• Title/Summary/Keyword: Complex algorithm

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Task Assignment Strategies for a Complex Real-time Network System

  • Kim Hong-Ryeol;Oh Jae-Joon;Kim Dae-Won
    • International Journal of Control, Automation, and Systems
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    • v.4 no.5
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    • pp.601-614
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    • 2006
  • In this paper, a study on task assignment strategies for a complex real-time network system is presented. Firstly, two task assignment strategies are proposed to improve previous strategies. The proposed strategies assign tasks with meeting end-to-end real-time constraints, and also with optimizing system utilization through period modulation of the tasks. Consequently, the strategies aim at the optimizationto optimize of system performance with while still meeting real-time constraints. The proposed task assignment strategies are devised using the genetic algorithmswith heuristic real-time constraints in the generation of new populations. The strategies are differentiated by the optimization method of the two objectives-meeting end-to-end real-time constraints and optimizing system utilization: the first one has sequential genetic algorithm routines for the objectives, and the second one has one multiple objective genetic algorithm routine to find a Pareto solution. Secondly, the performances of the proposed strategies and a well-known existing task assignment strategy using the BnB(Branch and Bound) optimization are compared with one other through some simulation tests. Through the comparison of the simulation results, the most adequate task assignment strategies are proposed for some as system requirements-: the optimization of system utilization, the maximization of running tasktasks, and the minimization of the number of network node nodesnumber for a network system.

3D Mesh Watermarking Using CEGI (CEGI를 이용한 3D 메쉬 워터마킹)

  • 이석환;김태수;김승진;권기룡;이건일
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.4C
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    • pp.472-484
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    • 2004
  • We proposed 3D mesh watermarking algorithm using CEGI distribution. In the proposed algorithm, we divide a 3D mesh of VRML data into 6 patches using distance measure and embed the same watermark bits into the normal vector direction of meshes that mapped into the cells of each patch that have the large magnitude of complex weight of CEGI. The watermark can be extracted based on the known center point of each patch and order information of cell. In an attacked model by affine transformation, we accomplish the realignment process before the extraction of the watermark. Experiment results exhibited the proposed algorithm is robust by extracting watermark bit for geometrical and topological deformed models.

Broad-band Multi-layered Radar Absorbing Material Design for Radar Cross Section Reduction of Complex Targets Consisting of Multiple Reflection Structures (다중반사 구조를 갖는 복합구조물의 RCS 감소를 위한 광대역 다층 전파흡수체 설계)

  • Kim, Kook-Hyun;Cho, Dae-Seung;Kim, Jin-Hyeong
    • Journal of the Society of Naval Architects of Korea
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    • v.44 no.4
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    • pp.445-450
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    • 2007
  • An optimum design process of the broad-band multi-layered radar absorbing material, using genetic algorithm, is established for the radar cross section reduction of a complex target, which consists of multiple reflection structures, such as surface warships. It follows the successive process of radar cross section analysis, scattering center analysis, radar absorbing material design, and reanalysis of radar cross section after applying the radar absorbing material. It is demonstrated that it is very effective even in the optimum design of the multi-layer radar absorbing material. This results from the fact that the three factors, i.e.. the incident angle range, broad-band frequencies, and maximum thickness can be simultaneously taken into account by adopting the genetic algorithm.

PVC Classification Algorithm Through Efficient R Wave Detection

  • Cho, Ik-Sung;Kwon, Hyeog-Soong
    • Journal of Sensor Science and Technology
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    • v.22 no.5
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    • pp.338-345
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    • 2013
  • Premature ventricular contractions are the most common of all arrhythmias and may cause more serious situation like ventricular fibrillation and ventricular tachycardia in some patients. Therefore, the detection of this arrhythmia becomes crucial in the early diagnosis and the prevention of possible life threatening cardiac diseases. Most methods for detecting arrhythmia require pp interval, or the diversity of P wave morphology, but they are difficult to detect the p wave signal because of various noise types. Thus, it is necessary to use noise-free R wave. So, the new approach for the detection of PVC is presented based on the rhythm analysis and the beat matching in this paper. For this purpose, we removed baseline wandering of low frequency band and made summed signals that are composed of two high frequency bands including the frequency component of QRS complex using the wavelet filter. And then we designed R wave detection algorithm using the adaptive threshold and window through RR interval. Also, we developed algorithm to classify PVC using RR interval. The performance of R wave and PVC detection is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate average detection rate of 99.76%, sensitivity of 99.30% and specificity of 98.66%; accuracy respectively for R wave and PVC detection.

EFFICIENT IMAGE SEGMENTATION FOR MANIFESTING VISUAL OBJECTS

  • Park, Hyun-Sang;Lim, Jung-Eun;Ra, Jong-Beom
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1999.06a
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    • pp.159-164
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    • 1999
  • Homogeneous but distinct visual objects having low-contrast boundaries are usually merged in most of the segmentation algorithms. To alleviate this problem, an efficient image segmentation algorithm based on a bottom-up approach is proposed by using spatial domain information only. For initial image segmentation, we adopt an efficient marker extraction algorithm conforming to the human visual system. Then, two region-merging algorithms are successively applied so that homogeneous visual objects can be represented as simple as possible without destroying low-contrast real boundaries among them. The resultant segmentation describes homogeneous visual objects with few regions while preserving semantic object shapes well. Finally, a size-based region decision procedure may be applied to represent complex visual objects simpler, if their precise semantic contents are not necessary. Experimental results show that the proposed image segmentation algorithm represents homogeneous visual objects with a few regions and describes complex visual objects with a marginal number of regions with well-preserved semantic object shapes.

