• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.5
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• pp.594-600
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• 2006

The optimization has been performed to search an economical running pattern in the view point of trip time and energy consumption. Fuzzy control model has been applied to build the meta-model. To identify the structure and its parameters of a fuzzy model, fuzzy c-means clustering method and differential evolutionary scheme ate utilized, respectively. As a result, two meta-models for trip time and energy consumption are constructed. The optimization to search an economical running pattern is achieved by differential evolutionary scheme. The result shows that the proposed methodology is very efficient and conveniently applicable to the operation of railway system.

• ETRI Journal
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• v.46 no.5
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• pp.793-805
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• 2024

Entanglement is crucial for achieving quantum advantages. However, in the context of quantum machine learning, existing optimization strategies for generating quantum classifier circuits often result in unentangled circuits, indicating an underutilization of the entanglement effect needed to learn complex patterns. In this study, we proposed a novel metaheuristic approach-genetic algorithm-for designing a quantum kernel classifier that incorporates expressive entanglement. This classifier utilizes a loopless entanglement-directed graph, where each directed edge represents the entanglement between the target and control qubits. The proposed method consistently outperforms classical and quantum baselines across various artificial and actual datasets, achieving improvements up to 32.4% and 17.5%, respectively, compared with the best model among all other baselines. Moreover, this method successfully reconstructs the hidden entanglement structures underlying artificial datasets. The results also demonstrate that the optimized circuits exhibit diverse entanglement variations across different datasets, indicating the versatility of the proposed approach.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.715-725
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• 2020

In this paper, we propose an optimization scheme for a k-Nearest Neighbor(k-NN) query, which finds k objects closest to the query in the high dimensional feature vectors. The k-NN query is converted and processed into a range query based on the range that is likely to contain k data. In this paper, we propose an optimization scheme using DNN model to derive an optimal range that can reduce processing cost and accelerate search speed. The entire system of the proposed scheme is composed of online and offline modules. In the online module, a query is actually processed when it is issued from a client. In the offline module, an optimal range is derived for the query by using the DNN model and is delivered to the online module. It is shown through various performance evaluations that the proposed scheme outperforms the existing schemes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2C
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• pp.217-225
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• 2009

Tone injection scheme has been known as one of peak to average power ratio (PAPR) reduction methods deployable to multi-carrier system like orthogonal frequency division multiplexing (OFDM). The basic idea in tone injection scheme is to enforce the constellation size larger so that each of original constellation points is mapped into the preassigned distinct locations. According to the tone injection scheme, it increases symbol power highly induced inherently by expanding constellation to get optimal PAPR reduction. In the other hand, to get optimal power increase, the PAPR would be reduced insufficiently with limited tone injection signal. To withstand these problems, this paper consider the reduction of the PAPR and power increase problem simultaneously, Toward this, the tone injection scheme accomplished by employing the weighted sum genetic algorithm which has been utilized to solve multi-objective optimization problem (MOOP). The simulation results verifies that the proposed scheme can control the effective PAPR performance and alleviation of power increase flexibly by the weight value at the expense of relatively low complexity.

• International Journal of Automotive Technology
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• v.8 no.3
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• pp.327-335
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• 2007

A new optimization scheme and some key techniques are proposed in the development of a vehicle glass drop design software system. The key issues of the design system are how to regenerate the glass surface and make the vehicle glass drop down along the glass channels. To resolve these issues, a parameterized model was created at first, in which the optimizing method and Knowledge Fusion techniques were adopted the optimized process was then written into the glass drop design system by coding with C language and UGS/Open Application Programme Interface functions etc. Therefore, the designer or engineer can simulate the process of glass dropping along the channels to assess the potential interference between glass and door accessory by using this software system. All of the testing results demonstrate the validity of the optimizing scheme, and the parametric design software effectively solves the key issues on development of the door accessory package.

