• Journal of the Korean Institute of Telematics and Electronics A
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• v.29A no.9
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• pp.56-64
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• 1992

Because of a small bandgap energy, a high doping density, and a low operating temperature, the dark current in HgCdTe photodiode is almost composed of a tunneling current. The tunneling current is devided into an indirect tunneling current via traps and a band-to-band direct tunneling current. The indirect tunneling current dominates the dark current for a relatively high temperature and a low reverse bias and forward bias. For a low temperature and a high reverse bias the direct tunneling current dominates. In this paper, to verify the tunneling currents in HgCdTe photodiode, the new tunneling-recombination equation via trap is introduced and tunneling-recombination current is calculated. The new tunneling-recombination equation via trap have the same form as SRH (Shockley-Read-Hall) generation-recombination equation and the tunneling effect is included in recombination times in this equation. Chakrabory and Biswas's equation being introduced, band to band direct tunneling current are calculated. By using these equations, HgCdTe (mole fraction, 0.29 and 0.222) photodiodes are analyzed. Then the temperature dependence of the tunneling-recombination current via trap and band to band direct tunneling current are shown and it can be known what is dominant current according to the applied bias at athe special temperature.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.89-96
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• 2018

When a fault occurs in a power system, the existing analytic models for the power system fault diagnosis could generate multiple solutions under the condition of one or more protective relays (PRs) and/or circuit breakers (CBs) malfunctioning, and/or an alarm or alarms of these PRs and/or CBs failing. Therefore, this paper presents an improved analytic model addressing the above problem. It takes into account the interaction between the uncertainty involved with PR operation and CB tripping and the uncertainty of the alarm reception, which makes the analytic model more reasonable. In addition, the existing analytic models apply the penalty function method to deal with constraints, which is influenced by the artificial setting of the penalty factor. In order to avoid the penalty factor's effects, this paper transforms constraints into an objective function, and then puts forward an improved immune clonal multi-objective optimization algorithm to solve the optimal solution. Finally, the cases of the power system fault diagnosis are served for demonstrating the feasibility and efficiency of the proposed model and method.

• Journal of Power Electronics
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• v.12 no.5
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• pp.787-799
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• 2012

Real and reactive power flows on a transmission line interact inherently. This situation degrades power flow controller performance when independent real and reactive power flow regulation is required. In this study, a quasi multi-pulse interline power flow controller (IPFC), consisting of eight six-pulse voltage source converters (VSC) switched at the fundamental frequency is proposed to control real and reactive power flows dynamically on a transmission line in response to a sequence of set-point changes formed by unit-step reference values. It is shown that the proposed hybrid fuzzy-PI commanded IPFC shows better decoupling performance than the parameter optimized PI controllers with analytically calculated feed-forward gains for decoupling. Comparative simulation studies are carried out on a 4-machine 4-bus test power system through a number of case studies. While only the fuzzy inference of the proposed control scheme has been modeled in MATLAB, the power system, converter power circuit, control and calculation blocks have been simulated in PSCAD/EMTDC by interfacing these two packages on-line.

• Journal of KIISE
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• v.42 no.5
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• pp.601-608
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• 2015

In order to answer questions successfully on behalf of the human contestant in DeepQA environments such as 'Jeopardy!', the American quiz show, the computer needs to have the capability of fast temporal and spatial reasoning on a large-scale commonsense knowledge base. In this paper, we present a hybrid spatial reasoning algorithm, among various efficient spatial reasoning methods, for handling directional and topological relations. Our algorithm not only improves the query processing time while reducing unnecessary reasoning calculation, but also effectively deals with the change of spatial knowledge base, as it takes a hybrid method that combines forward and backward reasoning. Through experiments performed on the sample spatial knowledge base with the hybrid spatial reasoner of our algorithm, we demonstrated the high performance of our hybrid spatial reasoning algorithm.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2286-2288
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• 2001

In this paper, a drive system of induction motor with high performance is realized on the viewpoint of the design and experiment, using the DSP (TMS320F240). The speed controller for induction motor drive system is designed on the basis of a neuro-fuzzy network. The neuro-fuzzy controller acts as a feed-forward controller that provides the right control input for the plant and accomplishes error back-propagation algorithm through the network. The proposed network is used to achieve the high speedy calculation of the space vector PWM (Pulse Width Modulation) and to build the neuro-fuzzy control algorithm, for the real-time control. The proposed neuro-fuzzy algorithm on the basis of DSP shows that experimental results have good performance for the precise speed control of an induction motor drive system. It is confirmed that the proposed controller could provide more improved control performance than conventional v/f vector controllers through the experiment.

