Sung-Yul Kim

Measurement of femoral neck anteversion in 3D. Part 2:3D modelling method

Femoral neck anteversion is the torsion of the femoral head with reference to the distal femur. Conventional methods that use cross-sectional computed tomography (CT), magnetic resonance or ultrasound images to estimate femoral anteversion have met with several problems owing to the complex, three-dimensional (3D) structure of the femur. These problems include not only the difficulty of defining the direction of the femoral neck axis and condylar line but also the dependency upon patient positioning. In particular, the femoral neck axis, the direction of the femoral head, known as the major source of error, is difficult to determine from either a single or several two-dimensional (2D) cross-sectional images. A new method has been devised for the measurement of femoral anteversion using the 3D imaging technique. 3D reconstructed CT images from the femoral head and trochanter to the distal femur are used to measure the anteversion. It is necessary to remove the soft tissue from the CT images and extract just the bone part. Then, the femoral anteversion is measured from a computer-rendered femur image. The 3D imaging method is compared with both the conventional 2D method and the physical method using 20 dried femurs. For the physical method, which is used as a reference value, a special apparatus is devised. The average difference between the results of the physical method and those of the 2D CT method is 5.33°. The average difference between the results of the physical method and those of the 3D imaging method is 0.45°. Seventy-four patients, who suffer from toe-in-gait disease, are tested to compare the 3D imaging method with the conventional 2D CT method. The average difference between the 2D and 3D methods is 8.6°, and the standard is 7.43°. This method provides a very accurate and reliable measurement of femoral anteversion, as it is virtually equivalent to the direct measurement of bisected dried femur in vitro.

Reliability Evaluation of Distribution Network With DG Considering the Reliability of Protective Devices Affected by SFCL

This paper proposes a reliability model for a superconducting fault current limiter (SFCL), which is a new alternative in limiting the fault current recently increasing in a network. An evaluation technique for distribution reliability that uses the improved failure rate of all protective devices in a network, depending on the location of the SFCL, is also proposed. As a result, it is expected that the SFCL makes the reliability of adjacent equipment on an existing network improve, and these changes are analyzed. In addition, in order to apply the effect of the intermittent output of renewable-energy sources, distribution reliability indices were redefined in this paper. Case studies verify that the SFCL is effective in reducing fault currents and improving distribution reliability. These effects are analyzed with respect to the location of the SFCL in a case study system.

Distribution reliability evaluation affected by superconducting fault current limiter

Distribution network has become more and more complex as mesh network to improve the distribution system reliability and increase the flexibility and agility of network operation. Also, as electric power demand of customers is constantly increasing, more bulk power systems are needed to install in a network. By development of renewable energies and high-efficient facilities and deregulated electricity market, moreover, the amount of distributed resource is considerably increasing in distribution network consequently. These changes make fault current increase. Therefore, the fault current will exceed a circuit breaker capacity. In order to solve this problem, replacing breaker, changing operation mode of system and rectifying transformer parameters can be taken into account. The superconducting fault current limiter(SFCL) is one of the most promising power apparatus.

Non-linear registration for brain images by maximising feature and intensity similarities with a Bayesian framework.

The objective of this work was to provide a new, precise registration of the cortical mantle with a non-linear transformation. Image registration is broadly classified into two types, using intensity similarity and feature similarity. Whereas the former approach has merit in global brain matching, the latter provides a fast registration centred on a region of interest. The hybrid registration proposed in this paper was achieved using a Bayesian framework, which consisted of a likelihood model including intensity similarity and a prior model including feature information and a smoothing constraint. In this approach, each voxel was spatially transformed, so that the distance between corresponding features was shortened and also so that the intensity correlation was maximised. The result of the hybrid method clearly showed a good match of global brain (r=0.930) by including intensity similarity. Moreover, this method compensated for the approximated sulcus of the feature-based method with intensity information, so that the geometric shape and thickness of the sulcus at the feature-defined region was likely to be registered. The accuracy in the feature-defined area was improved by 33.4% and 7.5% compared with feature-based and intensity-based methods, respectively.

Transmission Network Expansion Planning for the Penetration of Renewable Energy Sources - Determining an Optimal Installed Capacity of Renewable Energy Sources

Due to global environmental regulations and policies with rapid advancement of renewable energy technologies, the development type of renewable energy sources (RES) in power systems is expanding from small-scale distributed generation to large-scale grid-connected systems. In the near future, it is expected that RES achieves grid parity which means the equilibrium point where the power cost of RES is equal to the power costs of conventional generators. However, although RES would achieve the grid parity, the cost related with development of large-scale RES is still a big burden. Furthermore, it is hard to determine a suitable capacity of RES because of their output characteristics affected by locations and weather effects. Therefore, to determine an optimal capacity for RES becomes an important decision-making problem. This study proposes a method for determining an optimal installed capacity of RES from the business viewpoint of an independent power plant (IPP). In order to verify the proposed method, we have performed case studies on real power system in Incheon and Shiheung areas, South Korea.

