• Journal of Communications and Networks
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• v.16 no.3
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• pp.264-269
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• 2014

We consider transmission over body area networks. Due to the difficulty in assessing an accurate statistical model valid for multiple scenarios, we advocate a system design technique favoring robustness. Our approach, which is based on results in [12] and generalizes them, examines the variation of a performance metric when the nominal statistical distribution of fading is replaced by the worst distribution within a given Kullback-Leibler divergence from it. The sensitivity of the performance metric to the divergence from the nominal distribution can be used as an indication of the design robustness. This concept is applied by evaluating the error probability of binary uncoded modulation and the outage probability-the first parameter is useful to assess system performance with no error-control coding, while the second reflects the performance when a near-optimal code is used. The usefulness of channel coding can be assessed by comparing its robustness with that of uncoded transmission.

• Communications for Statistical Applications and Methods
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• v.25 no.3
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• pp.307-319
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• 2018

High-throughput technologies enable the simultaneous evaluation of thousands of genes that could discriminate different subclasses of complex diseases. Ranking genes according to differential expression is an important screening step for follow-up analysis. Many statistical measures have been proposed for this purpose. A good ranked list should provide a stable rank (at least for top-ranked gene), and the top ranked genes should have a high power in differentiating different disease status. However, there is a lack of emphasis in the literature on ranking genes based on these two criteria simultaneously. To achieve the above two criteria simultaneously, we proposed to apply a previously reported metric, the modified area under the receiver operating characteristic cure, to gene ranking. The proposed ranking method is found to be promising in leading to a stable ranking list and good prediction performances of top ranked genes. The findings are illustrated through studies on both synthesized data and real microarray gene expression data. The proposed method is recommended for ranking genes or other biomarkers for high-dimensional omics studies.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.11
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• pp.1099-1108
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• 2017

Data points obtained by conducting repetitive experiments under identical environmental conditions are, theoretically, required to correspond. However, experimental data often display variations due to generated errors or noise resulting from various factors and inherent uncertainties. In this study, an algorithm aiming to determine valid bounds of input variables, representing uncertainties, was developed using probabilistic and statistical methods. Furthermore, a reliability assessment was performed to verify and validate applications of this algorithm using bolt-fastening friction coefficient data in a sample application.

• Journal of Korea Multimedia Society
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• v.21 no.5
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• pp.617-625
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• 2018

Phishing website has become a crucial concern in cyber security applications. It is performed by fraudulently deceiving users with the aim of obtaining their sensitive information such as bank account information, credit card, username, and password. The threat has led to huge losses to online retailers, e-business platform, financial institutions, and to name but a few. One way to build anti-phishing detection mechanism is to construct classification algorithm based on machine learning techniques. The objective of this paper is to compare different classifier ensemble approaches, i.e. random forest, rotation forest, gradient boosted machine, and extreme gradient boosting against single classifiers, i.e. decision tree, classification and regression tree, and credal decision tree in the case of website phishing. Area under ROC curve (AUC) is employed as a performance metric, whilst statistical tests are used as baseline indicator of significance evaluation among classifiers. The paper contributes the existing literature on making a benchmark of classifier ensembles for web phishing detection.

• Journal of Multimedia Information System
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• v.5 no.2
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• pp.99-104
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• 2018

Phishing website has become a crucial concern in cyber security applications. It is performed by fraudulently deceiving users with the aim of obtaining their sensitive information such as bank account information, credit card, username, and password. The threat has led to huge losses to online retailers, e-business platform, financial institutions, and to name but a few. One way to build anti-phishing detection mechanism is to construct classification algorithm based on machine learning techniques. The objective of this paper is to compare different classifier ensemble approaches, i.e. random forest, rotation forest, gradient boosted machine, and extreme gradient boosting against single classifiers, i.e. decision tree, classification and regression tree, and credal decision tree in the case of website phishing. Area under ROC curve (AUC) is employed as a performance metric, whilst statistical tests are used as baseline indicator of significance evaluation among classifiers. The paper contributes the existing literature on making a benchmark of classifier ensembles for web phishing detection.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1203-1212
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• 2017

Intrusion detection systems (IDSs) are crucial in this overwhelming increase of attacks on the computing infrastructure. It intelligently detects malicious and predicts future attack patterns based on the classification analysis using machine learning and data mining techniques. This paper is devoted to thoroughly evaluate classifier ensembles for IDSs in IEEE 802.11 wireless network. Two ensemble techniques, i.e. voting and stacking are employed to combine the three base classifiers, i.e. decision tree (DT), random forest (RF), and support vector machine (SVM). We use area under ROC curve (AUC) value as a performance metric. Finally, we conduct two statistical significance tests to evaluate the performance differences among classifiers.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.179-187
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• 2022

The project performances can be measured in terms of meeting the project schedule, budget, and conformance to functional and technical specifications. Numerous studies have been conducted to examine the causes and effects of change orders for both vertical and horizontal construction, respectively. However, these studies mainly focus on a single project type, so this paper examines the impact of change order for cost growth and schedule overruns using four different building types to close the gap in the change order research area. A total of 211 building projects are collected from four building types: healthcare, residential, office, and education. Statistical analyses using ANOVA tests and linear regression models are used to examine the created metric $CO/day on the cost and schedule impacts. The results found that mean $CO/day values were not statistically different among building types, and that the sum of change orders is a statistically significant predictor of $CO/day. The results will help project stakeholders mitigate the negative change orders effects can be a challenge for project managers and researchers alike.

