• Clinical and Experimental Pediatrics
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• 제64권2호
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• pp.80-85
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• 2021

Background: Although identifying cases in large administrative databases may aid future research studies, previous reports demonstrated that the use of the International Classification of Diseases, Tenth Revision (ICD-10) code alone for diagnosis leads to disease misclassification. Purpose: We aimed to assess the value of the ICD-10 diagnostic code for identifying potential children with biliary atresia. Methods: Patients aged <18 years assigned the ICD-10 code of biliary atresia (Q44.2) between January 1996 and December 2016 at a quaternary care teaching hospital were identified. We also reviewed patients with other diagnoses of code-defined cirrhosis to identify more potential cases of biliary atresia. A proposed diagnostic algorithm was used to define ICD-10 code accuracy, sensitivity, and specificity. Results: We reviewed the medical records of 155 patients with ICD-10 code Q44.2 and 69 patients with other codes for biliary cirrhosis (K74.4, K74.5, K74.6). The accuracy for identifying definite/probable/possible biliary atresia cases was 80%, while the sensitivity was 88% (95% confidence interval [CI], 82%-93%). Three independent predictors were associated with algorithm-defined definite/probable/possible cases of biliary atresia: ICD-10 code Q44.2 (odds ratio [OR], 2.90; 95% CI, 1.09-7.71), history of pale stool (OR, 2.78; 95% CI, 1.18-6.60), and a presumed diagnosis of biliary atresia prior to referral to our hospital (OR, 17.49; 95% CI, 7.01-43.64). A significant interaction was noted between ICD-10 code Q44.2 and a history of pale stool (P<0.05). The area under the curve was 0.87 (95% CI, 0.84-0.89). Conclusion: ICD-10 code Q44.2 has an acceptable value for diagnosing biliary atresia. Incorporating clinical data improves the case identification. The use of this proposed diagnostic algorithm to examine data from administrative databases may facilitate appropriate health care allocation and aid future research investigations.

• Asian-Australasian Journal of Animal Sciences
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• 제31권12호
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• pp.1852-1862
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• 2018

Objective: The purpose of this study was to investigate a single step genome-wide association study (ssGWAS) for identifying genomic regions affecting reproductive traits in Landrace and Large White pigs. Methods: The traits included the number of pigs weaned per sow per year (PWSY), the number of litters per sow per year (LSY), pigs weaned per litters (PWL), born alive per litters (BAL), non-productive day (NPD) and wean to conception interval per litters (W2CL). A total of 321 animals (140 Landrace and 181 Large White pigs) were genotyped with the Illumina Porcine SNP 60k BeadChip, containing 61,177 single nucleotide polymorphisms (SNPs), while multiple traits single-step genomic BLUP method was used to calculate variances of 5 SNP windows for 11,048 Landrace and 13,985 Large White data records. Results: The outcome of ssGWAS on the reproductive traits identified twenty-five and twenty-two SNPs associated with reproductive traits in Landrace and Large White, respectively. Three known genes were identified to be candidate genes in Landrace pigs including retinol binding protein 7, and ubiquitination factor E4B genes for PWL, BAL, W2CL, and PWSY and one gene, solute carrier organic anion transporter family member 6A1, for LSY and NPD. Meanwhile, five genes were identified to be candidate genes in Large White, two of which, aldehyde dehydrogenase 1 family member A3 and leucine rich repeat kinase 1, associated with all of six reproduction traits and three genes; retrotransposon Gag like 4, transient receptor potential cation channel subfamily C member 5, and LHFPL tetraspan subfamily member 1 for five traits except W2CL. Conclusion: The genomic regions identified in this study provided a start-up point for marker assisted selection and estimating genomic breeding values for improving reproductive traits in commercial pig populations.

• Structural Engineering and Mechanics
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• 제68권5호
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• pp.575-589
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• 2018

It is well known that the incidence angle of seismic excitation has an influence on the structural response of buildings, and this effect can be more significant in the case of near-fault signals. However, current seismic codes do not include detailed requirements regarding the direction of application of the seismic action and they have only recently introduced specific provisions about near-fault earthquakes. Thus, engineers have the task of evaluating all the relevant directions or the most critical conditions case by case, in order to avoid underestimating structural demand. To facilitate the identification of the most critical incidence angle, this paper presents a procedure which makes use of a two-degree of freedom model for representing a building. The proposed procedure makes it possible to avoid the extensive computational effort of multiple dynamic analyses with varying angles of incidence of ground motion excitation, which is required if a spatial multi-degree of freedom model is used for representing a building. The procedure is validated through the analysis of two case studies consisting of an eight- and a six-storey reinforced concrete frame building, selected as representative of existing structures located in Italy. A set of 124 near-fault ground motion records oriented along 8 incidence angles, varying from 0 to 180 degrees, with increments of 22.5 degrees, is used to excite the structures. Comparisons between the results obtained with detailed models of the two structures and the proposed procedure are used to show the accuracy of the latter in the prediction of the most critical angle of seismic incidence.

