Earticle

기상이변과 도시화로 인한 투수면적 감소는 도시지역 침수 피해를 증가시킨다. 기후에너지환경부가 제공하는 빈도별 도시침수지도는 극한 강우에서 우수배제시설의 용량 초과, 고장을 가정해 침수범위와 침수심을 제시하지만, 영향요인과의 정량적 연계는 제한적이다. 본 연구는 경상북도 안동시를 대상으로 30·50년 빈도 침수지도를 200×200m 격자에 정렬하고, 관측 기상자료는 전처리 및 Ordinary Kriging 공간보간을 적용하였고, 지형·토양 및 세분류 토지피복 기반 불투수율을 동일 격자에 통합하였다. 연속형 인자는 Welch's t-test와 BH-FDR 보정, Cohen's d로, 범주형 인자는 Chi-squared test 과 Monte Carlo p-value, Cramér's V로 침수·미침수 집단의 차이를 평가하였다. 분석 결과 상대습도와 불투수율은 침수 격자에서 증가 경향을 보였고, 경사·토성 분포는 유의하게 달라 저경사·세립질 범주가 과대표현되었다. 본 연구는 빈도별 침수지도 기반 영향요인 정량화를 위한 격자 기반 통계 프레임워크를 제시하고자 한다.

Reductions in pervious surfaces driven by climate extremes and rapid urbanization have increased inundation damage in urban areas. Flood-frequency urban urban inundation map provided by the Ministry of Environment delineate inundation extent and depth under extreme rainfall scenarios assuming capacity exceedance and failures of stormwater drainage facilities; however, quantitative linkages with key driving factors remain limited. This study focuses on Andong City (Gyeongsangbuk-do), where 30- and 50-year return-period urban inudation map were aligned to a 200 × 200 m grid. Observed meteorological data were preprocessed and spatially interpolated using Ordinary Kriging, and terrain/soil attributes together with imperviousness derived from detailed land-cover data were integrated on the same grid. Continuous predictors were evaluated using Welch's t-test with Benjamini-Hochberg FDR correction and summarized by Cohen's d, while categorical predictors were assessed using chi-squared tests with Monte Carlo p-values and Cramér's V. Results indicate increasing tendencies of relative humidity and imperviousness in inundated grids, and significant shifts in slope and soil-texture distributions, with low-slope and fine-textured classes over-represented in inundated areas. The proposed grid-based statistical framework supports quantitative identification of influential factors associated with flood-frequency urban inudation maps.

The random numbers are needed in variety fields of applications in particular cryptography. They can be constructed by using several methods such as cellular Automata (CA). This later cannot produce a long random numbers sequence, supplementary the quality of random numbers depends especially on applied CA rules. For this reason, the modified binary particle swarm optimization (MBPSO) is used to discover a new rules set for CA. Rules of radius r=1 and periodic boundary conditions are considered for a non-uniform one-dimensional CA. Our contribution consists to combine this CA with MBPSO for satisfying the pseudo random number generator (PRNG) characteristics, called "PSOCA". Thus, different tests were applied to our PSOCA algorithm to prove its generated sequences quality, such as Diehard, Nist and other statistical tests, which have been successfully passed. Moreover, the comparison with other systems ensure the highlight randomness quality of our proposal system.

Investigations of biosimilarity between reference drugs and test drugs required statistical tests; in addition, statistical tests to evaluate biosimilarity have been recently proposed. Ordinal outcome data has been observed in research; however, appropriate statistical tests to deal with ordinal endpoints for biosimilar have not yet been proposed. This paper extends existing design for ordinal endpoints. Using measure of nominal-ordinal association and relative distances between drugs are defined so that testing procedures are developed. Through simulation studies, we investigate type I error rate and power to show the performance of our suggested method. Furthermore, a comparison between the statistical tests and other designs is proviede to show significance of ordinal endpoints.

