• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.46-49
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• 1998

In this paper, we introduce the notion of intelligent communication by introducing a novel intelligent receiver model. This receiver is continually evolving and learns and improves in performance as it compiles its experience over time. In digital communication context, in a typical training mode, it jearns the concept of "1" as is deteriorated by arbitrary (not necessarily additive as is typically assumed) disturbance and /or modulation. After learning "1", in test mode, it classifies the received signal "1" and "0" almost completely. The intelligent receiver as implemented is grounded on the recently introduced Stochastic Morphological Sampling Theorem(SMST), a distribution-free result which gives theoretical bounds on the sample complexity(training size) needed for the required performance parameters such as accuracy($\varepsilon$) and confidence($\delta$). Based on this theorem, we demonstrate --almost irrespective of channel and modulation model-- the number of samples needed to learn the concept of "1" is not too "large" and the resulting universal receiver structure, that corresponding to classical Nearest Neighbor rule in Pattern Recognition Theory, is trivial. We check the surprising efficiency and validity of this model through some simple simulations. and validity of this model through some simple simulations.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.120-126
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• 2020

Studies are being conducted regarding falling recognition using sensors on smartphonesto recognize falling in human daily life. These studies use a number of sensors, mostly acceleration sensors, gyro sensors, motion sensors, etc. Falling recognition system processes the values of sensor data by using a falling recognition algorithm and classifies behavior based on thresholds. If the threshold is ambiguous, the accuracy will be reduced. To solve this problem, Deep learning was introduced in the behavioral recognition system. Deep learning is a kind of machine learning technique that computers process and categorize input data rather than processing it by man-made algorithms. Thus, in this paper, we propose a falling recognition application system using deep learning based on smartphones. The proposed system is powered by apps on smartphones. It also consists of three layers and uses DataBase as a Service (DBaaS) to handle big data and address data heterogeneity. The proposed system uses deep learning to recognize the user's behavior, it can expect higher accuracy compared to the system in the general rule base.

• Journal of Industrial Technology
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• v.3
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• pp.69-74
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• 1983

For the determination of a reservoir capacity Rippl's mass-curve method has long been used with the past river flow data assuming the same flow records will be repeated in the future. This study aims to find out a better method for determining the reservoir capacity by employing the analytical theory based on the stochastic process. For the present study the synthetic generation methods of Thomas-Fiering type was used to synthetically generate 50 years of monthly river inflows to three single-purpose reservoirs and three multi-purpose reservoirs. The generated sequences of monthly flows were analyzed based on the range concept. With the optimum operation rule of the reservoirs as the one which maximizes the water-use downstream the waterrelease from the reservoir was determined and with due consideration to the mean inflows and the range of monthly flows the required reservoirs capacity was stochastically determined. It was possible to repersent the so-determined reservoir capacity in terms of the mean monthly inflows and the number of subseries in the determination of ranges. It is suggested that the result obtained in this study would be applied to approximately estimate, in the stage of preliminary design, the required capacity of a reservoir in question with the limited information such as the mean monthly inflow and the period of reservoir operation.

• Journal of Digital Contents Society
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• v.9 no.4
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• pp.785-790
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• 2008

Our Digital Carousel enables user to share media objects through media synchronization mechanism. We implemented the Digital Carousel so that the users participated in collaborative work may refer shared media or error objects as the same view to others. In this paper, we discuss a method for increasing reliability through fault tolerance. We describe the design and implementation of the ER running on distributed multimedia environment. ER is a system which is able to recover automatically a software error based on distributed multimedia. This paper explains a performance analysis of an error recovery system running on distributed multimedia environment using the rule-based DEVS modeling and simulation techniques. In DEVS, a system has a time base, inputs, states, outputs, and functions.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.12
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• pp.1127-1132
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• 2014

Fast tool servo (FTS) is an enabling technology to fabricate various shapes of functional surface geometries in a precise and controllable manner. FTS can be also employed as a straightforward and efficient surface treatment way of making such products more durable. In this work, process characteristics using high-precision FTS-based surface texturing were qualitatively and quantitatively investigated to provide a class of surface design rule. The morphologies of surfaces processed with different conditions were first examined by observing the resultant 2D/3D surface profiles. In addition, the effects of the surface treatment using FTS on hardness and wear properties were characterized and compared to those without treatment.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.7
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• pp.629-635
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• 2016

This paper presents a method for predicting and tracking the irregular motion of bio-systems, - such as petals of flowers, butterflies or seeds of dandelion - based on the particle filtering theory. In bio-inspired system design, the ability to predict the dynamic motion of particles through adequate, experimentally verified models is important. The modeling of petal particle systems falling in air was carried out using the Bayesian probability rule. The experimental results show that the suggested method has good predictive power in the case of random disturbances induced by the turbulence of air.

• Journal of Digital Contents Society
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• v.17 no.5
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• pp.359-366
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• 2016

In order to provide useful services for user in ubiquitous environment, a technique that can get the helpful information considering user activity and preference is needed and also user's interest actually changes as time passes. Therefore, the discovering method which reflects the concern degree of service information is needed. In this paper, we present the finding method of frequent pattern with dynamic weight on individual item based on service ontology we design. Our method can be applied to provide interested service information for user depending on context.

• The KIPS Transactions:PartD
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• v.8D no.5
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• pp.623-630
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• 2001

Recently, Internet solution market is focused on competition in Electronic Commerce (EC) rather than necessity and effectiveness of EC. In this paper, we propose a policy-oriented matching agent system that makes EC market active. We can pursue diverse promotion since policies are objects, and we can formulate, carry out, pursue, and evaluated a policy consistently on the proposed solution since our solution is integrated into merits of rule-based system and operation space (release post). There are three important points of the implementation. It is component-based structure that fits to be a basic platform for EC. It is connected with other system easily, so it can help marketing. Marketing.

• Structural Engineering and Mechanics
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• v.45 no.2
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• pp.233-257
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• 2013

Given the yield shear of a single-story inelastic structure with simple eccentricity, the problem of strength distribution among the resisting elements is investigated, with respect to minimize its torsional response during a ground motion. Making the hypothesis that the peak accelerations, of both modes of vibration, are determined from the inelastic acceleration spectrum, and assuming further that a peak response quantity is obtained by an appropriate combination rule (square root of sum of squares-SRSS or complete quadratic combination-CQC), the first aim of this study is to present an interaction relationship between the yield shear and the maximum torque that may be developed in such systems. It is shown that this torque may be developed, with equal probability, in both directions (clockwise and anticlockwise), but as it is not concurrent with the yield shear, a rational design should be based on a combination of the yield shear with a fraction of the peak torque. The second aim is to examine the response of such model structures under characteristic ground motions. These models provide a rather small peak rotation and code provisions that are based on such principles (NBCC-1995, UBC-1994, EAK-2000, NZS-1992) are superiors to EC8 (1993) and to systems with a stiffness proportional strength distribution.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2005.11a
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• pp.315-320
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• 2005

This paper is proposed adaptive fuzzy-neuro controller for high performance of induction motor drive. The design of this algorithm based on fuzzy-neural network controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of nor measured between the motor speed and output of a reference model. The control performance of the adaptive fuzy-neuro controller is evaluated by analysis for various operating conditions. The results of experiment prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.