• Steel and Composite Structures
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• v.24 no.6
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• pp.679-688
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• 2017

A GFRP-concrete composite bridge deck is presented in this paper. This composite deck is composed of concrete and a GFRP plate and is connected by GFRP perfobond (PBL) shear connectors with penetrating GFRP rebar. There are many outstanding advantages in mechanical behavior, corrosion resistance and durability of this composite deck over conventional reinforced concrete decks. To analyze the shear and flexural performance of this GFRP-concrete composite deck, a static loading experiment was carried out on seven specimens. The failure modes, strain development and ultimate bearing capacity were thoroughly examined. Based on elastic theory and strain-based theory, calculation methods for shear and flexural capacity were put forward and revised. The comparison of tested and theoretical capacity results showed that the proposed methods could effectively predict both the flexural and shear capacity of this composite deck. The ACI 440 methods were relatively conservative in predicting flexural capacity and excessively conservative in predicting shear capacity of this composite deck. The analysis of mechanical behavior and the design method can be used for the design of this composite deck and provides a significant foundation for further research.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.2830-2838
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• 2021

This work deals with the assessment of the burnup capabilities of the Serpent Monte Carlo code to predict spent nuclear fuel (SNF) isotopic concentrations for low-enriched uranium (LEU) fuel at different burnup levels up to 47 MWd/kgU. The irradiation of six UO₂ experimental samples in three different VVER-1000 reactor units has been simulated and the predicted concentrations of actinides up to ²⁴⁴Cm have been compared with the corresponding measured values. The results show a global good agreement between calculated and experimental concentrations, in several cases within the margins of the nuclear data uncertainties and in a few cases even within the reported experimental uncertainties. The differences in the performances of the JEFF3.1.1, ENDF/B-VII.1 and ENDF/B-VIII.0 nuclear data libraries (NDLs) have also been assessed and the use of the newly released ENDF/B-VIII.0 library has shown an increased accuracy in the prediction of the C/E's for some of the actinides considered, particularly for the plutonium isotopes. This work represents a step forward towards the validation of advanced simulation tools against post irradiation experimental data and the obtained results provide an evidence of the capabilities of the Serpent Monte-Carlo code with the associated modern NDLs to accurately compute SNF nuclide inventory concentrations for VVER-1000 type reactors.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.305-319
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• 2019

The prediction of the sum of container is very important in the field of container transport. Many influencing factors can affect the prediction results. These factors are usually composed of many variables, whose composition is often very complex. In this paper, we use gray relational analysis to set up a proper forecast index system for the prediction of the sum of containers in foreign trade. To address the issue of the low accuracy of the traditional prediction models and the problem of the difficulty of fully considering all the factors and other issues, this paper puts forward a prediction model which is combined with a back-propagation (BP) neural networks and the support vector machine (SVM). First, it gives the prediction with the data normalized by the BP neural network and generates a preliminary forecast data. Second, it employs SVM for the residual correction calculation for the results based on the preliminary data. The results of practical examples show that the overall relative error of the combined prediction model is no more than 1.5%, which is less than the relative error of the single prediction models. It is hoped that the research can provide a useful reference for the prediction of the sum of container and related studies.

• Journal of Korea Trade
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• v.26 no.1
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• pp.99-112
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• 2022

Purpose - This paper empirically investigates via a spatial lag model from the perspective of space economy to find the influencing factors of South Korea's OFDI along with 60 countries. Design/methodology - In the study of regional economic phenomena, we must first test the corresponding spatial correlation, and on this basis, complete the construction of the spatial model. For the target research object, after testing the spatial correlation, if there is spatial correlation, a spatial measurement model is needed. This paper uses the global Moran's I index for calculation. Based on the characteristics and research needs of the research object, this paper selects the spatial lag model to verify the existence of the spatial effect and factors affecting OFDI. Findings - Our results show that export scale, infrastructure, technology level, political stability, resource endowment, market size, distance and labor cost have a certain impact on Korea's OFDI, but at present the distance and market size factors are the most important influencing factors for South Korea's OFDI, The technical level and political stability have little effect on South Korea's OFDI, and are not main factors determining South Korea's OFDI. Originality/value - Through spatial measurement verification, it was found that the spatial effect has a significant impact on OFDI, along with more than 60 countries. On this basis, relevant suggestions are put forward, which have strong practical significance for South Korea's OFDI to achieve healthy and sustainable development.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.4
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• pp.185-194
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• 2023

Currently, drones are used in various fields such as transportation, agriculture and military. Especially, drones for military use are developed and utilized in many ways such as reconnaissance and bombing to minimize one's own damages. Nevertheless, they are developed as new weapons of modern types, so it is difficult to use them together with existing weapons. In this study, a drone program for effective bombing of mortar, which is often used in modern warfare, is developed. In mortar, a forward soldier comprehends the location of enemy for its distance and altitude, input them in data computer of launching angle, and applies the result value to cannon to launch. However, the existing method has low accuracy of bombing because observing shall be done within 1km from the target, and measuring accurate direction and velocity of the wind is difficult. Whereas, in the program of this study, the location of target, GPS, direction and velocity of the wind, and altitude are measured through drone. Each digit is used to calculate bombing specification for optimal bombing through the calculating formula of launching angle. In addition, when specifications are input in the program, the calculation is done automatically, so that it can be used in various mortars and shells. With the use of the program in this study, the location of enemy can be comprehended, and bombing specifications can be calculated quickly. It also enables the intensity of the wind to be applied for accurate bombing.