• 대한디지털의료영상학회논문지
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• 제11권2호
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• pp.59-62
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• 2009

The purpose of this study is to know about solution of insecurity sense for solving the tediousness and inducing comfortableness in long time MRI examination. Studies were examined with total of 117 patients that the intention expression of self is possible for a month without dividing man and woman in november 2006. Examination methods were filled in questionnaire after testing using Siemens Impact 1.0T. The musical art were selected through intranet search and record sale inquiry using CD player and speaker. That kind of a music were selected with Korean classical music's 10 chapter, pop song 10's chapter, classic's 10 chapter and Korean popular song's 10 chapter. With analytical method, patients of under 40 year-old, or older and patients using ear-pad and head-phone were classified into groups. As analysis result with question item of questionnaire, most of the patients were showed a favor(36.72%) in playing a music, specially, examination of about 15.38% which uses the headphone prefer a music as older generation of over 40 year-old. In conclusion, with installing of the professional musical program in MRI test rooms, if listening to the music with selection by oneself before testing by season, age, time through development of appropriate musical program will be able to expect the more effect.

• 한국미생물생명공학회:학술대회논문집
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• 한국미생물생명공학회 2000년도 Proceedings of 2000 KSAM International Symposium and Spring Meeting
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• pp.94-99
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• 2000

Bioluminescence is being used as a prevailing reporter of gene expression in microorganisms and mammalian cells. Bacterial bioluminescence draws special attention from environmental biotechnologists since it has many advantageous characteristics, such as no requirement of extra substractes, highly sensitive, and on-line measurability. Using bacterial bioluminescence as a reporter of toxicity has replaced the classical toxicity monitoring technology of using fish or daphnia with a cutting-edge technology. Fusion of bacterial stress promoters, which control the transcription of stress genes corresponding to heat-shock, DNA-, or oxidative-damaging stress, to the bacterial lux operon has resulted in the development of novel toxicity biosensors with a short measurement time, enhanced sensitivity, and ease and convenient usage. Therefore, these recombinant bioluminescent bacteria are expected to induce bacterial bioluminescence when the cells are exposed to stressful conditions, including toxic chemicals. We have used these recombinant bioluminescent bacteria in order to develop toxicity biosensors in a continuous, portable, or in-situ measurement from for air, water, and soil environments. All the data obtained from these toxicity biosensors for these environments were found to be repeatable and reproducible, and the minimum detection level of toxicity was found to be ppb (part per billion) levels for specific chemicals.

• ETRI Journal
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• 제41권6호
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• pp.797-810
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• 2019

Image saliency detection is the basis of perceptual image processing, which is significant to subsequent image processing methods. Most saliency detection methods can detect only a single object with a high-contrast background, but they have no effect on the extraction of a salient object from images with complex low-contrast backgrounds. With the prior knowledge, this paper proposes a method for detecting salient objects by combining the boundary contrast map and the geodesics-like maps. This method can highlight the foreground uniformly and extract the salient objects efficiently in images with low-contrast backgrounds. The classical receiver operating characteristics (ROC) curve, which compares the salient map with the ground truth map, does not reflect the human perception. An ROC curve with distance (distance receiver operating characteristic, DROC) is proposed in this paper, which takes the ROC curve closer to the human subjective perception. Experiments on three benchmark datasets and three low-contrast image datasets, with four evaluation methods including DROC, show that on comparing the eight state-of-the-art approaches, the proposed approach performs well.

• Applied Microscopy
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• 제46권4호
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• pp.206-216
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• 2016

This communication is to elucidate the state-of-the-art of techniques necessary to gather information on a new class of nanoelectronic devices known as memristors and related resistive switching devices, respectively. Unlike classical microelectronic devices such as transistors, the chemical and structural variations occurring upon switching of memristive devices require cutting-edge electron microscopy techniques. Depending on the switching mechanism, some memristors call for the acquisition of atomically resolved structural data, while others rely on atomistic chemical phenomena requiring the application of advanced X-ray and electron spectroscopy to correlate the real structure with properties. Additionally, understanding resistive switching phenomena also necessitates the application not only of pre- and post-operation analysis, but also during the process of switching. This highly challenging in situ characterization also requires the aforementioned techniques while simultaneously applying an electrical bias. Through this review we aim to give an overview of the possibilities and challenges as well as an outlook onto future developments in the field of nanoscopic characterization of memristive devices.

• 보존과학회지
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• 제6권1호
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• pp.71-78
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• 1997

유화는 재료 상호간의 접착력과 온도 및 습도에 대한 서로 다른 반응으로 인해 매우 다양한 피해양상을 보이게 된다. 그중에서 유화에 있어서 지지대의 평면성 변형은 가장 중요한 피해양상이다. 지지대 변형을 조정하기 위해 사용되었던 열, 압력, 수분과 고전적인 재료의 무분별한 사용은 작품에 오히려 피해를 주는 원인이 되었다. 현대회화 복원에 있어서는 이들 위험요소를 가급적 피하는 방법들이 고안되었고, 실제작품들에 시행되어 만족할만한 효과를 거두고 있다 본고에서는 작업시 작품의 안전성을 꾀하고 복원효과의 극대화를 위해 사용되는 저압 테이블, 변형조정틀과 신소재를 이용한 새로운 지지대 변형 조정 방법을 소개하였다.

