• Smart Structures and Systems
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• v.17 no.6
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• pp.917-933
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• 2016

In a prestressed concrete bridge, the magnitude of the prestress force (PF) decreases with time. This unexpected loss can cause failure of a bridge which makes prestress force identification (PFI) critical to evaluate bridge safety. However, it has been difficult to identify the PF non-destructively. Although some research has shown the feasibility of vibration based methods in PFI, the requirement of having a determinate exciting force in these methods hinders applications onto in-service bridges. Ideally, it will be efficient if the normal traffic could be treated as an excitation, but the load caused by vehicles is difficult to measure. Hence it prompts the need to investigate whether PF and moving load could be identified together. This paper presents a synergic identification method to determine PF and moving load applied on a simply supported prestressed concrete beam via the dynamic responses caused by this unknown moving load. This method consists of three parts: (i) the PF is transformed into an external pseudo-load localized in each beam element via virtual distortion method (VDM); (ii) then these pseudo-loads are identified simultaneously with the moving load via Duhamel Integral; (iii) the time consuming problem during the inversion of Duhamel Integral is overcome by the load-shape function (LSF). The method is examined against different cases of PFs, vehicle speeds and noise levels by means of simulations. Results show that this method attains a good degree of accuracy and efficiency, as well as robustness to noise.

• Tribology and Lubricants
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• v.36 no.6
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• pp.332-341
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• 2020

High-speed turbomachinery implements gas foil bearings (GFBs) due to their distinctive advantages, such as high efficiency, lesser part count, and lower weight. This paper provides the test results of the static structural stiffnesses and loss factors of bump-type foil thrust bearings with increasing preload and bearing deflection. The focus of the current work is to experimentally quantify variability in structural stiffnesses and loss factors among the four test thrust bearings with identical design values and material of the bump and top foil geometries using the same (open-source) fabrication method. A simple test setup, using a rigidly mounted non-rotating shaft and thrust disk, measures the bearing bump deflections with increasing static loads on the test bearing. The inner and outer diameters of the test bearings are 41 mm and 81 mm, respectively. The loss factor, best-representing energy dissipation in the test bearings, is estimated from the area inside the local hysteresis loop of the load versus the bearing deflection curve. The measurements show that structural stiffnesses and loss factors of the test bearings significantly rely on applied preloads and bearing deflections. Local structural stiffnesses of the test bearings increase with applied preloads but decrease with bearing deflections. Changes of loss factors are less sensitive to applied preloads and bearing deflections compared to those of structural stiffnesses. Up to 35% variability in static load structural stiffnesses is found between bearings, while up to 30% variability in loss factors is found between bearings.

• Hip & pelvis
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• v.36 no.2
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• pp.101-107
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• 2024

Treatment of femoral bone defects continues to be a challenge in revision total hip arthroplasty (THA); therefore, meticulous preoperative evaluation of patients and surgical planning are required. This review provides a concise synopsis of the etiology, classification, treatment strategy, and prosthesis selection in relation to femoral bone loss in revision THA. A search of literature was conducted for identification of research articles related to classification of bone loss, management of femoral revision, and comparison of different types of stems. Findings of a thorough review of the included articles were as follows: (1) the Paprosky classification system is used most often when defining femoral bone loss, (2) a primary-length fully coated monoblock femoral component is recommended for treatment of types I or II bone defects, (3) use of an extensively porous-coated stem and a modular fluted tapered stem is recommended for management of types III or IV bone defects, and (4) use of an impaction grafting technique is another option for improvement of bone stock, and allograft prosthesis composite and proximal femoral replacement can be applied by experienced surgeons, in selected cases, as a final salvage solution. Stems with a tapered design are gradually replacing components with a cylindrical design as the first choice for femoral revision; however, further confirmation regarding the advantages and disadvantages of modular and nonmodular stems will be required through conduct of higher-level comparative studies.

• Smart Structures and Systems
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• v.9 no.2
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• pp.165-188
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• 2012

In the first part of the paper, the optimal design parameters for tuned liquid column dampers (TLCD) in harmonic pitching motion were investigated. The configurations in design tables include uniform and non-uniform TLCDs with cross-sectional ratios of 0.3, 0.6, 1, 2 and 3 for the design in different situations. A closed-form solution of the structural response was used for performing numerical optimization. The results from optimization indicate that the optimal structural response always occurs when the two resonant peaks along the frequency axis are equal. The optimal frequency tuning ratio, optimal head loss coefficient, the corresponding response and other useful quantities are constructed in design tables as a guideline for practitioners. As the value of the head loss coefficient is only available through experiments, in the second part of the paper, the prediction of head loss coefficients in the form of a design chart are proposed based on a series of large scale tests in pitching base motions, aiming to ease the predicament of lacking the information of head loss for those who wishes to make designs without going through experimentation. A large extent of TLCDs with cross-sectional ratios of 0.3, 0.6, 1, 2 and 3 and orifice blocking ratios ranging from 0%, 20%, 40%, 60% to 80% were inspected by means of a closed-form solution under harmonic base motion for identification. For the convenience of practical use, the corresponding empirical formulas for predicting head loss coefficients of TLCDs in relation to the cross-sectional ratio and the orifice blocking ratio were also proposed. For supplemental information to horizontal base motion, the relation of head loss values versus blocking ratios and the corresponding empirical formulas were also presented in the end.

• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.492-503
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• 2008

With the recent development and increasing importance of personal identification systems, biometric technologies with less risk of loss or unauthorized use are being popularized rapidly. In particular, because of their high identification rate and convenience, fingerprint identification systems are being used much more commonly than other biometric systems such as iris recognition, face recognition and vein pattern recognition. However, a fingerprint identification system has the problem that artificially forged finger-prints can be used as input data. Thus, in order to solve this problem, the present study proposed a method for detecting forged fingerprints by measuring the degree of attenuation when the light from an optical fingerprint sensor passes through the finger and analyzing changes in the transmission of light over stages at fixed intervals. In order to prove improvement in the performance of the proposed system, we conducted an experiment that compared the system with an existing multi-sensor recognition system that measures also the temperature of fingerprint. According to the results of the experiment, the proposed system improved the forged fingerprint detection rate by around 32.6% and this suggests the possibility of solving the security problem in fingerprint identification systems.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1406-1416
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• 2017

In complex and large-scale industries, properly designed fault detection and identification (FDI) systems considerably improve safety, reliability and availability of target processes. In thermal power plants (TPPs), generating units operate under very dangerous conditions; system failures can cause severe loss of life and property. In this paper, we propose a bagged auto-associative kernel regression (AAKR)-based FDI approach for steam boilers in TPPs. AAKR estimates new query vectors by online local modeling, and is suitable for TPPs operating under various load levels. By combining the bagging method, more stable and reliable estimations can be achieved, since the effects of random fluctuations decrease because of ensemble averaging. To validate performance, the proposed method and comparison methods (i.e., a clustering-based method and principal component analysis) are applied to failure data due to water wall tube leakage gathered from a 250 MW coal-fired TPP. Experimental results show that the proposed method fulfills reasonable false alarm rates and, at the same time, achieves better fault detection performance than the comparison methods. After performing fault detection, contribution analysis is carried out to identify fault variables; this helps operators to confirm the types of faults and efficiently take preventive actions.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.1
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• pp.113-120
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• 2014

In this paper, I present a new echo canceller using the adaptive cascade system identification (CSI) method, which a system response is divided into several responses so that each response is adaptively estimated and combined. Echo cancellation is required for a dual-duplex DSL, in order to allow each individual loop to operate in a full duplex fashion. Echo cancellation was one of the most difficult aspects of DSL design, requiring high linearity and total echo return loss in excess of 70 dB. Especially, for a fickle response, if the response is estimated by an adaptive filter, the filter needs more taps and the performance is decreased. But the response is divided into several responses, the computation complexities are decreased and the performance is increased. For the stage constant n, which represents the number of stages, if the response is not divided (n=1), the computation complexity of multiply is $2N^2$. And if the response is divided into two responses (n=2), the computation complexity of multiply is $2N^2$. Also, if n=3, the computation complexity is ${\frac{2}{3}}N^2$. Therefore, it is known that the computation complexity is decreased as n is increased. Finally, this proposed method is verified through simulation of echo canceller for digital subscriber line (DSL) application.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.183-189
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• 2023

A stroke is a medical disease where a blood vessel in the brain ruptures, causes damage to the brain. If the flow of blood and different nutrients to the brain is intermittent, symptoms may occur. Stroke is other reason for loss of life and widespread disorder. The prevalence of stroke is high in growing countries, with ischemic stroke being the high usual category. Many of the forewarning signs of stroke can be recognized the seriousness of a stroke can be reduced. Most of the earlier stroke detections and prediction models uses image examination tools like CT (Computed Tomography) scan or MRI (Magnetic Resonance Imaging) which are costly and difficult to use for actual-time recognition. Machine learning (ML) is a part of artificial intelligence (AI) that makes software applications to gain the exact accuracy to predict the end results not having to be directly involved to get the work done. In recent times ML algorithms have gained lot of attention due to their accurate results in medical fields. Hence in this work, Stroke disease identification system by using Machine Learning algorithm is presented. The ML algorithm used in this work is Artificial Neural Network (ANN). The result analysis of presented ML algorithm is compared with different ML algorithms. The performance of the presented approach is compared to find the better algorithm for stroke identification.

• Journal of Microbiology and Biotechnology
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• v.19 no.9
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• pp.898-903
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• 2009

Pullorum disease affecting poultry is caused by Salmonella enterica serovar Pullorum and results in severe economic loss every year, especially in countries with a developing poultry industry. The pathogenesis of S. Pullorum is not yet well defined, as the specific virulence factors still need to be identified. Thus, to isolate specific DNA fragments belonging to S. Pullorum, this study used suppression subtractive hybridization. As such, the genome of the S. Pullorum C79-13 strain was subtracted from the genome of Salmonella enterica serovar Gallinarum 9 and Salmonella enterica serovar Enteritidis CMCC(B) 50041, respectively, resulting in the identification of 20 subtracted fragments. A sequence homology analysis then revealed three types of fragment: phage sequences, plasmid sequences, and sequences with an unknown function. As a result, several important virulence-related genes encoding the IpaJ protein, colicin Y, tailspike protein, excisionase, and Rhs protein were identified that may play a role in the pathogenesis of S. Pullorum.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.26.5-26
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• 2001

This paper proposes a new approach to identifying the unknown parameters of continuous LTI systems. For parameter identification in continuous-time systems, the Linear Integral Filter (LIF) method generally has been used in the beginning. Especially, one of the most efficient LIF methods in the literature is to use a weighting function satisfying specific three constraints. In high order systems, even though the weighting function satisfies the three constraints, it is impossible to identify the exact parameters of the systems because of information loss arising from a great amount of magnitude differences among the weighting function and its high-order derivatives. This paper, using an LMI technique, shows the limitation in designing the weighting function of the existing methods, and ...