• Clinical and Experimental Pediatrics
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• 제62권6호
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• pp.224-234
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• 2019

Purpose: Pompe disease (PD) is an autosomal recessive disorder caused by a deficiency of acid alpha-glucosidase resulting from pathogenic GAA variants. This study describes the clinical features, genotypes, changes before and after enzyme replacement therapy (ERT), and long-term outcomes in patients with infantile-onset PD (IOPD) and late-onset PD (LOPD) at a tertiary medical center. Methods: The medical records of 5 Korean patients (2 male, 3 female patients) diagnosed with PD between 2002 and 2013 at Samsung Medical Center in Seoul, Republic of Korea were retrospectively reviewed for data, including clinical and genetic characteristics at diagnosis and clinical course after ERT. Results: Common initial symptoms included hypotonia, cyanosis, and tachycardia in patients with IOPD and limb girdle weakness in patients with LOPD. Electrocardiography at diagnosis revealed hypertrophic cardiomyopathy in all patients with IOPD who showed a stable disease course during a median follow-up period of 10 years. Patients with LOPD showed improved hepatomegaly and liver transaminase level after ERT. Conclusion: As ERT is effective for treatment of PD, early identification of this disease is very important. Thus, patients with IOPD should be considered candidates for clinical trials of new drugs in the future.

• 해양환경안전학회지
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• 제25권3호
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• pp.269-277
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• 2019

Since 2020, according to the International Convention for the Prevention of Pollution from Ships (MARPOL) amended in 2016, each Administration shall transfer the annual fuel consumption of its registered ships of 5,000 gross tonnage and above to the International Maritime Organization (IMO) after verifying them. The Administration needs stacks of materials, which must not be manipulated by ship companies, including the Engine log book and also bears an administrative burden to verify them by May every year. This study considers using the Automatic Identification System (AIS), mandatory navigational equipment, as an objective and efficient tool among several verification methods. Calculating fuel consumption using a ship's speed in AIS information based on the theory of a relationship between ship speed and fuel consumption was reported in several examples of relevant literature. After pre-filtering by excluding AIS records which had speed errors from the raw data of five domestic cargo vessels, fuel consumptions calculated using Excel software were compared to actual bunker consumptions presented by ship companies. The former consumptions ranged from 96 to 123 percent of the actual bunker consumptions. The difference between two consumptions could be narrowed to within 20 percent if the fuel consumptions for boilers were deducted from the actual bunker consumption. Although further study should be carried out for more accurate calculation methods depending on the burning efficiency of the engine, the propulsion efficiency of the ship, displacement and sea conditions, this method of calculating annual fuel consumption according to the difference between two consumptions is considered to be one of the most useful tools to verify bunker consumption.

• Animal Systematics, Evolution and Diversity
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• 제38권4호
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• pp.226-237
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• 2022

Arcuospathidium is a haptorian ciliate genus composed of 18 species, and only one species has been reported in Korea. Here, we identify two unrecorded Arcuospathidium subspecies by morphological observation of both living and protargol-impregnated specimens with the small subunit ribosomal RNA (18S rRNA) gene sequence. These subspecies, Arcuospathidium cultriforme cultriforme (Penard, 1922) Foissner, 1984 and A. cultriforme scalpriforme (Kahl, 1930) Foissner, 2003, were isolated from various terrestrial habitats in July and August 2013, respectivley. Arcuospathidium cultriforme cultriforme is similar to A. cultriforme scalpriforme by a knife-shaped body, a twisted-shaped macronucleus, number of dorsal brushes, position of dorsal brushes, and shape of macronucleus but former mainly differs from the body length to oral bulge length ratio (27-38% vs. 41-53%), extrusome (one types vs. three types), cyst shape (roughly faceted wall vs. smooth surface and thin wall) and number of somatic kinety rows(18-30 vs. 30-44). Additionally, we analyzed the 18S rRNA gene sequences of two A. cultriforme subspecies and compared them with the sequences from GenBank to confirm their identification at the molecular level. As the results of genetic analysis, the 18S rRNA gene sequence of the Korean A. cultriforme cultriforme population is most similar to that of Austrian population. Also, the sequence of the Korean A. cultriforme scalpriforme population is most similar to that of another population with some nucleotide differences.

