• Title/Summary/Keyword: approximate approach

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Automatic Generation of Machining Parameters of Electric Discharge Wire-Cut Using 2-Step Neuro-Estimation (와이어 가공 조건 자동 생성 2 단계 신경망 추정)

  • 이건범;주상윤;왕지남
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.2
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    • pp.7-13
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    • 1998
  • This paper presents a methodology for determining machining conditions in Electric Discharge Wire-Cut. Unification of two phase neural network approach with an automatic generation of machining parameters is designed. The first phase neural network, which is 1 to M backward-mapping neural net, produces approximate machining conditions. Using approximate conditions, all possible conditions are newly created by the proposed automatic generation procedure. The second phase neural net, which is a M to 1 forward-mapping neural net, determines the best one among the generated candidates. Simulation results with ANN are given to verify that the presenting methodology could apply for determining machining parameters in Electric Discharge Wire-Cut.

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A Novel Cryptosystem Based on Steganography and Automata Technique for Searchable Encryption

  • Truong, Nguyen Huy
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.5
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    • pp.2258-2274
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    • 2020
  • In this paper we first propose a new cryptosystem based on our data hiding scheme (2,9,8) introduced in 2019 with high security, where encrypting and hiding are done at once, the ciphertext does not depend on the input image size as existing hybrid techniques of cryptography and steganography. We then exploit our automata approach presented in 2019 to design two algorithms for exact and approximate pattern matching on secret data encrypted by our cryptosystem. Theoretical analyses remark that these algorithms both have O(n) time complexity in the worst case, where for the approximate algorithm, we assume that it uses ⌈(1-ε)m)⌉ processors, where ε, m and n are the error of our string similarity measure and lengths of the pattern and secret data, respectively. In searchable encryption, our cryptosystem is used by users and our pattern matching algorithms are performed by cloud providers.

Cost Analysis Study : Development of HVAC&R System Cost Estimation and Prediction Methodology for Office Buildings (사무소 건물의 HVAC&R 시스템 공사비 분석방법 및 예측에 관한 연구)

  • Cho, Jinkyun;Shin, Seungho;Kim, Jonghurn
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.26 no.3
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    • pp.115-121
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    • 2014
  • HVAC&R system costs can often be one of the most expensive components, representing approximately 15% of the total construction cost for office buildings. Despite their significant importance, there is a lack of a consistent and homogeneous framework to approximate the estimate research. This research deals with the prediction methodology of HVAC&R system cost with the aim of establishing a common idea for the analysis of the construction cost estimate. Our approach deals with the concept of an HVAC&R set that is composed of subsystems. The matrix combination analysis is examined, and total 960 HVAC&R system cost estimation can be implemented to large scale office buildings.

Comparing Imputation Methods for Doubly Censored Data

  • Yoo, Han-Na;Lee, Jae-Won
    • The Korean Journal of Applied Statistics
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    • v.22 no.3
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    • pp.607-616
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    • 2009
  • In many epidemiological studies, the occurrence times of the event of interest are right-censored or interval censored. In certain situations such as the AIDS data, however, the incubation period which is the time between HIV infection and the diagnosis of AIDS is usually doubly censored. In this paper, we impute the interval censored HIV infection time using three imputation methods. Mid imputation, conditional mean imputation and approximate Bayesian bootstrap are implemented to obtain right censored data, and then Gibbs sampler is used to estimate the coefficient factor of the incubation period. By using Bayesian approach, flexible modeling and the use of prior information is available. We applied both parametric and semi-parametric methods for estimating the effect of the covariate and compared the imputation results incorporating prior information for the covariate effects.

Prospective Teachers' Understanding of the Constant π and their Knowledge of How to Prove its Constant Nature through the Concept of Linearity

  • Leung, K.C. Issic
    • Research in Mathematical Education
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    • v.18 no.1
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    • pp.1-29
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    • 2014
  • When taught the precise definition of ${\pi}$, students may be simply asked to memorize its approximate value without developing a rigorous understanding of the underlying reason of why it is a constant. Measuring the circumferences and diameters of various circles and calculating their ratios might just represent an attempt to verify that ${\pi}$ has an approximate value of 3.14, and will not necessarily result in an adequate understanding about the constant nor formally proves that it is a constant. In this study, we aim to investigate prospective teachers' conceptual understanding of ${\pi}$, and as a constant and whether they can provide a proof of its constant property. The findings show that prospective teachers lack a holistic understanding of the constant nature of ${\pi}$, and reveal how they teach students about this property in an inappropriate approach through a proving activity. We conclude our findings with a suggestion on how to improve the situation.

