• The Journal of the Acoustical Society of Korea
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• v.41 no.4
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• pp.468-479
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• 2022

To detect targets with active sonar system in the underwater environments, the targets are localized by receiving the echoes of the transmitted sounds reflected from the targets. In this case, reverberation from the scatterers is also generated, which prevents detection of the target echo. To detect the target effectively, reverberation suppression techniques such as pre-whitening based on autoregressive model and principal component inversion have been studied, and recently a Non-negative Matrix Factorization (NMF)-based technique has been also devised. The NMF-based reverberation suppression technique shows improved performance compared to the conventional methods, but the geometry of the transducer and receiver and attenuation by distance have not been considered. In this paper, the performance is improved through preprocessing such as the directionality of the receiver, Doppler related thereto, and attenuation for distance, in the case of using a continuous wave with a bistatic sonar. In order to evaluate the performance of the proposed system, simulation with a reverberation model was performed. The results show that the detection probability performance improved by 10 % to 40 % at a low false alarm probability of 1 % relative to the conventional non-negative matrix factorization.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.125-144
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• 2022

When a variable message signs (VMS) system displays false information related to traffic safety caused by malicious attacks, it could pose a serious risk to drivers. If the normal message patterns displayed on the VMS system are learned, it would be possible to detect and respond to the anomalous messages quickly. This paper proposes a method for detecting anomalous messages by learning the normal patterns of messages using a bi-directional generative pre-trained transformer (GPT) network. In particular, the proposed method was trained using the normal messages and their system parameters to minimize the corresponding negative log-likelihood (NLL) values. After adequate training, the proposed method could detect an anomalous message when its NLL value was larger than a pre-specified threshold value. The experiment results showed that the proposed method could detect malicious messages and cases when the system error occurs.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.17-25
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• 2023

The alarming global prevalence of Type 2 Diabetes Mellitus (T2DM) has catalyzed an urgent need for robust, early diagnostic methodologies. This study unveils a pioneering approach to predicting T2DM, employing the Extreme Gradient Boosting (XGBoost) algorithm, renowned for its predictive accuracy and computational efficiency. The investigation harnesses a meticulously curated dataset of 4303 samples, extracted from a comprehensive Chinese research study, scrupulously aligned with the World Health Organization's indicators and standards. The dataset encapsulates a multifaceted spectrum of clinical, demographic, and lifestyle attributes. Through an intricate process of hyperparameter optimization, the XGBoost model exhibited an unparalleled best score, elucidating a distinctive combination of parameters such as a learning rate of 0.1, max depth of 3, 150 estimators, and specific colsample strategies. The model's validation accuracy of 0.957, coupled with a sensitivity of 0.9898 and specificity of 0.8897, underlines its robustness in classifying T2DM. A detailed analysis of the confusion matrix further substantiated the model's diagnostic prowess, with an F1-score of 0.9308, illustrating its balanced performance in true positive and negative classifications. The precision and recall metrics provided nuanced insights into the model's ability to minimize false predictions, thereby enhancing its clinical applicability. The research findings not only underline the remarkable efficacy of XGBoost in T2DM prediction but also contribute to the burgeoning field of machine learning applications in personalized healthcare. By elucidating a novel paradigm that accentuates the synergistic integration of multifaceted clinical parameters, this study fosters a promising avenue for precise early detection, risk stratification, and patient-centric intervention in diabetes care. The research serves as a beacon, inspiring further exploration and innovation in leveraging advanced analytical techniques for transformative impacts on predictive diagnostics and chronic disease management.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.253-266
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• 2023

The Null Pointer Dereference vulnerability is a significant vulnerability that can cause severe attacks such as denial-of-service. Previous research has proposed methods for detecting vulnerabilities, but large and complex programs pose a challenge to their efficiency. In this paper, we present a lightweight tool for detecting specific functions in large binaryprograms through symbolizing variables and emulating program execution. The tool detects vulnerabilities through data dependency analysis and heuristics in each execution path. While our tool had an 8% higher false positive rate than the bap_toolkit, it detected all existing vulnerabilities in our dataset.