• ETRI Journal
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• 제44권4호
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• pp.613-623
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• 2022

Autism spectrum disorder (ASD) is a developmental disorder associated with cognitive and neurobehavioral disorders. It affects the person's behavior and performance. Autism affects verbal and non-verbal communication in social interactions. Early screening and diagnosis of ASD are essential and helpful for early educational planning and treatment, the provision of family support, and for providing appropriate medical support for the child on time. Thus, developing automated methods for diagnosing ASD is becoming an essential need. Herein, we investigate using various machine learning methods to build predictive models for diagnosing ASD in children using facial images. To achieve this, we used an autistic children dataset containing 2936 facial images of children with autism and typical children. In application, we used classical machine learning methods, such as support vector machine and random forest. In addition to using deep-learning methods, we used a state-of-the-art method, that is, automated machine learning (AutoML). We compared the results obtained from the existing techniques. Consequently, we obtained that AutoML achieved the highest performance of approximately 96% accuracy via the Hyperpot and tree-based pipeline optimization tool optimization. Furthermore, AutoML methods enabled us to easily find the best parameter settings without any human efforts for feature engineering.

• Structural Engineering and Mechanics
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• 제85권1호
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• pp.119-133
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• 2023

Impact event is the key factor influencing the operational state of the mechanical equipment. Additionally, nonlinear factors existing in the complex mechanical equipment which are currently attracting more and more attention. Therefore, this paper proposes a novel hybrid-separate identification strategy to solve the force identification problem of the nonlinear structure under impact excitation. The 'hybrid' means that the identification strategy contains both l1-norm (sparse) and l2-norm regularization methods. The 'separate' means that the nonlinear response part only generated by nonlinear force needs to be separated from measured response. First, the state-of-the-art two-step iterative shrinkage/thresholding (TwIST) algorithm and sparse representation with the cubic B-spline function are developed to solve established normalized sparse regularization model to identify the accurate impact force and accurate peak value of the nonlinear force. Then, the identified impact force is substituted into the nonlinear response separation equation to obtain the nonlinear response part. Finally, a reduced transfer equation is established and solved by the classical Tikhonove regularization method to obtain the wave profile (variation trend) of the nonlinear force. Numerical and experimental identification results demonstrate that the novel hybrid-separate strategy can accurately and efficiently obtain the nonlinear force and impact force for the nonlinear structure.

• Advances in nano research
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• 제14권2호
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• pp.141-154
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• 2023

Effects of viscoelastic foundation on vibration of curved-beam structure with clamped and simply-supported boundary conditions is investigated in this study. In doing so, a micro-scale laminate composite beam with two piezoelectric face layer with a carbon nanotube reinforces composite core is considered. The whole beam structure is laid on a viscoelastic substrate which normally occurred in actual conditions. Due to small scale of the structure non-classical elasticity theory provided more accurate results. Therefore, nonlocal strain gradient theory is employed here to capture both nano-scale effects on carbon nanotubes and microscale effects because of overall scale of the structure. Equivalent homogenous properties of the composite core is obtained using Halpin-Tsai equation. The equations of motion is derived considering energy terms of the beam and variational principle in minimizing total energy. The boundary condition is assumed to be clamped at one end and simply supported at the other end. Due to nonlinear terms in the equations of motion, semi-analytical method of general differential quadrature method is engaged to solve the equations. In addition, due to complexity in developing and solving equations of motion of arches, an artificial neural network is design and implemented to capture effects of different parameters on the inplane vibration of sandwich arches. At the end, effects of several parameters including nonlocal and gradient parameters, geometrical aspect ratios and substrate constants of the structure on the natural frequency and amplitude is derived. It is observed that increasing nonlocal and gradient parameters have contradictory effects of the amplitude and frequency of vibration of the laminate beam.

• Geomechanics and Engineering
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• 제34권5호
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• pp.507-527
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• 2023

Accurately estimation of the geo-mechanical parameters in Artificial Ground Freezing (AGF) is a most important scientific topic in soil improvement and geotechnical engineering. In order for this, one way is using classical and conventional constitutive models based on different theories like critical state theory, Hooke's law, and so on, which are time-consuming, costly, and troublous. The others are the application of artificial intelligence (AI) techniques to predict considered parameters and behaviors accurately. This study presents a comprehensive data-mining-based model for predicting the Young's Modulus of frozen sand under the triaxial test. For this aim, several single and hybrid models were considered including additive regression, bagging, M5-Rules, M5P, random forests (RF), support vector regression (SVR), locally weighted linear (LWL), gaussian process regression (GPR), and multi-layered perceptron neural network (MLP). In the present study, cell pressure, strain rate, temperature, time, and strain were considered as the input variables, where the Young's Modulus was recognized as target. The results showed that all selected single and hybrid predicting models have acceptable agreement with measured experimental results. Especially, hybrid Additive Regression-Gaussian Process Regression and Bagging-Gaussian Process Regression have the best accuracy based on Model performance assessment criteria.

• Steel and Composite Structures
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• 제50권6호
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• pp.609-625
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• 2024

This paper presents an in-depth analysis of the nonlinear vibration of microbeams, with a particular emphasis on their application in sports monitoring systems. The research utilizes classical beam theory, modified couple stress theory, and von-Kármán nonlinear parameters to explore the behavior of microbeams. These microbeams are characterized by a non-uniform geometry, with materials that continuously change along the beam radius and a thickness that varies along the beam length. The main contribution lies in its exploration of the stability of smart sensors in sports structures, particularly those with non-uniform geometries. The research findings indicate that these non-uniform microbeams, when used in smart systems made of functionally graded temperature-dependent materials, can operate effectively in thermal environments. The smart system developed in this study demonstrates significant potential for use in sports applications, particularly in monitoring and gathering information. The insights gained from this research contribute to the understanding of the performance and optimization of microbeams in sports applications, particularly in the context of non-uniform geometries. This research, therefore, provides a foundation for the development of advanced, reliable, and efficient monitoring systems in sports applications.