• Genomics & Informatics
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• v.10 no.1
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• pp.58-64
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• 2012

Intron prediction is an important problem of the constantly updated genome annotation. Using two model plant (rice and $Arabidopsis$) genomes, we compared two well-known intron prediction tools: the Blast-Like Alignment Tool (BLAT) and Sim4cc. The results showed that each of the tools had its own advantages and disadvantages. BLAT predicted more than 99% introns of whole genomic introns with a small number of false-positive introns. Sim4cc was successful at finding the correct introns with a false-negative rate of 1.02% to 4.85%, and it needed a longer run time than BLAT. Further, we evaluated the intron information of 10 complete plant genomes. As non-coding sequences, intron lengths are not limited by a triplet codon frame; so, intron lengths have three phases: a multiple of three bases (3n), a multiple of three bases plus one (3n + 1), and a multiple of three bases plus two (3n + 2). It was widely accepted that the percentages of the 3n, 3n + 1, and 3n + 2 introns were quite similar in genomes. Our studies showed that 80% (8/10) of species were similar in terms of the number of three phases. The percentages of 3n introns in $Ostreococcus$ $lucimarinus$ was excessive (47.7%), while in $Ostreococcus$ $tauri$, it was deficient (29.1%). This discrepancy could have been the result of errors in intron prediction. It is suggested that a three-phase evaluation is a fast and effective method of detecting intron annotation problems.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.451-456
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• 2004

Signature based intrusion detection system (IDS), having stored rules for detecting intrusions at the library, judges whether new inputs are intrusion or not by matching them with the new inputs. However their policy has two restrictions generally. First, when they couldn't make rules against new intrusions, false negative (FN) errors may are taken place. Second, when they made a lot of rules for maintaining diversification, the amount of resources grows larger proportional to their amount. In this paper, we propose the learning algorithm which can evolve the competent of anomaly detectors having the ability to detect anomalous attacks by genetic algorithm. The anomaly detectors are the population be composed of by following the negative selection procedure of the biological immune system. To show the effectiveness of proposed system, we apply the learning algorithm to the artificial network environment, which is a computer security system.

• Journal of Korean Tunnelling and Underground Space Association
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• v.17 no.4
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• pp.441-455
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• 2015

In the present study, a face safety monitoring system was developed that will enable judging collapse risks on faces during tunnel construction to secure workers' safety. This system enables detecting abnormal behaviors of faces by analyzing the displacement of faces measured in real time using the x-MR control chart technique. In addition, an algorithm to judge false alarms was developed so that abnormal behaviors of faces and errors occurring in the process of work can be distinguished from each other by comparing the number of measured values exceeding the management criteria and moving range k. The results of the present study are applicable to real-time monitoring of behavior on the face in dangerous ground sections to minimize damage to workers.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5967-5970
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• 2015

Background: The prevalence of prostate cancer is considered high in many countries, and screening tests are very important in order to detect prostate cancer in its early stages; however false positivity with these screening tests means that a lot of patients undergo unnecessary biopsy, which is an invasive procedure, for the confirmatory test. The purpose of this study was to estimate the frequency of unnecessary biopsy cases in patients referred for prostate biopsy in one of the most important and overload cancer centers in Syria. Materials and Methods: Retrospective data for a period of four years between January 2009 and December 2012 were collected in Al-Bayrouni University Medical hospital in Damascus, Syria. The patients from whom data were collected were referred to our histopathological department because of elevated prostate specific antigen (PSA) serum or an abnormal digital rectal examination (DRE). All patients underwent prostatic TRUS-guided biopsies. Diagnosis of prostate cancer (PCa) or benign prostatic hyperplasia (BPH) was based on histopathological examination and prostate cancers cases were graded and scored according to the Gleason score system. Results: For the 406 patients referred to biopsy, the $mean{\pm}SD$ age was $58.4{\pm}23.3$ years. The $mean{\pm}SD$ PSA level was $49.2{\pm}21.5ng/ml$. Of the total we found 237 patients diagnosed with PCa (58. 4%), 166 patients with BPH (40.9%) and 3 cases were unable to be diagnosed (0.7%) because of biopsy collection errors. Conclusions: Our study shows that a high percentage of patients are undergoing unnecessary biopsy, which suggests that the performed screening tests had a high level of false positive and may need re-evaluation.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.75-81
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• 2004

Signature based intrusion detection system (IDS), having stored rules for detecting intrusions at the library, judges whether new inputs are intrusion or not by matching them with the new inputs. However their policy has two restrictions generally. First, when they couldn`t make rules against new intrusions, false negative (FN) errors may are taken place. Second, when they made a lot of rules for maintaining diversification, the amount of resources grows larger proportional to their amount. In this paper, we propose the learning algorithm which can evolve the competent of anomaly detectors having the ability to detect anomalous attacks by genetic algorithm. The anomaly detectors are the population be composed of by following the negative selection procedure of the biological immune system. To show the effectiveness of proposed system, we apply the learning algorithm to the artificial network environment, which is a computer security system.