Optimization of filling process in RTM using genetic algorithm

  • Kim, Byoung-Yoon;Nam, Gi-Joon;Ryu, Ho-Sok;Lee, Jae-Wook
    • Korea-Australia Rheology Journal
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    • v.12 no.1
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    • pp.83-92
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    • 2000
  • In resin transfer molding (RTM) process, preplaced fiber mat is set up in a mold and thermoset resin is injected into the mold. An important interest in RTM process is to minimize cycle time without sacrificing part quality or increasing cost. In this study, the numerical simulation and optimization process in filling stage were conducted in order to determine the optimum gate locations. Control volume finite element method (CVFEM) was used in this numerical analysis with the coordinate transformation method to analyze the complex 3-dimensional structure. Experiments were performed to monitor the flow front to validate simulation results. The results of numerical simulation predicted well the experimental results with every single, simultaneous and sequential injection procedure. We performed the optimization analysis for the sequential injection procedure to minimize fill time. The complex geometry of an automobile bumper core was chosen. Genetic algorithm was used in order to determine the optimum gate locations with regard to 3-step sequential injection case. These results could provide the information of the optimum gate locations in each injection step and could predict fill time and flow front.

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Study on failure mode prediction of reinforced concrete columns based on class imbalanced dataset

  • Mingyi Cai;Guangjun Sun;Bo Chen
    • Earthquakes and Structures
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    • v.27 no.3
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    • pp.177-189
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    • 2024
  • Accurately predicting the failure modes of reinforced concrete (RC) columns is essential for structural design and assessment. In this study, the challenges of imbalanced datasets and complex feature selection in machine learning (ML) methods were addressed through an optimized ML approach. By combining feature selection and oversampling techniques, the prediction of seismic failure modes in rectangular RC columns was improved. Two feature selection methods were used to identify six input parameters. To tackle class imbalance, the Borderline-SMOTE1 algorithm was employed, enhancing the learning capabilities of the models for minority classes. Eight ML algorithms were trained and fine-tuned using k-fold shuffle split cross-validation and grid search. The results showed that the artificial neural network model achieved 96.77% accuracy, while k-nearest neighbor, support vector machine, and random forest models each achieved 95.16% accuracy. The balanced dataset led to significant improvements, particularly in predicting the flexure-shear failure mode, with accuracy increasing by 6%, recall by 8%, and F1 scores by 7%. The use of the Borderline-SMOTE1 algorithm significantly improved the recognition of samples at failure mode boundaries, enhancing the classification performance of models like k-nearest neighbor and decision tree, which are highly sensitive to data distribution and decision boundaries. This method effectively addressed class imbalance and selected relevant features without requiring complex simulations like traditional methods, proving applicable for discerning failure modes in various concrete members under seismic action.

Simulation of Active Noise Control on Harmonic Sound (복수조화음에 대한 능동소음제어 시뮬레이션)

  • Kwon, O-Cheol;Lee, Gyeong-Tae;Lee, Hae-Jin;Yang, In-Hyung;Oh, Jae-Eung
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2007.11a
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    • pp.737-742
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    • 2007
  • The method of the reducing duct noise can be classified by passive and active control techniques. However, passive control has a limited effect of noise reduction at low frequencies (below 500Hz) and is limited by the space. On the other hand, active control can overcome these passive control limitations. The active control technique mostly uses the Least-Mean-Square (LMS) algorithm, because the LMS algorithm can easily obtain the complex transfer function in real-time particularly when the Filtered-X LMS (FXLMS) algorithm is applied to an active noise control (ANC) system. However, the convergence performance of the LMS algorithm decreases slightly so it may delay the convergence time when the FXLMS algorithm is applied to the active control of duct noise. Thus the Co-FXLMS algorithm was developed to improve the control performance in order to solve this problem. The Co-FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Co-FXLMS algorithm is presented in comparison with the FXLMS algorithm. Simulation results show that active noise control using Co-FXLMS is effective in reducing duct noise.

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AN ESCAPE CRITERION FOR THE COMPLEX POLYNOMIAL, WITH APPLICATIONS TO THE DEGREE-n BIFURCATION SET

  • Kim, Young Ik
    • Journal of the Chungcheong Mathematical Society
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    • v.16 no.1
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    • pp.7-14
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    • 2003
  • Let $P_c(z)=z^n+c$ be a complex polynomial with an integer $n{\geq}2$. We derive a criterion that the critical orbit of $P_c$ escapes to infinity and investigate its applications to the degree-n bifurcation set. The intersection of the degree-n bifurcation set with the real line as well as with a typical symmetric axis is explicitly written as a function of n. A well-defined escape-time algorithm is also included for the improved construction of the degree-n bifurcation set.

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Traversing a door for mobile robot using PCA in complex environment

  • Seo, Min-Wook;Kim, Young-Joong;Lim, Myo-Taeg
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1408-1412
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    • 2004
  • This paper presents a method that a mobile robot finds location of doors in complex environments and safely traverses the door. A robot must be able to find the door in order that it achieves the behavior that is scheduled after traversing a door. PCA(Principal Component Analysis) algorithm using the vision sensor is used for a robot to find the location of door. Fuzzy controller using sonar data is used for a robot to avoid an obstacle and traverse the doors.

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