• Smart Structures and Systems
• /
• 제6권7호
• /
• pp.851-866
• /
• 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
• /
• 제12권5호
• /
• pp.813-820
• /
• 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
• /
• 제21권12spc호
• /
• pp.549-555
• /
• 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
• /
• 제22권4호
• /
• pp.261-273
• /
• 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.

• 한국ITS학회 논문지
• /
• 제19권6호
• /
• pp.222-234
• /
• 2020

자율주행차는 GPS 및 레이더, 라이다, 카메라, IMU 등 다수의 센서가 장착되어 도심 교차로 주행 환경에서 다양한 교통체계를 인지하고 판단하여 주행하지만 장착된 센서의 감지 거리를 벗어나는 영역에 대한 예측 및 판단의 한계 등으로 자율주행차의 교차로 사고 비율은 전체 사고의 88%로 사고 비율이 높다. 따라서 ITS 도입으로 V2V, V2I를 통한 비신호 교차로 사고 회피 전략 연구가 진행되고 있을 뿐만 아니라 고장 상황에서 안전한 교차로 주행에 대한 연구도 진행되고 있지만 단순한 교차로 시나리오를 통한 검증과 단편적인 V2V 고장만을 제시하고 있다. 본 논문에서는 V2V 모듈의 아키텍쳐를 분석하여 V2V 모듈별 위험 요인을 분석하여 고장모드를 정의하였다. 또한 다양한 도로 조건 및 교통량에 따라 교차로 시나리오를 제시하여 ISO-26262 Part3 프로세스를 활용하여 HARA를 수행하여 자율주행차의 오작동에 대해 시뮬레이션 기반 위험성을 분석하여 ASIL을 제시하였다. V2V 모듈의 각 컴포넌트별 모니터링 컨셉을 제안하였고 시뮬레이션을 통해 모니터링 커버리지를 제시하였다.

• 한국지반공학회논문집
• /
• 제23권11호
• /
• pp.87-98
• /
• 2007

화재 후 터널 구조물의 신속한 복구를 위하여 화재손상 구간을 정확하고 빠르게 파악하는 것이 무엇보다도 중요하다고 할 수 있다. 본 연구에서는 화재로 인한 라이닝 콘크리트의 역학적 특성 변과를 라이닝의 두께방향으로 연속적으로 측정하기 위한 천공저항시험법을 제안하고, 천공시험으로부터 측정된 천공 변수들로부터 모르타르와 콘크리트의 역학적 특성을 추정하고자 하였다. 비교적 균질한 모르타르에 대하여 일련의 천공저항시험을 실시한 결과, 분당회전수가 1,300rpm, 관입속도가 1.40mm/sec, 그리고 비트직경이 10mm인 경우에 측정된 천공 반력값의 편차가 가장 작게 나타나 최적의 시험조건으로 판별할 수 있었다. 최적 시험조건에서 모르타르에 대해 천공저항시험을 실시한 결과, 천공반력과 모르타트의 압축강도 및 탄성계수 사이의 결정계수가 각각 0.91 및 0.93으로 나타나 양호한 상관관계를 도출할 수 있었다. 또한 콘크리트에 존재하는 골재의 영향을 고려하기 위하여 반력 에너지 개념을 제시하였고 실제 압축강도와의 결정계수는 0.94로서 역시 양호한 상관관계를 도출할 수 있었다. 이상과 같이 천공 비트의 관입과 동시에 연속적으로 재료의 역학적 특성을 추정할 수 있는 천공저항시험의 적용 가능성을 파악할 수 있었다.

• Smart Structures and Systems
• /
• 제12권1호
• /
• pp.1-22
• /
• 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.

• 대한인간공학회지
• /
• 제31권1호
• /
• pp.63-76
• /
• 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.

• 대한간호학회지
• /
• 제50권3호
• /
• pp.444-458
• /
• 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.

• 센서학회지
• /
• 제27권2호
• /
• pp.118-125
• /
• 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.