• Title/Summary/Keyword: MFA

Search Result 231, Processing Time 0.027 seconds

Distributed Mean Field Genetic Algorithm for Channel Routing (채널배선 문제에 대한 분산 평균장 유전자 알고리즘)

  • Hong, Chul-Eui
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.14 no.2
    • /
    • pp.287-295
    • /
    • 2010
  • In this paper, we introduce a novel approach to optimization algorithm which is a distributed Mean field Genetic algorithm (MGA) implemented in MPI(Message Passing Interface) environments. Distributed MGA is a hybrid algorithm of Mean Field Annealing(MFA) and Simulated annealing-like Genetic Algorithm(SGA). The proposed distributed MGA combines the benefit of rapid convergence property of MFA and the effective genetic operations of SGA. The proposed distributed MGA is applied to the channel routing problem, which is an important issue in the automatic layout design of VLSI circuits. Our experimental results show that the composition of heuristic methods improves the performance over GA alone in terms of mean execution time. It is also proved that the proposed distributed algorithm maintains the convergence properties of sequential algorithm while it achieves almost linear speedup as the problem size increases.

FIDO Platform of Passwordless Users based on Multiple Biometrics for Secondary Authentication (암호 없는 사용자의 2차 인증용 복합생체 기반의 FIDO 플랫폼)

  • Kang, Min-goo
    • Journal of Internet Computing and Services
    • /
    • v.23 no.4
    • /
    • pp.65-72
    • /
    • 2022
  • In this paper, a zero trust-based complex biometric authentication was proposed in a passwordless environment. The linkage of FIDO 2.0 (Fast IDENTITY Online) transaction authentication platforms was designed in conjunction with metaverse. In particular, it was applied with the location information of a smart terminal according to a geomagnetic sensor, an accelerator sensor, and biometric information for multi-factor authentication(MFA). At this time, a FIDO transaction authentication platform was presented for adaptive complex authentication with user's environment through complex authentication with secondary authentication based on situational awareness such as illuminance and temperature/humidity. As a result, it is possible to authenticate secondary users based on zero trust with behavior patterns such as fingerprint recognition, iris recognition, face recognition, and voice according to the environment. In addition, it is intended to check the linkage result of the FIDO platform for complex integrated authentication and improve the authentication accuracy of the linkage platform for transaction authentication using FIDO2.0.

Classification of Magnetic Resonance Imagery Using Deterministic Relaxation of Neural Network (신경망의 결정론적 이완에 의한 자기공명영상 분류)

  • 전준철;민경필;권수일
    • Investigative Magnetic Resonance Imaging
    • /
    • v.6 no.2
    • /
    • pp.137-146
    • /
    • 2002
  • Purpose : This paper introduces an improved classification approach which adopts a deterministic relaxation method and an agglomerative clustering technique for the classification of MRI using neural network. The proposed approach can solve the problems of convergency to local optima and computational burden caused by a large number of input patterns when a neural network is used for image classification. Materials and methods : Application of Hopfield neural network has been solving various optimization problems. However, major problem of mapping an image classification problem into a neural network is that network is opt to converge to local optima and its convergency toward the global solution with a standard stochastic relaxation spends much time. Therefore, to avoid local solutions and to achieve fast convergency toward a global optimization, we adopt MFA to a Hopfield network during the classification. MFA replaces the stochastic nature of simulated annealing method with a set of deterministic update rules that act on the average value of the variable. By minimizing averages, it is possible to converge to an equilibrium state considerably faster than standard simulated annealing method. Moreover, the proposed agglomerative clustering algorithm which determines the underlying clusters of the image provides initial input values of Hopfield neural network. Results : The proposed approach which uses agglomerative clustering and deterministic relaxation approach resolves the problem of local optimization and achieves fast convergency toward a global optimization when a neural network is used for MRI classification. Conclusion : In this paper, we introduce a new paradigm to classify MRI using clustering analysis and deterministic relaxation for neural network to improve the classification results.

