• 약학회지
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• 제47권3호
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• pp.148-153
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• 2003

Skin moisture is an important factor in skin health. Measurement of moisture content can provide diagnostic information on the condition of skin. In this study, a portable near-infrared (NIR) system was newly integrated with a photo diode array detector that has no moving parts, and this system has been successfully applied for the evaluation of human skin moisture. Diffuse reflectance spectra were collected and transformed to absorbance using 1 nm step size over the wavelength range of 1100 nm to 2200 nm. Partial least squares regression (PLSR) was applied to develop a calibration model. For practical use for the evaluation of human skin moisture, the PLS model for human skin moisture was developed in vivo using the portable NIR system on the basis of the relative water content values of stratum corneum from the conventional capacitance method. The PLS model showed a good correlation. The calibration with the use of PLS model predicted human moisture with a standard error of prediction (SEP) of 3.5 at 1120∼1730 nm range. This study showed the possibility of skin moisture measurement using portable NIR system.

• IEIE Transactions on Smart Processing and Computing
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• 제4권6호
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• pp.407-412
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• 2015

In model-based tracking, an accurate 3D model of a target object or scene is mostly assumed to be known or given in advance, but the accuracy of the model should be guaranteed for accurate pose estimation. In many application domains, on the other hand, end users are not highly distracted by tracking errors from certain levels of modeling errors. In this paper, we examine perceptual tracking errors, which are predominantly caused by modeling errors, on subjective evaluation and compare them to computational tracking errors. We also discuss the tolerance of modeling errors by analyzing their permissible ranges.

• 한국항해항만학회지
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• 제47권2호
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• pp.93-99
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• 2023

This study aimed to determine relationships among risk factors influencing container port operation using Bayesian network. Risk factors identified from prior studies were classified into five groups: human error, machinery error, environmental risk, security risk, and natural disasters. P anel experts discussed identified risk factors to fulfil conditional probability tables of the interdependence model. The interdependence model was also validated by sensitivity analysis and provided an interrelation of factors influencing the direction of each other. Results of the interdependence model were partially in line with results from prior studies while practices in the global port industry confirmed interrelationships of risk factors. In addition, the relationship between top-ranked risk factors can provide a schematic drawing of the model. Accordingly, results of this study can expand the prior research in the Korean port industry, which may help port authorities improve risk management and reduce losses from the risk.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2011년도 추계학술대회
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• pp.13-15
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• 2011

This report represents analysis of the maritime casualty in terms of Bridge Resource Management. We evaluate the attitudes and knowledge of bridge officer regarding human factors issues that have been identified as causal to mishaps in high-risk situations. So to reduce human errors our goal is to establish effective officer resource management (ORM) program which is based on all subjects for cadets in IMO model course. In harmonization with STCW(The International Convention on Standards of training, Certification and Watch-keeping for Seafarers), as the result, the curriculumss in the maritime education institutions is surveyed to improve our education system and then reduce the human errors by mariners at sea.

• 품질경영학회지
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• 제24권1호
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• pp.10-19
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• 1996

In order to build a model to predict accidents in a complicated man-machine sytem, human errors and mechanical reliability can be viewed as the most important factors. Such factors are explicitly included in a generic model. Another point to keep in mind is that the model should be constructed so that the data in a type of accident can be utilized to predict other types of accidents. Based on such a generic prediction model, we analyze the effects of system reliability. When we improve the system reliability, in other words, when there are changes in model parameters, the predicted time to next accidents should be modified influencing the effects of system reliability improvements. We apply Bayesian approach and finds the formula to explain how a change on the machine reliability or human error probability influences the time to next accident.

• 대한전자공학회논문지
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• 제27권6호
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• pp.937-943
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• 1990

In this paper, a subband coding scheme using the human visual system(HVS) model for encoding monochrome images is proposed to produce perceptually higher quality images compared with the regular subband coding scheme. The proposed approach first transforms the intensity image to the density image by a point nonlinear transformation. A frequency band dexomposition of the density image is carried out by means of 2-D seaprable quadrature mirror filters, which split the density image spectrum into 16 equall rate subbands. Bits are allocated among the subbands to minimize the weighted mean squar error (WMSE) for differential pulse code modulation(DPCM) coding of the subbands. The weight for each subband is calculated from the modulation transfer function (MTF) of the HVS model at corresponding frequencies. The performances of the proposed approach are evaluated for 256 * 256 monochrome images at the bit rates of 0.5, 0.75 and 1.0 bita per pixel. Computer simulation results indicate that using the HVS model yields more pleasing reconstructed images than regular subband coding approach which does not use HVS model.

