• Communications of Mathematical Education
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• v.30 no.3
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• pp.393-418
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• 2016

Theory and fundamentals of mathematics consist mostly of proposition form. Activities by research of the proposition which leads to determine the true or false, justify the true propositions and refute with counterexample improve logical reasoning skills of students in emphases on mathematics education. Also, utilizing of counterexamples in school mathematics combines mathematical knowledge through the process of finding a counterexample, help the concept study and increase the critical thinking. These effects have been found through previous research. But many studies say that the learners have difficulty in generating counterexamples for false propositions and materials have not been developed a lot for the counterexample utilizing that can be applied in schools. So, this study analyzed the current textbook and examined the use of counterexamples and developed educational materials for counterexamples that can be applied at schools. That materials consisted of making true & false propositions and students was divided into three groups of academic achievement level. And then this study looked at the change of the students' thinking after counterexample classes. As a study result, in all three groups was showed a positive change in the cognitive domain and affective domain. Especially, in top-level group was mainly showed a positive change in the cognitive domain, in upper-middle group was mainly showed in the cognitive and the affective domain, in the sub-group was mainly found a positive change in the affective domain. Also in this study shows that the class that makes true or false propositions in education of utilizing counterexample, made students understand a given proposition, pay attention to easily overlooked condition, carefully observe symbol sign and change thinking of cognitive domain helping concept learning regardless of academic achievement levels of learners. Also, that class gave positive affect to affective domain that increase interest in the proposition and gain confidence about proposition.

• Journal of Communications and Networks
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• v.12 no.1
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• pp.74-85
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• 2010

For the purpose of compromising hosts, attackers including infected hosts initially perform a portscan using IP addresses in order to find vulnerable hosts. Considerable research related to portscan detection has been done and many algorithms have been proposed and implemented in the network intrusion detection system (NIDS). In order to distinguish portscanners from remote hosts, most portscan detection algorithms use a fixed threshold that is manually managed by the network manager. Because the threshold is a constant, even though the network environment or the characteristics of traffic can change, many false positives and false negatives are generated by NIDS. This reduces the efficiency of NIDS and imposes a high processing burden on a network management system (NMS). In this paper, in order to address this problem, we propose an automatic portscan detection system using an fast increase slow decrease (FISD) scheme, that will automatically and adaptively set the threshold based on statistical data for traffic during prior time periods. In particular, we focus on reducing false positives rather than false negatives, while the threshold is adaptively set within a range between minimum and maximum values. We also propose a new portscan detection algorithm, rate of increase in the number of failed connection request (RINF), which is much more suitable for our system and shows better performance than other existing algorithms. In terms of the implementation, we compare our scheme with other two simple threshold estimation methods for an adaptive threshold setting scheme. Also, we compare our detection algorithm with other three existing approaches for portscan detection using a real traffic trace. In summary, we show that FISD results in less false positives than other schemes and RINF can fast and accurately detect portscanners. We also show that the proposed system, including our scheme and algorithm, provides good performance in terms of the rate of false positives.

• Korean Journal of Child Studies
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• v.35 no.3
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• pp.49-69
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• 2014

The purposes of this study were (1) to investigate children's moral judgment, justification reasoning in terms of aggressive behavior, and (2) it examined the relationship to false belief understanding. Children aged between 3 to 5 years(N = 120) participated in this study. Each child was interviewed individually and responded questions designed to measure his/her moral judgment and justification reasoning and false belief understanding. The 12 pictorial tasks consisted of selfish and altruistic intentions and three different types of acts (physical, verbal, relational) as responses to aggressive behavior. The results indicated that the kind of moral judgment used was different according to the intention and the types of acts. There were significant differences in children's justification reasoning according to the age and the types of acts. There was a positive relationship between false belief understanding and moral judgment, justification reasoning. This paper also provided a detailed discussion of the results and recommendations in the context of more general cognitive developmental changes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5354-5369
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• 2019