  • PDF

제철공정에서의 제어기술동향

  • Park, Han-Gu
    • ICROS
    • /
    • v.15 no.1
    • /
    • pp.37-43
    • /
    • 2009
  • 철강제조공정에서 강판을 만드는 공정이 압연이다. 압연공정은 연속주조 공장에서 생산되는 Steel Slab, Bloom, Billet등의 반제품을 높은 온도로 재 가열하고 물리적인 힘을 가해 압연하는 열간압연(이하 열연)과 열연으로 얇아진 강판을 열을 가하지 않고 냉각상태에서 압연하는 냉간압연으로 나뉜다. 본 원고에서는 열연 공정의 가열로 온도제어에 적용한 MFA(Model Free Adaptive Controller)를 소개하고자 한다.

Cytotoxic Activity and Structure Activity Relationship of Ceramide Analogues in Caki-2 and HL-60 Cells

  • Kim, Yong-Jin;Kim, Eun-Ae;Sohn, Uy-Dong;Yim, Chul-Bu;Im, Chae-Uk
    • The Korean Journal of Physiology and Pharmacology
    • /
    • v.14 no.6
    • /
    • pp.441-447
    • /
    • 2010
  • B13, a ceramide analogue, is a ceramidase inhibitor and induces apoptosis to give potent anticancer activity. A series of thiourea B13 analogues was evaluated for their in vitro cytotoxic activities against human renal cancer Caki-2 and leukemic cancer HL-60 in the MTT assay. Some compounds (12, 15, and 16) showed stronger cytotoxicity than B13 and C6-ceramide against both tumor cell lines, and compound (12) gave the most potent activity with $IC_{50}$ values of 36 and $9\;{\mu}M$, respectively. Molecular modeling of thiourea B13 analogues was carried out by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). We obtained highly reliable and predictive CoMSIA models with cross-validated $q^2$ values of 0.707 and 0.753 and CoMSIA contour maps to show the structural requirements for potent activity. These data suggest that the amide group of B13 could be replaced by thiourea, that the stereochemistry of 1,3-propandiol may not be essential for activity and that long alkyl chains increase cytotoxicity.

A Clustering Algorithm for Handling Missing Data (손실 데이터를 처리하기 위한 집락분석 알고리즘)

  • Lee, Jong Chan
    • Journal of the Korea Convergence Society
    • /
    • v.8 no.11
    • /
    • pp.103-108
    • /
    • 2017
  • In the ubiquitous environment, there has been a problem of transmitting data from various sensors at a long distance. Especially, in the process of integrating data arriving at different locations, data having different property values of data or having some loss in data had to be processed. This paper present a method to analyze such data. The core of this method is to define an objective function suitable for the problem and to develop an algorithm that can optimize this objective function. The objective function is used by modifying the OCS function. MFA (Mean Field Annealing), which was able to process only binary data, is extended to be applicable to fields with continuous values. It is called CMFA and used as an optimization algorithm.

Docking and Quantitative Structure Activity Relationship studies of Acyl Guanidines as β-Secretase (BACE1) Inhibitor

  • Hwang, Yu Jin;Im, Chaeuk
    • Bulletin of the Korean Chemical Society
    • /
    • v.35 no.7
    • /
    • pp.2065-2071
    • /
    • 2014
  • ${\beta}$-Secretase (beta-amyloid converting enzyme 1 [BACE1]) is involved in the first and rate-limiting step of ${\beta}$-amyloid ($A{\beta}$) peptides production, which leads to the pathogenesis of Alzheimer's disease(AD). Therefore, inhibition of BACE1 activity has become an efficient approach for the treatment of AD. Ligand-based and docking-based 3D-quantitative structure-activity relationship (3D-QSAR) studies of acyl guanidine analogues were performed with comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) to obtain insights for designing novel potent BACE1 inhibitors. We obtained highly reliable and predictive CoMSIA models with a cross-validated $q^2$ value of 0.725 and a predictive coefficient $r{^2}_{pred}$ value of 0.956. CoMSIA contour maps showed the structural requirements for potent activity. 3D-QSAR analysis suggested that an acyl guanidine and an amide group in the $R_6$ substituent would be important moieties for potent activity. Moreover, the introduction of small hydrophobic groups in the phenyl ring and hydrogen bond donor groups in 3,5-dichlorophenyl ring could increase biological activity.