This study attempts to test the lead-lag relationship between the stock price and the business indicator in the multivariate context. It additionally investigates the short and long-run dynamic relationships among the four market variables. The hypothesis that the stock price leads the business indicator is found to be rejected for the whole study period. When structural change is considered, the statistical result appears to reflect the reality. The causal relationships among the variables in the former period are simpler than those in the latter period, and the stock price significantly appears to lead the business indicator. On the other hand, the relationship between the stock price and the business indicator in the latter period appears to prove the recent hypothesis of their coincidence.

Microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. In time-course experiments in which gene expression is monitored over time we are interested in testing gene expression profiles for different experimental groups. We propose a statistical test based on the ANOVA model to identify genes that have different gene expression profiles among experimental groups in time-course experiments. Using this test, we can detect genes that have different gene expression profiles among experimental groups. The proposed model is illustrated using cDNA microarrays of 3,840 genes obtained in an experiment to search for changes in gene expression profiles during neuronal differentiation of cortical stem cells.

The main reason for deinterlacing is frame-rate conversion. The other reason for deinterlacing is of course improve clarity and reduce flicker. Using a deinterlacer can help clarity and stability of the image. Many deinterlacing algorithms are available in image processing literatures such as ELA and E-ELA. This paper propose a new statistical deinterlacing algorithm based on statistical tests such as the Bartlett test, the Levene test and the Kruskal-Wallis test. The results obtained from the proposed algorithms are found to be comparable to those from many well-known deinterlacers. However, the results in the proposed deinterlacers are found to be more efficient than other deinterlacers.

In many image processing applications, a random noise makes some trouble since most video enhancement functions produce visual artifacts if a priori of the noise is incorrect. The basic difficulty is that the noise and the signal are difficult to be distinguished. Typical unsharp masking (UM) enhances the visual appearances of images, but it also amplifies the noise components of the image. Hence, the applications of a UM are limited when noises are presented. This paper proposed statistical algorithms based on parametric and nonparametric tests to adaptively enhance the image feature and the noise combining while applying UM. With the proposed algorithm, it is made possible to enhance the local contrast of an image without amplifying the noise.

In this paper, tests of statistical hypotheses for the expectation and variance of Gaussian fuzzy population are discussed.

We describe a method for detecting slope instability in flume tests using pore pressure and water content data in conjunction with a statistical control chart analysis. Specifically, we conducted univariate statistical analysis on x-MR control chart data (pore pressure and water content) collected at several points along the flume slope, which we separated into three parts: upper, middle, and lower. To assess our results in the context of landslide forecasting and warning systems, we applied control limit lines at $1{\sigma}$, $2{\sigma}$, and $3{\sigma}$ levels of uncertainty. In doing so, we observed that dispersion time varies depending on the control limit line used. Moreover, the detection of instabilities is highly dependent on the position and type of sensor. Our findings indicate that different characteristics of the data on various factors predict slope failure differently and these characteristics can be identified by univariate statistical analysis. Therefore, we suggest that a univariate statistical approach is an effective method for the early detection of slope instability.

In the era of the outcome-based education, multiple-choice test has been widely employed owing to its efficiency that enables educators to evaluate a quantity of students with much objectiveness. However, the prevalent test has not been reconsidered enough to overcome its apparent shortcomings: examiners' effort for developing plausible and faultless distracters defending from every falsification, and students' random guessing on key choices. For alleviating such defects, tiered test as an experimental format of multiple-choice tests has been suggested in science education. Since there has not accumulated much study on the implementation of tiered tests, our research aim is set to construct a framework suggesting statistical indexes for rationally discerning tiered units that develop an effective tiered test. Graded both by our tiered-scoring and by the conventional partial-scoring, the preliminary tiered test in secondary physics attests the improvement in its discrimination and difficulty distribution. The findings reveal that the two indexes discern effective tiered items: discrimination increase (Ct-p) and difficulty decrease (Dp-t). Based on the index information, 4 heterogeneous tier types are recommended in the content of secondary physics: directional manipulation, repeated calculation, diverse explanation, and plural variables.

