• Phonetics and Speech Sciences
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• v.9 no.4
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• pp.77-89
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• 2017

This study investigates the phonetic meaning of clarity and turbidity(淸濁) that has been used in psychoacoustics, musicology, and linguistics in both the East and the West. With a view to clarifying the phonetic meaning of clarity and turbidity, this study conducts three perception tests. First, 34 subjects were asked to take one of Clear and Turbid by forced choice for 5 pure and complex tones, respectively, ranging from A2 to A6 differing by octave. Second, they were asked to select between the two choices for 25 pure and complex tones, respectively, ranging from A2 to A4 differing by semitone. Third, they were asked to opt for one of the two choices for 8 different vowels of different formant and fundamental frequencies. Results showed that there is a certain range of tone which is perceived as clear, that clarity level increases as fundamental frequency increases, and that pure tones have a higher level of clarity than complex ones, fundamental frequency being equal. Results also showed that vocal tract resonance enhances clarity level on the whole, and that lower vowels have a higher level of clarity than higher ones. This study is significant in that it demonstrates that clarity level is proportional to fundamental frequency and the first formant frequency, all else being equal.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.2
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• pp.150-159
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• 2009

The heterogeneous fleet vehicle routing problem(HVRP) is a variant of the classical vehicle routing problem in which customers are served by a heterogeneous fleet of vehicles with various capacities, fixed costs and variable costs. We propose a new conceptual HVRPCR(HVRP with customer restriction) model including additional customer restrictions in HVRP. In this paper, we develop hybrid particle swarm optimization(HPSO) algorithm with 2-opt and node exchange technique for HVRP. The solution representation is a n-dimensional particle for HVRP with N customers. The decoding method for this representation starts with the transformation of particle into a priority list of customer to enter route and limit of vehicle to serve each customer. The vehicle routes are then constructed based on the customer priority list and limit of vehicle to serve. The proposed algorithm is tested using 8 benchmark problems and it consistently produces high-quality solutions, including new best solutions. The numerical results show that the proposed algorithm is robust and efficient.

• The KIPS Transactions:PartC
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• v.12C no.6 s.102
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• pp.793-798
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• 2005

We focus on the RP (Rendezvous Point) system model in the multicast network based on BcN (Broadband Convergence Network) integrating broadcasting, telecommunication and Internet with one. Based on the condition multiple queues with different service and single server, when the arrivals tome in group with the site of the group geometrically distributed, we define the relationship between incoming arrival rate and corresponding buffer size. We also investigate the Profit according to both Service Provider and Network Operator Then we make a decision whether a new service request is accepted or not based on given interning rate range.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.193-201
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• 2023

In this paper, we consider the maximum scatter traveling salesman problem (MSTSP), a travelling salesman problem (TSP) variant. The problem aims to maximize the minimum length edge in a salesman's tour that travels each city only once in a network. It is a very complicated NP-hard problem, and hence, exact solutions can be found for small sized problems only. For large-sized problems, heuristic algorithms must be applied, and genetic algorithms (GAs) are found to be very successfully to deal with such problems. So, this paper develops a hybrid GA (HGA) for solving the problem. Our proposed HGA uses sequential sampling algorithm along with 2-opt search for initial population generation, sequential constructive crossover, adaptive mutation, randomly selected one of three local search approaches, and the partially mapped crossover along with swap mutation for perturbation procedure to find better quality solution to the MSTSP. Finally, the suggested HGA is compared with a state-of-art algorithm by solving some TSPLIB symmetric instances of many sizes. Our computational experience reveals that the suggested HGA is better. Further, we provide solutions to some asymmetric TSPLIB instances of many sizes.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.12-22
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• 2024

The travelling salesman problem is very famous and very difficult combinatorial optimization problem that has several applications in operations research, computer science and industrial engineering. As the problem is difficult, finding its optimal solution is computationally very difficult. Thus, several researchers have developed heuristic/metaheuristic algorithms for finding heuristic solutions to the problem instances. In this present study, a new hybrid genetic algorithm (HGA) is suggested to find heuristic solution to the problem. In our HGA we used comprehensive sequential constructive crossover, adaptive mutation, 2-opt search and a new local search algorithm along with a replacement method, then executed our HGA on some standard TSPLIB problem instances, and finally, we compared our HGA with simple genetic algorithm and an existing state-of-the-art method. The experimental studies show the effectiveness of our proposed HGA for the problem.

