• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.181-190
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• 2009

DBMS access that used high speed internet web service through WAS is increasing. Need application of DB security technology for 3-Tier about DBMS by unspecified majority and access about roundabout way connection and competence control. If do roundabout way connection to DBMS through WAS, DBMS server stores WAS's information that is user who do not store roundabout way connection user's IP information, and connects to verge system. To DBMS in this investigation roundabout way connection through WAS do curie information that know chasing station security thanks recording and Forensic data study. Store session about user and query information that do login through web constructing MetaDB in communication route, and to DBMS server log storing done query information time stamp query because do comparison mapping actuality user discriminate. Apply making Rule after Pattern analysis receiving log by elevation method of security authoritativeness, and develop Module and keep in the data storing place through collection and compression of information. Kept information can minimize false positives of station chase through control of analysis and policy base administration module that utilize intelligence style DBMS security client.

• 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.

• Journal of Biomedical Engineering Research
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• v.44 no.6
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• pp.384-391
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• 2023

Among the elderly, fatal injuries and deaths are significantly attributed to falls. Therefore, a pre-impact fall detection system is necessary for injury prevention. In this study, a robust threshold-based algorithm was proposed for pre-impact fall detection, reducing false positives in highly dynamic daily-living movements. The algorithm was validated using public datasets (KFall and FARSEEING) that include the real-world elderly fall. A 6-axis IMU sensor (Movella Dot, Movella, Netherlands) was attached to S2 of 20 healthy adults (aged 22.0±1.9years, height 164.9±5.9cm, weight 61.4±17.1kg) to measure 14 activities of daily living and 11 fall movements at a sampling frequency of 60Hz. A 5Hz low-pass filter was applied to the IMU data to remove high-frequency noise. Sum vector magnitude of acceleration and angular velocity, roll, pitch, and vertical velocity were extracted as feature vector. The proposed algorithm showed an accuracy 98.3%, a sensitivity 100%, a specificity 97.0%, and an average lead-time 311±99ms with our experimental data. When evaluated using the KFall public dataset, an accuracy in adult data improved to 99.5% compared to recent studies, and for the elderly data, a specificity of 100% was achieved. When evaluated using FARSEEING real-world elderly fall data without separate segmentation, it showed a sensitivity of 71.4% (5/7).

• Journal of the Korean Society of Radiology
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• v.84 no.3
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• pp.520-535
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• 2023

Gastrointestinal (GI) bleeding is not a single disease but a symptom and clinical manifestation of a broad spectrum of conditions in the GI tract. According to its clinical presentation, GI bleeding can be classified into overt, occult, and obscure types. Additionally, it can be divided into upper and lower GI bleeding based on the Treitz ligament. Variable disease entities, including vascular lesions, polyps, neoplasms, inflammation such as Crohn's disease, and heterotopic pancreatic or gastric tissue, can cause GI bleeding. CT and conventional angiographies and nuclear scintigraphy are all radiologic imaging modalities that can be used to evaluate overt bleeding. For the work-up of occult GI bleeding, CT enterography (CTE) can be the first imaging modality. For CTE, an adequate bowel distention is critical for obtaining acceptable diagnostic performance as well as minimizing false positives and negatives. Meckel's scintigraphy can be complementarily useful in cases where the diagnosis of CTE is suboptimal. For the evaluation of obscured GI bleeding, various imaging modalities can be used based on clinical status and providers' preferences.

• Journal of the Korean Society of Radiology
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• v.84 no.3
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• pp.713-718
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• 2023

Orthotopic liver transplantation has become the treatment of choice for patients with end-stage liver disease. Various early or delayed vascular complications, including arterial pseudoaneurysm, thrombosis, or stenosis, and venous stenosis or occlusion, may lead to graft failure. Early detection and prompt management of such complications are essential to achieve successful transplantation and prevent the need for retransplantation. This report presents differentiating points, using computed tomography and digital subtraction angiography findings and measurement of pressure gradient across the stenotic lesion, that require immediate intervention in patients with inferior vena cava stenosis after orthotopic liver transplantation.

• The Korean Journal of Nuclear Medicine
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• v.30 no.4
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• pp.516-523
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• 1996

The purpose of this study was to evaluate the clinical usefulness of I-123 MIBG scintigraphy with early planar and SPECT image in the diagnosis of neuroendocrine tumors. We reviewed I-123 MIBG scintigraphies of 21 patients who had been suspected to have neuroendocrine tumors by CT or MRI findings. Early 4 hour planar and SPECT images were obtained in all patients and delayed (13-24 hour) planar images were performed in 17 patients. Final diagnoses were made by surgery, biopsy, or clinical follow up. Twelve patients were confirmed to have neuroendocrine tumors. With 4 hour planar and SPECT images, there were 9 true positives(6 pheochromocytomas, 1 paraganglioma, 1 neuroblastoma, and 1 medullary cancer of the thyroid), 8 true negatives(1 adrenal cortical adenoma, 1 malignant fibrous histiocytoma, 1 adenoma in colon and 5 benign nonfunctioning adrenal tumors), 1 false positive(hepatocellular carcinoma) and 3 false negatives(1 recurred medullary cancer of the thyroid, 1 liver metastasis of carcinoid tumor and 1 ganglioneuroma). The sensitivity and specificity of I-123 MIBG scintigraphy were 75% and 89%, respectively. SPECT images provided good anatomical correlation with CT or MRI. Delayed images showed increased tumor to background ratio in 5 out of 8 true positive patients, but did not change the diagnosis. In conclusion, early 4 hour images with I-123 MIBG is clinically convenient and useful method in the detection of neuroendocrine tumors, and SPECT images can provide good anatomical correlation with CT or MRI.

• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.679-688
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• 2006

Protein-protein interaction data obtained from high-throughput experiments includes high false positives. In this paper, we introduce a new protein-protein interaction reliability verification system. The proposed system integrates various biological features related with protein-protein interactions, and then selects the most relevant and informative features among them using a feature selection method. To assess the reliability of each protein-protein interaction data, the system construct a classifier that can distinguish true interacting protein pairs from noisy protein-protein interaction data based on the selected biological evidences using a classification technique. Since the performance of feature selection methods and classification techniques depends heavily upon characteristics of data, we performed rigorous comparative analysis of various feature selection methods and classification techniques to obtain optimal performance of our system. Experimental results show that the combination of feature selection method and classification algorithms provide very powerful tools in distinguishing true interacting protein pairs from noisy protein-protein interaction dataset. Also, we investigated the effects on performances of feature selection methods and classification techniques in the proposed protein interaction verification system.

• Journal of Preventive Medicine and Public Health
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• v.52 no.2
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• pp.131-139
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• 2019

Objectives: Self-reporting can be used to determine the incidence and prevalence of hypertension (HTN). The present study was conducted to determine the validity of self-reported HTN and to identify factors affecting discordance between self-reported and objectively measured HTN in participants in the Ravansar Non-Communicable Diseases (RaNCD) cohort. Methods: The RaNCD cohort included permanent residents of Ravansar, Iran aged 35-65 years. Self-reported data were collected before clinical examinations were conducted by well-trained staff members. The gold standard for HTN was anti-hypertensive medication use and blood pressure measurements. The sensitivity, specificity, positive and negative predictive values, and overall accuracy of self-reporting were calculated. Univariate and multivariate logistic regression were used to examine the discordance between self-reported HTN and the gold standard. Results: Of the 10 065 participants in the RaNCD, 4755 (47.4%) were male. The prevalence of HTN was 16.8% based on self-reporting and 15.7% based on medical history and HTN measurements. Of the participants with HTN, 297 (18.8%) had no knowledge of their disease, and 313 (19.9%) had not properly controlled their HTN despite receiving treatment. The sensitivity, specificity, and kappa for self-reported HTN were 75.5%, 96.4%, and 73.4%, respectively. False positives became more likely with age, body mass index (BMI), low socioeconomic status, and female sex, whereas false negatives became more likely with age, BMI, high socioeconomic status, smoking, and urban residency. Conclusions: The sensitivity and specificity of self-reported HTN were acceptable, suggesting that this method can be used for public health initiatives in the absence of countrywide HTN control and detection programs.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.896-905
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• 2021

In the field of SIEM(Security information and event management), many studies try to use a feedback system to solve lack of completeness of training data and false positives of new attack events that occur in the actual operation. However, the current feedback system requires too much human inputs to improve the running model and even so, those feedback from inexperienced analysts can affect the model performance negatively. Therefore, we propose "active model improving feedback technology" to solve the shortage of security analyst manpower, increasing false positive rates and degrading model performance. First, we cluster similar predicted events during the operation, calculate feedback priorities for those clusters and select and provide representative events from those highly prioritized clusters using XAI (eXplainable AI)-based event visualization. Once these events are feedbacked, we exclude less analogous events and then propagate the feedback throughout the clusters. Finally, these events are incrementally trained by an existing model. To verify the effectiveness of our proposal, we compared three distinct scenarios using PKDD2007 and CSIC2012. As a result, our proposal confirmed a 30% higher performance in all indicators compared to that of the model with no feedback and the current feedback system.

• KNOM Review
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• v.23 no.2
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• pp.18-28
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• 2020

With the development of the virtual community, the benefits that IT technology provides to people in fields such as healthcare, industry, communication, and culture are increasing, and the quality of life is also improving. Accordingly, there are various malicious attacks targeting the developed network environment. Firewalls and intrusion detection systems exist to detect these attacks in advance, but there is a limit to detecting malicious attacks that are evolving day by day. In order to solve this problem, intrusion detection research using machine learning is being actively conducted, but false positives and false negatives are occurring due to imbalance of the learning dataset. In this paper, a Random Oversampling method is used to solve the unbalance problem of the UNSW-NB15 dataset used for network intrusion detection. And through experiments, we compared and analyzed the accuracy, precision, recall, F1-score, training and prediction time, and hardware resource consumption of the models. Based on this study using the Random Oversampling method, we develop a more efficient network intrusion detection model study using other methods and high-performance models that can solve the unbalanced data problem.