Purpose: The purpose of this study is to develop the statistical test for process capability index $C_p$ based on mixture normal process. Methods: This study uses Bootstrap method to calculate the approximate P-value for various simulation conditions under mixture normal process. Results: This study indicates that our proposed method is effective way to test for process capability index $C_p$ based on mixture normal process. Conclusion: This study finds out that statistical test for process capability index $C_p$ based on mixture normal process is useful for real application.

본 연구는 실제 구조진단 사례에 기초하여 재료와 형식 및 공용기간에 따라 교량의 응답, 충격계수, 고유진동수 및 각 특성의 해석값/계측값 비 등에 관한 기술통계를 분석하고 주재료에 따른 T-검정과 구조형식 및 공용기간에 따른 분산분석을 통해서 요인 부집단 수준 간동질성 검정 및 다중비교분석을 수행하였다. 본 연구 결과는 응답 분포의 중심값, 산포도, 대칭성 등 통계적 특성 및 비교분석 집단 간 동질성 식별을 위한 참조값을 제공하며, 이것은 내하력 평가 등 구조 진단과 설계에서 엔지니어들이 취득한 계산 또는 계측값의 타당성을 비교검토하고 데이터베이스를 활용하는 등의 공학적 판단을 하는데 실제적으로 유용한 정보를 제공할 것으로 기대된다.

This study tests homogeneity and performs multiple comparison analysis among treatment levels of each factor group through t-test by materials and analysis of variance by structural type and service period. For that descriptive statistical analysis is performed for static and dynamic response characteristics and their ratios of calculated versus measured values based on a good many safety assessment reports for bridges. Homogeneity and post hoc test based on descriptive statistical analysis provide the measures for homogeneity identification among comparison groups in addition to the statistical reference values such as central tendency, variation and shape. This study is expected to be valuable for structural integrity assessment and design by comparing the measured and calculated values with the reference values for the homogeneous group identified, which can help the engineers review the adequacy of the values and put the group database to practical use.

Objectives: This study was performed to determine the correlation between Instrument on Pattern Identification for Depression and Psychological tests by Pearson Correlation Coefficient and Regression analysis.Methods: Two assessors carried out the evaluation using the instrument on pattern identification for depression. They also performed the following psychological tests: Beck Depression Inventory (BDI), State-Trait Anxiety Inventory (STAI), State-Trait Anger Expression Inventory (STAXI), the Temperament and Character Inventory (TCI), Insomnia Severity Index (ISI_Total), Self-disclosure Inventory, subjective well-being Inventory, Health perception Inventory, and Personality Assessment Inventory (PAI). A total of 167 participants who got HAM-D score over 12 were targeted for the evaluation. Our research team carried out Pearson correlation coefficient analyses and regression analysis between pattern identification for depression and Psychological tests. We listed the results by descending order and interpreted the results.Results: Pearson correlation analysis revealed the following results: 1) Stagnation of Liver Gi was associated with BDI (0.60) and STAI (0.55); 2) Dual Deficiency of the Heart and Spleen was associated with BDI (0.60), ISI_Total (0.52), and STAI (0.42); 3) Relieving stagnation of Phlegm-Gi was associated with BDI (0.65), STAI (0.54), and Subjective well-being inventory (?0.52); 4) Gi-deficiency Mingled with sputum was associated with BDI (0.50), ISI_Total (0.40), and STAI (0.395); 5) Stagnant Gi transforming into fire was associated with BDI (0.56), STAI_TR (0.51), and Health perception Inventory (?0.458); 6) Yin-Deficiency with Effulgent Fire was associated with BDI (0.55), ISI_total (0.54), and STAI (0.41).Conclusions: Through correlation analysis between Instrument on Pattern Identification for Depression and Psychological tests, we could suggest a System for Oriental Medical Diagnosis for Depression.

