• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.712-718
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• 2013

With the development of industry and the improvement of living standards, better quality in power electric service is required more than ever before. This paper deals with the optimal algorithms for voltage regulation in the case where Distributed Storage and Generation (DSG) systems are operated in distribution systems. It is very difficult to handle the interconnection issues for proper voltage managements, because the randomness of the load variations and the irregular operation of DSG should be considered. This paper proposes the optimal on-line real time voltage regulation methods in power distribution systems interconnected with the DSG systems. In order to deliver suitable voltage to as many customers as possible, the optimal sending voltage should be decided by the effective voltage regulation method by using artificial neural networks to consider the rapid load variation and random operation characteristics of DSG systems. The simulation results from a case study show that the proposed method can be a practical tool for the voltage regulation in distribution systems including many DSG systems.

• Journal of information and communication convergence engineering
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• v.11 no.2
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• pp.124-131
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• 2013

Extraction and representation of postures and/or gestures from human activities in videos have been a focus of research in this area of action recognition. With various applications cropping up from different fields, this paper seeks to improve the performance of these action recognition machines by proposing a shape-based silhouette-edge descriptor for the human body. Information entropy, a method to measure the randomness of a sequence of symbols, is used to aid the selection of vital key postures from video frames. Morphological operations are applied to extract and stack edges to uniquely represent different actions shape-wise. To classify an action from a new input video, a Hausdorff distance measure is applied between the gallery representations and the query images formed from the proposed procedure. The method is tested on known public databases for its validation. An effective method of human action annotation and description has been effectively achieved.

• Journal of information and communication convergence engineering
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• v.11 no.1
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• pp.30-44
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• 2013

Traffic congestion has become a serious problem with the recent exponential increase in the number of vehicles. In urban areas, almost all traffic congestion occurs at intersections. One of the ways to solve this problem is road expansion, but it is difficult to realize in urban areas because of the high cost and long construction period. In such cases, traffic signal control is a reasonable method for reducing traffic jams. In an actual situation, the traffic flow changes randomly and its randomness makes the control of traffic signals difficult. A prediction of traffic jams is, therefore, necessary and effective for reducing traffic jams. In addition, an autonomous distributed (stand-alone) point control of each traffic light individually is better than the wide and/or line control of traffic lights from the perspective of real-time control. This paper describes a stochastic optimum control of crossroads and multi-way traffic signals. First, a stochastic model of traffic flows and traffic jams is constructed by using a Bayesian network. Secondly, the probabilistic distributions of the traffic flows are estimated by using a cellular automaton, and then the probabilistic distributions of traffic jams are predicted. Thirdly, optimum traffic signals of crossroads and multi-way intersection are searched by using a modified particle swarm optimization algorithm to realize real-time traffic control. Finally, simulations are carried out to confirm the effectiveness of the real-time stochastic optimum control of traffic signals.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.326-329
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• 2017

Most modern computer communications and storage media support encryption technology. Many of the Ping Pong algorithms are stream ciphers that generate random numbers in the LFSR core structure. The LFSR has a structure that guarantees the maximum period of a given size, but it has a linear structure and can be predicted. Therefore, the Ping Pong algorithm has a feature of making the linearity of the LFSR into a nonlinear structure through variable clocks and functions. In this paper, we try to improve the existing linearity by replacing the linear disadvantages of LFSR with logistic maps.

• Journal of the Korean Institute of Gas
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• v.24 no.1
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• pp.56-65
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• 2020

Forecasting of coming fire accidents is quite a challenging problem cause normally fire accidents occur for a variety of reasons and seem randomness. However, if fire accidents that cause critical losses can be forecasted, it can expect to minimize losses through preemptive action. Classifications using machine learning were determined as appropriate classification criteria for the forecasting cause it classified as a constant damage scale and proportion. In addition, the analysis of the periodicity of a critical fire accident showed a certain pattern, but showed a high deviation. So it seems possible to forecast critical fire accidents using advanced prediction techniques rather than simple prediction techniques.

• Communications for Statistical Applications and Methods
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• v.17 no.2
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• pp.141-151
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• 2010

Hybrid fuzzy regression analysis is used for integrating randomness and fuzziness into a regression model. Least squares support vector machine(LS-SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate hybrid fuzzy linear and nonlinear regression models with crisp inputs and fuzzy output using weighted fuzzy arithmetic(WFA) and LS-SVM. LS-SVM allows us to perform fuzzy nonlinear regression analysis by constructing a fuzzy linear regression function in a high dimensional feature space. The proposed method is not computationally expensive since its solution is obtained from a simple linear equation system. In particular, this method is a very attractive approach to modeling nonlinear data, and is nonparametric method in the sense that we do not have to assume the underlying model function for fuzzy nonlinear regression model with crisp inputs and fuzzy output. Experimental results are then presented which indicate the performance of this method.