• Journal of Environmental Impact Assessment
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• v.26 no.2
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• pp.160-170
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• 2017

The purpose of this study is to perform clustering of the habitat types and to identify the characteristics of species in the habitat types using mammal data (70,562) of the 3rd National Ecosystem Survey conducted from 2006 to 2012. The 15 habitat types recorded in the field-paper of the 3rd National ecosystem survey were reclassified, which was followed by the statistical analysis of mammal habitat types. In the habitat types cluster analysis, non-hierarchical cluster analysis (k-means cluster analysis), hierarchical cluster analysis, and non-metric multidimensional scaling method were applied to 14 habitat types recorded more than 30 times. A total of 7 Orders, 16 Families, and 39 Species of mammals were identified in the 3rd National Ecosystem Survey collected nationwide. When 11 clusters were classified by habitat types, the simple structure index was the highest (ssi = 0.07). As a result of the similarities and hierarchies between habitat types suggested by the hierarchical clustering analysis, the residential areas were the most different habitat types for mammals; the next following type was a cluster together with rivers and coasts. The results of the non-metric multidimensional scaling analysis demonstrated that both Mus musculus and Rattus norvegicus restrictively appeared in a residential area, which is the most discriminating habitat type. Lutra lutra restrictively appeared in coastal and river areas. In summary, according to our results, the mammalian habitat can be divided into the following four types: (1) the forest type (using forest as the main habitat and migration route); (2) the river type (using water as the main habitat); (3) the residence habitat (living near residential area); and (4) the lowland type (consuming grain or seeds as the main feeding resource).

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.6
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• pp.84-95
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• 2013

Recently, to prevent damage to the landscape, outstanding landscape areas have been designated in advance. In particular, as a fundamental way to evaluate landscape elements, landscape diversity is an important criterion to assess an area with a high conservative value. Therefore, the purpose of this study is to develop a quantitative evaluation model of landscape diversity based on landscape elements and to verify the model by applying it to the study sites. The assessment indicators derived from the literature analysis are topography, vegetation, land-use pattern, and unusual landscape. Topography diversity is subdivided into land undulation and land-form. Vegetation diversity is subdivided into plant community diversity and stratification diversity. To quantitatively analyse each indicator's diversity, SHDI was selected as the central metric. All of the quantitative measures were implemented by using the statistical tool, FRAGSTATS. Through the process of each indicator's standardization and summary, the final landscape diversity index was calculated. The results of the study are significant as it was the initial study of landscape diversity evaluation to seek applicability. However, the results of the Landscape Diversity Evaluation Model in this study based on 4 indicators synthetically demonstrate that more than one or two outstanding indicators can be underrated. Therefore, each 4 assessment indicator results should be considered individually. Furthermore, using the maximum value for each indicator's standardization reflects that it is necessary to analyse various examples to obtain higher objectivity later.

• Korean Journal of Ecology and Environment
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• v.45 no.2
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• pp.218-231
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• 2012

The objectives of this study were to evaluate the physico-chemical water quality, trophic and tolerance guilds in the control ($C_o$) and impacted streams of the abandoned mine, along with the ecological health, using a multimetric health model and physical habitat conditions of Qualitative Habitat Evaluation Index (QHEI), during the period of three years, 2005~2007. Also, eco-toxicity ($EE_t$) enclosure tests were conducted to examine the toxic effects on the outflows from the mine wastewater, using the sentinel species of Rhynchocypris oxycephalus, and we compared the biological responses of the control ($C_o$) and treatment (T) to the effluents through a Necropybased Health Assessment Index ($N_b$-HAI). Tissue impact analysis of the spleen, kidney, gill, liver, eyes, and fins were conducted in the controlled enclosure experiments (10 individuals). According to the comparisons of the control ($C_o$) vs. the treatment (T) in physicochemical water quality, outflows from the abandoned mine resulted in low pH of 3.2, strong acid wastewater, high ionic concentrations, based on an electrical conductivity, and high total dissolved solid (TDS). Physical habitat assessments, based on Qualitative Habitat Evaluation Index (QHEI) did not show any statistical differences (p>0.05) in the sampling sites, whereas, the $M_m$-EH model values in a multimetric ecological health ($M_m$-EH) model of the Index of Biological Integrity (IBI), using fish assemblages, were 16~20 (fair condition) in the control and all zero (0, poor condition) in the impacted sites of mine wastewater. In addition, in enclosure eco-toxicity ($EE_t$) tests, the model values of $N_b$-HAI ranged between 0 and 3 in the controls during the three years, indicating an excellent~good condition (Ex~G), and were >100 (range: 100~137) in the impacted sites, which indicates a poor condition (P). Under the circumstances, organ tissues, such as the liver, kidney, and gills were largely impaired, so that efficient water quality managements are required in the outflow area of the abandoned mine watershed.