• Korea journal of population studies
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• v.20 no.1
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• pp.47-63
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• 1997

Problems concerning the vital registration system and its management, errors and methods to adjust them in the vital registration data in Korea have been studied. It is found that birth and death registration rates were above 95% in 1994. The registration rates rose rapidly since 1970 due to 1) simplification of registration form, 2) improving accessibility by allowing registration at the current residence, 3) enforcing fine against non-registration, and 4) improvements in social security system. However, there should be some continuing efforts for further improvement of the vital registration system. The content error in the data could be substantially reduced following the rapid rise of the registration rates in the 1980s, though this has never been actually studied. There are still substantial registrations with false date of death. The false date of events may affect the computed vital rates specially when the registration rates are rapidly rising. Especially the death rates of the young can be seriously affected. A study on the data in the 1970s shows that death of age between 3 to 19 has been over-registered up to 67% compared with the expected. It is a serious matter that some researchers analyze the registration data without adjusting the errors. It is strongly recommended for the Government Statistical Office to undertake a study on the registration behavior of the people.

• Journal of Radiation Protection and Research
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• v.45 no.3
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• pp.117-129
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• 2020

Background: Radiation portal monitors (RPMs) involving plastic scintillators installed at the border inspection sites can detect illicit trafficking of radioactive sources in cargo containers within seconds. However, RPMs may generate false alarms because of the naturally occurring radioactive materials. To manage these false alarms, we previously suggested an energy-weighted algorithm that emphasizes the Compton-edge area as an outstanding peak. This study intends to evaluate the identification of radioactive sources using an improved energy-weighted algorithm. Materials and Methods: The algorithm was modified by increasing the energy weighting factor, and different peak combinations of the energy-weighted spectra were tested for source identification. A commercialized RPM system was used to measure the energy-weighted spectra. The RPM comprised two large plastic scintillators with dimensions of 174 × 29 × 7 ㎤ facing each other at a distance of 4.6 m. In addition, the in-house-fabricated signal processing boards were connected to collect the signal converted into a spectrum. Further, the spectra from eight radioactive sources, including special nuclear materials (SNMs), which were set in motion using a linear motion system (LMS) and a cargo truck, were estimated to identify the source identification rate. Results and Discussion: Each energy-weighted spectrum exhibited a specific peak location, although high statistical fluctuation errors could be observed in the spectrum with the increasing source speed. In particular, ¹³⁷Cs and ⁶⁰Co in motion were identified completely (100%) at speeds of 5 and 10 km/hr. Further, SNMs, which trigger the RPM alarm, were identified approximately 80% of the time at both the aforementioned speeds. Conclusion: Using the modified energy-weighted algorithm, several characteristics of the energy weighted spectra could be observed when the used sources were in motion and when the geometric efficiency was low. In particular, the discrimination between ⁶⁰Co and ⁴⁰K, which triggers false alarms at the primary inspection sites, can be improved using the proposed algorithm.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.84.2-84.2
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• 2015

There are probabilistic forecast models for solar flare occurrence, which can be evaluated by various skill scores (e.g. accuracy, critical success index, heidek skill score, true skill score). Since these skill scores assume that two types of forecast errors (i.e. false alarm and miss) are equal or constant, which does not take into account different situations of users, they may be unrealistic. In this study, we make an evaluation of a probabilistic flare forecast model (Lee et al. 2012) which use sunspot groups and its area changes as a proxy of flux emergence. We calculate daily solar flare probabilities from 1996 to 2014 using this model. Overall frequencies are 61.08% (C), 22.83% (M), and 5.44% (X). The maximum probabilities computed by the model are 99.9% (C), 89.39% (M), and 25.45% (X), respectively. The skill scores are computed through contingency tables as a function of forecast probability, which corresponds to the maximum skill score depending on flare class and type of a skill score. For the critical success index widely used, the probability threshold values for contingency tables are 25% (C), 20% (M), and 4% (X). We use a value score with cost/loss ratio, relative importance between the two types of forecast errors. We find that the forecast model has an effective range of cost/loss ratio for each class flare: 0.15-0.83(C), 0.11-0.51(M), and 0.04-0.17(X), also depending on a lifetime of satellite. We expect that this study would provide a guideline to determine the probability threshold for space weather forecast.

• Journal of Broadcast Engineering
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• v.10 no.4 s.29
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• pp.540-547
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• 2005

In the DFE(Decision Feedback Equalizer) for ATSC DTV receivers, there are decision errors in the slicer or. the simplified trellis decoder, and these decided false data comes to the feedback filter to make the error propagation phenomenon. The error propagation degrades the equalizer performance by increasing residual errors as well as slowing down the convergence rate. In this paper we propose a dual-feedback equalization structure. There are two feedback filters. One is the decision feedback filter which uses the simplified trellis decoder output data, the other is non-decision feedback filter which uses the equalizer output data. The additional non-decision feedback filter doesn't introduce the error propagation, so it can compensate the error propagation. The proposed structure accelerates the convergence rate as well as reduces output men-square error(MSE). We analyzed the performance enhancement of DTV receiver using dual-feedback equalization structure.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.427-434
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• 2009

With the rapid evolution of the Internet and mobile environments, text including spelling errors such as newly-coined words and abbreviated words are widely used. These spelling errors make it difficult to develop NLP (natural language processing) applications because they decrease the readability of texts. To resolve this problem, we propose a spelling error correction model using a spelling error correction dictionary and a newspaper corpus. The proposed model has the advantage that the cost of data construction are not high because it uses a newspaper corpus, which we can easily obtain, as a training corpus. In addition, the proposed model has an advantage that additional external modules such as a morphological analyzer and a word-spacing error correction system are not required because it uses a simple string matching method based on a correction dictionary. In the experiments with a newspaper corpus and a short message corpus collected from real mobile phones, the proposed model has been shown good performances (a miss-correction rate of 7.3%, a F1-measure of 97.3%, and a false positive rate of 1.1%) in the various evaluation measures.