• The Pure and Applied Mathematics
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• v.24 no.1
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• pp.45-51
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• 2017

In this paper, we propose an accelerating scheme of convergence of numerical solutions of fuzzy non-linear equations. Numerical experiments show that the new method has significant acceleration of convergence of solutions of fuzzy non-linear equation. Three-dimensional graphical representation of fuzzy solutions is also provided as a reference of visual convergence of the solution sequence.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.1
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• pp.21-28
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• 2005

This paper proposes a new method for accelerating the search speed of genetic algorithms by taking derivative evaluation and conditional random selection into account in their evolution process. Derivative evaluation makes genetic algorithms focus on the individuals whose fitness is rapidly increased. This accelerates the search speed of genetic algorithms by enhancing exploitation like steepest descent methods but also increases the possibility of a premature convergence that means most individuals after a few generations approach to local optima. On the other hand, derivative evaluation under a premature convergence helps genetic algorithms escape the local optima by enhancing exploration. If GAs fall into a premature convergence, random selection is used in order to help escaping local optimum, but its effects are not large. We experimented our method with one combinatorial problem and five complex function optimization problems. Experimental results showed that our method was superior to the simple genetic algorithm especially when the search space is large.

• Journal of applied mathematics & informatics
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• v.28 no.3_4
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• pp.663-677
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• 2010

In this paper, the generalized SOR-like methods are presented for solving the saddle point problems. Based on the SOR-like methods, we introduce the uncertain parameters and the preconditioned matrixes in the splitting form of the coefficient matrix. The necessary and sufficient conditions for guaranteeing its convergence are derived by giving the restrictions imposed on the parameters. Finally, numerical experiments show that this methods are more effective by choosing the proper values of parameters.

• Bulletin of the Korean Mathematical Society
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• v.27 no.2
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• pp.165-172
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• 1990

In this paper, we study a method which speeds up the convergence of monotone iterations and give some numerical examples of the types (2) and (3). In [2] this method has been applied to a system of hyperbolic differential equations with initial and boundary conditions.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.11
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• pp.1386-1398
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• 2011

Slow fashion can be viewed as an activism that provides an alternative solution to the problematic issues of fast fashion in a practical sense; however, (from a theoretical point of view) it is a fashion phenomenon arising from the criticism of an accelerating society. Slowness emphasizes the virtues of moderation. Slowness refers to the recovery of human ethics that have been neglected due to the goal-oriented nature of an accelerating society. Slowness can solve the problem of conformity and discrimination in society through pluralism and respect for local indigenousness. The characteristics of slow fashion can be defined by the aesthetic values of circularity, sustainability, moderation, expressivity and convergence. This includes the beauty of circularity (which views the relationships of all processes as organic), the beauty of sustainability (which ensures the maintenance of continuous emotions and the durability of products that can be promoted through slow processes), the beauty of moderation (which places importance on spiritual values and the moderate use of materials), and the beauty of expressivity (which plays the role of a social messenger that facilitates social assertion). These combined values present the beauty of convergence such as the harmony of local communities and the world in a blend of the old and the new with an exchange between producers and consumers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.86-94
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• 2019

This paper describes the development of unmanned vehicle remote control system which is configured with steering and accelerating/braking hardware to improve the sense of reality and safety of control. Generally, in these case of the remote control system, a joystick-type device is used for steering and accelerating/braking control of unmanned vehicle in most cases. Other systems have been developing using simple steering wheel, but there is no function of that feedback the feeling of driving situation to users and it mostly doesn't include the accelerating/braking control hardware. The technology of feedback means that a reproducing the feeling of current driving situation through steering and accelerating/braking hardware when driving a vehicle in person. In addition to studying feedback technologies that reduce unfamiliarity in remote control of unmanned vehicles, it is necessary to develop the remote control system with hardware that can improve sense of reality. Therefore, in this study, the reliable remote control system is developed and required system specification is defined for applying force-feedback haptic control technology developed through previous research. The system consists of a steering-wheel module similar to a normal vehicle and an accelerating/braking pedal module with actuators to operate by feedback commands. In addition, the software environment configured by CAN communication to send feedback commands to each modules. To verify the reliability of the remote control system, the force-feedback haptic control algorithms developed through previous research were applied, to assess the behavior of the algorithms in each situation.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.87-94
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• 2019

IoT-based services are being released in accordance with the aging population and the demand for well-being pursuit needs. In addition to medical device companies, companies with ideas ranging from global ICT companies to startup companies are accelerating their market entry. The areas where these services are most commonly applied are health/medical, life/safety, city/energy, automotive and transportation. Furthermore, by expanding IoT technology convergence into the area of life care services, it contributes greatly to the development of service models in the public sector. It also provides an important opportunity for IoT-related companies to open up new markets. By addressing the problems of life care services that are still insufficient. We are providing opportunities to pursue the common interests of both users and workers and improve the quality of life. In order to establish IoT-based digital life care services, it is necessary to develop convergence technologies using cloud computing systems, big data analytics, medical information, and smart healthcare infrastructure.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.3 no.2
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• pp.5-16
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• 1999

We introduce a new projector for accelerating convergence of a symmetric eigenvalue problem Ax = x, and devise a power/Lanczos hybrid algorithm. Acceleration can be achieved by removing the hard-to-annihilate nonsolution eigencomponents corresponding to the widespread eigenvalues with modulus close to 1, by estimating them accurately using the Lanczos method. However, the additional Lanczos results can be obtained without expensive matrix-vector multiplications but a very small amount of extra work, by utilizing simple power-Lanczos interconversion algorithms suggested. Numerical experiments are given at the end.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.86-93
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• 2007

A new operation termed competitive generation in the processes of genetic algorithms is proposed for accelerating the optimization speed of genetic algorithms. The competitive generation devised by considering the competition of sperms for fertilization provides a good opportunity for the genetic algorithms to approach global optimum without falling into local optimum. Experimental results with typical problems showed that the genetic algorithms with competitive generation are superior to those without the competitive generation.

• The Journal of the Convergence on Culture Technology
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• v.3 no.4
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• pp.171-175
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• 2017

Recently, Training of the convolutional neural network (CNN) entails many iterative computations. Therefore, a method of accelerating the training speed through parallel processing using the hardware specifications of GPGPU is actively researched. In this paper, the operations of the feature extraction unit and the classification unit are divided into blocks and threads of GPGPU and processed in parallel. Convolution and Pooling operations of the feature extraction unit are processed in parallel at once without sequentially processing. As a result, proposed method improved the training time about 314%.