• Journal of Software Assessment and Valuation
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• v.7 no.1
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• pp.29-39
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• 2011

To evaluate the quality of clone detection tools, we should know how many clones the tool misses. Hence we need to have the standard code-clone reference corpus for a carefully chosen set of sample source codes. The reference corpus available so far has been built by manually collecting clones from the results of various existing tools. This paper presents a tree-pattern-based clone detection tool that can be used for automatic generation of reference corpus. Our tool is compared with CloneDR for precision and Bellon's reference corpus for recall. Our tool finds no false positives and 2 to 3 times more clones than CloneDR. Compared to Bellon's reference corpus, our tools shows the 93%-to-100% recall rate and detects far more clones.

• Investigative Magnetic Resonance Imaging
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• v.9 no.2
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• pp.109-116
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• 2005

Purpose : To determine the usefulness of additional Mn-DPDP MRI for preoperative evaluation of the patients with colorectal cancers by comparison of dual-phase CT scan, Mn-DPDP enhanced MRI and combination of CT and MRI. Materials and Methods : Fifty-three colorectal cancer patients with 92 metastatic nodules underwent dualphase (arterial and portal) helical CT scan and Mn-DPDP MRI prior to surgery. The indication of MRI was presence or suspected of having metastatic lesions at CT scan and/or increased serum carcinoembryonic antigen (CEA) levels (10 ng/mL or more). The diagnosis was established by the combination of findings at surgery, intraoperative ultrasonography, and histopathologic examination. Two radiologists interpreted CT, MRI, and combination of CT-MRI at discrete sessions and evaluated each lesion for location, size, and intrinsic characteristics. The lesions were divided into three groups according to their diameter; 1cm<, 1-2 cm, and >2 cm. Diagnostic accuracy was evaluated using the alternative-free response receiver operating characteristic method. Detection and false positive rate were also evaluated. Results : In the lesions smaller than 1 cm, detection rate of combined CT-MRI was superior to CT or MRI alone (82%, p=0.036). The mean accuracy (Az values) of combined CT and MRI was significantly higher than that of CT in the lesions smaller than 2 cm (1 cm<, p=0.034; 1-2 cm, p=0.045). However, there was no significant difference between MRI and combined CT-MRI. The false positive rate of CT was higher than those of combined CT-MR in the lesions smaller than 1 cm (28%, p=0.023). Conclusion : Additional MRI using Mn-DPDP besides routine CT scan was helpful in differentiating the hepatic lesions (<2 cm) and could improve detection of the small hepatic metastases (<1 cm) from colorectal carcinoma.

• The Korean Journal of Nuclear Medicine
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• v.34 no.3
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• pp.234-242
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• 2000

Purpose: Tc-99m MIBI scintimammography has been validated as an useful non-invasive diagnostic tool for the primary breast cancer. But most studies have included small population of patients. We have experienced a large study population and investigated the diagnostic usefulness of Tc-99m MIBI scintimammography in detection of primary breast cancer and axillary lymph node metastasis. Materials and Methods: This study included 305 patients who underwent scintimammogtaphy for palpable breast masses or abnormal radiologic findings. Tc-99m MIBI scintimammography was performed 10 minutes after intravenous injection of 925 MBq of Tc-99m MIBI. If the early image revealed abnormal finding, 3 hour delayed image was also acquired. We calculated early and delayed lesion to non-lesion ratios (L/N). The pathologic diagnosis was obtained from surgical operation or FNAB and compared with the results of Tc-99m MIBI scintimammography. Results: Malignant breast diseases were 155 and benign ones were 150. Tc-99m MIBI scintimammography revealed 132 true positive, 23 false negative, 10 false positive, and 140 true negative cases. The sensitivity, specificity, positive predictive value and negative predictive value for the primary breast cancer detection were 85.2%, 93.4%, 92.9%, and 85.9%, respectively. The sensitivity, specificity, positive predictive and negative predictive values of Tc-99m MIBI scintimammography in detecting metastatic axillary lymph node involvement were 22%, 90.4%, 61.9% and 62.3%, respectively. Early L/N of malignant breast disease was significantly higher than that of benign one ($2.44{\pm}0.97\;vs\;1.94{\pm}0.78$, p=0.01). Delayed L/N had no significant difference between malignant and benign breast diseases ($1.94{\pm}0.52\;vs\;1.91{\pm}0.73$, p=0.43). Conclusion: Our study revealed that Tc-99m MIBI scintimammography was an useful diagnostic tool for the diagnosis of breast cancer. And early L/N ratio might provide complementary role in the detection of breast cancer. But the Tc-99m MIBI scintimammography had limited value in the detection of small breast cancer (less than 1 cm) and axillary lymph node metastasis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5B
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• pp.931-941
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• 2000