Sensor networks are deployed in unheeded environment to monitor the situation. In view of the unheeded environment and by the nature of their communication channel sensor nodes are vulnerable to various attacks most commonly malicious packet dropping attacks namely blackhole, grayhole attack and sinkhole attack. In each of these attacks, the attackers capture the sensor nodes to inject fake details, to deceive other sensor nodes and to interrupt the network traffic by packet dropping. In all such attacks, the compromised node advertises itself with fake routing facts to draw its neighbor traffic and to plunge the data packets. False routing advertisement play vital role in deceiving genuine node in network. In this paper, behavior based routing misbehavior detection (BRMD) is designed in wireless sensor networks to detect false advertiser node in the network. Herein the sensor nodes are monitored by its neighbor. The node which attracts more neighbor traffic by fake routing advertisement and involves the malicious activities such as packet dropping, selective packet dropping and tampering data are detected by its various behaviors and isolated from the network. To estimate the effectiveness of the proposed technique, Network Simulator 2.34 is used. In addition packet delivery ratio, throughput and end-to-end delay of BRMD are compared with other existing routing protocols and as a consequence it is shown that BRMD performs better. The outcome also demonstrates that BRMD yields lesser false positive (less than 6%) and false negative (less than 4%) encountered in various attack detection.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.12 no.4
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• pp.29-39
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• 2002

In general, the intrusion detection method of anomalous behaviors has high false alarm rate which contains false-positive and false-negative. To increase the sensitivity of intrusion detection, we propose a method of aggregate detection to reduce false alarm rate by using correlation between misuse activity detection sensors and anomalous ones. For each normal behavior and anomalous one, we produce the reflection rate between the result from one sensor and another in off-line. Then, we apply this rate to the result of real-time detection to reduce false alarm rate.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.1
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• pp.237-241
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• 2012

Objective: Screening for colorectal cancer using guaiac-based fecal occult blood tests (gFOBT) is well established in Western populations, but is hampered by poor patient compliance due to the imposed dietary restrictions. Fecal immunochemical tests (FIT) do not require dietary restriction, but are more expensive than gFOBT and therefore restrict its use in developing countries in Asia. However, Asian diets being low in meat content may not require diet restriction for gFOBT to achieve equivalent results. The objective of this study was to evaluate and compare the validity and suitability of gFOBT and FIT or a combination of the two in screening for colorectal neoplasias without prior dietary restriction in an Asian population. Methods: Patients referred to the Endoscopic Unit for colonoscopy were recruited for the study. Stool samples were collected prior to bowel preparation, and tested for occult blood with both gFOBT and FIT. Dietary restriction was not imposed. To assess the validity of either tests or in combination to detect a neoplasm or cancer in the colon, their false positive rates, their sensitivity (true positive rate) and the specificity (true negative rate) were analyzed and compared. Results: One hundred and three patients were analysed. The sensitivity for picking up any neoplasia was 53% for FIT, 40% for gFOBT and 23.3% for the combination. The sensitivities for picking up only carcinoma were 77.8%, 66.7% and 55.5%, respectively. The specificity for excluding any neoplasia was 91.7% for FIT, 74% for gFOBT and 94.5% for a combination, whereas for excluding only carcinomas they were 84%, 73.4% and 93.6%. Of the 69 with normal colonoscopic findings, FOBT was positive in 4.3%, 23.2 %and 2.9% for FIT, gFOBT, or combination of tests respectively. Conclusion: FIT is the recommended method if we are to dispense with dietary restriction in our patients because of its relatively low-false positivity and better sensitivity and specificity rates.

• Journal of Yeungnam Medical Science
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• v.20 no.2
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• pp.117-128
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• 2003

