set of products with constant conversion factors. The final product demand flow is susceptible to joint random variations in the cycle time and batch size. The production processes have also joint random variations in cycle time and product quantity. The spoiled materials are treated through regeneration or waste disposal processes. The objective function of the optimization is minimizing the total cost, which is composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis the PSW (Periodic Square Wave) model, provides a judicious graphical method to find the upper and lower bounds of random flows. The advantage of this model is that it provides a set of simple analytic solutions while also maintaining a realistic description of the random material flows between processes and storage units; as a consequence of these analytic solutions, the computation burden is significantly reduced. The proposed method has the potential to rapidly provide very useful data on which to base investment decisions during the early plant design stage. It should be of particular use when these decisions must be made in a highly uncertain business environment.