• Journal of the Korea Society for Simulation
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• v.8 no.3
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• pp.49-66
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• 1999

Semiconductor wafer fabrication is known to be one of the most complex manufacturing processes due to process intricacy, random yields, product diversity, and rapid changing technologies. In this study we are concerned with the impact of lot release and dispatching policies on the performance of semiconductor wafer fabrication facilities. We consider several semiconductor wafer fabrication environments according to the machine failure types such as no failure, normal MTBF, bottleneck with low MTBF, high randomness, and high MTBF cases. Lot release rules to be considered are Deterministic, Poisson process, WR(Workload Regulation), SA(Starvation Avoidance), and Multi-SA. These rules are combined with several dispatching rules such as FIFO (First In First Out), SRPT (Shortest Remaining Processing Time), and NING/M(smallest Number In Next Queue per Machine). We applied the combined policies to each of semiconductor wafer fabrication environments. These policies are assessed in terms of throughput and flow time. Basically Weins fabrication setup was used to make the simulation models. The simulation parameters were obtained through the preliminary simulation experiments. The key results throughout the simulation experiments is that Multi-SA and SA are the most robust rules, which give mostly good performance for any wafer fabrication environments when used with any dispatching rules. The more important result is that for each of wafer fabrication environments there exist the best and worst choices of lot release and dispatching policies. For example, the Poisson release rule results in the least throughput and largest flow time without regard to failure types and dispatching rules.

• Membrane and Water Treatment
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• v.8 no.2
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• pp.161-169
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• 2017

The adsorption of phosphate onto mesoporous $TiO_2$ was investigated in order to reduce phosphorus concentrations in wastewater and provide a potential mode of phosphorus recovery. Three equilibrium isotherms were used to optimize and properly describe phosphate adsorption ($R^2$>0.95). The maximum capacity of phosphate on the adsorbent was found to be 50.4 mg/g, which indicated that mesoporous $TiO_2$ could be an alternative to mesoporous $ZrO_2$ as an adsorbent. A pseudo-second order model was appropriately fitted with experimental data ($R^2$>0.93). Furthermore, the suitable pH for phosphate removal by $TiO_2$ was observed to be in the range of pH 3-7 in accordance with ion dissociation. In contrast, increasing the pH to produce more basic conditions noticeably disturbed the adsorption process. Moreover, the kinetics of the conducted temperature study revealed that phosphate adsorption onto the $TiO_2$ adsorbent is an exothermic process that could have spontaneously occurred and resulted in a higher randomness of the system. In this study, the maximum adsorption using real wastewater was observed at $30^{\circ}C$.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.5
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• pp.635-639
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• 2021

As times goes by, a ton of electric devices have been developing. Nowadays, there are many personal electric goods that are connected each other and have important private information such as identification, account number, passwords, and so on. As many people own at least one electric device, security of the electric devices became significant. To prevent leakage of the information, study of Chaotic TRNG, "Chaotic True Random Number Generator", protecting the information by generating random numbers that are not able to be expected, is essential. In this paper, A chaotic TRNG is introduced is simulated. The proposed Chaotic TRNG is simulated with Virtuoso &, a circuit design program of Cadence that is a software company. For simulating the mentioned Chaotic TRNG, setting values, 0V low and 3V high on Vpulse, 1.2V on V-ref, 3.3V on VDD, and 0V on VSS, are used.

• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3711-3716
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• 2021

The addition of ferric ferrocyanide (Prussian blue; PB) to adsorbents could enhance the adsorption performance of ¹³³Cs. Toward this goal, we present a heterogeneously integrated carbonaceous material platform consisting of PB in direct contact with CO₂-activated carbon filters (PB-CACF). The resulted sample retains 24.39% more PB than vice versa probed by the ultraviolet-visible spectrometer. We leverage this effect to capture ¹³³Cs in the aqueous environment via the increase in ionic strength and micropores. We note that the amount of PB was likely to be the key factor for ¹³³Cs adsorption compared with specific surface characteristics. The revealed adsorption capacity of PB-CACF was 21.69% higher than the bare support. The adsorption characteristics were feasible and spontaneous. Positive values of 𝜟H^o and 𝜟S^o show the endothermic nature and increased randomness. Based on the concept of capturing hazardous materials via hazardous materials, our work will be of interest within the relevant academia for collecting radionuclides in a sufficient manner.