Thallium-201 scintigraphy is used to discriminate the malignant bone tumor from the benign by qualitatively and quantitatively, and to predict the response of preoperative chemotherapy in osteosarcoma, by comparing the changes of thallium uptake ratio after chemotherapy to the tumor necrosis ratio. Thallium-201 scintigraphy scan should be done prior to surgical biopsy. PICKER Prism 2000 gamma camera with high resolution parallel hole collimator is usually used for scanning. The patient is injected with 2-3mCi of Tl-201 and the early phase is checked in 30 minutes and delayed phase in 3 hours. The scan images are visually evaluated by a blinded nuclear medicine physician. We could evaluate true positive, true negative, false positive and false negative by the comparison of results with those of biopsy, and calculate positive and negative predictive value(%), sensitivity(%), specificity(%) and diagnostic accuracy(%). For the quantitative analysis of thallium uptake, we drew the region of interest on the tumor side and contralateral normal side as mirror image, and calculated the uptake ratio with dividing the amount of gamma count in tumor side by normal side. We could calculate the percent changes of thallium uptake ratio in early and delayed phase, and compare them to the ratio of tumor necrosis. Thallium-201 scintigraphy proved as useful imaging study to discriminate malignant bone tumor from benign, but had exception in giant cell tumor and low grade malignant bone tumors. We can use T1-201 scan to differentiate the benign from the malignant tumor, and to evaluate the response of preoperative chemotherapy or radiotherapy, and to determine the residual tumor or local recurrence. For the better result, we need to have a more detail information about false positive cases and a more objective and quantitative reading technique.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.21 no.4
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• pp.222-226
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• 2011

This study was conducted to identify the characteristics of analytical errors shown in the Korean quality control program on bulk asbestos analyses using polarized light microscopy (PLM). 179 participating laboratories were required to analyze 4 samples respectively and asked to classify each test sample as asbestos-containing (positive) or non-asbestos-containing (negative). For positive samples, participants were also asked to identify the type and semiquantitate the contents of asbestos present. The test results showed 21 (4%) false negative errors among 562 samples, 9 (6%) false positive errors among 154 samples and 53 (9%) asbestos identification errors among 562 samples. Most of false negative and positive errors were observed in a few types of samples. Higher frequencies of asbestos identification errors were shown in samples containing two or more types of asbestos and samples containing anthophyllite, tremolite or actinolite asbestos. For semiquantitative analyses, the ratios of mean to nominal weight contents were 2.1 for chrysotile and 2.9 for amphiboles. A tendency of over-estimation was observed in semiquantitative analyses using the visual estimation technique and higher in case of analyzing samples containing amphiboles than chrysotile. Coefficients of variation (CVs) of semiquantitative analytical results were 0.44~0.83 and 0.5~1.14 for samples containing chrysotile and amphibole asbestos, respectively.

• Genomics & Informatics
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• v.2 no.3
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• pp.131-133
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• 2004

MediScore is an information retrieval system, which helps to search for the set of genes associated with a specific disease or the set of diseases associated with a specific gene. Despite recent improvement of natural language processing (NLP) and other text mining approaches to search for disease associated genes, many false positive results come out due to diversity of exceptional cases as well as ambiguities in gene names. In order to overcome the weak points of current text mining approaches, MediScore introduces statistical normalization based on binomial to normal distribution approximation which corrects inaccurate scores caused by common words not representing genes and interactive rescoring by the user to remove the false positive results. Interactive rescoring includes individual alias scoring for each gene to remove false gene synonyms, referring MEDLINE abstracts, and cross referencing between OMIM and other related information.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.67-72
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• 2013

Cloud detection and analysis from satellite images has been a topic of research in many atmospheric and environmental studies; however, it still is a challenging task for many reasons. In this paper, we propose a new method for cloud-type classification using fuzzy logic. Knowing that visible-light images of clouds contain thickness related information, while infrared images haves height-related information, we propose a two-layered fuzzy logic based on the input source to provide us with a relatively clear-cut threshold in classification. Traditional noise-removal methods that use reflection/release characteristics of infrared images often produce false positive cloud areas, such as fog thereby it negatively affecting the classification accuracy. In this study, we used the color information from source images to extract the region of interest while avoiding false positives. The structure of fuzzy inference was also changed, because we utilized three types of source images: visible-light, infrared, and near-infrared images. When a cloud appears in both the visible-light image and the infrared image, the fuzzy membership function has a different form. Therefore we designed two sets of fuzzy inference rules and related classification rules. In our experiment, the proposed method was verified to be efficient and more accurate than the previous fuzzy logic attempt that used infrared image features.