본 논문에서는 스트림 암호 알고리즘과 블록 암호 알고리즘과 같은 비밀키 암호 시스템의 통계적 특성을 측정하기 위하여 사용된 여러 가지 randomness 테스트 방법들을 구현하여 그 성능을 randomness test의 power측면에서 서로 비교하였다. 여기서, power란 randomness test가 nonrandom한 비트 스트림을 얼마나 정확하게 검정할 수 있는 가를 나타내는 적도이다. 그리고, 스트림 암호 알고리즘과 블록 암호 알고리즘의 통계적 특성을 측정하기 위해 가장 효율적이라고 생각되는 테스트 방법들을 찾아 이 방법들을 사용할 것을 제안한다. 끝으로 제안된 방법들을 이용하여, DES, AES후보 알고리즘, SEED의 통계적 특성을 분석하였다.

상장은 기업의 자금 유치와 신뢰도 확보 수단으로 기술력과 성장가능성을 인정받는 지표가 되기도 한다. 하지만 높은 재무요건은 스타트업에게 진입 장벽이 되며, 이를 보완하기 위해 기술성장기업에 대한 특례나 기업인수목적회사(Special Purpose Acqusition Company, SPAC) 합병을 통한 상장이 주목받고 있다. 본 논문은 2020년부터 2024년까지 코스닥 시장에 상장한 기술성장기업 160개사를 대상으로 상장경로(기술성장기업에 대한 특례 상장 vs SPAC 합병)와 상장유형(신규상장 vs 이전상장)에 따라 상장 전 기업가치(Pre-money Valuation) 대비 조달자금 비율의 차이가 통계적으로 유의미한지 분석하였다. 분석 결과, SPAC 합병 기업의 기업가치 대비 실제 조달자금 비율 평균값은 기술성장기업에 대한 특례 상장 기업 평균보다 0.0486 낮은 수준을 보였으며, 순열검증 결과 p-value가 0.0143로, 이러한 값의 차이는 우연히 나올 수 있는 수준이 아님을 확인하였다. 또한 이전상장을 통한 기업의 기업가치 대비 실제 조달자금 비율 평균값은 신규상장 기업 평균보다 0.0308 낮은 수준을 보였으며 순열검증 결과 p-value는 0.061로 이러한 값의 차이는 충분히 우연히 나올 수 있는 수준으로 나타났다. 이는 코넥스를 통한 이전상장과 신규상장 간에는 자본조달 효율에서 본질적인 차이가 없음을 시사한다. 이러한 결과는 상장 방식 자체보다는 기업의 구조적 특성과 시장 인식차이에서 기인한 것일 가능성도 존재한다. 그럼에도 불구하고 동일한 기술성장기업 요건을 충족한 집단 내에서 상장방식에 따른 조달자금 규모 차이를 실증적으로 확인했다는 점에서 의의가 있으며, 제도적 특성을 반영한 실증자료로서 정책적 기여와 향후 기술성장기업의 상장 전략 수립 및 SPAC 제도 개선을 위한 참고자료로 활용될 수 있다.

Listing enables companies to attract capital and enhance credibility, often signaling recognized technological capability and growth potential. However, strict financial requirements create barriers for startups. Consequently, special listing exemptions for technology-growth companies and mergers with Special Purpose Acquisition Companies (SPACs) have emerged as notable alternatives. This study examines whether the ratio of capital raised to pre-money valuation differs significantly by listing pathway-special exemption listing versus SPAC merger-and by listing type-new listing versus transfer listing. The sample comprised 160 technology-growth companies listed on KOSDAQ between 2020 and 2024. Results show that the average ratio for SPAC-merger companies was 0.0486 lower than that for companies listed under the special exemption, with a permutation test p-value of 0.0143, indicating statistical significance. For transfer listings, the average ratio was 0.0308 lower than that for new listings; however, the p-value of 0.061 suggests this difference could occur by chance, implying no inherent gap in fundraising efficiency between KONEX-to-KOSDAQ transfers and new listings. These findings suggest that differences in capital raised may stem more from company structure and market perception than from the listing method itself. Nonetheless, this research is notable for empirically identifying variation in capital-raising scale within a cohort meeting the same technology-growth criteria. The results offer valuable empirical evidence reflecting institutional characteristics, informing policy considerations, guiding listing strategies for technology-growth companies, and supporting improvements to the SPAC framework.