The Design of Adaptive Controller for Nonminimum-Phase System using Approximate Inverse System (근사화 inverse 시스템을 사용한 비최소 위상플랜트의 적응제어기 설계)

  • Oh, Hyun-Cheol;Kim, Yoon-Sang;Jwa, Jong-Cheol;Lee, Jae-Chun;Kim, Jae-Il;Ahn, Doo-Soo
    • Proceedings of the KIEE Conference
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    • 1997.07b
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    • pp.575-577
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    • 1997
  • This paper presents a approach to the adaptive control of nonminimum-phase continuous-time systems. It is shown that pole-zero cancellations can be avoided by using approximate inverse systems. The computer simulation results are presented to illustrate the effectiveness of the proposed method.

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Approximate ML Detection with the Best Channel Matrix Selection for MIMO Systems

  • Jin, Ji-Yu;Kim, Seong-Cheol;Park, Yong-Wan
    • Journal of Electrical Engineering and Technology
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    • v.3 no.2
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    • pp.280-284
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    • 2008
  • In this paper, a best channel matrix selection scheme(BCMS) is proposed to approximate maximum likelihood(ML) detection for a multiple-input multiple-output system. For a one stage BCMS scheme, one of the transmitted symbols is selected to perform ML detection and the other symbols are detected by zero forcing(ZF). To increase the diversity of the symbols that are detected by ZF, multi-stage BCMS detection scheme is used to further improve the system performance. Simulation results show that the performance of the proposed BCMS scheme can approach that of ML detection with a significant reduction in complexity.

Development of a Risk Analysis Assessment Models for the Construction Projects (건설공사의 위험도 분석평가 및 모델개발)

  • Lee, Jeong-Sik
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.3 no.2
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    • pp.233-240
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    • 1999
  • Even though the recent construction safety disasters not only result in the loss inside construction sites but also become to a large public disasters, safety activities are managed in an irrational way and safety rules are ignored in the construction sites which leads to occur same type of disasters repeatedly. In this paper, a fuzzy set theoretic approach to risk analysis is proposed as an alternative to the techniques currently used in the general construction projects safety. Then the concept of risk evaluation using linguistic representation of the likelihood, exposure and consequences is introduced. A risk assessment model using approximate reasoning technique base on fuzzy logic is presented to drive fuzzy values of risk and numerical example for risk analysis is also presented to illustrate the results.

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New insights in piezoelectric free-vibrations using simplified modeling and analyses

  • Benjeddou, Ayech
    • Smart Structures and Systems
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    • v.5 no.6
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    • pp.591-612
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    • 2009
  • New insights are presented in simplified modeling and analysis of free vibrations of piezoelectric - based smart structures and systems. These consist, first, in extending the wide used piezoelectric-thermal analogy (TA) simplified modeling approach in currently static actuation to piezoelectric free-vibrations under short-circuit (SC) and approximate open-circuit (OC) electric conditions; second, the popular piezoelectric strain induced - potential (IP) simplified modeling concept is revisited. It is shown that the IP resulting frequencies are insensitive to the electric SC/OC conditions; in particular, SC frequencies are found to be the same as those resulting from the newly proposed OC TA. Two-dimensional plane strain (PStrain) and plane stress (PStress) free-vibrations problems are then analyzed for above used SC and approximate OC electric conditions. It is shown theoretically and validated numerically that, for both SC and OC electric conditions, PStress frequencies are lower than PStrain ones, and that 3D frequencies are bounded from below by the former and from above by the latter. The same holds for the modal electro-mechanical coupling coefficient that is retained as a comparator of presented models and analyses.

Sensitivity Approach of Sequential Sampling for Kriging Model (민감도법을 이용한 크리깅모델의 순차적 실험계획)

  • Lee, Tae-Hee;Jung, Jae-Jun;Hwang, In-Kyo;Lee, Chang-Seob
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.28 no.11
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    • pp.1760-1767
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    • 2004
  • Sequential sampling approaches of a metamodel that sampling points are updated sequentially become a significant consideration in metamodeling technique. Sequential sampling design is more effective than classical space filling design of all-at-once sampling because sequential sampling design is to add new sampling points by means of distance between sampling points or precdiction error obtained from metamodel. However, though the extremum points can strongly reflect the behaviors of responses, the existing sequential sampling designs are inefficient to approximate extremum points of original model. In this research, new sequential sampling approach using the sensitivity of Kriging model is proposed, so that new approach reflects the behaviors of response sequentially. Various sequential sampling designs are reviewed and the performances of the proposed approach are compared with those of existing sequential sampling approaches by using mean squared error. The accuracy of the proposed approach is investigated against optimization results of test problems so that superiority of the sensitivity approach is verified.