• Smart Structures and Systems
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• v.6 no.7
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• pp.851-866
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• 2010

This paper presents a new concept of using PZT (lead zircornate titanate) transducers as a non-destructive testing (NDT) tool for evaluating quality of concrete. Detection of defects in concrete is very important in order to check the integrity of concrete structures. The electro-mechanical impedance (EMI) response of PZT transducers bonded onto a concrete specimen can be used for evaluating local condition of the specimen. Measurements are carried out by electrically exciting the bonded PZT transducers at high frequency range and taking response measurements of the transducers. In this study, the compression test results showed that concrete specimens without sufficient compaction are likely to fall below the desired strength. In addition, the strength of concrete was greatly reduced as the voids in concrete were increased. It was found that the root mean square deviation (RMSD) values yielded between the EMI signatures for concrete specimens in dry and saturated states showed good agreement with the specimens' compressive strength and permeable voids. A quality metric was introduced for predicting the quality of concrete based on the dry-saturated state of concrete specimens. The simplicity of the method and the current development towards low cost and portable impedance measuring system, offer an advantage over other NDE methods for evaluating concrete quality.

• Journal of Power Electronics
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• v.12 no.5
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• pp.813-820
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• 2012

This paper presents the development of a software supported acquisition system for metrological verification and testing of the equipment for monitoring and analysis of the basic electrical power quality parameters. The described procedure consists of two functionally connected segments. The first segment involves generation of the reference three-phase voltage signals, including the possibility of simulation of the various power quality disturbances, typical for electrical power distribution networks. The second part of this procedure includes the real-time recording of power quality disturbances in three-phase distribution networks. The procedure is functionally supported by the virtual instrumentation concept, including a software application developed in LabVIEW environment and data acquisition boards NI 6713 and NI 9215A. The software support of this system performs graphical presentation of the previously generated and recorded signal waveforms. A number of the control functions and buttons, implemented on the virtual instrument front panels, are provided to adjust the basic signal acquisition, generation and recording parameters.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.549-555
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• 2021

Machine Learning(ML) splits data into 3 parts, which are usually 60% for training, 20% for validation, and 20% for testing. It just splits quantitatively instead of selecting each set of data by a criterion, which is very important concept for the adequacy of test data. ML measures a model's accuracy by applying a set of validation data, and revises the model until the validation accuracy reaches on a certain level. After the validation process, the complete model is tested with the set of test data, which are not seen by the model yet. If the set of test data covers the model's attributes well, the test accuracy will be close to the validation accuracy of the model. To make sure that ML's set of test data works adequately, we design an experiment and see if the test accuracy of model is always close to its validation adequacy as expected. The experiment builds 100 different SVM models for each of six data sets published in UCI ML repository. From the test accuracy and its validation accuracy of 600 cases, we find some unexpected cases, where the test accuracy is very different from its validation accuracy. Consequently, it is not always true that ML's set of test data is adequate to assure a model's quality.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.261-273
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• 2022

Over the last decade, the scientific community has been actively developing technologies for automated software bug fixes called Automated Program Repair (APR). Several APR techniques have recently been proposed to effectively address multiple classroom programming errors. However, little attention has been paid to the advances in effective APR techniques for software bugs that are widely occurring during the software life cycle maintenance phase. To further enhance the concept of software testing and debugging, we recommend an optimized automated software repair approach based on hybrid technology (OAPR-HOML'1). The first contribution of the proposed OAPR-HOML'1 technique is to introduce an improved grasshopper optimization (IGO) algorithm for fault location identification in the given test projects. Then, we illustrate an opposition learning based artificial neural network (OL-ANN) technique to select AST node-level transformation schemas to create the sketches which provide automated program repair for those faulty projects. Finally, the OAPR-HOML'1 is evaluated using Defects4J benchmark and the performance is compared with the modern technologies number of bugs fixed, accuracy, precession, recall and F-measure.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.222-234
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• 2020

Autonomous vehicles are equipped with a wide rage of sensors such as GPS, RADAR, LIDAR, camera, IMU, etc. and are driven by recognizing and judging various transportation systems at intersections in the city. The accident ratio of the intersection of the autonomous vehicles is 88% of all accidents due to the limitation of prediction and judgment of an area outside the sensing distance. Not only research on non-signalized intersection collision avoidance strategies through V2V and V2I is underway, but also research on safe intersection driving in failure situations is underway, but verification and fragments through simple intersection scenarios Only typical V2V failures are presented. In this paper, we analyzed the architecture of the V2V module, analyzed the causal factors for each V2V module, and defined the failure mode. We presented intersection scenarios for various road conditions and traffic volumes. we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to analyze the risk of autonomous vehicle based on the simulation. We presented ASIL, which is the result of risk analysis, proposed a monitoring concept for each component of the V2V module, and presented monitoring coverage.

• Journal of the Korean Geotechnical Society
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• v.23 no.11
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• pp.87-98
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• 2007

For the quick rehabilitation of a fire-damaged tunnel structure, it is the most important procedure to investigate the fire-induced damaged zone rapidly. This study aims to propose a new drilling resistance testing method by which mechanical properties of tunnel concrete lining altered by high temperature can be estimated easily and continuously. Especially, it alms to derive the relationships to estimate mechanical properties of mortar and concrete materials from drilling parameters. To obtain the optimum testing condition, a series of drilling resistance tests were carried out for mortar specimens. When the rotation per minute of drill bit, tile penetration rate and the bit diameter were 1,300 rpm, 1.40 mm/sec, and 10 mm respectively, the deviation of measured drilling resistance forces was minimal. Under the optimum testing condition, the relationships between drilling resistance and mechanical properties of mortar specimens were shown to be very favorable. The concept of replacing a mean value of resistance farces measured during drilling with the resistance energy was proposed to consider the effects of randomly distributed aggregates inside a concrete material on drilling resistance. When the concept was applied to concrete materials, a favorable relationship between actual compressive strength and drilling resistance energy was also successfully derived.

