• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.4
• /
• pp.2757-2763
• /
• 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 Information Processing Systems
• /
• v.8 no.3
• /
• pp.409-420
• /
• 2012

The decision-making by agents in games is commonly based on reinforcement learning. To improve the quality of agents, it is necessary to solve the problems of the time and state space that are required for learning. Such problems can be solved by Macro-Actions, which are defined and executed by a sequence of primitive actions. In this line of research, the learning time is reduced by cutting down the number of policy decisions by agents. Macro-Actions were originally defined as combinations of the same primitive actions. Based on studies that showed the generation of Macro-Actions by learning, Macro-Actions are now thought to consist of diverse kinds of primitive actions. However an enormous amount of learning time and state space are required to generate Macro-Actions. To resolve these issues, we can apply insights from studies on the learning of tasks through Programming by Demonstration (PbD) to generate Macro-Actions that reduce the learning time and state space. In this paper, we propose a method to define and execute Macro-Actions. Macro-Actions are learned from a human subject via PbD and a policy is learned by reinforcement learning. In an experiment, the proposed method was applied to a car simulation to verify the scalability of the proposed method. Data was collected from the driving control of a human subject, and then the Macro-Actions that are required for running a car were generated. Furthermore, the policy that is necessary for driving on a track was learned. The acquisition of Macro-Actions by PbD reduced the driving time by about 16% compared to the case in which Macro-Actions were directly defined by a human subject. In addition, the learning time was also reduced by a faster convergence of the optimum policies.

• Transactions of Materials Processing
• /
• v.11 no.5
• /
• pp.405-413
• /
• 2002

A process planning system for cold forging of non-axisymmetric parts of comparatively simple shape was developed in this study. Programs for the system have been written with Visual LISP in AutoCAD. Shape of the product must be drawn with the solid line and the hidden line, and with the plane and front view, as well. At the plane, the system recognizes the external shape of non-axisymmetric portions - the number of the sides of the regular polygons and the radii of circles inscribing and circumscribing the polygon. At the front view, the system cognizes the diameter of axisymmetric portions and the height of the primitive geometries such as polygon, cylinder, cone, concave, convex, etc. The system perceives that the list developed from the solid line must be formed by the operation of forward extrusion or upsetting, and that the list developed from the hidden line must be formed by the operation of backward extrusion. The system designs the intermediate geometries again by considering clearance between workpiece and die, and then finally the billet diameter, in reverse order from the finished product, on the basis of volume constancy and using the operations, the forming sequence, the number of operations and the intermediate geometries which were already designed. The design rules and knowledges for the system were extracted from the plasticity theories, handbook, relevant reference and empirical knowledge of field experts. Suitability of the process planning was analyzed using SuperForge of FVM simulation package. The results of analysis showed good formability.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.2
• /
• pp.168-177
• /
• 1996

In this paper, we propose an on-line recognition system of chinese characters using an adaptive resonance theory-1(ART-1) neural network. Strokes, primitive components of chinese characters are usually warped into a cursive form and classifying them is very difficult. To deal with such cursive strokes, we use an ART-1 neural network that has the following advantages: (1) it automatically assembles similar patterns together to form classes in a self-organized manner: (2) it directly accesses the recognition codes corresponding to binary input patterns after self-stabilizing; (3) it doesn't tends to get trapped in local minima, or globally incorrect solutions. A database for character recognition also dynamically constructed with generalized character lists, and a new character can be included simply by adding a new sequence to the list. Character recognition is achieved by traversing the chinese datbase with a sequence of recognized strokes and positional relations between the strokes. To verify the performance of the system. We tested it for 1800 daily-used basic chinese second per character. This results suggest that the proposed system is pertinent to be put into practical use.

• Journal of the Korea Society of Computer and Information
• /
• v.9 no.4 s.32
• /
• pp.85-91
• /
• 2004

The use of gestures provides an attractive alternate to cumbersome interface devices for human-computer interaction. This has motivated a very active research area concerned with computer vision-based analysis and interpretation of hand gestures The most important issues in gesture recognition are the simplification of algorithm and the reduction of processing time. The mathematical morphology based on geometrical set theory is best used to perform the processing. The key idea of proposed algorithm is to track a trajectory of center points in primitive elements extracted by morphological shape decomposition. The trajectory of morphological center points includes the information on shape orientation. Based on this characteristic we proposed the morphological gesture sequence recognition algorithm using feature vectors calculated to the trajectory of morphological center points. Through the experiment, we demonstrated the efficiency of proposed algorithm.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.6
• /
• pp.1105-1112
• /
• 2020

One-dimensional 3-neighborhood Cellular Automata (CA)-based pseudo-random number generators are widely applied in generating test patterns to evaluate system performance and generating key sequence generators in cryptographic systems. In this paper, in order to design a CA-based key sequence generator that can generate more complex and confusing sequences, we study a one-dimensional symmetric 5-neighborhood CA that expands to five neighbors affecting the state transition of each cell. In particular, we propose an n-cell one-dimensional symmetric 5-neighborhood CA synthesis algorithm using the algebraic method that uses the Krylov matrix and the one-dimensional 90/150 CA synthesis algorithm proposed by Cho et al. [6].

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.496-498
• /
• 2004

An action-selection-mechanism is proposed to deal with sequential behaviors, where associations between some of stimulus and behaviors will be learned by a shortest-path-finding-based reinforcement team ins technique. To be specific, we define behavioral motivation as a primitive node for action selection, and then sequentially construct a network with behavioral motivations. The vertical path of the network represents a behavioral sequence. Here, such a tree fur our proposed ASM can be newly generated and/or updated. whenever a new sequential behaviors is learned. To show the validity of our proposed ASM, some experimental results on a "pushing-box-into-a-goal task" of a mobile robot will be illustrated.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.17 no.4
• /
• pp.31-37
• /
• 1980

In this paper, we are concerned with the problems of fault- detection for combinational logic networks. The method which we can obtain the complete test sets using propagation of primitive test sets is presented by considering the relation between test sets of each line. A new method is proposed that can detect the fault through the observation of the output variance by applying only the test sets equivalent to the number of inputs We found that the method is much improved compared to the conventional fault detecting procedure that requires applying the complete test sets to the logic networks.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.170-175
• /
• 1998

Transporting a large table using multiple robotic agents requires at least two group behaviors of homing and herding which are to bo coordinated in a proper sequence. Existing GP methods for multi-agent learning are not practical enough to find an optimal solution in this domain. To evolve this kind of complex cooperative behavior we use a novel method called fitness switching. This method maintains a pool of basis fitness functions each of which corresponds to a primitive group behavior. The basis functions are then progressively combined into more complex fitness functions to co-evolve more complex behavior. The performance of the presented method is compared with that of two conventional methods. Experimental results show that coevolutionary fitness switching provides an effective mechanism for evolving complex emergent behavior which may not be solved by simple genetic programming.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2003.06a
• /
• pp.1235-1238
• /
• 2003

A rule-based CAPP(computer aided process planning) system is proposed in this research to develop integrated manufacturing process of machining and inspection using OMM(On-Machine Measurement) device. Generally workpiece composed of many primitive form features. This features are determined optimum inspection sequence by analyzing the feature information such as features-relationship, probe approach direction and etc. Proposed paper is more efficient method of CAIP(computer aided inspection planning) considered machining process