• Toxicological Research
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• v.30 no.3
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• pp.185-191
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• 2014

Statistical methods are frequently used in toxicology, yet it is not clear whether the methods employed by the studies are used consistently and conducted based on sound statistical grounds. The purpose of this paper is to describe statistical methods used in top toxicology journals. More specifically, we sampled 30 papers published in 2014 from Toxicology and Applied Pharmacology, Archives of Toxicology, and Toxicological Science and described methodologies used to provide descriptive and inferential statistics. One hundred thirteen endpoints were observed in those 30 papers, and most studies had sample size less than 10, with the median and the mode being 6 and 3 & 6, respectively. Mean (105/113, 93%) was dominantly used to measure central tendency, and standard error of the mean (64/113, 57%) and standard deviation (39/113, 34%) were used to measure dispersion, while few studies provide justifications regarding why the methods being selected. Inferential statistics were frequently conducted (93/113, 82%), with one-way ANOVA being most popular (52/93, 56%), yet few studies conducted either normality or equal variance test. These results suggest that more consistent and appropriate use of statistical method is necessary which may enhance the role of toxicology in public health.

• Journal of Microbiology and Biotechnology
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• v.29 no.10
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• pp.1629-1635
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• 2019

Azo dyes are recalcitrant pollutants, which are toxic, carcinogenic, mutagenic and teratogenic, that constitute a significant burden to the environment. The decolorization and the mineralization efficiency of Remazol Brillant Orange 3R (RBO 3R) was studied using a probiotic consortium (Lactobacillus acidophilus and Lactobacillus plantarum). Biodegradation of RBO 3R (750 ppm) was investigated under shaking condition in Mineral Salt Medium (MSM) solution at pH 11.5 and temperature $25^{\circ}C$. The bio-decolorization process was further confirmed by FTIR and UV-Vis analysis. Under optimal conditions, the bacterial consortium was able to decolorize the dye completely (>99%) within 12 h. The color removal was 99.37% at 750 ppm. Muliplex PCR technique was used to detect the Lactobacillus genes. Using phytotoxicity, cytotoxicity, mutagenicity and biototoxicity endpoints, toxicological studies of RBO 3R before and after biodegradation were examined. A toxicity assay signaled that biodegradation led to detoxification of RBO 3R dye.

• Korean Journal of Clinical Oncology
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• v.14 no.2
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• pp.108-115
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• 2018

Purpose: This study aimed to compare the results of treatment with adjuvant trastuzumab for 9 months versus 12 months in human epidermal growth factor 2 (HER2)-positive breast cancer patients. The primary endpoint was disease-free survival. Secondary endpoints included cardiac safety, tolerability, and overall survival. Methods: The study included 60 non-metastatic HER2-positive breast cancer patients. All study patients underwent surgery, received adjuvant chemotherapy, radiotherapy and hormonal therapy if indicated. Thirty patients were randomized in each group. Group I patients received adjuvant trastuzumab for 12 months, while group II patients received adjuvant trastuzumab for 9 months. Patients were assessed by clinical examination and Echocardiography during treatment. Results: After median follow-up of 12 months, 90% of the patients in group I were disease free and 83.3% of patients in group II were disease free (P=0.402). All studied population in both groups I and II were alive at the end of the 1-year follow-up period after the completion of adjuvant trastuzumab treatment thus overall survival is 100%. Conclusion: Trastuzumab is tolerable and its side effects are reversible. Nine months of adjuvant trastuzumab treatment is more cost effective than the standard 12 months.

• Communications for Statistical Applications and Methods
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• v.28 no.5
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• pp.411-424
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• 2021

Inference following two-stage adaptive designs (also known as two-stage randomization designs) with survival endpoints usually focuses on estimating and comparing survival distributions for the different treatment strategies. The aim is to identify the treatment strategy(ies) that leads to better survival of the patients. The objectives of this study were to assess the performance three commonly cited methods for estimating survival distributions in two-stage randomization designs. We review three non-parametric methods for estimating survival distributions in two-stage adaptive designs and compare their performance using simulation studies. The simulation studies show that the method based on the marginal mean model is badly affected by high censoring rates and response rate. The other two methods which are natural extensions of the Nelson-Aalen estimator and the Kaplan-Meier estimator have similar performance. These two methods yield survival estimates which have less bias and more precise than the marginal mean model even in cases of small sample sizes. The weighted versions of the Nelson-Aalen and the Kaplan-Meier estimators are less affected by high censoring rates and low response rates. The bias of the method based on the marginal mean model increases rapidly with increase in censoring rate compared to the other two methods. We apply the three methods to a leukemia clinical trial dataset and also compare the results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2568-2588
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• 2021

Shared mesh protection (SMP) protects traffic against failures occurring in a working path, as with linear protection, and allows resource sharing of protection paths with different endpoints. The SMP mechanism coordinates multiple protection paths that require shared resources when failures occur on multiple working paths. When multiple failures occur in SMP networks sharing limited resources, activation can fail because some of the resources in the protection path are already in use. In this case, a node confirming that a resource is not available has the option to wait until the resource is available or to withdraw activation of the protection path. In this study, we recognize that the protection switching time and the number of protected services can be different, depending on which option is used for SMP networks. Moreover, we propose a detailed design for the implementation of SMP by considering options and algorithms that are commonly needed for network nodes. A simulation shows the performance of an SMP system implemented with the proposed design and utilizing two options. The results demonstrate that resource utilization can be increased or protection switching time can be shortened depending on the option selected by the network administrator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4909-4926
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• 2020

