• KIPS Transactions on Computer and Communication Systems
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• v.8 no.9
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• pp.217-224
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• 2019

Recently, sensor networks are built and used on many kinds of fields such as home, traffic, medical treatment and power grid. Sensing data manipulation on these fields could be a serious threat on property and safety. Thus, a proper way to block sensing data manipulation is necessary. In this paper, we propose IoT(Internet of Things) sensing data validation mechanism based on data obfuscation and variance analysis to remove manipulated sensing data effectively. IoT sensor device modulates sensing data with obfuscation function and sends it to a user. The user demodulates received data to use it. Fake data which are not modulated with proper obfuscation function show different variance aspect with valid data. Our proposed mechanism thus can detect fake data by analyzing data variance. Finally, we measured data validation time for performance analysis. As a result, block rate for false data was improved by up to 1.45 times compared with the existing technique and false alarm rate was 0.1~2.0%. In addition, the validation time on the low-power, low-performance IoT sensor device was measured. Compared to the RSA encryption method, which increased to 2.5969 seconds according to the increase of the data amount, the proposed method showed high validation efficiency as 0.0003 seconds.

• Bulletin of the Korean Chemical Society
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• v.30 no.10
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• pp.2287-2293
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• 2009

Gas Chromatography-Mass Spectrometry (GC-MS) fingerprint analysis, Principle Components Analysis (PCA), and Hierarchical Cluster Analysis (HCA) were introduced for quality assessment of Curcuma longa L. (C. longa). The GC-MS fingerprint method was developed and validated by analyzing 33 batches of samples of C. longa from different geographic locations. 18 chromatographic peaks were selected as characteristic peaks and their relative peak areas (RPA) were calculated for quantitative expression. Two principal components (PCs) were extracted by PCA. C. longa collected from Guizhou and Fujian were separated from other samples by PC1, capturing 71.83% of variance. While, PC2 contributed for their further separation, capturing 11.13% of variance. HCA confirmed the result of PCA analysis. Therefore, GC-MS fingerprint study with chemometric techniques provides a very flexible and reliable method for quality assessment of C. longa.

• Journal of Korean Society of Transportation
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• v.33 no.4
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• pp.368-378
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• 2015

This study aims to analyse the differences of job satisfaction in road freight transportation industry workers by different types of employment. The researchers utilized reliability test and factor analysis to estimate the validity and feasibility of the questionnaire. Multivariate analysis of variance (MANOVA) was also applied to assess the differences of job satisfaction level by different employment types. The results of reliability test and factor analysis clearly show that questionnaire samples are reliable and feasible. The multivariate analysis of variance result shows statistical insignificance in the level of job satisfaction between part-time workers and special type ones. On the other hand, there was a significant difference between full-time workers and those in other types of employment. The significant variables such as income, welfare, and working hour, etc were discovered.

• Journal of Family Resource Management and Policy Review
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• v.13 no.4
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• pp.115-139
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• 2009

This study focused on the development of a scale measuring the effect of consumer education. The purposes of this study were to develop a tool which could measure consumer knowledge, consumer attitudes and consumer behavior. Data were collected from 266 college students. Analysis was done using frequency, cross tabulation analysis, reliability test, principle components factor analysis, confirmatory factor analysis (Amos 5.0), and multiple regression analysis. The results from this study were as follows: 1) Nine consumer knowledge factors (23-items) were identified: consciousness of consumer education and evaluation, consumer rights and allowance management, methods of consumer education and consumer institutions, green energy and environmental consumption, essence and content of consumer education, consumer rights and consumer duty, critical consideration and consumer's damage salvation, buying minds and decision-making, independent consumers. Total variance was 58.4%. Cronbach's alpha for the nine factors ranged from .68-.79. 2) Five consumer attitude factors (26-items) were identified: green environmental consumption, consumer's role and rights, resources saving and consumer's damage salvation, consciousness of consumers, and right consumption. Total variance was 59.2%. Cronbach's alpha for the five factors ranged from .89-.94. 3) Seven consumer behavior factors (27-items) were identified: social role and rights of consumer and consumer movement, right buying and segregated garbage collection, green environmental consumption and resources saving, altruism and decision-making, allowance management and impulse buying, consumer's damage salvation, and consciousness of consumer. The total variance was 59.1%. Cronbach's alpha for the seven factors ranged from .77-.88. Finally, a scale measuring the effect of consumer education consisting of 76 items (consumer knowledge: 23 items (9 factors), consumer attitude: 26 items (5 factors), consumer behavior: 27 items (7 factors)) was constructed.

• The Korean Journal of Applied Statistics
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• v.1 no.1
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• pp.57-67
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• 1987

In time series analysis, we usually require the assumption that time series are stationary. But we may often encounter time series whose parameter values subject to change. Inthis paper w propose a method which can detect the variance change point in anAR(1) model which is subjct to changesat non-predictable time points. Proposed method is compared with other methods using the simulated and real data.

