• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2757-2763
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• 2015

p-Snake is an energy minimizing algorithm that applies an additional prototype energy to the existing Active Contour Model and is used to extract the contour line in the area where the edge information is unclear. In this paper suggested the creation of a prototype energy field that applies a variable prototype expressed as a combination of circle and straight line primitives, and a fudge function, to improve p-Snake's contour extraction performance. The prototype was defined based on the parts codes entered and the appropriate initial contour was extracted in each primitive zones acquired from the pre-processing process. Then, the primitives variably adjusted to create the prototype and the contour probability based on the distance to the prototype was calculated through the fuzzy function to create the prototype energy field. This was applied to p-Snake to extract the contour from 100 images acquired from various small parts and compared its similarity with the prototype to find that p-Snake made with the adaptive prototype was about 4.6% more precise than the existing Snake method.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.6
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• pp.69-75
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• 2000

At the stage of initial design, prototypes are needed for engineering and aesthetic purposes. In order to get a fast and non-expensive prototype, designers prefer rapid prototyping(RP) to any other means. In driving a 3D CAD model into rapid prototyping, sectioning the model is essential and there are two negotiation-needed targets, enhancing accuracy while taking less build-time, which makes adaptive slicing taken into account. In spite of the advantages of adaptive slicing, it is not yet applied to real RP machines because of the limits of hardwares. In this thesis, a new slicing algorithm which (1)uses several values of thickness available in a RP machine. (2)determines total number of layers to make the prototype within the intended time and (3)arranges the layers using orthogonal arrays to minimize the volume error caused by the difference between a given CAD model and a fabricated model is presented. And the algorithm is expected to have possibility of assisting RP machines to take the advantages of adaptive slicing.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.143-160
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• 2001

Micro-simulation models have been recognized as an efficient assessment tool in developing traffic signal control technologies. In this paper a prototype of a microscopic simulation model which can be applied to evaluate the performance of traffic-adaptive signal control strategies was developed. In the simulation process, space-based arrays were appled to estimate parameters of car following and lane changing models. Two levels of link types, a micro-type and macro-type links, were also embodied in the simulation process. The proposed model was tested on a test network consists of 9 intersections. The performance of the proposed model was evaluated in link by link comparisons with the results of NETSIM. The results show that the proposed model could appropriately simulate traffic flows of the test network. The model also produces traffic adaptive signal timings, cycle lengths and green times for turning movements, based on the detector data. It implies that the optimization process of the model produces reasonable signal timings for the test network on the cycle basis.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.6
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• pp.369-375
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• 2017

In this paper, we present a self-adaptive software platform that enables an IoT gateway to perform autonomous operation considering IoT devices connected each other in resource-constrained environments. Based on the oneM2M device software platform publicly available, we have designed an additional part, called SAS (self-adaptive software) consisting of MAM (memory-aware module), NAM (network-aware module), BAM (battery-aware module), DAM (data-aware module), and DH (decision handler). A prototype system is implemented to show the feasibility of the proposed self-adaptive software architecture. Our proposed system demonstrates that it can adaptively adjust the operation of gateway and connected devices to their resource conditions under the desired service scenarios.

• Journal of Power Electronics
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• v.12 no.6
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• pp.904-911
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• 2012

This paper presents a fuzzy adaptive speed controller that guarantees a fast dynamic behavior and a precise trajectory tracking capability for surfaced-mounted permanent magnet synchronous motors (SPMSMs). The proposed fuzzy adaptive control strategy is simple and easy to implement. In addition, the proposed speed controller is very robust to system parameter and load torque variations because it does not require any accurate parameter values. The global stability of the proposed control system is analytically verified. To evaluate the proposed fuzzy adaptive speed controller, both simulation and experimental results are shown under motor parameter and load torque variations on a prototype SPMSM drive system.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.2_2
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• pp.313-321
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• 2020

In this paper, two types of linear actuation methods for the previously proposed adaptive gripper are presented, which includes actual parallelogram inside a five-bar mechanism and has the advantages of smaller actuation torque and larger stroke over the commercial adaptive gripper by RobotiQ. The forward/inverse kinematics and statics analyses for two types of linear actuations are derived. From the inverse kinematics and statics analyses, linear actuation type I is selected and the gripper prototype is designed.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.931-934
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• 2005

This paper describes an adaptive recommendation system that provides real-time personalized trading advice to the investors based on their profiles and trading information environment. A proposed system integrates Stochastic technical analysis and artificial neural network that incorporates an adaptive user modeling. The user model is constructed and updated based on initial user profile and recorded user interactions with the system. The information presented to each individual user is also tailor-made to fit the user's behavior and preference. A system prototype was implemented in JAVA. Experiments used to evaluate the system's performance were done on both human subjects and synthetic users. The results show our proposed system is able to rapidly learn to provide appropriate advice to different types of users.

• Journal of Power System Engineering
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• v.17 no.4
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• pp.120-130
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• 2013

An adaptive PID sliding mode controller is proposed for the position control of electro-hydrostatic actuator(EHA) systems with system uncertainties and saturation in the motor. An EHA prototype is developed and system modeling and parameter identification are executed. Then, adaptive PID sliding mode controller and optimal anti-windup PID controller are designed and the performance and robustness of the two control systems are compared by experiment. It was found that the adaptive PID sliding mode control system has better performance and is more robust to system uncertainties than the optimal anti-windup PID control system.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.195-200
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• 2002

ART (Adaptive Resonance Theory [1]) neural network and its variations perform non-hierarchical clustering by unsupervised learning. We propose a scheme "arboART" for hierarchical clustering by using several ART1.5-SSS networks. It classifies multidimensional vectors as a cluster tree, and finds features of clusters. The Basic idea of arboART is to use the prototype formed in an ART network as an input to other ART network that has looser distance criteria (Ishihara, et al., [2,3]). By sending prototype vectors made by ART to one after another, many small categories are combined into larger and more generalized categories. We can draw a dendrogram using classification records of sample and categories. We have confirmed its ability using standard test data commonly used in pattern recognition community. The clustering result is better than traditional computing methods, on separation of outliers, smaller error (diameter) of clusters and causes no chaining. This methodology is applied to Kansei evaluation experiment data analysis.

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.399-403
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• 2009

In IEEE 802.15.1 (Bluetooth) Ad-hoc networks, the frequency is resolved by the specific part of the digits of the Device clock and the Bluetooth address of the Master device in a given piconet. The piconet performs a fast frequency hopping scheme over 79 carriers of 1-MHz bandwidth. Since there is no coordination between different piconets, packet collisions may occur if two piconets are located near one another. In this paper, we proposed a software/hardware co-design of an adaptive frequency decision mechanism so that more than two different kinds of wireless devices can stay connected without frequency collision. Suggested method was implemented with C program and HDL (Hardware Description Language) and automatically synthesized and laid out. The adaptive frequency hopping circuit was implemented in a prototype and showed its operation at 24MHz correctly.