Cyberattacks penetrate the server and perform various malicious acts such as stealing confidential information, destroying systems, and exposing personal information. To achieve this, attackers perform various malicious actions by infecting endpoints and accessing the internal network. However, the current countermeasures are only anti-viruses that operate in a signature or pattern manner, allowing initial unknown attacks. Endpoint Detection and Response (EDR) technology is focused on providing visibility, and strong countermeasures are lacking. If you fail to respond to the initial attack, it is difficult to respond additionally because malicious behavior like Advanced Persistent Threat (APT) attack does not occur immediately, but occurs over a long period of time. In this paper, we propose a technique that detects an unknown attack using an event log without prior knowledge, although the initial response failed with anti-virus. The proposed technology uses a combination of AutoEncoder and 1D CNN (1-Dimention Convolutional Neural Network) based on semi-supervised learning. The experiment trained a dataset collected over a month in a real-world commercial endpoint environment, and tested the data collected over the next month. As a result of the experiment, 37 unknown attacks were detected in the event log collected for one month in the actual commercial endpoint environment, and 26 of them were verified as malicious through VirusTotal (VT). In the future, it is expected that the proposed model will be applied to EDR technology to form a secure endpoint environment and reduce time and labor costs to effectively detect unknown attacks.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.2
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• pp.39-46
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• 2021

Damages by malware have recently been increasing. Conventional signature-based antivirus solutions are helplessly vulnerable to unprecedented new threats such as Zero-day attack and ransomware. Despite that, many enterprises have retained signature-based antivirus solutions as part of the multiple endpoints security strategy. They do recognize the problem. This paper proposes a solution using the blockchain and deep learning technologies as the next-generation antivirus solution. It uses the antivirus software that updates through an existing DB server to supplement the detection unit and organizes the blockchain instead of the DB for deep learning using various samples and forms to increase the detection rate of new malware and falsified malware.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.399-408
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• 2020

The construction industry is suffering from aging workers, frequent accidents, as well as low productivity. With the rapid development of information technologies in recent years, automatic construction, especially automatic cranes, is regarded as a promising solution for the above problems and attracting more and more attention. However, in practice, limited by the complexity and dynamics of construction environment, manual inspection which is time-consuming and error-prone is still the only way to recognize the search object for the operation of crane. To solve this problem, an image-processing-based automated object recognition approach is proposed in this paper, which is a fusion of Convolutional-Neutral-Network (CNN)-based and traditional object detections. The search object is firstly extracted from the background by the trained Faster R-CNN. And then through a series of image processing including Canny, Hough and Endpoints clustering analysis, the vertices of the search object can be determined to locate it in 3D space uniquely. Finally, the features (e.g., centroid coordinate, size, and color) of the search object are extracted for further recognition. The approach presented in this paper was implemented in OpenCV, and the prototype was written in Microsoft Visual C++. This proposed approach shows great potential for the automatic operation of crane. Further researches and more extensive field experiments will follow in the future.

• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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• pp.79-83
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• 2002

Since its introduction in 1995 by Schena et al. cDNA microarrays have been established as a potential tool for high-throughput analysis which allows the global monitoring of expression levels for thousands of genes simultaneously. One of the characteristics of the cDNA microarray data is that there is inherent noise even after the removal of systematic effects in the experiment. Therefore, replication is crucial to the microarray experiment. The assessment of reproducibility among replicates, however, has drawn little attention. Reproducibility may be assessed with several different endpoints along the process of data reduction of the microarray data. We define the reproducibility to be the degree with which replicate arrays duplicate each other. The aim of this note is to develop a novel measure of reproducibility among replicates in the cDNA microarray experiment based on the unprocessed data. Suppose we have p genes and n replicates in a microarray experiment. We first develop a measure of reproducibility between two replicates and generalize this concept for a measure of reproducibility of one replicate against the remaining n-1 replicates. We used the rank of the outcome variable and employed the concept of a measure of tracking in the blood pressure literature. We applied the reproducibility measure to two sets of microarray experiments in which one experiment was performed in a more homogeneous environment, resulting in validation of this novel method. The operational interpretation of this measure is clearer than Pearson's correlation coefficient which might be used as a crude measure of reproducibility of two replicates.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2413-2419
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• 2013

Background: Use of epidermal growth factor receptor inhibitors (EGFR-TKIs ) is now standard for non-small-cell lung cancer (NSCLC). However, the effects of EGFR-TKIs in maintenance therapy for advanced NSCLC patients are still unclear. The preent meta-analysis was performed to examine pooled data of randomized control trials (RCT) where EGFR-TKIs were compared against placebo in maintenance regimens for patients with advanced NCSLC to quantify potential benefits and determine safety. Methods: Several data bases were searched, including PubMed, EMBASE and CENTRAL, and we performed an internet search of conference literature. The endpoints were objective response rates (ORR), progression-free survival (PFS) and overall survival (OS). We performed a meta-analysis of the published data, using Comprehensive Meta Analysis software (Version 2.0). with a fixed effects model and an additional random effects model, when applicable. The results of the meta-analysis are expressed as hazard ratios (HRs) or risk ratios (RRs), with their corresponding 95% confidence intervals (95%CIs). Results: The final analysis included six trials, covering 3,758 patients. Compared with placebo, EGFR-TKIs maintenance therapy improved ORR and PFS for patients with advanced NSCLC, the difference being statistically significant (P<0.05), but proved unable to prolong patients' OS. The main adverse reactions were diarrhea and rashes. Conclusion: EGFR-TKIs demonstrated encouraging efficacy, safety and survival when delivered as maintenance therapy for patients with advanced NSCLC after first-line chemotherapy, especially for the patients who had adenocarcinomas, were female, non-smokers and patients with EGFR gene mutations.