• Structural Engineering and Mechanics
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• v.42 no.1
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• pp.55-72
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• 2012

Precast-cast insitu concrete bridge construction is widely practiced for small to medium span structures. These bridges consist of precast pre-stressed concrete beams of various cross-sections with a cast in-situ reinforced concrete slab. The connection between the beams and the slab is via shear links often included during the manufacturing process of the beams. This form of construction is attractive as it provides for standardisation, reduced formwork and construction time. The assessment of the integrity of shear connectors in existing bridges is a major challenge. A procedure for assessment of shear connectors based on vibration testing and finite element model updating is proposed. The technique is applied successfully to a scaled model bridge model and an existing bridge structure.

• Structural Engineering and Mechanics
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• v.36 no.5
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• pp.529-544
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• 2010

Nonlinear equations of structures are generally solved numerically by the iterative solution of linear equations. However, this iterative procedure diverges when the tangent stiffness is ill-conditioned which occurs near limit points. In other words, a major challenge with simple iterative methods is failure caused by a singular or near singular Jacobian matrix. In this paper, using the Newton-Raphson algorithm based on Davidenko's equations, the iterations can traverse the limit point without difficulty. It is argued that the propose algorithm may be both more computationally efficient and more robust compared to the other algorithm when tracing path through severe nonlinearities such as those associated with structural collapse. Two frames are analyzed using the proposed algorithm and the results are compared with the previous methods. The ability of the proposed method, particularly for tracing the limit points, is demonstrated by those numerical examples.

• Nuclear Engineering and Technology
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• v.42 no.4
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• pp.414-425
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• 2010

In this paper, a procedure is developed for identifying a number of representative solutions manageable for decision-making in a multiobjective optimization problem concerning the test intervals of the components of a safety system of a nuclear power plant. Pareto Front solutions are identified by a genetic algorithm and then clustered by subtractive clustering into "families". On the basis of the decision maker's preferences, each family is then synthetically represented by a "head of the family" solution. This is done by introducing a scoring system that ranks the solutions with respect to the different objectives: a fuzzy preference assignment is employed to this purpose. Level Diagrams are then used to represent, analyze and interpret the Pareto Fronts reduced to the head-of-the-family solutions.

• Journal of Chest Surgery
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• v.52 no.1
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• pp.32-35
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• 2019

Surgical management of interrupted aortic arch (IAA) with systemic outflow tract obstruction is clearly a challenge. If both ventricles are adequate, the Yasui operation is a useful option. Otherwise, a staged approach through initial hybrid palliation and delayed biventricular repair, tailored to the degree of obstructed outflow, serves to avoid a high-risk neonatal procedure. Herein, we present a patient with IAA and severe systemic outflow tract obstruction whose treatment involved hybrid palliation, followed by a Yasui operation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3855-3867
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• 2022

Name separation (splitting full names into surnames and given names) is not a tedious task in a multiethnic country because the procedure for splitting surnames and given names is ethnicity-specific. Malaysia has multiple main ethnic groups; therefore, separating Malaysian full names into surnames and given names proves a challenge. In this study, we develop a two-phase framework for Malaysian name separation using deep learning. In the initial phase, we predict the ethnicity of full names. We propose a recurrent neural network with long short-term memory network-based model with character embeddings for prediction. Based on the predicted ethnicity, we use a rule-based algorithm for splitting full names into surnames and given names in the second phase. We evaluate the performance of the proposed model against various machine learning models and demonstrate that it outperforms them by an average of 9%. Moreover, transfer learning and fine-tuning of the proposed model with an additional dataset results in an improvement of up to 7% on average.

• Journal of Chest Surgery
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• v.42 no.1
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• pp.87-91
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• 2009

The surgical management of complete transposition of the great arteries, ventricular septal defect, and pulmonary stenosis still remain a significant challenge. The Rastelli (REV procedure) remains the most widely applied procedure for surgical repair of these lesions. Although the Rastelli procedure can be performed with good early results, the intermediate- and long-term results have been less than satisfactory because of deterioration of the hemodynamic performance of the LVOT or RVOT. We performed a modified Nikaidoh procedure as an alternative surgical procedure in a 19-month-old boy weighing 10.4 kg with this anomaly. Aortic translocation with biventricular outflow tract reconstruction resulted in a more "normal" anatomic repair and postoperative echocardiography showed straight, direct, and unobstructed ventricular outflow.

• Journal of Microbiology and Biotechnology
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• v.27 no.4
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• pp.718-724
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• 2017

The combination of rabies immunoglobulin (RIG) with a vaccine is currently effective against rabies infections, but improvements are needed. Genetic engineering antibody technology is an attractive approach for developing novel antibodies to replace RIG. In our previous study, a single-chain variable fragment, scFv57R, against rabies virus glycoprotein was constructed. However, its inherent weak stability and short half-life compared with the parent RIG may limit its diagnostic and therapeutic application. Therefore, an acidic tail of synuclein (ATS) derived from the C-terminal acidic tail of human alpha-synuclein protein was fused to the C-terminus of scFv57R in order to help it resist adverse stress and improve the stability and half-life. The tail showed no apparent effect on the preparation procedure and affinity of the protein, nor did it change the neutralizing potency in vitro. In the ELISA test of molecular stability, the ATS fusion form of the protein, scFv57R-ATS, showed an increase in thermal stability and longer half-life in serum than scFv57R. The protection against fatal rabies virus challenge improved after fusing the tail to the scFv, which may be attributed to the improved stability. Thus, the ATS fusion approach presented here is easily implemented and can be used as a new strategy to improve the stability and half-life of engineered antibody proteins for practical applications.