• The Journal of Korean Academy of Prosthodontics
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• v.38 no.3
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• pp.321-327
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• 2000

Statement of Problem. As a standard means of diagnostics, an orthopantomogram(OPT) permits to measure the vertical and mesiodistal dimension of available bone at the desired implant site with the help of suitable radioopaque references. Based on the clinical investigation of the dentition and the edentulous sites, information upon the width of the implant site can be obtained and documented in the dental scheme. Both findings permit together systematic primary planning for endosteal implants. Purpose of Study. Contents of the present article are the representation of a semiquantitative classification of available bone with the aim to simplify the primary phase of a systematic implant planning. Results. Thus the ASCIi- system permits a clear protocol of bone findings for the implant case with all information available during the primary appointment for treatment planning as a basis of further diagnostic and therapeutic measures. Conclusion. With the ASCIi system, important parameters such as alveolar height and sub-crestal alveolar width can be documented systematically, easily and time saving in the dental scheme as a basis for exact treatment planning.

• IE interfaces
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• v.23 no.2
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• pp.147-155
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• 2010

Reliability allocation is defined as a problem of determination of the reliability for subsystems and components to achieve target system reliability. The determination of both optimal component reliability and the number of component redundancy allowing mixed components to maximize the system reliability under resource constraints is called reliability-redundancy allocation problem(RAP). The main objective of this study is to suggest a mathematical programming model and a hybrid parallel genetic algorithm(HPGA) for reliability-redundancy allocation problem that decides both optimal component reliability and the number of component redundancy to maximize the system reliability under cost and weight constraints. The global optimal solutions of each example are obtained by using CPLEX 11.1. The component structure, reliability, cost, and weight were computed by using HPGA and compared the results of existing metaheuristic such as Genetic Algoritm(GA), Tabu Search(TS), Ant Colony Optimization(ACO), Immune Algorithm(IA) and also evaluated performance of HPGA. The result of suggested algorithm gives the same or better solutions when compared with existing algorithms, because the suggested algorithm could paratactically evolved by operating several sub-populations and improve solution through swap, 2-opt, and interchange processes. In order to calculate the improvement of reliability for existing studies and suggested algorithm, a maximum possible improvement(MPI) was applied in this study.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.3
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• pp.304-310
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• 2014

This paper presents the analysis of the coupling coefficient(k), Q value of the resonator, and the optimum loaded resistance at Rx for the magnetically coupled wireless power transmission using two loops(resonators). In addition, the metamaterial, conductor, and the relay methods have been used in order to improve the limitation problem of transmission efficiency by using the figure of merit. We have achieved the increase of transmission efficiency about 11~60 % using the proposed methods by analyzing and comparing the results based on EM simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1121-1141
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• 2020

We propose a robust visual object tracking algorithm fusing a convolutional neural network tracker trained offline from a large number of video repositories and a color histogram based tracker to track objects for mixing immersive audio. Our algorithm addresses the problem of occlusion and large movements of the CNN based GOTURN generic object tracker. The key idea is the offline training of a binary classifier with the color histogram similarity values estimated via both trackers used in this method to opt appropriate tracker for target tracking and update both trackers with the predicted bounding box position of the target to continue tracking. Furthermore, a histogram similarity constraint is applied before updating the trackers to maximize the tracking accuracy. Finally, we compute the depth(z) of the target object by one of the prominent unsupervised monocular depth estimation algorithms to ensure the necessary 3D position of the tracked object to mix the immersive audio into that object. Our proposed algorithm demonstrates about 2% improved accuracy over the outperforming GOTURN algorithm in the existing VOT2014 tracking benchmark. Additionally, our tracker also works well to track multiple objects utilizing the concept of single object tracker but no demonstrations on any MOT benchmark.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.12
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• pp.638-644
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• 2017

Optimal cooling operation algorithm was developed based on a simulation case of a single family house model equipped with renewable energy facility. EnergyPlus simulation results were used as virtual test data. The model contained three energy storage elements: thermal heat capacity of the living room, chilled water storage tank, and battery. Their charging and discharging schedules were optimized so that daily electricity bill became minimal. As an optimization tool, linear programming was considered because it was possible to obtain results in real time. For its adoption, EnergyPlus-based house model had to be linearly approximated. Results of this study revealed that dynamic cooling load of the living room could be approximated by a linear RC model. Scheduling based on the linear programming was then compared to that by a nonlinear optimization algorithm which was made using GenOpt developed by a national lab in USA. They showed quite similar performances. Therefore, linear programming can be a practical solution to optimal operation scheduling if linear dynamic models are tuned to simulate their real equivalents with reasonable accuracy.