• 한국안전학회지
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• 제37권2호
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• pp.35-42
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• 2022

When an accident occurs, the associated human activity is typically regarded as a "human error," or a temporal deviation. On the other hand, if the accident results in a serious loss or if it evokes a social issue, the person determined to be responsible may be punished with a "violation" of related laws or regulations. However, as Heinrich stated, it is neither appropriate nor reasonable in terms of probability theory and cognitive science to distinguish whether it is a "human error" or a "violation" with a criterion of resultant accident severity. Nonetheless, some in society get on the social climate to strengthen regulations on workers who have caused accidents, especially violations. This response can present a social issue due to the lack of systematic judgment procedure which distinguishes violations from human errors. The purpose of this study was to develop an objective and systematic procedure to assess whether workers' activities which induced industrial accidents should be categorized as violations rather than human errors. Various analysis techniques for the determination of violation procedure were investigated and compared using an analysis approach method. An appropriate technique was not found, however, for judging the culpability of intentional violations. As an alternative, this study developed the process of creating violations, based on cognitive procedure, as well as the criteria to determine and categorize an activity as a violation. In addition, the developed procedure was applied to cases of industrial accidents and nuclear power plant issues to test its practical applicability. The study demonstrated that the proposed model could be used to determine the existence of a violation even in the case of multiple workers who work simultaneously.

• Journal of Animal Science and Technology
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• 제64권3호
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• pp.531-538
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• 2022

In Italy, buffalo mozzarella is a largely sold and consumed dairy product. The fraudulent adulteration of buffalo milk with cheaper and more available milk of other species is very frequent. In the present study, Fourier transform infrared spectroscopy (FTIR), in combination with multivariate analysis by partial least square (PLS) regression, was applied to quantitatively detect the adulteration of buffalo milk with cow milk by using a fully automatic equipment dedicated to the routine analysis of the milk composition. To enhance the heterogeneity, cow and buffalo bulk milk was collected for a period of over three years from different dairy farms. A total of 119 samples were used for the analysis to generate 17 different concentrations of buffalo-cow milk mixtures. This procedure was used to enhance variability and to properly randomize the trials. The obtained calibration model showed an R² ≥ 0.99 (R² cal. = 0.99861; root mean square error of cross-validation [RMSEC] = 2.04; R² val. = 0.99803; root mean square error of prediction [RMSEP] = 2.84; root mean square error of cross-validation [RMSECV] = 2.44) suggesting that this method could be successfully applied in the routine analysis of buffalo milk composition, providing rapid screening for possible adulteration with cow's milk at no additional cost.

• 스마트미디어저널
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• 제12권11호
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• pp.48-56
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• 2023

3차원 인체자세추정은 스포츠, 동작인식, 영상매체의 특수효과 등의 분야에서 널리 활용되고 있는 기술이다. 이를 위한 여러 방법들 중 다중 시점 3차원 인체자세추정은 현실의 복잡한 환경에서도 정밀한 추정을 하기 위해 필수적인 방법이다. 하지만 기존 다중 시점 3차원 인체자세추정 모델들은 3차원 특징 맵을 사용함에 따라 시간 복잡도가 높은 단점이 있다. 본 논문은 계산 복잡도가 적은 트랜스포머 기반 기존 단안 시점 다중 프레임 모델을 다중 시점에 대한 3차원 인체자세추정으로 확장하는 방법을 제안한다. 다중 시점으로 확장하기 위하여 먼저 2차원 인체자세 검출자 CPN(Cascaded Pyramid Network)을 활용하여 획득한 4개 시점의 17가지 관절에 대한 2차원 관절좌표를 연결한 8차원 관절좌표를 생성한다. 그 다음 이들을 패치 임베딩 한 뒤 17×32 데이터로 변환하여 트랜스포머 모델에 입력한다. 마지막으로, 인체자세를 출력하는 MLP(Multi-Layer Perceptron) 블록을 매 반복 마다 사용한다. 이를 통해 4개 시점에 대한 3차원 인체자세추정을 동시에 수정한다. 입력 프레임 길이 27을 사용한 Zheng[5]의 방법과 비교했을 때 제안한 방법의 모델 매개변수의 수는 48.9%, MPJPE(Mean Per Joint Position Error)는 20.6mm(43.8%) 감소했으며, 학습 횟수 당 평균 학습 소요 시간은 20배 이상 빠르다.

• 대한음성학회지:말소리
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• 제59호
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• pp.89-99
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• 2006

This paper proposes a new structural head-related transfer function(HRTF) model to produce sounds in a virtual environment. The proposed HRTF model generates 3-D sounds by using a head model, a pinna model and the proposed distance model for azimuth, elevation, and distance that are three aspects for 3-D sounds, respectively. In particular, the proposed distance model consists of level normalization block distal region model, and proximal region model. To evaluate the performance of the proposed model, we setup an experimental procedure that each listener identifies a distance of 3-D sound sources that are generated by the proposed method with a predefined distance. It is shown from the tests that the proposed model provides an average distance error of $0.13{\sim}0.31$ meter when the sound source is generated as if it is 0.5 meter $\sim$ 2 meters apart from the listeners. This result is comparable to the average distance error of the human listening for the actual sound source.