• Communications for Statistical Applications and Methods
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• 제30권6호
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• pp.551-560
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• 2023

Recently, there has been significant research into the recognition of human activities using three-dimensional sequential skeleton data captured by the Kinect depth sensor. Many of these studies employ deep learning models. This study introduces a novel feature selection method for this data and analyzes it using machine learning models. Due to the high-dimensional nature of the original Kinect data, effective feature extraction methods are required to address the classification challenge. In this research, we propose using the first four moments as predictors to represent the distribution of joint sequences and evaluate their effectiveness using two datasets: The exergame dataset, consisting of three activities, and the MSR daily activity dataset, composed of ten activities. The results show that the accuracy of our approach outperforms existing methods on average across different classifiers.

• Genomics & Informatics
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• 제4권3호
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• pp.129-132
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• 2006

Toxicogenomics has recently emerged in the field of toxicology and the DNA microarray technique has become common strategy for predictive toxicology which studies molecular mechanism caused by exposure of chemical or environmental stress. Although microarray experiment offers extensive genomic information to the researchers, yet high dimensional characteristic of the data often makes it hard to extract meaningful result. Therefore we developed toxicant enrichment analysis similar to the common enrichment approach. We also developed web-based system graPT to enable considerable prediction of toxic endpoints of experimental chemical.

• Communications for Statistical Applications and Methods
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• 제29권4호
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• pp.441-451
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• 2022

In the era of bigdata, scalability is a crucial issue in learning models. Among many others, the Alternating Direction of Multipliers (ADMM, Boyd et al., 2011) algorithm has gained great popularity in solving large-scale problems efficiently. In this article, we propose applying the ADMM algorithm to solve the least square problem penalized by the pairwise-difference penalty, frequently used to identify group structures among coefficients. ADMM algorithm enables us to solve the high-dimensional problem efficiently in a unified fashion and thus allows us to employ several different types of penalty functions such as LASSO, Elastic Net, SCAD, and MCP for the penalized problem. Additionally, the ADMM algorithm naturally extends the algorithm to distributed computation and real-time updates, both desirable when dealing with large amounts of data.

• Communications for Statistical Applications and Methods
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• 제29권2호
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• pp.203-223
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• 2022

We propose a Bayesian approach to cumulative logistic regression model for the ordinal response based on the orthogonal principal components via singular value decomposition considering the multicollinearity among predictors. The advantage of the suggested method is considering dimension reduction and parameter estimation simultaneously. To evaluate the performance of the proposed model we conduct a simulation study with considering a high-dimensional and highly correlated explanatory matrix. Also, we fit the suggested method to a real data concerning sprout- and scab-damaged kernels of wheat and compare it to EM based proportional-odds logistic regression model. Compared to EM based methods, we argue that the proposed model works better for the highly correlated high-dimensional data with providing parameter estimates and provides good predictions.

• Applied Microscopy
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• 제45권3호
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• pp.131-134
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• 2015

Here we show how by processing energy dispersive X-ray spectrometry (EDS) data obtained using highly sensitive, new generation EDS detectors in the AZtec LayerProbe software we can obtain data of sufficiently high quality to non-destructively measure the number of layers in two-dimensional (2D) $MoS_2$ and $MoS_2/WSe_2$ and thereby enable the characterization of working devices based on 2D materials. We compare the thickness measurements with EDS to results from atomic force microscopy measurements. We also show how we can use electron backscatter diffraction (EBSD) to address fabrication challenges of 2D materials. Results from EBSD analysis of individual flakes of exfoliated $MoS_2$ obtained using the Nordlys Nano detector are shown to aid a better understanding of the exfoliation process which is still widely used to produce 2D materials for research purposes.

• Korean Journal of Radiology
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• 제22권11호
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• pp.1894-1908
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• 2021

Double outlet right ventricle (DORV) is a relatively common congenital heart disease in which both great arteries are connected completely or predominantly to the morphologic RV. Unlike other congenital heart diseases, DORV demonstrates various anatomic and hemodynamic subtypes, mimicking ventricular septal defect, tetralogy of Fallot, transposition of the great arteries, and functional single ventricle. Because different surgical strategies are applied to different subtypes of DORV with ventricular septal defects, a detailed assessment of intracardiac anatomy should be performed preoperatively. Due to high spatial and contrast resolutions, cardiac CT can provide an accurate characterization of various intracardiac morphologic features of DORV. In this pictorial essay, major anatomic factors affecting surgical decision-making in DORV with ventricular septal defects were comprehensively reviewed using three-dimensional cardiac CT data. In addition, the surgical procedures available for these patients and major postoperative complications are described.