• Korean Management Science Review
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• v.25 no.2
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• pp.25-42
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• 2008

CDMA/TOD with asymmetric capacity allocation between uplink and downlink is a highly attractive solution to support the next generation mobile systems. This is because flexible asymmetric allocation of capacity to uplink and downlink usually improves the utilization of the limited bandwidth. In this paper, we mathematically formulate an optimal timeslot and code allocation problem, which is to maximize the total utility considering the numbers of codes(channels) allocated to each data class and the forced terminations of previously allocated codes. We also suggest a real-time integrated timeslot and code allocation scheme using Lagrangean relaxation and subgradient optimization techniques. Experimental results show that the proposed scheme provides high-quality solutions in a fast time.

• International journal of advanced smart convergence
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• v.1 no.2
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• pp.34-38
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• 2012

The recent increase in use of the IEEE 802.15.4 standard for wireless connectivity in personal area networks makes of it an important technology for low-cost low-power wireless personal area networks. Studies showed that voice communications over IEEE 802.15.4 networks is feasible by Guaranteed Time Slot (GTS) allocation; but there are some constraints to accommodate voice transmission beyond two hops due to the excessive transmission delay. In this paper, we propose a GTS allocation scheme for bidirectional voice traffic in IEEE 802.15.4 multihop networks with the goal of achieving fairness and optimization of resource allocation. The proposed scheme uses a greedy algorithm to allocate GTSs to devices for successful completion of voice transmission with efficient use of bandwidth while considering closest devices with another factor for starvation avoidance. We analyze and validate the proposed scheme in terms of fairness and resource optimization through numeral analysis.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.108-114
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• 2014

This paper proposes a generation method of a navigation guidance direction and a fuzzy controller to achieve the autonomous navigation of a mobile robot using a particle swarm optimization(PSO) scheme in unknown environments. The proposed navigation guidance direction is the direction that leads a mobile robot to arrive a target point simultaneously with avoiding obstacles efficiently according to the surrounding local informations. It is generated by selecting the most suitable direction of the many directions in the surrounding environment using a particle swarm optimization scheme. Also, a robot can reach a target point with avoiding the various obstacles by controlling the robot so that it can move from its current orientation to the navigation guidance direction using the proposed fuzzy controller. Simulation results are presented to show the feasibility and validity of the proposed robot navigation scheme.

• Current Optics and Photonics
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• v.5 no.6
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• pp.711-720
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• 2021

A novel optical hybrid device that doubles the multilevel demodulation resolution by adding the optical interferometer with a waveguide crossover is proposed, theoretically analyzed and experimentally verified. We report two types of all-passive phase control schemes that will be referred to as a phase compensation scheme and a phase optimization scheme. We also apply the proposed phase control schemes to a 45° optical hybrid consisting of two parallel 90° optical hybrids together with the proposed phase control scheme for demodulating 8-level differential phase shift keying optical signals. Octagonal phase response with low wavelength sensitive excess loss of <0.8 dB over 31-nm-wide spectral range will be demonstrated in the InP-based material platform.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.15-24
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• 2022

At present, there are few studies on signal control of pedestrian traffic flow and non-motor traffic flow at intersections. Research on the optimization scheme of mixed traffic flow signal control can coordinate and control the overall traffic flow of pedestrians, non-motor vehicles and motor vehicles, which is of great significance to improve the congestion at intersections. For the traffic optimization of intersections, this paper starts from two aspects: channelization optimization and phase design, and reduces the number of conflict points at intersections from spatial and temporal right-of-way allocation respectively. Taking the classical signal timing method as the theoretical basis, and aiming at ensuring the safety and time benefit of traffic travelers, a channelization optimization and signal control scheme of the intersection is proposed. The channelization and phase design methods of intersections with motor vehicles, non-motor vehicles and pedestrians as objects are discussed, and measures to improve the channelization optimization of intersections are proposed. A multi-objective optimization model of intersection signal control was established, and the model was solved based on NSGA-II algorithm.