• Journal of Korean Public Health Nursing
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• v.14 no.1
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• pp.41-60
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• 2000

This study was designed and undertaken to identify the related factors of family caregivers' depression & quality of life with stroke elderly patient. The data was collected from August 16th to September 5th. 1999. The subjects in this study were 70 caregivers and 70 patients with stroke who were hospitalized in 2 oriental medicine hospitals and 3 hospitals located in Junla-buk do. The data was analized using percentage. means. t-test. ANOVA and pearson's correlation coefficients, step-wise multiple regression done with the SAS program. The results of this study are as follows; 1. The score for family caregivers' depression was 45.2 when total score was 80. The family caregivers who got more than 50 scores belongs to highly depression group amount to $29\%$. 2. The score for family caregivers' quality of life was 37.04 when total score was 56. 3. In the significant relationship between family caregivers' depression and general characteristics of the family caregivers ; age. sex, income. In the significant relationship between family caregivers' quality of life and general characteristics of family caregivers: age, education, income. In the significant relationship between family caregivers' depression and quality of life and general characteristics of stroke elderly patient ; sex. 4. The depression degree showed significant differences in the variables of family caregiver's physical health(r=-0.307, p=0.011), stress(r=0.463. p=0.011). social support (r=-0.241. p=0.046) and elderly stroke patient's ADL(r=-0.313, p=0.009). The quality of life degree showed significant differences in the variables of family caregivers' depression(r=-0.564, p=0.001), stress(r=-0.322, p=0.008), social support (r=0.353. p=0.003). 5. The most important variable affecting family caregiver's depression was caregivers' physical symptom which accounted for $32.0\%$ of the total variance in which multiple regression analysis. Total variance affecting the family caregivers' depression was $49\%$. The most important variable affecting family caregivers' quality of life was caregivers' depression which accounted for $48\%$ of the total variance in which multiple regression analysis. Total variance affecting the family caregivers' quality of life was $61\%$.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.9
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• pp.1407-1414
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• 2018

Objective: The aim of this study was to estimate (co) variance components and genetic parameters for categorical carcass traits using Bayesian inference via mixed linear and threshold animal models in Anglonubian goats. Methods: Data were obtained from Anglonubian goats reared in the Brazilian Mid-North region. The traits in study were body condition score, marbling in the rib eye, ribeye area, fat thickness of the sternum, hip height, leg perimeter, and body weight. The numerator relationship matrix contained information from 793 animals. The single- and two-trait analyses were performed to estimate (co) variance components and genetic parameters via linear and threshold animal models. For estimation of genetic parameters, chains with 2 and 4 million cycles were tested. An 1,000,000-cycle initial burn-in was considered with values taken every 250 cycles, in a total of 4,000 samples. Convergence was monitored by Geweke criteria and Monte Carlo error chain. Results: Threshold model best fits categorical data since it is more efficient to detect genetic variability. In two-trait analysis the contribution of the increase in information and the correlations between traits contributed to increase the estimated values for (co) variance components and heritability, in comparison to single-trait analysis. Heritability estimates for the study traits were from low to moderate magnitude. Conclusion: Direct selection of the continuous distribution of traits such as thickness sternal fat and hip height allows obtaining the indirect selection for marbling of ribeye.

• Animal Bioscience
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• v.34 no.4
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• pp.471-481
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• 2021

Objective: A comprehensive study was conducted to study the effects of partition of variance on accuracy of genetic parameters and genetic trends of economic traits in Vanaraja male line/project directorate-1 (PD-1) chicken. Methods: Variance component analysis utilizing restricted maximum likelihood animal model was carried out with five generations data to delineate the population status, direct additive, maternal genetic, permanent environmental effects, besides genetic trends and performance of economic traits in PD-1 chickens. Genetic trend was estimated by regression of the estimated average breeding values (BV) on generations. Results: The body weight (BW) and shank length (SL) varied significantly (p≤0.01) among the generations, hatches and sexes. The least squares mean of SL at six weeks, the primary trait was 77.44±0.05 mm. All the production traits, viz., BWs, age at sexual maturity, egg production (EP) and egg weight were significantly influenced by generation. Model four with additive, maternal permanent environmental and residual effects was the best model for juvenile growth traits, except for zero-day BW. The heritability estimates for BW and SL at six weeks (SL6) were 0.20±0.03 and 0.17±0.03, respectively. The BV of SL6 in the population increased linearly from 0.03 to 3.62 mm due to selection. Genetic trend was significant (p≤0.05) for SL6, BW6, and production traits. The average genetic gain of EP40 for each generation was significant (p≤0.05) with an average increase of 0.38 eggs per generation. The average inbreeding coefficient was 0.02 in PD-1 line. Conclusion: The population was in ideal condition with negligible inbreeding and the selection was quite effective with significant genetic gains in each generation for primary trait of selection. The animal model minimized the over-estimation of genetic parameters and improved the accuracy of the BV, thus enabling the breeder to select the suitable breeding strategy for genetic improvement.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.63 no.1
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• pp.1-7
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• 2018

Information on the patterns of genetic diversity and population structure is essential for the rational use and efficient management of germplasms; accurate information aids in monitoring germplasms, and can also be used to predict potential genetic gains. In this study, we assessed genetic diversity, focusing on Korean rice accessions for theand their sustainable conserved diversity. Using DNA profiling with 12 simple sequence repeat (SSR) markers, we detected a total of 333 alleles among 2,016 accessions. The number of alleles ranged from 21 to 53, with an average of 27.8. Average polymorphism information content was 0.797, with the lowest being 0.667 and the highest 0.940. CA cluster analysis and the model-based population structure revealed two main groups that could be subdivided into five subgroups. Analysis of the molecular variance study based on the SSR profile data showed 5% variance among the profiles, whereas we recorded 93% variance among individuals and 2% variance within individuals. Specifically, the utilized diversity for of the breeding program is restricted in that cultivars were located in limited clades. These results revealed that preserving the diversity of Korean landraces could be useful sources for breeding new rice cultivars, and cwould be the basis for the sustainable conservation and utilization of a Korean rice germplasm.

• Survey Research
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• v.1 no.1
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• pp.109-123
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• 2000

In order to make statistically valid inferences for survey data based on complex probability sample designs, survey researchers must incorporate the sample design in the data analysis If this in not the case the variance estimates of survey statistics derived under the usual simple random sampling assumptions from an infinite population generally underestimate the true variance, which results in high Type l error level. In this article we introduce new software packages dedicated to analyze complex survey data In particular, we summarize analysis capabilities on SUDAAN Version 7.5 and SAS Version 8.