We propose a serial acquisition scheme using antenna arrays for initial acquisition of direct sequence spread spectrum (DS-SS) signals, which can lower substantially the range of detectable signal-to-noise ratio (SNR). The proposed scheme uses the sum of the independent decision samples form psedo-noise (PN) co-phased noncoherent I-Q matched filters (MFs) associated with antenna arrays as a decision variable in order to enhance SNR of the resulting signal. We analyze its mean acquisition time performance under an additive white Gaussian noise (AWGN) channel and a flat Rayleigh fading channel by deriving the expressions for the probabilities of detection and false alarm. From mumerical results, we see that the acquisition performance of the proposal scheme becomes improved continually as the number of antennas increses.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.5
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• pp.617-623
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• 2008

A fine-mapping method exploiting linkage disequilibrium was used to detect quantitative trait loci (QTL) on the X chromosome affecting milk production, body conformation and productivity traits. The pedigree comprised 22 paternal half-sib families of Black-and-White Holstein bulls in the Netherlands in a grand-daughter design for a total of 955 sons. Twenty-five microsatellite markers were genotyped to construct a linkage map on the chromosome X spanning 170 Haldane cM with an average inter-marker distance of 7.1 cM. A covariance matrix including elements about identical-by-descent probabilities between haplotypes regarding QTL allele effects was incorporated into the animal model, and a restricted maximum-likelihood method was applied for the presence of QTL using the LDVCM program. Significance thresholds were obtained by permuting haplotypes to phenotypes and by using a false discovery rate procedure. Seven QTL responsible for conformation types (teat length, rump width, rear leg set, angularity and fore udder attachment), behavior (temperament) and a mixture of production and health (durable prestation) were detected at the suggestive level. Some QTL affecting teat length, rump width, durable prestation and rear leg set had small numbers of haplotype clusters, which may indicate good classification of alleles for causal genes or markers that are tightly associated with the causal mutation. However, higher maker density is required to better refine the QTL position and to better characterize functionally distinct haplotypes which will provide information to find causal genes for the traits.

• Journal of Microbiology and Biotechnology
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• v.18 no.3
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• pp.579-584
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• 2008

A commercial chromogenic agar medium (DFI) was supplemented with glucose (mDFI) to enhance the specificity of Enterobacter sakazakii (E. sakazakit) detection. Escherichia vulneris (E. vulneris), a putative false-positive strain on the DFI medium, produces ${\alpha}$-glucosidase. The enzyme ${\alpha}$-glucosidase hydrolyzes a substrate, 5-bromo-4-chloro-3-indolyl-${\alpha}$, D-glucopyranoside $(X{\alpha}Glc)$, producing green colonies. E. sakazakii strains produced green colonies on both DFI and mDFI agar, whereas E. vulneris produced green colonies on DFI agar but small white colonies on mDFI agar. E. sakazakii and E. vulneris were also readily differentiated by colony color when the mixed culture of the two strains was plated on mDFI agar and incubated for 24 h at $37^{\circ}C$. The results indicate that the selectivity of the commercial chromogenic agar medium could be improved by a simple supplementation with glucose.