• Korean Journal of Agricultural Science
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• v.41 no.2
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• pp.135-139
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• 2014

Pathogenic E. coli associated post-weaning diarrhea (PWD) and edema disease are common diseases in commercially-housed weanling pigs. An enterotoxigenic E. coli (ETEC) oral challenge model has been used to mimic the physiological responses observed in commercial conditions. However, an oral challenge procedure has two major limitations: (1) the ETEC cell density is unknown at the point of oral inoculation, and (2) blending ETEC with traditional TSB (trypticase soy broth) is not palatable and hence decreases acceptability by piglets. Therefore, the purposes of this study were to (1) establish a regression equation that can be used for estimation of ETEC concentration in dilution media using the spectrophotometric measurement of cell density; and (2) examine survival of ETEC after blending either with TSB, sweetener or dextrose. A strain of ETEC (serogroup beta-hemolytic E. coli O149; K91; F4; toxins LT, STa, STb) was grown in TSB for 3.5 hours, centrifuged, the supernatant was discarded, and the ETEC pellet was then blended either with TSB (100 mL), sweetener (60 mL TSB + 40 mL fruit flavored concentrate), or dextrose (50 mL TSB + 50 mL dextrose; 0.5g/mL dextrose). Cell density was measured using the colorimetric method and also plated on a 5% sheep blood agar for counting of ETEC colony forming units at 0, 5, 35, 65 and 125 min after blending. The optical density at 600 nm explained 83% of ETEC colony forming units, indicating that the established linear equation (y= 6E+08x - 4E+07, P<0.004) can be used for robust quantification of ETEC cell density in TSB, sweetener and dextrose media. When ETEC was blended with sweetener and dextrose, survival of ETEC was decreased by 45% and 72% within 5 min post-blending. Therefore, further research is required to find out the suitable medium that has potential to improve palatability without compromising survival of ETEC.

• Smart Structures and Systems
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• v.29 no.6
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• pp.757-766
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• 2022

To train deep learning algorithms, a sufficient number of data are required. However, in most engineering systems, the acquisition of fault data is difficult or sometimes not feasible, while normal data are secured. The dearth of data is one of the major challenges to developing deep learning models, and fault diagnosis in particular cannot be made in the absence of fault data. With this context, this paper proposes an anomaly detection methodology for rotating machines using only normal data with self-labeling. Since only normal data are used for anomaly detection, a self-labeling method is used to generate a new labeled dataset. The overall procedure includes the following three steps: (1) transformation of normal data to self-labeled data based on a pretext task, (2) training the convolutional neural networks (CNN), and (3) anomaly detection using defined anomaly score based on the softmax output of the trained CNN. The softmax value of the abnormal sample shows different behavior from the normal softmax values. To verify the proposed method, four case studies were conducted, on the Case Western Reserve University (CWRU) bearing dataset, IEEE PHM 2012 data challenge dataset, PHMAP 2021 data challenge dataset, and laboratory bearing testbed; and the results were compared to those of existing machine learning and deep learning methods. The results showed that the proposed algorithm could detect faults in the bearing testbed and compressor with over 99.7% accuracy. In particular, it was possible to detect not only bearing faults but also structural faults such as unbalance and belt looseness with very high accuracy. Compared with the existing GAN, the autoencoder-based anomaly detection algorithm, the proposed method showed high anomaly detection performance.

• Journal of Korean Society of Transportation
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• v.17 no.2
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• pp.55-68
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• 1999

Many ITS services require map databases in digital form to meet desired needs. Due to the dynamic nature of ITS and the sheer diversity of applications, the design and development of spatial databases to meet those needs pose a major challenge to both the public and private sectors. This challenge is further complicated by the necessity to transfer locationally referenced information between different kinds of databases and spatial data handling systems so that ITS products will work seamlessly across the region and nation. The Purpose of this paper is to develop the framework-models commonly to reference locations in the various applications and systems-the ITS Map Datum and LRS(Location Referencing System). The ITS Map Datum consists of the around control points which are the prime intersections (nodes) of the nationwide road network In this study, the major points have been determined along wish link-node modeling procedure. LRS, defined as a system for determining the position (location) of an entity relative to other entities or to some external frame of reference, has also been set up using CSOM type method. The method has been implemented using ArcView GIS software over the Kangnam and Seocho districts in the city of Seoul, showing that the implemented LRS scheme can be used successfully elsewhere. With the proper advent of the K.ITS architecture and services, the procedure can be used to improve the data sharing and to inter operate among systems, enhancing the efficiency both in terms of money and time.