• Architectural research
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• v.13 no.1
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• pp.25-32
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• 2011

The purpose of this research is to investigate the effect of specific hydration reaction on the stiffening process of cement paste. The cement compositions are manipulated to cause specific hydration reactions (secondary gypsum and syngenite formation) responsible for false set, and the relationship between specific hydration reactions and the flow and stiffening behavior of cement paste were investigated using modified ASTM C 403 penetration resistance measurement and oscillatory shear rheology. X-ray powder diffraction (XRD) was used for the phase identification associated with premature stiffening of cement paste. Differential thermal analysis (DTA) and thermogravimetric analysis (TGA) were used for verification of syngenite formation. From the results, both secondary gypsum and syngenite formation caused faster stiffening and set. The amount of syngenite produced during 1 hour hydration was approximately 1 % of total mass of the cement paste, but cement paste with syngenite formation showed significantly accelerated stiffening behavior compared to normal cement paste.

• Neonatal Medicine
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• v.17 no.2
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• pp.245-249
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• 2010

Purpose: Numerous false alarms by pulse oximetry, which is widely used in neonatal intensive care unit, can delay response to true alarms. Masimo $SET^{(R)}$ was introduced lately, to overcome false alarms by motion. We compared the clinical performance of two devices (Nellcor $N-595^{(R)}$ and Masimo $SET^{(R)}$) for the evaluation of the false alarm frequency during usual motion artifacts and stable state. Methods: A total of 20 preterm infants weighing 1,000-2,500 g were enrolled in the study. The sensors of two devices were placed on the different feet on the same infants, and both devices were programmed to emit an alarm for episode of hypoxemia (SpO2$\leq$85%). The false alarms were defined as episodes of poor correlation with ECG heart rate, poor waveforms, and the absence of obvious signs of hypoxia. We compared the frequency of false alarms between the two devices. Results: The mean chronological age was 20.8 days and the mean body weight was 1,668 g on the study day. The frequency of total false alarm was significantly fewer for Masimo $SET^{(R)}$ pulse oximetry (48 in Nellcor $N-595^{(R)}$, 27 in Masimo $SET^{(R)}$) although the false alarm during usual motion artifacts was not significantly between two devices (32 in Nellcor $N-595^{(R)}$, 19 in Masimo $SET^{(R)}$). Conclusion: The Masimo $SET^{(R)}$ pulse oximetry has fewer false alarm rates and identified more true hypoxic events than Nellcor $N-595^{(R)}$ pulse oximetry. Therefore, it is useful for adequate oxygen therapy and helps to decrease unnecessary handling by clinicians and nurses.

• 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.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.64-64
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• 2011

We present a new quasi-stellar object (QSO) selection algorithm using a Support Vector Machine, a supervised classification method, on a set of extracted time series features including period, amplitude, color, and autocorrelation value. We train a model that separates QSOs from variable stars, non-variable stars, and microlensing events using 58 known QSOs, 1629 variable stars, and 4288 non-variables in the MAssive Compact Halo Object (MACHO) database as a training set. To estimate the efficiency and the accuracy of the model, we perform a cross-validation test using the training set. The test shows that the model correctly identifies ~80% of known QSOs with a 25% false-positive rate. The majority of the false positives are Be stars. We applied the trained model to the MACHO Large Magellanic Cloud (LMC) data set, which consists of 40 million lightcurves, and found 1620 QSO candidates. During the selection, none of the 33,242 known MACHO variables were misclassified as QSO candidates. In order to estimate the true false-positive rate, we crossmatched the candidates with astronomical catalogs including the Spitzer Surveying the Agents of a Galaxy's Evolution (SAGE) LMC catalog and a few X-ray catalogs. The results further suggest that the majority of the candidates, more than 70%, are QSOs.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.1015-1019
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• 2010

An extensive research on exact string matching has been done, but there have been few researches on the matching in multi-byte character set texts such as EUC~KR. This paper shows that false matches may occur in multi-byte character set texts such as EUC-KR when using KMP algorithm, and presents a refined KMP algorithm without false matches applying a character-based prefix function. And also, Experimental results show that our algorithm is faster than string matching algorithms of widely used editors, Vim and Emacs, and the existing automata-based algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.316-321
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• 2008

Advanced computer network technology enables computers to be connected in an open network environment. Despite the growing numbers of security threats to networks, most intrusion detection identifies security attacks mainly by detecting misuse using a set of rules based on past hacking patterns. This pattern matching has a high rate of false positives and can not detect new hacking patterns, which makes it vulnerable to previously unidentified attack patterns and variations in attack and increases false negatives. Intrusion detection and analysis technologies are thus required. This paper investigates the asymmetric costs of false errors to enhance the performances the detection systems. The proposed method utilizes the network model to consider the cost ratio of false errors. By comparing false positive errors with false negative errors, this scheme achieved better performance on the view point of both security and system performance objectives. The results of our empirical experiment show that the network model provides high accuracy in detection. In addition, the simulation results show that effectiveness of anomaly traffic detection is enhanced by considering the costs of false errors.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.550-569
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• 2019

We propose approaches for improving Bloom filter in terms of false positive probability and membership query speed. To reduce the false positive probability, we propose special type of additional Bloom filters that are used to handle false positives caused by the original Bloom filter. Implementing the proposed approach for a routing table lookup, we show that our approach reduces the routing table lookup time by up to 28% compared to the original Bloom filter by handling most false positives within the fast memory. We also introduce an approach for improving the membership query speed. Taking the hash table-like approach while storing only values, the proposed approach shows much faster membership query speed than the original Bloom filter (e.g., 34 times faster with 10 subsets). Even compared to a hash table, our approach reduces the routing table lookup time by up to 58%.

• Journal of KIISE:Information Networking
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• v.31 no.2
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• pp.171-178
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• 2004

Port scanning detection systems should rather satisfy a certain level of the requirement for system performance like a low rate of “False Positive” and “False Negative”, and requirement for convenience for users to be easy to manage the system security with detection systems. However, public domain Real Time Scan Detection Systems have high rate of false detection and have difficulty in detecting various scanning techniques. In addition, as current real time scan detection systems are based on command interface, the systems are poor at user interface and thus it is difficult to apply them to the system security management. Hence, we propose TkRTSD(Tcl/Tk Real Time Scan Detection System) that is able to detect various scan attacks based on port scanning techniques by applying a set of new filter rules, and minimize the rate of False Positive by applying proposed ABP-Rules derived from attacker's behavioral patterns. Also a GUI environment for TkRTSD is implemented by using Tcl/Tk for user's convenience of managing network security.

• Convergence Security Journal
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• v.12 no.2
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• pp.61-70
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• 2012

The objective of this study is to achieve the most optimal data mining for effective analysis of false alarm event on mechanical security system. To perform this, this study searches the cause of false alarm and suggests the data conversion and analysis methods to apply to several algorithm of WEKA, which is a data mining program, based on statistical data for the number of case on movement by false alarm, false alarm rate and cause of false alarm. Analysis methods are used to estimate false alarm and set more effective reaction for false alarm by applying several algorithm. To use the suitable data for effective analysis of false alarm event on mechanical security analysis this study uses Decision Tree, Naive Bayes, BayesNet Apriori and J48Tree algorithm, and applies the algorithm by deducting the highest value.

• 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.