• The Korean Journal of Cytopathology
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• v.9 no.1
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• pp.37-44
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• 1998

OBJECTIVE: False negatives of cervical smears due to screening errors pose a significant and persistent problem. AutoPap 300 QC System, an automated screening device, is designed to rescreen conventionally prepared Pap smears initially screened by cytotechnologists as normal. Clinical experience and sensitivity of the AutoPap 300 QC System were assessed and compared with current 10% random qualify control technique. MATERIALS AND METHODS: In clinical practice, a total of 18,592 "within normal limits" or "benign cellular changes" cases classified by The Bethesda System were rescreened by the Autopap System. In study for sensitivity of The AutoPap System to detect false negatives, a total of 1,680 "within normal limits" or "benign cellular changes" cases were rescreened both manually and by the AutoPap System. The sensitivity of the AutoPap System to these false negatives was assessed at 10% review rate to compare 10% random manual rescreen. RESULTS: In clinical practice, 38 false negatives were identified by the AutoPap System and we had achieved 0.2% reduction in the false negative rate of screening error. In study for sensitivity, 37 false negatives were identified by manual rescreening, and 23 cases(62.2%) of the abnormal squamous cytology were detected by the AutoPap System at 10% review rate. CONCLUSONS: The AutoPap 300 QC System is a sensitive automated rescreening device that can detect potential false negatives prior to reporting and can reduce false negative rates in the laboratory. The device is confirmed to be about eight times superior to the 10% random rescreen in detecting false negatives.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.3
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• pp.163-168
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• 2015

Many IP address lookup approaches employ Bloom filters to obtain a high-speed search performance. Especially, it has been recently studied that the search performance of trie-based algorithms can be significantly improved by adding Bloom filters. In such algorithms, the number of trie accesses can be greatly reduced because Bloom filters can determine whether a node exists in a trie without actually accessing the trie. Bloom filters do not have false negatives but have false positives. False positives can lead to unnecessary trie accesses. The false positive rate must thus be reduced to enhance the performance of lookup algorithms applying Bloom filters. One important characteristic of trie-based algorithms is that all the ancestors of a node are also stored. The proposed algorithm utilizes this characteristic in reducing the false positive rate of a Bloom filter without increasing the size of the memory for the Bloom filter. When a Bloom filter produces a positive result for a node of a trie, we propose to check whether the ancestors of the node are also positives. Because Bloom filters have no false negatives, the negatives of any of the ancestors mean that the positive of the node is false. In other words, we propose to use more Bloom filter queries to reduce the false positive rate of a Bloom filter in trie-based algorithms. Simulation results show that querying one ancestor of a node can reduce the false positive rate by up to 67% with exactly the same architecture and the same memory requirement. The proposed approach can be applied to other trie-based algorithms employing Bloom filters.

• Convergence Security Journal
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• v.12 no.4
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• pp.57-69
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• 2012

C4ISR system is an important tool for military operational command and control. Therefore, it is frequently exposed to the cyber-terror attempt to paralyze the military command and control system. Generally, the information system uses IDS and firewall as major security computing tools. C4ISR system also uses them as major measures for the information protection. But the usefulness of IDS is reduced due to the frequent false-positives and false-negatives if the behavioral patterns are modified or new behavioral patterns appear. This paper presents new IDS structure which can create modified attack patterns and unexpected attack patterns automatically during IDS probing process. The proposed IDS structure is expected to enhance the information protection capability of the C4ISR system by reducing false-positives and false-negatives through the creation and verification of new attack patterns.

• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.154-168
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• 2021

COVID-19 has been spreading all around the world, and threatening global health. In this situation, identifying and isolating infected individuals rapidly has been one of the most important measures to contain the epidemic. However, the standard diagnosis procedure with RT-PCR (Reverse Transcriptase Polymerase Chain Reaction) is costly and time-consuming. For this reason, pooled testing for COVID-19 has been proposed from the early stage of the COVID-19 pandemic to reduce the cost and time of identifying the COVID-19 infection. For pooled testing, how many samples are tested in group is the most significant factor to the performance of the test system. When the arrivals of test requirements and the test time are stochastic, batch-service queueing models have been utilized for the analysis of pooled-testing systems. However, most of them do not consider the false-negative test results of pooled testing in their performance analysis. For the COVID-19 RT-PCR test, there is a small but certain possibility of false-negative test results, and the group-test size affects not only the time and cost of pooled testing, but also the false-negative rate of pooled testing, which is a significant concern to public health authorities. In this study, we analyze the performance of COVID-19 pooled-testing systems with false-negative test results. To do this, we first formulate the COVID-19 pooled-testing systems with false negatives as a batch-service queuing model, and then obtain the performance measures such as the expected number of test requirements in the system, the expected number of RP-PCR tests for a test sample, the false-negative group-test rate, and the total cost per unit time, using the queueing analysis. We also present a numerical example to demonstrate the applicability of our analysis, and draw a couple of implications for COVID-19 pooled testing.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.773-777
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• 2016