An optimal location for superconducting fault current limiter considering distribution reliability

As electric power demand has constantly been increasing, more bulk power systems have been installed in a network. For environmental and technical reasons, the amount of distributed resources is increasing considerably in a distribution network. Therefore, distribution networks have become more complex mesh networks, which improve the reliability of distribution system and the flexibility of network operation. These changes cause fault current to increase. As a result, the fault current will exceed the rated capacity of a circuit breaker in a network. In order to solve this problem, replacing breaker, changing operation mode of system and rectifying transformer parameters can be taken into account. Considering technical and economical aspects, however, one of the most promising power apparatuses is a superconducting fault current limiter(SFCL).

The Optimal Operation for Community Energy System Using a Low-Carbon Paradigm with Phase-Type Particle Swarm Optimization

By development of renewable energy and more efficient facilities in an increasingly de- regulated electricity market, the operation cost of distributed generation (DG) is becoming more com- petitive. International environmental regulations of the leaking carbon become effective to reinforce global efforts for a low-carbon paradigm. Through increased DG, operators of DG are able to supply electric power to customers who are connected directly to DG as well as loads that are connected to en- tire network. In this situation, a community energy system (CES) with DGs is a new participant in the energy market. DGs purchase price from the market is different from the DGs sales price to the market due to trans- mission service charges and other costs. Therefore, CES who owns DGs has to control the produced electric power per hourly period in order to maximize profit. Considering the international environ- ment regulations, CE will be an important element to decide the marginal cost of generators as well as the classified fuel unit cost and units efficiency. This paper introduces the optimal operation of CESs DG connected to the distribution network con- sidering CE. The purpose of optimization is to maximize the profit of CES. A Particle Swarm Optimi- zation (PSO) will be used to solve this complicated problem. The optimal operation of DG represented in this paper would guide CES and system operators in determining the decision making criteria.

Notch filter design using theα-scaled sampling kernel and its application to power line noise removal from ECG signals

A new design approach is proposed for sharp notch FIR filters, whereby a modified alpha- scaled sampling kernel is utilized. In particular, the proposed approach provides closed-form formulae for filter coefficients, leading to an effective design procedure for sharp notch filters with given specifications. Simulation results demonstrate that the proposed design method yields high performance in removing the power line interference from ECG signals.

Determining Optimal Installed Capacity and the Interconnected Bus of Renewable Energy Sources Considering the Cost of Energy Not Supplied

Due to environmental regulation and technical improvements, renewable energy sources (RES) are increasingly penetrated and operated in power systems. Clean energy technologies have become cost-competitive with conventional power systems, and in the near future, the generation cost of RES is expected to approach grid parity. In this situation, it should be considered an extraordinarily important issue to be maximized resulting in utilization of RES as well as to develop technologies for efficiency improvement of RES. Therefore, in this paper, the method for determining an optimal installed capacity and interconnected location of RES is proposed in order to minimize the cost of energy not supplied, which can contribute to improve distribution reliability.

The optimal operation of distributed generation possessed by community energy system considering low-carbon paradigm

By development of renewable energy and high-efficient faculties under the environment of deregulated electricity market, the operation cost of distributed generation(DG) becomes more competitive. Also, international environmental regulations of the leaking carbon become effective to keep pace with the global efforts for low-carbon paradigm. These contribute to spread out the business of DG. Therefore, the operator of DG is able to supply electric power to customers who are connected directly to DG as well as loads that are connected to entire network. In this situation, community energy system(CES) having DGs is recently a new participant in the energy market. DGs purchase price from the market is different from the DGs sales price to the market due to the transmission service charges and etc. Therefore, CES who owns DGs has to control the produced electric power per hourly period in order to maximize the profit. Considering the international environment regulation, CE newly will be an important element to decide the marginal cost of generators as well as the classified fuel unit cost and units efficiency. This paper introduces the optimal operation of CESs DG connected to the distribution network considering CE. The purpose of optimization is to maximize the profit of CES and Particle Swarm Optimization (PSO) will be used to solve this problem. The optimal operation of DG represented in this paper would guide to CES and system operator for determining the decision making criteria.