• Smart Structures and Systems
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• 제29권1호
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• International Journal of Computer Science & Network Security
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• 제23권9호
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• pp.150-156
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• 2023

For a doctor, diagnosing a patient's heart disease is not easy. It takes the ability and experience with high flying hours to be able to accurately diagnose the type of patient's heart disease based on the existing factors in the patient. Several studies have been carried out to develop tools to identify types of heart disease in patients. However, most only focus on the results of patient answers and lab results, the rest use only echocardiography data or electrocardiogram results. This research was conducted to test how accurate the results of the classification of heart disease by using two medical data, namely echocardiography and electrocardiogram. Three treatments were applied to the two medical data and analyzed using the decision tree approach. The first treatment was to build a classification model for types of heart disease based on echocardiography and electrocardiogram data, the second treatment only used echocardiography data and the third treatment only used electrocardiogram data. The results showed that the classification of types of heart disease in the first treatment had a higher level of accuracy than the second and third treatments. The accuracy level for the first, second and third treatment were 78.95%, 73.69% and 50%, respectively. This shows that in order to diagnose the type of patient's heart disease, it is advisable to look at the records of both the patient's medical data (echocardiography and electrocardiogram) to get an accurate level of diagnosis results that can be accounted for.

• 융합보안논문지
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• 제22권2호
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• pp.3-8
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• 2022

보안 위협은 외부에서 발생하기도 하지만 내부에서 발생하는 비율이 더 높다. 특히 내부 사용자는 정보 서비스에 대한 정보를 인지하고 있기에 보안 위협에 의한 피해는 더욱 커진다. 이러한 환경에서 중요 정보 서비스에 접근하는 모든 사용자의 행위는 실시간으로 모니터링되고 기록되어야 한다. 그러나 현재 운영체제는 시스템과 Application 실행에 대한 로그만을 기록하고 있어, 사용자의 행위를 실시간으로 모니터링하기에는 한계가 있다. 이러한 보안 환경에서는 사용자의 비인가 행위로 인한 피해가 발생할 수 있다. 본 연구는 이러한 문제점을 해결하기 위하여, Linux 환경에서 사용자의 행위를 실시간으로 모니터링하는 아키텍처를 제안한다. 제안하는 아키텍처의 실효성을 확인하기 위하여 기능을 검증한 결과, 운영체제에 접근한 모든 사용자의 console 입력값과 출력값을 모두 실시간으로 모니터링하고 이를 저장한다. 제안한 아키텍처의 성능은 운영체제에서 제공하는 식별 및 인증 기능보다는 다소 늦지만, 사용자가 인지할 수준은 아닌 것으로 확인되어, 충분히 실효적이라고 판단되었다.

• Journal of Periodontal and Implant Science
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• 제54권1호
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• pp.3-12
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• 2024

Deep learning (DL) offers promising performance in computer vision tasks and is highly suitable for dental image recognition and analysis. We evaluated the accuracy of DL algorithms in identifying and classifying dental implant systems (DISs) using dental imaging. In this systematic review and meta-analysis, we explored the MEDLINE/PubMed, Scopus, Embase, and Google Scholar databases and identified studies published between January 2011 and March 2022. Studies conducted on DL approaches for DIS identification or classification were included, and the accuracy of the DL models was evaluated using panoramic and periapical radiographic images. The quality of the selected studies was assessed using QUADAS-2. This review was registered with PROSPERO (CRDCRD42022309624). From 1,293 identified records, 9 studies were included in this systematic review and meta-analysis. The DL-based implant classification accuracy was no less than 70.75% (95% confidence interval [CI], 65.6%-75.9%) and no higher than 98.19 (95% CI, 97.8%-98.5%). The weighted accuracy was calculated, and the pooled sample size was 46,645, with an overall accuracy of 92.16% (95% CI, 90.8%-93.5%). The risk of bias and applicability concerns were judged as high for most studies, mainly regarding data selection and reference standards. DL models showed high accuracy in identifying and classifying DISs using panoramic and periapical radiographic images. Therefore, DL models are promising prospects for use as decision aids and decision-making tools; however, there are limitations with respect to their application in actual clinical practice.