• Smart Structures and Systems
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• v.12 no.1
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• pp.1-22
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• 2013

Magnetic nanoparticle based bioseparation in microfluidics is a multiphysics phenomenon that involves interplay of various parameters. The ability to understand the dynamics of these parameters is a prerequisite for designing and developing more efficient magnetic cell/bio-particle separation systems. Therefore, in this work proof-of-concept experiments are combined with advanced numerical simulation to design and optimize the capturing process of magnetic nanoparticles responsible for efficient microfluidic bioseparation. A low cost generic microfluidic platform was developed using a novel micromolding method that can be done without a clean room techniques and at much lower cost and time. Parametric analysis using both experiments and theoretical predictions were performed. It was found that flow rate and magnetic field strength greatly influence the transport of magnetic nanoparticles in the microchannel and control the capturing efficiency. The results from mathematical model agree very well with experiments. The model further demonstrated that a 12% increase in capturing efficiency can be achieved by introducing of iron-grooved bar in the microfluidic setup that resulted in increase in magnetic field gradient. The numerical simulations were helpful in testing and optimizing key design parameters. Overall, this work demonstrated that a simple low cost experimental proof-of-concept setup can be synchronized with advanced numerical simulation not only to enhance the functional performance of magneto-fluidic capturing systems but also to efficiently design and develop microfluidic bioseparation systems for biomedical applications.

• Journal of the Ergonomics Society of Korea
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• v.31 no.1
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• pp.63-76
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• 2012

Objective: The main objective of this study is to propose a user-centered assessment metric for ubiquitous services. Background: As the ubiquitous era took off, the interactions between ubiquitous services and users have come to take an important position. It is essential to conceptualize a new assessment model that considers human-system interaction capability with a user-centered design perspective. Method: The evaluation model for the interactivity of ubiquitous service was approached from the concept of usability and inter-personality of services. As a validation study, suggested assessment metric was utilized to evaluate the u-Home service. Priority weighting of each assessment metric was derived using the quantification type-I analysis. Results: To evaluate interactivity, this study suggested a quantitative metric for user testing performed after classifying the interactivity characteristics to contextualization; ubiquity; user experience; and service capability. Conclusion: This study suggest the metric for the ubiquitous service that are experienced in real life, and introduced the concept of ubiquitous service interactivity. Application: The suggested evaluation metric can be used to evaluate interactivity level of ubiquitous service and identify the potential problem and usability requirements at the early stage of service development.

• Journal of Korean Academy of Nursing
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• v.50 no.3
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• pp.444-458
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• 2020

Purpose: The purpose of this study was to develop the Job Esteem Scale for Korean Nurses (JES-KN) and verify its validity and reliability. Methods: Preliminary items were based on the attributes and indicators elicited from a concept analysis study on Korean nurses' job-esteem. The final preliminary tool for the main survey was confirmed through the content validity test of 10 experts and preliminary survey of 20 hospital nurses. The final preliminary scale was used on 350 hospital nurses in the scale testing phase for the main survey designed to test the validity and reliability of the scale. Results: The final scale consisted of 28 items and 6 factors, these factor explained 66.6% of the total variance. The correlation between the total score and factors ranged from .64 and .84, validating that each sub-factor is suitable to explain job esteem. The correlation coefficient between this scale and the Job Satisfaction Scale for Clinical Nurses ranged from .41 to .70, and the internal consistency for the scale using Cronbach's α for the total items was .94. Conclusion: The JES-KN is a valid and reliable tool that reflects the reality of clinical sites accordingly. The JES-KN may well be used effectively to assess and evaluate the job esteem of Korean nurses.

• Journal of Sensor Science and Technology
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• v.27 no.2
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• pp.118-125
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• 2018

An evaluation system for an electronic-nose concept using three types of metal oxide gas sensors that react similarly to the human olfactory cells was constructed for the quantitative and qualitative evaluation of aroma fragrances. Four types of aroma fragrances (lavender, orange, jasmine, and Roman chamomile), which are commonly used in aromatherapy, were evaluated. All the gas sensors reacted remarkably to the aroma fragrances and the good correlation of r=0.58-0.88 with the aromatic odor intensities by olfaction was confirmed. From the results of the analysis of an electronic-nose concept for classifying the characteristics of aroma oil fragrances, aroma oils could be classified using the fragrance characteristics and oil extraction methods with the cumulative variability contribution rate of 95.65% (F1: 69.65%, F2: 26.03%) by principal component analysis. In the pattern recognition based on the artificial neural network, the four aroma fragrances were 100% recognized through the training data of 56 cases (70%) out of 80 cases, and the pattern recognition rate was 57.1%-71.4% through the validation and testing data of 24 cases (30%). The pattern recognition success rate through all confusion matrices was 82.1%, indicating that the classification of aroma oil fragrances using the three types of gas sensors was successful.