In this paper, a novel multi-object tracking method to track an unknown number of objects is proposed. To handle multiple object states and uncertain observations efficiently, a probability hypothesis density (PHD) filter is adopted and modified. The PHD filter is capable of reducing false positives, managing object appearances and disappearances, and estimating the multiple object trajectories in a unified framework. Although the PHD filter is robust in cluttered environments, it is vulnerable to false negatives. For this reason, we propose to exploit local observations in an RFS of the observation model. Each local observation is generated by using an online trained object detector. The main purpose of the local observation is to deal with false negatives in the PHD filtering procedure. The experimental results demonstrated that the proposed method robustly tracked multiple objects under practical situations.

• Journal of Microbiology and Biotechnology
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• v.16 no.11
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• pp.1773-1777
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• 2006

We evaluated the usefulness of DNA microarray as a comparative genomics tool, and tested the validity of the cutoff values for defining absent genes in test genomes. Three genome-sequenced E. coli strains (K-12, EDL933, and CFT073) were subjected to comparative genomic hybridization with DNA microarrays covering almost all ORFs of the reference strain K-12, and the microarray results were compared with the results obtained from in silico analyses of genome sequences. For defining the K-12 ORFs absent in test genomes (reference strain-specific ORFs), we applied and evaluated the cutoff level of -1. The average sequence similarity between ORFs, to which corresponding spots showed a log-ratio of>-1, was $96.9{\pm}4.8$. The numbers of spots showing a log-ratio of <-1 (P<0.05, t-test) were 90 (2.5%) and 417 (10.6%) for the EDL933 genome and the CFT073 genome, respectively. Frequency of false negatives (FN) was ca. 0.2, and the cutoff level of -1.3 was required to achieve the FN of 0.1. The average sequence similarity of the false negative ORFs was $77.8{\pm}14.8$, indicating that the majority of the false negatives were caused by highly divergent genes. We concluded that the microarray is useful for identifying missing or divergent ORFs in closely related prokaryotic genomes.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.3-10
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• 2017

Counting Bloom filters (CBFs) have been popularly used in many network algorithms and applications for the membership queries of dynamic sets, since CBFs can provide delete operations, which are not provided in a standard 1-bit vector Bloom filter. However, because of the counting functions, a CBF can have overflows and accordingly false negatives. CBFs composed of 4-bit counters are generally used, but the 4-bit CBF wastes memory spaces by allocating 4 bits for every counter. In this paper, we propose a simple alternative of a 4-bit CBF named ternary Bloom filter (TBF). In the proposed TBF structure, if two or more elements are mapped to a counter in programming, the counters are not used for insertion or deletion operations any more. When the TBF consumes the same amount of memory space as a 4-bit CBF, it is shown through simulation that the TBF provides a better false positive rate than the CBF as well as the TBF does not generate false negatives.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.803-806
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• 2000

The correspondence problem is known to be difficult to solve because false positives and false negatives almost always exist in real image sequences. In this paper, we propose a robust feature tracking algorithm considering incomplete trajectories such as entering and/or vanishing trajectories. We solve the correspondence problem as the optimal graph search problem, by considering false feature points and by properly reflecting motion characteristics. The proposed algorithm finds a local optimal correspondence so that the effect of false feature points can be minimized in the decision process. The time complexity of the proposed graph search algorithm is given by O(mn) in the best case and O(m$^2$n) in the worst case, where m and n are the number of feature points in two consecutive frames. The proposed algorithm can find trajectories correctly and robustly, which has been shown by experimental results.

• Journal of Trauma and Injury
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• v.19 no.2
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• pp.135-142
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• 2006

Purpose: We planned to determine the diagnostic capability of focused assessment with sonography for trauma (FAST) in cases of blunt abdominal injury (BAI). Methods: A retrospective analysis of FAST sheets was performed from April 2002 to December 2004. During the study period, 135 BAI patients were evaluated with FAST at the Emergency Department of Bundang CHA Hospital. Of this group, twenty-eight patients were excluded, leaving 107 patients for analysis. Abdomen CT (computerized tomography) or exploratory laparotomy confirmed the presence of hemoperitoneum. At the secondary survey, patients underwent a three-view FAST examination (LogicQ; General Electric, Waukesha, USA) by an emergency physician, followed within 2 hours by an abdomen CT or exploratory laparotomy. The FAST examination was considered positive if it demonstrated evidence of free intra-abdominal fluid. Results: There were 45 true-positive FAST examination, 57 true-negatives, 1 false-positive, and 4 false negatives (sensitivity 91.8%, specificity 98.3%, positive predictive value 97.8%, negative predictive value 93.4%). The area under the ROC curve was 0.951 for the FAST examination. Conclusion: FAST is a highly reliable method for screening patients suspected of having BAI for the presence or absence of hemoperitoneum.