• The KIPS Transactions:PartB
• /
• v.12B no.4 s.100
• /
• pp.429-436
• /
• 2005

A simple stereo matching algorithm using population-based incremental learning(PBIL) is proposed in this paper to decrease the general problem of genetic algorithms, such as memory consumption and inefficiency of search. PBIL is a variation of genetic algorithms using stochastic search and competitive teaming based on a probability vector. The structure of PBIL is simpler than that of other genetic algorithm families, such as serial and parallel ones, due to the use of a probability vector. The PBIL strategy is simplified and adapted for stereo matching circumstances. Thus, gene pool, chromosome crossover, and gene mutation we removed, while the evolution rule, that fitter chromosomes should have higher survival probabilities, is preserved. As a result, memory space is decreased, matching rules are simplified and computation cost is reduced. In addition, a scheme controlling the distance of neighbors for disparity smoothness is inserted to obtain a wide-area consistency of disparities, like a result of coarse-to-fine matchers. Because of this scheme, the proposed algorithm can produce a stable disparity map with a small fixed-size window. Finally, an alterative version of the proposed algorithm without using probability vector is also presented for simpler set-ups.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.1 no.3
• /
• pp.69-76
• /
• 2008

This paper concerns Fuzzy Radial Basis Function Neural Network (FRBFNN) and automatic rule generation of extraction of the FRBFNN by means of mountain clustering. In the proposed network, the membership functions of the premise part of fuzzy rules do not assume any explicit functional forms such as Gaussian, ellipsoidal, triangular, etc., so its resulting fitness values (degree of membership) directly rely on the computation of the relevant distance between data points. Also, we consider high-order polynomial as the consequent part of fuzzy rules which represent input-output characteristic of sup-space. The number of clusters and the centers of clusters are automatically generated by using mountain clustering method based on the density of data. The centers of cluster which are obtained by using mountain clustering are used to determine a degree of membership and weighted least square estimator (WLSE) is adopted to estimate the coefficients of the consequent polynomial of fuzzy rules. The effectiveness of the proposed model have been investigated and analyzed in detail for the representative nonlinear function.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.5 no.4
• /
• pp.738-745
• /
• 2001

In this paper, when the moving object move to the three-dimentional space, the tracking system track the moving object using the fuzzy reasoning. The joint angle el of the manipulator rotate from $0^{\circ}\; to\; 360^{\circ}$ , and the joint angle $\theta_2$rotate from$0^{\circ}\; to\; 360^{\circ}$. The fuzzy singleton is used for fuzzification and the control rule is twenty five and the fuzzy inference method is simplified Mamdani's reasoning and the defuzzification is the SCOG(Simplified Center Of Gravity) of the fuzzy controller To measure of the performance of the designed system, the fuzzy controller is compared with the CTM(Computed Torque Method) controller at the same condition. when the disturbance torque is ON, the both of CTM and fuzzy controller tracked object without error, However, the disturbance torque changed 0.4N, the CTM controller is 10 times greater than fuzzy controller at the sum of absolute error difference. The designed system is showed it's robustness against with disturbance.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.7
• /
• pp.1459-1466
• /
• 2009

In ubiquitous environment, various and amount of sensor data information occur continuously and periodically about thing and user from RHO, sensor network of various space. Such, the users from among many of provider who provide sensor service should find service that themselves is wanted. And when service use, service right to user should be provided. But in the current environment of the USN(Ubiquitous Sensor Network) Application Service, there is no the registry to find these services but only business- oriented UDDI(Universal Description Discovery, and integration). In addition, when service use, service right to user should be provided but current services provided only services one of the conditions or events. Therefore, rules-based processing system of service event that can provide service according various conditions and events is need. In this paper research into service registry for sensor service search with reference to existing UDDI and event processing system for USN application service with reference to event rule based on web service as WS-ECA(Web Service-Event Condition Action).

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.3
• /
• pp.847-852
• /
• 2010

Text in natural images has a various and important feature of image. Therefore, to detect text and extraction of text, recognizing it is a studied as an important research area. Lately, many applications of various fields is being developed based on mobile phone camera technology. Detecting edge component form gray-scale image and detect an boundary of text regions by local standard deviation and get an connected components using Euclidean distance of RGB color space. Labeling the detected edges and connected component and get bounding boxes each regions. Candidate of text achieved with heuristic rule of text. Detected candidate text regions was merged for generation for one candidate text region, then text region detected with verifying candidate text region using ectilarity characterization of adjacency and ectilarity between candidate text regions. Experctental results, We improved text region detection rate using completentary of edge and color connected component.

• Journal of Internet Computing and Services
• /
• v.5 no.2
• /
• pp.97-105
• /
• 2004

The reason that an intelligent agent cannot understand the representation of its own perception or activity is caused by the traditional syntactic approach that translates a semantic feature into a simulated string, To implement an autonomously learning intelligent agent, Cohen introduces a experimentally semantic approach that the system learns a contentful representation of physical schema from physically interacting with environment using its own sensors and effectors. We propose that negation is a meta-level schema that enables an agent to recognize its own physical schema, To improve the planner's efficiency, Graphplan introduces the control rule that manipulates the inconsistency between planning operators, but it cannot cognitively understand negation and suffers from redundancy problem. By introducing a negative function not, IPP solves the problem, but its approach is still syntactic and is inefficient in terms of time and space. In this paper, we propose that, to represent a negative fact, a positive atom, which is called opposite concept, is a very efficient technique for implementing an cognitive agent, and demonstrate some empirical results supporting the hypothesis.