• International Journal of Computer Science & Network Security
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• 제24권5호
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• pp.79-88
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• 2024

The information retrieval domain deals with the retrieval of unstructured data such as text documents. Searching documents is a main component of the modern information retrieval system. Locality Sensitive Hashing (LSH) is one of the most popular methods used in searching for documents in a high-dimensional space. The main benefit of LSH is its theoretical guarantee of query accuracy in a multi-dimensional space. More enhancement can be achieved to LSH by adding a bit to its steps. In this paper, a new Dynamic Locality Sensitive Hashing (DLSH) algorithm is proposed as an improved version of the LSH algorithm, which relies on employing the hierarchal selection of LSH parameters (number of bands, number of shingles, and number of permutation lists) based on the similarity achieved by the algorithm to optimize searching accuracy and increasing its score. Using several tampered file structures, the technique was applied, and the performance is evaluated. In some circumstances, the accuracy of matching with DLSH exceeds 95% with the optimal parameter value selected for the number of bands, the number of shingles, and the number of permutations lists of the DLSH algorithm. The result makes DLSH algorithm suitable to be applied in many critical applications that depend on accurate searching such as forensics technology.

• 한국측량학회지
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• 제20권2호
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• pp.111-118
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• 2002

오늘날 측량장비 개발의 급속한 발전과 더불어 정밀도가 많이 향상되고 있고 컴퓨터를 이용한 지형공간정보체계기술의 발달로 더욱 정밀한 3차원 지형의 재현이 가능하게 되었다. 그런데 실제 현장에서 이루어지고 있는 면적 및 체적산출방법에 있어서는 재래적인 측량방법인 평판측량으로 지형을 만들어낸 후 구적기나 기타 다른 방법을 통해서 2차원 면적을 산출한다. 여기에 일정량의 경사보정계수를 곱하여 3차원 면적을 산출하는 방법을 사용하고 있다. 본 연구에서는 재래적인 측량방법 및 면적산출방법에 대한 비효율성 및 비정밀성을 제시하고 광파거리측량기와 GPS를 이용하여 불규칙삼각형방식과 격자형방식으로 측량을 실시하였다. 두 가지 측량데이터를 가지고 각각의 방법에 따라 3차원 지형모델을 구축한 후 2차원 및 3차원 면적을 산출하였으며 재래적인 측량방법을 이용한 면적산출량을 기준으로 불규칙삼각형방식과 격자형방식으로 산출한 면적산출량을 비교 분석함으로써 정밀하고 효율성이 높은 3차원 면적산출기법을 제시하였다.

• 전자통신동향분석
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• 제37권3호
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• pp.64-73
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• 2022

As the COVID-19 pandemic has decreased face-to-face communication in everyday life, our interest in cultural communication via virtual world has grown significantly. In particular, the demand for applications that use three-dimensional (3D) data generation technology such as virtual reality, augmented reality, virtual performances, and realistic content is rapidly increasing in the entertainment and gaming industries. Additionally, improved computing capacity has increased the demand for high-resolution data. This study investigates the trends in 3D scanning and photogrammetry technologies that can support high-quality 3D data generation and introduces the high-resolution 3D data generation technology developed and reported in ETRI.

• 대한치과교정학회지
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• 제45권3호
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• pp.105-112
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• 2015

Objective: A recently developed facial scanning method uses three-dimensional (3D) surface imaging with a light-emitting diode. Such scanning enables surface data to be captured in high-resolution color and at relatively fast speeds. The purpose of this study was to evaluate the accuracy and precision of 3D images obtained using the Morpheus 3D$^{(R)}$ scanner (Morpheus Co., Seoul, Korea). Methods: The sample comprised 30 subjects aged 24.34 years (mean $29.0{\pm}2.5$ years). To test the correlation between direct and 3D image measurements, 21 landmarks were labeled on the face of each subject. Sixteen direct measurements were obtained twice using digital calipers; the same measurements were then made on two sets of 3D facial images. The mean values of measurements obtained from both methods were compared. To investigate the precision, a comparison was made between two sets of measurements taken with each method. Results: When comparing the variables from both methods, five of the 16 possible anthropometric variables were found to be significantly different. However, in 12 of the 16 cases, the mean difference was under 1 mm. The average value of the differences for all variables was 0.75 mm. Precision was high in both methods, with error magnitudes under 0.5 mm. Conclusions: 3D scanning images have high levels of precision and fairly good congruence with traditional anthropometry methods, with mean differences of less than 1 mm. 3D surface imaging using the Morpheus 3D$^{(R)}$ scanner is therefore a clinically acceptable method of recording facial integumental data.