• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.2
• /
• pp.329-335
• /
• 2023

Avocado, a superfood selected by Time magazine and one of the late ripening fruits, is one of the foods with a big difference between local prices and domestic distribution prices. If this sorting process of avocados is automated, it will be possible to lower prices by reducing labor costs in various fields. In this paper, we aim to create an optimal classification model by creating an avocado dataset through crawling and using a number of deep learning-based transfer learning models. Experiments were conducted by directly substituting a deep learning-based transfer learning model from a dataset separated from the produced dataset and fine-tuning the hyperparameters of the model. When an avocado image is input, the model classifies the ripeness of the avocado with an accuracy of over 99%, and proposes a dataset and algorithm that can reduce manpower and increase accuracy in avocado production and distribution households.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.38 no.3
• /
• pp.337-344
• /
• 2014

An optimal shape design algorithm is suggested to systematically design a traditional Korean musical instrument, the Pyeongyeong. The Pyeongyeong consists of 16 different chime stones called Gyeongpyeons. The first natural vibration frequency of each Gyeongpyeon must be adjusted to its target frequency, which is determined by the traditional sound tuning method. The second and third natural frequencies must be proportional to the first natural frequency with a specific ratio (1:1.498:2.378). The key idea in our suggested design algorithm is to use the sensitivity of natural frequencies to the variation in the length of each side of a Gyeongpyeon. The dimensions of five different Gyeongpyeons are determined by following the suggested algorithm. Changes in natural frequencies with respect to local thickness variation are closely investigated to compensate for errors that may occur during manufacturing.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.53 no.8
• /
• pp.561-570
• /
• 2004

In this paper, new architectures and comprehensive design methodologies of Genetic Algorithms(GAs) based Genetically optimized Neurofuzzy Networks(GoNFN) are introduced, and a series of numeric experiments are carried out. The proposed GoNFN is based on the rule-based Neurofuzzy Networks(NFN) with the extended structure of the premise and the consequence parts of fuzzy rules being formed within the networks. The premise part of the fuzzy rules are designed by using space partitioning in terms of fuzzy sets defined in individual variables. In the consequence part of the fuzzy rules, three different forms of the regression polynomials such as constant, linear and quadratic are taken into consideration. The structure and parameters of the proposed GoNFN are optimized by GAs. GAs being a global optimization technique determines optimal parameters in a vast search space. But it cannot effectively avoid a large amount of time-consuming iteration because GAs finds optimal parameters by using a given space. To alleviate the problems, the dynamic search-based GAs is introduced to lead to rapidly optimal convergence over a limited region or a boundary condition. In a nutshell, the objective of this study is to develop a general design methodology o GAs-based GoNFN modeling, come up a logic-based structure of such model and propose a comprehensive evolutionary development environment in which the optimization of the model can be efficiently carried out both at the structural as well as parametric level for overall optimization by utilizing the separate or consecutive tuning technology. To evaluate the performance of the proposed GoNFN, the models are experimented with the use of several representative numerical examples.

• KIPS Transactions on Computer and Communication Systems
• /
• v.6 no.9
• /
• pp.377-384
• /
• 2017

The performance improvement of a single core processor has reached its limit since the circuit density cannot be increased any longer due to overheating. Therefore, the multicore and manycore architectures have emerged as viable approaches and parallel programming becomes more important. Haskell, a purely functional language, is getting popular in this situation since it naturally supports parallel programming owing to its beneficial features including the implicit parallelism in evaluating expressions and the monadic tools supporting parallel constructs. However, the performance of Haskell parallel programs is strongly influenced by the performance of the run-time system including the garbage collector. Though a memory profiling tool namely GC-tune has been suggested, we need a more systematic way to use this tool. Since GC-tune finds the optimal memory size by executing the target program with all the different possible GC options, the GC-tuning time takes too long. This paper suggests a basic divide-and-conquer method to reduce the number of GC-tune executions by reducing the search area by one-quarter for every searching step. Applying this method to two parallel programs, a maximally independent set and a K-means programs, the memory tuning time is reduced by 7.78 times with accuracy 98% on average.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.21 no.6
• /
• pp.113-125
• /
• 2017

In spite of bulk literature about the tuning of TMD, the effectiveness of TMD in reducing the seismic response of engineering structures is still in a row. This paper deals with the optimum tuning parameters of a passive TMD and simulated on MATLAB with a ten-story numerical shear building. A weighted multi-objective optimization method based on computer experiment consisting of coupled with central composite design(CCD) central composite design and response surface methodology(RSM) was applied to find out the optimum tuning parameters of TMD. After the optimization, the so-conceived TMD turns out to be optimal with respect to the specific seismic event, hence allowing for an optimum reduction in seismic response. The method was employed on above structure by assuming first the El Centro seismic input as a sort of benchmark excitation, and then additional recent strong-motion earthquakes. It is found that the RSM based weighted multi-objective optimized damper improves frequency responses and root mean square displacements of the structure without TMD by 31.6% and 82.3% under El Centro earthquake, respectively, and has an equal or higher performance than the conventionally designed dampers with respect to frequency responses and root mean square displacements and when applied to earthquakes.