• Neonatal Medicine
• /
• v.28 no.3
• /
• pp.133-138
• /
• 2021

Osteopetrosis refers to a group of genetic skeletal disorders characterized by osteosclerosis and fragile bones. Osteopetrosis can be classified into autosomal dominant, autosomal recessive, or X-linked forms, which might differ in clinical characteristics and disease severity. Autosomal recessive osteopetrosis, also known as malignant osteopetrosis, has an earlier onset, more serious clinical symptoms, and is usually fatal. We encountered a 1-day-old girl who was born full-term via vaginal delivery, which was complicated by meconium-stained amniotic fluid, cephalo-pelvic disproportion, and nuchal cord. Routine neonatal care was provided, in addition to blood tests and chest radiography to screen for sepsis, as well as skull radiography to rule out head injuries. Initial blood tests revealed hypocalcemia, which persisted on follow-up tests the next day. Radiographic examinations revealed diffusely increased bone density and a "space alien" appearance of the skull. Based on radiographic and laboratory findings, the infantile form of osteopetrosis was suspected and genetic testing for identification of the responsible gene. Eventually, a heterozygous mutation of the T cell immune regulator 1, ATPase H+ transporting V0 subunit a3 (TCIRG1) gene (c.292C>T) was identified, making this the first reported case of neonatal-onset malignant osteopetrosis with TCIRG1 mutation in South Korea. Early-onset hypocalcemia is common and usually results from prematurity, fetal growth restriction, maternal diabetes, perinatal asphyxia, and physiologic hypoparathyroidism. However, if hypocalcemia persists, we recommend considering 'infantile of osteopetrosis' as a rare cause of neonatal hypocalcemia and performing radiographic examinations to establish the diagnosis.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.13 no.6
• /
• pp.1145-1154
• /
• 2018

In order to prevent interference and interference of the frequency, it is required to convert the regulatory standard into the center of the radiation power radiated to the actual public. Since the radiation power regulation is related to general radio management such as technical standards, permits, and inspections, it is gradually introduced in consideration of applicability and urgency, and the radiation power related laws of major countries And a method of controlling the output of the radio equipment such as measurement, inspection, and authentication. In Korea, the proportion of antenna power supply is high, and in Europe, radiation power is high. Since the number of radio stations will increase and diversify in the future, institutional improvement should be made so that it can be measured in parallel with the radiocommunication infrastructure of the space manager. In order to convert to the radiative power management system, the system for the related radio system needs(Technical standards, certification, inspection of radio stations, post-management, etc.) to be improved.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.2
• /
• pp.439-446
• /
• 2019

In this paper, we propose a encryption method using C-MLCA and 1D CAT to secure medical image for efficiently. First, we generate a state transition matrix using a Wolfram rule and create a sequence of maximum length. By operating the complemented vector, it converts an existing sequence to a more complex sequence. Then, we multiply the two sequences by rows and columns to generate C-MLCA basis images of the original image size and go through a XOR operation. Finally, we will get the encrypted image to operate the 1D CAT basis function created by setting the gateway values and the image which is calculated by transform coefficients. By comparing the encrypted image with the original image, we evaluate to analyze the histogram and PSNR. Also, by analyzing NPCR and key space, we confirmed that the proposed encryption method has a high level of stability and security.

• Structural Engineering and Mechanics
• /
• v.83 no.3
• /
• pp.293-304
• /
• 2022

In this work, a novel reliability approach for combined high and low cycle fatigue (CCF) estimation is developed by combining active learning strategy with least squares support vector machines (LS-SVM) (named as ALS-SVM) surrogate model to address the multi-resources uncertainties, including working loads, material properties and model itself. Initially, a new active learner function combining LS-SVM approach with Monte Carlo simulation (MCS) is presented to improve computational efficiency with fewer calls to the performance function. To consider the uncertainty of surrogate model at candidate sample points, the learning function employs k-fold cross validation method and introduces the predicted variance to sequentially select sampling. Following that, low cycle fatigue (LCF) loads and high cycle fatigue (HCF) loads are firstly estimated based on the training samples extracted from finite element (FE) simulations, and their simulated responses together with the sample points of model parameters in Coffin-Manson formula are selected as the MC samples to establish ALS-SVM model. In this analysis, the MC samples are substituted to predict the CCF reliability of turbine blades by using the built ALS-SVM model. Through the comparison of the two approaches, it is indicated that the reliability model by linear cumulative damage rule provides a non-conservative result compared with that by the proposed one. In addition, the results demonstrate that ALS-SVM is an effective analysis method holding high computational efficiency with small training samples to gain accurate fatigue reliability.