• Journal of KIISE:Computer Systems and Theory
• /
• v.27 no.1
• /
• pp.44-52
• /
• 2000

This paper is contented with packet transmission scheduling problem for repeating all-to-all broadcasts in WDM optical passive-star networks in which there are N nodes and k wavelengths. It is assumed that each node has one tunable transmitter and one fixed-tuned receiver, and each transmitter can tune to k different wavelengths. The tuning delay represents the time taken for a transmitter to tune from one wavelength to another and represented as ${\delta}$(>0) in units of packet durations. We define all-to-all broadcast as the one where every node transmits packets to all the other nodes except itself. So, there are in total N(N-1) packets to be transmitted for an all-to-all broadcast. The optimal transmission scheduling is to schedule In such a way that all packets can be transmitted within the minimum time. In this paper, we propose the condition for optimal transmission schedules and present an optimal transmission scheduling algorithm for arbitrary values of N, k, and ${\delta}$ The cycle length of the optimal schedules is $max{[\frac{N}{k}](M-1)$, $k{\delta}+N-1$}.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.10 no.2
• /
• pp.138-145
• /
• 2000

A identification algorithm that finds optimal fuzzy membership functions and rule base to fuzzy model isproposed and a fuzzy controller is designed to get more accurate position and velocity control of wheeled mobile robot. This procedure that is composed of three steps has its own unique process at each step. The elements of output term set are increased at first step and then the rule base is varied according to increase of the elements. The adjusted system is in competition with system which doesn't include any increased elements. The adjusted system will be removed if the system lost. Otherwise, the control system is replaced with the adjusted system. After finished regulation of output term set and rule base, searching for input membership functions is processed with constraints and fine tuning of output membership functions is done.

• Smart Structures and Systems
• /
• v.19 no.6
• /
• pp.665-678
• /
• 2017

In this paper the tuned mass-damper-inerter (TMDI) is considered for passive vibration control and energy harvesting in harmonically excited structures. The TMDI couples the classical tuned mass-damper (TMD) with a grounded inerter: a two-terminal linear device resisting the relative acceleration of its terminals by a constant of proportionality termed inertance. In this manner, the TMD is endowed with additional inertia, beyond the one offered by the attached mass, without any substantial increase to the overall weight. Closed-form analytical expressions for optimal TMDI parameters, stiffness and damping, given attached mass and inertance are derived by application of Den Hartog's tuning approach to suppress the response amplitude of force and base-acceleration excited single-degree-of-freedom structures. It is analytically shown that the TMDI is more effective from a same mass/weight TMD to suppress vibrations close to the natural frequency of the uncontrolled structure, while it is more robust to detuning effects. Moreover, it is shown that the mass amplification effect of the inerter achieves significant weight reduction for a target/predefined level of vibration suppression in a performance-based oriented design approach compared to the classical TMD. Lastly, the potential of using the TMDI for energy harvesting is explored by substituting the dissipative damper with an electromagnetic motor and assuming that the inertance can vary through the use of a flywheel-based inerter device. It is analytically shown that by reducing the inertance, treated as a mass/inertia-related design parameter not considered in conventional TMD-based energy harvesters, the available power for electric generation increases for fixed attached mass/weight, electromechanical damping, and stiffness properties.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2000.11a
• /
• pp.282-286
• /
• 2000

In this paper, magneto-rheological(MR) damper is studied for vibration control of large infra structures under earthquake. Generally, active control devices need a large control force and a high power supply system to reduce the vibration effectively. Large and miss tuned control force may induce the dangerous situation such that the generated large control force acts to amplify the structural vibration. Recently, to overcome the weaknesses of the active control, the semi-active control method is suggested by many researchers. Semi-active control uses the passive control device of which the characteristics can be modified. Control force of the semi-active device is not generated from the actuator with power supply. It is generated as a dynamic reaction force of the device same as in the passive control case, so the control system is inherently stable and robust. Unlike the case of passive control, control force of semi-active control is adjusted depending on the measured response of the structure, so the vibration can be reduced more effectively against various unknown environmental loads. Magneto-rheological(MR) damper is one of the semi-active devices. Dynamic characteristics of the MR material can be changed by applying the magnetic fields. So the control of MR damper needs only small power. Response time of MR to the input voltage is very short, so the high performance control is possible. MR damper has a high force capacity so it is adequate to the vibration control of large infra structure. Because MR damper has a nonlinear property, normal control method used in active control may not be effective. Clipped optimal control, modified bang-bang control etc. have been suggested to MR damper by many researchers. In this study, sliding mode fuzzy control(SMFC) is applied to MR damper. Genetic algorithm is used for the controller tuning. To verify the applicability of MR damper and suggested algorithm, numerical simulation on the aseismic control is carried out. Simulation model is three-story building structure, which was used in the paper of Dyke, et al. The control performance is compared with clipped optimal control. The present results indicate that the SMFC algorithm can reduce the earthquake-induced vibration very effectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.3
• /
• pp.106-118
• /
• 2019

In recent years, research and development on image object recognition using artificial intelligence have been actively carried out, and it is expected to be used for road maintenance. Among them, artificial intelligence models for object detection of road surface are continuously introduced. In order to develop such object recognition algorithms, a backbone network that extracts feature maps is essential. In this paper, we will discuss how to select the appropriate neural network. To accomplish it, we compared with 4 different deep neural networks using 6,000 road surface damage images. Based on three evaluation methods for analyzing characteristics of neural networks, we propose a method to determine optimal neural networks. In addition, we improved the performance through optimal tuning of hyper-parameters, and finally developed a light backbone network that can achieve 85.9% accuracy of road surface damage classification.